LOCAL	
  PERCEPTIONS	
  OF	
  RISK	
  AND	
  VULNERABILITY	
  ASSOCIATED	
  WITH	
  HUMAN-­‐
WILDLIFE	
  CONFLICTS	
  IN	
  NAMIBIAN	
  CONSERVANCIES	
  
	
  
	
  
By	
  
	
  
Jessica	
  Siders	
  Kahler	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
A	
  THESIS	
  
	
  
Submitted	
  to	
  	
  
Michigan	
  State	
  University	
  
in	
  partial	
  fulfillment	
  of	
  the	
  requirements	
  
for	
  the	
  degree	
  of	
  
	
  
MASTER	
  OF	
  SCIENCE	
  
	
  
Fisheries	
  and	
  Wildlife	
  
	
  
2010

ABSTRACT	
  
	
  
LOCAL	
  PERCEPTIONS	
  OF	
  RISK	
  AND	
  VULNERABILITY	
  ASSOCIATED	
  WITH	
  HUMAN-­‐
WILDLIFE	
  CONFLICTS	
  IN	
  NAMIBIAN	
  CONSERVANCIES	
  
	
  
By	
  
	
  
Jessica	
  Siders	
  Kahler	
  
	
  
In	
  northeastern	
  Namibia	
  human-­‐wildlife	
  conflicts	
  (HWC)	
  pose	
  risks	
  to	
  livelihoods	
  and	
  
wildlife,	
  creating	
  challenges	
  for	
  conservancies	
  mandated	
  to	
  promote	
  conservation	
  and	
  
sustainable	
  development.	
  	
  Insights	
  about	
  factors	
  influencing	
  local	
  stakeholders’	
  risk	
  
perceptions	
  and	
  vulnerability	
  associated	
  with	
  HWC	
  is	
  lacking;	
  such	
  information	
  is	
  crucial	
  
for	
  effective	
  management	
  strategies.	
  	
  To	
  better	
  understand	
  stakeholders’	
  perceptions	
  of	
  
HWC-­‐related	
  risks	
  to	
  livelihoods	
  and	
  wildlife,	
  I	
  (a)	
  assessed	
  the	
  effects	
  of	
  conservancy	
  
status	
  on	
  residents’	
  HWC-­‐related	
  risk	
  perceptions	
  in	
  an	
  emerging	
  (n=	
  61)	
  and	
  established	
  
(n	
  =	
  65)	
  conservancy,	
  (b)	
  evaluated	
  stakeholders	
  perceptions	
  of	
  HWC-­‐related	
  risks	
  relative	
  
to	
  non-­‐HWC	
  related	
  risks,	
  and	
  (c)	
  described	
  the	
  conceptual	
  and	
  physical	
  space	
  between	
  
assessed	
  and	
  perceived	
  poaching-­‐related	
  risks.	
  	
  Results	
  show	
  that	
  the	
  establishment	
  of	
  a	
  
conservancy	
  influenced	
  study	
  residents’	
  characterization,	
  prioritization	
  and	
  perceived	
  
severity	
  of	
  HWC-­‐related	
  risks.	
  	
  Additionally,	
  non-­‐HWC-­‐related	
  risks,	
  such	
  as	
  lack	
  of	
  
employment,	
  were	
  cited	
  as	
  exacerbating	
  human	
  and	
  wildlife	
  vulnerability	
  to	
  and	
  
decreasing	
  stakeholder	
  tolerance	
  of	
  HWC.	
  	
  Conservancy	
  residents	
  described	
  the	
  spatial	
  and	
  
conceptual	
  relationships	
  between	
  HWC-­‐risks,	
  such	
  as	
  crop	
  damage	
  and	
  poaching,	
  that	
  may	
  
undermine	
  conservation	
  and	
  development	
  in	
  their	
  conservancies.	
  	
  	
  Understanding	
  local	
  
stakeholders’	
  perceptions	
  of	
  risks	
  and	
  vulnerability	
  can	
  inform	
  the	
  content,	
  format,	
  and	
  
design	
  of	
  HWC	
  interventions	
  and	
  prioritize	
  risk	
  management	
  and	
  mitigation	
  to	
  assist	
  the	
  
conservancies’	
  most	
  HWC-­‐vulnerable	
  residents	
  and	
  promote	
  wildlife	
  conservation.
	
  

	
   ii	
  

DEDICATION	
  
	
  
	
  
To	
  the	
  diverse	
  people	
  and	
  wildlife	
  of	
  the	
  conservancies	
  of	
  Mudumu	
  South,	
  Tatumeri.	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

iii	
  

AKNOWLEDGEMENTS	
  
	
  

	
  

	
  

There	
  are	
  a	
  number	
  of	
  individuals,	
  agencies,	
  and	
  organizations	
  that	
  have	
  made	
  this	
  

research	
  possible.	
  	
  First	
  and	
  foremost,	
  thank	
  you	
  to	
  the	
  Department	
  of	
  Fisheries	
  &	
  Wildlife,	
  
The	
  Graduate	
  School	
  at	
  Michigan	
  State	
  University	
  and	
  The	
  School	
  of	
  Criminal	
  Justice	
  for	
  
financially	
  giving	
  me	
  the	
  ability	
  to	
  pursue	
  graduate	
  education	
  and	
  research.	
  	
  Additionally,	
  I	
  
have	
  a	
  great	
  deal	
  of	
  gratitude	
  for	
  the	
  Namibian	
  organizations	
  and	
  agencies	
  that	
  so	
  willingly	
  
provided	
  invaluable	
  advice	
  and	
  in-­‐kind	
  support	
  to	
  “another”	
  researcher:	
  Caprivi’s	
  
Integrated	
  Rural	
  Development	
  and	
  Nature	
  Conservation	
  (IRDNC),	
  Chief	
  Sifu’s	
  Traditional	
  
Authority,	
  Dzoti	
  Conservancy,	
  the	
  Namibian	
  Ministry	
  of	
  Environment	
  and	
  Tourism	
  (MET)-­‐	
  
Caprivi,	
  Shikhakhu	
  Conservancy,	
  World	
  Wildlife	
  Fund	
  (WWF)-­‐Namibia	
  and	
  Wuparo	
  
Conservancy.	
  	
  
	
  

One	
  of	
  the	
  most	
  rewarding	
  aspects	
  of	
  my	
  experience	
  in	
  Namibia	
  was	
  meeting	
  the	
  

men,	
  women	
  and	
  children	
  of	
  Dzoti	
  and	
  Wuparo	
  conservancies.	
  	
  Thank	
  you	
  for	
  sharing	
  your	
  
knowledge	
  and	
  experiences	
  related	
  to	
  co-­‐existing	
  with	
  wildlife,	
  and	
  your	
  culture,	
  language,	
  
dance,	
  food,	
  living	
  space	
  and	
  most	
  importantly	
  your	
  company.	
  	
  Without	
  your	
  hospitality	
  
and	
  willingness	
  to	
  take	
  valuable	
  time	
  out	
  of	
  your	
  lives	
  to	
  share	
  your	
  views,	
  this	
  project	
  
simply	
  wouldn’t	
  have	
  happened.	
  
	
  

I	
  would	
  like	
  to	
  acknowledge	
  the	
  un-­‐sung	
  heroes	
  of	
  my	
  research	
  project:	
  the	
  research	
  

and	
  field	
  assistants	
  from	
  Caprivi.	
  	
  To	
  Mulonga	
  Chris,	
  Sinasi	
  Hasken,	
  Nkwazi	
  Lasken,	
  Elvis	
  
Liswaniso,	
  Fidelis	
  Lizumo,	
  Robert	
  Makanyi,	
  Courley	
  Mutabani,	
  Ophelia	
  Tama,	
  and	
  Joseph	
  
Ziezo,	
  I	
  thank	
  you	
  for	
  your	
  dedicated	
  assistance,	
  professionalism,	
  friendship	
  and	
  your	
  
guidance	
  in	
  navigating	
  the	
  politics,	
  culture,	
  language	
  and	
  many	
  ‘flat	
  tires’	
  (literally	
  and	
  

	
  

iv	
  

figuratively)	
  during	
  my	
  research.	
  	
  Additionally,	
  special	
  thanks	
  to	
  Richard	
  Diggle	
  (WWF-­‐
Namibia),	
  Dr.	
  Jonathan	
  Barnes,	
  and	
  Beaven	
  Munali	
  for	
  their	
  advice,	
  feedback	
  and	
  interest	
  in	
  
this	
  research.	
  Thank	
  you	
  to	
  Lise	
  Hanssen,	
  for	
  not	
  only	
  taking	
  me	
  out	
  to	
  radio	
  collar	
  a	
  hyena,	
  
but	
  also	
  sharing	
  her	
  vast	
  experience	
  and	
  knowledge	
  about	
  conserving	
  large	
  carnivores	
  
amongst	
  farmers	
  and	
  cattle.	
  
	
  

Also,	
  to	
  my	
  ‘lab	
  mates,’	
  Shauna	
  Hanisch,	
  Michelle	
  Lute,	
  Bret	
  Muter	
  and	
  Brent	
  

Rudolph,	
  thank	
  you	
  for	
  your	
  feedback,	
  friendship	
  and	
  camaraderie	
  that	
  has	
  made	
  my	
  
experience	
  at	
  MSU	
  an	
  enjoyable	
  one.	
  A	
  big	
  thank	
  you	
  is	
  owed	
  to	
  my	
  undergraduate	
  
research	
  assistant,	
  Alyssa	
  Berger,	
  for	
  the	
  immense	
  amount	
  of	
  data	
  entry	
  she	
  completed.	
  	
  To	
  
my	
  numerous	
  peers	
  and	
  friends	
  that	
  have	
  supported	
  me	
  during	
  various	
  stages-­‐	
  you	
  know	
  
who	
  you	
  are	
  –	
  thank	
  you.	
  
	
  

I	
  am	
  especially	
  grateful	
  to	
  my	
  graduate	
  committee	
  (members	
  past	
  and	
  present)-­‐	
  Dr.	
  

Meredith	
  Gore,	
  Dr.	
  Robert	
  Hitchcock,	
  Dr.	
  Kelly	
  Millenbah,	
  and	
  Dr.	
  Gary	
  Roloff.	
  	
  Meredith,	
  
thank	
  you	
  for	
  your	
  support	
  and	
  dedication	
  to	
  this	
  research	
  despite	
  all	
  the	
  unforeseen	
  
setbacks	
  and	
  roadblocks	
  along	
  the	
  way.	
  	
  Gary,	
  I	
  want	
  to	
  thank	
  you	
  for	
  the	
  technical	
  
assistance,	
  extra	
  time	
  and	
  effort	
  you	
  have	
  provided	
  during	
  my	
  data	
  analysis	
  and	
  write-­‐up	
  
phase.	
  	
  Thank	
  you	
  to	
  Paul	
  Curran	
  for	
  statistics	
  advice	
  and	
  consultation.	
  	
  Also	
  to	
  Dr.	
  Joe	
  
Arvai,	
  Dr.	
  William	
  McConnell,	
  and	
  Dr.	
  Shawn	
  Riley,	
  thank	
  you	
  for	
  your	
  advice	
  and	
  
consultation	
  at	
  various	
  stages	
  of	
  my	
  research.	
  
	
  	
  

To	
  my	
  family	
  and	
  friends,	
  thank	
  you	
  for	
  your	
  patience	
  and	
  support	
  and	
  sharing	
  this	
  

experience	
  with	
  me.	
  	
  Last	
  but	
  certainly	
  far	
  from	
  least,	
  to	
  my	
  husband,	
  my	
  best	
  friend,	
  my	
  
rock-­‐	
  Benjamin,	
  this	
  wouldn’t	
  have	
  happened	
  without	
  your	
  love	
  and	
  support,	
  thank	
  you.	
  
	
  

	
  

v	
  

TABLE	
  OF	
  CONTENTS	
  
	
  
List	
  of	
  Tables.……………………………………………………………………………………………………………..ix	
  
	
  
List	
  of	
  Figures	
  ……………………………………………………………………………………………………………xi	
  
	
  
Key	
  to	
  Abbreviations…………………………………………………………….....................................................xiii	
  
	
  
Chapter	
  1:	
  Human-­‐wildlife	
  conflict,	
  risk	
  perception,	
  and	
  vulnerability	
  in	
  Caprivi,	
  
Namibia…………………………………………………………………………………....................................................1	
  
	
  
1.1.	
  Introduction…………………………………………………………………………………..………..…..1	
  
	
  
	
  
1.1.1.	
  Human-­‐wildlife	
  conflicts………………………………………....................................1	
  
	
  
	
  
1.1.2.	
  Managing	
  human-­‐wildlife	
  conflicts………………………………….……………...2	
  
	
  
1.2.	
  Conceptual	
  Background……………………………………………………………..………….........4	
  
	
  
	
  
1.2.1.	
  Risk	
  perception…………………………………………………………………………......4	
  
	
  
	
  
1.2.2.	
  Vulnerability…………………………………………………………………………….…...6	
  
	
  
	
  
1.2.3.	
  Integrating	
  risk	
  perception	
  and	
  vulnerability…………………………..……...9	
  
	
  
1.3.	
  Study	
  Area……………………………………………………………………………………………..….10	
  
	
  
	
  
1.3.1.	
  The	
  Republic	
  of	
  Namibia……………………………………………….………….......10	
  
	
  
	
  
1.3.2.	
  Namibian	
  communal	
  conservancies………………………….............................11	
  
	
  
	
  
1.3.3.	
  The	
  Caprivi	
  Strip…………………………………………………………………….….…14	
  
	
  
1.4.	
  Research	
  Statement	
  and	
  Objectives…………………………………………………………….16	
  
	
  
1.5.	
  Thesis	
  Organization………………………………………..……………………………..…..……….18	
  
	
  
Chapter	
  2:	
  Does	
  conservancy	
  establishment	
  affect	
  residents’	
  human-­‐wildlife	
  conflict	
  	
  
related	
  risk	
  perceptions?	
  Insights	
  from	
  Namibia………………………………………..…………….…...24	
  
	
  
2.1.	
  Introduction……………………………………………………………………………………….….…..24	
  
	
  
2.2.	
  Background………………………………………………………………………………….………........25	
  
	
  
	
  
2.2.1.	
  Community-­‐based	
  natural	
  resources	
  management………..…..……..….....25	
  
	
  
	
  
2.2.2.	
  Risk	
  perceptions…………………………………………………………….……………..26	
  
	
  
	
  
2.2.3.	
  Namibian	
  conservancies………………………………………………..………………28	
  
	
  
2.3.	
  Methods………………………………………………………………………………………………...…..29	
  
	
  
	
  
2.3.1.	
  Study	
  location…………………………………………………………..…………………..29	
  
	
  
	
  
2.3.2.	
  Data	
  collection……………………………………………………….…..………….……..29	
  
	
  
	
  
2.3.3.	
  Data	
  analysis……………………………………………………………..………..…….….33	
  
	
  
2.4.	
  Results…………………………………………………………………………………...…………..……..36	
  
	
  
	
  
2.4.1.	
  Effect	
  of	
  conservancy	
  status	
  on	
  risk	
  and	
  vulnerability	
  	
  
	
  
	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  perceptions…………………………………………………………………..……………...37	
  
	
  
	
  
2.4.2.	
  Human-­‐wildlife	
  conflict	
  risks	
  relative	
  to	
  other	
  risks	
  to	
  	
  
	
  
	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  livelihoods	
  and	
  wildlife……………………………………………………………..…..40	
  
	
  
	
  
	
  
	
  
	
  

vi	
  

	
  
	
  
	
  
	
  

2.5.	
  Discussion……………………………………………………………………………………………..…..41	
  
	
  
2.5.1.	
  Conservancy	
  effects	
  on	
  HWC-­‐related	
  risk	
  perception……………………..41	
  
	
  
2.5.2.	
  Human-­‐wildlife	
  conflict	
  relative	
  to	
  other	
  risks………….….………………...44	
  
	
  
2.5.3.	
  Conclusions………………………………………………………………………..…………46	
  
	
  
Chapter	
  3:	
  A	
  conservation	
  criminology	
  approach	
  to	
  estimating	
  poaching	
  activities:	
  	
  
Co-­‐mapping	
  risks	
  and	
  characterizing	
  motivations	
  in	
  Namibian	
  conservancies……………….57	
  
	
  
3.1.	
  Introduction…………………………………………..……………………………………………….….57	
  
	
  
3.2.	
  Background……………………………………………………………………………………………….58	
  
	
  
	
  
3.2.1.	
  Perception	
  of	
  poaching	
  risks…………………………..………………….………….59	
  
	
  
	
  
3.2.2.	
  Stakeholder	
  motivations	
  to	
  poach………………………...……………………….60	
  
	
  
	
  
3.2.3.	
  Management	
  interventions	
  to	
  increase	
  compliance………………………..61	
  
	
  
	
  
3.2.4.	
  Poaching	
  in	
  Namibia’s	
  conservancy	
  system………………………….………...63	
  
	
  
3.3.	
  Methods……………………………………………………………………………………………..…..….64	
  
	
  
	
  
3.3.1.	
  Study	
  location…………………………….…………………………………………………64	
  
	
  
	
  
3.3.2.	
  Data	
  collection………………………….……………………………………………….….65	
  
	
  
	
  
3.3.3.	
  Data	
  analysis………………………………………………………………………………...67	
  
	
  
3.4.	
  Results……………………………………………………………………………………………..………..69	
  
	
  
	
  
3.4.1.	
  Perceived	
  poaching	
  risk…………………………….………………………………….69	
  
	
  
	
  
3.4.2.	
  Assessed	
  poaching	
  risk……………………………..…………………………………..70	
  
	
  
	
  
3.4.3.	
  Poaching	
  motivations………………………………….………………………………..70	
  
	
  
	
  
3.4.4.	
  Co-­‐mapping	
  assessed	
  and	
  perceived	
  poaching	
  risks…………….………...70	
  
	
  
3.5.	
  Discussion………………………………………………………………………………………...…….…72	
  
	
  
	
  
3.5.1.	
  Estimating	
  poaching	
  risks……………………………..……………………………...72	
  
	
  
	
  
3.5.2.	
  Local	
  motivations	
  for	
  poaching………………..……………………………………73	
  
	
  
	
  
3.5.3.	
  Co-­‐mapping	
  poaching	
  risks……………………….……………………………….…75	
  
	
  
	
  
3.5.4.	
  Conclusions…………………………………….……………………………………………76	
  
	
  
Chapter	
  4:	
  Summary	
  of	
  research	
  findings:	
  implications	
  for	
  theory,	
  methods,	
  and	
  
practice……………………………………………………………………………………………………….……………..84	
  
	
  
4.1.	
  Theoretical	
  implications………………………………………………...…………………………..84	
  
	
  
	
  
4.1.1.	
  Conservancy	
  effects	
  on	
  risk	
  perception	
  and	
  vulnerability…..…………..84	
  
	
  
	
  
4.1.2.	
  Multidirectional	
  perceptions	
  of	
  risk………………………………………………85	
  
	
  
	
  
4.1.3.	
  Similarities	
  and	
  differences	
  between	
  assessed	
  and	
  perceived	
  
	
  
	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  human-­‐wildlife	
  conflict	
  related	
  risks…………………..………………..….…….86	
  
	
  
4.2.	
  Methodological	
  implications……………………………………………………………………….87	
  
	
  
	
  
4.2.1.	
  Visual	
  interview	
  aids……………………………………………………………………..87	
  
	
  
	
  
4.2.2.	
  Focus	
  group	
  procedures………………………………………………..………………88	
  
	
  
4.3.	
  Practical	
  implications………………………………………………………………..……….……….89	
  
	
  
	
  
4.3.1.	
  HWC	
  interventions……………………………………………….……………….………89	
  
	
  
	
  
4.3.2.	
  Fostering	
  compliance…………………………………………………………………….91	
  
	
  
Appendix	
  A:	
  Focus	
  group	
  protocol……………………………………………………………..………………...95	
  
	
  
Appendix	
  B:	
  Interview	
  guide……………………………………………………………………………………...114	
  
	
  
	
  

vii	
  

Appendix	
  C:	
  Visual	
  aids…………………………………………………………………………….………………..133	
  
	
  
Appendix	
  D:	
  Coding	
  protocol……………………………………………………………………………………...135	
  
Appendix	
  E:	
  Interview	
  respondent	
  demographic	
  information	
  by	
  conservancy…..………....144	
  
Appendix	
  F:	
  Data	
  on	
  species-­‐specific	
  vulnerability………………………………………………..…….147	
  
Appendix	
  G:	
  Additional	
  co-­‐mapping	
  risk	
  maps……………………………………………………………154	
  
References.…………………………………………………………………………………………………………..……161	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

viii	
  

LIST	
  OF	
  TABLES	
  
	
  
Table	
  1.1	
  
	
  
Table	
  2.1	
  
	
  
Table	
  2.2	
  
	
  
	
  
	
  
	
  
	
  
Table	
  2.3	
  
	
  
	
  
	
  
	
  
	
  
Table	
  2.4	
  
	
  
	
  
	
  
	
  
	
  
Table	
  2.5	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
Table	
  2.6	
  
	
  
	
  
	
  
	
  
	
  
Table	
  3.1	
  
	
  
	
  
	
  
Table	
  3.2	
  
	
  
	
  
	
  
	
  
	
  
Table	
  3.3	
  
	
  
	
  
	
  
	
  
	
  
Table	
  3.4	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

Definitions	
  of	
  research	
  concepts	
  and	
  terminology…………………………………..19	
  
Characteristics	
  of	
  study	
  conservancies	
  in	
  East	
  Caprivi,	
  Namibia………..…….47	
  
Risk	
  categories,	
  select	
  category	
  attributes	
  and	
  risk	
  themes	
  (direct,	
  	
  
indirect,	
  non-­‐HWC)	
  generated	
  during	
  risk	
  ranking	
  activity	
  in	
  two	
  	
  
	
  
conservancies	
  (n=50):	
  Caprivi,	
  Namibia	
  (July-­‐September,	
  2009)………..……48	
  
Perceived	
  ranking	
  and	
  severity	
  of	
  risks	
  to	
  local	
  livelihoods	
  and	
  wildlife	
  	
  
in	
  two	
  conservancies	
  (emerging	
  =	
  20;	
  established	
  =	
  30)	
  in	
  East	
  Caprivi,	
  	
  
Namibia	
  (July-­‐September,	
  2009)…………………………………………………………….49	
  
The	
  effect	
  of	
  conservancy	
  status	
  (emerging	
  =	
  41;	
  established	
  =	
  35)	
  on	
  	
  	
  
attitudes	
  towards	
  human-­‐wildlife	
  conflict	
  (HWC)	
  as	
  expressed	
  by	
  odds	
  	
  
ratio:	
  Caprivi,	
  Namibia	
  (2009)…………………………………………………………..……51	
  
Ordinary	
  least	
  squares	
  (OLS)	
  regression	
  coefficients	
  (±	
  standard	
  error)	
  
for	
  estimated	
  affects	
  of	
  conservancy	
  status	
  on	
  HWC	
  perception	
  scores	
  	
  
(n=73)	
  for	
  dread	
  risk	
  (DREAD),	
  frequency	
  (FREQ),	
  consequence	
  	
  
(CONSQ),	
  vulnerability	
  (VUL)	
  and	
  risk	
  (RISK)	
  to	
  livelihoods	
  (XLH)	
  and	
  	
  
wildlife	
  (XWL)	
  controlling	
  for	
  age,	
  decision-­‐making	
  authority,	
  education,	
  	
  
gender	
  and	
  wealth:	
  Caprivi,	
  Namibia	
  (2009)……………………………………..……52	
  
Results	
  of	
  two-­‐sample	
  independent	
  t-­‐tests	
  for	
  equality	
  of	
  means	
  for	
  	
  
total	
  and	
  mean	
  annual	
  incidents	
  of	
  wildlife	
  damage	
  in	
  an	
  emerging	
  and	
  	
  
established	
  conservancy	
  (Event	
  Book	
  Data,	
  2003-­‐2008)…………………………54	
  
Characteristics	
  of	
  the	
  Mudumu	
  South	
  Complex	
  in	
  East	
  Caprivi,	
  	
  
Namibia…………………………………………………………………………………………………77	
  
Local	
  perceptions	
  (n=48)	
  about	
  the	
  seriousness	
  of	
  risks	
  to	
  wildlife	
  as	
  	
   	
  
identified	
  by	
  focus	
  groups	
  in	
  two	
  conservancies	
  in	
  Mudumu	
  South	
  	
  
Complex:	
  Caprivi,	
  Namibia	
  (July-­‐September,	
  2009)………………………………….78	
  
Participant-­‐generated	
  (n-­‐48)	
  and	
  ranked	
  motivations	
  for	
  poaching	
  in	
  	
  
two	
  conservancies	
  in	
  Mudumu	
  South	
  Complex:	
  Caprivi,	
  Namibia	
  (July-­‐	
  	
  
September,	
  2009)……………………………………………………………………………………79	
  
Conservancy	
  participants’	
  (n=48)	
  cited	
  motivations	
  for	
  poaching	
  	
  
	
  
conceptually	
  sorted	
  using	
  Muth	
  and	
  Bowe’s	
  (1998)	
  typology	
  of	
  the	
  	
   	
  
motivations	
  for	
  poaching	
  (categories	
  underlined):	
  Mudumu	
  South	
  	
  
Complex,	
  Namibia	
  (2009)………………………………………………………………….…….80	
  
ix	
  

Table	
  E1	
  
	
  
	
  
	
  
	
  
	
  
	
  
Table	
  F1	
  
	
  
	
  
	
  
	
  
	
  
	
  
Table	
  F2	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

Demographic	
  information	
  from	
  interviews	
  in	
  two	
  conservancies	
  	
  
(emerging	
  =	
  41;	
  established	
  =	
  35)	
  in	
  Mudumu	
  South	
  Complex:	
  Caprivi,	
  	
  
Namibia	
  (July-­‐September,	
  2009)…………………………………………………………..144	
  
	
  	
  
Perceived	
  and	
  reported	
  species	
  implicated	
  in	
  crop	
  damage,	
  livestock	
  	
  
loss	
  and	
  human	
  attack	
  in	
  two	
  conservancies	
  in	
  Mudumu	
  South	
  	
  
Complex	
  (n=50):	
  Caprivi,	
  Namibia	
  (July-­‐September,	
  2009)…………………...147	
  
	
  
	
  
Wildlife	
  species	
  vulnerability	
  to	
  poaching	
  according	
  to	
  conservancy	
  	
  
incident	
  reports	
  (Event	
  Book,	
  2001-­‐2008)	
  and	
  local	
  perceptions	
  from	
  	
  
a	
  risk	
  ranking	
  activity	
  (Focus	
  Group,	
  2009;	
  n=50)	
  in	
  two	
  conservancies	
  	
  
in	
  Mudumu	
  South	
  Complex:	
  Caprivi,	
  Namibia.........................................................150	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

x	
  

LIST	
  OF	
  FIGURES	
  
	
  
Figure	
  1.1	
  
	
  
	
  
	
  
Figure	
  1.2	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  1.3	
  
	
  
	
  
	
  
Figure	
  2.1	
  
	
  
	
  
	
  
	
  
	
  	
  
Figure	
  2.2	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  3.1	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  3.2	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  3.3	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  C1	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  F1	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

Conceptual	
  framework	
  of	
  stakeholders’	
  risk	
  perception	
  associated	
  
with	
  human-­‐wildlife	
  conflicts	
  (HWC)……………………………………………..……….21	
  
Map	
  of	
  study	
  area,	
  the	
  Caprivi	
  Strip,	
  Northeastern	
  Namibia.	
  For	
  	
  
	
  
interpretation	
  of	
  the	
  references	
  to	
  color	
  in	
  this	
  and	
  all	
  other	
  figures,	
  	
  
the	
  reader	
  is	
  referred	
  to	
  the	
  electronic	
  version	
  of	
  this	
  thesis	
  ………………......22	
  
Map	
  of	
  study	
  conservancies,	
  Dzoti	
  and	
  Wuparo,	
  in	
  Mudumu	
  South	
  	
  
Complex:	
  Caprivi,	
  Namibia……………………………………………………………………..23	
  
Conservancy	
  residents’	
  perceptions	
  (n=50)	
  about	
  the	
  incidence	
  and	
  	
   	
  
importance	
  of	
  risks	
  to	
  livelihoods	
  in	
  two	
  conservancies	
  in	
  East	
  Caprivi,	
  	
  
Namibia	
  (Focus	
  groups:	
  July-­‐September,	
  2009)………………………………………55	
  
Conservancy	
  residents’	
  perceptions	
  (n=48)	
  about	
  the	
  incidence	
  and	
  	
   	
  
importance	
  of	
  risks	
  to	
  wildlife	
  in	
  two	
  conservancies	
  in	
  East	
  Caprivi,	
  	
   	
  
Namibia	
  (Focus	
  groups:	
  July-­‐September,	
  2009)……………………………………….56	
  
Recorded	
  incidents	
  of	
  poaching	
  (e.g.,	
  number	
  of	
  snares	
  confiscated,	
  	
  
firearm	
  and	
  traditional	
  incidents)	
  in	
  two	
  Mudumu	
  South	
  Complex	
  	
  
	
  
conservancies:	
  East	
  Caprivi,	
  Namibia	
  (Dzoti	
  &	
  Wuparo	
  Event	
  Books	
  	
  
2001;	
  2003-­‐2008)…………………………………………………………………………………..81	
  
Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  poaching	
  and	
  	
   	
  
Event	
  Book	
  data	
  for	
  poaching	
  incidents	
  (2001-­‐2008)	
  in	
  two	
  Mudumu	
  	
  
South	
  Complex	
  conservancies:	
  East	
  Caprivi,	
  Namibia.	
  ……………………..……….82	
  
Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  wildlife	
  attack	
  	
  
and	
  livelihood	
  damage	
  that	
  motivated	
  retaliatory	
  poaching	
  and	
  Event	
  	
  
Book	
  data	
  for	
  poaching	
  incidents	
  by	
  incident	
  type	
  (2001-­‐2008)	
  in	
  two	
  	
  
Mudumu	
  South	
  Complex	
  conservancies:	
  East	
  Caprivi,	
  Namibia…………………83	
  
Developed	
  visual	
  Likert-­‐type	
  scales	
  (a.	
  intensity	
  or	
  amount;	
  	
  
b.	
  frequency)	
  for	
  use	
  with	
  semi-­‐structured	
  interviews	
  and	
  focus	
  	
  
groups	
  in	
  Mudumu	
  South	
  Complex:	
  Caprivi,	
  Namibia	
  	
  
(July-­‐September,	
  2009)…………………………………………………………………………133	
  
Top	
  fifteen	
  most	
  threatening	
  wildlife	
  species	
  to	
  local	
  livelihoods	
  as	
  	
   	
  
perceived	
  by	
  residents	
  in	
  two	
  conservancies	
  (n=50)	
  in	
  Mudumu	
  	
  
South	
  Complex:	
  Caprivi,	
  Namibia	
  (Focus	
  Groups;	
  July-­‐September,	
  	
  
	
  
2009)……………………………………………………………………………………..…………......151	
  
	
  
	
  
xi	
  

Figure	
  F2	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  G1	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  G2	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  G3	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  G4	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  G5	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
Figure	
  G6	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

Top	
  fifteen	
  most	
  threatened	
  wildlife	
  species	
  from	
  conflicts	
  with	
  people	
  	
  
as	
  perceived	
  by	
  residents	
  in	
  two	
  conservancies	
  (n=48)	
  in	
  Mudumu	
  	
  
South	
  Complex:	
  Caprivi,	
  Namibia	
  (Focus	
  Groups;	
  July-­‐September,	
  	
  
	
  
2009)………………………………………………………………………………………………........152	
  
Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  crop	
  damage	
  	
   	
  
incidents	
  and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  crop	
  damage	
  	
  
incidents	
  in	
  Wuparo	
  (a)	
  and	
  Dzoti	
  (b)	
  conservancies:	
  Mudumu	
  South	
  	
   	
  
Complex,	
  Caprivi,	
  Namibia…………………………………………………………………….154	
  
Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  human-­‐attack	
  	
   	
  
incidents	
  and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  human-­‐attack	
  	
  
	
  
incidents	
  in	
  Wuparo	
  (a)	
  and	
  Dzoti	
  (b)	
  conservancies:	
  Mudumu	
  South	
  	
   	
  
Complex,	
  Caprivi,	
  Namibia	
  ……………………………………………….…………..……….155	
  
Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  livestock	
  	
  
	
  
depredation	
  incidents	
  and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  	
  
livestock	
  depredation	
  incidents	
  in	
  Wuparo	
  (a)	
  and	
  Dzoti	
  (b)	
  	
  
conservancies:	
  Mudumu	
  South	
  Complex,	
  Caprivi,	
  Namibia	
  ………….….………156	
  
Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  crop	
  damage	
  	
   	
  
incidents	
  and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  poaching	
  	
   	
  
	
  
incidents	
  in	
  Wuparo	
  (a)	
  and	
  Dzoti	
  (b)	
  conservancies:	
  Mudumu	
  South	
  	
   	
  
Complex,	
  Caprivi,	
  Namibia..……………………………………………………………….…..157	
  	
  
Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  human-­‐	
  
attack	
  incidents	
  and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  poaching	
  	
   	
  
incidents	
  in	
  Wuparo	
  (a)	
  and	
  Dzoti	
  (b)	
  conservancies:	
  Mudumu	
  South	
  	
   	
  
Complex,	
  Caprivi,	
  Namibia	
  ……………………………………………………………….……158	
  
Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  livestock	
  	
  
	
  
depredation	
  incidents	
  and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  	
  
poaching	
  incidents	
  in	
  Wuparo	
  (a)	
  and	
  Dzoti	
  (b)	
  conservancies:	
  	
  
Mudumu	
  South	
  Complex,	
  Caprivi,	
  Namibia	
  ……………….…………………….……...159	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
xii	
  

KEY	
  TO	
  ABBREVIATIONS	
  
	
  
	
  
	
  
	
  
Community-­‐based	
  natural	
  resources	
  management	
  (CBNRM)	
  
	
  
Human-­‐wildlife	
  conflicts	
  (HWC)	
  
	
  
Human-­‐wildlife	
  interactions	
  (HWI)	
  
	
  
Integrated	
  Rural	
  Development	
  and	
  Nature	
  Conservation	
  (IRDNC)	
  
	
  
Ministry	
  of	
  Environment	
  and	
  Tourism	
  (MET)	
  
	
  
Mudumu	
  South	
  Complex	
  (MSC)	
  
	
  
Namibian	
  Association	
  of	
  Community	
  Based	
  Natural	
  Resource	
  Management	
  Support	
  
Organizations	
  (NACSO)	
  
	
  
National	
  Park	
  (NP)	
  
	
  
Non-­‐governmental	
  organization	
  (NGO)	
  
	
  
Participatory	
  risk	
  mapping	
  (PRM)	
  
	
  
Participatory	
  risk	
  ranking	
  and	
  scoring	
  (PRRS)	
  
	
  
Problem	
  animal	
  incident	
  (PAI)	
  
	
  
World	
  Wildlife	
  Fund	
  (WWF)	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

xiii	
  

CHAPTER	
  1:	
  	
  HUMAN-­WILDLIFE	
  CONFLICT,	
  RISK	
  PERCEPTION,	
  AND	
  VULNERABILITY	
  
IN	
  CAPRIVI,	
  NAMIBIA	
  
1.1.	
  INTRODUCTION	
  
1.1.1.	
  Human-­wildlife	
  conflicts.	
  
Globally,	
  human-­‐wildlife	
  conflicts	
  (HWC)	
  pose	
  risks	
  to	
  human	
  livelihoods	
  and	
  
wildlife	
  conservation;	
  HWC	
  occurs	
  when	
  the	
  actions	
  of	
  either	
  humans	
  or	
  wildlife	
  have	
  
adverse	
  effects	
  on	
  the	
  other	
  (Conover,	
  2002).	
  	
  Concerns	
  about	
  HWC	
  can	
  shape	
  public	
  
attitudes,	
  beliefs,	
  and	
  support	
  for	
  wildlife	
  management	
  activities	
  (Knuth,	
  Stout,	
  Siemer,	
  
Decker,	
  &	
  Stedman,	
  1992),	
  influence	
  wildlife	
  tolerance	
  among	
  stakeholders	
  (e.g.,	
  Knuth	
  et	
  
al.,	
  1992;	
  Marker,	
  Mills	
  &	
  MacDonald,	
  2002)	
  and	
  stimulate	
  stakeholder	
  action	
  (Decker,	
  
Lauber	
  &	
  Siemer,	
  2002).	
  	
  Often,	
  when	
  HWC	
  occurs,	
  it	
  represents	
  a	
  lose-­‐lose	
  situation	
  for	
  
both	
  humans	
  and	
  wildlife	
  (Conover,	
  2002)	
  through	
  its	
  myriad	
  negative	
  effects,	
  discussed	
  
below,	
  on	
  both	
  natural	
  systems	
  and	
  human	
  livelihoods	
  (Woodroffe,	
  Thirgood	
  &	
  Rabinowitz,	
  
2005).	
  	
  Reducing	
  risks	
  to	
  both	
  people	
  and	
  wildlife	
  from	
  HWC	
  is	
  a	
  conservation	
  imperative.	
  	
  
	
  

The	
  direct	
  effects	
  of	
  HWC	
  on	
  human	
  livelihoods	
  occur	
  across	
  a	
  continuum	
  and	
  range	
  

from	
  nuisance	
  behavior	
  (e.g.,	
  bears	
  eating	
  from	
  birdfeeders)	
  to	
  life-­‐threatening	
  interactions	
  
(e.g.,	
  wildlife-­‐vehicle	
  collisions,	
  wildlife	
  attack)	
  (Conover,	
  2002;	
  Ogra	
  2008;	
  Thirgood,	
  
Woodroff	
  &	
  Rabinowitz,	
  2005).	
  	
  Direct	
  HWC	
  effects	
  on	
  livelihoods	
  can	
  include	
  crop	
  raiding,	
  
livestock	
  predation	
  (Conover,	
  2002;	
  Ogra,	
  2008),	
  attacks	
  on	
  humans	
  (Aust,	
  Boyle,	
  
Fergusson	
  &	
  Coulson,	
  2009;	
  Dunham,	
  Ghiurghi,	
  Cumbi	
  &	
  Urbano,	
  2010),	
  and	
  zoonotic	
  
disease	
  (e.g.,	
  bubonic	
  plague)	
  transmission	
  (Swift,	
  Hunter,	
  Less	
  &	
  Bell,	
  2007).	
  	
  These	
  HWC-­‐
related	
  risks	
  may	
  reduce	
  food	
  security	
  and	
  livelihood	
  resources	
  and	
  threaten	
  human	
  health	
  
and	
  safety.	
  	
  HWC	
  has	
  the	
  potential	
  to	
  result	
  in	
  indirect	
  effects	
  as	
  well,	
  including	
  increased	
  

	
  

1	
  

labor	
  burdens,	
  economic	
  hardship,	
  or	
  fear	
  to	
  leave	
  home	
  in	
  search	
  of	
  livelihood	
  resources	
  
(Ogra,	
  2008).	
  	
  Ogra	
  (2008)	
  noted	
  indirect	
  HWC	
  effects	
  often	
  go	
  uncompensated,	
  are	
  
temporally	
  delayed	
  and	
  can	
  lead	
  to	
  negative	
  psychological,	
  health	
  or	
  social	
  consequences.	
  	
  
Additionally,	
  although	
  they	
  are	
  not	
  discussed	
  extensively	
  in	
  the	
  extant	
  literature	
  or	
  
incorporated	
  into	
  conservation	
  action,	
  conflicts	
  between	
  people	
  about	
  HWC	
  are	
  also	
  part	
  of	
  
the	
  spectrum	
  (Peterson,	
  Birkhead,	
  Leong,	
  Peterson	
  &	
  Peterson,	
  2010).	
  
When	
  wildlife	
  is	
  involved,	
  or	
  thought	
  to	
  be	
  involved,	
  in	
  HWC,	
  the	
  resultant	
  human	
  
response	
  may	
  be	
  lethal	
  control	
  (legal	
  or	
  illegal).	
  	
  This	
  is	
  especially	
  true	
  in	
  instances	
  where	
  
wildlife	
  is	
  viewed	
  as	
  a	
  threat	
  to	
  human	
  livelihood	
  systems	
  (e.g.,	
  agriculture,	
  ranching),	
  
health	
  and	
  safety,	
  or	
  property	
  (Treves,	
  Wallace,	
  Naughton-­‐Treves	
  &	
  Morales,	
  2006a;	
  
Woodroffe	
  et	
  al.,	
  2005).	
  	
  Orders	
  of	
  wildlife,	
  such	
  as	
  Carnivores,	
  are	
  often	
  the	
  target	
  of	
  
predator	
  eradication	
  efforts	
  (Carpaneto	
  &	
  Fusari,	
  2000;	
  Kissui,	
  2008),	
  which	
  has	
  led	
  to	
  
population	
  suppression,	
  range	
  collapse	
  or	
  extinction	
  for	
  some	
  predators	
  (Woodroffe	
  et	
  al.,	
  
2005).	
  	
  Indirectly,	
  increases	
  in	
  human	
  and	
  livestock	
  populations	
  can	
  change	
  the	
  availability	
  
of	
  resources	
  upon	
  which	
  species	
  depend	
  for	
  survival	
  (Vaughan	
  &	
  Long,	
  2007).	
  	
  
Additionally,	
  altering	
  wildlife	
  habitats	
  can	
  affect	
  species	
  structure,	
  composition,	
  and	
  overall	
  
biomass	
  (Foley,	
  DeFries,	
  Asner,	
  Barford,	
  Bonan,	
  Carpenter	
  et	
  al.,	
  2005).	
  	
  
1.1.2.	
  Managing	
  human-­wildlife	
  conflicts.	
  
Early	
  HWC	
  studies	
  focused	
  on	
  measuring	
  and	
  mitigating	
  impacts	
  from	
  HWC	
  on	
  local	
  
livelihoods	
  and	
  were	
  framed	
  within	
  the	
  context	
  of	
  wildlife	
  damage	
  management.	
  	
  Overall,	
  
these	
  studies	
  focused	
  on	
  evaluating	
  the	
  effectiveness	
  of	
  wildlife-­‐focused	
  methods	
  for	
  HWC	
  
management	
  (e.g.,	
  wildlife	
  deterrence,	
  relocation,	
  lethal	
  control)	
  (Conover,	
  2002).	
  	
  HWC-­‐
related	
  research	
  then	
  began	
  examining	
  the	
  effectiveness	
  of	
  human-­‐focused	
  methods	
  for	
  

	
  

2	
  

HWC	
  management	
  such	
  as	
  economic	
  incentives,	
  compensation	
  schemes,	
  or	
  other	
  efforts	
  
designed	
  to	
  increase	
  human	
  tolerance	
  of	
  problem	
  wildlife	
  and	
  foster	
  co-­‐existence	
  of	
  human	
  
and	
  wildlife	
  populations	
  (Bulte	
  &	
  Rondeau,	
  2007;	
  Fascione,	
  Delach	
  &	
  Smith,	
  2004;	
  
Woodroffe	
  et	
  al.,	
  2005).	
  	
  Most	
  recently,	
  HWC	
  has	
  examined	
  stakeholders’	
  perceptions	
  of	
  
risks	
  from	
  wildlife	
  to	
  their	
  livelihoods	
  (Aust	
  et	
  al.,	
  2009;	
  Gore,	
  Knuth,	
  Curtis	
  &	
  Shanahan,	
  
2007;	
  Marker	
  et	
  al.,	
  2003),	
  stakeholder	
  attitudes	
  towards	
  various	
  wildlife	
  species	
  (Kissui,	
  
2008;	
  Kuriyan,	
  2002;	
  Romañach,	
  Lindsey	
  &	
  Woodroffe,	
  2007),	
  human	
  vulnerability	
  to	
  
direct	
  (e.g.,	
  economic)	
  and	
  indirect	
  (e.g.,	
  psychological)	
  impacts	
  of	
  HWC	
  (Ogra,	
  2008),	
  and	
  
stakeholder	
  preferences	
  for	
  HWC	
  management	
  and	
  interventions	
  (Ogra,	
  2009;	
  Treves,	
  
Wallace	
  &	
  White,	
  2009).	
  	
  These	
  newer	
  studies	
  focus	
  on	
  how	
  people	
  cope	
  with	
  living	
  with	
  
wildlife.	
  	
  
HWC-­‐related	
  interventions	
  can	
  be	
  people-­‐focused,	
  wildlife-­‐focused,	
  or	
  focused	
  on	
  
both	
  people	
  and	
  wildlife.	
  	
  Many	
  types	
  of	
  wildlife-­‐focused	
  interventions,	
  such	
  as	
  lethal	
  
control	
  (e.g.,	
  poisoning,	
  sharp	
  shooting),	
  may	
  be	
  incompatible	
  with	
  conservation	
  goals.	
  	
  For	
  
example,	
  wildlife-­‐focused	
  interventions	
  designed	
  to	
  reduce	
  the	
  rate	
  and	
  magnitude	
  of	
  HWC	
  
(e.g.,	
  fencing,	
  habitat	
  modification),	
  may	
  result	
  in	
  changes	
  to	
  the	
  availability	
  of	
  resources	
  
upon	
  which	
  wildlife	
  depend	
  for	
  survival	
  (Woodroffe	
  et	
  al.,	
  2005).	
  	
  Additionally,	
  wildlife-­‐
focused	
  interventions	
  can	
  impact	
  disease	
  transmission	
  between	
  livestock	
  and	
  wildlife	
  
(Daszak,	
  Cunningham	
  &	
  Hyatt,	
  2000),	
  disrupt	
  foraging	
  and	
  breeding	
  behavior,	
  and	
  alter	
  
migration	
  patterns	
  (Woodroff	
  et	
  al.,	
  2005).	
  	
  
	
  

People-­‐focused	
  interventions	
  can	
  include	
  direct	
  methods	
  to	
  reduce	
  interactions	
  

with	
  wildlife	
  (e.g.,	
  excluding	
  people	
  from	
  wildlife	
  habitat)	
  or	
  indirect	
  methods	
  to	
  change	
  
human	
  attitudes,	
  tolerance	
  or	
  behavior	
  (e.g.,	
  compensation,	
  education)	
  (Treves	
  et	
  al.,	
  

	
  

3	
  

2009).	
  	
  For	
  instance,	
  programs	
  that	
  compensate	
  farmers	
  for	
  crop	
  damage	
  or	
  livestock	
  
depredation	
  often	
  aim	
  to	
  increase	
  tolerance	
  of	
  wildlife	
  species	
  that	
  damage	
  livelihood	
  
resources	
  and	
  decrease	
  the	
  use	
  of	
  lethal	
  methods	
  on	
  wildlife	
  (Bulte	
  &	
  Rondeau,	
  2007).	
  	
  	
  
State	
  and	
  federal	
  agencies	
  can	
  create	
  regulations	
  (e.g.,	
  no	
  feeding	
  wildlife	
  in	
  protected	
  
areas)	
  to	
  decrease	
  the	
  likelihood	
  of	
  a	
  negative	
  encounter,	
  or	
  provide	
  outreach	
  to	
  ease	
  fear	
  
about	
  wildlife	
  and	
  increase	
  tolerance	
  (Conover,	
  2002).	
  	
  People-­‐focused	
  interventions	
  are	
  
often	
  linked	
  with	
  broader	
  conservation	
  and	
  development	
  projects,	
  such	
  ecotourism	
  
ventures,	
  and	
  are	
  implemented	
  by	
  diverse	
  stakeholders	
  (Gore,	
  Knuth,	
  Scherer	
  &	
  Curtis,	
  
2008).	
  	
  
Empirical	
  insight	
  about	
  the	
  human	
  dimensions	
  of	
  wildlife	
  is	
  essential	
  for	
  developing	
  
more	
  effective	
  HWC	
  interventions	
  (Manfredo	
  &	
  Dayer,	
  2004;	
  Ogra,	
  2009;	
  Treves	
  et	
  al.,	
  
2006a)	
  as	
  well	
  as	
  evaluating	
  their	
  ability	
  to	
  achieve	
  objectives	
  (Gore	
  et	
  al.	
  2008).	
  	
  	
  
Information	
  about	
  stakeholders’	
  vulnerability	
  and	
  risk	
  perception	
  associated	
  with	
  HWC	
  can	
  
enhance	
  practitioners'	
  ability	
  to	
  respond	
  to	
  the	
  social	
  consequences	
  of	
  HWC	
  and	
  foster	
  co-­‐
existence	
  between	
  people	
  and	
  wildlife.	
  
1.2.	
  CONCEPTUAL	
  BACKGROUND	
  	
  
This	
  research	
  integrates	
  theories	
  of	
  risk	
  perception	
  and	
  vulnerability	
  to	
  better	
  understand	
  
stakeholder	
  attitudes	
  associated	
  with	
  the	
  negative	
  effects	
  of	
  HWC	
  on	
  local	
  livelihoods	
  and	
  
wildlife.	
  	
  Below,	
  I	
  highlight	
  key	
  principles,	
  review	
  the	
  historical	
  significance,	
  and	
  identify	
  
key	
  gaps	
  in	
  understanding	
  associated	
  with	
  each	
  theory.	
  	
  Table	
  1	
  summarizes	
  key	
  concepts	
  
and	
  definitions.	
  	
  
	
  
	
  

	
  

4	
  

1.2.1.	
  Risk	
  Perception.	
  	
  
Risk	
  can	
  be	
  defined	
  as	
  an	
  estimation	
  of	
  both	
  the	
  likelihood	
  of	
  a	
  hazard	
  (e.g.,	
  nuclear	
  
disaster,	
  HWC)	
  and	
  the	
  magnitude	
  and	
  character	
  of	
  the	
  negative	
  consequences	
  of	
  the	
  
hazard	
  if	
  it	
  occurs	
  (Sjöberg,	
  2000a).	
  	
  Estimations	
  of	
  risk	
  can	
  be	
  made	
  through	
  technical	
  
assessments	
  or	
  intuitive	
  perceptions.	
  	
  Risk	
  assessments,	
  or	
  technical	
  estimations,	
  are	
  
objective	
  calculations	
  about	
  the	
  probability	
  of	
  occurrence	
  and	
  magnitude	
  of	
  the	
  
consequences	
  related	
  to	
  a	
  given	
  hazard	
  (Renn,	
  1992).	
  	
  The	
  psychometric	
  risk	
  paradigm	
  
defines	
  risk	
  perceptions	
  as	
  subjective	
  judgments	
  about	
  the	
  characteristics	
  of	
  particular	
  
hazards,	
  such	
  as	
  perceived	
  control	
  over	
  a	
  risk,	
  the	
  amount	
  of	
  dread	
  a	
  risk	
  elicits,	
  or	
  the	
  
perceived	
  severity	
  of	
  consequences	
  associated	
  with	
  risk	
  exposure	
  (Slovic,	
  1987;	
  Willis	
  &	
  
DeKay,	
  2007).	
  	
  Originally,	
  risk	
  perception	
  research	
  focused	
  on	
  technological	
  hazards	
  (e.g.,	
  
nuclear	
  power	
  generation,	
  toxic	
  waste	
  disposal).	
  	
  Today,	
  the	
  notion	
  is	
  more	
  broadly	
  
applied.	
  	
  	
  
Risk	
  perception	
  has	
  both	
  theoretical	
  and	
  practical	
  relevance	
  to	
  HWC.	
  	
  Theoretically,	
  
risk	
  perception	
  offers	
  a	
  lens	
  with	
  which	
  to	
  consider	
  how	
  individuals	
  think	
  and	
  behave	
  in	
  
response	
  to	
  risks.	
  Practically,	
  risk	
  perception	
  can	
  foster	
  deeper	
  understanding	
  of	
  
psychological	
  factors	
  that	
  influence	
  decision-­‐making.	
  Further,	
  risk	
  perception	
  can	
  be	
  used	
  
to	
  measure	
  stakeholder	
  support	
  for	
  management	
  actions	
  (Gore,	
  Knuth,	
  Curtis	
  &	
  Shanahan,	
  
2006;	
  McFarlane,	
  2005;	
  Weber,	
  2006)	
  and	
  is	
  important	
  for	
  predicting	
  behavior	
  (Knuth	
  et	
  
al.,	
  1992;	
  O’Connor,	
  Bord	
  &	
  Fisher,	
  1999).	
  For	
  example,	
  Gore	
  et	
  al.	
  (2006)	
  asserted	
  that	
  
understanding	
  public	
  perceptions	
  of	
  risk	
  associated	
  with	
  HWC	
  could	
  inform	
  policies	
  
designed	
  to	
  change	
  human	
  behavior	
  and	
  reduce	
  HWC-­‐related	
  risk.	
  	
  Understanding	
  
stakeholders’	
  risk	
  perceptions	
  can	
  inform	
  the	
  content	
  and	
  format	
  of	
  communication	
  and	
  

	
  

5	
  

education	
  messages	
  (Gore	
  et	
  al.,	
  2006;	
  Gore	
  et	
  al.,	
  2007;	
  Knuth	
  et	
  al.,	
  1992;	
  Schmidt	
  &	
  Wei,	
  
2006;	
  Weber,	
  2006)	
  and	
  improve	
  risk	
  communication	
  efforts	
  by	
  better	
  anticipating	
  how	
  
messages	
  may	
  be	
  interpreted	
  (Gore	
  et	
  al.,	
  2006).	
  	
  Finally,	
  risk	
  perception	
  may	
  improve	
  
research	
  design,	
  policy	
  development	
  and	
  institutional	
  decision-­‐making	
  (Gore	
  et	
  al.,	
  2006;	
  
Knuth	
  et	
  al.,	
  1992;	
  Quinn,	
  Huby,	
  Kiwasila	
  &	
  Lovett,	
  2003).	
  	
  For	
  example,	
  Knuth	
  et	
  al.	
  (1992)	
  
said	
  that	
  understanding	
  stakeholder	
  perceptions	
  of	
  risk	
  and	
  benefits	
  of	
  wildlife	
  could	
  
inform	
  the	
  development	
  of	
  alternative	
  management	
  actions	
  that	
  better	
  balance	
  positive	
  
and	
  negative	
  outcomes	
  associated	
  with	
  human-­‐wildlife	
  interactions	
  (HWI).	
  	
  
The	
  literature	
  notes	
  diverse	
  factors	
  influence	
  stakeholder	
  perceptions	
  of	
  risk	
  
associated	
  with	
  HWC	
  (see	
  Gore	
  et	
  al.,	
  2007;	
  Muter,	
  Gore	
  &	
  Riley,	
  2009;	
  Riley	
  &	
  Decker,	
  
2000)	
  and	
  has	
  been	
  primarily	
  focused	
  on	
  stakeholder	
  perceptions	
  of	
  HWC	
  impacts	
  on	
  
human	
  livelihoods	
  (e.g.,	
  economics,	
  health,	
  safety)	
  and	
  acceptance	
  of	
  wildlife	
  species,	
  
abundance	
  and	
  management	
  (e.g.,	
  Aust	
  et	
  al.,	
  2009;	
  Gore	
  et	
  al.,	
  2007;	
  Hill,	
  2004;	
  Riley	
  &	
  
Decker,	
  2000).	
  	
  However,	
  it	
  appears	
  that	
  few	
  scholars	
  or	
  practitioners	
  have	
  identified	
  the	
  
difference	
  between	
  factors	
  that	
  influence	
  stakeholder	
  risk	
  perceptions	
  to	
  and	
  from	
  wildlife	
  
associated	
  with	
  HWC.	
  	
  This	
  is	
  problematic	
  because	
  understanding	
  stakeholders’	
  risk	
  
perceptions	
  to	
  wildlife	
  could,	
  much	
  like	
  livelihood-­‐related	
  HWC	
  risk	
  perceptions,	
  influence	
  
stakeholders’	
  responses	
  to	
  HWC	
  incidents	
  (Hill,	
  2004)	
  and	
  influence	
  preferences	
  for	
  HWC	
  
policy	
  and	
  management	
  (McFarlane,	
  2005).	
  
1.2.2.	
  Vulnerability.	
  
	
  While	
  psychometric	
  risk	
  perception	
  research	
  tends	
  to	
  focus	
  on	
  judgments	
  about	
  the	
  
characteristics	
  of	
  a	
  particular	
  hazard	
  (e.g.,	
  hurricanes,	
  nuclear	
  technology)	
  (Slovic,	
  2000),	
  
vulnerability	
  research	
  focuses	
  on	
  the	
  factors	
  that	
  influence	
  a	
  system’s	
  (e.g.,	
  individual,	
  

	
  

6	
  

wildlife	
  species,	
  country)	
  exposure	
  and	
  sensitivity	
  (i.e.,	
  condition	
  of	
  susceptibility	
  to	
  harm)	
  
to	
  a	
  hazard	
  (Schmidtlein,	
  Deutsch,	
  Piegorsch	
  &	
  Cutter,	
  2008).	
  	
  In	
  the	
  broadest	
  sense,	
  
vulnerability	
  is	
  the	
  potential	
  for	
  a	
  loss	
  when	
  exposed	
  to	
  a	
  hazard	
  (Cutter,	
  Boruff	
  &	
  Shirley,	
  
2003;	
  Schmidtlein	
  et	
  al.,	
  2008).	
  	
  	
  Vulnerability	
  can	
  manifest	
  at	
  a	
  variety	
  of	
  social	
  (e.g.,	
  
individuals,	
  groups,	
  countries)	
  and	
  environmental	
  (e.g.,	
  species,	
  taxonomic	
  groups,	
  
systems)	
  scales	
  (Smit	
  &	
  Wandel,	
  2007).	
  	
  Vulnerability	
  is	
  influenced	
  by	
  a	
  combination	
  of	
  
environmental	
  (i.e.,	
  biophysical)	
  and	
  social	
  factors	
  that	
  determine	
  the	
  propensity	
  of	
  being	
  
exposed	
  to	
  and	
  constraining	
  the	
  ability	
  to	
  recover	
  from	
  exposure	
  to	
  a	
  hazard	
  (Smit	
  &	
  
Wandel,	
  2006).	
  	
  
Early	
  vulnerability	
  studies	
  generally	
  focused	
  on	
  the	
  biophysical	
  characteristics	
  (e.g.,	
  
geographic	
  location)	
  of	
  a	
  system	
  and	
  how	
  those	
  characteristics	
  influenced	
  vulnerability	
  
(Schmidtlein	
  et	
  al.,	
  2008).	
  	
  Later,	
  sociological	
  characteristics	
  (e.g.,	
  ethnicity,	
  gender,	
  wealth)	
  
of	
  communities	
  and	
  individuals	
  were	
  studied	
  (Cutter	
  et	
  al.,	
  2003).	
  	
  Contemporary	
  
vulnerability	
  research	
  integrates	
  biophysical	
  and	
  sociological	
  theories	
  to	
  assess	
  a	
  system’s	
  
overall	
  vulnerability	
  (Chazal,	
  Quétier,	
  Lavorel	
  &	
  Van	
  Doorn,	
  2008;	
  Cutter	
  et	
  al.,	
  2003;	
  Flint	
  
&	
  Luloff,	
  2005).	
  	
  
We	
  know	
  that	
  different	
  species	
  and	
  ecosystems	
  vary	
  in	
  their	
  vulnerability	
  and	
  
ability	
  to	
  adapt	
  to	
  environmental	
  hazards	
  such	
  as	
  drought	
  and	
  human	
  hazards	
  such	
  as	
  
overharvesting	
  (Beier,	
  Patterson	
  &	
  Chapin,	
  2008;	
  Kissui,	
  2008;	
  Thuiller,	
  Broennimann,	
  
Hughes,	
  Alkemades,	
  Midgley	
  &	
  Corsi,	
  2006).	
  	
  	
  For	
  example,	
  Kissui	
  (2008)	
  found	
  that	
  the	
  
vulnerability	
  of	
  carnivores	
  to	
  retaliatory	
  killing	
  in	
  Tanzania	
  was	
  driven	
  by	
  both	
  biological	
  
factors	
  (e.g.,	
  nocturnal	
  predatory	
  behavior)	
  and	
  social	
  factors	
  (e.g.,	
  human	
  intolerance).	
  	
  
Both	
  biophysical	
  and	
  social	
  factors	
  are	
  known	
  to	
  affect	
  human	
  vulnerability	
  to	
  HWC	
  as	
  well.	
  	
  

	
  

7	
  

For	
  instance,	
  Naughton-­‐Treves	
  (1997)	
  found	
  that	
  stakeholders’	
  biophysical	
  vulnerability	
  to	
  
crop	
  damage	
  from	
  wildlife	
  among	
  Ugandan	
  farmers	
  increased	
  with	
  proximity	
  to	
  protected	
  
area	
  boundaries	
  and	
  varied	
  depending	
  on	
  crop	
  type.	
  	
  However,	
  social	
  determinants	
  also	
  
influenced	
  overall	
  stakeholder	
  vulnerability	
  to	
  HWC,	
  as	
  migrants	
  and	
  ethnic	
  minorities	
  in	
  
the	
  community	
  were	
  only	
  given	
  access	
  to	
  the	
  most	
  HWC-­‐prone	
  land;	
  many	
  did	
  not	
  have	
  the	
  
resources	
  to	
  conduct	
  HWC	
  prevention	
  activities	
  (Naughton-­‐Treves,	
  1997).	
  	
  
Resource	
  wealth,	
  gender,	
  ethnic	
  affiliation	
  and	
  the	
  capacity	
  to	
  engage	
  in	
  HWC	
  
deterrence	
  activities	
  (e.g.,	
  construct	
  sturdy	
  fences)	
  may	
  predict	
  social	
  vulnerability	
  to	
  HWC	
  
(Jones	
  &	
  Barnes,	
  2006;	
  Naughton-­‐Treves,	
  1997;	
  Ogra,	
  2008).	
  	
  Variables	
  such	
  as	
  decision-­‐
making	
  authority,	
  age,	
  education,	
  marital	
  status,	
  household	
  size	
  and	
  livelihood	
  strategy	
  
affect	
  vulnerability	
  to	
  environmental	
  hazards	
  such	
  as	
  hurricanes	
  (Cutter	
  et	
  al.,	
  2003;	
  
Schmidtlien	
  et	
  al.,	
  2008)	
  and	
  warrant	
  further	
  consideration	
  within	
  the	
  context	
  of	
  HWC.	
  	
  	
  
Additionally,	
  it	
  is	
  necessary	
  to	
  understand	
  the	
  broader	
  context	
  of	
  local	
  risks,	
  as	
  the	
  
presence	
  and	
  combination	
  of	
  non-­‐HWC	
  related	
  risks	
  (e.g.,	
  climate,	
  HIV/AIDS)	
  may	
  heighten	
  
vulnerability	
  of	
  stakeholders	
  and	
  wildlife	
  to	
  HWC-­‐related	
  risks	
  (Reid	
  &	
  Vogel,	
  2006;	
  
Tschakert,	
  2007).	
  	
  
Increased	
  understanding	
  about	
  local	
  livelihood	
  and	
  wildlife	
  vulnerability	
  to	
  HWC-­‐
related	
  risks	
  would	
  be	
  advantageous	
  for	
  improving	
  the	
  management	
  of	
  those	
  risks,	
  as	
  it	
  can	
  
guide	
  the	
  prioritization	
  of	
  interventions	
  designed	
  to	
  mitigate	
  loss	
  (Hill,	
  2004;	
  Nathan,	
  2008;	
  
Naughton-­‐Treves,	
  1997)	
  and	
  help	
  identify	
  opportunities	
  for	
  adaptation	
  (Smit	
  &	
  Wandel,	
  
2006;	
  Tschakert,	
  2007).	
  	
  Jones	
  &	
  Barnes	
  (2006),	
  Ogra	
  (2008)	
  and	
  World	
  Wildlife	
  Fund	
  
(WWF)	
  (2008)	
  identified	
  the	
  need	
  to	
  better	
  understand	
  what	
  drives	
  disparate	
  HWC	
  
vulnerability	
  of	
  local	
  communities	
  and	
  individuals	
  so	
  that	
  HWC	
  can	
  be	
  better	
  managed.	
  	
  

	
  

8	
  

The	
  likelihood	
  of	
  exposure	
  to	
  a	
  HWC-­‐related	
  hazard	
  as	
  well	
  as	
  the	
  sociological	
  drivers	
  that	
  
constrain	
  or	
  enable	
  the	
  human	
  response	
  when	
  encountering	
  wildlife	
  are	
  not	
  well	
  
understood.	
  	
  
1.2.3.	
  Integrating	
  risk	
  perception	
  and	
  vulnerability.	
  	
  	
  
The	
  concepts	
  of	
  risk	
  perception	
  and	
  vulnerability	
  appear	
  to	
  be	
  intertwined,	
  however	
  
the	
  relationship	
  is	
  nebulous.	
  	
  The	
  concept	
  of	
  vulnerability	
  emerged	
  through	
  the	
  study	
  of	
  
risk	
  assessments	
  (Marandola	
  &	
  Hogan,	
  2006).	
  	
  Local	
  risk	
  perceptions	
  are	
  often	
  used	
  to	
  
identify	
  disparately	
  vulnerable	
  or	
  influential	
  stakeholders	
  in	
  regards	
  to	
  a	
  specific	
  hazard	
  
(Ogra,	
  2008;	
  Quinn	
  et	
  al.,	
  2003;	
  Smith,	
  Barrett	
  &	
  Box,	
  2000).	
  	
  However,	
  few	
  studies	
  of	
  risk	
  
perception	
  overtly	
  address	
  the	
  relationship	
  between	
  perceived	
  risk	
  and	
  perceived	
  
vulnerability;	
  most	
  interpret	
  high-­‐risk	
  perception	
  as	
  being	
  equivalent	
  to	
  high	
  vulnerability	
  
perception	
  (Satterfield,	
  Mertz	
  &	
  Slovic,	
  2004).	
  	
  Satterfield	
  et	
  al.	
  (2004)	
  found	
  that	
  people	
  
with	
  high	
  perceptions	
  of	
  vulnerability	
  also	
  exhibited	
  higher	
  perceptions	
  of	
  risk.	
  	
  	
  However,	
  
Ogra	
  (2008)	
  found	
  stakeholders	
  with	
  a	
  higher	
  assessed	
  vulnerability	
  to	
  HWC	
  risks	
  
perceived	
  themselves	
  to	
  be	
  equally	
  affected	
  by	
  HWC	
  as	
  their	
  less	
  vulnerable	
  counterparts.	
  	
  
To	
  explore	
  the	
  relationship	
  between	
  perceived	
  risk	
  and	
  vulnerability,	
  I	
  developed	
  an	
  
integrated	
  risk	
  and	
  vulnerability	
  conceptual	
  framework	
  (Figure	
  1).	
  	
  In	
  relation	
  to	
  HWC-­‐	
  
related	
  risk	
  perceptions,	
  I	
  measured	
  judgments	
  about	
  HWC	
  characteristics	
  for	
  a	
  variety	
  of	
  
factors	
  (e.g.,	
  control,	
  dread,	
  risk	
  fairness).	
  	
  I	
  considered	
  perceived	
  HWC	
  vulnerability	
  to	
  be	
  a	
  
function	
  of	
  exposure	
  risk	
  (i.e.,	
  perceived	
  frequency	
  of	
  personal	
  exposure	
  to	
  HWC)	
  and	
  
perceived	
  consequences	
  (i.e.,	
  anticipated	
  losses	
  associated	
  with	
  HWC	
  exposure)	
  of	
  HWC-­‐
related	
  risks	
  (see	
  Nathan,	
  2008;	
  Satterfield	
  et	
  al.,	
  2004),	
  ultimately	
  embedding	
  perceived	
  
vulnerability	
  as	
  a	
  factor	
  influencing	
  risk	
  perception.	
  	
  I	
  also	
  investigated	
  the	
  influence	
  of	
  

	
  

9	
  

demographic	
  characteristics	
  (e.g.,	
  gender,	
  age)	
  on	
  stakeholders’	
  perceptions	
  of	
  
vulnerability	
  to	
  HWC.	
  	
  Additionally,	
  I	
  investigated	
  HWC-­‐related	
  risks	
  relative	
  to	
  other	
  risks	
  
to	
  human	
  livelihoods	
  and	
  wildlife.	
  	
  Lastly,	
  I	
  assessed	
  the	
  influence	
  of	
  risk	
  management	
  
regime	
  (e.g.,	
  conservancy	
  establishment)	
  on	
  stakeholder	
  perceptions	
  of	
  HWC-­‐related	
  risks.	
  	
  
1.3.	
  STUDY	
  AREA	
  
1.3.1.	
  The	
  Republic	
  of	
  Namibia.	
  	
  
Namibia	
  is	
  a	
  democratic	
  republic	
  in	
  southwestern	
  Africa.	
  	
  A	
  former	
  South	
  African	
  
territory	
  that	
  achieved	
  its	
  independence	
  in	
  1990,	
  Namibia	
  encompasses	
  approximately	
  
824,000	
  km2	
  and	
  has	
  over	
  two	
  million	
  residents	
  (Weaver	
  &	
  Skyer,	
  2005).	
  	
  The	
  economy	
  in	
  
Namibia	
  is	
  highly	
  dependent	
  upon	
  renewable	
  and	
  non-­‐renewable	
  natural	
  resources,	
  
particularly	
  the	
  export	
  of	
  minerals,	
  livestock,	
  and	
  marine	
  resources	
  (Wardell-­‐Johnson,	
  
2000).	
  	
  The	
  exploitation	
  of	
  key	
  minerals,	
  particularly	
  diamonds,	
  has	
  fuelled	
  the	
  
accumulation	
  of	
  wealth	
  in	
  Namibia	
  (Krugmann,	
  2001).	
  	
  However,	
  Krugmann	
  (2001)	
  stated	
  
that	
  the	
  rate	
  of	
  resource	
  exploitation	
  and	
  lack	
  of	
  economic	
  diversification	
  has	
  put	
  Namibia	
  
at	
  risk	
  for	
  unsustainable	
  development.	
  	
  Additionally,	
  there	
  is	
  great	
  economic	
  disparity	
  
among	
  Namibians;	
  the	
  country	
  has	
  one	
  of	
  the	
  world’s	
  most	
  inequitable	
  distributions	
  of	
  
income,	
  wealth	
  and	
  access	
  to	
  resources	
  (Krugmann,	
  2001).	
  	
  Further,	
  although	
  state-­‐owned	
  
communal	
  lands	
  comprise	
  40%	
  of	
  the	
  country	
  (Nott	
  &	
  Jacobsohn,	
  2004),	
  more	
  than	
  65%	
  of	
  
the	
  population	
  lives	
  as	
  subsistence	
  farmers	
  on	
  these	
  lands	
  (Weaver	
  &	
  Skyer,	
  2005).	
  	
  
Historically,	
  communal	
  area	
  residents	
  have	
  depended	
  on	
  subsistence-­‐based	
  agricultural	
  
and	
  livestock	
  to	
  support	
  local	
  livelihoods.	
  	
  Today,	
  these	
  areas	
  have	
  integrated	
  wildlife	
  
utilization	
  and	
  tourism	
  into	
  their	
  economic	
  development	
  (Weaver	
  &	
  Skyer,	
  2005).	
  	
  

	
  

10	
  

Namibia	
  is	
  home	
  to	
  over	
  250	
  species	
  of	
  extant	
  mammals	
  (Griffin,	
  1998),	
  including	
  
Africa’s	
  largest	
  cheetah	
  population	
  (Acinonyx	
  jubatus)	
  (Marker,	
  2001)	
  and	
  644	
  species	
  of	
  
birds	
  (Robertson,	
  Jarvis	
  &	
  Brown,	
  1998).	
  	
  Currently,	
  greater	
  than	
  38%	
  of	
  Namibia’s	
  land	
  is	
  
under	
  some	
  form	
  of	
  conservation	
  management	
  regime	
  including	
  state	
  protected	
  areas	
  
(17%),	
  communal	
  conservancies	
  (15%),	
  privately	
  owned	
  conservancies	
  (6%)	
  and	
  
conservation	
  concession	
  areas	
  (1%)	
  (Namibian	
  Association	
  of	
  Community	
  Based	
  Natural	
  
Resource	
  Management	
  Support	
  Organizations	
  (NACSO),	
  2009).	
  	
  Namibia	
  faces	
  numerous	
  
conservation	
  challenges	
  including	
  invasive	
  alien	
  species,	
  habitat	
  alteration	
  (Griffin,	
  1998)	
  
and	
  human-­‐wildlife	
  conflict	
  (Marker,	
  2001;	
  O’Connell-­‐Rodwell,	
  Rodwell,	
  Rice	
  &	
  Hart,	
  
2000).	
  	
  Some	
  wildlife	
  species	
  continue	
  to	
  persist	
  widely	
  (e.g.,	
  leopard,	
  brown	
  hyena)	
  while	
  
other	
  species	
  (e.g.,	
  lion,	
  spotted	
  hyena)	
  have	
  been	
  largely	
  eliminated	
  due	
  in	
  part	
  to	
  conflicts	
  
with	
  agriculture	
  and	
  livestock	
  operations	
  (Barnes	
  &	
  Jones,	
  2009).	
  	
  Reducing	
  HWC	
  in	
  
Namibia	
  is	
  a	
  critical	
  development	
  and	
  conservation	
  issue	
  (Ministry	
  of	
  Environment	
  and	
  
Tourism	
  [MET],	
  2009).	
  
1.3.2.	
  Namibian	
  communal	
  conservancies.	
  	
  	
  
Namibia’s	
  communal	
  conservancies,	
  a	
  form	
  of	
  community-­‐based	
  natural	
  resource	
  
management	
  (CBNRM),	
  are	
  joint	
  management	
  ventures	
  between	
  rural	
  communities,	
  
relevant	
  government	
  agencies	
  and	
  non-­‐governmental	
  organizations.	
  Local	
  communities	
  
maintain	
  the	
  right	
  to	
  financially	
  benefit	
  from	
  local	
  wildlife	
  (Stuart-­‐Hill,	
  Diggle,	
  Munali,	
  Tagg	
  
&	
  Ward,	
  2005).	
  	
  	
  Although	
  tourism	
  (e.g.,	
  trophy	
  hunting,	
  lodges,	
  campsites)	
  provides	
  the	
  
majority	
  of	
  economic	
  benefits	
  to	
  conservancy	
  residents	
  (Suich,	
  2010),	
  selling	
  crafts,	
  veld	
  
products	
  (e.g.,	
  thatch,	
  commercial	
  plant	
  products)	
  and	
  wildlife	
  products	
  (e.g.,	
  meat,	
  skins	
  or	
  
trophies	
  from	
  hunting)	
  provide	
  additional	
  income	
  to	
  conservancy	
  residents	
  (NACSO,	
  2009).	
  	
  

	
  

11	
  

Namibia's	
  conservancies	
  are	
  often	
  lauded	
  as	
  a	
  successful	
  example	
  of	
  a	
  CBNRM	
  regime	
  in	
  
that	
  they	
  simultaneously	
  conserve	
  natural	
  resources	
  and	
  preserve	
  livelihoods	
  (Hoole	
  &	
  
Berkes,	
  2010;	
  Suich,	
  2010).	
  	
  
The	
  legislative	
  precedent	
  for	
  conservancies	
  in	
  Namibia	
  was	
  set	
  in	
  1968	
  when	
  
commercial	
  farmers	
  were	
  granted	
  limited	
  rights	
  over	
  wildlife	
  found	
  on	
  their	
  land	
  (Weaver	
  
&	
  Skyer,	
  2005).	
  	
  However,	
  the	
  model	
  for	
  what	
  would	
  become	
  the	
  conservancy	
  program	
  
emerged	
  in	
  the	
  1980’s	
  in	
  the	
  form	
  of	
  Community	
  Game	
  Guards,	
  which	
  was	
  a	
  CBNRM	
  
program	
  administered	
  by	
  the	
  non-­‐governmental	
  organization	
  (NGO)	
  Integrated	
  Rural	
  
Development	
  and	
  Nature	
  Conservation	
  (IRDNC)	
  (Weaver	
  &	
  Skyer,	
  2005).	
  	
  After	
  majority	
  
rule	
  was	
  enacted	
  in	
  post-­‐apartheid,	
  independent	
  Namibia,	
  there	
  was	
  political	
  and	
  social	
  
backing	
  to	
  extend	
  the	
  wildlife	
  use	
  rights	
  conferred	
  on	
  white	
  commercial	
  farmers	
  to	
  
communal	
  area	
  residents	
  (Hoole	
  &	
  Berkes,	
  2010;	
  Roe,	
  Nelson	
  &	
  Sandbrook,	
  2009).	
  	
  In	
  1992	
  
the	
  MET	
  began	
  drafting	
  policies	
  that	
  would	
  extend	
  rights	
  over	
  wildlife	
  and	
  other	
  natural	
  
resources	
  to	
  communal	
  land	
  residents.	
  	
  The	
  legislation	
  passed	
  in	
  1996	
  and	
  was	
  
implemented	
  in	
  1998	
  (Suich,	
  2010).	
  	
  Today,	
  the	
  conservancy	
  program	
  includes	
  over	
  50	
  
registered	
  conservancies	
  covering	
  approximately	
  12.2	
  million	
  hectares	
  of	
  communal	
  land	
  
and	
  over	
  224,000	
  residents	
  (NACSO,	
  2009).	
  	
  
Key	
  features	
  of	
  the	
  Namibian	
  conservancy	
  system	
  include:	
  1)	
  legally	
  secure	
  
communal	
  rights	
  over	
  the	
  management	
  of	
  natural	
  resources,	
  with	
  no	
  term-­‐limits	
  (Roe	
  et	
  al.,	
  
2009);	
  2)	
  a	
  legislative	
  basis	
  for	
  consumptive	
  use	
  of	
  wildlife1	
  (e.g.,	
  subsistence	
  and	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
1	
  The	
  Ministry	
  of	
  Environment	
  and	
  Tourism	
  (MET)	
  retains	
  the	
  right	
  to	
  grant	
  permission	
  to	
  
harvest	
  ‘specially	
  protected	
  game’	
  (i.e.,	
  giraffe,	
  elephant,	
  rhinoceros,	
  hippopotamus)	
  and	
  
‘protected	
  game’	
  (i.e.,	
  roan,	
  cheetah,	
  leopard,	
  tortoises,	
  most	
  bird	
  species).	
  

	
  

12	
  

commercial	
  hunting)	
  (Corbett	
  &	
  Daniels,	
  1996);	
  3)	
  100%	
  of	
  economic	
  benefits	
  retained	
  at	
  
the	
  local	
  level	
  (e.g.,	
  no	
  government	
  tax	
  on	
  revenue,	
  direct	
  revenue	
  sharing	
  between	
  
conservancies	
  and	
  private	
  sector)	
  (Roe	
  et	
  al.,	
  2009);	
  and	
  4)	
  codified	
  wildlife	
  damage	
  
management	
  procedures	
  (MET,	
  2009).	
  	
  In	
  accordance	
  with	
  regulations	
  governing	
  
conservancies	
  in	
  Namibia,	
  each	
  conservancy	
  must	
  engage	
  in	
  the	
  sustainable	
  management	
  
of	
  their	
  natural	
  resources	
  (Stuart-­‐Hill	
  et	
  al.,	
  2005);	
  the	
  rights	
  to	
  manage	
  resources	
  through	
  
a	
  conservancy	
  are	
  conditional	
  and	
  can	
  be	
  revoked	
  (Roe	
  et	
  al.,	
  2009).	
  
A	
  change	
  in	
  predominantly	
  negative	
  local	
  attitudes	
  towards	
  wildlife	
  is	
  often	
  cited	
  as	
  
one	
  of	
  the	
  conservancies’	
  greatest	
  conservation	
  successes	
  (e.g.	
  Weaver	
  &	
  Skyer,	
  2005).	
  	
  	
  
Whereas	
  wildlife	
  under	
  state	
  ownership	
  was	
  considered	
  a	
  liability	
  to	
  local	
  livelihoods	
  
because	
  residents	
  were	
  burdened	
  with	
  the	
  economic	
  costs	
  of	
  living	
  with	
  wildlife,	
  
conservancies	
  created	
  a	
  situation	
  in	
  which	
  wildlife	
  could	
  become	
  an	
  economic	
  asset	
  
(Weaver	
  &	
  Skyer,	
  2005).	
  The	
  establishment	
  of	
  the	
  conservancy	
  system	
  has	
  been	
  credited	
  as	
  
a	
  major	
  contributing	
  factor	
  in	
  the	
  reduction	
  of	
  poaching,	
  which	
  was	
  high	
  in	
  the	
  1980s	
  and	
  
early	
  1990s	
  and	
  has	
  recently	
  declined	
  (Nott	
  &	
  Jacobsohn,	
  2004;	
  Vaughn	
  &	
  Long,	
  2007).	
  	
  	
  
Human	
  and	
  wildlife	
  populations	
  are	
  growing	
  in	
  Namibia,	
  which	
  has	
  led	
  to	
  reports	
  of	
  
increased	
  frequencies	
  and	
  magnitudes	
  of	
  HWC	
  both	
  inside	
  and	
  outside	
  of	
  conservancies	
  
(Jones	
  &	
  Barnes,	
  2006;	
  MET,	
  2009).	
  	
  In	
  2009,	
  in	
  response	
  to	
  increasing	
  reports	
  of	
  HWC,	
  the	
  
federal	
  government	
  established	
  a	
  nationwide	
  policy	
  for	
  HWC	
  management	
  (MET,	
  2009).	
  	
  	
  
This	
  legal	
  framework	
  mandated	
  conservancies	
  compensate	
  farmers	
  for	
  livestock	
  losses	
  and	
  
crop	
  damage	
  under	
  the	
  Human	
  Wildlife	
  Self	
  Reliance	
  Scheme	
  and	
  devolved	
  the	
  authority	
  to	
  

	
  

13	
  

destroy	
  problem	
  animals	
  to	
  regional	
  MET	
  staff	
  members	
  and	
  conservancies	
  (MET,	
  2009).2	
  	
  	
  	
  
The	
  policy	
  put	
  the	
  onus	
  of	
  taking	
  preventative	
  measures	
  to	
  avoid	
  HWC	
  on	
  all	
  citizens	
  and	
  
mandates	
  that	
  a	
  portion	
  of	
  conservancy	
  trophy	
  hunting	
  revenues,	
  not	
  governmental	
  funds,	
  
be	
  used	
  to	
  fund	
  the	
  compensation	
  program	
  (MET,	
  2009).	
  	
  This	
  legislation	
  further	
  devolved	
  
not	
  only	
  rights	
  over	
  wildlife	
  but	
  also	
  the	
  responsibility	
  of	
  HWC	
  management	
  to	
  
conservancies.	
  
1.3.3.	
  The	
  Caprivi	
  Strip.	
  	
  
This	
  research	
  was	
  conducted	
  in	
  East	
  Caprivi,	
  part	
  of	
  the	
  Zambezian	
  Baikiaea	
  
woodlands	
  and	
  flooded	
  grasslands	
  (Burgess,	
  Hales,	
  Underwood,	
  Dinerstein,	
  Olson,	
  Itoua	
  et	
  
al.,	
  2004)	
  (Figure	
  1.2),	
  in	
  an	
  emerging	
  (Dzoti)	
  and	
  established	
  (Wuparo)	
  conservancy	
  
(Figure	
  1.3).	
  	
  The	
  Caprivi	
  region	
  has	
  a	
  mild	
  climate	
  (O’Connell-­‐Rodwell	
  et	
  al.,	
  2000),	
  the	
  
highest	
  rainfall	
  in	
  Namibia	
  (Wardell-­‐Johnson,	
  2000),	
  and	
  proximity	
  to	
  four	
  major	
  rivers	
  
(i.e.,	
  Okavango,	
  Kwando,	
  Chobe,	
  Zambezi)	
  and	
  their	
  tributaries.	
  	
  Local	
  livelihoods	
  in	
  Caprivi	
  
are	
  largely	
  supported	
  by	
  natural	
  resources,	
  including	
  agriculture,	
  fisheries,	
  forestry,	
  
livestock,	
  and	
  hunting	
  and	
  gathering	
  activities	
  (Jones	
  &	
  Barnes,	
  2006;	
  Murphy	
  &	
  Mulonga,	
  
2002).	
  	
  Despite	
  Caprivi’s	
  rich	
  natural	
  resource	
  base	
  and	
  favorable	
  climate,	
  the	
  region	
  
remains	
  one	
  of	
  Namibia’s	
  most	
  impoverished	
  and	
  least	
  developed	
  (Suich,	
  2010).	
  	
  
Additionally,	
  Caprivians	
  struggle	
  with	
  one	
  of	
  the	
  nations'	
  highest	
  infection	
  rates	
  for	
  
HIV/AIDS	
  and	
  malaria,	
  natural	
  disasters	
  that	
  damage	
  agriculture	
  and	
  spread	
  disease,	
  and	
  
poor	
  access	
  to	
  health	
  services	
  (Jones	
  &	
  Barnes,	
  2006).	
  	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
2	
  Crop	
  damage	
  is	
  compensated	
  only	
  if	
  caused	
  by	
  elephant	
  or	
  hippopotamus.	
  	
  Livestock	
  
losses	
  are	
  compensated	
  only	
  if	
  they	
  meet	
  the	
  criteria	
  related	
  to	
  the	
  location	
  of	
  the	
  incident	
  
(no	
  national	
  park	
  or	
  wildlife	
  exclusive	
  zone),	
  reporting	
  and	
  verification	
  and	
  precautionary	
  
measures	
  have	
  been	
  taken	
  (MET,	
  2009).	
  

	
  

14	
  

Caprivi	
  has	
  many	
  systems	
  of	
  conservation	
  and	
  land	
  tenure,	
  including	
  communal	
  
areas	
  supporting	
  11	
  conservancies,	
  state	
  land	
  holdings	
  supporting	
  6	
  national	
  parks	
  and	
  
game	
  reserves	
  (MET,	
  2009),	
  private	
  land	
  holdings	
  supporting	
  game	
  farms	
  and	
  tourist	
  
ventures	
  (Jones	
  &	
  Barnes,	
  2006),	
  and	
  a	
  transnational	
  wildlife	
  corridor	
  shared	
  with	
  Angola,	
  
Zambia,	
  and	
  Botswana	
  (WWF,	
  2008).	
  	
  Currently,	
  Caprivi’s	
  registered	
  conservancies	
  cover	
  
16%	
  of	
  the	
  region;	
  approximately	
  29%	
  of	
  the	
  Caprivian	
  population	
  resides	
  in	
  a	
  
conservancy	
  (NACSO,	
  2009).	
  
There	
  is	
  nowhere	
  in	
  Namibia	
  where	
  the	
  issue	
  of	
  HWC	
  is	
  more	
  salient	
  than	
  Caprivi;	
  
indeed	
  Caprivi	
  has	
  the	
  highest	
  estimated	
  incident	
  rates	
  of	
  HWC,	
  including	
  high	
  livestock	
  
depredation	
  and	
  crop	
  damage	
  (Jones	
  &	
  Barnes,	
  2006;	
  O’Connell-­‐Rodwell	
  et	
  al.,	
  2000).	
  	
  HWC	
  
in	
  the	
  region	
  is	
  estimated	
  to	
  cause	
  an	
  annual	
  loss	
  of	
  US	
  $770,000	
  (WWF,	
  2008).	
  	
  Numerous	
  
species	
  are	
  implicated	
  in	
  conflicts	
  with	
  people	
  in	
  Caprivi,	
  however	
  two	
  species,	
  elephants	
  
and	
  lions,	
  contribute	
  to	
  the	
  greatest	
  number	
  of	
  incidents	
  reported	
  and	
  the	
  highest	
  
economic	
  losses	
  (O’Connell-­‐Rodwell	
  et	
  al.,	
  2000).	
  	
  While	
  the	
  total	
  annual	
  per	
  capita	
  value	
  of	
  
losses	
  due	
  to	
  wildlife	
  in	
  Caprivi	
  is	
  $75	
  USD	
  or	
  approximately	
  7%	
  of	
  household	
  income,	
  
these	
  losses	
  are	
  unequally	
  distributed	
  among	
  households	
  and	
  do	
  not	
  take	
  into	
  account	
  
agricultural	
  products	
  not	
  sold	
  at	
  market	
  but	
  needed	
  for	
  subsistence	
  (WWF,	
  2008).	
  	
  Jones	
  
and	
  Barnes	
  (2006)	
  asserted	
  that	
  lethally	
  removing	
  problem	
  animals	
  did	
  not	
  appear	
  to	
  be	
  
threatening	
  population	
  levels.	
  	
  However,	
  they	
  (ibid)	
  cautioned	
  that	
  increasing	
  perceptions	
  
of	
  threats	
  from	
  wildlife	
  conflict	
  could	
  undermine	
  positive	
  local	
  attitudes	
  towards	
  wildlife	
  in	
  
Caprivi,	
  potentially	
  resulting	
  in	
  increased	
  retaliation,	
  problem	
  animal	
  removals,	
  and	
  
ultimately	
  affecting	
  wildlife	
  population	
  levels	
  in	
  the	
  long	
  term.	
  	
  

	
  

15	
  

The	
  high	
  levels	
  of	
  HWC	
  in	
  Caprivi	
  are	
  due	
  in	
  large	
  part	
  to	
  its	
  high	
  human	
  and	
  wildlife	
  
population	
  densities.	
  	
  Caprivi	
  boasts	
  the	
  second	
  most	
  densely	
  populated	
  area	
  in	
  Namibia,	
  
with	
  over	
  4	
  people	
  per	
  square	
  kilometer	
  (Jones	
  &	
  Barnes,	
  2006).	
  	
  It	
  also	
  supports	
  high	
  
concentrations	
  of	
  wildlife,	
  including	
  one	
  of	
  the	
  largest	
  populations	
  of	
  free	
  ranging	
  
elephants	
  in	
  Africa	
  (O’Connell-­‐Rodwell	
  et	
  al.,	
  2000).	
  	
  The	
  dependence	
  of	
  the	
  majority	
  of	
  
Caprivians	
  on	
  subsistence	
  farming	
  increases	
  their	
  vulnerability	
  to	
  HWC	
  and	
  exacerbates	
  
livelihood	
  insecurity	
  already	
  affected	
  by	
  environmental	
  risks	
  (e.g.,	
  floods,	
  drought)	
  and	
  
socio-­‐economic	
  challenges	
  (e.g.,	
  limited	
  market	
  access,	
  HIV/AIDS)	
  (Jones	
  &	
  Barnes,	
  2006).	
  	
  	
  
1.4.	
  RESEARCH	
  STATEMENT	
  AND	
  OBJECTIVES	
  
	
  

Deeper	
  theoretical	
  understanding	
  about	
  the	
  factors	
  that	
  influence	
  perceptions	
  of	
  

HWC-­‐related	
  risk	
  and	
  vulnerability	
  may	
  inform	
  local	
  HWC	
  management	
  by	
  facilitating	
  
greater	
  integration	
  of	
  stakeholders’	
  risk	
  priorities	
  into	
  decision	
  making.	
  	
  Practically,	
  
wildlife	
  stakeholders	
  have	
  expressed	
  a	
  need	
  for	
  more	
  effective	
  HWC-­‐related	
  interventions,	
  
which	
  requires	
  understanding	
  of	
  both	
  how	
  stakeholders	
  differentially	
  prioritize	
  risks	
  as	
  
well	
  as	
  identifying	
  those	
  most	
  vulnerable	
  to	
  risks.	
  	
  This	
  research	
  provided	
  knowledge	
  on	
  
risk	
  perception,	
  vulnerability,	
  and	
  HWC	
  in	
  Caprivi.	
  	
  
Objective	
  1:	
  Characterize	
  HWC-­related	
  risks	
  and	
  risk	
  perceptions	
  to	
  and	
  from	
  people	
  and	
  
wildlife.	
  	
  	
  
Approach:	
  	
  I	
  explored	
  stakeholders'	
  perceptions	
  of	
  HWC-­‐related	
  risks	
  to	
  and	
  from	
  people	
  
and	
  wildlife.	
  	
  Risk	
  perceptions	
  were	
  quantified	
  and	
  described	
  by	
  querying	
  perceived	
  
severity	
  of	
  HWC-­‐related	
  risks	
  in	
  regard	
  to	
  other	
  risks	
  to	
  livelihoods	
  and	
  wildlife,	
  describing	
  
risk	
  intensities	
  in	
  a	
  spatially	
  explicit	
  way,	
  and	
  examining	
  perceptions	
  of	
  HWC-­‐related	
  risk	
  
and	
  vulnerability	
  to	
  livelihoods	
  and	
  conservancy	
  wildlife.	
  	
  Risk	
  perceptions	
  and	
  

	
  

16	
  

vulnerability	
  were	
  queried	
  using	
  both	
  local	
  livelihoods	
  and	
  conservancy	
  wildlife	
  as	
  a	
  risk	
  
target	
  (i.e.,	
  the	
  subject	
  toward	
  which	
  the	
  risk	
  is	
  directed).	
  	
  
Objective	
  2:	
  Evaluate	
  factors	
  influencing	
  risk	
  perception	
  associated	
  with	
  HWC.	
  
Approach:	
  	
  I	
  adapted	
  Gore	
  et	
  al.'s	
  (2007)	
  factors	
  influencing	
  risk	
  perception	
  to	
  measure	
  
stakeholders’	
  perceptions	
  of	
  risk	
  associated	
  with	
  HWC.	
  	
  I	
  used	
  seven	
  constructs	
  to	
  measure	
  
risk	
  perception:	
  dread,	
  environment,	
  frequency,	
  control	
  (Gore	
  et	
  al.,	
  2007),	
  risk	
  fairness	
  
(McDaniels,	
  Axelrod,	
  Cavanagh	
  &	
  Slovic,	
  1997;	
  Schmidt	
  &	
  Wei,	
  2006),	
  acceptability	
  and	
  
consequence	
  (Slovic,	
  1987).	
  	
  Additionally,	
  I	
  assessed	
  the	
  extent	
  to	
  which	
  conservancy	
  
establishment	
  influenced	
  perceptions	
  of	
  HWC-­‐related	
  risks.	
  	
  Five	
  demographic	
  factors	
  (age,	
  
decision-­‐making	
  authority,	
  education,	
  gender,	
  resource	
  wealth)	
  were	
  assessed	
  to	
  
determine	
  their	
  influence	
  on	
  stakeholders’	
  perception	
  of	
  HWC-­‐related	
  risks	
  (Cutter	
  et	
  al.	
  
2003;	
  Naughton-­‐Treves,	
  1997;	
  Ogra,	
  2008).	
  	
  I	
  measured	
  risk	
  perception	
  relative	
  to	
  two	
  risk	
  
targets:	
  local	
  livelihoods	
  and	
  conservancy	
  wildlife.	
  	
  
Objective	
  3:	
  Evaluate	
  factors	
  influencing	
  vulnerability	
  to	
  HWC.	
  
Approach:	
  	
  I	
  assessed	
  the	
  extent	
  to	
  which	
  conservancy	
  establishment	
  and	
  demographic	
  
factors	
  influenced	
  perceptions	
  of	
  vulnerability	
  to	
  HWC-­‐related	
  risks	
  to	
  livelihoods	
  and	
  
wildlife.	
  	
  I	
  considered	
  perceived	
  HWC-­‐related	
  vulnerability	
  to	
  be	
  a	
  function	
  of	
  the	
  
frequency	
  and	
  perceived	
  consequences	
  of	
  exposure	
  to	
  HWC	
  (see	
  Nathan,	
  2008;	
  Satterfield	
  
et	
  al.,	
  2004)	
  and	
  considered	
  perceived	
  vulnerability	
  to	
  be	
  a	
  factor	
  influencing	
  risk	
  
perception	
  (Figure	
  1).	
  	
  Five	
  demographic	
  variables	
  theoretically	
  linked	
  to	
  HWC-­‐related	
  
vulnerability	
  were	
  tested,	
  based	
  on	
  Cutter	
  et	
  al.	
  (2003),	
  Naughton-­‐Treves	
  (1997)	
  and	
  Ogra	
  
(2008):	
  age,	
  decision-­‐making	
  authority,	
  education,	
  gender,	
  and	
  resource	
  wealth.	
  	
  I	
  also	
  
described	
  perceptions	
  of	
  spatial	
  vulnerability	
  related	
  to	
  HWC	
  within	
  the	
  conservancy	
  and	
  

	
  

17	
  

stakeholders’	
  perceptions	
  of	
  exposure	
  of	
  livelihoods	
  and	
  wildlife	
  to	
  multiple	
  HWC-­‐related	
  
and	
  non-­‐HWC	
  related	
  risks.	
  
1.5.	
  THESIS	
  ORGANIZATION	
  
	
  

Chapter	
  two	
  of	
  this	
  thesis	
  examines	
  local	
  stakeholders'	
  conceptualization	
  of	
  HWC-­‐

related	
  risks	
  relative	
  to	
  other	
  risks	
  affecting	
  local	
  livelihoods	
  and	
  conservancy	
  wildlife,	
  
describes	
  local	
  perceptions	
  of	
  risks	
  both	
  to	
  and	
  from	
  wildlife	
  due	
  to	
  HWC,	
  and	
  examines	
  the	
  
effect	
  that	
  conservancy	
  establishment	
  has	
  on	
  perceptions	
  of	
  risk	
  and	
  vulnerability	
  to	
  HWC-­‐
related	
  risks.	
  	
  Chapter	
  three	
  explores	
  local	
  perceptions	
  of	
  poaching	
  as	
  a	
  risk	
  to	
  conservancy	
  
wildlife	
  and	
  examines	
  stakeholder	
  motivations	
  to	
  poach.	
  	
  This	
  chapter	
  also	
  demonstrates	
  a	
  
participatory	
  method	
  for	
  identifying	
  HWC	
  vulnerability	
  hotspots	
  in	
  the	
  landscape,	
  which	
  
has	
  implications	
  for	
  targeted	
  enforcement	
  and	
  interventions	
  meant	
  to	
  increase	
  compliance.	
  
Chapter	
  four	
  summarizes	
  the	
  theoretical,	
  methodological	
  and	
  practical	
  implications	
  of	
  this	
  
research.	
  	
  Points	
  for	
  future	
  research	
  are	
  discussed.	
  Appendices	
  provide	
  information	
  on	
  
research	
  procedures	
  and	
  provide	
  breadth	
  and	
  depth	
  to	
  research	
  findings.	
  
	
  
	
  

	
  

18	
  

	
  

Table	
  1.1:	
  Definitions	
  of	
  research	
  concepts	
  and	
  terminology	
  
Concept	
  

	
  	
   Definition	
  

Biophysical	
  vulnerability	
  

The	
  likelihood	
  of	
  a	
  system's	
  exposure	
  to	
  and	
  ability	
  
to	
  adapt	
  to	
  a	
  hazard	
  based	
  on	
  the	
  biological,	
  physical	
  
	
   and/or	
  geographic	
  characteristics	
  of	
  the	
  system	
  
(adapted:	
  Cutter	
  et	
  al.,	
  2003;	
  Hogan	
  &	
  Marandola,	
  
2005).	
  	
  

Community-­‐based	
  natural	
  
resource	
  management	
  
(CBNRM)	
  

A	
  system	
  of	
  management	
  of	
  natural	
  resources,	
  for	
  
	
   commercial	
  and/or	
  subsistence	
  uses,	
  by	
  collective,	
  
local	
  institutions	
  for	
  local	
  benefit	
  (Roe	
  et	
  al.,	
  2009).	
  

Compliance	
  

Behavior	
  of	
  people	
  to	
  conform	
  to	
  rules,	
  which	
  may	
  
	
   be	
  formal	
  laws	
  or	
  informal	
  norms	
  that	
  have	
  been	
  
formulated	
  to	
  influence	
  their	
  actions	
  (Hauck,	
  2008).	
  

Hazard	
  

Anything	
  with	
  a	
  potential	
  to	
  harm,	
  injure	
  or	
  damage	
  
	
   (Kerns	
  &	
  Ager,	
  2007)	
  human,	
  environmental	
  or	
  
wildlife	
  systems.	
  

Human-­‐wildlife	
  conflict	
  
(HWC)	
  

An	
  action	
  by	
  either	
  humans	
  or	
  wildlife	
  that	
  results	
  in	
  
	
   a	
  negative	
  effect,	
  realized	
  or	
  perceived,	
  upon	
  the	
  
other	
  (Conover,	
  2002).	
  

Management	
  interventions	
  

Methods	
  used	
  to	
  mitigate	
  human	
  wildlife	
  conflicts,	
  
which	
  include	
  direct	
  methods	
  that	
  are	
  designed	
  to	
  
reduce	
  the	
  frequency	
  and	
  severity	
  of	
  encounters	
  
	
  
between	
  people	
  and	
  wildlife	
  and	
  indirect	
  methods	
  
that	
  attempt	
  to	
  raise	
  human	
  tolerance	
  for	
  
encounters	
  (Treves	
  et	
  al.,	
  2009).	
  

Risk	
  

An	
  estimation	
  of	
  both	
  the	
  likelihood	
  of	
  a	
  hazard	
  and	
  
the	
  magnitude	
  and	
  character	
  of	
  the	
  negative	
  
	
  
consequences	
  of	
  that	
  hazard	
  given	
  that	
  it	
  occurs	
  
(Sjöberg,	
  2000a)	
  

Risk	
  assessment	
  

A	
  technical	
  estimation	
  of	
  the	
  probability	
  and	
  
	
   magnitude	
  of	
  consequences	
  related	
  to	
  a	
  given	
  
hazard	
  (Renn,	
  1992).	
  

Risk	
  perception	
  

	
  

Intuitive	
  judgments	
  about	
  a	
  hazard	
  made	
  by	
  
stakeholders	
  (Slovic,	
  1987)	
  

	
  
	
  

19	
  

Table	
  1.1(continued):	
  Definitions	
  of	
  research	
  concepts	
  and	
  
terminology	
  
Concept	
  

	
  	
   Definition	
  

Social	
  vulnerability	
  

The	
  likelihood	
  of	
  a	
  system's	
  exposure	
  to	
  and	
  ability	
  
to	
  adapt	
  to	
  a	
  hazard	
  based	
  on	
  the	
  demographic,	
  
	
   social	
  and/or	
  cultural	
  characteristics	
  of	
  the	
  system	
  
(adapted:	
  Cutter	
  et	
  al.,	
  2003;	
  Hogan	
  &	
  Marandola,	
  
2005).	
  	
  

Vulnerability	
  

A	
  system's	
  potential	
  for	
  a	
  loss	
  in	
  response	
  to	
  
exposure	
  to	
  a	
  hazard	
  (Cutter	
  et	
  al.,	
  2003)	
  and	
  the	
  
	
  
ability	
  to	
  recover	
  or	
  adapt	
  to	
  losses	
  (Schmidtlein	
  et	
  
al.,	
  2008).	
  

Vulnerability	
  perception	
  

A	
  judgment	
  of	
  likelihood	
  and	
  sensitivity	
  to	
  harm	
  
from	
  exposure	
  to	
  a	
  hazard,	
  which	
  may	
  include	
  
	
  
beliefs	
  about	
  the	
  system's	
  fragility,	
  social	
  or	
  physical	
  
vulnerability	
  (adapted:	
  Satterfield	
  et	
  al.,	
  2004).	
  	
  	
  

Wildlife	
  stakeholder	
  

Any	
  person	
  affected	
  by	
  or	
  will	
  affect	
  decisions	
  
related	
  to	
  wildlife	
  management;	
  includes	
  those	
  that	
  
benefit	
  or	
  are	
  negatively	
  effected	
  by	
  wildlife	
  and/or	
  
	
  	
  
those	
  that	
  have	
  a	
  vested	
  or	
  latent	
  interest	
  in	
  wildlife,	
  
wildlife	
  conservation	
  or	
  wildlife	
  management	
  
(Decker,	
  Brown	
  &	
  Siemer,	
  2001).	
  

	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

20	
  

Figure	
  1.1:	
  Conceptual	
  framework	
  of	
  stakeholders’	
  risk	
  perception	
  associated	
  with	
  human-­‐wildlife	
  conflicts.	
  
	
  
Demographic
characteristics of
the stakeholder !

HWC
Risks!

Judgments on the characteristics of the risk!

Risk management
strategy!

Acceptability!

Risk
perception!

Control!

Behavioral
intention!

Dread!
Environment!
Fairness!

Frequency!

Perception of
vulnerability!

Consequence!

	
  

	
  

21	
  

±
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Figure	
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  Map	
  of	
  the	
  Study	
  Area;	
  Caprivi,	
  Northeastern	
  Namibia.	
  	
  For	
  interpretation	
  of	
  the	
  references	
  to	
  color	
  in	
  this	
  and	
  all	
  
other	
  figures,	
  the	
  reader	
  is	
  referred	
  to	
  the	
  electronic	
  version	
  of	
  this	
  thesis.	
  
	
  
	
  	
  	
  
	
  
	
  
	
  
	
  
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Figure	
  1.3:	
  Map	
  of	
  Study	
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  Dzoti	
  (emerging)	
  and	
  Wuparo	
  (established),	
  in	
  Mudumu	
  South	
  Complex:	
  Caprivi,	
  
Namibia.	
  

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CHAPTER	
  2:	
  DOES	
  CONSERVANCY	
  ESTABLISHMENT	
  AFFECT	
  RESIDENTS’	
  HUMAN-­
WILDLIFE	
  CONFLICT	
  RELATED	
  RISK	
  PERCEPTIONS?	
  INSIGHTS	
  FROM	
  NAMIBIA.	
  	
  
2.1.	
  INTRODUCTION	
  
	
  

Negative	
  human-­‐wildlife	
  interactions	
  [i.e.,	
  human-­‐wildlife	
  conflicts	
  (HWCs)]	
  pose	
  

risks	
  to	
  human	
  livelihoods	
  and	
  wildlife	
  species	
  globally	
  and	
  have	
  been	
  the	
  subject	
  of	
  
numerous	
  studies	
  within	
  the	
  context	
  of	
  livelihood	
  development	
  and	
  wildlife	
  conservation	
  
(see	
  Hill,	
  2004;	
  Kissui,	
  2008;	
  Naughton-­‐Treves,	
  1997;	
  O’Connell-­‐Rodwell,	
  Rodwell,	
  Rice	
  &	
  
Hart,	
  2000).	
  	
  Practitioners	
  have	
  a	
  large	
  volume	
  of	
  best	
  practices	
  for	
  managing	
  HWCs	
  in	
  
myriad	
  contexts.	
  	
  Regardless	
  of	
  management	
  strategy,	
  species	
  involved,	
  or	
  context,	
  HWC	
  
management	
  commonly	
  aims	
  to	
  reduce	
  risks	
  to	
  both	
  people	
  and	
  wildlife.	
  	
  However,	
  even	
  
with	
  a	
  substantial	
  knowledge	
  base,	
  HWC	
  persists	
  and	
  continues	
  to	
  be	
  a	
  high	
  conservation	
  
and	
  development	
  priority	
  for	
  diverse	
  stakeholders	
  (Hill,	
  2004;	
  O’Connell	
  et	
  al.,	
  2000;	
  
Treves,	
  Wallace	
  &	
  White,	
  2009).	
  	
  Management	
  strategies	
  that	
  reduce	
  HWC-­‐related	
  risks	
  are	
  
of	
  particular	
  importance	
  in	
  landscapes	
  managed	
  under	
  community-­‐based	
  approaches	
  [i.e.,	
  
community-­‐based	
  natural	
  resource	
  management	
  (CBNRM)]	
  as	
  the	
  success	
  of	
  economic	
  
development	
  and	
  wildlife	
  conservation	
  initiatives	
  depend	
  on	
  coexistence	
  of	
  people	
  and	
  
wildlife.	
  	
  Some	
  scholars	
  have	
  suggested	
  that	
  because	
  the	
  outcomes	
  of	
  HWCs	
  are	
  ultimately	
  
rooted	
  in	
  human	
  perceptions,	
  actions,	
  and	
  reactions	
  (Manfredo	
  &	
  Dayer,	
  2004)	
  human	
  
dimensions	
  insight	
  about	
  HWC-­‐related	
  risks	
  is	
  an	
  essential	
  but	
  often	
  overlooked	
  part	
  of	
  the	
  
HWC	
  management	
  equation	
  (Treves,	
  Wallace,	
  Naughton-­‐Treves	
  &	
  Morales,	
  2006a).	
  	
  This	
  
research	
  aims	
  to	
  contribute	
  to	
  the	
  human	
  dimensions	
  knowledge	
  base	
  about	
  HWC-­‐related	
  
risks	
  in	
  CBNRM	
  systems.	
  
	
  

	
  

24	
  

2.2.	
  BACKGROUND	
  
2.2.1.	
  Community-­based	
  natural	
  resource	
  management.	
  
CBNRM	
  is	
  the	
  management	
  of	
  natural	
  resource	
  (e.g.,	
  wildlife,	
  forest	
  products)	
  by	
  
collectives	
  or	
  local	
  institutions	
  to	
  derive	
  local	
  benefits	
  (e.g.,	
  commercial,	
  subsistence	
  use)	
  
(Roe,	
  Nelson	
  &	
  Sandbrook,	
  2009).	
  	
  Theoretically,	
  the	
  primary	
  incentive	
  for	
  locals	
  to	
  change	
  
unsustainable	
  behaviors	
  (e.g.,	
  poaching)	
  hinges	
  on	
  the	
  ability	
  of	
  CBNRM	
  to	
  develop	
  and	
  
distribute	
  benefits	
  (Vaughan	
  &	
  Long,	
  2007).	
  	
  For	
  example,	
  using	
  the	
  case	
  of	
  wildlife,	
  
CBNRM	
  should	
  create	
  benefits	
  from	
  the	
  use	
  of	
  wildlife	
  (e.g.,	
  selling	
  trophy	
  animals)	
  that	
  
exceed	
  the	
  costs	
  of	
  living	
  with	
  wildlife	
  (e.g.,	
  HWC-­‐related	
  risks)	
  (Hoole,	
  2010).	
  	
  CBNRM	
  
systems	
  may	
  employ	
  a	
  suite	
  of	
  HWC	
  management	
  strategies,	
  such	
  as	
  compensation	
  
schemes	
  and	
  preventative	
  livestock	
  husbandry	
  practices,	
  to	
  reduce	
  livelihood	
  costs	
  
associated	
  with	
  living	
  with	
  wildlife.	
  	
  When	
  benefits	
  outweigh	
  costs,	
  CBNRM	
  regimes	
  may	
  
engender	
  pro-­‐conservation	
  attitudes	
  (i.e.,	
  greater	
  tolerance,	
  acceptance	
  and	
  conservation	
  
concern	
  for	
  wildlife)	
  among	
  stakeholders.	
  	
  	
  
CBNRM	
  has	
  been	
  used	
  as	
  a	
  conservation	
  tool	
  for	
  decades,	
  however	
  practitioners	
  and	
  
scholars	
  have	
  extensively	
  questioned	
  its	
  success	
  in	
  terms	
  of	
  providing	
  either	
  sustainable	
  
development	
  or	
  adequate	
  biodiversity	
  conservation	
  (Shackleton,	
  Willis,	
  Brown	
  &	
  Polunin,	
  
2010).	
  Additionally,	
  despite	
  the	
  fact	
  that	
  CBNRM	
  approaches	
  are	
  theorized	
  to	
  positively	
  
influence	
  local	
  attitudes	
  towards	
  conservation	
  initiatives,	
  empirical	
  evidence	
  about	
  the	
  
effects	
  of	
  CBNRM	
  schemes	
  on	
  stakeholders’	
  risk	
  perception	
  associated	
  with	
  HWC-­‐related	
  
risks	
  to	
  and	
  from	
  wildlife	
  is	
  scant	
  (see	
  Schumann,	
  Watson	
  &	
  Schumann,	
  2008).	
  	
  Although	
  
Schumann	
  et	
  al.	
  (2008)	
  found	
  that	
  farmers	
  who	
  were	
  members	
  of	
  a	
  commercial	
  
conservancy	
  (e.g.,	
  type	
  of	
  CBNRM	
  program	
  in	
  Namibia)	
  reported	
  greater	
  tolerance	
  for	
  

	
  

25	
  

carnivores	
  regardless	
  of	
  their	
  farming	
  enterprise	
  (e.g.,	
  livestock,	
  mixed	
  livestock/game),	
  
additional	
  research	
  is	
  needed	
  to	
  evaluate	
  whether	
  CBNRM	
  schemes	
  can	
  deliver	
  similar	
  
results	
  across	
  diverse	
  economic,	
  environmental	
  and	
  social	
  conditions,	
  and	
  stakes.	
  
Ideally,	
  CBNRM	
  initiatives	
  lower	
  stakeholders'	
  vulnerability	
  to	
  HWC-­‐related	
  risks	
  
and	
  increase	
  community	
  members'	
  ability	
  to	
  cope	
  with	
  the	
  costs	
  of	
  living	
  with	
  wildlife	
  
through	
  wildlife-­‐derived	
  benefits	
  (Naughton-­‐Treves,	
  1997).	
  	
  These	
  benefits	
  are	
  thought	
  to	
  
lower	
  wildlife	
  vulnerability	
  to	
  HWC	
  by	
  increasing	
  stakeholder	
  tolerance	
  of	
  wildlife	
  when	
  
HWC	
  occurs	
  (Schumann	
  et	
  al.,	
  2008)	
  and	
  reduce	
  stakeholders'	
  propensity	
  to	
  engage	
  in	
  
unsustainable	
  resource	
  use	
  (e.g.,	
  poaching)	
  (Robertson	
  &	
  Lawes,	
  2005).	
  	
  Understanding	
  
vulnerability,	
  an	
  individual's	
  sensitivity	
  and	
  ability	
  to	
  recover	
  from	
  losses	
  when	
  exposed	
  to	
  
a	
  hazard	
  (e.g.,	
  HWC)	
  (Cutter,	
  Boruff	
  &	
  Shirley,	
  2003),	
  requires,	
  in	
  part,	
  knowledge	
  about	
  the	
  
multitude	
  of	
  risks	
  that	
  stakeholders	
  and	
  wildlife	
  face	
  that	
  may	
  aggravate	
  sensitivity	
  to	
  a	
  
harmful	
  event	
  (Reid	
  &	
  Vogel,	
  2006)	
  such	
  as	
  HWC.	
  	
  Research	
  that	
  incorporates	
  local	
  
stakeholders’	
  perceptions	
  associated	
  with	
  multiple	
  risks	
  to	
  livelihoods	
  and	
  wildlife	
  can	
  aid	
  
in	
  understanding	
  local	
  vulnerability	
  to	
  specific	
  risks	
  (e.g.,	
  HWC)	
  (Reid	
  &	
  Vogel,	
  2006;	
  Smith,	
  
Barrett	
  &	
  Box,	
  2000;	
  Tschakert,	
  2007).	
  
	
  2.2.2.	
  Risk	
  perceptions.	
  	
  	
  	
  
Risk	
  perceptions	
  are	
  intuitive	
  judgments	
  made	
  by	
  stakeholders	
  (Slovic,	
  1987);	
  risk	
  
perceptions	
  can	
  influence	
  stakeholders’	
  risk-­‐related	
  decision-­‐making	
  (Gore,	
  Wilson,	
  
Siemer,	
  Hudenko,	
  Clarke,	
  Hart,	
  Maguire	
  &	
  Muter,	
  2009)	
  and	
  may	
  ultimately	
  influence	
  how	
  
individuals	
  think	
  and	
  behave	
  in	
  response	
  to	
  risks	
  (Baird,	
  Leslie	
  &	
  McCabe,	
  2009).	
  
Stakeholder	
  risk	
  perceptions	
  contribute	
  to	
  evaluating	
  trade-­‐offs	
  between	
  natural	
  resource	
  
management	
  alternatives	
  (Gore	
  et	
  al.,	
  2009)	
  and	
  may	
  influence	
  overall	
  stakeholder	
  support	
  

	
  

26	
  

for	
  management	
  actions	
  (Gore,	
  Knuth,	
  Curtis	
  &	
  Shanahan,	
  2006;	
  Knuth,	
  Stout,	
  Siemer,	
  
Decker	
  &	
  Stedman,	
  1992).	
  	
  The	
  value	
  of	
  risk	
  perception	
  research	
  in	
  characterizing	
  
stakeholder	
  attitudes	
  towards	
  wildlife,	
  HWC	
  and	
  conservation	
  initiatives	
  has	
  increasingly	
  
been	
  demonstrated	
  through	
  empirical	
  investigations	
  in	
  a	
  variety	
  of	
  contexts	
  (e.g.,	
  Baird	
  et	
  
al.,	
  2009;	
  Gore	
  et	
  al.,	
  2006;	
  Hill,	
  2004;	
  Knuth	
  et	
  al.,	
  1992;	
  LeBreton,	
  Prosser,	
  Tamoufe,	
  
Sateren,	
  Mpoudi-­‐Ngole	
  et	
  al.,	
  2006;	
  Muter,	
  Gore	
  &	
  Riley,	
  2009).	
  	
  	
  
Although	
  we	
  have	
  a	
  solid	
  understanding	
  of	
  factors	
  influencing	
  stakeholders'	
  risk	
  
perceptions	
  associated	
  with	
  HWC,	
  the	
  target	
  (i.e.,	
  the	
  subject	
  towards	
  which	
  the	
  conflict	
  
consequences	
  are	
  directed)	
  of	
  those	
  perceptions	
  has	
  always	
  been	
  people.	
  	
  There	
  is	
  a	
  lack	
  of	
  
understanding	
  about	
  factors	
  influencing	
  HWC	
  risk	
  perceptions	
  with	
  wildlife	
  as	
  the	
  target	
  
(see	
  McFarlane,	
  2005).	
  	
  Systematic	
  investigations	
  of	
  local	
  stakeholders’	
  perceptions	
  of	
  
HWC-­‐related	
  risk	
  to	
  wildlife,	
  within	
  a	
  CBNRM	
  context	
  or	
  otherwise,	
  are	
  largely	
  absent	
  from	
  
the	
  literature.	
  	
  A	
  question	
  of	
  interest	
  to	
  diverse	
  stakeholders	
  and	
  practitioners	
  is,	
  "How	
  do	
  
stakeholders	
  perceive	
  risks	
  to	
  wildlife	
  from	
  HWC?"	
  	
  Answering	
  this	
  question	
  is	
  important	
  
because	
  perceptions	
  of	
  risk	
  to	
  wildlife	
  could,	
  much	
  like	
  livelihood-­‐related	
  HWC	
  risk	
  
perceptions,	
  influence	
  stakeholders’	
  responses	
  to	
  HWC	
  incidents	
  (Hill,	
  2004)	
  and	
  influence	
  
preferences	
  for	
  overall	
  policy	
  and	
  management	
  (McFarlane,	
  2005)	
  of	
  HWC;	
  however,	
  they	
  
may	
  do	
  so	
  in	
  different	
  ways.	
  
The	
  literature	
  about	
  stakeholders’	
  perceptions	
  of	
  HWC-­‐related	
  risks	
  to	
  livelihoods	
  
and	
  wildlife	
  relative	
  to	
  non-­‐HWC	
  related	
  risks	
  is	
  nebulous	
  and	
  ill	
  defined	
  (see	
  Baird	
  et	
  al.,	
  
2009).	
  	
  This	
  is	
  problematic	
  because	
  non-­‐HWC	
  related	
  risks	
  may	
  increase	
  both	
  people's	
  and	
  
wildlife's	
  vulnerability	
  to	
  HWCs.	
  	
  Indeed,	
  risks	
  are	
  not	
  experienced	
  as	
  discrete	
  entities	
  
(Baird	
  et	
  al.,	
  2009)	
  and	
  exposure	
  to	
  one	
  risk	
  may	
  aggravate	
  sensitivity	
  to	
  or	
  lessen	
  one's	
  

	
  

27	
  

ability	
  to	
  adapt	
  to	
  another	
  risk	
  (Tschakert,	
  2007;	
  Reid	
  &	
  Vogel,	
  2006).	
  	
  Increasing	
  our	
  
understanding	
  about	
  the	
  broader	
  context	
  in	
  which	
  HWC-­‐related	
  risks	
  occur	
  and	
  the	
  
influence	
  of	
  CBNRM	
  schemes	
  on	
  stakeholders’	
  HWC-­‐related	
  risk	
  perceptions	
  can	
  inform	
  
HWC	
  theory	
  and	
  practice.	
  	
  Accordingly,	
  I	
  set	
  two	
  research	
  objectives:	
  1)	
  investigate	
  the	
  
influence	
  of	
  CBNRM	
  on	
  perceptions	
  of	
  HWC-­‐related	
  risks	
  and	
  vulnerability;	
  and	
  2)	
  
contextualize	
  HWC-­‐related	
  risks	
  relative	
  to	
  other	
  livelihood	
  and	
  wildlife–related	
  risks,	
  
according	
  to	
  the	
  perceptions	
  of	
  HWC-­‐vulnerable	
  stakeholders.	
  	
  
2.2.3.	
  Namibian	
  conservancies.	
  
In	
  1996,	
  Namibia	
  adopted	
  a	
  communal	
  conservancy-­‐based	
  approach	
  to	
  natural	
  
resource	
  management.	
  	
  Key	
  features	
  of	
  the	
  Namibian	
  conservancy	
  system	
  include:	
  1)	
  
collaboration	
  between	
  government	
  agencies,	
  national	
  non-­‐governmental	
  organizations	
  and	
  
rural	
  communities	
  living	
  on	
  communal	
  land	
  (Stuart-­‐Hill,	
  Diggle,	
  Munali,	
  Tagg	
  &	
  Ward,	
  
2005);	
  2)	
  devolved	
  rights	
  over	
  natural	
  resources,	
  including	
  wildlife,	
  to	
  local	
  communities	
  
(Barnes,	
  MacGregor	
  &	
  Weaver,	
  2002);	
  3)	
  a	
  legislative	
  basis	
  for	
  consumptive	
  wildlife	
  
utilization	
  (e.g.,	
  subsistence	
  and	
  commercial	
  hunting);	
  and	
  4)	
  codified	
  HWC	
  management	
  
procedures	
  (Ministry	
  of	
  Environment	
  &	
  Tourism	
  (MET),	
  2009).	
  	
  
Namibia's	
  conservancies	
  are	
  often	
  considered	
  successful	
  CBNRM	
  regimes	
  in	
  that	
  
they	
  simultaneously	
  conserve	
  natural	
  resources	
  and	
  preserve	
  livelihoods	
  (Hoole	
  &	
  Berkes,	
  
2010).	
  	
  Residents	
  of	
  Namibian	
  communal	
  conservancies	
  directly	
  benefit	
  from	
  the	
  
sustainable	
  use	
  of,	
  and	
  decisions	
  about,	
  wildlife	
  resources	
  (Barnes	
  et	
  al.,	
  2002).	
  	
  Literature	
  
on	
  Namibia’s	
  conservancies	
  often	
  anecdotally	
  assert	
  that	
  conservation	
  success	
  is,	
  in	
  large	
  
part,	
  due	
  to	
  the	
  positive	
  effects	
  of	
  conservancies	
  on	
  local	
  attitudes	
  towards	
  wildlife	
  (e.g.,	
  
Weaver	
  &	
  Skyer,	
  2005).	
  	
  While	
  many	
  Namibian	
  conservancies	
  report	
  increased	
  wildlife	
  

	
  

28	
  

populations	
  (Nott	
  &	
  Jacobsohn,	
  2004),	
  many	
  also	
  report	
  increased	
  frequencies	
  and	
  
magnitudes	
  of	
  HWC	
  (Jones	
  &	
  Barnes,	
  2006;	
  MET,	
  2009).	
  	
  In	
  2009,	
  in	
  response	
  to	
  increasing	
  
reports	
  of	
  HWC	
  across	
  the	
  country,	
  the	
  federal	
  government	
  established	
  a	
  legal	
  framework	
  
for	
  HWC	
  management	
  (MET,	
  2009).	
  	
  The	
  legislation	
  stipulated	
  that	
  HWC	
  management	
  and	
  
financial	
  compensation	
  to	
  HWC-­‐affected	
  citizens	
  residing	
  in	
  conservancies	
  was	
  the	
  
responsibility	
  of	
  the	
  conservancies	
  (MET,	
  2009).	
  	
  
2.3.	
  METHODS	
  	
  
2.3.1.	
  Study	
  location	
  
Two	
  conservancies	
  in	
  East	
  Caprivi,	
  Wuparo	
  (hereafter	
  established	
  3)	
  and	
  Dzoti	
  
(hereafter	
  emerging),	
  were	
  selected	
  for	
  this	
  research	
  based	
  on	
  the:	
  1)	
  recommendation	
  of	
  
local	
  and	
  regional	
  nongovernmental	
  organizations	
  with	
  a	
  long-­‐term	
  presence	
  in	
  the	
  region;	
  
2)	
  permission	
  of	
  local	
  and	
  relevant	
  traditional	
  authorities;	
  3)	
  willingness	
  of	
  conservancies	
  
to	
  participate;	
  4)	
  variation	
  in	
  conservancy	
  management	
  structure	
  and	
  function;	
  and	
  5)	
  
comparability	
  of	
  conservancies	
  based	
  on	
  similar	
  habitat	
  types,	
  wildlife	
  species	
  
composition,	
  and	
  presence	
  of	
  HWC	
  (Table	
  2.1).	
  	
  
2.3.2.	
  Data	
  Collection	
  	
  
This	
  research	
  used	
  a	
  case	
  study	
  approach	
  (Yin,	
  2009),	
  focus	
  groups,	
  and	
  semi-­‐
structured	
  interviews	
  to	
  achieve	
  the	
  objectives.	
  	
  Both	
  objectives	
  were	
  addressed	
  using	
  a	
  
multidirectional	
  approach	
  consistent	
  with	
  the	
  notion	
  that	
  wildlife	
  is	
  both	
  a	
  source	
  and	
  
recipient	
  of	
  the	
  negative	
  consequences	
  of	
  HWC-­‐related	
  risks.	
  	
  An	
  identical	
  research	
  
protocol	
  was	
  implemented	
  in	
  each	
  conservancy.	
  	
  Six	
  local	
  research	
  assistants	
  were	
  hired	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
3	
  Wuparo	
  was	
  established	
  in	
  1999	
  and	
  Dzoti	
  was	
  established	
  in	
  2009,	
  after	
  research	
  
concluded.	
  	
  

	
  

29	
  

based	
  on	
  the	
  following	
  criteria:	
  (1)	
  fluent	
  in	
  English,	
  Lozi,	
  and/or	
  Sheyeyi;	
  (2)	
  completed	
  
secondary	
  school;	
  (3)	
  were	
  not	
  members	
  of	
  the	
  conservancy	
  committees	
  or	
  traditional	
  
authority;	
  and	
  (4)	
  agreed	
  to	
  work	
  the	
  entire	
  duration	
  of	
  research	
  activities.	
  	
  All	
  research	
  
assistants	
  participated	
  in	
  a	
  day-­‐long	
  training	
  session	
  before	
  data	
  collection	
  commenced	
  
and	
  in	
  accordance	
  with	
  MSU	
  Human	
  Research	
  Protection	
  Program	
  requirements.	
  	
  
Focus	
  group	
  and	
  interview	
  participants	
  were	
  solicited	
  from	
  each	
  of	
  the	
  village	
  zones	
  
(i.e.,	
  distinct	
  residential	
  areas)	
  in	
  proportion	
  to	
  the	
  respective	
  village’s	
  population	
  using	
  a	
  
random	
  sampling	
  technique	
  (i.e.,	
  cluster	
  sampling	
  technique	
  with	
  probability	
  
proportionate	
  to	
  size)	
  (Bernard,	
  2006).	
  	
  Given	
  that	
  there	
  were	
  no	
  reliable	
  lists	
  (e.g.,	
  
property	
  tax	
  records)	
  of	
  residents	
  in	
  the	
  conservancies,	
  this	
  technique	
  entailed	
  identifying	
  
population	
  clusters	
  (i.e.,	
  village	
  zones)	
  and	
  then	
  assigning	
  a	
  given	
  number	
  of	
  interviews	
  to	
  
each	
  cluster	
  based	
  on	
  their	
  population	
  size	
  relative	
  to	
  other	
  clusters	
  (Bernard,	
  2006).	
  	
  All	
  
village	
  zones	
  within	
  each	
  conservancy	
  were	
  sampled.	
  	
  Convenience	
  sampling	
  was	
  used	
  
within	
  each	
  village	
  zone	
  (Bernard,	
  2006).	
  	
  This	
  sampling	
  protocol	
  facilitated	
  inferential	
  
statistical	
  analysis	
  that	
  could	
  be	
  generalized	
  to	
  all	
  residents	
  of	
  the	
  study	
  conservancies.	
  
However,	
  results	
  herein	
  may	
  not	
  be	
  generalized	
  to	
  the	
  regional	
  or	
  national	
  conservancy	
  
level.	
  	
  
Interview	
  and	
  focus	
  group	
  participants	
  were	
  all	
  permanent	
  residents	
  of	
  their	
  
respective	
  conservancies	
  and	
  18	
  years	
  of	
  age	
  or	
  older;	
  ethnic	
  affiliation,	
  educational	
  
attainment,	
  or	
  socio-­‐economic	
  status	
  were	
  not	
  prerequisites	
  for	
  participation.	
  	
  Gender	
  
parity	
  was	
  maintained	
  by	
  specifying	
  an	
  allotted	
  number	
  of	
  participants	
  to	
  each	
  gender	
  
within	
  each	
  cluster	
  sampled.	
  	
  Only	
  one	
  participant	
  per	
  household	
  was	
  eligible	
  to	
  
participate.	
  	
  Participation	
  in	
  one	
  research	
  activity	
  (interview/focus	
  group)	
  did	
  not	
  exclude	
  

	
  

30	
  

participation	
  in	
  the	
  other.	
  	
  However,	
  interview	
  and	
  focus	
  group	
  participants	
  were	
  
independently	
  selected	
  using	
  the	
  above-­‐defined	
  sampling	
  protocols.	
  
Focus	
  Groups.	
  In	
  each	
  conservancy,	
  the	
  lead	
  researcher	
  and	
  six	
  research	
  assistants	
  
facilitated	
  a	
  two-­‐day	
  focus	
  group	
  (see	
  Appendix	
  A	
  for	
  protocol).	
  	
  Focus	
  group	
  participants	
  
were	
  divided	
  into	
  three	
  groups	
  comprised	
  of:	
  1)	
  male	
  residents;	
  2)	
  female	
  residents;	
  and	
  3)	
  
local	
  environmental	
  decision-­‐makers	
  of	
  either	
  gender	
  to	
  promote	
  a	
  non-­‐threatening	
  and	
  
permissive	
  environment	
  for	
  dialogue	
  (Smith	
  et	
  al.,	
  2000)	
  and	
  help	
  diffuse	
  power	
  
differentials	
  between	
  participants	
  (Morgan,	
  1993).	
  	
  	
  
	
  

The	
  purpose	
  of	
  the	
  focus	
  group	
  was	
  to	
  conduct	
  participatory	
  risk	
  ranking	
  and	
  

scoring	
  (PRRS)	
  activities	
  (Quinn,	
  Huby,	
  Kiwasila	
  &	
  Lovett,	
  2003;	
  Smith	
  et	
  al.,	
  2000;	
  
Tschakert,	
  2007).	
  	
  During	
  the	
  four-­‐step	
  PRRS	
  process,	
  the	
  participants	
  first	
  individually	
  
free-­‐listed	
  risks	
  associated	
  with	
  a	
  target.	
  Second,	
  participants	
  assigned	
  ordinal	
  values	
  to	
  
rank	
  the	
  importance	
  of	
  each	
  risk.	
  	
  Third,	
  participants	
  rated	
  the	
  severity	
  of	
  each	
  risk	
  on	
  a	
  
five-­‐point	
  Likert-­‐type	
  scale	
  (1=not	
  severe,	
  5=life	
  threatening).	
  	
  Fourth,	
  within	
  their	
  groups,	
  
participants	
  shared	
  and	
  discussed	
  their	
  results,	
  identifying	
  what,	
  if	
  any,	
  risks	
  were	
  related	
  
to	
  HWC.	
  	
  The	
  PRRS	
  process	
  was	
  completed	
  independently	
  for	
  two	
  risk	
  targets:	
  local	
  
livelihoods	
  and	
  conservancy	
  wildlife.	
  	
  	
  
Semi-­structured	
  Interviews.	
  Semi-­‐structured	
  interviews	
  (Bernard,	
  2006)	
  were	
  
conducted	
  with	
  conservancy	
  residents	
  concurrently	
  with	
  focus	
  group	
  activities.	
  	
  Interview	
  
questions	
  elicited	
  information	
  related	
  to	
  non-­‐demographic	
  and	
  demographic	
  factors	
  found	
  
to	
  influence	
  risk	
  perception	
  and	
  vulnerability	
  related	
  to	
  HWC	
  (see	
  Appendix	
  B	
  for	
  interview	
  
guide).	
  Most	
  questions	
  were	
  measured	
  using	
  four-­‐point	
  visual	
  Likert-­‐type	
  scales	
  (0	
  =	
  no	
  
risk,	
  1	
  =	
  low,	
  2	
  =	
  medium,	
  3	
  =	
  high),	
  which	
  have	
  been	
  shown	
  to	
  lessen	
  culturally-­‐driven	
  bias	
  

	
  

31	
  

towards	
  neutral	
  or	
  extreme	
  response	
  categories	
  (Reid,	
  1990;	
  Roster,	
  Albaum	
  &	
  Rogers,	
  
2006)	
  and	
  are	
  appropriate	
  in	
  situations	
  of	
  low	
  literacy	
  (Chachamovich,	
  Fleck	
  &	
  Power,	
  
2009).	
  Likert-­‐type	
  scales	
  were	
  depicted	
  visually	
  to	
  aid	
  participant	
  interpretation	
  of	
  scales	
  
in	
  instances	
  of	
  low	
  literacy	
  (Appendix	
  C).	
  
	
  

I	
  used	
  seven	
  constructs	
  to	
  measure	
  non-­‐demographic	
  factors	
  that	
  influence	
  risk	
  

perception:	
  dread,	
  environment,	
  frequency,	
  control	
  (Gore,	
  Knuth,	
  Curtis	
  &	
  Shanahan,	
  
2007),	
  risk	
  fairness	
  (McDaniels,	
  Axelrod,	
  Cavanagh	
  &	
  Slovic,	
  1997;	
  Schmidt	
  &	
  Wei,	
  2006),	
  
acceptability,	
  and	
  consequence	
  (Slovic,	
  1987).	
  	
  Each	
  construct	
  was	
  queried	
  using	
  at	
  least	
  
one	
  close-­‐ended	
  question	
  designed	
  to	
  measure	
  respondent’s	
  attitude	
  and	
  across	
  three	
  risk	
  
targets	
  (i.e.,	
  general	
  risk	
  from	
  HWC,	
  risk	
  to	
  livelihoods,	
  risk	
  to	
  wildlife).	
  	
  Risk	
  perceptions	
  to	
  
local	
  livelihoods	
  were	
  defined	
  as	
  risks	
  posed	
  to	
  individual	
  livelihoods	
  or	
  immediate	
  familial	
  
relations,	
  while	
  risks	
  to	
  wildlife	
  were	
  defined	
  as	
  risks	
  posed	
  to	
  wildlife	
  within	
  the	
  
conservancy.	
  	
  Perceived	
  HWC	
  vulnerability	
  was	
  measured	
  as	
  a	
  function	
  of	
  exposure	
  risk	
  
(i.e.,	
  frequency	
  of	
  personal	
  exposure	
  to	
  HWC)	
  and	
  perceived	
  consequences	
  (i.e.,	
  anticipated	
  
losses	
  associated	
  with	
  exposure	
  to	
  a	
  hazard)	
  of	
  HWC-­‐related	
  risks	
  (see	
  Nathan,	
  2008;	
  
Satterfield,	
  Mertz	
  &	
  Slovic,	
  2004).	
  	
  	
  	
  
Five	
  demographic	
  variables	
  were	
  queried	
  based	
  on	
  Cutter	
  et	
  al.	
  (2003),	
  Hill	
  (2004),	
  
Naughton-­‐Treves	
  (1997)	
  and	
  Ogra	
  (2008):	
  age	
  (years),	
  decision-­‐making	
  authority	
  
(dichotomous),	
  education	
  (12	
  ordinal	
  categories),	
  gender	
  (dichotomous),	
  and	
  resource	
  
wealth	
  (agricultural,	
  land	
  and	
  livestock	
  holdings).	
  	
  Conservancy	
  status	
  (dichotomous)	
  was	
  
recorded	
  and	
  two	
  HWC	
  deterrence	
  behaviors,	
  actively	
  guarding	
  crops	
  and/or	
  livestock	
  
against	
  wildlife	
  damage,	
  were	
  also	
  queried.	
  	
  	
  	
  

	
  

32	
  

Event	
  Books.	
  The	
  Event	
  Book	
  system	
  is	
  the	
  Namibian	
  conservancy-­‐based	
  monitoring	
  
program	
  used	
  to	
  monitor	
  stochastic	
  events	
  (e.g.,	
  problem	
  animal	
  incidents,	
  poaching)	
  
(Stuart-­‐Hill	
  et	
  al.,	
  2005).	
  	
  Event	
  Book	
  data	
  represent	
  reported	
  HWC	
  incident	
  rates	
  and	
  were	
  
used	
  to	
  aid	
  interpretation	
  of	
  conservancy	
  effects	
  on	
  HWC-­‐related	
  risks	
  and	
  vulnerability	
  
perceptions.	
  	
  The	
  date,	
  species,	
  location,	
  incident	
  type,	
  specified	
  damage	
  and	
  quantity	
  of	
  
damages	
  are	
  recorded	
  for	
  each	
  reported	
  HWC	
  incident.	
  	
  Event	
  Book	
  data	
  between	
  2003	
  
and	
  2008	
  were	
  digitally	
  photographed	
  and	
  transcribed	
  with	
  permission	
  of	
  relevant	
  
conservancy	
  authorities.	
  	
  
2.3.3.	
  Data	
  Analysis	
  
Focus	
  Groups.	
  An	
  iterative	
  process	
  guided	
  coding	
  and	
  analysis	
  of	
  individual	
  
participants'	
  free-­‐listed,	
  ranked	
  and	
  scored	
  risks	
  generated	
  during	
  the	
  PRRS	
  activity	
  
(Bernard,	
  2006).	
  	
  First,	
  I	
  reviewed	
  all	
  text	
  produced	
  during	
  the	
  free-­‐listing	
  stage	
  to	
  
generate	
  a	
  wide	
  range	
  of	
  response	
  categories	
  (Saldaña,	
  2009).	
  	
  Next,	
  I	
  compared	
  responses	
  
within	
  categories	
  and	
  created	
  a	
  coding	
  protocol	
  to	
  systematically	
  transcribe	
  each	
  risk	
  into	
  
an	
  exclusive	
  categorical	
  variable	
  (Bernard,	
  2006).	
  	
  Then,	
  I	
  coded	
  all	
  risks	
  according	
  to	
  the	
  
protocol,	
  revised	
  protocol	
  rules	
  where	
  appropriate,	
  and	
  conducted	
  a	
  final	
  iteration	
  of	
  
review	
  coding	
  to	
  validate	
  findings	
  (Saldaña,	
  2009)	
  (Appendix	
  D).	
  	
  Three	
  HWC	
  risk	
  themes	
  
were	
  generated	
  based	
  on	
  participant	
  descriptions:	
  direct,	
  indirect	
  and	
  non-­‐HWC.	
  	
  Direct	
  
HWCs	
  included	
  conflicts	
  with	
  unambiguous	
  negative	
  outcomes	
  for	
  humans	
  or	
  wildlife	
  (e.g.,	
  
crop	
  damage,	
  poaching),	
  while	
  indirect	
  HWCs	
  included	
  conflicts	
  with	
  ambiguous	
  outcomes	
  
(e.g.,	
  habitat	
  alteration,	
  increased	
  human-­‐wildlife	
  interaction).	
  	
  Non-­‐HWC	
  related	
  threats	
  
included	
  risks	
  not	
  mediated	
  through	
  human-­‐wildlife	
  interactions	
  (HWI)	
  such	
  as	
  local	
  
climate	
  (e.g.,	
  drought,	
  flood).	
  	
  

	
  

33	
  

I	
  adapted	
  statistical	
  methods	
  from	
  Tschakert	
  (2007)	
  to	
  analyze	
  PRRS	
  data.	
  	
  I	
  
calculated	
  an	
  incident	
  index	
  (I),	
  importance	
  index	
  (P),	
  joint	
  risk	
  index	
  (R)	
  and	
  severity	
  
index	
  (S)	
  for	
  each	
  livelihood	
  and	
  wildlife-­‐related	
  risk.	
  	
  The	
  incident	
  index	
  (I),	
  ranging	
  from	
  
0	
  to	
  1,	
  is	
  the	
  proportion	
  of	
  participants	
  that	
  identified	
  a	
  particular	
  risk.	
  The	
  importance	
  
index	
  (P),	
  which	
  also	
  ranges	
  from	
  0	
  to	
  1	
  (1=highest	
  importance),	
  reflects	
  the	
  ordinal	
  rank	
  
that	
  participants	
  assigned	
  to	
  a	
  particular	
  risk	
  in	
  relation	
  to	
  the	
  total	
  number	
  of	
  risks	
  listed,	
  
where	
  r	
  is	
  the	
  rank	
  and	
  n	
  the	
  total	
  number	
  of	
  threats	
  identified	
  by	
  that	
  participant:	
  	
  
	
  

# (r "1) &
Pj = %
( ) ("1) +1
$ (n "1) '

	
  

!

	
  The	
  joint	
  risk	
  index	
  (Rj)	
  represents	
  the	
  most	
  critical	
  risk	
  and	
  is	
  a	
  function	
  of	
  a	
  risk’s	
  
average	
  incident	
  index	
  score	
  (Ij)	
  and	
  average	
  importance	
  index	
  score	
  (Pj);	
  it	
  ranges	
  from	
  0	
  

!

to	
  1	
  (1=most	
  critical)	
  and	
  is	
  calculated	
  Rj=	
  Ij/	
  (2-­‐Pj).	
  	
  The	
  severity	
  index	
  (Sj),	
  represents	
  the	
  
mean	
  severity	
  score	
  assigned	
  to	
  each	
  risk	
  by	
  participants	
  that	
  mentioned	
  that	
  risk	
  and	
  
ranges	
  from	
  0	
  to	
  5.	
  Mean	
  incidence	
  (Ij),	
  importance	
  (Pj),	
  joint	
  risk	
  (Rj),	
  and	
  severity	
  (Sj)	
  
index	
  scores	
  were	
  calculated	
  for	
  each	
  conservancy.	
  	
  
	
  	
  

Semi-­structured	
  Interview.	
  	
  Responses	
  from	
  four-­‐point	
  Likert-­‐type	
  scales	
  (0=no	
  risk;	
  

1=	
  low	
  risk;	
  2=	
  medium	
  risk	
  and;	
  3=high	
  risk)	
  were	
  recoded	
  as	
  dichotomous	
  variables	
  
(1=low	
  risk;	
  2=high	
  risk).	
  	
  All	
  variables	
  were	
  cross-­‐tabulated	
  to	
  assess	
  the	
  percentage	
  of	
  
positive	
  (yes	
  or	
  high)	
  responses	
  within	
  each	
  conservancy	
  and	
  Pearson	
  chi-­‐square	
  tests	
  
were	
  performed	
  to	
  test	
  for	
  statistically	
  significant	
  differences	
  between	
  the	
  conservancies	
  
(Vaske,	
  2008).	
  	
  Binary	
  logistic	
  regression	
  	
  (p	
  ≤	
  0.05)	
  was	
  used	
  to	
  calculate	
  the	
  odds	
  of	
  
positive	
  responses	
  in	
  the	
  established	
  conservancy	
  compared	
  to	
  the	
  emerging	
  conservancy	
  

	
  

34	
  

(Schumann	
  et	
  al.,	
  2008).	
  	
  Conservancy	
  membership	
  was	
  set	
  as	
  the	
  independent	
  variable	
  in	
  
all	
  analysis	
  and	
  the	
  emerging	
  conservancy	
  served	
  as	
  the	
  reference	
  group.	
  	
  
Summative	
  scales	
  were	
  created	
  using	
  multiple	
  questions	
  in	
  the	
  survey	
  conceptually	
  
related	
  to	
  dread	
  (DREAD),	
  frequency	
  (FREQ),	
  and	
  consequences	
  (CONSQ)	
  of	
  HWC	
  for	
  
livelihood	
  and	
  wildlife	
  risk	
  targets.	
  	
  Cronbach’s	
  alpha	
  was	
  calculated	
  as	
  a	
  measure	
  of	
  
internal	
  consistency	
  for	
  all	
  summative	
  scales	
  related	
  to	
  concepts	
  of	
  dread,	
  frequency	
  and	
  
consequence;	
  a	
  value	
  of	
  0.60	
  or	
  higher	
  was	
  considered	
  satisfactory	
  (Vaske,	
  2008).	
  	
  
Multiplicative	
  scales	
  were	
  created	
  for	
  perceived	
  vulnerability	
  to	
  livelihoods	
  (VULLH)	
  and	
  
wildlife	
  (VULWL)	
  by	
  calculating	
  a	
  respondent’s	
  mean	
  index	
  scores	
  for	
  frequency	
  and	
  
consequence	
  question	
  responses.	
  	
  Scales	
  for	
  perceived	
  risk	
  to	
  livelihoods	
  (RISKLH)	
  and	
  
wildlife	
  (RISKWL)	
  were	
  created	
  by	
  multiplying	
  the	
  mean	
  index	
  scores	
  for	
  dread	
  and	
  
vulnerability.	
  	
  A	
  wealth	
  score,	
  representing	
  a	
  per	
  capita	
  wealth	
  measure,	
  was	
  developed	
  
based	
  on	
  Baird	
  et	
  al.	
  (2009)	
  and	
  calculated	
  as	
  a	
  function	
  of	
  a	
  household’s	
  livestock	
  assets	
  
and	
  size	
  of	
  agricultural	
  land	
  holdings	
  divided	
  by	
  the	
  total	
  number	
  of	
  people	
  in	
  the	
  
household	
  4.	
  	
  	
  
Linear	
  [Ordinary	
  least	
  squares	
  (OLS)]	
  regression	
  5	
  was	
  used	
  to:	
  1)	
  assess	
  how	
  well	
  
conservancy	
  status	
  predicted	
  the	
  resulting	
  dread,	
  vulnerability	
  and	
  risk	
  indices;	
  and	
  2)	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
4	
  Livestock	
  and	
  agricultural	
  land	
  values	
  (price/hectare)	
  were	
  calculated	
  using	
  the	
  
Namibian	
  Ministry	
  of	
  Environment	
  and	
  Tourism’s	
  (MET)	
  payment	
  scheme	
  for	
  livestock	
  and	
  
2009	
  crop	
  damage	
  estimates	
  published	
  in	
  the	
  Human	
  Wildlife	
  Self	
  Reliance	
  Scheme	
  (MET,	
  
2009).	
  Price	
  for	
  fowl,	
  not	
  covered	
  in	
  compensation	
  payments,	
  was	
  determined	
  by	
  local	
  
prices	
  during	
  field	
  season,	
  July-­‐September	
  2009.	
  
5	
  To	
  assess	
  the	
  appropriateness	
  of	
  OLS	
  regression,	
  I	
  checked	
  the	
  distribution	
  of	
  variables	
  

for	
  normality	
  (skewness),	
  examined	
  residual	
  plots	
  to	
  check	
  for	
  heteroscedasticity	
  and	
  
	
  

35	
  

control	
  for	
  confounding	
  predictors	
  theoretically	
  linked	
  to	
  risk	
  perceptions	
  (Vaske,	
  2008).	
  	
  
Independent	
  variables	
  in	
  the	
  model	
  included	
  demographic	
  factors:	
  	
  (1)	
  conservancy	
  status	
  
(1=established,	
  2	
  =	
  emerging);	
  (2)	
  education	
  (12	
  ordinal	
  categories);	
  (3)	
  membership	
  in	
  
local	
  environmental	
  decision-­‐making	
  body	
  (0=	
  no;	
  1=	
  yes);	
  (4)	
  respondent’s	
  gender	
  
(0=male;	
  1=female);	
  (5)	
  respondents	
  age	
  (in	
  years);	
  and	
  (6)	
  respondent’s	
  wealth	
  (index	
  
score).	
  	
  Pearson	
  r	
  tests	
  were	
  used	
  to	
  diagnose	
  multicollinearity;	
  values	
  greater	
  than	
  0.7	
  
were	
  considered	
  correlated	
  (Vaske,	
  2008).	
  Independent	
  variables	
  were	
  tested	
  for	
  entry	
  
into	
  the	
  model	
  at	
  p	
  ≤	
  0.05	
  and	
  removal	
  from	
  the	
  model	
  at	
  p	
  ≥	
  0.10	
  using	
  a	
  forward	
  stepwise	
  
procedure	
  (Vaske,	
  2008).	
  	
  	
  
Event	
  Book.	
  	
  Reported	
  HWC	
  incidents	
  were	
  analyzed	
  using	
  a	
  series	
  of	
  two-­‐sample	
  
independent	
  t-­‐tests	
  for	
  equality	
  of	
  the	
  means	
  between	
  conservancies	
  based	
  on	
  six	
  years	
  
(2003-­‐2008)	
  of	
  data	
  collected	
  on	
  crop	
  damage,	
  livestock	
  depredation	
  and	
  fatal	
  human	
  
attacks.	
  Additionally,	
  t-­tests	
  were	
  performed	
  on	
  the	
  total	
  HWC	
  incidents,	
  per	
  capita	
  HWC	
  
incidents	
  and	
  per	
  area	
  (km2)	
  HWC	
  incidents.	
  	
  A	
  Levene’s	
  test	
  was	
  used	
  to	
  test	
  for	
  the	
  
equality	
  of	
  variances	
  (Vaske,	
  2008).	
  	
  All	
  data	
  was	
  analyzed	
  using	
  PSAW	
  18	
  (SPSS	
  Inc.,	
  
2009).	
  	
  The	
  methods	
  for	
  this	
  research	
  were	
  approved	
  for	
  the	
  duration	
  of	
  the	
  project	
  by	
  the	
  
Michigan	
  State	
  University	
  (MSU)	
  Committee	
  on	
  Human	
  Subjects,	
  Protocol	
  ID#	
  X09-­‐443.	
  	
  
2.4.	
  RESULTS	
  
Fifty	
  stakeholders	
  (established	
  conservancy	
  =	
  30;	
  emerging	
  conservancy	
  =	
  20)	
  participated	
  
in	
  PRRS	
  activities	
  related	
  to	
  livelihoods.	
  Forty-­‐eight	
  stakeholders	
  (established	
  =	
  31;	
  
emerging	
  =	
  17)	
  participated	
  in	
  PRRS	
  activities	
  related	
  to	
  wildlife.	
  	
  Focus	
  group	
  participants	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
performed	
  a	
  Durbin-­‐Watson	
  test	
  for	
  independence	
  (Norušis,	
  2010).	
  	
  Non-­‐normally	
  
distributed	
  variables	
  were	
  log-­‐transformed.	
  

	
  

36	
  

ranged	
  in	
  educational	
  background	
  from	
  no	
  formal	
  schooling	
  to	
  college	
  educated,	
  age	
  (18-­‐
60+	
  years),	
  and	
  all	
  participated	
  in	
  some	
  form	
  of	
  subsistence	
  based	
  activities	
  or	
  rural	
  
industries	
  (e.g.,	
  artisanal	
  fisheries,	
  vegetable	
  farming,	
  thatch	
  roof	
  harvesting).	
  	
  A	
  total	
  of	
  76	
  
local	
  stakeholders	
  (emerging=	
  41;	
  established=	
  35)	
  were	
  interviewed.	
  	
  Demographic	
  
information	
  was	
  collected	
  from	
  interview	
  participants	
  (Appendix	
  E).	
  	
  Interview	
  
participants	
  ranged	
  in	
  formal	
  education	
  from	
  no	
  school	
  to	
  college	
  educated,	
  age	
  (18-­‐88),	
  
and	
  all	
  participated	
  in	
  some	
  form	
  of	
  subsistence-­‐based	
  activity	
  or	
  rural	
  industry.	
  	
  	
  
2.4.1.	
  Effect	
  of	
  conservancy	
  status	
  on	
  risk	
  and	
  vulnerability	
  perceptions.	
  	
  	
  
Livelihoods.	
  Emerging	
  and	
  established	
  conservancy	
  participants	
  differed	
  in	
  their	
  
perceptions	
  of	
  which	
  HWC-­‐risks	
  were	
  the	
  most	
  critical	
  and	
  severe	
  to	
  livelihoods.	
  	
  Emerging	
  
conservancy	
  participants	
  rated	
  crop	
  damage	
  and	
  livestock	
  loss	
  as	
  the	
  most	
  critical	
  risks;	
  
socio-­‐cultural	
  insecurity	
  and	
  habitat	
  modification	
  were	
  rated	
  as	
  the	
  most	
  severe	
  (Table	
  
2.3).	
  	
  Established	
  conservancy	
  participants	
  rated	
  poor	
  human	
  health	
  and	
  financial	
  
insecurity	
  as	
  the	
  most	
  critical;	
  the	
  most	
  critical	
  direct-­‐HWC	
  was	
  crop	
  damage	
  (Table	
  2.3).	
  	
  
Established	
  conservancy	
  participants	
  rated	
  poaching	
  of	
  conservancy	
  wildlife	
  and	
  poor	
  
human	
  health	
  as	
  the	
  most	
  severe	
  (Table	
  2.3).	
  	
  However,	
  poaching	
  was	
  reported	
  by	
  only	
  3%	
  
of	
  established	
  conservancy	
  participants.	
  	
  
	
  

Emerging	
  and	
  established	
  conservancies	
  differed	
  in	
  their	
  perception	
  of	
  acceptability	
  

of	
  HWC-­‐related	
  risks	
  to	
  livelihoods.	
  	
  Established	
  conservancy	
  participants	
  were	
  nearly	
  four	
  
times	
  as	
  likely	
  to	
  perceive	
  risks	
  to	
  livelihoods	
  as	
  more	
  acceptable	
  than	
  those	
  in	
  the	
  
emerging	
  conservancy	
  (Table	
  2.4).	
  Overall	
  worry	
  about	
  HWC-­‐related	
  risks	
  to	
  livelihoods	
  
was	
  high	
  in	
  both	
  conservancies,	
  with	
  71%	
  of	
  established	
  conservancy	
  and	
  85%	
  of	
  emerging	
  
conservancy	
  residents	
  judging	
  these	
  risks	
  as	
  high	
  (Table	
  2.4).	
  

	
  

37	
  

	
  

Conservancy	
  status	
  predicted	
  the	
  proportion	
  of	
  positive	
  responses	
  associated	
  with	
  

the	
  equality	
  of	
  benefit	
  distribution	
  in	
  the	
  conservancy	
  (e.g.,	
  meat	
  allocation	
  from	
  trophy	
  
hunts,	
  problem	
  animal	
  removal);	
  emerging	
  conservancy	
  participants	
  reported	
  higher	
  
perceived	
  consequences	
  of	
  HWC	
  in	
  terms	
  of	
  losses	
  to	
  household	
  food	
  supply,	
  income,	
  labor	
  
and	
  happiness	
  (Table	
  2.4).	
  Conservancy	
  status	
  did	
  not	
  influence	
  beliefs	
  about	
  the	
  level	
  of	
  
personal	
  control	
  of	
  experiencing	
  a	
  conflict	
  with	
  wildlife,	
  the	
  frequency	
  of	
  HWC	
  in	
  
conservancy,	
  or	
  propensity	
  of	
  respondents	
  reporting	
  that	
  they	
  guard	
  livestock	
  (Table	
  2.4).	
  	
  	
  
Conservancy	
  status	
  and	
  education	
  level	
  predicted	
  livelihood-­‐related	
  dread	
  and	
  
consequences	
  associated	
  with	
  HWC;	
  residents	
  of	
  the	
  established	
  conservancy	
  and	
  those	
  
with	
  higher	
  educational	
  attainment	
  perceived	
  HWC	
  effects	
  on	
  livelihoods	
  as	
  less	
  dreaded	
  
and	
  of	
  less	
  consequence	
  (Table	
  2.5).	
  	
  Conservancy	
  status	
  did	
  not	
  predict	
  perceptions	
  of	
  
vulnerability	
  to	
  HWC;	
  participants	
  with	
  less	
  education	
  and	
  those	
  having	
  local	
  decision-­‐
making	
  authority	
  held	
  higher	
  perceptions	
  of	
  vulnerability	
  (Table	
  2.5).	
  	
  Residents	
  of	
  the	
  
established	
  conservancy,	
  those	
  with	
  higher	
  education	
  and	
  non-­‐decision	
  makers	
  held	
  lower	
  
HWC-­‐related	
  risk	
  perceptions	
  to	
  livelihoods.	
  These	
  demographic	
  factors	
  explained	
  20%	
  of	
  
the	
  variance	
  related	
  to	
  HWC-­‐related	
  risk	
  perceptions	
  to	
  livelihoods	
  (Table	
  2.5)	
  
Wildlife.	
  Emerging	
  and	
  established	
  conservancy	
  participants	
  differed	
  in	
  their	
  
perceptions	
  about	
  relative	
  severity	
  and	
  critical	
  nature	
  of	
  risks	
  to	
  wildlife;	
  they	
  revealed	
  
more	
  agreement	
  about	
  the	
  criticalness	
  of	
  a	
  variety	
  of	
  risks	
  (e.g.,	
  agricultural	
  activities,	
  
habitat	
  modification)	
  (Table	
  2.3).	
  	
  The	
  emerging	
  conservancy	
  rated	
  wildlife	
  deterrence	
  
activities	
  and	
  agricultural	
  activities	
  as	
  most	
  critical;	
  agricultural	
  activities	
  and	
  legal	
  hunting	
  
were	
  considered	
  most	
  severe	
  (Table	
  2.3).	
  	
  The	
  established	
  conservancy	
  participants	
  rated	
  

	
  

38	
  

poaching	
  and	
  agricultural	
  activities	
  as	
  most	
  critical	
  risks	
  to	
  wildlife;	
  ecological	
  threats	
  and	
  
poaching	
  were	
  viewed	
  as	
  most	
  severe	
  (Table	
  2.3).	
  	
  
Conservancy	
  status	
  did	
  not	
  influence	
  the	
  acceptability	
  of	
  HWC-­‐related	
  risks	
  to	
  
wildlife	
  (emerging	
  =	
  51.4;	
  established=	
  68.3),	
  both	
  conservancies	
  judged	
  these	
  risks	
  as	
  
more	
  acceptable	
  to	
  wildlife	
  than	
  livelihoods	
  (Table	
  2.4).	
  	
  Established	
  conservancy	
  
participants	
  rated	
  risks	
  to	
  wildlife	
  from	
  HWC	
  as	
  being	
  high	
  74%	
  of	
  the	
  time	
  whereas	
  the	
  
emerging	
  conservancy	
  participants	
  rated	
  risks	
  to	
  wildlife	
  as	
  high	
  50%	
  of	
  the	
  time	
  (Table	
  
2.4).	
  There	
  were	
  no	
  differences	
  between	
  conservancy	
  participants	
  in	
  regard	
  to	
  their	
  
perceived	
  consequences	
  of	
  HWC	
  on	
  wildlife.	
  Both	
  conservancies’	
  participants	
  rated	
  the	
  
consequence	
  of	
  reduced	
  resources	
  for	
  wildlife	
  due	
  to	
  HWC	
  as	
  high	
  concern	
  (emerging=	
  
92.7;	
  established	
  =	
  88.6)	
  (Table	
  2.4).	
  	
  	
  
Conservancy	
  status	
  did	
  not	
  enter	
  into	
  any	
  model	
  to	
  predict	
  wildlife-­‐related	
  risk	
  
perceptions	
  (Table	
  2.5).	
  	
  Age	
  of	
  participants	
  influenced	
  their	
  beliefs	
  about	
  the	
  frequency	
  of	
  
HWC	
  incidents	
  directed	
  towards	
  wildlife,	
  vulnerability,	
  and	
  risk	
  perceptions	
  to	
  wildlife.	
  	
  
The	
  older	
  the	
  participant,	
  the	
  more	
  likely	
  they	
  were	
  to	
  perceive	
  HWC	
  incidents	
  as	
  being	
  
less	
  frequent,	
  wildlife	
  as	
  less	
  HWC-­‐vulnerable,	
  and	
  HWC	
  as	
  less	
  risky	
  to	
  wildlife	
  (Table	
  2.5).	
  
Overall	
  risk	
  perception	
  to	
  livelihoods	
  (mean	
  =11.41;	
  SE=5.93,	
  n=73)	
  was	
  over	
  five	
  times	
  
higher	
  than	
  risk	
  perception	
  to	
  wildlife	
  (mean	
  =2.00;	
  SE=2.19,	
  n=76).	
  
Assessed	
  HWC.	
  The	
  mean	
  number	
  of	
  total	
  reported	
  HWC	
  incidents	
  varied	
  according	
  
to	
  conservancy	
  (emerging	
  =	
  126.67;	
  established	
  =	
  71.83;	
  t	
  =	
  3.98;	
  df	
  =10;	
  p	
  <	
  0.05).	
  	
  The	
  
difference	
  is	
  largely	
  driven	
  by	
  livestock	
  depredation	
  incidents	
  (emerging=	
  56.33;	
  
established=	
  27.33;	
  t	
  =	
  2.81;	
  df=10;	
  p	
  <	
  0.05)	
  (Table	
  2.6).	
  Although	
  there	
  was	
  no	
  difference	
  
in	
  the	
  mean	
  number	
  of	
  total	
  HWC	
  incidents	
  per	
  area	
  (km2),	
  the	
  emerging	
  conservancy	
  

	
  

39	
  

reported	
  higher	
  per	
  capita	
  rates	
  of	
  problem	
  animal	
  incidents	
  than	
  the	
  established	
  
conservancy	
  (emerging	
  =	
  0.32;	
  established	
  =	
  0.03;	
  t	
  =	
  10.44;	
  df=5.23;	
  p<0.05)	
  (Table	
  2.6).	
  	
  
2.4.2.	
  HWC-­related	
  risks	
  relative	
  to	
  other	
  risks	
  to	
  livelihoods	
  and	
  wildlife.	
  	
  
Participants	
  listed	
  165	
  risks	
  to	
  livelihoods	
  (mean=	
  3.3,	
  range	
  2-­‐11)	
  that	
  were	
  
grouped	
  into	
  15	
  risk	
  categories.	
  Participants	
  also	
  generated	
  a	
  total	
  of	
  157	
  risks	
  to	
  wildlife	
  
(mean=	
  3.3,	
  range	
  1-­‐9)	
  summarized	
  by	
  14	
  risk	
  categories.	
  	
  Nine	
  risk	
  categories	
  were	
  cross-­‐
listed	
  as	
  affecting	
  	
  both	
  livelihoods	
  and	
  wildlife;	
  21	
  discrete	
  risk	
  categories	
  were	
  generated	
  
and	
  included	
  direct	
  (n=8)	
  and	
  indirect	
  (n=6)	
  HWC	
  and	
  non-­‐HWC	
  related	
  risks	
  (n=7)	
  (Table	
  
2.2).	
  	
  Pooling	
  data	
  between	
  conservancies,	
  non-­‐HWC	
  risks	
  (Rj=0.65)	
  were	
  considered	
  the	
  
most	
  threatening	
  to	
  livelihoods,	
  followed	
  by	
  direct-­‐HWC	
  risks	
  (Rj=	
  0.59)	
  and	
  indirect-­‐HWC	
  
risks	
  (Rj=0.24).	
  	
  Direct-­‐HWC	
  risks	
  (Rj=0.65)	
  and	
  indirect-­‐HWC	
  risks	
  (Rj=	
  0.60)	
  were	
  seen	
  
as	
  the	
  most	
  critical	
  to	
  wildlife	
  but	
  non-­‐HWC	
  related	
  risks	
  (Rj=0.34)	
  were	
  also	
  considered	
  
threatening	
  to	
  wildlife.	
  
Livelihood	
  risk	
  categories	
  were	
  plotted	
  using	
  increasing	
  incidents	
  (Ij)	
  against	
  
increasing	
  importance	
  (Pj)	
  (Figure	
  2.1).	
  No	
  risk	
  was	
  rated	
  as	
  having	
  low	
  importance	
  and	
  
high	
  incidence.	
  	
  The	
  risk	
  to	
  livelihoods	
  with	
  the	
  highest	
  incidence	
  was	
  crop	
  damage;	
  
poaching	
  was	
  rated	
  most	
  important	
  to	
  livelihoods	
  (Figure	
  2.1).	
  	
  Direct	
  HWCs	
  tended	
  to	
  
have	
  high	
  importance	
  (>0.4)	
  and	
  the	
  largest	
  range	
  of	
  incidence	
  (0.02	
  to	
  0.52).	
  	
  Indirect	
  
HWCs	
  were	
  rated	
  as	
  having	
  low	
  incidence	
  (<0.4)	
  and	
  increased	
  in	
  a	
  linear	
  fashion	
  with	
  
increasing	
  importance.	
  	
  The	
  majority	
  of	
  non-­‐HWC	
  risks	
  were	
  rated	
  as	
  moderately	
  
important	
  (0.34	
  ≥	
  0.57)	
  with	
  a	
  wide	
  range	
  of	
  incidence	
  (0.18	
  ≥	
  0.50).	
  	
  The	
  most	
  severe	
  risk	
  
was	
  crop	
  damage	
  (Figure	
  2.1).	
  	
  

	
  

40	
  

The	
  distribution	
  of	
  plotted	
  risks	
  to	
  wildlife	
  was	
  non-­‐linear	
  with	
  the	
  majority	
  of	
  risks	
  
rated	
  as	
  moderate	
  to	
  high	
  importance	
  (3.0	
  >	
  7.0)	
  and	
  ranging	
  from	
  low	
  to	
  high	
  incidence	
  
(Figure	
  2.2).	
  	
  The	
  wildlife	
  risks	
  with	
  the	
  highest	
  incidence	
  were	
  agricultural	
  activities	
  and	
  
poaching.	
  	
  Human	
  financial	
  insecurity	
  and	
  legal	
  hunting	
  were	
  ranked	
  the	
  highest	
  in	
  terms	
  
of	
  importance.	
  	
  Poaching	
  and	
  wildlife	
  deterrence	
  activities	
  were	
  rated	
  as	
  high	
  incidence	
  (≥	
  
0.50),	
  hunting	
  was	
  of	
  moderate	
  incidence	
  (<	
  0.4)	
  and	
  retaliation	
  was	
  of	
  low	
  incidence	
  
(<0.2)	
  (Figure	
  2.2).	
  	
  Indirect	
  HWCs	
  were	
  widely	
  dispersed	
  in	
  terms	
  of	
  incidence	
  (I	
  =	
  0.04	
  to	
  
0.67)	
  yet	
  moderate	
  in	
  terms	
  of	
  importance	
  (Pj=	
  0.32	
  to	
  0.56).	
  	
  Non-­‐HWC	
  related	
  risks	
  were	
  
rated	
  as	
  low	
  incidence	
  (<0.4);	
  ecological	
  threats,	
  local	
  climate	
  and	
  human	
  financial	
  
insecurity	
  were	
  of	
  moderate	
  to	
  high	
  importance	
  (Figure	
  2.2).	
  	
  
2.5.	
  DISCUSSION	
  
2.5.1.	
  Conservancy	
  effects	
  on	
  HWC-­related	
  risk	
  perceptions.	
  
Conservancy	
  status	
  affected	
  overall	
  perceptions	
  of	
  risk	
  related	
  to	
  livelihoods	
  and	
  
consequences	
  of	
  HWC-­‐related	
  risks	
  to	
  local	
  livelihoods,	
  but	
  conservancy	
  status	
  it	
  did	
  not	
  
have	
  the	
  same	
  effects	
  on	
  risk	
  perceptions	
  to	
  wildlife.	
  	
  Conservancy	
  status	
  also	
  influenced	
  
the	
  prioritization	
  of	
  HWC-­‐related	
  risk	
  to	
  both	
  livelihoods	
  and	
  wildlife	
  and	
  preferences	
  for	
  
management.	
  	
  Residents	
  of	
  the	
  established	
  conservancy	
  found	
  the	
  distribution	
  of	
  HWC-­‐
related	
  benefits	
  more	
  equitable,	
  risks	
  to	
  livelihoods	
  less	
  dreaded,	
  and	
  more	
  acceptable	
  than	
  
residents	
  of	
  the	
  emerging	
  conservancy.	
  	
  There	
  was	
  no	
  effect	
  of	
  conservancy	
  establishment	
  
on	
  residents’	
  feelings	
  of	
  control	
  over	
  experiencing	
  HWC	
  events.	
  	
  Nearly	
  60%	
  of	
  residents	
  in	
  
the	
  established	
  conservancy	
  and	
  40%	
  in	
  the	
  emerging	
  conservancy	
  felt	
  they	
  had	
  little	
  
control	
  over	
  experiencing	
  HWC.	
  	
  This	
  finding	
  may	
  be	
  of	
  high	
  relevance	
  to	
  conservation	
  
practitioners.	
  	
  	
  Perceptions	
  that	
  HWC	
  are	
  largely	
  uncontrollable	
  may	
  lead	
  to	
  conservancy	
  

	
  

41	
  

residents	
  failing	
  to	
  take	
  preventative	
  measures,	
  even	
  if	
  risk	
  management	
  practices	
  (e.g.,	
  
chili	
  bombs,	
  lion	
  proof	
  fencing)	
  exist	
  and	
  are	
  promoted	
  at	
  the	
  conservancy	
  level	
  (McDaniels	
  
et	
  al.,	
  1997).	
  	
  However,	
  perceived	
  control	
  over	
  experiencing	
  HWC	
  may	
  not	
  be	
  the	
  only	
  
factor	
  influencing	
  residents’	
  participation	
  in	
  wildlife	
  deterrence	
  activities.	
  For	
  example,	
  
emerging	
  conservancy	
  residents	
  ranked	
  wildlife	
  deterrence	
  activities	
  as	
  the	
  most	
  critical	
  
risk	
  to	
  wildlife	
  in	
  their	
  conservancy.	
  	
  This	
  may	
  indicate	
  that	
  managers	
  need	
  to	
  evaluate	
  the	
  
social	
  acceptability	
  of	
  interventions	
  designed	
  to	
  reduce	
  conflict	
  (Treves	
  et	
  al.,	
  2009),	
  as	
  
current	
  methods	
  may	
  be	
  deemed	
  effective	
  in	
  terms	
  of	
  reducing	
  risks	
  to	
  humans	
  but	
  too	
  
risky	
  to	
  wildlife.	
  	
  	
  
Residents	
  in	
  the	
  established	
  conservancy	
  may	
  be	
  displaying	
  attitudes	
  consistent	
  
with	
  the	
  notion	
  that	
  devolved	
  rights	
  over	
  wildlife	
  promote	
  more	
  positive	
  attitudes	
  towards	
  
wildlife	
  conservation	
  (Hoole,	
  2010).	
  	
  There	
  was	
  a	
  higher	
  propensity	
  for	
  residents	
  in	
  the	
  
established	
  conservancy	
  to	
  report	
  higher	
  “overall	
  worry”	
  about	
  HWC-­‐effects	
  on	
  wildlife.	
  
Additionally,	
  established	
  conservancy	
  residents	
  ranked	
  poaching	
  as	
  a	
  threat	
  to	
  wildlife	
  and	
  
local	
  livelihoods,	
  which	
  may	
  indicate	
  that	
  the	
  devolution	
  of	
  wildlife	
  ownership	
  to	
  local	
  
communities	
  may	
  be	
  affecting	
  local	
  attitudes	
  towards	
  wildlife	
  as	
  a	
  resource.	
  	
  However,	
  
conservancy	
  status	
  did	
  not	
  influence	
  factors	
  affecting	
  risk	
  perception	
  to	
  wildlife,	
  such	
  as	
  
acceptability,	
  dread,	
  consequences	
  and	
  vulnerability.	
  	
  This	
  may	
  indicate	
  that	
  changes	
  in	
  
local	
  attitudes	
  towards	
  wildlife	
  may	
  be	
  more	
  broadly	
  tied	
  to	
  individual	
  rights	
  to	
  use	
  wildlife	
  
as	
  an	
  economic	
  resource,	
  and	
  the	
  perceived	
  fairness	
  of	
  benefit	
  distribution	
  (Robertson	
  &	
  
Lawes,	
  2005),	
  rather	
  than	
  concerns	
  over	
  wildlife	
  conservation	
  or	
  ecological	
  sustainability.	
  
Interpreting	
  the	
  effects	
  of	
  conservancy	
  status	
  on	
  HWC-­‐risk	
  perceptions	
  also	
  
necessitates	
  understanding	
  historical	
  HWC	
  incidents	
  (realized	
  risk)	
  (Sjöberg,	
  2000b).	
  	
  

	
  

42	
  

Although	
  established	
  conservancy	
  residents	
  had	
  overall	
  lower	
  perceptions	
  of	
  HWC-­‐related	
  
risks,	
  they	
  also	
  experience	
  significantly	
  lower	
  historical	
  incidents	
  of	
  reported	
  HWC	
  
(hereafter	
  realized	
  risk).	
  Differences	
  in	
  realized	
  risk	
  between	
  conservancies	
  were	
  largely	
  
influenced	
  by	
  livestock	
  depredation	
  rates	
  in	
  the	
  emerging	
  conservancy.	
  	
  Residents	
  in	
  the	
  
two	
  conservancies	
  did	
  not	
  differ	
  in	
  their	
  perceptions	
  of	
  the	
  frequency	
  of	
  HWC	
  events	
  and	
  in	
  
their	
  livestock	
  guarding	
  behavior,	
  despite	
  the	
  emerging	
  conservancies	
  higher	
  realized	
  risk.	
  	
  
This	
  suggests	
  that	
  conservancy	
  status	
  may	
  have	
  a	
  greater	
  effect	
  on	
  the	
  emotional,	
  value-­‐
laden,	
  factors	
  that	
  influence	
  risk	
  perception	
  (dread,	
  acceptability)	
  rather	
  than	
  more	
  
calculated,	
  analytical,	
  cognitive	
  factors	
  (frequency,	
  control)	
  (Slovic,	
  Fiucane,	
  Peters	
  &	
  
MacGregor,	
  2004).	
  	
  	
  
Greater	
  understanding	
  about	
  differences	
  between	
  realized	
  and	
  perceived	
  HWC-­‐risks	
  
could	
  lead	
  to	
  effectively	
  deconstructing	
  the	
  ‘conservancy	
  effect’	
  into	
  various	
  components	
  
that	
  may	
  affect	
  residents’	
  perceptions	
  and	
  attitudes.	
  Is	
  it	
  the	
  resource	
  tenure	
  system	
  (i.e.,	
  
devolved	
  resource	
  rights)	
  (Sutherland,	
  Adams,	
  Aronson,	
  Aveling,	
  Blackburn,	
  Broad	
  et	
  
al.,2009)	
  that	
  is	
  affecting	
  HWC-­‐related	
  attitudes	
  in	
  the	
  conservancies?	
  	
  Is	
  it	
  the	
  economic	
  
incentives	
  (e.g.,	
  HWC	
  compensation,	
  trophy	
  hunting	
  revenues)	
  (Sutherland	
  et	
  al.,	
  2009)	
  
associated	
  with	
  conservancy	
  establishment?	
  What	
  part	
  does	
  the	
  provision	
  of	
  education,	
  
outreach	
  or	
  information	
  (Sutherland	
  et	
  al.,	
  2009)	
  play	
  in	
  shaping	
  HWC	
  and	
  conservation-­‐
related	
  behavior?	
  What	
  role	
  does	
  realized	
  risk	
  (Sjöberg,	
  2000b)	
  play	
  in	
  the	
  affects	
  of	
  
conservancy	
  status	
  on	
  stakeholders’	
  HWC	
  risk	
  perceptions?	
  	
  Ultimately,	
  answering	
  these	
  
questions	
  may	
  lead	
  to	
  improved	
  HWC	
  management	
  in	
  existing	
  CBNRM	
  areas	
  and	
  inform	
  
the	
  appropriateness	
  of	
  using	
  CBNRM	
  to	
  manage	
  HWC	
  in	
  additional	
  contexts.	
  	
  	
  
	
  

	
  

43	
  

2.5.2.	
  Human-­wildlife	
  conflict	
  relative	
  to	
  other	
  risks.	
  
	
  

A	
  diversity	
  of	
  risks	
  impact	
  local	
  livelihoods	
  and	
  wildlife.	
  	
  Both	
  direct	
  and	
  indirect	
  

HWCs	
  figured	
  prominently	
  into	
  conservancy	
  residents'	
  conceptualization	
  of	
  threats	
  to	
  local	
  
livelihoods.	
  	
  However,	
  when	
  taken	
  together,	
  risks	
  characterized	
  as	
  being	
  unrelated	
  to	
  
wildlife	
  (non-­‐HWC)	
  were	
  most	
  threatening	
  to	
  livelihoods.	
  	
  Given	
  that	
  vulnerability	
  may	
  
emerge	
  or	
  be	
  exacerbated	
  by	
  multiple	
  stressors	
  (Reid	
  &	
  Vogel,	
  2006;	
  Tschakert,	
  2007),	
  
understanding	
  the	
  larger	
  risk	
  context	
  of	
  an	
  individual	
  stakeholder	
  or	
  wildlife	
  species	
  could	
  
provide	
  an	
  indication	
  of	
  their	
  overall	
  vulnerability	
  to	
  HWC	
  events.	
  	
  For	
  example,	
  
participants	
  often	
  mentioned	
  flooding	
  increased	
  human-­‐wildlife	
  interactions	
  because	
  
flooding	
  forced	
  wildlife	
  and	
  people	
  to	
  compete	
  for	
  less	
  space,	
  resulting	
  in	
  increased	
  
frequency	
  and	
  sensitivity	
  to	
  crop	
  raiding.	
  	
  	
  
Examining	
  HWC-­‐related	
  risk	
  perceptions	
  in	
  a	
  multidirectional	
  manner	
  is	
  consistent	
  
with	
  the	
  evolution	
  away	
  from	
  synonymous	
  treatment	
  of	
  HWC	
  as	
  a	
  wildlife	
  damage	
  event	
  
(Peterson,	
  Birckhead,	
  Leong,	
  Peterson	
  &	
  Peterson,	
  2010)	
  and	
  gives	
  a	
  forum	
  for	
  local	
  
stakeholders	
  to	
  demonstrate	
  their	
  understanding	
  of	
  the	
  negative	
  consequences	
  of	
  HWC	
  on	
  
not	
  only	
  their	
  livelihoods	
  but	
  wildlife	
  as	
  well.	
  	
  For	
  example,	
  technical	
  assessments	
  of	
  
anthropogenic	
  risks	
  to	
  wildlife,	
  such	
  as	
  poaching	
  (Waltert,	
  Meyer	
  &	
  Kiffner,	
  2009),	
  habitat	
  
alteration	
  (Laurance,	
  Croes,	
  Guissouegou,	
  Buij,	
  Bethier	
  &	
  Alonso,	
  2008)	
  and	
  human	
  socio-­‐
economic	
  conditions	
  (Dudley,	
  Ginsberg,	
  Plumptre,	
  Hart	
  &	
  Campos,	
  2002),	
  are	
  common	
  in	
  
the	
  conservation	
  literature.	
  	
  Results	
  presented	
  herein	
  about	
  the	
  risk	
  ranking	
  exercise	
  
indicated	
  that	
  conservancy	
  residents	
  also	
  perceive	
  ties	
  between	
  human	
  socio-­‐economic	
  
conditions	
  and	
  wildlife	
  conservation.	
  	
  For	
  instance,	
  stakeholders	
  cited	
  that	
  high	
  

	
  

44	
  

unemployment,	
  poverty,	
  land	
  and	
  agricultural	
  insecurities	
  all	
  exacerbated	
  human	
  and	
  
wildlife	
  vulnerability	
  to	
  and	
  decreased	
  stakeholder	
  tolerance	
  of	
  HWC.	
  	
  
What	
  extent	
  does	
  conservancy	
  residents’	
  prioritization	
  and	
  quantification	
  of	
  HWC-­‐
related	
  risks	
  overlap	
  with	
  those	
  of	
  conservation	
  agency	
  and	
  organizational	
  professionals’	
  
risk	
  assessments?	
  	
  Identifying	
  overlapping	
  concerns	
  may	
  aid	
  in	
  prioritization	
  of	
  risk	
  
management	
  interventions	
  and	
  help	
  further	
  promote	
  the	
  role	
  of	
  conservancy	
  stakeholders	
  
as	
  influential	
  in	
  wildlife-­‐related	
  decision-­‐making	
  (Treves	
  et	
  al.,	
  2006a),	
  which	
  aligns	
  with	
  
the	
  ideals	
  of	
  CBNRM.	
  	
  Identifying	
  risk	
  priorities	
  of	
  mutual	
  concern	
  to	
  communities	
  and	
  
managers	
  may	
  bolster	
  community	
  support	
  for	
  management	
  and	
  foster	
  cooperation	
  
between	
  conservancy	
  residents	
  and	
  managers	
  to	
  more	
  effectively	
  address	
  local	
  risks	
  to	
  
wildlife	
  (Treves	
  et	
  al.,	
  2006a).	
  	
  
Taken	
  together,	
  the	
  results	
  of	
  conservancy	
  residents’	
  characterization	
  of	
  risks	
  
suggest	
  that	
  successful	
  HWC	
  management	
  may	
  necessitate	
  addressing	
  non-­‐wildlife	
  related	
  
risks	
  (e.g.,	
  poor	
  human	
  health)	
  as	
  the	
  social	
  acceptability	
  and	
  tolerance	
  of	
  HWC	
  appear	
  to	
  
be	
  closely	
  tied	
  to	
  overall	
  gains	
  in	
  human	
  livelihood	
  development	
  and	
  security.	
  	
  Further,	
  
conservationists	
  interested	
  in	
  improving	
  human	
  welfare	
  through	
  sustainable	
  development	
  
projects	
  will	
  need	
  to	
  consider	
  the	
  ramifications	
  of	
  such	
  projects	
  on	
  relationships	
  between	
  
local	
  people	
  and	
  wildlife	
  in	
  order	
  to	
  avoid	
  unintentionally	
  exacerbating	
  conflict	
  or	
  
negatively	
  affecting	
  wildlife	
  resources.	
  	
  Given	
  that	
  completely	
  eliminating	
  HWC-­‐related	
  
risks	
  is	
  untenable	
  (MET,	
  2009)	
  and	
  even	
  undesirable	
  in	
  many	
  circumstances,	
  identifying	
  
non-­‐HWC	
  related	
  risks	
  that	
  may	
  be	
  more	
  efficiently	
  managed	
  could	
  help	
  reduce	
  
vulnerability	
  to	
  HWC-­‐related	
  risks.	
  
3.5.3.	
  Conclusion.	
  

	
  

	
  

45	
  

This	
  research	
  extends	
  the	
  current	
  HWC	
  literature	
  by	
  exploring	
  stakeholder-­‐
perceptions	
  of	
  HWC-­‐related	
  risks	
  to	
  wildlife	
  in	
  addition	
  to	
  risk	
  perceptions	
  from	
  wildlife,	
  
and	
  includes	
  empirical	
  investigation	
  of	
  conservancy	
  membership	
  as	
  a	
  factor	
  influencing	
  
HWC-­‐related	
  risk	
  perceptions.	
  	
  Understanding	
  local	
  stakeholder	
  perceptions	
  of	
  risks	
  and	
  
vulnerability	
  to	
  livelihoods	
  and	
  wildlife	
  may	
  help	
  managers	
  better	
  design	
  HWC-­‐
interventions,	
  prioritize	
  threats	
  for	
  management	
  and	
  mitigation,	
  and	
  create	
  vulnerability-­‐
reducing	
  management	
  plans	
  that	
  assist	
  the	
  most	
  HWC-­‐sensitive	
  individuals	
  and	
  wildlife	
  
species	
  in	
  conservancies.	
  	
  Important	
  questions	
  remain.	
  	
  There	
  is	
  less	
  understanding	
  of	
  the	
  
factors	
  that	
  influence	
  the	
  perceptions	
  of	
  HWC-­‐related	
  risks	
  to	
  wildlife	
  versus	
  those	
  that	
  
influence	
  perceptions	
  of	
  HWC-­‐related	
  risks	
  to	
  livelihoods.	
  Further	
  inquiry	
  is	
  also	
  needed	
  to	
  
understand	
  the	
  adaptive	
  capacity	
  of	
  communities	
  in	
  the	
  face	
  of	
  HWC-­‐related	
  risks	
  and	
  
should	
  incorporate	
  community	
  perceptions	
  of	
  risk	
  and	
  vulnerability	
  (Flint	
  &	
  Luloff,	
  2005).	
  	
  
Greater	
  understanding	
  of	
  how	
  HWC-­‐related	
  and	
  non-­‐HWC	
  related	
  risks	
  interact	
  to	
  shape	
  
stakeholders’	
  responses	
  would	
  have	
  both	
  theoretical	
  and	
  practical	
  applications	
  on	
  
understanding	
  the	
  effect	
  that	
  conservation	
  initiatives	
  (e.g.,	
  conservancies)	
  have	
  on	
  
attitudes	
  and	
  behaviors	
  (Baird	
  et	
  al.,	
  2009).	
  	
  	
  	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

46	
  

	
  
	
  
Table	
  2.1:	
  Characteristics	
  of	
  study	
  conservancies	
  in	
  East	
  Caprivi,	
  Namibia	
  
	
  	
  

Dzoti	
  &	
  Wuparo	
  Conservancies	
  

Climate	
  

Semi-­‐arid	
  (Average	
  annual	
  rainfall	
  ≥625	
  mm)	
  

Biome	
  classification	
  

Mosaic	
  of	
  mopane	
  (Colophospermum	
  mopane)	
  
woodland,	
  Kalahari	
  grassland	
  with	
  floodplains	
  

Major	
  wildlife	
  resources	
  a	
  

Buffalo,	
  Duiker,	
  Elephant,	
  Impala,	
  Kudu,	
  
Leopard,	
  Lion,	
  Reedbuck,	
  Roan,	
  Tsessebe,	
  
Warthog,	
  Wildebeest	
  

	
  	
  

Dzoti	
  

Wuparo	
  

Registered	
  

October	
  2009	
  b	
  

December	
  1999	
  

Management	
  classification	
  

Emerging	
  b	
  

Established	
  

Size	
  

245	
  km	
  2	
  

148	
  km	
  2	
  

Approximate	
  population	
  density	
  

1.6	
  per	
  km	
  2	
  

14.2	
  per	
  km	
  2	
  

Village	
  zones	
  

5	
  

3	
  

HWC	
  compensation	
  scheme	
  

No	
  

Yes	
  

Hunting	
  concessions	
  

No	
  

Yes	
  

Problem	
  animal	
  removal	
  	
  

Yes	
  

Yes	
  

Alternative	
  income	
  generation	
  

No	
  

Yes	
  

Traditional	
  authorities	
  (kutas)	
  

Chief	
  Mbambo;	
  Chief	
  
Sifu	
  

Chief	
  Sifu	
  

a	
  Based	
  on	
  Conservancy	
  Profile	
  (NASCO,	
  2009)	
  for	
  Wuparo;	
  Conservancy	
  

information	
  for	
  Dzoti	
  not	
  available	
  at	
  this	
  time	
  yet	
  Wuparo	
  information	
  is	
  an	
  
appropriate	
  proxy	
  due	
  to	
  their	
  continuity	
  in	
  the	
  landscape	
  
b	
  Conservancy	
  not	
  established	
  during	
  research	
  timeframe;	
  table	
  treats	
  remaining	
  

	
  
	
  
	
  
	
  
	
  

characteristics	
  as	
  pre-­‐registration	
  condition.	
  

47	
  

Table	
  2.2:	
  Risk	
  categories,	
  select	
  category	
  attributes,	
  and	
  risk	
  themes	
  (direct,	
  
indirect,	
  non-­HWC)	
  generated	
  during	
  risk	
  ranking	
  activity	
  in	
  two	
  conservancies	
  
(n=50):	
  Caprivi,	
  Namibia	
  (July-­September,	
  2009)	
  
DIRECT	
  HUMAN-­WILDLIFE	
  CONFLICT	
  
Crop	
  damage	
  

	
   INDIRECT	
  HUMAN-­WILDLIFE	
  
CONFLICT	
  
	
  

Buffalo,	
  elephants,	
  porcupine	
  	
  
Human	
  attack	
  
Elephants,	
  lions	
  	
  
Hunting	
  
Commercial,	
  local	
  subsistence	
  
Monetary	
  utilization	
  of	
  wildlife	
  

	
   Habitat	
  modification	
  
	
  
Deforestation	
  
	
  
Environmental	
  Damage	
  
	
   Increased	
  human-­wildlife	
  interaction	
  
	
  
Increased	
  proximity,	
  intimidation	
  
	
  
Resource	
  competition	
  	
  

Human-­wildlife	
  conflict	
  (general)	
  

	
   Subsistence	
  insecurity	
  

Buffalo,	
  elephants,	
  hippopotamus,	
  lion	
  
Livestock	
  loss	
  
Elephants,	
  hyena,	
  lion	
  

	
  

Agriculture,	
  food,	
  land	
  

	
  

Livestock	
  disease	
  

	
   NON-­HUMAN-­WILDLIFE	
  CONFLICT	
  

Poaching	
  

	
   Climate	
  

Firearms,	
  snares	
  and	
  traps	
  
Retaliation	
  
Poisoning	
  wildlife,	
  retaliation	
  
Wildlife	
  deterrence	
  activities	
  
Chili,	
  fence,	
  shooting	
  firearms	
  

	
  
Drought,	
  flooding	
  
	
   Ecological	
  threats	
  
	
  
Insect	
  pests,	
  natural	
  predation	
  
	
  
Wildlife	
  disease	
  
	
   Education	
  and	
  training	
  

INDIRECT	
  HUMAN-­WILDLIFE	
  CONFLICT	
  
Agricultural	
  activities	
  
Farming,	
  fire,	
  livestock	
  operations	
  
Conservancy	
  service	
  &	
  management	
  
Insufficient	
  benefits,	
  compensation	
  
Lack	
  of	
  infrastructure,	
  zonation	
  
Poor	
  enforcement	
  and	
  patrolling	
  
Development	
  
Development	
  in	
  wildlife	
  corridors	
  
Pollution-­‐waste	
  
Roadways	
  and	
  transportation	
  
	
  	
  

	
  

	
  

Lack	
  of	
  education,	
  training	
  

	
   Financial	
  insecurity	
  
	
  
Lack	
  of	
  money,	
  work,	
  social	
  security	
  
	
  
Poverty	
  
	
   Poor	
  human	
  health	
  
	
  
Bad	
  Health,	
  malaria	
  
	
  
HIV/	
  AIDS	
  
	
   Rural	
  services	
  &	
  infrastructure	
  
	
  
Lack	
  of	
  potable	
  water,	
  infrastructure	
  
	
  
Poor	
  healthcare,	
  living	
  conditions	
  
	
   Socio-­cultural	
  insecurity	
  
	
  
Alcohol,	
  domestic	
  violence	
  
	
  	
   Social	
  conflict,	
  war	
  

48	
  

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Figure	
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  residents’	
  perceptions	
  (n=50)	
  about	
  the	
  incidence	
  and	
  importance	
  of	
  risks	
  to	
  livelihoods	
  in	
  
two	
  conservancies	
  (n=	
  50)	
  in	
  East	
  Caprivi,	
  Namibia	
  (Focus	
  groups;	
  July-­September,	
  2009).	
  

DEM%
6#'27.8)%
DEL%

,.4&4.5*%'11'23%

DEK%

A&<2'1.#8%

!"#$%&'(')*%

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.80*2<".1=%

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DEJ%
!"#$%&'(")*(+,-$.&"#%*/012*

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+<('8%>.4&4.5*%
.81*"'21.#8%

N8&."*21%
+*'417%

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DEI%

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-#2'4%24.('1*%

DEH%

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.85"'01"<21<"*%

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DEG%

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DEF%

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A2#4#).2'4%17"*'10%

D%
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DEF%

DEG%

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DEH%

DEI%

DEJ%

DEK%

DEL%

CDEF%
!"#$%&'(")*("#(3%"#%*/!12*
	
  
	
  

55	
  

	
  
Figure	
  2.2:	
  Conservancy	
  residents’	
  perceptions	
  (n=48)	
  about	
  the	
  incidence	
  and	
  importance	
  of	
  risks	
  to	
  wildlife	
  in	
  two	
  
conservancies	
  in	
  East	
  Caprivi,	
  Namibia	
  (Focus	
  groups;	
  July-­September,	
  2009).	
  

CDL'

236.*'7"*.*+".#'
"*;&+3)"(<'

23*("*0'

CDK'

8&9&#-:6&*('

A-*;&)9.*+<';&)9"+&;''

CDJ'

1&(.#".("-*'
CDI'

!"#$%&'(")*(+,-$.&"#%*/012*

<=>*?%'()"&.(-"*

,-.+/"*0'''

!"#$#"%&'$&(&))&*+&'

M-*B2!A'

2.5"(.('6-$"7"+.("-*'

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=*+)&.;&$'/36.*'
>"#$#"%&'"*(&).+("-*'

CDG'

8%9%$(.:*!"3%;*/812*
CDF'
4*

236.*';-+".#'+-*7#"+(;'
CDE'

564*
7*

C'
BCDE'

C'
BCDE'

	
  

8")&+( !
=*$")&+('

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"*;&+3)"(<'

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CDE'

CDF'

CDG'

CDH'

!"#$%&'(")*("#(3%"#%*/!12*

CDI'

CDJ'

CDK'

	
  
56	
  

CHAPTER	
  3:	
  A	
  CONSERVATION	
  CRIMINOLOGY	
  APPROACH	
  TO	
  ESTIMATING	
  
POACHING	
  ACTIVITIES:	
  CO-­MAPPING	
  RISKS	
  AND	
  CHARACTERIZING	
  MOTIVATIONS	
  IN	
  
NAMIBIAN	
  CONSERVANCIES	
  	
  
	
  
3.1.	
  INTRODUCTION	
  
Poaching,	
  the	
  illegal	
  harvest	
  of	
  wildlife,	
  may	
  have	
  myriad	
  biological,	
  ecological	
  and	
  
social	
  consequences	
  and	
  implications	
  for	
  natural	
  resource	
  management.	
  	
  For	
  example,	
  
wildlife	
  species	
  subjected	
  to	
  poaching	
  can	
  experience	
  population	
  suppression,	
  range	
  
collapse	
  and	
  extinction	
  (Woodroff,	
  Thirgood	
  &	
  Rabinowitz,	
  2005).	
  	
  These	
  outcomes	
  may	
  
threaten	
  ecosystem	
  function	
  (Waite,	
  2007;	
  Wright,	
  Stoner,	
  Beckman,	
  Corlett,	
  Dirzo,	
  Muller-­‐
Landau	
  et	
  al.,	
  2007)	
  and	
  ecological	
  services	
  (e.g.,	
  pollination)	
  (Bruno	
  &	
  Cardinale,	
  2008;	
  
Wright	
  et	
  al.,	
  2007).	
  	
  The	
  loss	
  of	
  wildlife-­‐related	
  resources	
  may	
  threaten	
  rural	
  livelihoods	
  
by	
  decreasing	
  food	
  security	
  (Bowen-­‐Jones,	
  Brown	
  &	
  Robinson,	
  2003;	
  Robinson	
  &	
  Bennet,	
  
2004)	
  and	
  disrupting	
  human	
  cultural	
  practices	
  that	
  depend	
  on	
  wildlife	
  (Basset,	
  2005;	
  
Bowen-­‐Jones	
  et	
  al.,	
  2003).	
  	
  In	
  community-­‐based	
  natural	
  resource	
  management	
  (CBNRM)	
  
systems,	
  poaching	
  may	
  negatively	
  affect	
  stakeholders	
  by	
  reducing	
  the	
  capacity	
  of	
  CBNRM	
  
to	
  deliver	
  economic	
  improvements	
  through	
  sustainable	
  wildlife	
  use	
  	
  (Sethi	
  &	
  Hilborn,	
  
2008).	
  
The	
  illicit	
  nature	
  of	
  poaching	
  has	
  long	
  made	
  monitoring,	
  enforcement	
  and	
  
deterrence	
  cumbersome	
  in	
  terms	
  of	
  time,	
  expenditure	
  and	
  reliability	
  (Solomon,	
  Jacobson,	
  
Wald	
  &	
  Gavin,	
  2007).	
  	
  Monitoring	
  and	
  deterrence	
  activities	
  require	
  significant	
  financial	
  and	
  
human	
  resources	
  (Keane,	
  Jones,	
  Edwards-­‐Jones	
  &	
  Milner-­‐Gulland,	
  2008;	
  Kuperan	
  &	
  
Sutinen,	
  1998;	
  Nielsen,	
  2003)	
  and	
  managers	
  must	
  prioritize	
  monitoring	
  and	
  assessment	
  
activities	
  relative	
  to	
  other	
  natural	
  resource	
  issues	
  (Sheil,	
  2001).	
  	
  Ultimately,	
  the	
  decision	
  to	
  

	
  

57	
  

direct	
  resources	
  toward	
  combating	
  poaching	
  is	
  based,	
  in	
  part,	
  on	
  tradeoffs	
  between	
  the	
  
nature	
  of	
  the	
  poaching	
  risk	
  relative	
  to	
  other	
  risks	
  and	
  the	
  relevance	
  of	
  reducing	
  poaching	
  
for	
  achieving	
  conservation	
  objectives	
  (Sheil,	
  2001).	
  	
  	
  
The	
  goal	
  of	
  this	
  research	
  was	
  to	
  explore	
  the	
  conceptual	
  and	
  physical	
  space	
  between	
  
a	
  technical	
  assessment	
  and	
  local	
  perceptions	
  of	
  poaching	
  as	
  a	
  risk	
  to	
  wildlife	
  in	
  a	
  CBNRM	
  
system	
  with	
  the	
  hopes	
  that	
  such	
  understanding	
  can	
  inform	
  more	
  effective	
  wildlife	
  decision-­‐
making,	
  including	
  monitoring	
  and	
  enforcement.	
  	
  I	
  used	
  conservation	
  criminology,	
  an	
  
interdisciplinary	
  conceptual	
  framework	
  applying	
  theories	
  from	
  the	
  disciplines	
  of	
  
criminology,	
  natural	
  resources	
  management	
  and	
  risk	
  and	
  decision	
  sciences	
  (Gibbs,	
  Gore,	
  
McGarrell	
  &	
  Rivers,	
  2010),	
  to	
  guide	
  my	
  research.	
  	
  
3.2.	
  BACKGROUND	
  
Conservation	
  practitioners	
  regularly	
  face	
  two	
  challenges	
  when	
  attempting	
  to	
  
manage	
  risks	
  to	
  wildlife,	
  including	
  poaching:	
  1)	
  a	
  lack	
  of	
  adequate	
  information	
  about	
  local	
  
stakeholders'	
  attitudes	
  about	
  risks	
  to	
  wildlife,	
  and;	
  2)	
  a	
  deficit	
  of	
  spatially	
  explicit	
  
information	
  about	
  risks	
  to	
  wildlife	
  (Treves,	
  Andriamapianina,	
  Didier,	
  Gibson,	
  Plumptre,	
  
Wilkie	
  et	
  al.,	
  2006).	
  	
  Understanding	
  stakeholders'	
  perceptions	
  about	
  risks	
  to	
  wildlife	
  is	
  
essential	
  for	
  encouraging	
  compliance	
  with	
  anti-­‐poaching	
  regulations	
  (Hampshire,	
  Bell,	
  
Wallace	
  &	
  Stepukonis,	
  2004;	
  McFarlane,	
  2005).	
  	
  Additionally,	
  identifying	
  the	
  spatial	
  
distribution	
  of	
  poaching	
  activities	
  is	
  essential	
  because	
  failing	
  to	
  delineate	
  the	
  extent	
  and	
  
location	
  of	
  poaching	
  may	
  lead	
  managers	
  to	
  expend	
  limited	
  resources	
  combating	
  poaching	
  
in	
  areas	
  where	
  poaching	
  activities	
  are	
  low	
  at	
  the	
  expense	
  of	
  areas	
  where	
  poaching	
  may	
  be	
  
higher	
  (Knapp,	
  Rentsch,	
  Schmitt,	
  Lewis	
  &	
  Polasky,	
  2010).	
  	
  
	
  

	
  

58	
  

3.2.1.	
  Perception	
  of	
  poaching	
  risks.	
  	
  
Different	
  stakeholders,	
  whether	
  they	
  are	
  trained	
  experts	
  or	
  experienced	
  publics,	
  will	
  
think	
  about	
  risks	
  such	
  as	
  poaching	
  differently	
  (McFarlane,	
  2005).	
  	
  Experts'	
  technical	
  
estimates	
  about	
  the	
  probability	
  and	
  consequences	
  of	
  a	
  risk	
  are	
  termed	
  risk	
  assessments	
  
and	
  are	
  based	
  on	
  objective	
  measures	
  (Renn,	
  1992).	
  	
  Alternatively,	
  risk	
  perceptions	
  are	
  
intuitive	
  judgments	
  made	
  by	
  stakeholders	
  (Slovic,	
  1987)	
  and	
  may	
  be	
  informed	
  by	
  
subjective	
  measures	
  (e.g.,	
  outrage,	
  trust,	
  perceived	
  control	
  over	
  exposure)	
  (Slovic,	
  2000)	
  in	
  
addition	
  to	
  experiences	
  related	
  to	
  the	
  risk.	
  	
  Risk	
  perceptions	
  are	
  important	
  for	
  determining	
  
behavioral	
  intentions	
  (i.e.,	
  whether	
  a	
  stakeholder	
  plans	
  to	
  engage	
  in	
  a	
  behavior)	
  and	
  
support	
  for	
  management	
  actions	
  (Gore,	
  Knuth,	
  Curtis	
  &	
  Shanahan,	
  2006;	
  Knuth,	
  Stout,	
  
Siemer,	
  Decker	
  &	
  Stedman,	
  1992;	
  McFarlane,	
  2005;	
  Weber,	
  2006)	
  and	
  predicting	
  
compliance	
  with	
  natural	
  resource	
  laws	
  (Kuperan	
  &	
  Sutinen,	
  1998).	
  	
  	
  
Compliance	
  is	
  the	
  behavior	
  of	
  people	
  conforming	
  to	
  rules	
  that	
  were	
  created	
  to	
  
influence	
  their	
  actions	
  	
  (Hauck,	
  2008).	
  	
  Without	
  compliance,	
  rules	
  may	
  fail	
  to	
  achieve	
  
management	
  objectives	
  (Keane	
  et	
  al.,	
  2008).	
  	
  Diverse	
  management	
  interventions,	
  such	
  as	
  
provision	
  of	
  alternative	
  livelihood	
  options	
  (Kühl,	
  Balinova,	
  Bykova,	
  Arylov,	
  Esipov,	
  
Lushchekina	
  et	
  al.,	
  2009),	
  animal	
  damage	
  compensation	
  programs	
  (Bulte	
  &	
  Rondeau,	
  2007)	
  
and	
  educational	
  outreach	
  programs	
  (Eliason,	
  2003),	
  can	
  influence	
  stakeholders'	
  
willingness	
  and	
  ability	
  to	
  comply.	
  	
  The	
  effectiveness	
  of	
  these	
  interventions	
  are	
  dependent,	
  
in	
  part,	
  on	
  understanding	
  stakeholders'	
  motivations	
  for	
  engaging	
  in	
  an	
  activity	
  such	
  as	
  
poaching	
  (Kühl	
  et	
  al.,	
  2009;	
  Muth	
  &	
  Bowe,	
  2009)	
  and	
  their	
  risk	
  perceptions	
  associated	
  with	
  
the	
  illegal	
  activity	
  (Bell,	
  Hampshire	
  &	
  Topalidou,	
  2007).	
  	
  Spatial	
  analysis	
  of	
  poaching	
  risks	
  
has	
  led	
  to	
  greater	
  understanding	
  of	
  poachers’	
  motivations	
  and	
  more	
  effective	
  interventions	
  

	
  

59	
  

(Sánchez-­‐Mercado,	
  Ferrer-­‐Paris,	
  García-­‐Rangel	
  &	
  Rodríguez-­‐Clark,	
  2008)	
  yet	
  there	
  is	
  a	
  lack	
  
of	
  integration	
  between	
  stakeholders’	
  spatially-­‐explicit	
  risk	
  perceptions	
  and	
  experts’	
  
assessments	
  of	
  illegal	
  activities.	
  
3.2.2.	
  Stakeholder	
  motivations	
  to	
  poach.	
  
Stakeholders’	
  decisions	
  to	
  comply	
  with	
  poaching	
  rules	
  are	
  highly	
  complex	
  in	
  large	
  
part	
  because	
  of	
  the	
  diverse	
  economic,	
  geographic,	
  social,	
  and	
  psychological	
  contexts	
  within	
  
which	
  poaching	
  occurs	
  (Kuperan	
  &	
  Sutinen,	
  1998).	
  	
  Poaching	
  can	
  manifest	
  itself	
  in	
  a	
  variety	
  
of	
  ways,	
  from	
  an	
  individual	
  poaching	
  for	
  home	
  consumption	
  or	
  trade	
  in	
  a	
  local	
  market	
  
(Bassett,	
  2005)	
  to	
  commercial	
  poachers	
  selling	
  wildlife	
  trophies	
  in	
  international,	
  illegal	
  
markets	
  (Leader-­‐Williams	
  &	
  Milner-­‐Gulland,	
  1993).	
  	
  Animal	
  damage	
  incidents,	
  such	
  as	
  
livestock	
  depredation,	
  may	
  motivate	
  retaliatory	
  (Bulte	
  &	
  Rondeau,	
  2007)	
  or	
  preventative	
  
(e.g.,	
  setting	
  snares,	
  poison)	
  (Naughton,	
  1997)	
  poaching	
  among	
  affected	
  stakeholders.	
  	
  
Opportunistic	
  poaching	
  may	
  occur	
  due	
  to	
  chance	
  encounters	
  between	
  humans	
  and	
  wildlife	
  
in	
  the	
  landscape	
  (Sánchez-­‐Mercado	
  et	
  al.,	
  2008)	
  or	
  be	
  related	
  to	
  unemployment	
  (Knapp,	
  
2007).	
  	
  
Poaching	
  incidents	
  may	
  not	
  always	
  be	
  the	
  result	
  of	
  intentional	
  violations	
  of	
  wildlife	
  
law,	
  such	
  as	
  incidents	
  where	
  hunters	
  are	
  unaware	
  of	
  regulations	
  (Sethi	
  &	
  Hilborn,	
  2008).	
  
Poaching	
  is	
  not	
  always	
  driven	
  by	
  economic	
  necessity	
  (Bell	
  et	
  al.,	
  2007).	
  	
  For	
  example,	
  
poaching	
  may	
  manifest	
  as	
  an	
  act	
  of	
  social	
  defiance	
  or	
  symbolic	
  protest	
  of	
  local	
  natural	
  
resource	
  management	
  practices	
  (Bell	
  et	
  al.,	
  2007)	
  or	
  as	
  an	
  act	
  of	
  rebellion	
  towards	
  specific	
  
laws	
  or	
  local	
  authority	
  (Muth	
  &	
  Bowe,	
  1998).	
  	
  Many	
  poachers	
  likely	
  have	
  multiple	
  
motivations	
  for	
  engaging	
  in	
  illegal	
  behavior	
  (Bassett,	
  2005).	
  	
  Characterizing	
  stakeholders'	
  
motivations	
  to	
  comply	
  with	
  wildlife	
  poaching	
  rules	
  can	
  guide	
  management	
  decisions	
  and	
  

	
  

60	
  

aid	
  in	
  designing	
  responses	
  aimed	
  at	
  reducing	
  illegal	
  activity	
  (Hampshire	
  et	
  al.,	
  2004;	
  Kühl	
  
et	
  al.,	
  2009;	
  Muth	
  &	
  Bowe,	
  1998).	
  	
  
3.2.3.	
  Management	
  interventions	
  to	
  increase	
  compliance.	
  
Risks	
  to	
  wildlife	
  from	
  poaching	
  can	
  be	
  addressed	
  through	
  a	
  variety	
  of	
  interventions	
  
intended	
  to	
  increase	
  compliance	
  and	
  reduce	
  poaching,	
  such	
  as	
  formal	
  legislative	
  
regulations	
  (Leader-­‐Williams	
  &	
  Milner-­‐Gulland,	
  1993);	
  informal,	
  locally	
  supported	
  rules	
  or	
  
agreements	
  (Kuperan	
  &	
  Sutinen,	
  1998);	
  provision	
  of	
  alternative	
  livelihood	
  options	
  (Kühl	
  et	
  
al.,	
  2009);	
  animal	
  damage	
  compensation	
  programs	
  (Bulte	
  &	
  Rondeau,	
  2007);	
  or	
  
educational	
  outreach	
  programs	
  (Eliason,	
  2003).	
  	
  Traditional	
  law	
  enforcement	
  
interventions,	
  such	
  as	
  increasing	
  detection	
  through	
  patrols	
  and	
  adjusting	
  penalties	
  to	
  
discourage	
  offenders,	
  can	
  also	
  reduce	
  or	
  prevent	
  poaching	
  (Leader-­‐Williams	
  &	
  Milner-­‐
Gulland,	
  1993).	
  	
  For	
  example,	
  increasing	
  the	
  intensity	
  of	
  anti-­‐poaching	
  patrolling	
  units,	
  
through	
  community	
  schemes	
  (e.g.	
  local	
  game	
  guards)	
  (Vaughn	
  &	
  Long,	
  2007)	
  or	
  state-­‐level	
  
authorities	
  (e.g.,	
  wildlife	
  officers),	
  has	
  shown	
  to	
  increase	
  offenders’	
  perceived	
  risk	
  of	
  being	
  
detected	
  and	
  lower	
  poaching	
  rates	
  in	
  a	
  variety	
  of	
  contexts	
  (Leader-­‐Williams	
  &	
  Milner-­‐
Gulland,	
  1993).	
  	
  
	
  In	
  addition	
  to	
  traditional	
  law	
  enforcement	
  frameworks	
  for	
  combating	
  poaching,	
  
normative	
  approaches	
  can	
  be	
  used	
  to	
  understand	
  compliance	
  and	
  evaluate	
  monitoring	
  and	
  
enforcement	
  interventions	
  (Keane	
  et	
  al.,	
  2008;	
  Kuperan	
  &	
  Sutinen,	
  1998).	
  	
  Normative	
  
factors	
  include	
  moral	
  obligations	
  (e.g.,	
  standards	
  of	
  personal	
  morality,	
  ethics),	
  social	
  
environmental	
  influences	
  (e.g.,	
  peer	
  opinion,	
  social	
  influence)	
  and	
  perceived	
  legitimacy	
  of	
  
laws	
  implemented	
  by	
  authorities	
  (e.g.,	
  procedural	
  fairness,	
  perceptions	
  of	
  how	
  just	
  the	
  
laws	
  are)	
  (Kuperan	
  &	
  Sutinen,	
  1998).	
  	
  For	
  example,	
  Eliason	
  (2003)	
  proposed	
  increasing	
  the	
  

	
  

61	
  

discourse	
  and	
  content	
  related	
  to	
  hunting	
  ethics	
  in	
  hunters’	
  education	
  courses	
  as	
  a	
  means	
  to	
  
reduce	
  poaching	
  and	
  increase	
  the	
  likelihood	
  of	
  poaching	
  being	
  treated	
  as	
  a	
  serious	
  offense	
  
by	
  hunters.	
  	
  
	
  

The	
  spatial	
  vulnerability	
  of	
  wildlife	
  to	
  poaching	
  is	
  another	
  key	
  dimension	
  for	
  

monitoring	
  and	
  enforcement	
  efforts	
  that	
  can	
  contribute	
  to	
  increased	
  compliance	
  with	
  rules	
  
(Sánchez-­‐Mercado	
  et	
  al.,	
  2008).	
  	
  The	
  spatial	
  vulnerability	
  of	
  wildlife	
  to	
  poaching	
  varies	
  
according	
  to	
  the	
  distribution	
  of	
  human	
  and	
  wildlife	
  populations,	
  their	
  overlap	
  in	
  the	
  
landscape	
  (Jachmann,	
  2008;	
  Knapp	
  et	
  al.,	
  2010),	
  and	
  the	
  distribution	
  of	
  limiting	
  resources	
  
such	
  as	
  water	
  (O’Connell-­‐Rodwell,	
  Rodwell,	
  Rice	
  &	
  Hart,	
  2000).	
  	
  Poaching	
  pressure	
  may	
  be	
  
lower	
  for	
  wildlife	
  that	
  occur	
  in	
  remote	
  areas	
  with	
  difficult-­‐to-­‐access	
  terrain	
  because	
  the	
  
landscape	
  can	
  increase	
  the	
  effort	
  needed	
  to	
  successfully	
  poach	
  (Wilkie,	
  Shaw,	
  Rotberg,	
  
Morelli	
  &	
  Auzel,	
  2000).	
  	
  Conversely,	
  deterrence	
  activities	
  (e.g.,	
  patrolling)	
  and	
  detection	
  
rates	
  for	
  poaching	
  in	
  remote	
  areas	
  is	
  often	
  lower	
  than	
  easy-­‐to-­‐access	
  areas,	
  which	
  may	
  
result	
  in	
  increased	
  poaching	
  activity	
  in	
  those	
  areas	
  (Knapp	
  et.	
  al.,	
  2010).	
  
Ultimately,	
  knowledge	
  related	
  to	
  the	
  diversity	
  of	
  local	
  poachers’	
  motivations	
  
(Sánchez-­‐Mercado	
  et	
  al.,	
  2008),	
  the	
  cultural	
  context	
  of	
  poaching	
  (Hampshire	
  et	
  al.,	
  2004),	
  
local	
  poaching-­‐related	
  economic	
  conditions	
  (e.g.,	
  market	
  prices	
  for	
  poached	
  species)	
  
(Leader-­‐Williams	
  &	
  Milner-­‐Gulland,	
  1993),	
  law	
  enforcement	
  capacity	
  (Robinson	
  &	
  Bennet,	
  
2004),	
  and	
  the	
  context	
  of	
  human-­‐wildlife	
  interactions	
  (Sánchez-­‐Mercado	
  et	
  al.,	
  2008)	
  
should	
  guide	
  the	
  choice	
  between	
  management	
  interventions	
  aimed	
  at	
  increasing	
  
compliance.	
  	
  Importantly,	
  such	
  choices	
  between	
  management	
  interventions	
  must	
  be	
  
informed	
  by	
  empirical	
  data	
  about	
  these	
  local	
  conditions	
  (Eliason,	
  2003).	
  	
  Given	
  the	
  
contextual	
  and	
  spatial	
  complexity	
  of	
  poaching,	
  it	
  is	
  unlikely	
  that	
  one	
  approach	
  (e.g.,	
  only	
  

	
  

62	
  

increasing	
  patrolling	
  or	
  adjusting	
  fines	
  and	
  penalties)	
  will	
  suffice	
  to	
  greatly	
  alter	
  local	
  
compliance	
  rates.	
  	
  
3.2.4.	
  Poaching	
  in	
  Namibia’s	
  conservancy	
  system.	
  
In	
  1996,	
  the	
  government	
  of	
  Namibia	
  launched	
  a	
  CBNRM	
  program,	
  devolving	
  rights	
  
over	
  wildlife	
  to	
  local	
  communities	
  (Barnes,	
  MacGregor	
  &	
  Weaver,	
  2002).	
  	
  Key	
  features	
  of	
  
the	
  CBNRM-­‐based	
  conservancy	
  system	
  include:	
  1)	
  collaboration	
  between	
  government	
  
agencies,	
  national	
  non-­‐governmental	
  organizations	
  (NGOs)	
  and	
  rural	
  communities	
  living	
  
on	
  communal	
  land	
  (Stuart-­‐Hill,	
  Diggle,	
  Munali,	
  Tagg	
  &	
  Ward,	
  2005);	
  2)	
  a	
  legislative	
  basis	
  
for	
  consumptive	
  wildlife	
  utilization	
  (e.g.,	
  subsistence	
  and	
  commercial	
  hunting),	
  and;	
  3)	
  
wildlife	
  damage	
  management	
  procedures	
  (Ministry	
  of	
  Environment	
  &	
  Tourism	
  (MET),	
  
2009).	
  	
  Namibians	
  residing	
  in	
  conservancies	
  directly	
  benefit	
  from	
  the	
  consumptive	
  use	
  of	
  
wildlife	
  and	
  integrate	
  wildlife	
  into	
  local	
  economic	
  development	
  (Barnes	
  et	
  al.,	
  2002);	
  
theoretically,	
  conservancies	
  and	
  their	
  residents	
  have	
  a	
  vested	
  interest	
  to	
  insure	
  that	
  
wildlife	
  use	
  is	
  sustainable.	
  	
  
Poaching	
  in	
  Namibia	
  was	
  unsustainably	
  high	
  in	
  the	
  1980s	
  and	
  early	
  1990s	
  (Nott	
  &	
  
Jacobsohn,	
  2004).	
  	
  Exacerbated	
  by	
  drought	
  and	
  volatile	
  periods	
  of	
  political	
  instability	
  
(Bruchmann,	
  2002;	
  Vaughan	
  &	
  Long,	
  2007),	
  poaching	
  threatened	
  to	
  virtually	
  exterminate	
  
populations	
  of	
  Black	
  rhino	
  (Diceros	
  bicornis)	
  and	
  African	
  elephants	
  (Loxodonta	
  africana)	
  in	
  
the	
  northwestern	
  regions	
  (Nott	
  &	
  Jacobsohn,	
  2004),	
  and	
  wildlife	
  numbers	
  in	
  the	
  north	
  
central	
  and	
  eastern	
  regions	
  of	
  Namibia	
  declined	
  as	
  well	
  (Jones,	
  2003).	
  	
  In	
  Caprivi,	
  northeast	
  
Namibia,	
  South	
  African	
  Defense	
  Force	
  personnel	
  poached	
  heavily	
  in	
  previously	
  declared	
  
reserves	
  leaving	
  wildlife	
  populations	
  in	
  the	
  region	
  greatly	
  reduced	
  at	
  the	
  time	
  Namibia	
  
achieved	
  independence	
  (Bruchmann,	
  2002).	
  	
  Poaching	
  levels	
  decreased	
  after	
  independence	
  

	
  

63	
  

in	
  1990	
  (Nott	
  &	
  Jacobsohn,	
  2004)	
  and	
  Namibia’s	
  expanding	
  conservancy	
  system	
  has	
  been	
  
credited	
  with	
  contributing	
  to	
  this	
  reduction	
  (Vaughn	
  &	
  Long,	
  2007).	
  	
  Each	
  Namibian	
  
conservancy	
  is	
  charged	
  with	
  monitoring	
  poaching	
  incidents	
  in	
  their	
  conservancies	
  using	
  a	
  
system	
  developed	
  for	
  community-­‐based	
  monitoring	
  called	
  the	
  “Event	
  Book”	
  (Stuart-­‐Hill	
  et	
  
al.,	
  2005).	
  	
  Community	
  game	
  guards	
  are	
  hired,	
  trained	
  and	
  deployed	
  on	
  regular	
  patrols	
  in	
  
each	
  registered	
  conservancy	
  (Vaughn	
  &	
  Long,	
  2007).	
  Game	
  guards	
  enter	
  their	
  findings	
  into	
  
Event	
  Books.	
  
Jones	
  and	
  Barnes	
  (2006)	
  asserted	
  poaching	
  does	
  not	
  currently	
  appear	
  to	
  threaten	
  
populations	
  of	
  the	
  many	
  commonly	
  implicated	
  problem	
  species	
  (e.g.,	
  elephant,	
  lion)	
  (see	
  
Appendix	
  F	
  for	
  resident	
  and	
  Event	
  book	
  species-­‐specific	
  information).	
  	
  However,	
  they	
  also	
  
(ibid)	
  cautioned	
  that	
  positive	
  local	
  attitudes	
  toward	
  wildlife	
  could	
  be	
  undermined	
  by	
  
increasing	
  perceptions	
  of	
  risks	
  from	
  wildlife	
  conflicts,	
  particularly	
  in	
  the	
  Caprivi	
  region,	
  
potentially	
  resulting	
  in	
  increased	
  poaching.	
  	
  Indeed,	
  Caprivi	
  boasts	
  high	
  human	
  (Jones	
  &	
  
Barnes,	
  2006)	
  and	
  wildlife	
  (O’Connell-­‐Rodwell	
  et	
  al.,	
  2000)	
  population	
  densities,	
  is	
  one	
  of	
  
Namibia’s	
  poorest	
  regions	
  (Suich,	
  2010)	
  and	
  has	
  the	
  highest	
  incident	
  rates	
  of	
  human	
  
wildlife	
  conflicts	
  (Jones	
  &	
  Barnes,	
  2006;	
  O’Connell-­‐Rodwell	
  et	
  al.,	
  2000)	
  (refer	
  to	
  chapter	
  1	
  
for	
  more	
  information	
  on	
  Caprivi).	
  	
  	
  
3.3.	
  METHODS	
  
3.3.1.	
  Study	
  location.	
   	
  
Two	
  conservancies	
  in	
  East	
  Caprivi’s	
  Mudumu	
  South	
  Complex	
  6,	
  Wuparo	
  and	
  Dzoti,	
  
were	
  selected	
  for	
  this	
  research	
  based	
  on	
  the:	
  1)	
  recommendation	
  of	
  local	
  and	
  regional	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
6	
  Mudumu	
  South	
  Complex	
  (MSC)	
  is	
  a	
  geographically	
  clustered	
  group	
  of	
  conservancies	
  with	
  
similar	
  environmental,	
  economic	
  and	
  cultural	
  features.	
  	
  MSC	
  can	
  interact	
  with	
  agencies	
  and	
  
	
  

64	
  

NGOs	
  with	
  a	
  long-­‐term	
  presence	
  in	
  the	
  region,	
  2)	
  permission	
  of	
  relevant	
  traditional	
  
authorities,	
  3)	
  willingness	
  of	
  conservancies	
  to	
  participate,	
  4)	
  comparability	
  of	
  
conservancies	
  based	
  on	
  similar	
  habitat	
  types	
  and	
  wildlife	
  species	
  composition,	
  and	
  5)	
  
presence	
  of	
  poaching	
  and	
  animal	
  damage	
  records.	
  	
  These	
  conservancies	
  are	
  contiguous	
  in	
  
the	
  landscape,	
  located	
  between	
  two	
  national	
  parks,	
  and	
  share	
  a	
  boundary	
  with	
  the	
  Kwando	
  
River	
  (Table	
  3.1).	
  
3.3.2.	
  Data	
  Collection.	
  
	
  
This	
  research	
  used	
  focus	
  groups	
  (Morgan,	
  1993)	
  and	
  secondary	
  data	
  analysis	
  (Aust,	
  
Boyle,	
  Fergusson	
  &	
  Coulson,	
  2009)	
  from	
  Event	
  Books	
  in	
  two	
  conservancies.	
  Focus	
  groups	
  
were	
  used	
  to	
  elicit	
  information	
  about	
  stakeholders’	
  perceptions	
  of	
  poaching	
  risks,	
  
motivations,	
  and	
  perceived	
  location	
  of	
  poaching	
  events	
  (Bell	
  et	
  al.,	
  2007)	
  because	
  direct	
  
questioning	
  related	
  to	
  sensitive	
  subjects	
  (e.g.,	
  illegal	
  activities)	
  may	
  generate	
  mistrust	
  and	
  
concealment	
  from	
  respondents	
  (Solomon	
  et	
  al.,	
  2007).	
  	
  Event	
  Book	
  data	
  from	
  2003	
  to	
  2008	
  
were	
  acquired	
  with	
  permission	
  from	
  the	
  Dzoti	
  and	
  Wuparo	
  Conservancy	
  offices	
  and	
  were	
  
used	
  to	
  assess	
  poaching	
  risks.	
  
Focus	
  groups.	
  Focus	
  group	
  participants	
  were	
  all	
  permanent	
  residents	
  of	
  their	
  
respective	
  conservancies	
  and	
  ≥18	
  years	
  old.	
  No	
  person	
  was	
  excluded	
  from	
  participating	
  
based	
  on	
  ethnic	
  affiliation,	
  educational	
  attainment,	
  or	
  socio-­‐economic	
  status.	
  	
  Only	
  one	
  
person	
  per	
  household	
  was	
  eligible	
  to	
  participate.	
  Participants	
  were	
  solicited	
  from	
  each	
  of	
  
the	
  village	
  zones	
  (i.e.,	
  distinct	
  residential	
  areas)	
  in	
  proportion	
  to	
  that	
  village	
  zone's	
  
population	
  using	
  a	
  cluster	
  sampling	
  technique	
  with	
  probability	
  proportionate	
  to	
  size	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
organizations	
  as	
  a	
  larger	
  management	
  body,	
  negotiate	
  for	
  translocation	
  of	
  wildlife	
  into	
  the	
  
area,	
  resolve	
  disputes	
  and	
  pursue	
  economic	
  development	
  projects.	
  

	
  

65	
  

(Bernard,	
  2006)	
  (see	
  Chapter	
  2	
  for	
  sampling	
  protocol	
  methodology).	
  	
  Each	
  conservancy’s	
  
staff	
  provided	
  census-­‐type	
  information	
  (e.g.,	
  number	
  of	
  households,	
  approximate	
  
population)	
  about	
  their	
  village	
  zones	
  to	
  facilitate	
  sampling.	
  Six	
  research	
  assistants	
  were	
  
selected	
  and	
  trained	
  to	
  aid	
  facilitation	
  of	
  focus	
  group	
  activities	
  (see	
  Chapter	
  2	
  for	
  research	
  
assistant	
  selection	
  and	
  training	
  criteria).	
  
Each	
  conservancy	
  completed	
  an	
  identical	
  two-­‐day	
  focus	
  group	
  (see	
  Appendix	
  A	
  for	
  
focus	
  group	
  protocol).	
  Participants	
  were	
  divided	
  into	
  groups	
  (e.g.,	
  men,	
  women,	
  and	
  male	
  
and	
  female	
  decision-­‐makers)	
  to	
  promote	
  a	
  non-­‐threatening,	
  permissive	
  environment	
  for	
  
dialogue	
  (Morgan,	
  1993;	
  Smith,	
  Barrett	
  &	
  Box,	
  2000).	
  	
  Each	
  group	
  engaged	
  in	
  	
  participatory	
  
risk	
  ranking	
  and	
  scoring	
  (PRRS)	
  (Baird,	
  Leslie	
  &	
  McCabe,	
  2009;	
  Quinn,	
  Huby,	
  Kiwasila	
  &	
  
Lovett,	
  2003;	
  Smith	
  et	
  al.,	
  2000;	
  Tschakert,	
  2007)	
  and	
  participant	
  risk	
  mapping	
  (PRM)	
  
(Treves	
  et	
  al.,	
  2006)	
  activities.	
  	
  PRRS	
  is	
  useful	
  for	
  documenting	
  stakeholders'	
  risk	
  
perceptions	
  in	
  a	
  way	
  that	
  allows	
  participants	
  to	
  self-­‐generate	
  and	
  prioritize	
  major	
  risk	
  
themes	
  while	
  not	
  constraining	
  discussion	
  about	
  risks	
  to	
  researcher-­‐defined	
  concepts	
  
(Smith	
  et	
  al.,	
  2000).	
  Participants	
  conducted	
  the	
  PRRS	
  process	
  for	
  two	
  risk	
  targets:	
  local	
  
livelihoods	
  and	
  conservancy	
  wildlife.	
  	
  
After	
  participants	
  completed	
  PRRS	
  activities	
  they	
  began	
  PRM	
  activities.	
  	
  Participants	
  
mapped	
  the	
  perceived	
  location	
  and	
  frequency	
  of	
  poaching	
  activities	
  onto	
  transparent	
  
overlays	
  secured	
  over	
  "basemaps"	
  created	
  by	
  the	
  lead	
  researcher	
  and	
  assistants.	
  	
  During	
  
PRM	
  participants:	
  1)	
  identified	
  important	
  local	
  features	
  (e.g.,	
  community	
  resources,	
  rivers)	
  
on	
  the	
  map,	
  2)	
  added	
  any	
  features	
  absent	
  on	
  the	
  basemap,	
  and	
  3)	
  mapped	
  where	
  and	
  with	
  
what	
  intensity	
  risks	
  identified	
  from	
  PRRS	
  (e.g.,	
  poaching,	
  crop	
  damage)	
  took	
  place.	
  	
  Risks	
  
were	
  ranked	
  according	
  to	
  the	
  intensity	
  of	
  occurrence	
  (rarely	
  (1-­‐5	
  times	
  a	
  year);	
  sometimes	
  

	
  

66	
  

(6-­‐12	
  times	
  a	
  year);	
  often	
  (more	
  than	
  12	
  times	
  a	
  year)	
  (Treves	
  et	
  al.,	
  2006).	
  	
  Finally,	
  each	
  
group	
  discussed	
  motivations	
  for	
  poaching.	
  	
  Participants	
  free-­‐listed	
  motivations	
  and	
  then	
  
rank-­‐ordered	
  them	
  from	
  the	
  most	
  to	
  the	
  least	
  prevalent.	
  
Event	
  Book.	
  Digital	
  photographs	
  for	
  six	
  years	
  (2003	
  through	
  2008)	
  of	
  Problem	
  
Animal	
  Incident	
  (PAI)	
  and	
  Poaching	
  Event	
  (PE)	
  cards	
  were	
  aquired	
  from	
  each	
  conservancy	
  
and	
  transcribed.	
  PAI	
  cards	
  included	
  information	
  about	
  the	
  incident	
  date,	
  damage	
  type	
  (e.g.,	
  
crops,	
  livestock,	
  human	
  attack),	
  specific	
  crop	
  or	
  livestock	
  type,	
  number	
  of	
  livestock	
  or	
  
humans	
  attacked	
  (if	
  applicable),	
  wildlife	
  species	
  implicated,	
  descriptive	
  notes	
  and	
  location	
  
within	
  a	
  4	
  km2	
  grid	
  cell.	
  PE	
  cards	
  included	
  information	
  about	
  the	
  date,	
  species	
  affected	
  (if	
  
applicable),	
  number	
  of	
  animals	
  involved	
  in	
  the	
  incident,	
  type	
  of	
  incident	
  (e.g.,	
  firearm,	
  
snare,	
  traditional)	
  7,	
  number	
  of	
  incidents,	
  descriptive	
  notes	
  and	
  location.	
  	
  
3.3.3.	
  Data	
  Analysis.	
  
Participatory	
  risk	
  ranking	
  and	
  scoring.	
  Coding	
  of	
  free-­‐listed	
  risks	
  generated	
  during	
  
the	
  PRRS	
  activity	
  followed	
  an	
  iterative	
  process	
  (Bernard,	
  2006).	
  First,	
  I	
  reviewed	
  all	
  risks	
  
to	
  generate	
  categories	
  (Saldaña,	
  2009).	
  	
  Next,	
  I	
  assigned	
  each	
  risk	
  into	
  a	
  category	
  and	
  coded	
  
each	
  risk	
  into	
  an	
  exclusive	
  categorical	
  variable	
  (Bernard,	
  2006).	
  I	
  conducted	
  a	
  final	
  
iteration	
  of	
  coding	
  to	
  double-­‐check	
  findings	
  (Saldaña,	
  2009)	
  (see	
  Appendix	
  D	
  for	
  coding	
  
protocol).	
  	
  
Following	
  Tschakert’s	
  (2007)	
  methods	
  for	
  PRRS	
  analysis,	
  I	
  calculated	
  an	
  incident	
  
index	
  (I),	
  importance	
  index	
  (Pj),	
  joint	
  risk	
  index	
  (Rj)	
  and	
  severity	
  index	
  (Sj)	
  for	
  each	
  
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
7	
  The	
  conservancies	
  define	
  the	
  designation	
  of	
  firearm,	
  snare	
  and	
  traditional	
  poaching	
  
incidents.	
  	
  Traditional	
  incidents	
  include	
  poaching	
  by	
  means	
  of	
  traditional	
  methods	
  such	
  as	
  
spears,	
  bows	
  and	
  arrows,	
  and	
  traps.	
  

	
  

67	
  

livelihood	
  and	
  wildlife-­‐related	
  risk.	
  	
  The	
  incident	
  index	
  (I),	
  ranging	
  from	
  0	
  to	
  1,	
  is	
  the	
  
proportion	
  of	
  participants	
  that	
  identified	
  a	
  particular	
  risk.	
  The	
  importance	
  index	
  (Pj)	
  also	
  
ranges	
  from	
  0	
  to	
  1	
  (0=not	
  important;	
  1=most	
  important)	
  and	
  reflects	
  the	
  rank	
  that	
  
participants	
  assigned	
  to	
  a	
  particular	
  risk	
  in	
  relation	
  to	
  the	
  total	
  number	
  of	
  risks	
  they	
  listed,	
  
where	
  r	
  is	
  the	
  rank	
  and	
  n	
  the	
  total	
  number	
  of	
  risks	
  identified	
  by	
  that	
  participant:	
  
	
  

# (r "1) &
Pj = %
( ) ("1) +1
$ (n "1) '

	
  

!

	
  The	
  joint	
  risk	
  index	
  (Rj)	
  is	
  a	
  function	
  of	
  a	
  risks'	
  average	
  incident	
  index	
  score	
  (Ij)	
  and	
  
average	
  importance	
  index	
  score	
  (Pj).	
  	
  The	
  joint	
  risk	
  index	
  ranges	
  from	
  0	
  to	
  1	
  and	
  is	
  

!

calculated	
  as	
  Rj=	
  Ij/	
  (2-­‐Pj).	
  	
  Finally,	
  the	
  severity	
  index	
  (Sj)	
  represents	
  the	
  mean	
  severity	
  
score	
  assigned	
  to	
  each	
  risk	
  by	
  participants	
  that	
  mentioned	
  that	
  risk	
  and	
  ranges	
  from	
  0	
  to	
  5	
  
(0=not	
  severe;	
  5=most	
  severe).	
  	
  An	
  incident	
  index	
  (Ij),	
  importance	
  index	
  (Pj)	
  and	
  joint	
  risk	
  
index	
  (Rj)	
  were	
  calculated	
  for	
  all	
  the	
  poaching	
  motivations	
  identified	
  by	
  participants	
  during	
  
the	
  PRRS	
  activity.	
  
	
  

Participatory	
  risk	
  mapping.	
  	
  Digital	
  photographs	
  of	
  participants'	
  maps	
  were	
  overlaid	
  

and	
  rectified	
  with	
  georeferenced	
  conservancy	
  boundary	
  layers	
  (CONINFO,	
  2009)	
  using	
  
ArcGIS	
  9.2	
  (Environmental	
  Systems	
  Research	
  Institute,	
  2004).	
  	
  Participants’	
  maps	
  
contained	
  discrete	
  locations	
  (e.g.,	
  villages,	
  schools),	
  linear	
  features	
  (e.g.,	
  roads,	
  rivers),	
  and	
  
risk	
  points,	
  lines,	
  and	
  polygons.	
  	
  Risk	
  features	
  (e.g.,	
  poaching,	
  crop	
  damage)	
  that	
  were	
  
initially	
  drawn	
  as	
  polygons	
  by	
  participants	
  were	
  converted	
  to	
  patches	
  of	
  points	
  (10	
  m	
  
spacing).	
  	
  Line	
  features	
  were	
  similarly	
  converted	
  to	
  points.	
  	
  The	
  risk	
  points	
  were	
  combined	
  
to	
  form	
  a	
  single	
  risk	
  point	
  layer.	
  	
  Subsequently,	
  the	
  distance	
  from	
  each	
  location	
  (10	
  m	
  
spacing)	
  within	
  the	
  conservancy	
  boundaries	
  to	
  the	
  closest	
  risk	
  point	
  was	
  measured.	
  	
  A	
  

	
  

68	
  

separate	
  distance	
  layer	
  was	
  generated	
  for	
  each	
  intensity	
  of	
  occurrence	
  score	
  (ranging	
  from	
  
1-­‐3).	
  	
  	
  Distance	
  layers	
  were	
  interpolated	
  using	
  an	
  inverse	
  distance	
  weighted	
  (IDW)	
  method	
  
resulting	
  in	
  continuous	
  surfaces	
  (10	
  m	
  resolution)	
  of	
  distance	
  to	
  nearest	
  threat	
  point	
  by	
  
risk	
  intensity	
  (Childs,	
  2004).	
  	
  The	
  interpolated	
  surfaces	
  were	
  subsequently	
  combined,	
  
weighted	
  by	
  perceived	
  risk	
  intensity	
  (high,	
  moderate,	
  low),	
  into	
  a	
  single	
  risk	
  surface.	
  	
  	
  	
  	
  	
  	
  	
  
	
  

Event	
  Book.	
  	
  Event	
  Book	
  poaching	
  data	
  from	
  each	
  conservancy	
  was	
  pooled	
  and	
  

analyzed	
  by	
  year	
  and	
  incident	
  type	
  using	
  descriptive	
  statistics.	
  	
  Locations	
  (4	
  km2)	
  from	
  the	
  
PAI	
  and	
  PE	
  cards	
  were	
  overlaid	
  on	
  the	
  interpolated	
  participant	
  maps	
  in	
  ArcGIS.	
  	
  
3.4.	
  RESULTS	
  
Fifty	
  local	
  stakeholders	
  participated	
  in	
  PRRS	
  and	
  PRM	
  activities	
  with	
  livelihoods	
  as	
  
the	
  risk	
  target	
  and	
  48	
  stakeholders	
  completed	
  the	
  activities	
  with	
  wildlife	
  as	
  the	
  risk	
  target.	
  	
  
Participants	
  ranged	
  in	
  educational	
  background	
  from	
  no	
  formal	
  schooling	
  to	
  college	
  
education,	
  age	
  (18-­‐60+	
  years),	
  and	
  all	
  participated	
  in	
  some	
  form	
  of	
  subsistence	
  based	
  
activities	
  or	
  rural	
  industries	
  (e.g.,	
  artisanal	
  fisheries,	
  vegetable	
  farming,	
  thatch	
  roof	
  
harvesting).	
  
3.4.1.	
  Perceived	
  poaching	
  risk.	
  	
  	
  
Participants	
  generated	
  a	
  total	
  of	
  157	
  risks	
  to	
  wildlife	
  (3.3	
  threats	
  per	
  participant	
  
average;	
  range	
  1-­‐9)	
  that	
  were	
  coded	
  into	
  14	
  categories.	
  	
  Participants	
  identified	
  eight	
  of	
  14	
  
risks	
  to	
  wildlife	
  as	
  being	
  anthropogenic	
  (i.e.,	
  resulting	
  from	
  human	
  activity).	
  	
  Three	
  of	
  these	
  
anthropogenic	
  risks	
  were	
  direct	
  forms	
  of	
  mortality:	
  poaching	
  (i.e.,	
  illegal	
  hunting	
  or	
  
trapping),	
  legal	
  hunting	
  (i.e.,	
  commercial,	
  trophy,	
  subsistence)	
  and	
  retaliation	
  (i.e.,	
  legal	
  or	
  
illegal	
  lethal	
  removal	
  for	
  damage).	
  	
  Participants	
  ranked	
  poaching	
  (Rj=	
  0.37;	
  Sj=	
  3.5)	
  as	
  the	
  
most	
  critical	
  anthropological	
  risk	
  and	
  the	
  second	
  most	
  critical	
  risk	
  overall	
  (Table	
  3.2).	
  	
  Over	
  
	
  

69	
  

half	
  of	
  all	
  participants	
  (Ij=0.52)	
  cited	
  poaching	
  as	
  a	
  risk	
  to	
  conservancy	
  wildlife	
  and	
  
poaching	
  ranked	
  as	
  the	
  most	
  severe	
  threat	
  to	
  wildlife	
  (Table	
  3.2).	
  	
  
3.4.2.	
  Assessed	
  poaching	
  risk.	
  	
  	
  
Fifty-­‐three	
  discrete	
  poaching	
  events	
  were	
  recorded	
  between	
  2001-­‐2008	
  in	
  the	
  
Event	
  Books,	
  of	
  which	
  62%	
  were	
  snares,	
  28%	
  firearms,	
  and	
  9%	
  traditional	
  methods	
  
(Figure	
  3.1).	
  	
  Game	
  guards	
  collected	
  147	
  snares	
  in	
  study	
  conservancies	
  during	
  this	
  time;	
  
there	
  was	
  a	
  peak	
  in	
  snares	
  collected	
  in	
  2007	
  (n=67).	
  More	
  than	
  95%	
  of	
  documented	
  
poaching	
  incidents	
  have	
  occured	
  since	
  2006	
  (Figure	
  3.1);	
  alone,	
  these	
  data	
  suggest	
  an	
  
increase	
  in	
  poaching,	
  particularly	
  in	
  the	
  use	
  of	
  illegal	
  snares,	
  since	
  2005.	
  	
  	
  	
  
3.4.3.	
  Poaching	
  motivations.	
  	
  
	
  Participants	
  identified	
  14	
  motivations	
  to	
  poach	
  (Table	
  3.3).	
  The	
  top	
  two	
  poaching	
  
motivations	
  were,	
  income	
  generation	
  (Rj=	
  0.48)	
  and	
  food	
  (Rj=	
  0.47).	
  Income	
  generation	
  
and	
  food	
  were	
  perceived	
  as	
  nearly	
  twice	
  as	
  prevalent	
  a	
  motivation	
  to	
  poach	
  than	
  protecting	
  
fields	
  (Rj=0.24)	
  (Table	
  3.3).	
  Three	
  motivations	
  to	
  poach	
  were	
  driven	
  by	
  retaliation	
  
(protecting	
  fields,	
  protecting	
  human	
  lives	
  and	
  protecting	
  livestock)	
  and	
  were	
  of	
  particular	
  
importance	
  to	
  study	
  participants.	
  Retaliation	
  was	
  identified	
  as	
  being	
  an	
  important	
  threat	
  to	
  
wildlife	
  (Table	
  3.2).	
  	
  Protecting	
  livestock	
  and	
  human	
  lives	
  ranked	
  low	
  among	
  all	
  
motivations	
  to	
  poach,	
  yet	
  protecting	
  agricultural	
  fields	
  was	
  important.	
  	
  Two	
  poaching	
  
motivations	
  provided	
  by	
  participants	
  were	
  related	
  to	
  conservancy	
  management	
  and	
  
services:	
  protesting	
  conservancy	
  regulations	
  or	
  establishment	
  and	
  lack	
  of	
  conservancy	
  
benefits.	
  	
  Firearm	
  training	
  and	
  entertainment	
  were	
  also	
  cited	
  as	
  motivations	
  for	
  poaching	
  
in	
  the	
  conservancies	
  (Table	
  3.3).	
  	
  	
  
	
  

	
  

70	
  

3.4.4.	
  Co-­mapping	
  assessed	
  and	
  perceived	
  poaching	
  risks.	
  	
  	
  
Participants	
  created	
  6	
  maps	
  for	
  the	
  wildlife-­‐as-­‐risk	
  target.	
  	
  All	
  mapped	
  poaching	
  as	
  a	
  
risk	
  to	
  wildlife	
  and	
  livestock	
  loss,	
  crop	
  damage	
  and	
  wildlife	
  attack	
  as	
  threats	
  to	
  local	
  
livelihoods	
  (see	
  Appendix	
  G	
  for	
  additional	
  maps).	
  There	
  was	
  little	
  spatial	
  overlap	
  between	
  
the	
  PRM-­‐generated	
  (hereafter	
  perceived)	
  and	
  Event	
  Book-­‐generated	
  (hereafter	
  assessed)	
  
poaching	
  maps	
  (Figure	
  3.2).	
  Assessed	
  poaching	
  risk	
  maps	
  indicated	
  poaching	
  events	
  were	
  
primarily	
  concentrated	
  around	
  residential	
  areas	
  and	
  along	
  main	
  roads	
  (Figure	
  3.2).	
  
Perceived	
  poaching	
  risk	
  maps	
  depicted	
  the	
  highest	
  levels	
  of	
  poaching	
  at	
  the	
  southern	
  
conservancy	
  boundaries	
  near	
  Mamili	
  NP,	
  the	
  northern	
  boundary	
  near	
  Mudumu	
  NP	
  and	
  east	
  
of	
  Mudumu	
  NP	
  (Figure	
  3.2);	
  those	
  areas	
  also	
  had	
  the	
  highest	
  perceived	
  occurrence	
  of	
  
wildlife.	
  	
  Participants	
  in	
  Dzoti	
  conservancy	
  (Figure	
  3.2)	
  identified	
  highest	
  levels	
  of	
  poaching	
  
as	
  occurring	
  within	
  the	
  residential	
  zones	
  south	
  of	
  the	
  main	
  road.	
  	
  Perceived	
  poaching	
  risks	
  
were	
  lowest	
  near	
  the	
  southeastern	
  boundary	
  with	
  the	
  Kwando	
  River	
  (Figure	
  3.2).	
  	
  	
  
	
  

Perceived	
  risk	
  maps	
  for	
  livestock	
  loss,	
  crop	
  damage	
  and	
  humans	
  attacked	
  by	
  wildlife	
  

were	
  combined	
  into	
  a	
  single	
  map	
  representing	
  wildlife	
  vulnerability	
  to	
  poaching	
  motivated	
  
by	
  retaliation	
  (Figure	
  3.3).	
  The	
  perceived	
  risk	
  of	
  wildlife	
  attack	
  on	
  humans	
  and	
  livelihood	
  
damage	
  (hereafter	
  perceived	
  retaliation	
  risk)	
  was	
  highest	
  near	
  residential	
  areas	
  and	
  along	
  
roads	
  and	
  trails	
  with	
  the	
  exception	
  of	
  high-­‐perceived	
  retaliation	
  risk	
  along	
  the	
  southwest	
  
portion	
  of	
  the	
  shared	
  conservancy	
  boundary	
  (Figure	
  3.3).	
  	
  There	
  was	
  a	
  high	
  level	
  of	
  overlap	
  
between	
  the	
  assessed	
  poaching	
  risk	
  and	
  perceived	
  retaliation	
  risk	
  (Figure	
  3.3).	
  	
  The	
  
majority	
  of	
  snares	
  were	
  found	
  close	
  to	
  areas	
  with	
  higher	
  levels	
  of	
  perceived	
  retaliation	
  
risks	
  and	
  the	
  majority	
  of	
  firearm	
  incidents	
  were	
  clustered	
  near	
  the	
  southern	
  border	
  with	
  

	
  

71	
  

Mamili	
  NP	
  and	
  the	
  Kwando	
  River,	
  and	
  the	
  northeastern	
  region	
  of	
  the	
  conservancy	
  adjacent	
  
to	
  Mudumu	
  NP	
  (Figure	
  3.3).	
  	
  
3.5.	
  DISCUSSION	
  
3.5.1.	
  Estimating	
  poaching	
  risks.	
  	
  
Conservancy	
  residents	
  feel	
  that	
  poaching	
  is	
  adversely	
  affecting	
  conservancy	
  wildlife.	
  	
  
Participants	
  rated	
  poaching	
  as	
  the	
  second	
  most	
  critical	
  threat	
  to	
  wildlife	
  and	
  the	
  highest	
  in	
  
terms	
  of	
  severity.	
  	
  Beyond	
  poaching,	
  participants	
  are	
  aware	
  of	
  other	
  risks	
  affecting	
  wildlife;	
  
these	
  factors	
  provide	
  additional	
  detail	
  about	
  the	
  wildlife	
  conservation	
  climate	
  within	
  which	
  
poaching	
  exists.	
  	
  For	
  example,	
  human	
  financial	
  insecurity,	
  subsistence	
  insecurity	
  
(Jachmann,	
  2008;	
  Kühl	
  et	
  al.,	
  2009),	
  and	
  socio-­‐cultural	
  insecurity	
  (e.g.,	
  war)	
  (de	
  Merode,	
  
Smith,	
  Homewood,	
  Pettifor,	
  Rowcliff	
  &	
  Cowlishaw,	
  2007)	
  have	
  been	
  linked	
  to	
  increased	
  
poaching	
  and	
  illustrate	
  that	
  fluctuations	
  in	
  local	
  poaching	
  activities	
  may	
  be	
  tied	
  to	
  dynamic	
  
economic,	
  political	
  and	
  social	
  conditions.	
  	
  Conservancy	
  residents	
  reported	
  high	
  perceptions	
  
of	
  poaching	
  risks.	
  	
  These	
  perceptions	
  may	
  translate	
  into	
  high	
  levels	
  of	
  local	
  willingness	
  to	
  
support	
  poaching	
  rules	
  and	
  sanctions	
  and	
  act	
  against	
  a	
  behavior	
  they	
  have	
  deemed	
  an	
  
unacceptable	
  risk	
  to	
  local	
  wildlife	
  resources	
  (Bell	
  et	
  al.,	
  2007;	
  Hampshire	
  et	
  al.,	
  2004).	
  	
  	
  
However,	
  Kühl	
  et	
  al.	
  (2009)	
  warned	
  that	
  poaching	
  behavior	
  could	
  continue	
  despite	
  
stakeholders	
  voicing	
  concern	
  for	
  wildlife	
  and	
  support	
  for	
  management.	
  	
  Livelihood	
  needs	
  
may	
  override	
  these	
  sentiments.	
  
According	
  to	
  the	
  conservancy	
  Event	
  Books	
  the	
  assessed	
  poaching	
  risk	
  over	
  the	
  last	
  
seven	
  years	
  is	
  low	
  and	
  may	
  not	
  represent	
  a	
  technical	
  threat	
  to	
  wildlife	
  resources	
  in	
  the	
  
area.	
  	
  However,	
  Event	
  Book	
  data	
  also	
  suggest	
  an	
  increase	
  in	
  documented	
  poaching	
  
incidents	
  with	
  a	
  greater	
  number	
  of	
  snares	
  confiscated	
  and	
  firearm	
  and	
  traditional	
  incidents	
  

	
  

72	
  

since	
  2006.	
  	
  Deriving	
  poaching	
  trends	
  from	
  enforcement	
  records,	
  such	
  as	
  Event	
  Books,	
  
however,	
  may	
  not	
  wholly	
  portray	
  actual	
  poaching	
  incidence	
  as	
  such	
  monitoring	
  data	
  
depend	
  on	
  the	
  surveillance	
  effort	
  exerted	
  by	
  anti-­‐poaching	
  staff	
  over	
  time	
  (Kangwana	
  &	
  
Mako,	
  2001).	
  	
  In	
  addition	
  to	
  challenges	
  associated	
  with	
  monitoring,	
  Vaughan	
  and	
  Long	
  
(2007)	
  reported	
  community	
  game	
  guards,	
  responsible	
  for	
  reporting	
  poachers	
  in	
  
conservancies,	
  may	
  not	
  arrest	
  an	
  offender	
  with	
  whom	
  they	
  have	
  strong	
  social	
  ties	
  due	
  to	
  
fear	
  of	
  being	
  socially	
  ostracized	
  within	
  the	
  community.	
  	
  Combining	
  Event	
  Book	
  data	
  with	
  
the	
  data	
  gathered	
  from	
  community	
  focus	
  groups	
  provides	
  a	
  more	
  holistic	
  portrayal	
  of	
  the	
  
potential	
  extent	
  of	
  poaching	
  activities	
  in	
  the	
  conservancies.	
  	
  High	
  perceptions	
  of	
  poaching	
  
risk	
  among	
  stakeholders	
  coupled	
  with	
  an	
  unexplained	
  trend	
  of	
  increasing	
  assessed	
  
poaching	
  risk	
  indicate	
  a	
  need	
  for	
  continued	
  yet	
  integrated	
  approach	
  to	
  monitoring	
  
poaching.	
  	
  
3.5.2.	
  Local	
  motivations	
  for	
  poaching.	
  
Conservancy	
  participants	
  identified	
  diverse	
  motivations	
  for	
  poaching.	
  Muth	
  and	
  
Bowe’s	
  (1998)	
  typology	
  of	
  poaching	
  motivations	
  provides	
  one	
  method	
  for	
  interpreting	
  
these	
  results;	
  it	
  is	
  useful	
  in	
  guiding	
  the	
  transition	
  between	
  stated	
  motivations	
  and	
  
recommendations	
  for	
  management	
  interventions.	
  Participant-­‐cited	
  motivations	
  for	
  
poaching	
  fit	
  into	
  eight	
  of	
  Muth	
  and	
  Bowe's	
  (1998)	
  ten	
  categories,	
  although	
  conceptually,	
  
many	
  participant	
  motivations	
  fit	
  into	
  multiple	
  categories	
  (Table	
  3.4).	
  The	
  most	
  often	
  cited	
  
motivations	
  related	
  to	
  commercial	
  gain	
  (e.g.,	
  income	
  generation,	
  lack	
  of	
  employment)	
  and	
  
household	
  consumption	
  (e.g.,	
  meat)	
  (Table	
  3.4).	
  	
  Although	
  protecting	
  fields	
  was	
  identified	
  
as	
  the	
  third	
  most	
  prevalent	
  motivation	
  for	
  poaching,	
  protecting	
  human	
  lives	
  and	
  livestock	
  
were	
  low	
  in	
  terms	
  of	
  prevalence.	
  	
  This	
  may	
  be	
  an	
  artifact	
  of	
  Namibian's	
  legal	
  right	
  to	
  use	
  

	
  

73	
  

lethal	
  force	
  against	
  wildlife	
  found	
  immediately	
  threatening	
  livestock	
  or	
  human	
  lives;	
  
wildlife	
  in	
  agricultural	
  fields	
  are	
  to	
  be	
  reported	
  to	
  local	
  game	
  guards,	
  who	
  initially	
  remove	
  
them	
  using	
  non-­‐lethal	
  methods	
  (MET,	
  2009).	
  	
  
Poaching	
  acts	
  motivated	
  by	
  rebellion	
  or	
  disagreements	
  with	
  regulations	
  are	
  related	
  
to	
  negative	
  local	
  attitudes	
  regarding	
  the	
  establishment,	
  governance	
  or	
  benefit	
  distribution	
  
scheme	
  of	
  the	
  conservancy.	
  	
  The	
  extent	
  to	
  which	
  these	
  motivations	
  drive	
  local	
  poaching	
  
activities	
  would	
  be	
  of	
  particular	
  interest	
  to	
  conservancy	
  managers	
  given	
  that	
  such	
  
motivations	
  are	
  rooted	
  in	
  public	
  perceptions	
  of	
  regulations,	
  local	
  decision-­‐makers,	
  and	
  
effectiveness	
  of	
  the	
  conservancy	
  to	
  provide	
  benefits	
  to	
  stakeholders.	
  	
  No	
  participant	
  cited	
  
thrill	
  killing	
  (i.e.,	
  the	
  psychological	
  excitement	
  of	
  killing	
  an	
  animal)	
  or	
  gamesmanship	
  (i.e.,	
  
desire	
  to	
  outwit	
  law	
  enforcement)	
  as	
  motivations	
  for	
  poaching	
  in	
  their	
  conservancies	
  
(Muth	
  &	
  Bowe,	
  1998).	
  	
  
The	
  diversity	
  of	
  motivations	
  for	
  poaching	
  may	
  seem	
  daunting	
  in	
  terms	
  of	
  generating	
  
management	
  interventions.	
  However,	
  one	
  management	
  intervention	
  may	
  address	
  multiple	
  
related	
  motivations.	
  For	
  example,	
  conservancy	
  managers	
  may	
  focus	
  on	
  generating	
  
additional	
  employment	
  opportunities	
  such	
  as	
  ecotourism	
  to	
  reduce	
  poaching	
  (Knapp,	
  
2007).	
  	
  The	
  increased	
  income	
  provided	
  by	
  employment	
  could	
  reduce	
  poaching	
  motivated	
  
by	
  economic	
  gains,	
  lower	
  dependency	
  on	
  poaching	
  as	
  a	
  source	
  of	
  protein	
  and	
  decrease	
  
opportunities	
  for	
  recreational	
  poaching.	
  	
  Increasing	
  outreach	
  activities	
  to	
  prevent	
  animal	
  
damage	
  events	
  could	
  reduce	
  poaching	
  motivated	
  by	
  crop	
  damage,	
  human	
  attacks	
  and	
  
livestock	
  depredation	
  in	
  addition	
  to	
  addressing	
  sentiments	
  that	
  there	
  is	
  a	
  lack	
  of	
  benefits	
  
from	
  the	
  conservancy.	
  	
  However,	
  reducing	
  poaching	
  incidents	
  motivated	
  by	
  larger	
  profits,	
  
such	
  as	
  those	
  related	
  to	
  the	
  illegal	
  sale	
  of	
  skins,	
  horns	
  or	
  ivory,	
  will	
  likely	
  require	
  more	
  

	
  

74	
  

traditional	
  methods	
  of	
  increasing	
  compliance	
  such	
  as	
  increased	
  patrolling	
  and	
  fines	
  
(Leader-­‐Williams	
  &	
  Milner-­‐Gulland,	
  1993).	
  	
  
3.5.3.	
  Co-­mapping	
  poaching	
  risks.	
  
Co-­‐mapping	
  offers	
  a	
  multifaceted	
  tool	
  for	
  conservation	
  planning	
  in	
  CBNRM	
  areas	
  
such	
  as	
  study	
  conservancies.	
  	
  Examining	
  the	
  spatial	
  patterns	
  associated	
  with	
  risk	
  to	
  both	
  
local	
  livelihoods	
  and	
  wildlife	
  may	
  assist	
  in	
  understanding	
  poaching	
  motivations	
  and	
  
identifying	
  more	
  effective	
  enforcement	
  strategies	
  (Sánchez-­‐Mercado	
  et	
  al.,	
  2008).	
  	
  There	
  
was	
  a	
  high	
  degree	
  of	
  consistency	
  between	
  participant-­‐generated	
  and	
  ranked	
  motivations	
  
for	
  poaching	
  and	
  the	
  geographic	
  depiction	
  of	
  said	
  poaching	
  risks.	
  For	
  instance,	
  the	
  
stakeholder-­‐identified	
  areas	
  of	
  poaching	
  near	
  national	
  park	
  boundaries	
  corresponded	
  with	
  
areas	
  perceived	
  to	
  have	
  high	
  densities	
  of	
  wildlife.	
  	
  This	
  could	
  represent	
  poaching	
  activities	
  
aimed	
  at	
  harvesting	
  particular	
  species	
  prized	
  for	
  meat	
  or	
  trophies.	
  	
  Stakeholder-­‐generated	
  
maps	
  may	
  prove	
  to	
  be	
  a	
  valuable	
  monitoring	
  tool	
  to	
  reduce	
  poaching	
  motivated	
  by	
  
commercial	
  gain	
  or	
  acquisition	
  of	
  trophies	
  as	
  this	
  requires	
  identification	
  of	
  areas	
  where	
  
relevant	
  species	
  are	
  concentrated	
  (Sánchez-­‐Mercado	
  et	
  al.,	
  2008).	
  	
  
Considering	
  the	
  spatial	
  relatedness	
  of	
  risks	
  to	
  livelihoods	
  and	
  wildlife	
  may	
  aid	
  in	
  
identifying	
  more	
  appropriate	
  enforcement	
  and	
  management	
  strategies	
  (Sánchez-­‐Mercado	
  
et	
  al.,	
  2008)	
  and	
  aid	
  in	
  addressing	
  the	
  criminology	
  of	
  conservation.	
  For	
  example,	
  there	
  
appeared	
  to	
  be	
  a	
  spatial	
  relationship	
  between	
  participant-­‐mapped	
  retaliation	
  risk	
  and	
  
Event	
  Book	
  records	
  for	
  poaching	
  events.	
  	
  Additionally,	
  the	
  prevalence	
  of	
  confiscated	
  snares	
  
and	
  traditional	
  poaching	
  methods	
  within	
  these	
  perceived	
  risk-­‐retaliation	
  zones	
  is	
  
consistent	
  with	
  Muth	
  and	
  Bowe's	
  (1998)	
  protection	
  of	
  self	
  and	
  property	
  (e.g.,	
  crops,	
  
livestock)	
  motivation.	
  	
  Co-­‐mapping	
  risks	
  to	
  livelihoods	
  from	
  wildlife	
  could	
  aid	
  in	
  

	
  

75	
  

identification	
  of	
  areas	
  of	
  the	
  highest	
  likelihood	
  of	
  retaliation-­‐motivated	
  events	
  (legal	
  or	
  
illegal)	
  and	
  better	
  prioritize	
  intervention	
  efforts	
  in	
  those	
  high-­‐risk	
  areas.	
  	
  	
  Additionally,	
  the	
  
use	
  of	
  spatially	
  explicit	
  risk	
  maps	
  may	
  also	
  improve	
  risk	
  communication	
  between	
  
stakeholders	
  and	
  managers	
  about	
  interventions	
  in	
  the	
  conservancy	
  (Dransch,	
  Rotzoll	
  &	
  
Poser,	
  2010).	
  	
  For	
  example,	
  as	
  managers	
  approach	
  individual	
  farmers	
  to	
  discuss	
  crop	
  
damage	
  or	
  livestock	
  depredation	
  preventative	
  practices,	
  maps	
  can	
  illustrate	
  areas	
  of	
  high	
  
likelihood	
  of	
  risk	
  exposure	
  and	
  aid	
  individuals	
  in	
  contextualizing	
  their	
  risk	
  perceptions	
  
(Dransch	
  et	
  al.,	
  2010).	
  	
  	
  
3.5.4.	
  Conclusions.	
  	
  	
  
Uncertainty	
  surrounding	
  the	
  extent	
  and	
  intensity	
  of	
  local	
  poaching	
  can	
  constrain	
  
managers	
  and	
  conservation	
  practitioners’	
  ability	
  to	
  set	
  sustainable	
  legal	
  harvest	
  quotas	
  on	
  
wildlife	
  (Sethi	
  &	
  Hilborn,	
  2008).	
  	
  This	
  is	
  a	
  critical	
  problem	
  in	
  CBNRM	
  systems	
  where	
  
financial	
  and	
  human	
  resources	
  for	
  monitoring	
  poaching	
  may	
  be	
  limited	
  yet	
  economic	
  
development	
  objectives	
  are	
  dependent	
  on	
  sustainable	
  use	
  of	
  wildlife.	
  Using	
  conservation	
  
criminology	
  as	
  an	
  analytical	
  framework	
  [i.e.,	
  applying	
  notions	
  of	
  compliance	
  (criminology),	
  
risk	
  perception	
  (risk	
  and	
  decision	
  sciences)	
  and	
  wildlife	
  management	
  (natural	
  resources	
  
management)	
  (Gibbs	
  et	
  al.,	
  2010)]	
  ,	
  was	
  advantageous	
  in	
  dealing	
  with	
  the	
  contextual	
  
complexity	
  surrounding	
  poaching	
  activities	
  and	
  their	
  physical	
  manifestation	
  in	
  the	
  
landscape.	
  	
  Integrated	
  approaches	
  that	
  increase	
  communication	
  between	
  local	
  
environmental	
  decision-­‐makers	
  and	
  local	
  stakeholders	
  in	
  relation	
  to	
  poaching	
  risks	
  could	
  
help	
  further	
  prioritize	
  monitoring	
  efforts,	
  target	
  vulnerable	
  wildlife	
  habitats	
  and	
  
stakeholders,	
  influence	
  local	
  policies	
  and	
  management	
  strategies	
  and	
  educate	
  the	
  local	
  
stakeholders	
  about	
  the	
  biological,	
  ecological	
  and	
  socio-­‐cultural	
  consequences	
  of	
  poaching.	
  

	
  

76	
  

	
  
Table	
  3.1:	
  Characteristics	
  of	
  the	
  Mudumu	
  South	
  Complex	
  in	
  East	
  
Caprivi,	
  Namibia	
  
	
  
Characteristic	
  

Mudumu	
  South	
  Complex	
  a	
  

Adjacent	
  conservation	
   Mudumu	
  National	
  Park	
  (north);	
  Mamili	
  National	
  
areas	
  
Park	
  (south)	
  
Approximate	
  
population	
  	
  

Balyerwa	
  (1500),	
  Dzoti	
  (391),	
  Shikhakhu	
  
(unknown),	
  Wuparo	
  (2100)	
  

Biome	
  classification	
  

Mosaic	
  of	
  mopane	
  (Colophospermum	
  mopane)	
  
woodland,	
  Kalahari	
  grassland	
  with	
  floodplains,	
  
riverine	
  (Kwando	
  River)	
  

Climate	
  

Semi-­‐arid	
  (Average	
  annual	
  rainfall	
  ≥625	
  mm)	
  

Conservancies	
  
(registered)	
  

Balyerwa	
  (2006),	
  Dzoti	
  (2009),	
  Shikhakhu	
  
(stalled)	
  b,	
  Wuparo	
  (1999)	
  

Major	
  wildlife	
  
resources	
  

Black-­‐backed	
  jackal,	
  buffalo,	
  bush	
  pig,	
  crocodile,	
  
duiker,	
  elephant,	
  hippopotamus,	
  hyena,	
  impala,	
  
kudu,	
  leopard,	
  lion,	
  reedbuck,	
  roan,	
  tsessebe,	
  
warthog,	
  wildebeest,	
  zebra	
  

Size	
  (km	
  2)	
  

Balyerwa	
  (223),	
  Dzoti	
  (245),	
  Shikhakhu	
  
(unknown),	
  Wuparo	
  (148)	
  

a	
  Information	
  available	
  on	
  the	
  Namibian	
  Association	
  of	
  CBNRM	
  Support	
  

Organizations'	
  (NASCO)	
  online	
  database	
  (http://www.nasco.org.na/)	
  

b	
  Establishment	
  of	
  conservancy	
  has	
  been	
  stalled	
  due	
  to	
  internal	
  conflicts.	
  

	
  
	
  
	
  
	
  
	
  
	
  
	
  

77	
  

Table	
  3.2:	
  Local	
  perceptions	
  (n=48)	
  about	
  the	
  seriousness	
  of	
  risks	
  to	
  wildlife	
  as	
  
identified	
  by	
  focus	
  groups	
  in	
  two	
  conservancies	
  in	
  Mudumu	
  South	
  Complex:	
  
Caprivi,	
  Namibia	
  (July-­September,	
  2009).	
  
Overall	
  Rank	
  
Incidence	
   Importance	
  
Threat	
  category	
  
Severity	
  
(Joint	
  Risk	
  
Index	
  
index	
  
Index)	
  
Agricultural	
  activities	
  

1	
  

(0.46)	
  

0.67	
  

0.54	
  

3.2	
  

Poaching	
  

2	
  

(0.37)	
  

0.52	
  

0.59	
  

3.5	
  

Wildlife	
  deterrence	
  activities	
  

3	
  

(0.34)	
  

0.50	
  

0.52	
  

3.1	
  

Development	
  (e.g.,	
  roadways)	
  

4	
  

(0.31)	
  

0.44	
  

0.56	
  

3.2	
  

Increased	
  human	
  wildlife	
  
interactions	
  

5	
  

(0.29)	
  

0.48	
  

0.32	
  

2.9	
  

Habitat	
  modification	
  (e.g.,	
  
deforestation)	
  

6	
  

(0.28)	
  

0.42	
  

0.47	
  

2.9	
  

0.31	
  

0.67	
  

3.4	
  

7	
  

(0.23)	
  
0.33	
  

0.58	
  

3.3	
  

0.10	
  

0.52	
  

2.8	
  

0.08	
  

0.41	
  

2.8	
  

0.06	
  

0.68	
  

2.7	
  

Hunting	
  
Climate	
  (e.g.,	
  drought)	
  
Retaliation	
  a	
  
Ecological	
  threats	
  (e.g.,	
  
predation)	
  

8	
  

9	
  

(0.07)	
  

(0.05)	
  

Financial	
  insecurity	
  
Subsistence	
  insecurity	
  (e.g.,	
  
food	
  insecurity)	
  

10	
  

(0.04)	
  

0.06	
  

0.52	
  

2.0	
  

Conservancy	
  service	
  and	
  
management	
  

11	
  

(0.03)	
  

0.04	
  

0.55	
  

3.0	
  

Socio-­‐cultural	
  insecurity	
  (e.g.,	
  
war)	
  

12	
  

(0.02)	
  

0.04	
  

0.10	
  

1.5	
  

a	
  	
  Legal	
  or	
  illegal	
  removal	
  of	
  problem	
  animals	
  due	
  to	
  damage	
  to	
  crops,	
  livestock,	
  

infrastructure	
  or	
  human.	
  
	
  
	
  

78	
  

	
  
Table	
  3.3:	
  Participant-­generated	
  (n=48)	
  and	
  ranked	
  motivations	
  for	
  
poaching	
  in	
  two	
  conservancies	
  in	
  Mudumu	
  South	
  Complex:	
  Caprivi,	
  
Namibia	
  (July-­September,	
  2009).	
  
Motivations	
  for	
  poaching	
  

Overall	
  Rank	
  
(Joint	
  Risk	
  Index)	
  

Incidence	
  
Index	
  

Importance	
  
Index	
  

Income	
  generation	
  a	
  

1	
  

(0.48)	
  

0.54	
  

0.88	
  

Food	
  (Meat)	
  

2	
  

(0.47)	
  

0.54	
  

0.85	
  

Protecting	
  fields	
  

3	
  

(0.24)	
  

0.38	
  

0.41	
  

Skins	
  (pelts)	
  

4	
  

(0.19)	
  

0.31	
  

0.38	
  

0.15	
  

0.38	
  

0.15	
  

0.25	
  

0.15	
  

0.25	
  

0.15	
  

0.00	
  

0.08	
  

0.50	
  

0.08	
  

0.50	
  

Firearm	
  training	
  

0.08	
  

0.13	
  

Entertainment	
  

0.08	
  

0.00	
  

0.08	
  

0.00	
  

0.08	
  

0.00	
  

Trophies	
  b	
  (antlers)	
  
Lack	
  of	
  employment	
  

5	
  

(0.09)	
  

Protesting	
  regulations/	
  
conservancy	
  
Medicine	
  
Elephant	
  ivory	
  
Protecting	
  human	
  lives	
  

Lack	
  of	
  benefits	
  from	
  
conservancy	
  

6	
  

(0.08)	
  

7	
  

(0.05)	
  

8	
  

(0.04)	
  

Protecting	
  livestock	
  

a	
  Income	
  generation	
  was	
  kept	
  separate	
  from	
  skins,	
  trophies,	
  medicine	
  and	
  

elephant	
  ivory	
  due	
  to	
  the	
  fact	
  that	
  these	
  wildlife	
  products	
  may	
  be	
  utilized	
  by	
  
local	
  people	
  for	
  non-­‐economic	
  purposes	
  (e.g.,	
  subsistence	
  based,	
  cultural).	
  	
  
b	
  Trophies	
  refer	
  to	
  non-­‐ivory,	
  non-­‐pelt	
  based	
  products	
  (e.g.,	
  antlers,	
  teeth	
  and	
  

	
  
	
  
	
  
	
  

	
  

head	
  mounts).	
  

79	
  

Table	
  3.4:	
  Conservancy	
  participants'	
  (n=48)	
  cited	
  motivations	
  for	
  poaching	
  
conceptually	
  sorted	
  using	
  Muth	
  and	
  Bowe's	
  (1998)	
  typology	
  of	
  the	
  motivations	
  
for	
  poaching	
  (categories	
  underlined):	
  Mudumu	
  South	
  Complex,	
  Namibia	
  (2009)	
  
	
  
Poaching	
  for	
  commercial	
  gain	
  

	
  
	
  

	
  
Poaching	
  to	
  protect	
  self	
  and	
  property	
  

Elephant	
  ivory	
  a	
  

	
  

Lack	
  of	
  benefits	
  from	
  conservancy	
  

Income	
  generation	
  

	
  

Protecting	
  fields	
  

Lack	
  of	
  benefits	
  from	
  conservancy	
  

	
  

Protecting	
  human	
  lives	
  

Lack	
  of	
  employment	
  

	
  

Protecting	
  livestock	
  

Medicine	
  

	
  

Skins	
  (pelts)	
  

	
  

Protesting	
  regulations/	
  conservancy	
  

Trophies	
  b	
  (antlers,	
  mounts)	
  

	
  

Lack	
  of	
  benefits	
  from	
  conservancy	
  

	
  

Poaching	
  as	
  a	
  traditional	
  right	
  of	
  use	
  

Poaching	
  for	
  household	
  consumption	
  

Poaching	
  as	
  rebellion	
  

Food	
  (Meat)	
  

	
  

Elephant	
  ivory	
  

Lack	
  of	
  benefits	
  from	
  conservancy	
  

	
  

Medicine	
  

	
  

Skins	
  (pelts)	
  

Entertainment	
  

	
  

Trophies	
  b	
  (antlers,	
  mounts)	
  

Firearm	
  training	
  

	
  

Disagreement	
  with	
  specific	
  regulations	
  

Trophy	
  poaching	
  

	
  

Lack	
  of	
  benefits	
  from	
  conservancy	
  

Elephant	
  ivory	
  

	
  

Protesting	
  regulations/	
  conservancy	
  

Skins	
  (pelts)	
  

	
  

	
  

Trophies	
  b	
  (antlers,	
  mounts)	
  

	
  

	
  

	
  	
  

	
  

Recreational	
  poaching	
  

	
  	
  

a	
  Italicized	
  motivations	
  cannot	
  be	
  exclusively	
  designated	
  under	
  one	
  category	
  using	
  Muth	
  

and	
  Bowe's	
  (1998)	
  typology.	
  

b	
  Trophies	
  refer	
  to	
  non-­‐ivory,	
  non-­‐pelt	
  based	
  products	
  (e.g.,	
  antlers,	
  teeth	
  and	
  head	
  

mounts).	
  
	
  
	
  
	
  
	
  

	
  

80	
  

Figure	
  3.1:	
  Recorded	
  incidents	
  of	
  poaching	
  (e.g.,	
  number	
  of	
  snares	
  confiscated,	
  firearm	
  and	
  
traditional	
  incidents)	
  in	
  two	
  Mudumu	
  South	
  Complex	
  conservancies:	
  East	
  Caprivi	
  Namibia	
  
(Dzoti	
  &	
  Wuparo	
  Event	
  Books	
  2001;	
  2003-­‐2008).	
  
	
  

*!"

!"#$%&'()*+,&"-&.'/.0+'#1&

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(!"
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/24/.5206"

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/24/.5206"

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92-,56"
412:/64-05."

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#!"
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2+$,&&

	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

81	
  

	
  

Figure	
  3.2:	
  Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  poaching	
  and	
  Event	
  
Book	
  data	
  for	
  poaching	
  incidents	
  (2001-­‐2008)	
  in	
  two	
  Mudumu	
  South	
  Complex	
  
conservancies:	
  Caprivi,	
  Namibia.	
  

Mudumu National Park

b) Dzoti Conservancy

!
"
!
"

#

a) Wuparo Conservancy

!
"

!
"
!
"

#

! !

!
"

!
"

! #
"

!
"

!
"
#!

!
#

!
"
#

#

!!
""

!
"

!!
!
"
! !! !
"

#

#

!

!
"

!
"
#

!
"

!
!
!!
!
!!

!

#

!
"
!
"

#
!!
! !! !
!

!
"

!
"

#

!
"
!
"
!
"

!
"

"
" !
#!! #

!
!

!
#

#

!

!
"

!
!
#

! !!

!!
!

#

#

!

#

!

#

!

#

!
"

!
"

!

!
"

#

#

Kwando River

#

Mamili National Park

!
"
!
"
!
"

Wildlife Occurs Often

!

Event Book Incidence Perceived Incidence
#

1

Wildlife Occurs Rarely

#

2

Villages

#

3

Roads and Trails

#

4-6

Water

#

7 - 10

Wildlife Occurs Sometimes

Low
High

!

Conservancy Boundaries

0 1 2

6

8
Kilometers

	
  

	
  
	
  

4

82	
  

Figure	
  3.3:	
  Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  wildlife	
  attack	
  and	
  
livelihood	
  damage	
  that	
  motivates	
  retaliatory	
  poaching	
  and	
  Event	
  Book	
  data	
  for	
  poaching	
  
incidents	
  by	
  incident	
  type	
  (2001-­‐2008)	
  in	
  two	
  Mudumu	
  South	
  Complex	
  conservancies:	
  
Caprivi,	
  Namibia.	
  

Mudumu National Park

b) Dzoti Conservancy

!
"
!
"

a) Wuparo Conservancy

!
"

!
"
!
"
! !

!
"

!
"

!
"

!
"

!! !
" "

!
!

!

!
"

!
!
! !! !
"
!
"

!

!
"

!

!
"

!
!
!
! !
!!

!

!
"

!
"

!

!
"
!
"
!
"

!!
""

!
"

!
"

!
"

!

!
"
!

!
"
!
"

!
"

!!
! !! !
!
!
!
!!
!

! !!

!
"

!
!

!
"

!

!
"
Kwando River

Mamili National Park

!
"
!
"
!
"

Wildlife Occurs Often

!

Event Book Incidents

Wildlife Occurs Sometimes

Snares

Wildlife Occurs Rarely

Firearms

Villages

Perceived Incidence
Low

Traditional

!

High

Roads
Water
Conservancy Boundaries

0

1

2

4

6

8
Kilometers

	
  

	
  

83	
  

CHAPTER	
  4:	
  SUMMARY	
  OF	
  RESEARCH	
  FINDINGS:	
  IMPLICATIONS	
  FOR	
  THEORY,	
  
METHODS,	
  AND	
  PRACTICE	
  
	
  

This	
  thesis	
  fills	
  knowledge	
  gaps	
  related	
  to	
  the	
  influence	
  of	
  conservancy	
  status	
  on	
  

perceptions	
  of	
  human-­‐wildlife	
  conflict	
  (HWC)	
  risks	
  and	
  vulnerability,	
  local	
  
characterizations	
  of	
  HWC-­‐related	
  risks	
  relative	
  to	
  non-­‐HWC	
  related	
  risks	
  (e.g.,	
  flooding)	
  
and	
  differences	
  between	
  perceived	
  and	
  assessed	
  risks.	
  	
  In	
  producing	
  new	
  knowledge,	
  this	
  
research	
  makes	
  theoretical,	
  methodological,	
  and	
  practical	
  contributions	
  to	
  the	
  extant	
  
literature	
  on	
  risk	
  perception,	
  vulnerability,	
  and	
  HWC.	
  	
  Data	
  herein	
  provide	
  novel	
  
understanding	
  about	
  local	
  stakeholders'	
  perceptions	
  of	
  wildlife-­‐related	
  risks	
  and	
  
vulnerability,	
  the	
  influence	
  of	
  conservancy	
  membership	
  on	
  HWC-­‐related	
  risk	
  perceptions,	
  
and	
  participatory	
  approaches	
  that	
  enhance	
  understanding	
  of	
  HWC-­‐related	
  risks	
  both	
  to	
  
and	
  from	
  wildlife.	
  	
  Below,	
  I	
  discuss	
  key	
  implications	
  for	
  theory,	
  methods,	
  and	
  practice	
  from	
  
this	
  research.	
  
4.1.	
  THEORECTICAL	
  IMPLICATIONS	
  
4.1.1.	
  Conservancy	
  effects	
  on	
  risk	
  perception	
  and	
  vulnerability.	
  
Naughton-­‐Treves	
  (1997)	
  and	
  others	
  suggested	
  that	
  decentralizing	
  wildlife	
  
management	
  [i.e.,	
  community-­‐based	
  natural	
  resource	
  management	
  (CBNRM)]	
  from	
  state	
  or	
  
federal	
  levels	
  to	
  local	
  communities	
  reduces	
  human	
  vulnerability	
  to	
  HWCs	
  by	
  offsetting	
  the	
  
costs	
  of	
  living	
  with	
  wildlife	
  with	
  economic	
  benefits.	
  	
  There	
  was	
  previously	
  a	
  lack	
  of	
  
empirical	
  evidence	
  surrounding	
  the	
  effects	
  of	
  such	
  decentralized	
  systems	
  (e.g.,	
  communal	
  
conservancies)	
  on	
  stakeholders'	
  livelihood	
  and	
  wildlife-­‐related	
  risk	
  perceptions	
  and	
  
vulnerability	
  associated	
  with	
  HWC	
  (Schumann,	
  Watson	
  &	
  Schumann,	
  2008).	
  	
  

	
  

84	
  

	
  

Research	
  in	
  chapter	
  two	
  highlights	
  conservancy	
  status	
  effects	
  on	
  stakeholders'	
  

prioritization,	
  characterization,	
  and	
  perceived	
  severity	
  of	
  HWC-­‐related	
  risks	
  and	
  
vulnerability.	
  	
  Although	
  results	
  provide	
  evidence	
  that	
  the	
  establishment	
  of	
  a	
  conservancy	
  
may	
  reduce	
  risk	
  perceptions	
  to	
  livelihoods	
  from	
  HWC,	
  conservancy	
  effects	
  on	
  HWC-­‐related	
  
risk	
  perceptions	
  to	
  wildlife	
  are	
  less	
  clear.	
  	
  Established	
  conservancy	
  residents	
  perceived	
  
more	
  equitable	
  distribution	
  of	
  benefits	
  and	
  less	
  risks	
  from	
  living	
  with	
  wildlife;	
  they	
  failed,	
  
however,	
  to	
  differ	
  from	
  emerging	
  conservancy	
  residents	
  regarding	
  their	
  sense	
  of	
  control	
  
over	
  HWC	
  and	
  participation	
  in	
  anti-­‐HWC	
  related	
  animal	
  husbandry	
  practices.	
  	
  Established	
  
conservancy	
  membership,	
  higher	
  education	
  level	
  and	
  not	
  being	
  a	
  local	
  environmental	
  
decision-­‐maker	
  strongly	
  predicted	
  lower	
  stakeholder	
  perceptions	
  of	
  risk	
  to	
  livelihoods	
  
from	
  HWC.	
  	
  Age	
  moderately	
  predicted	
  lower	
  perceptions	
  of	
  risk	
  to	
  wildlife	
  (i.e.,	
  older	
  
participants	
  perceived	
  lower	
  risks	
  to	
  wildlife),	
  while	
  established	
  conservancy	
  membership	
  
marginally	
  predicted	
  higher	
  risk	
  perceptions	
  to	
  wildlife.	
  
4.1.2.	
  Multidirectional	
  perceptions	
  of	
  risks.	
  	
  	
  
We	
  know	
  multiple	
  factors	
  influence	
  stakeholders'	
  risk	
  perceptions	
  to	
  livelihoods	
  
associated	
  with	
  wildlife	
  such	
  as	
  dread,	
  responsiveness	
  of	
  managers,	
  and	
  control	
  over	
  
exposure	
  (Gore,	
  Knuth,	
  Curtis,	
  &	
  Shanahan,	
  2007);	
  factors	
  influencing	
  stakeholders'	
  
perceptions	
  of	
  risk	
  to	
  wildlife	
  were	
  previously	
  less	
  clear	
  (McFarlane,	
  2005;	
  Treves,	
  
Andriamampianina,	
  Didier,	
  Gibson,	
  Plumptre,	
  Wilkie,	
  et	
  al.,	
  2006).	
  	
  Further,	
  distinctions	
  
between	
  stakeholders’	
  risk	
  perceptions	
  associated	
  with	
  HWC	
  to	
  livelihoods	
  and	
  wildlife	
  
relative	
  to	
  non-­‐HWC	
  risks	
  have	
  largely	
  been	
  unevaluated	
  (Baird,	
  Leslie	
  &	
  McCabe,	
  2009).	
  	
  
Stakeholders'	
  risk	
  perceptions	
  to	
  wildlife	
  may	
  influence,	
  much	
  like	
  risk	
  perceptions	
  to	
  
livelihoods,	
  their	
  motivations	
  to	
  comply	
  with	
  HWC-­‐related	
  rules	
  (Hampshire,	
  Bell,	
  Wallace	
  

	
  

85	
  

&	
  Stepukonis,	
  2004;	
  McFarlane,	
  2005).	
  	
  Research	
  herein	
  considers	
  HWC-­‐related	
  risk	
  
perceptions	
  with	
  both	
  human	
  livelihoods	
  and	
  wildlife	
  as	
  risk	
  targets.	
  
Chapter	
  two	
  presents	
  data	
  about	
  conservancy	
  residents'	
  perceptions	
  and	
  
characterizations	
  of	
  multidirectional	
  HWC-­‐related	
  risks.	
  	
  Residents	
  characterized	
  a	
  variety	
  
of	
  risks	
  to	
  livelihoods	
  and	
  wildlife	
  related	
  and	
  unrelated	
  to	
  interactions	
  between	
  people	
  
and	
  wildlife.	
  	
  Taken	
  together,	
  these	
  risks	
  influence	
  the	
  vulnerability	
  of	
  conservancy	
  
residents	
  and	
  wildlife.	
  	
  For	
  example,	
  residents	
  stated	
  that	
  local	
  climate	
  conditions	
  intensify	
  
crop	
  damage,	
  threatening	
  local	
  livelihoods,	
  which	
  can	
  lead	
  to	
  retaliation	
  towards	
  wildlife.	
  	
  
Participants	
  noted	
  that	
  although	
  risks	
  to	
  livelihoods	
  are	
  both	
  related	
  and	
  unrelated	
  to	
  
wildlife,	
  the	
  most	
  critical	
  risks	
  are	
  unrelated	
  (e.g.,	
  anthropogenic).	
  	
  Risks	
  to	
  wildlife	
  were	
  
also	
  perceived	
  as	
  mostly	
  anthropogenic	
  in	
  nature.	
  	
  
4.1.3.	
  Similarities	
  and	
  differences	
  between	
  assessed	
  and	
  perceived	
  HWC-­related	
  risks.	
  
Research	
  in	
  chapter	
  three:	
  a)	
  presents	
  data	
  about	
  risk	
  perceptions	
  associated	
  with	
  
specific	
  types	
  of	
  HWC	
  such	
  as	
  poaching,	
  b)	
  compares	
  these	
  perceptions	
  to	
  those	
  associated	
  
with	
  non-­‐HWC	
  related	
  risks	
  to	
  wildlife	
  (e.g.,	
  agriculture),	
  c)	
  explores	
  stakeholder	
  
motivations	
  for	
  poaching,	
  and	
  d)	
  co-­‐maps	
  risk	
  assessments	
  and	
  perceptions	
  associated	
  
with	
  HWC.	
  	
  In	
  comparing	
  maps	
  of	
  conservancy	
  residents'	
  risk	
  perceptions	
  of	
  conservancy	
  
poaching	
  and	
  animal	
  damage	
  records,	
  I	
  provide	
  a	
  unique	
  picture	
  of	
  the	
  relationship	
  
between	
  risk	
  perceptions	
  and	
  assessments,	
  specifically	
  differences	
  in	
  severity	
  and	
  the	
  
extent	
  of	
  poaching	
  risk	
  in	
  the	
  study	
  conservancies	
  (Knapp,	
  Rentsch,	
  Schmitt,	
  Lewis	
  &	
  
Polasky,	
  2010).	
  	
  Co-­‐mapping	
  risks	
  in	
  this	
  way	
  facilitates	
  examining	
  patterns	
  (e.g.,	
  areas	
  of	
  
overlap)	
  associated	
  with	
  risk	
  to	
  local	
  livelihoods	
  and	
  wildlife.	
  	
  Further,	
  such	
  examination	
  
can	
  increase	
  our	
  understanding	
  of	
  the	
  interrelatedness	
  of	
  HWC-­‐related	
  risks	
  (e.g.,	
  crop	
  

	
  

86	
  

damage,	
  poaching)	
  and	
  may	
  aid	
  in	
  identifying	
  appropriate	
  management	
  strategies	
  
(Sánchez-­‐Mercado,	
  Ferrer-­‐Paris,	
  García-­‐Rangel	
  &	
  Rodríguez-­‐Clark,	
  2008).	
  
New	
  questions	
  emerge	
  and	
  warrant	
  further	
  inquiry.	
  Factors	
  that	
  influence	
  
perceptions	
  of	
  HWC-­‐related	
  risks	
  to	
  wildlife	
  remain	
  more	
  ambiguous	
  than	
  our	
  
understanding	
  of	
  factors	
  that	
  influence	
  perceptions	
  of	
  HWC-­‐related	
  risks	
  to	
  livelihoods	
  
(McFarlane,	
  2005);	
  more	
  information	
  is	
  needed	
  to	
  elucidate	
  what	
  these	
  factors	
  may	
  be.	
  
Deeper	
  understanding	
  about	
  the	
  relationships	
  between	
  risk	
  perception	
  and	
  HWC-­‐related	
  
behavior	
  would	
  be	
  beneficial	
  for	
  theory	
  and	
  practice.	
  	
  For	
  example,	
  how	
  do	
  HWC-­‐risk	
  
perceptions	
  affect	
  an	
  individual's	
  HWC-­‐risk	
  preventing	
  behavior,	
  such	
  as	
  adoption	
  of	
  best	
  
practices	
  for	
  reducing	
  conflict?	
  	
  How	
  do	
  HWC-­‐related	
  risk	
  beliefs	
  towards	
  wildlife	
  affect	
  
compliance	
  with	
  wildlife	
  management	
  laws	
  and	
  conservation	
  norms	
  (e.g.,	
  not	
  retaliating	
  
for	
  animal	
  damage)?	
  	
  Finally,	
  it	
  would	
  be	
  useful	
  to	
  explore	
  how	
  stakeholders	
  conceptually	
  
map	
  relationships	
  between	
  direct,	
  indirect	
  and	
  non-­‐HWC-­‐related	
  risks	
  to	
  livelihoods	
  and	
  
wildlife.	
  	
  
4.2.	
  METHODOLOGICAL	
  IMPLICATIONS	
  
4.2.1.	
  Visual	
  interview	
  aids.	
  
	
  

This	
  research	
  produced	
  a	
  novel	
  method,	
  a	
  visual	
  Likert-­‐type	
  scale,	
  to	
  maximize	
  data	
  

collection	
  in	
  a	
  cross-­‐cultural,	
  low	
  literacy,	
  English	
  as	
  a	
  second	
  language	
  context.	
  Visual	
  
Likert-­‐type	
  scales	
  used	
  multiple	
  visual	
  indicators	
  (e.g.,	
  color,	
  size,	
  numeric	
  and	
  non-­‐
numerical	
  quantitative	
  measures)	
  of	
  increasing	
  intensity	
  (Appendix	
  C).	
  	
  This	
  approach	
  
proved	
  useful	
  and	
  efficient	
  for	
  data	
  collection	
  in	
  the	
  field.	
  	
  Visual	
  aids	
  were	
  also	
  developed	
  
to	
  supplement	
  interview	
  questions.	
  Illustrations	
  were	
  provided	
  to	
  interview	
  participants	
  to	
  
insure	
  construct	
  validity.	
  	
  In	
  providing	
  line	
  drawings	
  of	
  what	
  I	
  considered	
  wildlife	
  to	
  be	
  
	
  

87	
  

(and	
  not	
  to	
  be),	
  I	
  was	
  able	
  to	
  minimize	
  confusion	
  between	
  respondents	
  and	
  myself	
  about	
  
the	
  construct	
  of	
  wildlife.	
  I	
  was	
  also	
  able	
  to	
  maximize	
  understanding	
  among	
  different	
  
participants	
  about	
  the	
  construct	
  of	
  wildlife.	
  	
  
4.2.2.	
  Focus	
  group	
  procedures.	
  
This	
  research	
  adapted	
  risk	
  ranking	
  (Tschakert,	
  2007;	
  Smith,	
  Barrett	
  &	
  Box,	
  2000)	
  
and	
  threat	
  mapping	
  (Treves	
  et	
  al.,	
  2006)	
  techniques	
  to	
  capture	
  local	
  perceptions	
  of	
  HWC-­‐
related	
  risks.	
  Tschakert's	
  (2007)	
  risk	
  ranking	
  methodology,	
  which	
  allows	
  for	
  a	
  participant-­‐
centered	
  conceptualization	
  and	
  relative	
  weighting	
  of	
  risks,	
  was	
  adapted	
  to	
  aid	
  in	
  the	
  spatial	
  
depiction	
  of	
  risk	
  perceptions	
  (Appendix	
  A).	
  	
  	
  Treves'	
  et	
  al.	
  (2006)	
  spatially	
  explicit	
  
methodology	
  for	
  capturing	
  stakeholder	
  perceptions	
  of	
  risks	
  to	
  wildlife	
  was	
  maintained;	
  
however,	
  the	
  unidirectional,	
  researcher-­‐constrained	
  approach	
  was	
  modified	
  to	
  account	
  for	
  
stakeholders’	
  conceptualizations	
  of	
  HWC-­‐related	
  risks.	
  	
  While	
  both	
  methods	
  were	
  
developed	
  to	
  investigate	
  perceptions	
  in	
  a	
  unidirectional	
  manner	
  (e.g.,	
  Tschakert’s	
  (2007)	
  
livelihood	
  risk	
  target;	
  Treves’	
  et	
  al.	
  (2006)	
  biodiversity	
  risk	
  target),	
  they	
  were	
  adapted	
  to	
  
investigate	
  HWC-­‐related	
  risks	
  in	
  a	
  multidirectional	
  manner	
  in	
  accordance	
  with	
  research	
  
objectives.	
  	
  Synthesizing	
  both	
  approaches	
  proved	
  useful	
  for	
  this	
  research	
  context;	
  they	
  
proved	
  effective	
  and	
  efficient	
  for	
  data	
  collection.	
  
Future	
  research	
  may	
  employ	
  or	
  adapt	
  these	
  methods;	
  with	
  additional	
  field-­‐testing,	
  
visual	
  aids	
  may	
  significantly	
  improve	
  a	
  researcher's	
  ability	
  to	
  collect	
  valid	
  data	
  in	
  the	
  
context	
  of	
  low	
  literacy	
  or	
  English	
  as	
  a	
  second	
  language	
  contexts.	
  	
  Comparative	
  
methodological	
  research	
  between	
  the	
  developed	
  visual	
  Likert-­‐type	
  scale	
  and	
  extant	
  
alphanumeric	
  Likert-­‐type	
  scales	
  could	
  lead	
  to	
  further	
  developments	
  to	
  improve	
  scale	
  
validity	
  in	
  capturing	
  attitudinal	
  responses	
  in	
  a	
  variety	
  of	
  demographic	
  and	
  cultural	
  

	
  

88	
  

contexts.	
  	
  Additional	
  research	
  employing	
  the	
  adapted	
  focus	
  group	
  methodology	
  is	
  needed	
  
to	
  assess	
  its	
  effectiveness	
  not	
  only	
  as	
  a	
  data	
  collection	
  methodology	
  but	
  also	
  as	
  a	
  
participatory	
  tool	
  in	
  risk	
  management.	
  	
  
4.3.	
  PRACTICAL	
  IMPLICATIONS	
  
4.3.1.	
  HWC	
  interventions.	
  
Risk	
  perceptions	
  about	
  HWC	
  can	
  inform	
  the	
  design,	
  implementation,	
  and	
  evaluation	
  
of	
  more	
  effective	
  interventions	
  designed	
  to	
  reduce	
  negative	
  HWC	
  consequences	
  on	
  
livelihoods	
  and	
  wildlife.	
  	
  For	
  example,	
  practitioners	
  may	
  leverage	
  information	
  provided	
  on	
  
combined	
  risk	
  perception	
  and	
  assessment	
  maps	
  to	
  more	
  accurately	
  target	
  HWC-­‐related	
  
services	
  to	
  the	
  areas	
  that	
  need	
  it	
  most	
  (e.g.,	
  regions	
  of	
  greatest	
  frequency	
  of	
  HWC,	
  regions	
  
experiencing	
  HWC	
  but	
  previously	
  ignored).	
  	
  The	
  use	
  of	
  spatially	
  explicit	
  and	
  colorful	
  risk	
  
maps	
  could	
  improve	
  risk	
  communication	
  in	
  the	
  conservancy	
  (Dransch,	
  Rotzoll	
  &	
  Poser,	
  
2010).	
  	
  For	
  example,	
  when	
  communicating	
  HWC	
  mitigation	
  strategies	
  to	
  stakeholders,	
  
maps	
  can	
  illustrate	
  areas	
  of	
  high	
  likelihood	
  of	
  risk	
  exposure	
  and	
  aid	
  individuals	
  in	
  
contextualizing	
  their	
  risk	
  perceptions	
  based	
  on	
  their	
  unique	
  situation	
  within	
  the	
  
conservancy’s	
  landscape	
  (Dransch	
  et	
  al.,	
  2010).	
  	
  
Detailed	
  insights	
  about	
  local	
  livelihood	
  and	
  wildlife	
  vulnerability	
  to	
  HWC	
  may	
  be	
  
used	
  to	
  guide	
  prioritization	
  of	
  HWC	
  management	
  to	
  focus	
  on	
  the	
  most	
  sensitive	
  people	
  and	
  
wildlife	
  resources	
  (Smith	
  et	
  al.,	
  2000;	
  Tschakert,	
  2007).	
  	
  For	
  example,	
  conservancy	
  
residents	
  reported	
  concerns	
  about	
  the	
  negative	
  consequences	
  of	
  retaliation	
  on	
  wildlife	
  yet	
  
they	
  did	
  not	
  prioritize	
  managing	
  that	
  risk	
  over	
  other	
  risks	
  (e.g.,	
  agricultural	
  activities,	
  
poaching).	
  	
  Characterizing	
  HWC-­‐related	
  risk	
  perception	
  and	
  vulnerability	
  may	
  provide	
  new	
  
opportunities	
  for	
  mitigation	
  and	
  strategies	
  for	
  improved	
  risk	
  management	
  (Smit	
  &	
  Wandel,	
  
	
  

89	
  

2006;	
  Tschakert,	
  2007).	
  	
  For	
  example,	
  conservancy	
  residents	
  identified	
  the	
  agricultural	
  
interface	
  between	
  people	
  and	
  wildlife	
  as	
  highly	
  problematic	
  for	
  managing	
  HWC	
  risks.	
  	
  The	
  
lack	
  of	
  land	
  use	
  zoning	
  within	
  the	
  conservancy	
  was	
  cited	
  as	
  increasing	
  vulnerability	
  at	
  this	
  
interface.	
  	
  	
  Zoning	
  areas	
  for	
  agriculture	
  and	
  wildlife	
  could	
  improve	
  management	
  of	
  crop	
  
damage	
  risk	
  and	
  reduce	
  agricultural	
  encroachment	
  into	
  wildlife	
  habitat.	
  	
  	
  	
  
Vulnerability	
  is	
  an	
  important	
  concept	
  for	
  evaluating	
  the	
  efficacy	
  of	
  HWC	
  
management	
  strategies;	
  participatory	
  evaluation	
  strategies,	
  especially	
  those	
  that	
  involve	
  
the	
  most	
  vulnerable	
  stakeholders	
  in	
  addition	
  to	
  experts	
  and	
  decision-­‐makers,	
  are	
  
considered	
  to	
  be	
  more	
  accurate	
  than	
  those	
  that	
  do	
  not	
  involve	
  vulnerable	
  stakeholders	
  
(Treves,	
  Wallace	
  &	
  White,	
  2009).	
  	
  While	
  residents	
  in	
  the	
  two	
  study	
  conservancies	
  failed	
  to	
  
differ	
  in	
  their	
  perceptions	
  of	
  the	
  likelihood	
  of	
  their	
  households	
  experiencing	
  an	
  HWC-­‐
related	
  risk,	
  this	
  research	
  identified	
  emerging	
  (versus	
  established)	
  conservancy	
  residents	
  
as	
  having	
  higher	
  perceptions	
  of	
  vulnerability	
  to	
  the	
  negative	
  consequences	
  of	
  such	
  risks.	
  	
  
Emerging	
  residents	
  also	
  viewed	
  some	
  HWC	
  management	
  strategies	
  (e.g.,	
  conservancy-­‐
prescribed	
  use	
  of	
  chili	
  as	
  a	
  wildlife	
  deterrent)	
  as	
  a	
  significant	
  threat	
  to	
  wildlife.	
  	
  	
  Being	
  
aware	
  of	
  the	
  existence	
  and	
  nature	
  of	
  vulnerability	
  perceptions	
  among	
  conservancy	
  
residents	
  can	
  aid	
  decision	
  makers.	
  	
  Decision-­‐makers	
  may	
  then	
  opt	
  to	
  explicitly	
  address,	
  
through	
  communication,	
  educational	
  or	
  other	
  efforts,	
  how	
  different	
  HWC	
  management	
  
strategies	
  will	
  affect	
  members'	
  and	
  wildlife’s	
  vulnerability.	
  	
  Such	
  understanding	
  may	
  help	
  
decision-­‐makers	
  better	
  anticipate	
  the	
  extent	
  to	
  which	
  stakeholders	
  will	
  accept	
  certain	
  HWC	
  
interventions	
  (Treves	
  et	
  al.,	
  2009).	
  	
  If	
  decision-­‐makers	
  are	
  able	
  to	
  more	
  aptly	
  respond	
  to	
  
local	
  stakeholders,	
  there	
  is	
  the	
  potential	
  for	
  them	
  to	
  increase	
  stakeholders'	
  perceived	
  
legitimacy	
  of	
  management	
  interventions	
  (Kuperan	
  &	
  Sutinen,	
  1998).	
  

	
  

90	
  

Finally,	
  characterizing	
  stakeholder	
  perceptions	
  of	
  multiple	
  risks,	
  both	
  related	
  and	
  
unrelated	
  to	
  human	
  wildlife	
  interactions,	
  can	
  foster	
  understanding	
  about	
  how	
  discrete	
  
wildlife-­‐related	
  risks	
  may	
  most	
  effectively	
  be	
  managed	
  (Baird	
  et	
  al.,	
  2009).	
  	
  Data	
  herein	
  
indicate	
  that	
  stakeholders’	
  perceptions	
  of	
  risks	
  from	
  HWC	
  are	
  connected	
  to	
  and	
  contingent	
  
upon	
  a	
  wide	
  range	
  of	
  risks	
  to	
  livelihoods	
  and	
  wildlife.	
  	
  For	
  example,	
  stakeholders	
  perceived	
  
risks	
  such	
  as	
  human	
  financial	
  insecurity,	
  local	
  climate,	
  inadequate	
  conservancy	
  services	
  
and	
  socio-­‐cultural	
  insecurity	
  (human-­‐human	
  conflict)	
  as	
  threats	
  to	
  livelihoods	
  and	
  wildlife	
  
within	
  their	
  conservancies.	
  	
  This	
  information	
  could	
  be	
  used	
  to	
  formulate	
  interventions	
  
seemingly	
  unrelated	
  but	
  very	
  applicable	
  to	
  HWC,	
  such	
  as	
  human-­‐human	
  conflict	
  resolution	
  
or	
  improved	
  disaster	
  planning,	
  with	
  the	
  benefit	
  of	
  lessening	
  human	
  and	
  wildlife	
  
vulnerability	
  to	
  HWC	
  risks.	
  	
  Given	
  the	
  financial	
  and	
  social	
  resources	
  some	
  HWC	
  
interventions	
  require	
  (e.g.,	
  compensation	
  schemes),	
  anticipating	
  the	
  intervention’s	
  social	
  
viability	
  before	
  it	
  is	
  implemented	
  and	
  employing	
  indirect	
  interventions	
  when	
  appropriate	
  
could	
  be	
  invaluable	
  to	
  decision-­‐makers	
  with	
  limited	
  resources.	
  	
  
4.3.2.	
  Fostering	
  compliance.	
  
Illegal	
  conservancy	
  activities	
  such	
  as	
  poaching	
  are	
  of	
  concern	
  to	
  both	
  conservancy	
  
residents	
  and	
  decision-­‐makers.	
  	
  Unfortunately,	
  there	
  are	
  significant	
  logistical,	
  economic,	
  
and	
  sociopolitical	
  constraints	
  to	
  measuring	
  poaching	
  activities	
  in	
  conservancies	
  (Solomon,	
  
Jacobson,	
  Wald	
  &	
  Gavin,	
  2007;	
  Vaughan	
  &	
  Long,	
  2007).	
  	
  Equipped	
  with	
  an	
  increased	
  
understanding	
  of	
  the	
  local	
  context	
  of	
  human-­‐wildlife	
  interactions,	
  including	
  locally	
  relevant	
  
motivations	
  for	
  poaching,	
  conservation	
  practitioners	
  could	
  explore	
  alternatives	
  to	
  
financially	
  costly	
  deterrence	
  measures.	
  	
  Combining	
  Event	
  Book	
  data	
  with	
  residents’	
  
perceptions	
  captured	
  in	
  focus	
  groups	
  can	
  provide	
  a	
  rapid	
  and	
  cost	
  effective	
  way	
  to	
  

	
  

91	
  

holistically	
  and	
  more	
  accurately	
  assess	
  the	
  conservation	
  impact	
  and	
  geographical	
  extent	
  of	
  
illegal	
  activity.	
  	
  Such	
  information	
  can	
  prove	
  essential	
  for	
  conservancy	
  game	
  guards	
  who	
  are	
  
tasked	
  with	
  monitoring	
  and	
  enforcing	
  anti-­‐poaching	
  rules.	
  	
  Understanding	
  the	
  variety	
  of	
  
motives	
  to	
  poach	
  (Hampshire	
  et	
  al.,	
  2004),	
  the	
  geographic	
  extent	
  and	
  patterns	
  of	
  
interactions	
  between	
  people	
  and	
  wildlife	
  (Sánchez-­‐Mercado	
  et	
  al.,	
  2008)	
  in	
  the	
  
conservancy	
  may	
  allow	
  conservation	
  practitioners	
  to	
  more	
  deliberately	
  select	
  optimal	
  
management	
  strategies	
  for	
  reducing	
  poaching.	
  
A	
  number	
  of	
  pragmatic	
  questions	
  were	
  generated	
  and	
  necessitate	
  further	
  inquiry.	
  	
  
More	
  research	
  is	
  needed	
  to	
  understand	
  the	
  relationship	
  between	
  risk	
  perceptions,	
  
vulnerability	
  and	
  the	
  willingness	
  of	
  stakeholders	
  to	
  participate	
  in	
  specific	
  HWC-­‐related	
  
intervention	
  programs.	
  	
  For	
  instance,	
  do	
  high	
  perceptions	
  of	
  risk	
  influence	
  stakeholders’	
  
willingness	
  to	
  adopt	
  alternative	
  agriculture	
  or	
  animal	
  husbandry	
  practices?	
  	
  What	
  effects	
  
will	
  high	
  perceptions	
  of	
  risk	
  to	
  wildlife	
  have	
  on	
  acceptability	
  of	
  wildlife	
  deterrence	
  
programs	
  such	
  as	
  the	
  use	
  of	
  chili?	
  	
  Additionally,	
  understanding	
  how	
  different	
  interventions	
  
influence	
  the	
  behavior	
  and	
  attitudes	
  of	
  conservancy	
  stakeholders	
  could	
  be	
  of	
  interest	
  to	
  
practitioners.	
  	
  For	
  example,	
  do	
  monetary	
  compensation	
  schemes	
  decrease	
  negative	
  
attitudes	
  towards	
  wildlife	
  within	
  conservancies?	
  	
  Do	
  monetary	
  compensation	
  schemes	
  
influence	
  stakeholder	
  participation	
  in	
  HWC-­‐related	
  prevention	
  activities	
  within	
  
conservancies?	
  	
  Lastly,	
  monitoring	
  the	
  effectiveness	
  of	
  research	
  informed	
  interventions	
  in	
  
terms	
  of	
  decreased	
  HWC	
  vulnerability	
  and	
  increased	
  compliance	
  would	
  be	
  essential	
  to	
  
evaluate	
  such	
  approaches	
  in	
  terms	
  of	
  their	
  practical	
  and	
  theoretical	
  significance	
  in	
  
improving	
  HWC-­‐management.	
  	
  	
  
	
  
	
  

92	
  

APPENDICES	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

93	
  

APPENDIX	
  A	
  
	
  
Focus	
  Group	
  Protocol	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

94	
  

HWC FOCUS GROUP
Facilitator’s Handbook

Research funded by Michigan State University’s
Department of Fisheries & Wildlife

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95	
  

HWC: Risk Perception, Vulnerability & Compliance
FOCUS GROUP ACTIVITY: COMMUNITY MAPPING (CM) & PARITICPATORY RISK RANKING
(PRR)
Rationale
Community mapping (CM) is an effective way to spatially locate the areas within a community that
are most vulnerable to human-wildlife conflict (HWC). CM is adaptable and can explore gender and
age-stratified division of labor, which spatially influence the distribution of various people. These
constructs may be a useful in exploring the interactions between spatial and socio-demographic
vulnerability to HWC. CM can be used to explore people’s perceptions, needs, and access to
important resources within the community. Community maps may be left with a community to aid in
the HWC planning, monitoring, and evaluation. CM also serves as a good community entry
exercise.
Participatory risk ranking (PRR) is an effective way to quantify perceptions of risks to livelihoods and
biodiversity. PRR has been used successfully in developing countries, where participants may have
low literacy rates. PRR can explore similarities and differences between the risk perceptions of
local men, women and decision makers. Results from PRR can be mapped conceptually or spatially
and can inform discussions about solutions and response strategies, and evaluation metrics for
intervention measures intended to reduce risks from HWC.
Activity Objectives
Conducting the community mapping and participatory risk ranking activities has the following
objectives:
1. Identify risks to local biodiversity and livelihoods utilizing local perceptions.
2. Identify risks to regional biodiversity and livelihoods from HWC utilizing local perceptions.
3. Compare the perceived importance and severity of threats from HWC relative to threats unrelated
to HWC.
4. Depict threats to biodiversity and livelihoods from HWC spatially in order to assess vulnerability.
Time
Workshop (two full-days; one day prep); each day- 6 hours of activity; 1-hour lunch and two 15minute breaks
Session Outline
I. Introduction & Consent (day one); Question & Answers (day two)- (15-20 minutes)
II. Risk Ranking & Scoring- Livelihoods (day one); Biodiversity (day two)- (90-120 minutes)
BREAK (15 MINUTES)
III. Discussion- vulnerabilities – (30-40 minutes)
LUNCH (1 HOUR)
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96	
  

IV. Community Mapping- Part 1 (day 1); Part II (day 2) (60-90 minutes)
V. Discussions group (40-60 minutes)
BREAK (15 MINUTES)
VI. Debrief (25-30 minutes)
!"!
Participants
• All participants must be of 18 years of age.
• Participants will be chosen through consultation with leaders and opportunistically.
• Total number of participants will be 30: environmental decision makers (n <8-10), men (n< 810) and women (n< 8-10).
• Can be completed with up to 15 people in each group; men, women and key decision makers
complete the activities separately
• Only one participant per household unit.
Materials
Risk Ranking Activities

• Mylar or acetate transparent film (3
sheets large enough to cover maps)

• Large butcher paper or poster paper

• For relative HWC frequency, small
colored stickers of 3 different colors

• Large index cards of different colors
• Markers

• For social vulnerability, 3 different
shapes of colored stickers (same
approximate size; in three different
colors per shape-one shape needed for
each group mapping)

• Pebbles or beans (several hundred)
• Tape or glue
• Stickers

• For species involved in HWC, 2 small
sticky note pads

• Post-it notes
• Digital camera (for both activities

• For facilitator, small (11 x 8) print out of
larger map

Risk Mapping Activities
• Large aerial photograph, Arc View or
other GIS reference base map of the
community
• Grease pencils (assorted colors- 3 for
severity ranking and additional for
mapping features), markers of assorted
colors
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97	
  

FACILITATOR’S NOTE: You will need at least two people to facilitate this workshop. All
facilitators need to receive training on procedures before hand, receive a copy of this booklet
and recording instruments. Decision-makers may be surveyed prior to general workshop.
Materials should ultimately be left with the community or conservation area once facilitators
have adequately recorded information. Lead facilitator should provide a final report of finding to
the community/conservation area in an appropriate format.
Procedure
DAY ONE
I. INTRODUCTION & CONSENT (15-20 minutes)
You are being asked to participate in a research project related to understanding opinions of threats
to local livelihoods and wildlife from human-wildlife conflicts. I am required to make sure that you
understand that your participation in this workshop is voluntary, to explain the risks and benefits of
participating and answer any questions you have at any time.
I am a graduate student from the United States and my name is Jessica Kahler. I attend Michigan
State University and study human-wildlife interactions. By human-wildlife interactions I mean I study
the benefits and risks to both people and wildlife that live and interact in an area. This research
helps me complete requirements for my education, but more importantly may help improve
management of conflicts or negative interactions between people and wildlife.
I am very interested in hearing what you think about this topic. There are no wrong answers to the
questions and discussions that will take place at this workshop. I ask only for your honest opinion.
Your participation will help regional and local decision-makers better understand what local people
and communities think about conflicts between people and wildlife. Your responses are completely
confidential, as I will not record the names of people attending the workshop and all posters and
maps that are created will be created by the group, so no one person will be responsible for the
information on the maps and posters. The entire workshop should take two full days. You will be
provided with lunch, refreshments and all materials needed to complete the activities.
I would like to use my voice recorder and digital camera during the workshop. The voice recordings
will not be available for any local person or group to review. My American advisor and I will be the
only people to review the recording. I will take digital photographs of the maps and posters that the
group creates and I may also take photographs of participants or the group. If you are
uncomfortable with being photographed I will not photograph you.
These activities are voluntary, which means that you may choose not to participate in the workshop
at any time. If you do not understand the questions or activities please ask me and I will explain in
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98	
  

greater detail. You have been given some materials in a folder for the workshop. The folder also
has my contact information both here in Namibia and at my school in the US, if you should need to
contact me later. You must be at least 18 years of age to participate in this workshop. By remaining
here at the workshop you are telling me that you at least 18 years of age and want to participate.
Do you have any questions before we get started? Before we start I will go over the schedule for the
day.
!SCHEDULE SHOULD BE POSTED AT THE FRONT OF THE ROOM
II. RISK RANKING & SCORING- LIVELIHOODS (90-120 minutes)
1. INTRODUCE THE ACTIVITY
“A person’s livelihood is the way they come by or get the things they need to live. Many things can
threaten people and the things they value or rely on to live. These threats, sometimes called
worries, concerns, risks or dangers, may be of different importance to the community. Some worries
may be very serious and threaten human life or health, while others cause only small problems or
hassles. The reason we are going to do this activity is to find out what the worries or threats of the
community are and how important you think these worries are in threatening local people’s
wellbeing. This should take about 2 hours.”
2. FACILITATOR GIVES EACH PARTICIPANT A SET OF CARDS AND MARKERS AND GIVES
THE FOLLOWING INSTRUCTIONS
• On these cards I want you to write or draw a threat or worry that affects the entire community.
• Each card should have only one worry or threat on it.
• You can write or draw as many threats to the community as you want.
• These worries can be big problems or small problems; whatever you think worries the
community. The worries you list should be worries for the entire community not your
individual worries.
• If you need to write in your local language please feel free or if you need help please ask. I
will walk around the room to answer questions.
• Please take 20 minutes to write down as many worries as you can think of that threaten the
community and the lives of people in the community. Remember we are listing worries that
affects the entire community not your individual worries.
3. RANK THE LIVELIHOOD THREATS; USE A LARGE SHEET OF PAPER
• Now I want you to bring your cards with your worries, around this large piece of paper. The
paper has most important written at the top and least important written at the bottom.
• I want you to rank your worries starting with the most important worry to the community, then
the second most important and ending with the least important worry at the bottom.
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99	
  

• Everyone will get a chance to rank his/her worries and there is no wrong or right answer.
Remember the most worrisome threat will be at the top and the least worrisome will be at the
bottom.
• After you are happy with your ranking use this tape to attach your card to the paper.
4. FACILITATOR TURNS THE DISCUSSION TOWARDS HUMAN-WILDLIFE CONFLICT
“Human-wildlife conflicts are bad or negative interactions between people and wildlife. By wildlife I
mean all animals in the area, including birds and reptiles (i.e., such as snakes and lizards) that are
not domesticated animals or insects. Lets look at these pictures that show what animals are wildlife
and what animals are not wildlife.”
!FACILITATOR HAS PRE-PREPARED VISUAL WITH WILDLIFE, DOMESTICATED ANIMALS
AND INVERTEBRATES.
• It is important to remember that not all interactions or relationships between people and
wildlife are bad. Can you think of some benefits to living close to wildlife?
• However, bad interactions or negative relationships may threaten both people and the
animals themselves. Can you think of different threats to people’s livelihoods from bad
interactions between people and wildlife? (i.e., What about wildlife injuring people? How
about threats from wildlife to gardens or livestock? Does wildlife ever make people in the
community feel afraid or scared?)
• Are human-wildlife conflicts a worry for the local community?
• Lets look at our worries and rankings again. Are any of the worries that you listed humanwildlife conflicts? If so, lets put a sticker on the cards that are or could be human-wildlife
conflicts.
• Are there any worries from human-wildlife conflicts that are not on your lists? If there are, lets
put them on a card and put them in your rankings where you feel they belong in relation to
threats that are not related to wildlife conflict.
5. QUANTIFY THE THREAT SEVERITY
• Some worries or threats may be very harmful to people’s wellbeing or livelihoods, while
others may not be very harmful but are much smaller problems or hassles.
• I am going to give you five beans for each of the worries you listed. You are going to use
these beans to give a score to the worries; giving five beans to a worry means that that worry
is life threatening, while giving one bean to a worry means that the worry is very little problem
or only a hassle. Giving a worry four beans would mean that the worry is less threatening
than a five but more threatening than a three, while giving a worry two beans means it is
more than a small hassle but less threatening than five, four and three beans.
• You can give your worries each a score of 1,2,3,4 or 5. Now you can score your worries;
remember a score of 5 means it is life threatening while the lowest score of one the smallest
problem or hassle.
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100	
  

• There are no right or wrong numbers of beans.
!FACILITATOR ALLOWS PARTICIPANTS TO SCORE THEIR RISK RANKING; AFTER
SCORING IS COMPLETED THE ASSISTANT NEEDS TO RECORD THE NUMBER OF BEANS ON
EACH CARD OR RECORD SHEET
!BREAK 15 MINUTES (REFRESHMENTS)
6. DESCRIBING AND QUANTIFYING THE THREATS
• Lastly, lets talk about the threats to your livelihood from human-wildlife conflict. I am going to
list all the HWCs; that you listed and scored in your ranking as threats to local livelihoods on
these large sheets of paper.
• We are going to discuss these threats and write down some important information regarding
these threats.
!THESE ARE GROUP DISCUSSIONS AND WILL BE RECORDED THROUGH A CONCENSUS.
FACILITATOR WILL GUIDE PARTICIPANTS TO ANSWER EACH OF THE FOLLOWING
QUESTIONS FOR EACH HWC THREAT (ANSWERING ALL QUESTIONS FOR ONE THREAT
THEN MOVING TO THE NEXT THREAT. VISUAL SCALES WILL BE USED FOR QUESTIONS A,
C AND D.
A. How often does this activity or threat happen? Lets use this scale to give this threat a
number score.
0-NEVER, 1-RARELY, 2-SOMETIMES & 3- OFTEN
B. When during the year does this threat happen (i.e., certain months or wet/dry seasons)?
Does it happen the same time every year?
C. Overall, how threatening is this human-wildlife conflict to community livelihoods?
0- NO THREAT, 1-LOW THREAT, 2-MEDIUM THREAT AND 3-HIGH THREAT
D. How important is it for the community to take steps to reduce this threat?
0-NOT IMPORTANT, 1-LOW IMPORTANCE, 2- MEDIUM IMPORTANCE, 3- HIGH IMPORTANCE
E. What animals (i.e., species or types of animals) are involved with this particular threat?
FACILITATOR HAS COMMON SPECIES CARDS AVAILABLE AND AS DISCUSSION PROCEEDS
THE SPECIES ARE PRESENTED.
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101	
  

• Now, that you have chosen the animals please rank them from the most important animal
involved in this threat to the least important. Feel free to talk among yourselves and come to
a decision.
• Once you have a decision, please attach your animals to the sheet in the order from the most
important to the least important.
III. DISCUSSION-VULNERABILITITES (30-40 minutes)
1. FACILITATOR INTRODUCES IDEA OF VULNERABILITY AND LEADS DISCUSSION OF HWC
VULNERABILITY
!THIS IS A GROUP DISCUSSION AND FACILITATOR MODERATES THE DISCUSSION AND
TAKES NOTES; VULNERABILITY FACTORS THAT HAVE STRONG SUPPORT ARE LISTED ON
THE THREAT DESCRIPTION POSTERS WITH BRIEF DISCRIPTIONS
“Lets look at each of the threats and discuss who in the community faces the most threat from this
conflict. People in your community may have different chances of experiencing a conflict with
wildlife. People in your community may also be different in their ability to cope or recover from a
conflict with wildlife after a conflict has happened.”
•

Are there different traits that make people more likely to have a conflict with wildlife in your
community (e.g., where their land is located, how large their land may be, if they take
measures to scare away wildlife)?

• Are there different traits that make some people suffer more than others once a conflict with
wildlife has happened (e.g., how many people live in the household, gender, wealth,
landholding size)?
"LUNCH (1 HOUR)
IV. COMMUNITY MAPPING PART 1 (60-90 minutes)
1. INTRODUCTION TO COMMUNITY MAPPING
“Community maps can be important to show where in the area many of the conflicts with wildlife
happen and who lives and works in those areas. This is a map of your community and the
surrounding area. The purpose of this activity is for you to show where the important areas and
resources are in your community, where there have been conflicts with wildlife, which animals are
involved in those conflicts, how often these conflicts occur and where in the community particular
community members spend time to work and live. Once we are done with this activity we will have a
good picture of where in the community conflicts with wildlife occur. This activity should take less
than two hours. “
• Lets gather around and look at this map. Has anyone ever seen a map before? On this map
let’s locate some important areas for the community.
FACILITATOR WILL USE A GEOREFERENCED BASE MAP WITH PRE-MAPPING OF KEY
AREAS IN THE COMMUNITY BY CONSULTING LOCAL LEADERS.
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102	
  

Lets quickly locate some important features on the map that are found in the community:
a. Locate rivers, lakes, ponds and community water sources.
b. Locate important community areas, places to gather for meetings, schools, clinics, roads,
businesses, guest areas and community projects.
c. Locate houses, village boundaries, fences, gardens and livestock areas.
• Are there any important community areas are not on the map? If so, lets take this pencil and
add the important areas to the map.
2. MAPPING SOCIAL SPACES
1. Next, I am going to give each of you a set of stickers and we are going to discuss where you
spend the most time completing tasks and activities.
• The blue stickers indicate areas where you spend the least amount of time, such as an area
visited only a few times a year.
• The yellow sticker indicates an area that you visit more often, such as an area you may visit
nearly monthly.
• Finally, the red sticker indicates and area that you spend a great deal of time completing
tasks and activities, an area that you visit almost weekly or more than once a week.
• Lets discuss which places you and other women in your community spend their time and
when you have decided please put your stickers on the map.
• Remember, blue stickers are places you spend the least amount of time, yellow stickers are
areas you more time and the red are areas you are in almost every day.
!THIS ACIVITY IS COMPLETED ON TRANSPARENT SHEETS SECURED TO THE ORIGNAL
BASEMAP OF COMMUNITY RESOURCES AND ACTIVITIES. ALL LAYLERS NEED TO BE
PHOTOGRAPHED USING A DIGITAL CAMERA FOR LATER ANALYSIS.
3. MAPPING HWC
“We are now going to use the HWC threat posters that we created and map these threats onto the
community map. First lets number the threats from human wildlife conflict to your livelihoods starting
with number one. Write the number on each poster.”
• I am going to give you each a set of three different markers. Lets look at the posters and the
numbers related to how threatening this threat is to community livelihoods.
• We are going to draw where these threats occur on the map. This may be a circle, a line or a
dot depending on how large of an area this threat happens in.
• The blue marker is for the low threat worries; an area where wildlife conflict occurs yet has
little impact on the community or families, as the damage from the conflict is minimal. These
are threats that were ranked as a one.
!

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103	
  

• The yellow marker will represent medium threat or an area where the wildlife conflict occurs
and has some impact on the community or families, as the damage from the conflict is
moderate or more severe. These threats are those that were ranked as a number two on our
number scale.
• The red marker is for areas where the wildlife damage is the most severe, area of high threat,
and has a great impact on the community or families. These are threats listed scored as a
three on our number scale.
• Make sure to write the number of the conflict in the circle or next to the line or point.
• You can talk with each other about the map and share your ideas. However, remember that
each have your individual knowledge of where wildlife conflict occurs. Please be respectful of
everybody’s thoughts. You may have some areas where you share conflict and others that
are different from your peers.
• After you have made your final comments and collected your thoughts you may draw the
threat areas on the map with the color that corresponds to the level of threat on its poster.
!FACILITATOR WILL, AT A LATER TIME TRANSFER INFORMATION FROM THE HWC
THREAT POSTERS (FREQUENCY, IMPORTANT SPECIES INVOLVED) ONTO THE THREAT
MAP IN THE CORRECT POLYGON OR ON THE CORRECT LINE OR POINT.
V. GROUP DISCUSSIONS (40-60 minutes)
1. GROUP DISCUSSION ABOUT RESULTS OF MAPPING ACTIVITY
• Are there any surprising things that you see from looking at the maps?
• What are some ways that the community has tried to lessen the threat from human-wildlife
conflict or solve human wildlife conflicts?
• For each worry related to a human wildlife conflict, the posters we have created, lets write a
few common ways that the community or individuals cope or deal with the conflict.
• For each strategy or way the community has tried to solve or lessen the conflict lets talk
about how good this strategy is at helping the community or individuals deal with the conflict.
• Sometimes there are people who benefit from certain solutions (i.e. winners, gain a benefit)
and others that do not or are actually harmed even more (i.e. losers, do not benefit). For
each solution lets discuss who benefits and who does not benefit.
• What do you think are the best things the community could do to help reduce or solve the
most worrisome problems related to human-wildlife conflict?
Thank you for completing this activity. I will work to make one list with total scores for each worry
and present it to community before I leave the village.

!

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104	
  

We need a couple volunteers to present our posters and maps to the large group after break. Select
a reporter from the group to discuss the final map with the entire group. Now lets take a short break
and we will come back in one large group to close the day’s activities.
!BREAK 15 MINUTES
VI. DEBRIEF (25-30 minutes)
1. GROUP DISCUSSIONS OF RISK RANKING AND MAPPING ACTIVITY
• Now lets look at the maps created. Each group’s reporters please briefly discuss your maps
and posters with the entire group. Please describe the map to the group.
• Are there areas within the community that have more severe conflicts with wildlife?
• Are there areas within the community that have conflicts more often than others?
• Do any areas overlap with areas often used in completing daily tasks and activities?
•

Are there concerns about conflicts with particular animals?

IF THE ACTIVITY WAS CONGRUENTLY COMPLETED BY MEN AND WOMEN:
Now that we have looked at both group’s maps, discuss the similarities and differences between
these two maps.
• What do you think are the reasons for the differences and the similarities?
• Are the areas that men and women use the same in terms of frequency and severity of
conflicts with wildlife? If not, why might that be?
• What do you think are the best things the community could do to help reduce or solve the
most threatening problems for wildlife related to human-wildlife conflict?
Thank you for completing that activity. I will work to complete one community map based on the two
maps that you completed and make one list with total scores for each threat and present it to
community before I leave the village.
Are there any questions?
CLOSING DAY ACTIVITIES, REMARKS AND ANNOUNCEMENTS
!
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5"/#$,/&(!3&"#6$,&".#5.#/&),$(#$3&'",&#,(!/5",#(#*"!&(!3&(!(+8/*/9&&
".#5.#/&(,$&+$'#&:*#6&#6$&)"--.!*#8&#"&6$+5&(*3&+")(+&5+(!!*!49&

DAY TWO

I. ICEBREAKER, QUESTIONS & ANSWERS (15-20 minutes)
FACILITATOR MAY CHOOSE APPROPRIATE ICEBREAKER ACTIVITY OR ASK SOMEONE TO
OPEN WITH PRAYER IN ACCORDANCE WITH LOCAL CUSTOM
!

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105	
  

• Does anyone have any questions from yesterday’s activities?
• Does anyone have any comments from yesterday’s activities?
FACILITATOR PRESENTS THE SCHEDULE FOR DAY TWO’S ACTIVITIES AND SPLITS THE
GROUPS INTO TWO.
II. RISK RANKING & SCORING-BIODIVERSITY (90-120 minutes)
1. INTRODUCE THE ACTIVITY
“Today we are going to discuss threats to local wildlife in your area. By wildlife I mean all animals in
the area, including birds and reptiles (e.g., such as snakes and lizards) that are not domesticated
animals or insects. Lets look again at these pictures that show what animals are wildlife and what
animals are not wildlife. Many things can threaten wildlife and the things they rely on to live. These
threats, sometimes called concerns, risks or dangers, may be of different importance to the wildlife.
Some threats may be very serious and threaten to reduce wildlife numbers, reduce the types or
diversity of wildlife found in the area or make them go extinct, while others cause only small
problems for wildlife. The reason we are going to do this activity is to find out what the threats to
wildlife are and how important you think these threats are in reducing healthy wildlife numbers and
types of wildlife found in the area. This should take about 2 hours.”
2. FACILITATOR GIVES EACH PARTICIPATN A SET OF CARDS AND MARKERS AND GIVES
THE FOLLOWING INSTRUCTIONS
• On these cards I want you to write or draw a threat that affects or threatens wildlife in this
area.
• Each card should have only one threat on it.
• You can write or draw as many threats to the wildlife as you want. These threats can be big
problems or small problems; whatever you think threatens the local wildlife.
• If you need to write in your local language please feel free or if you need help please ask. I
will walk around the room to answer questions.
• Please take 20 minutes to write down as many threats as you can think of that endanger or
threaten local wildlife.
• Remember we are listing threats from people or not from people that affects wildlife.
•

If you write down an activity that people do that threatens wildlife this does NOT mean that
you do this activity.

• Try to think about regional or local threats, not just large global threats, such as global
warming, but threats that are manageable by local people.
3. RANK THE LIVELIHOOD THREATS; USE A LARGE SHEET OF PAPER AND TAPE
• Now I want you to bring your cards, the threats, around this large piece of paper. The paper
has most important written at the top and least important written at the bottom.
!

"#!

	
  
	
  

	
  

106	
  

• I want you to rank your threats starting with the most important, the most threatening to
wildlife on top, then the second most important and ending with the least important threat at
the bottom.
• Everyone will get a chance to rank his/her threats and there is no wrong or right answer.
Remember the most worrisome threat will be at the top and the least worrisome will be at the
bottom.
• After you are happy with your ranking use this tape to attach your card to the paper.
4. FACILITATOR TURNS THE DISCUSSION TOWARDS HUMAN-WILDLIFE CONFLICT
Human-wildlife conflicts are bad or negative interactions between people and wildlife. It is important
to remember that not all interactions or relationships between people and wildlife are bad, as we
discussed yesterday.
However, bad interactions or negative relationships may threaten both people and the animals
themselves.
• Can you think of different threats to wildlife that result from a conflict with people? (i.e. What
about people killing wildlife because of threats to gardens or livestock? How about threats
from people to the places wildlife depend on to live? What about poisoning or pollution? What
about disease from livestock?)
• Are human-wildlife conflicts a threat to local wildlife?
• Lets look at our threats and rankings again. Are any of the threats that you listed humanwildlife conflicts or are these threats on wildlife because of a bad interaction with people? If
so, lets put a sticker on the cards that are human-wildlife conflicts.
• Are there any threats to wildlife from human-wildlife conflicts that are not on your lists? If
there are, lets put them on a card and put them in your rankings where you feel they belong.
5. QUANTIFY THE THREAT SEVERITY
• Some threats may be very harmful to wildlife, while others may not be very harmful but are
much smaller problems that wildlife may easily recover from. I am going to give you five
beans for each of the threats you listed. You are going to use these beans to give a score to
the threats.
• Giving five beans to a threat means that that threat is very serious and may result in the loss
of a species or type of animal in the area, while giving one bean to a worry means that the
worry is very little problem and does not affect overall wildlife numbers or types of wildlife in
the area.
• Giving a threat four beans would mean that the threat is less threatening than a five but more
threatening than a three, while giving a threat two beans means it is more than a small
problem but less threatening than five, four and three beans.
• You can give your threats to wildlife each a score of 1,2,3,4 or 5.
!

"#!

	
  
	
  

	
  

107	
  

• Now you can score your worries; remember a score of 5 means it is very threatening while
the lowest score of one the smallest problem.
!FACILITATOR ALLOWS PARTICIPANTS TO SCORE THEIR RISK RANKING; AFTER
SCORING IS COMPLETED THE ASSISTANT NEEDS TO RECORD THE NUMBER OF BEANS ON
EACH CARD OR RECORD SHEET
!BREAK 15 MINUTES (REFRESHMENTS)
6. DESCRIBING AND QUANTIFYING THE THREATS
• Lastly, lets talk about the threats to wildlife from human-wildlife conflict. I am going to list all
the HWCs that you listed and scored in your ranking as threats to local wildlife on these large
sheets of paper.
•

We are going to discuss these threats and write down some important information regarding
these threats.

!THESE ARE GROUP DISCUSSIONS AND WILL BE RECORDED THROUGH A CONCENSUS.
FACILITATOR WILL GUIDE PARTICIPANTS TO ANSWER EACH OF THE FOLLOWING
QUESTIONS FOR EACH HWC THREAT (ANSWERING ALL QUESTIONS FOR ONE THREAT
THEN MOVING TO THE NEXT THREAT. VISUAL SCALES WILL BE USED FOR QUESTIONS A,
C AND D.
A. How often does this activity or threat happen? Lets use this scale to give this threat a
number score.
0-NEVER, 1- RARELY, 2-SOMETIMES, 3- OFTEN
B. When during the year does this threat happen (i.e., certain months or wet/dry seasons)?
Does it happen the same time every year?
C. Overall, how threatening is this human-wildlife conflict to wildlife?
1-LOW THREAT, 2-MEDIUM THREAT AND 3-HIGH THREAT
D. How important is it for the community to take steps to reduce this threat to local wildlife?
0-NOT IMPORTANT, 1-LOW IMPORTANCE, 2-MEDIUM IMPORTANCE, 4- HIGH IMPORTANCE
E. What animals (i.e. species or types of animals) are threatened the most by these conflicts?
FACILITATOR HAS COMMON SPECIES CARDS AVAILABLE AND AS DESCUSSION
PROCEEDS THE SPECIES ARE PRESENTED.
• Now, that you have chosen the animals please rank them from the most threatened animal
involved to the least important. Feel free to talk among yourselves and come to a decision.
• Once you have a decision, please attach your animals to the sheet in the order from the most
threatened to the least threatened.
III. DISCUSSION-VULNERABILITITES (30-40 minutes)
!

"#!

	
  
	
  

	
  

108	
  

1. FACILITATOR INTRODUCES IDEA OF VULNERABILITY AND LEADS DISCUSSION OF HWC
VULNERABILITY
!THIS IS A GROUP DISCUSSION AND FACILITATOR MODERATES THE DISCUSSION AND
TAKES NOTES; VULNERABILITY FACTORS THAT HAVE STRONG SUPPORT ARE LISTED ON
THE THREAT DESCRIPTION POSTERS WITH BRIEF DISCRIPTIONS
“Lets look at each of the threats and discuss which animals face the most threat from this conflict.
Different species or kinds of animals may have different chances of experiencing a conflict with
people. Different species in your area may also be different in their ability to cope or recover from a
conflict with people after a conflict has happened.”
• Are there different traits that make certain animals more likely to have a conflict with people in
your community (e.g., where these animals forage or drink water, how large their territory
needs to be, migration patterns, cultural factors, hunting or foraging patterns)?
• Are there different traits that make some animals suffer more than others once a conflict with
wildlife has happened (e.g., how long it takes to reproduce, other threats they face,
behavioral factors)?
"LUNCH (1 HOUR)
IV. COMMUNITY MAPPING PART 2 (60-90 minutes)
FACILITATOR IS TO CLEAN OR REMOVE THE MYLAR SHEET FROM DAY ONE ACTIVITIES
AND REPLACE WITH A CLEAN SHEET
1. MAPPING THREATS TO WILDLIFE
We are now going to use the threat posters that we created and map these threats onto the
community map.
• First lets number the threats from human wildlife conflict to wildlife starting with number one.
Write the number on each poster.
• I am going to give you each a set of three different markers. Lets look at the posters and the
numbers related to how threatening this threat is to wildlife.
• We are going to draw where these threats occur on the map. This may be a circle, a line or a
dot depending on how large of an area this threat happens in.
• The blue marker is for the low threat worries; an area where wildlife conflict occurs yet has
little impact on local wildlife, as the damage from the conflict is minimal. These are threats to
wildlife that we gave a score of one.
• The yellow marker will represent medium threat or an area where the wildlife conflict occurs
and has some impact on the wildlife, as the damage from the conflict is moderate or more
severe. These threats had a score of two.
!

"#!

	
  
	
  

	
  

109	
  

• The red marker is for areas where the damage or threat to wildlife is the most severe, area of
high threat, and has a great impact on the local wildlife numbers or variety. These threats are
the ones that you gave a score of three.
• Make sure to write the number of the conflict in the circle or next to the line or point.
• You can talk with each other about the map and share your ideas. However, remember that
each have your different knowledge of where these threats occur. Please be respectful of
everybody’s thoughts.
• After you have made your final comments and collected your thoughts you may draw the
threat areas on the map with the color that corresponds to the level of threat on its poster.
V. GROUP DISCUSSION (40-60 minutes)
1. GROUP DISCUSSION ABOUT RESULTS OF MAPPING ACTIVITY
• Are there any surprising things that you see from looking at the maps?
• What are some ways that the community has tried to lessen the threat from human-wildlife
conflict or solve human wildlife conflicts?
• For each worry related to a human wildlife conflict, the posters we have created, lets write a
few common ways that the community or individuals cope or deal with the conflict.
• For each strategy or way the community has tried to solve or lessen the conflict lets talk
about how good this strategy is at helping the community or individuals deal with the conflict.
• Sometimes there are people who benefit from certain solutions (i.e. winners, gain a benefit)
and others that do not or are actually harmed even more (i.e. losers, do not benefit). For
each solution lets discuss who benefits and who does not benefit.
!FACILITATOR WILL RETURN TO THE THREAT MAPS AND RECORD GROUP RESPONSES
IN TERMS OF STRATEGY EFFICIENCY AND WHO IS BENEFITING FROM THE STRATEGY.
THIS IS A GROUP DISCUSSION.
• What do you think are the best things the community could do to help reduce or solve the
most worrisome problems related to human-wildlife conflict?
Thank you for completing this activity. I will work to make one list with total scores for each worry
and present it to community before I leave the village.
We need a couple volunteers to present our posters and maps to the large group after break. Select
a reporter from the group to discuss the final map with the entire group. Now lets take a short break
and we will come back in one large group to close the day’s activities.
!BREAK 15 MINUTES
!

"#!

	
  
	
  

	
  

110	
  

VI. DEBRIEF (25-30 minutes)
1. GROUP DISCUSSIONS OF RISK RANKING AND MAPPING ACTIVITY
Now lets look at the maps created. Each group’s reporters please briefly discuss your maps and
posters with the entire group. Please describe the map to the group.
• Are there areas within the community that have more severe conflicts with wildlife?
• Are there areas within the community that have conflicts more often than others?
• Do any areas overlap with areas often used in completing daily tasks and activities?
• Are there concerns about conflicts with particular animals?
If the activity was congruently completed by men and women:
• Now that we have looked at both group’s maps, discuss the similarities and differences
between these two maps. What do you think are the reasons for the differences and the
similarities?
• Are the areas that men and women use the same in terms of frequency and severity of
conflicts with wildlife? If not, why might that be?
• What do you think are the best things the community could do to help reduce or solve the
most threatening problems for wildlife related to human-wildlife conflict?
Thank you for completing that activity. I will work to complete one community map based on the two
maps that you completed and make one list with total scores for each threat and present it to
community before I leave the village.
• Are there any questions?
CLOSING DAY ACTIVITIES, REMARKS AND ANNOUNCEMENTS

!"#$%&'()*+*#(#",&-./#&#(0$&$1#$!/*2$&3*4*#(+&56"#"4,(56/&"'&
#6$&-(5/7&5"/#$,/&(!3&"#6$,&".#5.#/&),$(#$3&'",&
#,(!/5",#(#*"!&(!3&(!(+8/*/9&&".#5.#/&(,$&+$'#&:*#6&#6$&
)"--.!*#8&#"&6$+5&(*3&+")(+&5+(!!*!49&

Relevant Methodological References
• Model Sessions: PACA Tools (Booklet #5). U.S. Peace Corps Training Sessions. ICE:
GED5_pacatools.pdf, p. 3-8.
• Treves, A. et al., (2006). A Simple, Cost-Effective Method for Involving Stakeholders in
Spatial Assessments of Threats to Biodiversity. Human Dimensions of Wildlife, 11, 43-54.
!

"#!

	
  
	
  

	
  

111	
  

• Tschakert, P. (2007). Views from the vulnerable: Understanding climatic and other stressors
in the Sahel. Global Environmental Change – Human and Policy Dimensions, 17 (3-4), pp.
381-396.
• Tschakert, P.I. (2009). Participatory Assessment and Learning Tools: Participatory Risk
Mapping, Ranking, and Scoring. Climate Change Collective Learning and Observatory
Network Ghana. (In press, acquired through personal communication with author).
• Smith, K., Barrett, C.B., and Box, P.W. (2000). Participatory Risk Mapping for Targeting
Research and Assistance: With an Example from East African Pastoralists. World
Development, 28 (11), pp. 1945-1959.
• Quinn, C.H., Huby, M., Kiwasila, H. and Lovett, J.C. (2003). Local perceptions of risk to
livelihood in semi-arid Tanzania. Journal of Environmental Management, 68, pp.111-119.
• Wildlife Conservation Society (WCS), September (2004). Technical Manual 1: Participatory
spatial assessment of human activities- a tool for conservation planning. Living Landscapes
Program-Human Activities Mapping, 1-12.

!

"#!

	
  
	
  

	
  

112	
  

APPENDIX	
  B	
  
	
  
Interview	
  Guide	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

113	
  

Opinions of Risks to Local
Livelihoods & Wildlife from
Human-Wildlife Conflict

!

Research funded by Michigan State University’s
Department of Fisheries & Wildlife
!

	
  
	
  

114	
  

INTERVIEW GUIDE- VERBAL CONSENT SCRIPT
I am a graduate student from the United States and my name is Jessica Kahler. I attend
Michigan State University and study human-wildlife conflicts. By human-wildlife conflicts I
mean a bad or negative interactions between people and wildlife. This research helps
me complete requirements for my education, but more importantly may help improve
management of conflicts between people and wildlife.
I am very interested in hearing what you think about this topic. There are no
wrong answers to the questions that will be asked. I ask only for your honest opinion.
Your participation will help researchers, regional and local decision-makers better
understand the threats to local people, communities and wildlife from conflicts between
people and wildlife. Your responses are completely confidential, as I will not record your
name in association with your answers. I will only give your interview a number. The
entire interview should take about 1 hour - 1.5 hours.
This interview is voluntary, which means that you may choose not to participate in
interview at any time. You may also chose not answer a particular question of the
interview. If you do not understand the questions please ask me and I will be happy
explain in greater detail. You must be at least 18 years of age to participate in this
interview. By saying “Yes I understand,” you are telling me that you at least 18 years of
age and want to participate.
Do you have any questions before we get started?
HWC INTERVIEW: Risk Perception, Vulnerability & Compliance
Case Study Code: _03- ______Language: ___________ Date:___________________
Interview #: ______________ Time Start: ____________
Setting (circle one):

Residential

Outdoors

!

Commercial

Community
"!

	
  
	
  

Time End: ____________

115	
  

Introduction & Ice-Breakers
Many of the questions that I am going to have you answer will have a number as an
answer. This picture illustrates the numbers (SHOW IMAGE). Larger numbers indicate
more or greater, which can mean that you have more concern, you think there is more
threat or you think it always happens. Lower numbers indicate you have less concern,
you think there is a little threat or you think it never happens. First you get a chance to
practice using the number scale. [INTERPRETERS EXPLAIN SCALE]
1. How often did you eat porridge last year?
0
1
2
Never
Rarely
Sometimes

3
Often

2. Please tell me how concerned you are that South Africa’s football team will beat
Namibia’s football team during the world cup in 2010.
0
1
2
3
No
Low
Medium
High
concern
concern
concern
concern
Section 1: Factors influence HWC
Human-wildlife conflicts (HWC1) are bad or negative interactions between people and
wildlife. [INTERPRETER AND RESEARCHER SHOW VISUAL AID THAT CLARIFIES
WILDLIFE]. HWCs can threaten the health and safety of either people or wildlife. I am
going to ask you how you feel about human-wildlife conflicts.
3. How often does HWCs happen in your community?
0
Never

1
Rarely

2
Sometimes

3
Often

4. Do you think that the current threat from conflicts with wildlife to your
community is low enough (i.e., is the risk of HWC to your community okay)?
YES or

NO

IF NO: Are the threats from wildlife to your community?
1
2
3
Low
Medium
High
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

HWC will be used as shorthand through the remainder of the document. Investigator will say
“human-wildlife conflict” throughout interview.
1

!

"!

	
  
	
  

116	
  

5. Do you think that the current threat from people to local wildlife populations is
low enough (i.e., is the risk of HWC to local wildlife populations okay)?
YES or
NO
If NO, are the threats to local wildlife populations from people?
1
2
3
Low
Medium
High
6. How much do you think that natural factors (i.e., drought, or floods) increase
conflicts with wildlife in your area?
0
1
2
3
No
Low
Medium
High
increase
increase
increase
increase
7. How much do you think that your community’s development (i.e., where people
build housing or plant crops) increases conflicts with wildlife in your area?
0
No
increase

1
Low
increase

2
Medium
increase

3
High
increase

8. How much control do you think you have over whether your family has a
conflict with wildlife?
0
No
control

1
Low
control

2
Medium
control

3
High
control

9. Does everyone in your community have the same chance to benefit from local
wildlife?
YES or

NO

IF NO: In your community, how much are the benefits from wildlife shared?
0
1
2
3
No
Low
Medium
High
sharing
sharing
sharing
sharing

!

"!

	
  
	
  

117	
  

10. Does everyone in your community have the same risk of experiencing a
conflict with wildlife?
YES
or
NO
IF NO: In your community, how much are the risks (threats) from conflicts with wildlife
shared?
0
No
sharing

1
Low
sharing

2
Medium
sharing

3
High
sharing

Section 2: Perception of risks to livelihoods from HWC
I am now going to ask you questions about the threats from wildlife to your livelihood. By
livelihood I mean your way of life and your quality of life. Seeing a wild animal is not
necessarily a conflict unless you feel bad or threatened.
11. People have different levels of concern about living with wildlife. How
concerned are you personally about:
No
concern

Low
concern

Medium
concern

High
concern

Being injured by wildlife

0

1

2

3

Damage to agricultural products caused by
wildlife (e.g., crops, fisheries)

0

1

2

3

How concerned are you personally about:
Loss of livestock to wildlife

0

1

2

3

Damage to your property caused by wildlife
(e.g., equipment, fence, house)

0

1

2

3

1

2

3

How concerned are you personally about:
The work needed to keep wildlife
away from your agricultural property
(e.g., crops, livestock, fisheries)

0

!

"!

	
  
	
  

118	
  

How concerned are you personally about:
Feeling threatened by wildlife

0

1

2

3

Conflicts with other people in your
community over wildlife issues

0

1

2

3

Livestock getting a disease from wildlife

0

1

2

3

12. People have different levels of concern about loss that may result from humanwildlife conflict. How concerned are you that a conflict with wildlife that would:
No
concern

Low
concern

Medium
concern

High
concern

Reduce your household food supply

0

1

2

3

Reduce family income
(i.e. lost marketable products)

0

1

2

3

How concerned are you that a conflict with wildlife that would:
Reduce household labor available
due to injury caused by wildlife

0

2

3

0

Increase labor needs due to agricultural
damage by wildlife

1

1

2

3

How concerned are you that a conflict with wildlife that would:
Reduce your family’s ability to meet
cultural obligations (e.g., festivals, weddings,
pay fines)

!

2

3

1

2

3

"!

	
  
	
  

1

0

Reduce your family’s social status
(e.g., reduction in livestock #’s or wealth)

0

119	
  

How concerned are you about losses from conflict with wildlife that may:
Reduce your family’s happiness due to worry

0

1

2

3

Reduce future wildlife resources to benefit
your grandchildren (i.e., future generations)

0

1

2

3

13. Now I am going to ask you about how often you come up against certain types
of threats from conflicts with wildlife. We are going to use this scale [SHOW
SCALE AND GO THROUGH CATEGORIES]. How often has your family come up
against:
Never

Rarely

Sometimes

Often

Agricultural crop loss to wildlife

0

1

2

3

Livestock predation by wildlife

0

1

2

3

Damage to your property by wildlife
(e.g., equipment, fences, house )

0

1

2

3

Injury due to wildlife

0

1

2

3

How often has your family come up against:

How often has your family come up against: Never

Rarely

Sometimes

Often

Feeling threatened by wildlife

0

1

2

3

Conflicts with other people in the community
over wildlife issues

0

1

2

3

Livestock getting a disease from wildlife

0

1

2

3

14. Overall, please rate how often you worry about threats from wildlife to your
livelihood.
0
Never

1
Rarely

2
Sometimes

!

"!

	
  
	
  

3
Often

120	
  

15. Can you give me an example of something that you or your family does to
reduce the threats to your livelihoods from conflicts with wildlife (i.e. can you give
me an example of ways you protect yourselves against wildlife)?
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
Section 3: Perceptions of risk to wildlife from HWC
I am now going to ask you questions about threats that people cause to wildlife. By
threats to wildlife I mean that things that people do have a negative effect on the overall
numbers of wildlife, the diversity of wildlife (i.e., different types of wildlife) or harm the
environment wildlife needs for survival.
16. People have different levels of concern about the negative effects on wildlife
due to conflicts that wildlife has with people. Using this scale [SCALE CHANGE
SHOW IMAGE], how much threat to local wildlife in this area is:
No threat
at all

Low
threat

Medium
threat

High
threat

People killing wildlife for food

0

1

2

3

People killing wildlife because of conflicts with
people (i.e., agriculture, injury, water)

0

1

2

3

People killing wildlife because of cultural beliefs
(i.e., taboos, trophies, rites of passage)
0

1

2

3

People killing wildlife for money
(i.e., tourism, meat)

1

2

3

In your area, how threatening to wildlife is:

0

!

"!

	
  
	
  

121	
  

No threat
at all

Low
threat

Medium
threat

High
threat

In your area, how threatening to wildlife is:
People using the resources wildlife need
for survival (i.e., water, pasture)

0

1

2

3

Wildlife getting a disease from domestic
animals

0

1

2

3

In your area, how threatening to wildlife is:
People changing wildlife areas to support
their livelihoods (i.e., agriculture, fuel wood)

0

1

2

3

People changing wildlife areas to exclude
wildlife (i.e., putting up fences, clearing brush)

0

1

2

3

Poaching

0

1

2

3

17. OMITTED QUESTION
18. People have different levels of concern about losses that wildlife may face as a
result of conflict with people. How concerned are you about that the following
types of losses are happening to wildlife in your area:
No
concern

Low
concern

Medium
concern

High
concern

Reduce overall wildlife numbers

0

1

2

3

Reduce the number of different wildlife
species in the area (i.e., losing diversity)

0

1

2

3

Loss of a certain wildlife species
(i.e., losing one kind of animal in the area)

0

1

2

3

!

"!

	
  
	
  

122	
  

How concerned are you about wildlife losses from conflict with people that may:
Reduce wildlife health

0

1

2

3

Reduce resources to support future
wildlife populations

0

1

2

3

19. Now I am going to ask you about how often you think wildlife comes up
against certain types of threats from HWC. [SHOW SCALE AND GO THROUGH
CATEGORIES]. How often does the following happen in your area:
Never

People killing wildlife due to damage
to agricultural products (i.e., crops, livestock)

Rarely

Sometimes Often

0

1

2

3

People killing wildlife due to damage to property
(i.e., housing, fences, water tanks)
0

1

2

3

People killing wildlife that threaten to
injure people

1

2

3

0

How often do you think the following threatens wildlife in your area:
Wildlife getting a disease from domestic
animals

0

1

2

3

People using resources wildlife needs
for survival (e.g., water, pasture)

0

1

2

3

How often do you think the following threatens wildlife in your area:
People changing wildlife areas to support
their livelihoods (e.g., clearing land for
agriculture, removing fire wood)

0

1

2

3

People changing wildlife areas to exclude
wildlife (e.g., putting up fences, clearing bush)

0

1

2

3

Poaching

0

1

2

3

!

"#!

	
  
	
  

123	
  

20. Overall, how often you do you worry about threats to wildlife from people in
your area?
0
Never

1
Rarely

2
Sometimes

3
Often

21. Can you give me an example of something that your community or
conservancy does to reduce the threats to wildlife from conflicts with people (i.e.,
Can you give me an example of something your community is doing to protect
wildlife)?
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
Section 4: Compliance and Legitimacy
Now I am going to talk to you about your feelings about wildlife rules. The rules I am
interested in tell you how you should and can interact with wildlife populations and
include both laws and community rules. I will ask you about how good you think wildlife
rules are at reducing threats to people and to wildlife. I will also ask you about your
opinion on how these rules and laws are created but I will not ask you about whether you
break wildlife rules.
22. Are you aware there are rules in relation to wildlife?
YES or NO
IF YES: Can you give me an example of a wildlife law (i.e., enforced by
government or local decision-makers that you are aware of)?
______________________________________________________________________
______________________________________________________________________
Can you give me an example of a local rule (i.e., enforced by community or
culture)?
______________________________________________________________________
______________________________________________________________________
!

""!

	
  
	
  

124	
  

23. I am now going to ask you to use this scale to measure importance [SHOW
SCALE]. People may choose to follow wildlife rules for different reasons. How
important do you think the following reasons are in relation to why people in your
community may follow rules regarding wildlife?
Not
important

Low
importance

Medium
importance

High
importance

Because the rule is doing the right thing

0

1

2

3

Because following rules is the right
thing to do

0

1

2

3

Respect for authority

0

1

2

3

When people decide to follow wildlife rules how important is:
Fear of getting caught

0

1

2

3

How severe the punishment is (i.e., the
punishment is serious)

0

1

2

3

Shame if caught

0

1

2

3

24. Do you think that decision makers are doing the right thing by creating rules
in relation to wildlife?
YES or

NO

25. How good do you think decision makers are at enforcing the rules about
wildlife?
0
Not at all
good

1
Low
good

2
Medium
good

!

"#!

	
  
	
  

3
High
good

125	
  

26. How good do you think decision makers are at enforcing the rules about
wildlife in a fair way?
0
Not at all
good

1
Low
good

2
Medium
good

3
High
good

27. How good do you think the rules are now at lowering the threats from
conflicts with wildlife to :
Not at all
good

Low
good

Medium
good

High
good

All people in your community

0

1

2

3

People like yourself

0

1

2

3

How good are these wildlife rules at lowering the threats to:
All wildlife species in the area

0

1

2

3

Wildlife species at high risk (i.e., wildlife
of conservation concern, endangered animals)

0

1

2

3

28. Some people may feel they are not able to participate in decision-making about
wildlife rules as much as they want to. In your opinion, how important are the
following factors in deciding whether people in your community are able to
participate in decision making related to wildlife rules:
Not at all
important

Low
important

Medium
important

High
important

Their desire to participate

0

1

2

3

Being male (i.e., being a man, gender)

0

1

2

3

Being a community elder

0

1

2

3

!

"#!

	
  
	
  

126	
  

In deciding whether people are able to participate in decision making related to
wildlife how important is:
Having a formal education

0

1

2

3

Whether their family lived in area
for a long time

0

1

2

3

What tribe they belong to

0

1

2

3

29. How good are local decision makers at taking the views of people like you into
account when making wildlife rules (i.e., how good are the decision makers now at
listening to opinions of people like yourself)?
0
Not at all
good

1
Low
good

2
Medium
good

3
High
good

30. How good are decision makers not at considering threats to your livelihood
when making wildlife rules?
0
Not at all
good

1
Low
good

2
Medium
good

3
High
good

31. How good are decision makers now at considering threats to wildlife
populations when making wildlife rules?
0
Not at all
good

1
Low
good

2
Medium
good

!

"#!

	
  
	
  

3
High
good

127	
  

Section 4: Vulnerability
I am now going to ask some questions that are personal in nature. This is a very
important part of the interview. Remember, I will not ask for your name or any questions
that would indicate who you are.
32. Respondent’s gender [OBSERVED]:
33. Ethnic affiliation:
[ ]
[ ]
Kavango Kwanyama
[ ]
[ ]
Totela
Twana

[ ]
Lozi
[ ]
Yeyi

Male

or

Female

[ ]
[ ]
[ ]
[ ]
Mafwe
Mbukushu Ndonga
Subiya
[ ]
Other: __________________________________

34. What would you say is the primary way that you make a living: (check no more
than two)
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
Agriculture Livestock Fishing
Hunting
Trading/
Rural industry (beer
vending
brewing, handicraft)
Wage or salary work [ ]; If wage or salary check one below:
[ ]
[ ]
[ ]
[ ]
[ ]
[ ]
Agricultural/
Tourism
Childcare/ Business Government
Service/
livestock
industry
homecare
NGO
[ ] Other (specify): _________________________________
35. How old are you? ______ (IF UNSURE): What year were you born?
______________(IF UNSURE CONSULT THE CAPRIVI HISTORICAL CHRONOLOGY
FOR GROSS GENERATIONAL ESTIMATES):
I was born before: ____________________________________
36. What is your highest level of formal education that you completed? _________
(check one)
Did not complete lower primary
[ ]
Completed lower primary
[ ]
Some upper primary
[ ]
Completed upper primary
[ ]
Some junior secondary
[ ]
Completed junior secondary [ ]
Some senior secondary
[ ]
Completed senior secondary [ ]
Some college
[ ]
Completed college
[ ]
Adult vocational training
(adult education courses)
[ ]
!

"#!

	
  
	
  

128	
  

37. How long has your family been living in this community? (UTILIZE THE
CAPRIVI HISTORICAL CHRONOLOGY FOR GROSS GENERATIONAL ESTIMATES)
Have lived here since: _________________________
38. Are you a member of any decision-making body such as a committee, council
or elected position (e.g., Village development committees (VDC), Farmer’s
committees, health committees, parent-teacher associations, women’s group,
water committee, conservation committee)?
YES or NO (IF NO ! SKIP TO NEXT QUESTION; IF YES ANSWER
FOLLOWING TWO QUESTIONS)
IF YES: What decision making group do you belong to:
_____________________________________________________________________
What is your position in that group? ________________________________
39. What is your current marital status?
[ ] Never Married

[ ] Married

[

] Divorced

[

] Widowed

IF MARRIED: How many spouses do you have? _______
40. How many people are currently living in your household? _______
41. Of the people living in your household how many are under 18 years of age?
________
42. Do you own any land?

YES or

NO

IF NO LAND OWNERSHIP OR NO AGRICULTURAL/ GRAZING LAND !SKIP
TO QUESTION 44
IF YES: Is the land that belongs to you: (check all that apply)
[ ]
Residential

[ ]
[ ]
Arable/
Grazing
agriculture

[ ]
Business sites

!

"#!

	
  
	
  

[ ]
Other (hunting, collecting)

129	
  

43. How large is your agricultural and/or grazing land? ________________
[ ] Small
Less than 5 hectares

[

] Medium
5-10 hectares

[ ] Large
Greater than 10 hectares

44. Is any of your agricultural/ grazing land fenced, including bush fence?
YES or NO
IF YES, is the fence: [ ] Bush (Acacia, thorn) [
[ ] Other:________
45. Do you rent or lease land for agriculture?

] Barbed Wire [
YES or

] Electric

NO

46. Does your household currently grow agricultural crops?
IF NO ! SKIP TO QUESTION 48

YES or

NO

47. Are your agricultural crops regularly guarded?
IF NO ! SKIP TO QUESTION 48

YES or

NO

IF YES: Of the following, who in the household is responsible for guarding the
crops (check all that apply):
[ ]
Everyone/
anyone
[ ]
Paid labor

[ ]
Household
men
[ ]
Guard animal

[ ]
[ ]
[ ]
Household
ChildrenChildrenwomen
boys
girls
[ ]
Other: _______________________

48. Do you have livestock?
IF NO!SKIP TO QUESTION 50

YES or

NO

IF YES: Can you tell me what kind of livestock you have and approximately how
many head of each?
[
[
[
[

]
]
]
]

Cattle: Estimation of #: ________
[ ] Goats: Estimation of #: ________
Donkeys: Estimation of #:______
[ ] Horses: Estimation of #:________
Pigs: Estimation of #: _________
[ ] Fowl (chickens, ducks): #: ______
Other: ____________: Estimation of #: __________________

!

"#!

	
  
	
  

130	
  

49. Does anyone or anything, such as a guard animal, in your household guard
your livestock?
YES or NO
IF NO !SKIP TO QUESTION 50
IF YES: Who in the household is responsible for guarding the livestock and what
livestock do they guard (CHECK ALL THAT APPLY AND INDICATE LIVESTOCK
GUARDED-LG):
[ ]
[ ]
[ ]
Household men
Household women
Children-boys
LG: _____________________ LG: _____________________LG: _______________
[ ]
[ ]
[ ]
Children-girls
Paid labor
Guard animal (specify):
LG: _____________________LG: ______________________LG: _______________
[ ]
Other: ___________________LG: __________________________
50. Do you have any other comments you would like to share with me related to
HWC?
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
______________________________________________________________________
Thank you for your time. That concludes the interview related to human wildlife
conflict. Please feel free to contact me later if you think of anything else you would
like to add. If you would like to contact the researcher I can provide you with
contact information including a Namibian cell phone number. If you are interested
in learning about the results of this research the researcher will be happy to share
them with you when she is finished in August 2010. (Time End: _____________)

!

"#!

	
  
	
  

131	
  

	
  
APPENDIX	
  C	
  
	
  
Visual	
  aids	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

132	
  

Figure	
  C1:	
  Developed	
  visual	
  Likert-­‐type	
  scales	
  (a.	
  intensity	
  or	
  amount;	
  b.	
  frequency)	
  for	
  use	
  
with	
  semi-­‐structured	
  interviews	
  and	
  focus	
  groups	
  in	
  Mudumu	
  South	
  Complex:	
  Caprivi	
  
Namibia	
  (July-­‐September,	
  2009)	
  
	
  
	
  a.	
  
!
!

0

!
!

1

2

3

!
!
!
!
!
!
!
!
!
!

NO
!
!

LOW

MEDIUM

HIGH

!
!

	
  b.	
  

!

!

!

!

!

!

	
  

	
  

!

!

0

NEVER

!

1

2

3

RARELY

SOMETIMES

OFTEN

!

!
!
!
!
!
!
!
!
!
!

NEVER
HAPPENS
!
!

LESS
THAN 1- 5
TIMES A
YEAR
SEASONALLY!

6-12
TIMES A
YEAR

MONTHLY

!
!
!

	
  

!

	
  

133	
  

MORE THAN 12
TIMES A YEAR

WEEKLY

	
  

APPENDIX	
  D	
  
	
  
Coding	
  Protocol	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

134	
  

Focus Group Data - Coding Protocol
Human dimensions of HWC Research
East Caprivi, Namibia (July-September, 2009)
Author: Jessica Kahler
Revised: February 21, 2010
A. IDENTIFYING HEADERS & DESCRIPTIONS
Participants recorded their opinions about risks onto index cards
(hereafter cards). For the purpose of coding text on the cards it is
necessary to break each card into its component parts. Every card had at
least one risk, depicted as a single word, phrase or sentence (header);
some cards had additional information (descriptions) related to the risk.
Sample Index Card:
HEADER
Floods
destroy crops and limits
living space

DESCRIPTION
!

Header !

The lone text on the index card or the subject of the text
to follow; often written at the top of the card or above
accompanying text below and may be distinguished by
being underlined, written in capital letters or other.

Description!

Text written in addition to the header; text elaborates on
the header, may list additional risks that are perceived to
be causally related to the header risk or give examples or
additional explanation.

	
  
	
  

	
  

135	
  

B. RULES REGULATING THE TREATMENT OF HEADER AND
DESCRIPTIONS:
A) Priority is given to the participantsʼ header on the index card when
assigning a primary category; if the card contains additional risk
categories in the description the header risk will remain as the
primary category.
Example: (Header) Flooding
Primary category !

(Description) destroys crops and limits
living space
Flooding

B) If description text is present and it contains additional keywords
and concepts related to risk categories (Table 1), it should be coded
for a secondary categorical variable. Secondary categories must be
distinct from the primary category assignment.
Example: (Header) Bridges

Primary category !

(Description) During construction of
bridges large machines can scare
[wildlife][sic].
Development

Secondary category ! Increased human-wildlife interaction

C) If the description contains multiple examples of additional risk
categories related to the header risk category (primary category), the
first example given will become the second category.
Example: (Header) Cash benefits

Primary category !

(Description) Cash benefits [are]
not enough to feed the family OR
take [children] to school [sic].

Insufficient benefits from conservancy

Secondary category ! Subsistence insecurity

!

"!

	
  
	
  

	
  

136	
  

D) If a participant has listed the same risk category as a header on
more than one of their cards (replicating risk headers), the
description (if available) on the second, replicated card will be used
to reassign a primary category and the header on the replicated card
will become the secondary category.
Example: (1st Header) Flooding (1st Description) decreases food
security
(2nd Header) Flooding (2nd Description) brings wildlife closer to
people
(1st Primary category) !Flooding (1ST Secondary category)! Food
insecurity
(2nd Primary category)!Increased (2nd Secondary category)! Flooding
wildlife
proximity
C. RISK CATEGORY CODING RULES
Individual cards with text generated during the risk ranking and
scoring activity must be coded into categories for analysis. Below are
yes or no question for coding “text” on cards into categories
generated during the initial, iterative review of text (see Table 1 for
list of categories). “Text” refers to headers in the first round of
coding in which the primary category is assigned. If there are
descriptions available on cards (text in addition to the header), then
the card is subjected to a second round of coding in which the
secondary category is assigned from the description. Therefore,
“text” in the second round of coding refers to descriptions on cards.
1) Does the text mention a wildlife species, a problem animal damage
incident, activities to control wildlife or human-induced wildlife death?
IF YES ! NEXT QUESTION
IF NO !

SKIP TO QUESTION #8

!

"!

	
  

	
  

137	
  

2) Does the text mention more than one type of human-wildlife conflict
(HWC) (e.g., crop damage and livestock depredation) or HWC in general?
IF YES ! Card will be coded as a generalized designation of
HWC
IF NO !

NEXT QUESTION

3) Does the header-text mention a specific wildlife species or wildlife in
general?
IF YES ! Card will be coded using the description (secondary
category). If the description contains more than one type
of conflict, refer to rule #2. If the description contains one
risk category in the text, that category becomes the
primary category (refer to next question).
IF NO !

NEXT QUESTION

4) Does the text mention a specific type of wildlife damage incident (e.g.,
crop damage, livestock depredation, people injured or killed by wildlife)?
IF YES ! Card will be coded as the specific category of wildlife
damage type as generated by the initial review of all text
(crop damage, human attack, livestock loss).
IF NO !

NEXT QUESTION

5) Does the text mention illegal harvest of wildlife or use of illegal harvest
methods (e.g., snares, poison)?
IF YES ! If the text mentions the illegal act in terms the context of a
problem animal incident, card is coded as “retaliation.” If
text does not mention the illegal act in the context of a
problem animal incident, card will be coded as
“poaching.”
IF NO !

NEXT QUESTION

!

"!

	
  

	
  

138	
  

6) Does the text mention hunting or wildlife harvest sanctioned by the
conservancy?
IF YES ! Card will be coded as “hunting.”
IF NO !

NEXT QUESTION

7) Does the text mention preventative activities meant to avoid conflict with
wildlife or scare wildlife away from property?
IF YES ! Card will be coded as “wildlife deterrence activities.”
IF NO !

STOP. Coding should be complete for all cards for which
the answer to question #1 was ʻyes.ʼ For coding of
secondary categories (descriptions), return to question #1
and follow all rules accordingly.

8) Does the text mention services or management activities that are related
to conservancy function or fall under conservancy management duties or
authority (e.g., translocation of wildlife, compensation)?
IF YES ! Card will be coded as “conservancy services and
management”
IF NO !

NEXT QUESTION

9) Does the text mention human activities within the conservancy related
farming, animal husbandry, or anthropogenic use of fire?
IF YES ! Card will be coded as “agricultural activities”
IF NO !

NEXT QUESTION

10) Does the text mention anything that results in changes in the interaction
between, the proximity of or the competition between people and wildlife for
space or resources?
IF YES ! Card will be coded as “increased human-wildlife
interactions”
IF NO !

NEXT QUESTION

!

"!

	
  

	
  

139	
  

11) Does the text mention the development of infrastructure (e.g., housing,
roads) within the conservancy or the negative consequences of
development activities?
IF YES ! Card will be coded as “development”
IF NO !

NEXT QUESTION

12) Does the text mention human or wildlife activities (e.g., deforestation)
that modify or change the environment not related to development of
infrastructure (question #11)?
IF YES ! Card will be coded as “habitat modification”
IF NO !

NEXT QUESTION

13) Does the text mention a lack of subsistence-based resources (e.g.,
land, food, skills, livestock) or conditions that reduce subsistence-based
resources?
IF YES ! Card will be coded “subsistence insecurity”
IF NO !

NEXT QUESTION

14) Does the text mention lack of economic development, financial
resources, employment opportunities or chronic deficiencies in monetary
resources?
IF YES ! Card will be coded “Financial insecurity”
IF NO !

NEXT QUESTION

15) Does the text mention a lack of education opportunities, educationalrelated infrastructure or adult training in job-related skills?
IF YES ! Card will coded “education and training”
IF NO !

NEXT QUESTION

16) Does the text mention a lack of non-education related services (e.g.,
health care), inadequate infrastructure or unsatisfactory living conditions?
IF YES ! Card will be coded “rural services and infrastructure”
IF NO !

NEXT QUESTION

!

"!

	
  

	
  

140	
  

17) Does the text mention poor human health related to disease, chronic
conditions or reduced physiological health conditions?
IF YES ! Card will be coded “poor human health”
IF NO !

NEXT QUESTION

18) Does the text mention conditions related to social welfare (e.g.,
alcoholism), social or cultural conflicts or concerns about cultural or
theological deterioration?
IF YES ! Card will be coded “socio-cultural insecurity”
IF NO !

NEXT QUESTION

19) Does the mention text mention climatic conditions, natural climaterelated disasters or changes in weather patterns?
IF YES ! Card will be coded “climate”
IF NO !

NEXT QUESTION

20) Does the text mention non-anthropogenic competition between or
among wildlife species for resources (e.g., predation) or biotic (nonclimatic) related environmental risks (e.g., wildlife disease outbreak)?
IF YES ! Card will be coded “ecological risks”
IF NO !

STOP: ALL CARDS SHOULD BE CODED FOR A
PRIMARY CATEGORY.

IF CARDS REMAINS UNCODED, REVISIT CODING RULES FOR
VERIFICATION. RULES MUST BE REVISED IF ANY TEXT REMAINS
UNCODED FOR A PRIMARY CATEGORY AFTER FINAL
VERIFICATION. FAILURE TO CODE FOR SECONDARY CATEGORIES
IN THE DESCRIPTION DOES NOT WARRANT REVISION OF CODING
RULES (ENTER “OTHER” AS SECONDARY CATEGORY).

!

"!

	
  
	
  

	
  

141	
  

Table 1: Risk categories generated by reviewing
participant generated text during risk ranking and
scoring activities; Caprivi HWC research (JulySeptember, 2009)
Risk Category

Coding

Agricultural activities

01

Climate

02

Conservancy service and management

03

Crop damage

04

Development

05

Ecological risks

06

Education and training

07

Financial insecurity

08

Habitat modification

09

Human attack

10

Human-wildlife conflict

11

Hunting

12

Increased human-wildlife interaction

13

Livestock loss

14

Poaching

15

Poor human health

16

Retaliation

17

Rural services and infrastructure

18

Socio-cultural insecurity

19

Subsistence insecurity

20

Wildlife deterrence activities

21

Other- description (does not fit categories)

22

!

"!

	
  
	
  
	
  
	
  

142	
  

	
  
APPENDIX	
  E	
  
	
  
Interview	
  respondent	
  demographic	
  information	
  by	
  conservancy	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

143	
  

Table	
  E1:	
  Demographic	
  information	
  from	
  interviews	
  in	
  
two	
  conservancies	
  (emerging	
  =	
  41;	
  established	
  =	
  35)	
  in	
  
Mudumu	
  South	
  Complex:	
  Caprivi,	
  Namibia	
  (July-­
September,	
  2009)	
  
Characteristic	
  
Emerging	
   	
   Established	
  
Educational	
  attainment	
  
No	
  schooling	
  
Some	
  primary	
  
Completed	
  primary	
  
Some	
  secondary	
  
Completed	
  secondary	
  
Some	
  college	
  education	
  
Adult	
  vocational	
  training	
  
Ethnic	
  group	
  
Kwanyama	
  
Mafwe	
  
Mayeyi	
  
Totela	
  
Gender	
  
Female	
  
Male	
  
Language	
  (used	
  in	
  
interview)	
  

Percent	
  of	
  participants	
  (%)	
  
12	
  
	
  
23	
  
5	
  
	
  
6	
  
20	
  
	
  
6	
  
44	
  
	
  
40	
  
12	
  
	
  
25	
  
5	
  
	
  
0	
  
2	
  
	
  
0	
  
	
  
	
  
	
  
0	
   	
  
3	
  
0	
   	
  
3	
  
100	
   	
  
86	
  
0	
   	
  
8	
  
	
  
	
  
	
  
49	
   	
  
49	
  
51	
   	
  
51	
  
	
  

English	
  a	
  
Lozi	
  
Shiyeyi	
  
Subiya	
  
Totela	
  
Missing	
  (unknown)	
  

	
  

	
  

24	
   	
  

34	
  

12	
  
59	
  
0	
  
0	
  
5	
  

	
  
	
  
	
  
	
  
	
  

6	
  
51	
  
3	
  
3	
  
3	
  

Local	
  environmental	
  decision-­maker	
  b	
  
No	
  	
  	
  
71	
   	
  
Yes	
  
29	
   	
  	
  

86	
  
14	
  

a	
  Includes	
  English	
  and	
  English	
  with	
  Sheyeyi	
  or	
  Lozi.	
  
b	
  Members	
  of	
  conservancy	
  staff	
  or	
  traditional	
  authority.	
  

	
  
	
  

	
  

144	
  

	
  
Table	
  E1	
  (continued):	
  Demographic	
  information	
  from	
  
interviews	
  in	
  two	
  conservancies	
  (emerging	
  =	
  41;	
  
established	
  =	
  35)	
  in	
  Mudumu	
  South	
  Complex:	
  Caprivi,	
  
Namibia	
  (July-­September,	
  2009)	
  
Characteristic	
  

Emerging	
  

Marital	
  status	
  

	
  

Established	
  

Percent	
  of	
  participants	
  (%)	
  

Never	
  married	
  

20	
   	
  

20	
  

Married	
  

68	
   	
  

60	
  

Divorced	
  

2	
   	
  

3	
  

Widowed	
  

10	
   	
  

17	
  

Primary	
  livelihood	
  strategy	
   	
  
Agriculture	
  

	
  

	
  

98	
   	
  

89	
  

Livestock	
  

2	
   	
  

0	
  

Rural	
  industry	
  

0	
   	
  

6	
  

Wage	
  (Service/NGO)	
  

0	
   	
  

3	
  

Other	
  

0	
   	
  

2	
  

Age	
  (years)	
  

People	
  (#)	
  

Mean	
  

43	
   	
  

43	
  

Minimum	
  

18	
   	
  

18	
  

Maximum	
  

84	
   	
  

88	
  

Household	
  size	
  

	
  	
  

	
  

	
  	
  

Mean	
  

6	
   	
  

6	
  

Minimum	
  

1	
   	
  

1	
  

Maximum	
  

10	
   	
  

15	
  

Wealth	
  index	
  c	
  

Household	
  ($NAD/capita)	
  

Mean	
  

5024	
   	
  

3513	
  

Minimum	
  

50	
   	
  

0	
  

Maximum	
  

85160	
   	
  	
  

43900	
  

c	
  The	
  wealth	
  index	
  was	
  calculated	
  using	
  a	
  household's	
  

livestock	
  assets,	
  size	
  of	
  agricultural	
  land	
  holdings	
  divided	
  by	
  
the	
  total	
  number	
  of	
  people	
  in	
  the	
  household.	
  
	
  

	
  

145	
  

	
  
APPENDIX	
  F	
  
	
  
Data	
  on	
  species-­‐specific	
  vulnerability	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

146	
  

Table	
  F1:	
  Perceived	
  and	
  reported	
  species	
  implicated	
  in	
  crop	
  damage,	
  livestock	
  loss	
  and	
  human	
  attack	
  in	
  
two	
  conservancies	
  in	
  Mudumu	
  South	
  Complex	
  (n=50):	
  Caprivi,	
  Namibia	
  (July-­September,	
  2009)	
  
Perceived	
  (Focus	
  Group,	
  2009)	
  

	
  	
  
Crop	
  damage	
  a	
  
Elephant	
  
Hippopotamus	
  
Baboons	
  
Porcupine	
  
Buffalo	
  
Monkeys	
  
Bush	
  pig	
  
Kudu	
  
Jackal	
  
Fox	
  
Duiker	
  
Impala	
  

Rank	
   Incidence	
  index	
  
	
  	
  

0.52	
  
1	
  
2	
  
3	
  
3	
  
4	
  
5	
  
6	
  
7	
  
8	
  
9	
  
9	
  
10	
  

Reported	
  (Event	
  Book,	
  2001-­2008)	
  

Importance	
  
index	
  
0.61	
  

1.00	
  
1.00	
  
1.00	
  
1.00	
  
0.83	
  
0.83	
  
0.67	
  
0.50	
  
0.50	
  
0.33	
  
0.33	
  
0.17	
  

	
  

	
  	
  

	
   Crop	
  damage	
  
	
  
Elephant	
  
	
  
Hippopotamus	
  
	
  
Buffalo	
  
	
  
Porcupine	
  
	
  
Bush	
  pig	
  
	
  
Monkey	
  
	
  
Baboon	
  
	
  
Duiker	
  
	
  
Spring	
  hare	
  
	
  
Kudu	
  
	
  
Jackal	
  
	
  	
   Reed	
  Buck	
  

1.00	
  
0.79	
  
0.49	
  
0.49	
  
0.73	
  
0.23	
  
0.37	
  
0.47	
  
0.07	
  
0.11	
  
0.06	
  
0.11	
  

Total	
  #	
  
incidents	
  
678	
  

Percent	
  
56.8	
  

290	
  
176	
  
79	
  
41	
  
32	
  
18	
  
18	
  
9	
  
6	
  
4	
  
4	
  
1	
  

42.8	
  
26.0	
  
11.7	
  
6.0	
  
4.7	
  
2.7	
  
2.7	
  
1.3	
  
0.9	
  
0.6	
  
0.6	
  
0.1	
  

a	
  Incidence	
  and	
  importance	
  index	
  scores	
  for	
  crop	
  damage,	
  livestock	
  loss	
  and	
  injury	
  or	
  death	
  based	
  on	
  participants	
  

overall	
  ranking	
  and	
  scoring	
  for	
  all	
  threats	
  to	
  livelihoods.	
  

	
  
	
  
	
  
	
  
	
  

	
  

147	
  

Table	
  F1	
  (continued):	
  Perceived	
  and	
  reported	
  species	
  implicated	
  in	
  crop	
  damage,	
  livestock	
  loss	
  and	
  
human	
  attack	
  in	
  two	
  conservancies	
  in	
  Mudumu	
  South	
  Complex	
  (n=50):	
  Caprivi,	
  Namibia	
  (July-­September,	
  
2009)	
  
Perceived	
  (Focus	
  Group,	
  2009)	
  

	
  	
  
	
  	
  
Livestock	
  loss	
  
Hyena	
  
Lion	
  
African	
  wild	
  dog	
  
Crocodile	
  
Snakes	
  
Leopard	
  
Jackal	
  
Birds	
  of	
  prey	
  
Cheetah	
  
Genet	
  
African	
  wild	
  cat	
  
Caracal	
  
Fox	
  

Rank	
  
	
  	
  
	
  	
  
1	
  
2	
  
3	
  
4	
  
4	
  
5	
  
6	
  
7	
  
8	
  
9	
  
9	
  
9	
  
9	
  

Reported	
  (Event	
  Book,	
  2001-­2008)	
  

Incidence	
  
index	
  

Importance	
  
index	
  

	
  	
  

	
  	
  

0.34	
  

	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

0.46	
  
1.00	
  
1.00	
  
1.00	
  
0.67	
  
0.67	
  
0.50	
  
0.33	
  
0.17	
  
0.17	
  
0.17	
  
0.17	
  
0.17	
  
0.17	
  

	
  

0.91	
  
0.87	
  
0.34	
  
0.41	
  
0.40	
  
0.19	
  
0.27	
  
0.71	
  
0.60	
  
0.13	
  
0.00	
  
0.00	
  
0.00	
  

	
  	
  
	
  	
  
Livestock	
  loss	
  
Hyena	
  
Lion	
  
Elephant	
  
Crocodile	
  
Leopard	
  
Cheetah	
  
Hippopotamus	
  
Jackal	
  
Snake	
  
	
  
	
  
	
  
	
  

Total	
  #	
  
incidents	
  

Percent	
  
	
  	
  

	
  	
  

352	
  
137	
  
5	
  
3	
  
3	
  
1	
  
1	
  
1	
  
1	
  
	
  
	
  
	
  
	
  	
  

42.2	
  
69.8	
  
27.2	
  
1.0	
  
0.6	
  
0.6	
  
0.2	
  
0.2	
  
0.2	
  
0.2	
  
	
  
	
  
	
  
	
  

504	
  

a	
  Incidence	
  and	
  importance	
  index	
  scores	
  for	
  crop	
  damage,	
  livestock	
  loss	
  and	
  injury	
  or	
  death	
  based	
  on	
  participants	
  

overall	
  ranking	
  and	
  scoring	
  for	
  all	
  threats	
  to	
  livelihoods.	
  

	
  
	
  
	
  
	
  
	
  

148	
  

Table	
  F1	
  (continued):	
  Perceived	
  and	
  reported	
  species	
  implicated	
  in	
  crop	
  damage,	
  livestock	
  loss	
  and	
  
human	
  attack	
  in	
  two	
  conservancies	
  in	
  Mudumu	
  South	
  Complex	
  (n=50):	
  Caprivi,	
  Namibia	
  (July-­September,	
  
2009)	
  
Perceived	
  (Focus	
  Group,	
  2009)	
  

	
  	
  
Human	
  attack	
  
Elephant	
  
Lion	
  
Hippopotamus	
  
Snakes	
  
Crocodile	
  
Buffalo	
  
Leopard	
  

Rank	
   Incidence	
  index	
  
	
  	
  
1	
  
2	
  
3	
  
3	
  
4	
  
5	
  
6	
  

0.20	
  
1.00	
  
1.00	
  
0.80	
  
1.00	
  
1.00	
  
0.80	
  
0.20	
  

Reported	
  (Event	
  Book,	
  2001-­2008)	
  

Importance	
  
index	
  

	
  

0.60	
   	
  
1.00	
  
	
  
0.33	
  
	
  
0.65	
  
	
  
0.30	
  
	
  
0.26	
  
	
  
0.48	
  
	
  
0.50	
  
	
  	
  

Total	
  #	
  
incidents	
  

	
  	
  
Human	
  attack	
  
Elephant	
  
Hippopotamus	
  
	
  
	
  
	
  
	
  
	
  	
  

Percent	
  

10	
  
8	
  
2	
  
	
  
	
  
	
  
	
  
	
  	
  

0.8	
  
80.0	
  
20.0	
  
	
  
	
  
	
  
	
  
	
  	
  

a	
  Incidence	
  and	
  importance	
  index	
  scores	
  for	
  crop	
  damage,	
  livestock	
  loss	
  and	
  injury	
  or	
  death	
  based	
  on	
  participants	
  

overall	
  ranking	
  and	
  scoring	
  for	
  all	
  threats	
  to	
  livelihoods.	
  

	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  

149	
  

	
  
Table	
  F2:	
  Wildlife	
  species	
  vulnerability	
  to	
  poaching	
  according	
  to	
  conservancy	
  incident	
  reports	
  
(Event	
  Book,	
  2001-­2008)	
  and	
  local	
  perceptions	
  from	
  a	
  risk	
  ranking	
  activity	
  (Focus	
  Group,	
  2009;	
  
n=50)	
  in	
  two	
  conservancies	
  in	
  Mudumu	
  South	
  Complex:	
  Caprivi,	
  Namibia.	
  
Perceived	
  (Focus	
  Group,	
  2009)	
  
Species	
  

	
  

Incidence	
   Importance	
   Overall	
  
	
  
index	
  
index	
  
rank	
  b	
  

Reported	
  (Event	
  Book,	
  2001-­2008)	
  
Incident	
  
type(s)	
  

Species	
  

Total	
  #	
  
Incidences	
  

Buffalo	
  

0.88	
  

0.84	
  

1	
  

	
   Hippopotamus	
  

Firearm	
  

4	
  

Kudu	
  

1.00	
  

0.45	
  

2	
  

Firearm	
  

3	
  

Elephant	
  

0.88	
  

0.60	
  

3	
  

	
   Duiker	
  a	
  
	
   Wildebeest	
  

Firearm	
  

3	
  

Hippopotamus	
  

0.88	
  

0.56	
  

4	
  

	
   Buffalo	
  

Firearm	
  

2	
  

Warthog	
  

0.75	
  

0.50	
  

5	
  

	
   Elephant	
  

Firearm	
  

2	
  

Guinea	
  fowl	
  a	
  
Zebra	
  

0.63	
  

0.63	
  

6	
  

Snares	
  

2	
  

0.50	
  

0.37	
  

7	
  

	
   Partridge	
  a	
  
	
   Warthog	
  

Traditional	
  

2	
  

Spring	
  hare	
  

0.25	
  

1.00	
  

8	
  

	
   Bird	
  a	
  	
  

Firearm	
  

1	
  

Duiker	
  a	
  

0.38	
  

0.44	
  

9	
  

	
   Quail	
  a	
  

Snares	
  

1	
  

Hyena	
  

0.38	
  

0.38	
  

10	
  

Snares	
  

1	
  

Lion	
  

0.25	
  

0.56	
  

11	
  

	
   Snake	
  a	
  
	
   Pangolin	
  

Traditional	
  

1	
  

Pangolin	
  

0.25	
  

0.50	
  

11	
  

	
   	
  

	
  

	
  

Porcupine	
  

0.25	
  

0.44	
  

12	
  

	
  	
   	
  	
  

	
  	
  

	
  	
  

a	
  Wildlife	
  taxa	
  not	
  reported	
  to	
  species-­‐specific	
  level	
  (i.e.,	
  genus,	
  family	
  or	
  order	
  level	
  classification).	
  

Genus	
  level	
  reporting	
  may	
  not	
  represent	
  the	
  lone	
  species	
  found	
  in	
  Caprivi.	
  

b	
  Overall	
  rank	
  is	
  based	
  on	
  the	
  joint	
  risk	
  score;	
  calculated	
  from	
  the	
  importance	
  and	
  incidence	
  index	
  

scores.	
  
	
  

150	
  

Figure	
  F1:	
  Top	
  fifteen	
  most	
  threatening	
  wildlife	
  species	
  to	
  local	
  livelihoods	
  as	
  perceived	
  by	
  residents	
  in	
  two	
  	
  	
  	
  	
  
conservancies	
  (n=	
  50)	
  in	
  Mudumu	
  South	
  Complex:	
  Caprivi,	
  Namibia	
  (Focus	
  Groups;	
  July-­September,	
  2009)	
  
1.00!

Elephant!

0.90!
Hyena!
0.80!

Buffalo!

0.70!

Hippopotamus!
Lion!

Increasing importance (P)!

0.60!
Kudu!
Porcupine!

0.50!
Bush pig!

Threat Diversity
Index!

Crocodile!

0.40!
Snakes!

Baboons!
Wild dog!

0.30!
Leopard!

5!

Monkeys!

0.20!

2!
Jackal!

0.10!
0.00!
0.00!

1!
0.10!

0.20!

0.30!

0.40!

0.50!

0.60!

0.70!

0.80!

Increasing incidence (I)!

	
  

	
  

151	
  

	
  

Figure	
  F2:	
  Top	
  fifteen	
  most	
  threatened	
  wildlife	
  species	
  from	
  conflicts	
  with	
  people	
  as	
  perceived	
  by	
  residents	
  in	
  two	
  
conservancies	
  (n=	
  48)	
  in	
  Mudumu	
  South	
  Complex:	
  Caprivi,	
  Namibia	
  (Focus	
  Groups;	
  July-­September,	
  2009)	
  

0.9!
Elephant!
0.8!

0.7!
Buffalo!

Guinea fowl!
0.6!
Baboons!

Increasing importance (P)!

Rabbits!

Hippopotamus!

0.5!
Kudu!

Lion!

Impala!
Porcupine!

0.4!

Warthog !
0.3!

Hyena!

Threat Diversity
Index!

Duiker!

9!

Zebra!
0.2!
Springbok!

4!

0.1!

1!

0!
0!

0.1!

0.2!

0.3!

0.4!

0.5!

Increasing incidence (I)!

	
  

	
  

152	
  

0.6!

0.7!

0.8!

	
  

APPENDIX	
  G	
  
	
  
Additional	
  co-­‐mapping	
  risk	
  maps	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

153	
  

b) Dzoti Conservancy

Mudumu National Park

Figure	
  G1:	
  Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  crop	
  damage	
  incidents	
  
and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  crop	
  damage	
  incidents	
  in	
  Wuparo	
  (a)	
  and	
  Dzoti	
  
(b)	
  conservancies:	
  Mudumu	
  South	
  Complex,	
  Caprivi,	
  Namibia.	
  	
  

!
"
b) Dzoti

!
"

!
"
!
"

#

! !

!
"

!
"

! #
"

a) Wuparo

!

!
"

!

"
#! !
!

!

#

#

!

!
"
#

#

#

!
"
!!
""

!

!

!
!

!
"

!

!

!!
"

!

!

!

!
"

!

!

!

!

!
"
!

!

!
!
!!
!! !

!

!

!

!

!
"

#

!
!
#

!

Mamili National Park

!
!

!
#
!
"
!

#

!

!

Villages

Roads

!

Roads and Trails

Water

!

Kwando River
!

!

!

!

!

!

Wildlife Occurs Often

!

!

!

!

#

!

!

!

!
"
!
"
!
"

!

!
!!

! !!

!

!

!
!

#

!

!

#

!

!

!

!

!
!
!
! !
!!

!

!
"

! !! !
!

#

!

!

!

!!
!
!
! !!! ! !

!

!

#

!

!
!
!
! !
!!

!

!

!
"
#

#

!

#

!
"

#
!!
! !! !
!

!
"

!

!

!
"

#

!!
!
"
! !! !
"

!
"

!
!
!

!

!
"

!

#

! !
!

!
"
!
"

!
"

"
" !
#!! #

!
!

Mudumu National Park

a) Wuparo Conservancy

#

!

Kwando River

!

Mamili National Park
Event Book Incidence Perceived Incidence

!

Wildlife Occurs Sometimes
Wildlife Occurs ! Villages
Rarely

Water
Conservancy Boundaries

#

1

#
2
Event Book Crop Damage

#

1 -3
5

Low
Perceived Crop Damage
Low
High

!
!

# 6 -415 6

!

#
!
!

16 - 35

7 - 10

High

36 - 59

60 - 126

0

1

2
0

4
1

2

6
4

6

8
Kilometers
8
Kilometers

	
  
	
  

154	
  

b) Dzoti Conservancy

Mudumu National Park

Figure	
  G2:	
  Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  human-­‐attack	
  incidents	
  
and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  human-­‐attack	
  incidents	
  in	
  Wuparo	
  (a)	
  and	
  Dzoti	
  
(b)	
  conservancies:	
  Mudumu	
  South	
  Complex,	
  Caprivi,	
  Namibia.	
  	
  

!
"
b) Dzoti

!
"

!
"
!
"

!
"

!
"

! #
"

! !

!
"

"
" !
#!! #

!
!

!

a) Wuparo

!
"

!
"
#!

!

#

#

!
"
#

#

!
"
! !!
"

!

!
"

!
"

!
!
!
! !
!!

!

#

!

!
"

!
"

!

!
!

!
"

#

!

#

!
"

#
!!
! !! !
!

!
"

!

!

!

!!
""

#

!!

#

! !

#
!

!
"
!
"

Mudumu National Park

a) Wuparo Conservancy

#

!
"

#

!
"
!
"

!

!
"

!

!

!

!

!
!
! !!

#

Mamili National Park

!
!
!
! !
#
!!
!

!

!!

!
"

!!
! !! !
!
#

#

!! !
!
!

!

#

!
"
!

!

#

!!
!

!
"

! !!

#

Kwando River

#

!
!

!!
!

#

!
!
Kwando River

!

!
"
!
"
!
"

Wildlife Occurs Often

!

Villages

Wildlife Occurs Sometimes
Wildlife Occurs Rarely
!

Roads and Trails
Water

Villages
Roads
Water

Conservancy Boundaries

Mamili National Park
Event Book Incidence Perceived Incidence
#

1

#

2

Event Book Human Attacks
# 3

# 14 - 6
! 2
# 3 7 - 10
!
!

Low
Perceived Attacks on Humans
High

High

0

1

2
0

4
1

2

6
4

6

8
Kilometers
8
Kilometers

	
  

	
  
	
  

!
!

Low

155	
  

b) Dzoti Conservancy

Mudumu National Park

Figure	
  G3:	
  Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  livestock	
  depredation	
  
incidents	
  and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  livestock	
  depredation	
  incidents	
  in	
  
Wuparo	
  (a)	
  and	
  Dzoti	
  (b)	
  conservancies:	
  Mudumu	
  South	
  Complex,	
  Caprivi,	
  Namibia.	
  

!
"
b) Dzoti

!
"

!
"
!
"

#

! !

!
"

!
"

! #
"
!

!

!

!
"

"
#!
!

!

#

#

!
"
#

#

#

!
"
!
"
!
"

!

!
"

!
"

#

!

!

!
"
!

#

!
!
!
! !
!!

!

#

!
"
!

#
!!
! !! !
!

!
"

!
"

!
!

!
"
!!
""

#

!
"
!
"

!
"

#

!!
!
"
! !! !
"

! !
!

!
"
!
"

!
"

"
" !
a) Wuparo ! #
#!

Mudumu National Park

a) Wuparo Conservancy

#

!
"
!
#

!
!
!! !
!

!

!

#

!!
!
! !! ! !
#

!

!
!

#

#

!!
!

! !!

!
"

!

#

!

Mamili National Park

#

!
!
!
! !
!!

!

!
"

! !! !
!

#

!

!
"

!
!

!

Kwando River

#

!
!

Wildlife Occurs Often
Wildlife Occurs Sometimes
Wildlife Occurs Rarely
!

Villages

Roads and Trails

Villages

Roads
Water

Water
Conservancy Boundaries

Kwando River

Mamili National Park
Event Book Incidence Perceived Incidence
#

1

#

2

Event Book Livestock Damage

#

3

Low
Perceived Livestock Loss

High

1-4

#

!
!

Low

# 5 -412 6
137 21
- - 10

High

22 - 35
36 - 95

0

1

2
0

4
1

2

6
4

6

8
Kilometers
8
Kilometers

	
  
	
  

156	
  

b) Dzoti Conservancy

Mudumu National Park

Figure	
  G4:	
  Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  crop	
  damage	
  incidents	
  
and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  poaching	
  incidents	
  in	
  Wuparo	
  (a)	
  and	
  Dzoti	
  (b)	
  
conservancies:	
  Mudumu	
  South	
  Complex,	
  Caprivi,	
  Namibia.	
  	
  

!
"
b) Dzoti

!
"

!
"
!
"

#

! !

!
"

!
"

! #
"
!

!

!

!
"

"
#!
!

!

#

#

!
"
#

#

#

!
"

!
"

#

!

!

!
"
!

#

!
!
!
! !
!!

!

#

!
"
!

#
!!
! !! !
!

!
"

!
"

!
!

!
"
!!
""

#

!
"
!
"

!
"
!
#

!
!
!! !
!

!

!

#

!!
!
! !! ! !
#

#

!
!
!
! !
!!

!
!

!
"

! !! !
!

#

!

!
"

!
!

!
!

#

#

!!
!

! !!

!
"

!

#

!

Mamili National Park

!
"

#

!!
!
"
! !! !
"

! !
!

!
"
!
"

!
"

"
" !
a) Wuparo ! #
#!

Mudumu National Park

a) Wuparo Conservancy

#

!

Kwando River

#

!
!

!
"
!
"
!
"

Wildlife Occurs Often

!

Villages

Wildlife Occurs Rarely
!

Roads and Trails
Water

Villages
Roads
Water

Conservancy Boundaries

#

1

#

2

#

Wildlife Occurs Sometimes

Kwando River

Mamili National Park
Event Book Incidence Perceived Incidence

3

Event Book Incidents

4# Snares6

#

Low
High

!
!

Perceived Crop Damage
Low

7 - 10
Firearms
Traditional

High

0

1

2
0

4
1

2

6
4

6

8
Kilometers
8
Kilometers

	
  
	
  

157	
  

b) Dzoti Conservancy

Mudumu National Park

Figure	
  G5:	
  Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  human-­‐attack	
  incidents	
  
and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  poaching	
  incidents	
  in	
  Wuparo	
  (a)	
  and	
  Dzoti	
  (b)	
  
conservancies:	
  Mudumu	
  South	
  Complex,	
  Caprivi,	
  Namibia.	
  

!
"
b) Dzoti

!
"

!
"
!
"

#

! !

!
"

!
"

! #
"

!

!
"

"
#!
!

!

#

#

!
"
#

#

#

!
"

!
"

#

!

!

!
"
!

#

!
!
!
! !
!!

!

#

!
"
!

#
!!
! !! !
!

!
"

!
"

!
!

!
"
!!
""

#

!
"
!
"

!
"
!
#

!
!
!! !
!

!

!

#

!!
!
! !! ! !
#

#

!
!
!
! !
!!

!
!

!
"

! !! !
!

#

!

!
"

!
!

!
!

#

#

!!
!

! !!

!
"

!

#

!

Mamili National Park

!
"

#

!!
!
"
! !! !
"

! !
!

!
"
!
"

!
"

!
"
a) Wuparo!! #
#"

!
!

Mudumu National Park

a) Wuparo Conservancy

#

!

Kwando River

#

!
!

!
"
!
"
!
"

Wildlife Occurs Often

!

Villages

Wildlife Occurs Rarely
!

Roads and Trails
Water

Villages
Roads
Water

Conservancy Boundaries

#

1

#

2

#

Wildlife Occurs Sometimes

Kwando River

Mamili National Park
Event Book Incidence Perceived Incidence

3

Event Book Incidents

4# Snares6

#

Low
High

!
!

Perceived Human Attacks
Low

7 - 10
Firearms
Traditional

High

0

1

2
0

4
1

2

6
4

6

8
Kilometers
8
Kilometers

	
  
	
  

158	
  

b) Dzoti Conservancy

Mudumu National Park

Figure	
  G6:	
  Perceived	
  geographic	
  incidents	
  (Focus	
  Group,	
  2009)	
  of	
  livestock	
  depredation	
  
incidents	
  and	
  location	
  of	
  Event	
  Book	
  (2003-­‐2008)	
  poaching	
  incidents	
  in	
  Wuparo	
  (a)	
  and	
  
Dzoti	
  (b)	
  conservancies:	
  Mudumu	
  South	
  Complex,	
  Caprivi,	
  Namibia.	
  

!
"
b) Dzoti

!
"

!
"
!
"

#

! !

!
"

!
"

! #
"

!

!
"

"
#!
!

!

#

#

!
"
#

#

#

!
"

!
"

#

!

!

!
"
!

#

!
!
!
! !
!!

!

#

!
"
!

#
!!
! !! !
!

!
"

!
"

!
!

!
"
!!
""

#

!
"
!
"

!
"
!
#

!
!
!! !
!

!

!

#

!!
!
! !! ! !
#

#

!
!
!
! !
!!

!
!

!
"

! !! !
!

#

!

!
"

!
!

!
!

#

#

!!
!

! !!

!
"

!

#

!

Mamili National Park

!
"

#

!!
!
"
! !! !
"

! !
!

!
"
!
"

!
"

"
" !
a) Wuparo ! #
#!

!
!

Mudumu National Park

a) Wuparo Conservancy

#

!

Kwando River

#

!
!

!
"
!
"
!
"

Wildlife Occurs Often

!

Villages

Wildlife Occurs Sometimes
Wildlife Occurs Rarely
!

Villages

Roads and Trails

Roads

Water

Water

Conservancy Boundaries

Kwando River

Mamili National Park
Event Book Incidence Perceived Incidence
#

1

#

2

# 3
Event Book Incidents
4# Snares6

#

Low
High
Perceived Livestock Loss

!
!

Low

Firearms

7 - 10

Traditional

High

0

1

2
0

4
1

2

6
4

6

8
Kilometers
8
Kilometers

	
  
	
  

159	
  

	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
REFERENCES	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

160	
  

	
  
REFERENCES	
  
	
  
	
  
	
  
	
  
Aust,	
  P.,	
  Boyle,	
  B.,	
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  &	
  Coulson,	
  T.	
  (2009).	
  The	
  impact	
  of	
  Nile	
  crocodiles	
  on	
  rural	
  
livelihoods	
  in	
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  Namibia.	
  South	
  African	
  Journal	
  of	
  Wildlife	
  Research,	
  39	
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  57-­‐
69.	
  
	
  
Baird,	
  T.D.,	
  Leslie,	
  P.W.	
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  J.T.	
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  The	
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Perceptions	
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Barnes,	
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  Child	
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Spenceley	
  (Eds.),	
  Evolution	
  &	
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to	
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  113-­‐126).	
  London:	
  Earthscan.	
  
	
  
Barnes,	
  J.I.,	
  MacGregor,	
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  Economic	
  Efficiency	
  and	
  Incentives	
  for	
  
Change	
  with	
  Namibia’s	
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  Wildlife	
  Use	
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667-­‐681.	
  
	
  
Bassett,	
  T.J.	
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  Card-­‐carrying	
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  rural	
  poverty,	
  and	
  wildlife	
  decline	
  in	
  northern	
  
Cote	
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  The	
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  24-­‐35.	
  
	
  
Beier,	
  C.M.,	
  Patterson,	
  T.M.	
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  Ecosystem	
  Services	
  and	
  Emergent	
  
Vulnerabilities	
  in	
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  Decision-­‐Support	
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923-­‐938.	
  
	
  
Bell,	
  S.,	
  Hampshire,	
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  The	
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  case	
  
study	
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  399-­‐418.	
  
	
  
Bernard,	
  H.R.	
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  Research	
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  Quantitative	
  
Approaches.	
  	
  Oxford:	
  AltaMira.	
  
	
  
Bowen-­‐Jones,	
  E.,	
  Brown,	
  D.,	
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  Robinson,	
  E.J.Z.	
  (2003).	
  Economic	
  commodity	
  or	
  
environmental	
  crisis?	
  An	
  interdisciplinary	
  approach	
  to	
  analyzing	
  the	
  bushmeat	
  trade	
  in	
  
central	
  and	
  west	
  Africa.	
  Area,	
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  390-­‐402.	
  
	
  
Bruchmann,	
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  Namibia’s	
  
Tropical	
  Region	
  where	
  four	
  Countries	
  meet.	
  	
  Bruchmann:	
  Northcliff,	
  South	
  Africa.	
  
	
  
Bruno,	
  J.F.	
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  Cardinale,	
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  (2008).	
  Cascading	
  effects	
  of	
  predator	
  richness.	
  Frontiers	
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Ecology	
  and	
  the	
  Environment,	
  6	
  (10),	
  539-­‐546.	
  
	
  

	
  

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  E.	
  &	
  Rondeau,	
  D.	
  (2007).	
  	
  Compensation	
  for	
  wildlife	
  damages:	
  Habitat	
  conversion,	
  
species	
  preservation	
  and	
  local	
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  Journal	
  of	
  Environmental	
  Economics	
  and	
  
Management,	
  54,	
  311-­‐322.	
  
	
  
Burgess,	
  N.,	
  Hales,	
  J.,	
  Underwood,	
  E.,	
  Dinerstein,	
  E.,	
  Olson,	
  D.,	
  Itoua,	
  I.,	
  et	
  al.	
  (Eds.).	
  (2004).	
  
Terrestrial	
  Ecoregions	
  of	
  Africa	
  and	
  Madagascar:	
  A	
  Conservation	
  Assessment.	
  Washington,	
  
DC:	
  Island	
  Press.	
  
	
  
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  G.M.	
  &	
  Fusari,	
  A.	
  (2000).	
  	
  Subsistence	
  hunting	
  and	
  bushmeat	
  exploitation	
  in	
  
central	
  western	
  Tanzania.	
  	
  Biodiversity	
  and	
  Conservation,	
  9,	
  1571-­‐1585.	
  
	
  
Chachamovich,	
  E.,	
  Fleck,	
  M.P.	
  &	
  Power,	
  M.	
  (2009).	
  Literacy	
  affected	
  ability	
  to	
  adequately	
  
discriminate	
  among	
  categories	
  in	
  multipoint	
  Likert	
  Scales.	
  Journal	
  of	
  Clinical	
  Epidemiology,	
  
62,	
  37-­‐46.	
  
	
  
Chazal,	
  J.,	
  Quétier,	
  F.,	
  Lavorel,	
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  &	
  Doorn,	
  A.	
  (2008).	
  Including	
  multiple	
  differing	
  
stakeholder	
  values	
  into	
  vulnerability	
  assessments	
  of	
  socio-­‐ecological	
  systems.	
  Global	
  
Environmental	
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  18,	
  508-­‐520.	
  
	
  
Childs,	
  C.	
  (2004,	
  July-­‐September).	
  	
  	
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  Surfaces	
  in	
  ArcGIS	
  Spatial	
  Analyst.	
  
ArcUser,	
  32-­‐35.	
  	
  Retrieved	
  February	
  1,	
  2010,	
  from	
  
http://www.esri.com/news/arcuser/0704/files/interpolating.pdf	
  
	
  
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  (2009).	
  Conservation	
  Information	
  [Database].	
  	
  Windhoek,	
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  Ministry	
  of	
  
Environment	
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  Tourism	
  (MET),	
  Republic	
  of	
  Namibia.	
  
	
  
Conover,	
  M.	
  (2002).	
  Resolving	
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  Conflicts:	
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  of	
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  Damage	
  
Management.	
  	
  Boca	
  Raton,	
  FL:	
  Lewis	
  Publishers.	
  
	
  
Corbett,	
  A.	
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Dunham,	
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Foley,	
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Gibbs,	
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Gore,	
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Associated	
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Gore,	
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163	
  

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Hampshire,	
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Lessons	
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Keane,	
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164	
  

	
  
Kerns,	
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  Risk	
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vulnerability	
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422-­‐432.	
  
	
  
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Serengeti,	
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Oryx,	
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Knuth,	
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Concepts	
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Conservation	
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Laws:	
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Conservation	
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