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This is to certify that the
thesis entitled

INVASIVE SPECIES IMPACTS ON ECOSYSTEM
STRUCTURE AND FUNCTION

presented by

ANDREA L. JAEGER

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INVASIVE SPECIES IMPACTS ON ECOSYSTEM STRUCTURE AND FUNCTION
By

Andrea L. Jaeger

A THESIS
Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of
MASTER OF SCIENCE
Department of Fisheries and Wildlife

2006

ABSTRACT
INVASIVE SPECIES IMPACTS ON ECOSYSTEM STRUCTURE AND FUNCTION
By

Andrea L. J aeger

Exotic species invasion is a worldwide threat to the integrity of aquatic
ecosystems. To understand ecosystem level response to the introduction of exotic
species, I compared food web characteristics of two eutrophic Great Lakes ecosystems -
the Bay of Quinte, Lake Ontario, Canada, and Oneida Lake, New York, USA - before
and after zebra mussel (Dreissena polymorpha) invasion using ecological network
analysis (ENA) and a social network analysis method, cohesion analysis (CA). ENA
quantiﬁes ecosystem function through an analysis of food web transfers, while CA
assesses ecosystem structure by organizing food web members into subgroups of strongly
interacting predators and prey. In Oneida Lake and the Bay of Quinte, zebra mussel
invasion increased food web organization and the potential for system development.
Additionally, zebra mussel invasion stimulated benthic production in both systems.
Effects on food web structure were strongest in the Bay of Quinte where zebra mussel
invasion removed subgroup structure entirely. In Oneida Lake, over 33% of taxa
changed subgroup association after invasion, with benthically associated subgroups
gaining the most members. This analysis suggested that the effects of zebra mussel
introduction are similar in ecosystems of comparable trophic status and that future

invasions of eutrophic systems could have similar impacts on ecosystem structure and

function.

Dedicated to the memory of

Beryl Timmer

iii

ACKNOWLEDGEMENTS

This research was supported by the Great Lakes Fishery Commission, the NOAA
Great Lakes Environmental Research Laboratory, and Michigan State University. I am
indebted to the numerous people at these organizations that made this work possible.

My major professor, Dr. Doran M. Mason, has been a valuable mentor throughout
this research. Despite the distance between his ofﬁce and mine, he has motivated,
guided, and inspired me. My committee members have also contributed greatly to this
work. Dr. Kenneth A. Frank offered much assistance with cohesion analysis methods
and interpretation; Dr. William W. Taylor was a source of boundless energy and
enthusiasm; and Dr. Scott D. Peacor always provided insightful feedback. The graduate
work of Dr. Ann E. Krause formed the foundation for much of this research. I highly
value her insight in the merging of ecological and social network analysis methods, and
the effort she devoted to these analyses. I would also like to thank Dr. Stefano Allesina
for his willingness to discuss network analysis, and Drs. Michael L. Jones and James R.
Bence for making me a part of their lab.

This research was linked with another food web modeling effort to understand the
effects of zebra mussel invasion on Oneida Lake and the Bay of Quinte. The Bay of
Quinte — Oneida Lake Comparative Modelling Project Workgroup, a group composed of
many respected scientists including Dr. E. Scott Millard, P.I. (DFO-GLLFAS), Dr.
Edward L. Mills, P.I. (Cornell University), and Dr. Marten Koops (DFO-GLLFAS),

provided extensive data and guidance. Additionally, Dr. Mills and the staff at the Cornell

iv

University Biological Field Station graciously hosted me during June 2004 for Oneida
Lake data collection.

I would also like to acknowledge the many others who surround and inﬂuence my
daily life. My (ﬁber) labmates were an abundant source of intellectual discussion and
entertainment. My close friends and colleagues at the Illinois Natural History Survey
Lake Michigan Biological Station, my previous employer, have continued to encourage
me throughout this research. The instruction of Drs. Stephen B. Hager (Augustana
College), C. Kevin Geedey (Augustana College), and Jason Powell (Zion-Benton
Township High School) still inspires me even today; these teachers brought learning
outside the classroom and into my life. I thank my parents, Douglas and Barbara Jaeger,
and brother, Jeffrey Jaeger, for encouraging me to explore all that holds my curiosity.

Finally, I thank Scott M. Miehls, my fiance, for unwavering support and companionship.

TABLE OF CONTENTS

LIST OF TABLES ........................................................................................................... viii
LIST OF FIGURES ......................................................................................................... x
CHAPTER 1
A Prologue and Context to Understanding Invasive Species Impacts on Ecosystems....l
References ........................................................................................................... 6
CHAPTER 2
Invasive Species Impacts on Ecosystem Structure and Function: A comparison of
Oneida Lake, USA, Before and After Zebra Mussel Invasion ........................................ 8
Abstract ............................................................................................................... 8
Introduction ......................................................................................................... 9
Methods ............................................................................................................... 1 3
Study Site ................................................................................................... 13
Network Construction ................................................................................ l4
Ecological Network Analysis ..................................................................... 17
Cohesion Analysis ...................................................................................... 19
Results ................................................................................................................. 22
Ecological Network Analysis — Entire Network ........................................ 22
Cohesion Analysis ...................................................................................... 24
Ecological Network Analysis - Grouped Network .................................... 25
Discussion ........................................................................................................... 29 ~
Cohesion Analysis — Structure ................................................................... 30
Ecological Network Analysis — Function .................................................. 32
Acknowledgements ............................................................................................. 38
References ........................................................................................................... 59
CHAPTER 3

Invasive Species Impacts on Ecosystem Structure and Function: A Comparison of
the Bay of Quinte, Canada, and Oneida Lake, USA, Before and After Zebra Mussel

Invasion ............................................................................................................................ 65
Abstract ............................................................................................................... 65
Introduction ......................................................................................................... 66
Methods ............................................................................................................... 70

Study Site ................................................................................................... 70
Network Construction ................................................................................ 71
Ecological Network Analysis ..................................................................... 71
Cohesion Analysis ...................................................................................... 73
Results ................................................................................................................. 75
Ecological Network Analysis — Entire Network ........................................ 75
Cohesion Analysis ...................................................................................... 76

vi

Ecological Network Analysis — Grouped Network .................................... 77

Discussion ........................................................................................................... 78

Cohesion Analysis -— Structure ................................................................... 79

Ecological Network Analysis — Function .................................................. 80

Acknowledgements ............................................................................................. 84

References ........................................................................................................... 96
APPENDICES ................................................................................................................. 101

vii

LIST OF TABLES

Table 2.1 List of food web taxa. Cisco were present in the pro-zebra mussel
time stanza but not the post-zebra mussel time stanza; lake sturgeon,
zebra mussels, and Camptocercus harpae were present in the post-
zebra mussel time stanza, but not the pre-zebra mussel time stanza ......... 40

Table 2.2 Association between common subgroup membership and the
occurrence of ties between predators and prey (adapted from Frank
1995). The odds ratio method maximizes the ratio AD : BC ................... 41

Table 2.3 Ecosystem indices for the full Oneida Lake food web network before
and after zebra mussel invasion. The percent difference was

calculated as: %Diﬂerence = Wx100% ...................................... 42

re

Table 2.4 Subgroups identiﬁed for the pre-zebra mussel invasion time stanza.
* Refers to taxa present in the pre-zebra mussel time stanza, but not
the post-zebra mussel time stanza .............................................................. 43

Table 2.5 Subgroups identiﬁed for the post-zebra mussel invasion time stanza.
"‘ Refers to taxa present in the post-zebra mussel time stanza, but not
the pre-zebra mussel time stanza. T Refers to taxa that changed
subgroup membership after zebra mussel invasion ................................... 44

Table 2.6 Throughput of subgroups before and after zebra mussel invasion.
Only six subgroups were identiﬁed before zebra mussel invasion ............ 45

Table 2.7 Ecosystem indices for the zebra mussel subgroup before and after
zebra mussel invasion. The percent difference was calculated as:

%Difference = M x100% ............................................................. 46

Pre

Table 3.1 List of food web taxa. Brook silverside, emerald shiners,
largemouth bass, round gobies, zebra mussels, and Cercopagis
pengoi, were present in the post-zebra mussel time stanza, but not
the pre-zebra mussel time stanza ................................................................ 85

Table 3.2 Association between common subgroup membership and the

occurrence of ties between predators and prey (adapted from Frank

1996). The odds ratio method maximizes the ratio AD : BC ................... 86
Table 3.3 Ecosystem indices for the full food web (Panel A), subgroup

throughput (Panel B), and ecosystem indices for subgroup 1

viii

(Panel C). The percent difference was calculated as:

%Diﬂerence = 132% x100% ............................................................. 87

re

Table 3.4 Subgroups identiﬁed for the pre-zebra mussel invasion time stanza ......... 88

ix

Figure 2.1

Figure 2.2

Figure 2.3

Figure 2.4

Figure 2.5

Figure 2.6

Figure 3.1

LIST OF FIGURES
Images in this thesis are presented in color

Zebra mussel impacts on the Oneida Lake food web, organized by
subgroup. The scale is relative: impacts above the zero line are

positive impacts of zebra mussels and impacts below the zero line are
negative impacts of zebra mussels. Taxa numbers are placed above

or below each bar. Taxon 21 was not present after zebra mussel

invasion; taxa 75-77 were not used in the subgroup analysis. See

Table 2.1 for taxa codes ............................................................................. 47

Panel A: Crystalized sociogram for the pre-zebra mussel time stanza.
Units are relative distances based on the inverse of the density of
interactions (see Frank 1996). Subgroups 1 through 6 are plotted with

the direction of feeding relationships represented by arrows (e.g.,
subgroup 6 consumes members of subgroup 1, but not vice versa);
thickness of arrow indicates weight of feeding relationships. Panel

B: Placement of taxa within subgroups. Circles indicate subgroup
boundaries and colors represent general trophic groupings of taxa.
Subgroup numbers are located to the upper right of all subgroups ............ 49

Crystalized sociogram for the post-zebra mussel time stanza. See
Figure 2.2 for description of panels ........................................................... 51

Zebra mussel impacts on subgroup members. The scale is relative:
impacts above the zero line are positive impacts of zebra mussels and
impacts below the zero line are negative impacts of zebra mussels .......... 53

Lindeman trophic spine for the pre-zebra mussel time stanza. Boxes
with Roman numerals represent the integer trophic levels; the number
within each trophic box is the percent efﬁciency of that trophic level
at processing material. Arrows between the trophic boxes are ﬂows in
the grazer food chain, arrows leaving the top of trophic boxes are
exports, arrows entering the top of trophic boxes are imports, and
arrows leaving the bottom of trophic boxes are ﬂows to detritus,
represented by the detrital box. The ground symbol from

electronic circuitry represents ﬂow loss due torespiration. All ﬂows

are in gC 111'2 yr.1 ........................................................................................ 55

Lindeman trophic spine for the post-zebra mussel time stanza. See
Figure 2.5 for a description of the ﬁgure ................................................... 57

Map of the Bay of Quinte (Source: Carolyn Bakelaar, Department of
Fisheries and Oceans, Canada) .................................................................. 89

Figure 3.2

Figure 3.3

Figure 3.4

Zebra mussel impacts on the Bay of Quinte food web. The scale is
relative: impacts above the zero line are positive impacts of zebra

mussels and impacts below the zero line are negative impacts of

zebra mussels. Taxa numbers are placed above or below each bar.

See Table 3.1 for taxa codes ...................................................................... 90

Panel A: Crystalized sociogram for the pre-zebra mussel time stanza.
Units are relative distances based on the inverse of the density of
interactions (see Frank 1996). Subgroups 1 through 6 are plotted with

the direction of feeding relationships represented by arrows; thickness

of arrow indicates weight of feeding relationships. Panel B: Placement

of taxa within subgroups. Circles indicate subgroup boundaries and

colors represent general trophic groupings of taxa. Subgroup numbers

are located to the upper right of all subgroups ........................................... 92

Lindeman trophic spine for the pre-zebra mussel time stanza. Boxes
with Roman numerals represent the integer trophic levels; the number
within each trophic box is the percent efﬁciency of that trophic level
at processing material. Arrows between the trophic boxes are ﬂows in
the grazer food chain, arrows leaving the top of trophic boxes are
exports, arrows entering the top of trophic boxes are imports, and
arrows leaving the bottom of trophic boxes are ﬂows to detritus,
represented by the detrital box. The ground symbol from electronic
circuitry represents ﬂow loss due to respiration. All ﬂows are in

gC m'z yr'l .................................................................................................. 94

xi

CHAPTER 1
A Prologue and Context to Understanding Invasive Species Impacts on Ecosystems

Andrea L. J aeger

Aquatic ecosystems worldwide are in the midst of large-scale ecological
alteration, including exotic species invasion (Mills et al. 1994; Holeck et al. 2004),
ﬁsheries collapse (Pauly et al. 1998; Myers 2003), trophic uncoupling from global
climate change (Winder and Schindler 2004), and rapid loss of native biodiversity
(Dunne et al. 2002). Exotic species invasion, in particular, is one of the most insidious
anthropogenic inﬂuences on ecosystems (Mills et al. 1994) and is the most signiﬁcant
worldwide threat to native biota (Hall and Mills 2000). The Laurentian Great Lakes of
North America have experienced pronounced invasion pressure for centuries. Exotic
species introductions have been documented since the early 18005 (Mills et al. 1993) and
number over 170 for recognized invaders (Holeck et al. 2004).1 Many more species
threaten introduction into the Great Lakes, but have yet to become established.

The numerous invasions in the Great Lakes have greatly affected ecosystem
integrity (Mills et al. 1994), structure, and function (Vanderploeg et al. 2002), causing
substantial economic hardship through damaging highly valued commercial and
recreational ﬁsheries and municipal structures (Mills et al. 1994; F acon et a1. 2005). The
extent and frequency of these disturbances make management of Great Lakes ecosystems

challenging. To address these types of challenges, some researchers (e. g. Christensen et

 

' In this context, we deﬁne exotic species as non-indigenous ﬂora and fauna which have successfully
established reproducing populations (Mills et al. 1993).

al. 1996; Pauly 2002) advocate an ecosystem management approach. Christensen et a1.
(1996) deﬁne ecosystem management as “management driven by explicit goals, executed
by policies, protocols, and practices, and made adaptable by monitoring and research
based on our best understanding of the ecological interactions and processes necessary to
sustain ecosystem composition, structure, and function.” Many policy makers and
managers have embraced this paradigm shift from historical single-species management
to ecosystem management. As of 1994, at least 18 Federal agencies committed to
ecosystem management (Congressional Research Service 1994) and that number has
surely risen in the past decade. However, understanding ecosystem structure and
function — which is fundamental to ecosystem management — is a formidable task due to
the complexity of ecosystem processes (Gaedke 1995). If we do not have a clear
depiction of ecosystem structure and function, then we have no goal for which to manage.
Moreover, ecosystems are dynamic, undergoing both natural and anthropogenic change
(e.g., exotic species invasion) that can impact ecosystem processes on a continual basis.
To meet the goals of ecosystem management, we first need an understanding of
ecosystem structure and function, inclusive of ongoing ecological change.

In this research, I used a suite of methods collectively termed network analysis to
examine the effects of exotic species invasion on food webs in the Great Lakes basin.
Network analysis has wide applicability across disciplines, including ecology,
engineering, economics (Ulanowicz 1986), and sociology (Johnson et al. 2001). In the
context of ecology, network analysis depicts food webs as networks of exchange and
evaluates the efﬁciency of energy and material ﬂow. On a more comprehensive scale,

network analysis examines the development of ecosystems and can be used to study

ecosystem change. Network analysis differs from traditional food web analysis by
incorporating weighted ﬂows between taxa, as opposed to simply using ﬂow presence or
absence data. As such, network analysis allows for a more realistic depiction of food
web ﬂow and better understanding of ecosystem processes (Gaedke 1995). Moreover,
network analysis offers an objective means to articulate the structure and function of
ecosystems.

To evaluate structure and function, I used two network analysis methods:
ecological network analysis (ENA), which quantiﬁed ecosystem function, and a social
network analysis method, cohesion analysis (CA), which quantiﬁed structure. Food web
structure encompasses the components of ecosystems, including food web taxa and the
arrangement of interactions between them, whereas function incorporates the ﬂux
processes in food webs, such as production, consumption, and respiration (Stevenson et
al. 1996). ENA quantiﬁes function through an analysis of the efﬁciency of ﬂow between
predators and prey, trophic levels, and cumulatively across the entire food web
(Ulanowicz 1986). The efﬁciency of ﬂow corresponds to ecosystem development such
that highly developed (mature), stable ecosystems sustain greater ﬂow efficiency than
lesser developed or perturbed ecosystems (Ulanowicz 1986). CA quantiﬁes structure by
organizing the food web into subgroups of strongly interacting predators and prey
(Krause et al. 2003). Subgroup structure is theorized to increase the stability of food
webs and buffer ecosystems from perturbation (Krause et al. 2003). In this research, I
applied ENA and CA methodologies to understand how exotic species invasion (as an

ecosystem perturbation) affects the functional and structural attributes of food webs.

One of the best studied exotic species in the Great Lakes basin is zebra mussels
(Dreissena polymorpha). Zebra mussels are part of a recent wave of invaders from the
Ponto-Caspian region of eastern Europe and Russia. Zebra mussels pose a considerable
threat to the Great Lakes through engineering ecosystems (V anderploeg et al. 2002) and
facilitating the establishment of other Ponto-Caspian species (Ricciardi 2001). Zebra
mussel impacts have been far-reaching in the Great Lakes, affecting habitat structure,
nutrient dynamics, and all trophic levels (Mills et al. 2003). With this research, I
examined the effects of zebra mussel invasion in Oneida Lake, New York, USA, and the
Bay of Quinte, Lake Ontario, Canada, two eutrophic ecosystems in the Great Lakes
watershed. Both systems are valuable recreationally to their surrounding areas and
sustain economically important walleye (Sander vitreus) and yellow perch (Perca
flavescens) ﬁsheries which have declined in recent years (Rudstam et al. 2004; Mills et
al. 2003). Zebra mussels were discovered in 1991 in Oneida Lake and were established
throughout the ecosystem by 1992 (Mayer et al. 2000); zebra mussels colonized the Bay
of Quinte in 1993-1994, but were not established until 1995 (Nicholls et al. 2002). The
ecology of both systems has been studied since the mid-19005, making Oneida Lake and
the Bay of Quinte ideal systems in which to examine ecological change. Finally, to
facilitate this research, I collaborated with researchers in the Bay of Quinte — Oneida
Lake Comparative Modelling Project Workgroup who built dynamic simulation models
to examine the effects of zebra mussel introduction on these systems.

Our network analysis of Oneida Lake and the Bay of Quinte was guided by three
research objectives: 1) quantify zebra mussel impacts on food web subgroup structure; 2)

quantify zebra mussel effects on ecosystem function at the full food web and subgroup

level; and 3) compare results between Oneida Lake and the Bay of Quinte, assessing
whether ecosystems of comparable trophic status respond similarly to zebra mussel
invasion. Chapter 2 addresses objectives 1 and 2 in Oneida Lake; Chapter 3 focuses on
objectives 1 and 2 for the Bay of Quinte, and concludes with a comparison between
Oneida Lake and the Bay of Quinte, addressing objective 3. With this analysis, I tested
the hypothesis that zebra mussel invasion led to the benthiﬁcation of Oneida Lake and the
Bay of Quinte. Mills et al. (2003) deﬁne benthiﬁcation as a shift of importance from
pelagic to benthic processes promoting bottom-dwelling organisms and benthic sources
of production. These changes not only have implications for how these ecosystems
should be managed (e.g., for pelagic versus benthic ﬁsheries), but also the prediction of

zebra mussel impacts in other systems.

References

Christensen, N. L., A. M. Bartuska, J. H. Brown, S. Carpenter, C. D'Antonio, R. Francis,
J. F. Franklin, J. A. MacMahon, R. F. Noss, D. J. Parsons, C. H. Peterson, M. G.
Turner, and R. G. Woodmansee. 1996. The report of the Ecological Society of

America Committee on the scientiﬁc basis for ecosystem management. Ecol.
Applic. 6: 665-691.

Congressional Research Service. 1994. Ecosystem management: Federal agency
activities. Congressional Research Service, Library of Congress, Washington,
DC, USA.

Dunne, J. A., R. J. Williams, and N. D. Martinez. 2002. Network structure and

biodiversity loss in food webs: Robustness increases with connectance. Ecol. Lett.
5: 558-567.

Facon, B., B. J. Genton, J. Shykoff, P. Jame, A. Estoup, and P. David. 2005. A general
coo-evolutionary framework for understanding bioinvasions. TREE. 21: 130-135.

Gaedke, U. 1995. A comparison of whole-community and ecosystem approaches
(biomass size distributions, food web analysis, network analysis, simulation
models) to study the structure, function and regulation of pelagic food webs. J.
Plankton Res. 17: 1273-1305.

Hall, S. R. and E. L. Mills. 2000. Exotic species in large lakes of the world. Aq. Ecosys.
Health Man. 3: 105-135.

Holeck, K. T., E. L. Mills, H. J. MacIsaac, M. R. Dochoda, R. I. Colautti, and A.
Ricciardi. 2004. Bridging troubled waters: Biological invasions, transoceanic
shipping, and the Laurentian Great Lakes. BioScience. 54: 919-929.

Johnson, J. C., S. P. Borgatti, J. J. Luczkovich, and M. G. Everett. 2001. Network role
analysis in the study of food webs: An application of regular role coloration. J.
Soc. Struct. 2: 1-15.

Krause, A. E., K. A. Frank, D. M. Mason, R. E. Ulanowicz, and W. W. Taylor. 2003.
Compartments revealed in food-web structure. Nature. 426: 282-285.

Mayer, C. M., A. J. VanDeValk, J. L. Fomey, L. G. Rudstam, and E. L. Mills. 2000.
Response of yellow perch (Percaﬂavescens) in Oneida Lake, New York, to the
establishment of zebra mussels (Dreissena polymorpha). Can. J. Fish. Aquat. Sci.

57: 742-754.

Mills, E. L., J. H. Leach, J. T. Carlton, and C. L. Secor. 1993. Exotic species in the Great
Lakes: A history of biotic crises and anthropogenic introductions. J. Great Lakes
Res. 19: 1-54.

Mills, E. L., J. H. Leach, J. T. Carlton, and C. L. Secor. 1994. Exotic species and the
integrity of the Great Lakes. BioScience. 44: 666-676.

Mills, E. L., J. M. Casselman, R. Derrnott, J. D. F itzsimons, G. Gal, K. T. Holeck, J. A.
Hoyle, O. E. Johannsson, B. F. Lantry, J. C. Makarewicz, E. S. Millard, I. F.
Munawar, M. Munawar, R. O'Gorman, R. W. Owens, L. G. Rudstam, T. Schaner,
and T. J. Stewart. 2003. Lake Ontario: Food web dynamics in a changing
ecosystem (1970-2000). Can. J. Fish. Aquat. Sci. 60: 471-490.

Myers, R. A. and B. Worm. 2003. Rapid worldwide depletion of predatory ﬁsh
communities. Nature. 423: 280-283.

Nicholls, K. H., L. Heintsch, and E. Carney. 2002. Univariate step-trend and multivariate
assessments of the apparent effects of P loading reductions and zebra mussels on
the phytoplankton of the Bay of Quinte, Lake Ontario. J. Great Lakes Res. 28: 15-
3 l.

Pauly, D., V. Christensen, J. Dalsgaard, R. Froese, F . Torres, Jr. 1998. Fishing down
marine food webs. Science. 279: 860-863.

Pauly, D., V. Christensen, S. Guenette, T. J. Pitcher, U. R. Sumaila, C. J. Walters, R.
Watson and D. Zeller. 2002. Towards sustainability in world ﬁsheries. Nature.
418: 689-695.

Ricciardi, A. 2001. Facilitative interactions among aquatic invaders: Is an "invasional
meltdown" occurring the Great Lakes? Can. J. Fish. Aquat. Sci. 58: 2513-2525.

Rudstam, L. G., A. J. VanDeValk, C. M. Adams, J. T. H. Coleman, J. L. F omey, and M.
E. Richmond. 2004. Cormorant predation and the population dynamics of walleye
and yellow perch in Oneida Lake. Ecol. Applic. 14: 149—163.

Stevenson, R. J ., M. L. Bothwell, and R. L. Lowe. 1996. Algal Ecology: Freshwater
Benthic Ecosystems. Academic Press.

Winder, M. and D. E. Schindler. 2004. Climate change uncouples trophic interactions in
an aquatic ecosystem. Ecology. 85: 2100-2106.

Ulanowicz, R. E. 1986. Growth and Development: Ecosystems Phenomenology. Springer
Verlag.

Vanderploeg, H. A., T. F. Nalepa, D. J. Jude, E. L. Mills, K. T. Holeck, J. R. Liebig, I.A.
Grigorovich, and H. Ojaveer. 2002. Dispersal and emerging ecological impacts of
Ponto Caspian species in the Laurentian Great Lakes. Can. J. Fish. Aquat. Sci. 59:
1209-1228.

CHAPTER TWO

Invasive Species Impacts on Ecosystem Structure and Function: A Comparison of Oneida

Lake, USA, Before and After Zebra Mussel Invasion

Andrea L. J aeger, Doran M. Mason, Ann E. Krause, Kenneth A. Frank, William W.

Taylor, and Scott D. Peacor

Abstract

Exotic species invasion is one of the greatest ecological restructuring forces. To
understand impacts of exotic species on ecosystem level properties, we compared Oneida
Lake, New York, USA, food web characteristics before and after zebra mussel
(Dreissena polymorpha) invasion using ecological network analysis (ENA) and social
network analysis (SNA) methods. ENA quantiﬁes ecosystem function through an
analysis of food web energy and material transfer. The SNA method we used, cohesion
analysis, assesses ecosystem structure by organizing food web members into subgroups
of strongly interacting predators and prey. These methods detected direct and indirect
effects, changes in trophic ﬂow efﬁciency, and alterations of food web organization and
ecosystem activity resulting from zebra mussel invasion. ENA indicated that zebra
mussels altered food web function by shunting energy from pelagic to benthic pathways,
increasing dissipative ﬂow loss, and decreasing ecosystem growth. SNA suggested that
zebra mussels altered food web structure by reorganizing carbon ﬂow within and between

discrete subgroups of predators and prey and also increasing the importance of

benthically associated subgroups. Together, these analyses demonstrate that zebra
mussels exert strong inﬂuence on food webs and promote the benthiﬁcation of aquatic

ecosystems.

Introduction

Globally, exotic species invasion is one of the greatest restructuring forces to
ecosystems (Baxter et al. 2004). Non-native species can impact ecosystems through
competition with and predation on native species, and by altering habitats, nutrient
cycles, and energy budgets (Mack et a1. 2000). Invasions can occur across all trophic
levels with effects propagating throughout entire ecosystems via direct and indirect
pathways (Crooks 2002). In recent years, vertebrate and invertebrate species from the
Ponto-Caspian region of eastern Europe have exerted pronounced invasion pressure in
North America, Europe, and Russia (Drake and Bossenbroek 2004). Among the most
recognized Ponto-Caspian invertebrate invaders in North America are two species of
mussels, the zebra (Dreissena polymorpha) and quagga (D. bugensis) mussels. These
invaders exhibit wide environmental tolerances and high phenotypic variability (Reid and
Orlova 2002) which make them adaptable to many different ecosystems and thus helps
facilitate their invasion into non-native food webs.

Dreissenid mussels pose a considerable threat to aquatic environments by altering
food web structure and function (Jones et al. 1994; Vanderploeg et al. 2002). Zebra
mussels increase water clarity through ﬁltration (Idrisi et al. 2001) and shunt energy from
pelagic to benthic pathways (Rutherford et al. 1999; Mayer et a1. 2002). Additionally,

dreissenid mussels can affect zooplankton production and abundance through decreasing

pelagic primary production and changing nutrient cycling in lakes (Mellina et al. 1995;
Johannsson et al. 2000) and rivers (Strayer et al. 1999; Thorp and Casper 2003). Also,
dreissenid mussels may facilitate macroinvertebrates, such as amphipod and isopod
species, in the Laurentian Great Lakes through pseudofeces deposition which can be used
as a food resource (Beekey et al. 2004). Yet, the abundance of some macroinvertebrate
species, such as Diporeia spp., has precipitously declined in correlation with the invasion
and expansion of dreissenids (Nalepa et al. 2000).

Dreissenid invasions may also affect ﬁsh communities, although the causal
linkages are difﬁcult to establish in some systems. Dreissenids may affect ﬁsh
recruitment and production through modiﬁcation or degradation of spawning habitat
(Stewart et al. 1999; Marsden and Chotkowski 2001). Additionally, some Great Lakes
ﬁshes, such as lake Whiteﬁsh (Coregonus clupeaformis), exhibit decreased body
condition and growth potentially due to a diet shift away from high-energy prey, such as
Diporeia, to the lower-energy dreissenid mussels (Pothoven et al. 2001). Dreissenid
impacts on yellow perch (Percaﬂavescens) vary by life stage and ecosystem. For
example in Lake Michigan, zebra mussels may have adversely affected larval yellow
perch by decreasing zooplankton food resources (Dettrners et al. 2003). Conversely in
some inland lakes, zebra mussels have not noticeably affected young yellow perch
growth, biomass, or production (Mayer et al. 2000, Idrisi et al. 2001) and may indirectly
beneﬁt adult yellow perch and lake sturgeon (Acipenserfulvescens) through enhanced
benthic invertebrate production (Rutherford et al. 1999; Jackson et al. 2002). Centrarchid
ﬁsh can also beneﬁt indirectly by zebra mussel facilitation of macrophyte production

which serves as habitat (Strayer et al. 2004).

10

The uncertainty within systems and confounding results of dreissenid impacts
between systems highlight the complexities associated with understanding ecosystem
level response to invaders. Integrated and quantitative approaches, such as network
analyses, offer innovative methods to disentangle the complexities of ecosystems. For
network analysis, food webs are depicted as networks of exchange by quantifying (i.e.,
weighting) feeding interactions and energy ﬂow (Bondavalli et al. 2000). The ability to
quantify trophic interactions can contribute signiﬁcantly to food web analysis (Gaedke
1995; Zorach and Ulanowicz 2003; Krause et al. 2003). Much of the early work
conducted on food webs used unweighted ﬂows, frequently over-simplifying or
misrepresenting ﬂux processes: the role of minor contributors was exaggerated while the
role of major contributors was diminished. By quantifying ﬂows, researchers tease apart
these unequal contributions to provide a clearer depiction of food web energy and
material transfer, and allow a better understanding of how interactions are transmitted
through ecosystems.

Moreover, network analyses are applicable at the whole-system level. By
quantifying interactions throughout the entire ecosystem, insight into processes not
evident at small-scale resolutions may be gained (Heymans et al. 2002). Bailey et al.
(1999) suggested that small-scale impacts may aggregate synergistically and these overall
impacts may only be visible when viewed at the ecosystem level. As such, network
analysis has proven useful for examining the effects of ﬁsheries harvest (Pauly et al.
1998), ﬁsheries stocking (Fayram et al. In press), and nutrient loading (Bondavalli et al.
In press) on ecosystems, while having implications for managing carbon emissions

(Bondavalli et al. 2000) and habitat for endangered species (Heymans ct al. 2002). By

11

taking into account entire ecosystems, the use of network analysis in these studies
allowed an understanding — distinct from, but complementary to, single-species, species-
pair or similar studies — of how changes percolated through entire food webs, including
indirect pathways. Moreover, network analysis can give insight into causality between
events, not just correlation. The causality aspect makes network analysis a valuable tool
for clarifying the effects of ecosystem perturbation, including exotic species invasion. In
light of the equivocal effects of dreissenid invasion described above, we seek to elucidate
dreissenid impacts at the ecosystem scale using network analysis.

Numerous data exist describing the qualitative effects of dreissenid mussels,
especially zebra mussels; however, less literature quantiﬁes these effects at the ecosystem
scale, speciﬁcally with regard to ecosystem structure and function. Ecosystem structure
encompasses the components of a food web, whereas ecosystem function refers to the
processes that occur within food webs (Stevenson et al. 1996). Structural characteristics
include measurements of system state, such as biomass and taxonomic composition;
whereas, functional characteristics deal with rates of change in a system state, including
measurements of productivity and respiration (Stevenson et al. 1996). Mills et al. (2003)
documented changes in Lake Ontario structure and function after zebra mussel invasion
and coined the term “benthiﬁcation” to encompass these changes. Benthiﬁcation refers
to a shift of importance from pelagic processes to benthic processes, entailing a change in
energy ﬂow “favoring colonization of bottom-dwelling organisms, promoting ﬁsh
communities that make efﬁcient use of the benthic habitat, and enhancing growth rate
cycles of benthic algae and submersed aquatic vegetation”. Using Mills ct al. (2003)

attributes of ecosystem benthiﬁcation, we examined ecosystem properties of a eutrophic

12

lake, Oneida Lake, New York, USA, to determine if benthiﬁcation occurred as a result of
zebra mussel invasion.

The primary objective of this paper was to quantify zebra mussel impacts on
ecosystem structure and function in Oneida Lake, speciﬁcally by addressing the
following questions:

1. Structure: Do zebra mussels alter the membership of food webs and food web
subgroups (deﬁned as clusters of strongly interacting predators and prey)?

2. Function: Does the magnitude of carbon ﬂow within food webs and food web
subgroups change as a result of zebra mussel invasion?

Using food web network analysis, we hypothesized that zebra mussels led to the
benthiﬁcation of Oneida Lake with concomitant changes in ecosystem structure and

function that promoted benthic communities.

Methods
Study Site
Oneida Lake is a shallow, eutrophic, 207 km2 lake on the Ontario Lake Plain in

central New York with a mean depth of 6.8 m and maximum depth of 16.8 m (Jackson et
al. 2002; Rudstam et al. 2004). The lake freezes in winter and mixes continuously during
summer except for brief periods of thermal stratiﬁcation during calm weather (Hansen
and Hairston 1998). Oneida Lake supports a valuable warrnwater recreational ﬁshery for
walleye (Sander vitreus) and yellow perch, in addition to multiple other species

(V anDeValk et al. 2002). Zebra mussels were discovered in 1991 and were established

throughout the ecosystem by 1992 (Mayer et al. 2000). Because of the long-terrn history

13

of limnological and ﬁshery research on Oneida Lake (e.g., Mills et al. 1978; Mills and
Fomey 1988), data exist throughout the various stages of invasion - from pre-
introduction, to invasion, through establishment, and ﬁnally reorganization and
accommodation of the ecosystem — to examine the effects of zebra mussel invasion.
Network Construction

We constructed weighted food web networks before and after zebra mussel
invasion and analyzed the networks using ecological network analysis (ENA) (U lanowicz
1986) and a social network analysis (SNA) method, cohesion analysis (CA) (Frank 1995;
Krause et al. 2003). We deﬁned the years 1986 to 1991 as the pre-zebra mussel invasion
time stanza and the years 1992 to 2002 as the post-zebra mussel invasion time stanza. To
construct the networks, we ﬁrst identiﬁed the taxa in the ecosystem (including full-year
resident taxa as well as transient taxa), and then quantiﬁed material exchange (ﬂows)
between taxa and with the environment (we adjusted ﬂows for transient taxa based on
duration in the ecosystem). For taxa identiﬁcation, we attempted to be as thorough as
possible and included all species from Oneida Lake for which data were available.
Taxonomic resolution affects the study of food webs and lumping organisms into
aggregate groups may decrease the ability to detect differences in strengths of
connections between functionally different organisms (Abarca-Arenas and Ulanowicz
2002; Krause et al. 2003; Pinnegar et al. 2005). Therefore, wherever possible, we used
species level data to avoid information loss and in some cases, e.g., walleye, yellow
perch, and seven other ﬁsh taxa, species data was sub-divided by life stage. However, in
some cases, data limitations forced aggregation of taxa (e.g., age-0 panﬁsh). In some of

these situations, we aggregated by “trophospecies”, a collection of species in a food web

14

that share similar predators and prey (Yodzis and Winemiller 1999). This aggregation
method is a fundamental unit of study in food web and ecosystem research (Yodzis and
Winemiller 1999) and is widely used in food web analysis (e.g., Teal 1962; Moloney and
Field 1991; Bondavalli et al. 2000). Where high resolution trophic information was not
available (such as for benthic invertebrate and phytoplankton species), clustering adhered
closely to taxonomic distinctions as opposed to trophic relationships. Finally, data on the
microbial food web was not available for Oneida Lake and was not included in our
networks. The complete list of the seventy-seven species and aggregate groups for the
pre- and post-zebra mussel invasion networks are listed in Table 2.1.

After identifying the food web components, we created the network connection
topography, i.e., food web exchanges. Exchanges occur both within the food web
through predator-prey interactions and between the food web and surrounding

environment through migration, primary production, respiration, and harvest (Bondavalli

et al. 2000). We used carbon as our network currency for biomass (gC m'z) and

exchange between taxa (gC m"2 yr'l). To estimate carbon exchanges, we obtained data

on biomass, production-, consumption-, and respiration-to-biomass ratios, diet
proportions, migrations, and harvest for all taxa from the primary literature, ﬁeld studies,
and expert researchers on Oneida Lake (including the Bay of Quinte - Oneida Lake
Comparative Modelling Workgroup). These parameters along with their sources are
listed in Appendix 2.1. Exchanges either ﬂow into a taxa as a carbon input (e. g.,
consumption and immigration), or ﬂow out of the taxa as a carbon output (e.g.,
production, respiration, harvest, and emigration). To calculate production, consumption,

and respiration for taxa, we multiplied the production-, consumption-, and respiration-to-

15

biomass ratios by the taxa biomass. To quantify feeding relationships between predatory
taxa and prey, we apportioned the predator’s consumption among its prey items by
multiplying the predator consumption estimate and predator diet vector (a list of predator

diet items proportioned by weight). This calculation yielded a vector of carbon
exchanges (gC rn'2 yr'l) between the predator and its prey. Aligning the exchange

vectors for every predator in the system creates what is called the exchange matrix. The
exchange matrix quantiﬁes all feeding relationships within the network and is the
foundation of our network analysis calculations.

Our ENA required networks to be mass-balanced, i.e., a condition where the
amount of medium entering any taxa equals the amount leaving (Allesina and Bondavalli
2003). We assessed the ﬂow balance of our networks by comparing inputs and outputs
for all taxa. If a ﬂow imbalance existed, we rectiﬁed the discrepancy by either assigning
a ﬂow to detritus (if inputs exceeded outputs) or changing one or more model inputs.
The detrital-balancing approach is partially drawn from mass-balance methods employed
in the software EcoPath (Christensen and Pauly 1992) and was our means to assign ﬂow
to detritus in lieu of ﬁeld estimates. When changing a model input to obtain mass-
balance, we used factors such as ecological plausibility (i.e., the similarity of the Oneida
Lake parameter to other systems of similar trophic status) and conﬁdence in accuracy of
parameter estimates as guides to determine which parameter to change. Finally, to
resolve any remaining imbalances, we used the DATBAL routine incorporated in the
EcoNetwrk software (http://www.glerl.noaa.gov/EcoNetwrk/). These routines resulted in

balanced food web networks with as few changes to the original model inputs as possible.

16

Appendix 2.2 presents the balanced exchange matrices for the pre- and post-zebra mussel
invasion networks.
Ecological Network Analysis

After we constructed the networks, we performed the ENA and CA routines to
quantify Oneida Lake function (via ENA) and structure (via CA) before and after zebra
mussel invasion. ENA is a method that evaluates the efficiency of energy and material
ﬂow (e. g., transfers, assimilations, and dissipations) in ecosystems (U lanowicz 1986).
We used three types of ecological network analyses (U lanowicz 1986): 1) input / output
analysis, 2) trophic level analysis, and 3) the calculation of ecosystem indices. To
perform the analyses, we used the software package EcoNetwrk, a Windows-based
version of the NETWRK software (U lanowicz & Kay 1991). We provide a brief
description of ENA methods below; for greater detail see Ulanowicz (1986) and
Ulanowicz (1997).

Input / output analysis (Harmon 1973; Patten et al. 1976) details the direct and
indirect linkages between any two taxa in a network, quantifying the requisite carbon
needs of any one taxon supplied by any other taxon (Bondavalli et al. 2000). The
analysis includes a routine called IMPACTS that quantiﬁes the relative effect of one
taxon on another by tracing direct and indirect predatory interactions (Heymans and
Baird 2000).

Trophic analysis reinterprets the web of predator-prey transfers in terms of the
linear trophic chain concept of Lindeman (Lindeman 1942). Using input / output

techniques, the trophic analysis apportions the activities of omnivores among a series of

17

hypothetical integer trophic levels to create the Lindeman spine, which can be used to
evaluate the efﬁciency of carbon ﬂow in the system (Heymans and Baird 2000).

Ecosystem indices quantify abstract system level properties such as growth and
development, and provide insight into both the vulnerability and resilience of an
ecosystem to perturbation (Ulanowicz 1997). These indices are: total system throughput
(TST), average mutual information (AMI), ascendency (A), overhead (0), and

development capacity (C). The activity level of the ecosystem is quantiﬁed via TST
which is simply the sum of all the carbon ﬂows (gC rn'2 yr'l) in the system. TST relates

to the size of an ecosystem gauged similarly to how economic activity is measured (i.e.,
as the ﬂow of some currency) and can be used to quantify ecosystem growth. AMI is an
information theoretic index (Shannon 1948; McEliece 1977) that quantiﬁes the
organization of a network based on pathway ﬂow constraints. Ascendency quantiﬁes the
growth and development of an ecosystem (Ulanowicz 1986) as well as the network’s
performance in processing medium. Ascendency is calculated by scaling the AMI with
TST: A = TST x AMI . As such, ascendency encompasses both the size (via TST scaling)
and organization (via AMI) of an ecosystem. Overhead quantiﬁes the system’s
inefﬁciencies at processing material and energy (Heymans et al. 2002) as well as the
degree of freedom that the system has to reconﬁgure itself in the face of perturbation
(Heymans and Baird 2000). There are four main contributors to ecosystem overhead:
imports (i.e., immigrations) to and exports (i.e., emigrations and ﬁsheries harvest) from
the ecosystem, dissipative ﬂow loss due to respiration, and redundant food web ﬂows
(i.e., multiple paths over which energy ﬂows between taxa). Overhead is calculated by

scaling the system’s conditional entropy (Ulanowicz 1986), a measure of the

18

disorganization in a network, by TST: 0 = T ST x Conditional Entropy. Development

capacity represents the theoretical upper bound on system organization and growth.
Capacity subsumes both ascendency and overhead, such that: C = A + 0.
Cohesion Analysis

Cohesion analysis identiﬁes subgroups in food webs based on the strength of
interactions (i.e., predator-prey relationships) within subgroups (Krause et al. 2003),
where the maximization of an odds ratio is used as a criterion to assign subgroup
membershipz. CA uses an iterative algorithm that reassigns taxa to subgroups to
maximize the odds that interactions occur within subgroups, versus between subgroups.
The algorithm uses interaction weight to preferentially assign predators and prey with
strong interactions to common subgroups. This algorithm is a robust method for
assigning subgroups because it: 1) is an objective technique to assign subgroups; 2) does
not require pre-speciﬁcation of the number of subgroups; 3) identiﬁes discrete (i.e., non-
overlapping) subgroups; and 4) tests the statistical signiﬁcance of the results (Frank 1995;
Frank 1996; Krause et al. 2003). To determine the optimized subgroups, the algorithm
sums the weight of realized interactions (i.e., predator-prey exchanges) within a subgroup
and evaluates that sum against realized interactions that occur between subgroups, in
addition to unrealized interactions (i.e., taxa combinations that do not interact) within and
between subgroups. Table 2.2 describes this process. The intent is to determine the
network structure that maximizes realized interactions within subgroups and unrealized
interactions between subgroups while minimizing realized interactions between

subgroups and unrealized interactions within subgroups.

 

2 Our use of the term “subgroup” is analogous to the Pimm and Lawton (1980) deﬁnition of food web
“compartment”. We use the term “subgroup” to avoid confusion between Pimm and Lawton (1980) and
Ulanowicz(1986) uses of the term “compartment”.

19

Using the software Kliqueﬁnder (Frank 1995), we identiﬁed subgroups within the
Oneida Lake food web networks before and after zebra mussel invasion and compared
the grouped webs to reveal changes in food web structure. Although our ENA required
balanced networks, our CA did not. Therefore, in order to avoid introducing uncertainty
to the CA models from ENA balancing procedures, we used the unbalanced networks for
CA of both time stanzas. Furthermore, because we derive detrital diet as a result of
balancing procedures, we could not include detrital groups in our CA.

For the pre-zebra mussel invasion network, carbon ﬂows ranged from 8.26x10'lo

to 8.25 gC rn'2 yr'l, a difference of 10 orders of magnitude; for the post-invasion

-ll

- network, carbon ﬂows ranged from 7.48x10 to 18.38 gC rn'2 yr'l, a difference of 12

orders of magnitude. Kliqueﬁnder accepts ﬂow weights only within 5 orders of
magnitude; therefore, we needed to adjust the range of network data. Appendix 2.3
describes, in detail, the method we used. We tested three adjustments of data ranges, and
compared the adjustments based on statistical tests of subgroup membership. The three
adjustments involved: 1) changing the range of data by one order of magnitude between
the schemes; 2) assigning the maximum ﬂow weight to ﬂows above the range of
Kliqueﬁnder; and 3) assigning the minimum ﬂow weight to non-zero ﬂows below the
range of Kliqueﬁnder. Adjustment one set the highest ﬂows one order of magnitude
above the upper range of Kliqueﬁnder, and adj ustrnents two and three set the highest
ﬂows two and three orders of magnitude above the upper range for Kliqueﬁnder,
respectively. Subgroup membership was similar for all adjustments (p g 0.001 for all
comparisons); we chose adjustment two because it assigned maximum and minimum

values to the fewest ﬂows overall.

20

Kliqueﬁnder incorporates a Monte Carlo-like routine to test the odds ratio of a
subgrouped network against a distribution of odds ratios from randomly generated re-
combinations of data (Frank 1996). Using this method, we tested the statistical
signiﬁcance of our subgroups against 1,000 randomized versions of our networks.
Additionally, using the Quadratic Assignment Procedure (QAP) method (Hubert 1987)
for signiﬁcance testing, we statistically compared subgroup membership between the pre-
and post-zebra mussel invasion time stanzas.

We summarized results of the CA as “crystallized sociograms” through
multidimensional scaling (Frank 1996) in SAS System for Windows. With this scaling
method, proximity of subgroups corresponds to: 1) the strength of predator-prey
relationships spanning the subgroups (i.e., closely spaced subgroups have relatively
stronger interactions connecting them than subgroups farther apart); 2) connections to
similar subgroups; and 3) the subgroup’s importance to overall food web structure (i.e.,
centrally located subgroups are more important to food web structure than peripherally
located subgroups). Also, taxa location within a subgroup boundary indicates: 1) the
strength of interactions between taxa; and 2) the importance of taxa to the subgroup (i.e.,
taxa in the center of subgroups relate more strongly to the subgroup, while taxa near
subgroup boundaries only experience peripheral relationships to the subgroup).

After we identiﬁed cohesive subgroups, we performed ENA on the largest
subgroup before and after zebra mussel invasion to evaluate functional linkages. We
maintained the same mass-balance in the subgroup analysis as the full food webs by
treating all ﬂows to and from taxa outside the subgroup as imports and exports to

subgroup taxa. Because detrital groups were not assigned to subgroups, detritus could

21

not be explicitly incorporated into the subgroup ENA. Inclusion of the microbial food
web could serve as a surrogate for detritus ﬂow; however, as stated above, microbial data
was not available for Oneida Lake. Nevertheless, ﬂow to detritus was implicitly included
in the subgroup ENA by treating detrital ﬂow as an export from the subgroup. This
procedure had two ramiﬁcations: 1) we could address detrital ﬂow, albeit indirectly, in
the subgroups; and 2) we maintained the same mass-balance used in the full food web
ENA. If, as hypothesized, zebra mussels led to the benthiﬁcation of Oneida Lake, we

expected to see increased importance of benthic pathways within this subgroup.

Results
Ecological Network Analysis — Entire Network

Input / output analysis

Zebra mussels had more negative impacts across all taxa than neutral or positive
impacts (Figure 2.1). In general, zebra mussels positively inﬂuenced benthic ﬁsh such as
ictalurids, carp, and lake sturgeon, while negatively affecting pelagic ﬁsh, including
walleye, yellow perch (pelagic for some life stages), white perch, alewife, and shiners.
Some ﬁsh, such as gizzard shad and centrarchid species, showed mixed impacts based on
life stage (e.g., juvenile gizzard shad were negatively affected while adult gizzard shad
were positively affected). Most likely this is due to ontogenetic diet shifts between the
juvenile and adult life stages (Werner and Gilliam 1984), although some ﬁsh that undergo
diet shifts, e.g., yellow perch, did not show a similar pattern. Benthic invertebrates
exhibited mixed impacts, with amphipods and isopods beneﬁting from zebra mussel

interaction, while zebra mussels had a large negative inﬂuence on themselves due to

22

heavy grazing on their food sources. Zebra mussels also negatively inﬂuenced
zooplankton and phytoplankton. Zebra mussels had little, if any, effect on some ﬁshes
(e.g., smallmouth bass and white bass), invertebrates (e.g., oligochaetes and snails), and
periphyton, epiphyton, and macrophytes. Finally, zebra mussel inﬂuence on detritus was
mixed: pelagic detritus and DOC were negatively affected, most likely through direct
consumption by zebra mussels, while sedimented detritus was positively affected likely
due to deposition of pseudofeces. The positive effect on sedimented detritus may explain
why impacts on benthic invertebrates were mixed. Amphipods and isopods rely more
heavily on sedimented detritus and less heavily on plankton resources than do other
benthic invertebrates such as chironomids and clams.
Lindeman trophic analysis

We were unable to create the Lindeman trophic spine for the full Oneida Lake
food web networks due to computational limitations in the EcoNetwrk software resulting
from the complexity of our networks. Although we could not analyze efficiency of ﬂow

between trophic levels, we can diagnose the efﬁciency of ﬂow summed across the entire
food web. Flow loss due to respiration in the full food web was 1015.6 gC m'2 yr'l
before zebra mussel invasion and 777.9 gC rn'2 yr'1 after zebra mussel invasion, a 23%
decrease. Total production (i.e., feeding exchanges between taxa plus the usable exports
from the system) in the full food web was 624.1 gC m'2 yr'l before zebra mussel invasion
and 589.1 gC m'2 yr.1 after zebra mussel invasion, 3 5% decrease.
Ecosystem indices

TST decreased from 2653.8 to 2143.6 gC m'2 yr'l, approximately a 20% loss in

ecosystem activity (Table 2.3). Additionally, the development capacity decreased from

23

13316.7 to 11037.2 gC-bits m'2 yr'1 after zebra mussel invasion. Likewise, ascendency
dropped after invasion, from 3350.9 to 2926.3 gC-bits rn'2 yr'l constituting a 13%

decrease, as did total overhead, from 9965.9 to 8110.9 gC-bits rn'2 yr'l representing a

19% decrease. However, these results were partially driven by changes in TST (i.e.,
system growth), which scales capacity, ascendency, and overhead. To remove the effects
of TST scaling on capacity, we divided capacity by TST. Unsealed capacity increased
from 5.0 to 5.1 bits, representing a 2% increase in the potential for system development.
To remove the effect of TST scaling on ascendency and overhead, and look solely at the
amount of organized and disorganized ecosystem function, we divided both indices by
the development capacity. This calculation removed the TST scaling through division
and yielded the proportion that ascendency and overhead comprised of capacity
(expressed as a percent of capacity in Table 2.3), termed “relative ascendency” and
“relative overhead”, respectively. Ascendency constituted 25.2% of capacity before
zebra mussel invasion and 26.5% of capacity after invasion. Overhead represented
74.8% of capacity before zebra mussel invasion and 73.5% after. These results indicate
that the Oneida Lake food web is predominantly comprised of disorganized ﬂow, but
became slightly more organized after zebra mussel invasion. Considering the ecosystem
processes that contribute to system overhead (imports, exports, dissipations, and ﬂow
redundancies), the relative overhead indices decreased after zebra mussel invasion
between 1% and 22% except for ﬂow redundancies, which increased almost 7%.
Cohesion Analysis
We identiﬁed six signiﬁcant subgroups for the pre-zebra mussel invasion network

(p S. 0.001; odds ratio = 15.4) and seven signiﬁcant subgroups for the post-invasion

24

network (p 5 0.001; odds ratio = 14.7). Tables 2.4 and 2.5 present the subgroup
membership for the pre- and post-invasion networks, respectively. Both networks
contained three subgroups of predator-prey interactions: 1) a planktivorous food web
(including planktivorous ﬁsh, zooplankton, and phytoplankton), 2) benthically associated
predators and prey, and 3) planktivores and zooplankton prey. Additionally, both
networks contained three mostly ﬁsh subgroups: l) panﬁsh, 2) piscivores, and 3)
piscivores and invertivores. Finally, the seventh subgroup in the post-invasion network
contained mainly low biomass taxa from multiple trophic levels. We loosely named
subgroups based on ecological descriptions that represent the majority of taxa within each
subgroup. The names are meant as a tool to facilitate discussion of analyses; however,
not all taxa ﬁt the subgroup name.

Subgroup membership was similar between the two time stanzas (Z-score =
20.60, p 5 0.001) despite a large number of changes to subgroup membership. Of the
seventy taxa present for both time stanzas, twenty-three (33% of all taxa) changed
subgroup membership after invasion: seventeen ﬁsh, ﬁve zooplankton, and one benthic
invertebrate. Zebra mussels invaded the planktivorous food web subgroup (subgroup 1),
the largest subgroup (based on number of taxa) in both time stanzas. Subgroup shifts
relevant to Oneida Lake ﬁsheries management include subadult (age 1-3 years) walleye,
which moved to the subgroup (subgroup 6) with cormorants (Phalacrocorax auritus)
after invasion and adult walleye (age 4 years and older), which shifted to the subgroup
containing zebra mussels. Juvenile (age-0) yellow perch also transferred to the subgroup
containing zebra mussels while subadult (age 1-2 years) yellow perch shifted to the

benthically associated subgroup (subgroup 2).

25

Figures 2.2 and 2.3 summarize the cohesion analysis in crystallized sociograrns.
Before zebra mussel invasion, the planktivorous food web, benthically associated, and
piscivore (subgroup 5) subgroups strongly interacted and played central roles within the
food web (Panel A). The remaining subgroups had more peripheral roles. After
invasion, the subgroups were more closely related except for the subgroup containing low
biomass taxa (subgroup 7). The taxa within the planktivorous food web and benthically
associated subgroups strongly interact whereas the taxa in the remaining subgroups are
not as cohesive (Panel B). Phytoplankton and zooplankton play central roles within the
planktivorous food web subgroup, while benthic invertebrates occupy central positions
within the benthically associated subgroup.

Ecological Network Analysis — Grouped Network

Below, we analyze the functional characteristics of the subgroup that zebra
mussels invaded, the planktivorous food web subgroup (hereafter also referred to as the
zebra mussel subgroup), which is the largest subgroup before and after invasion in terms
of number of taxa and TST (Table 2.6).
Input / output analysis

When we deciphered the direct and indirect effects of zebra mussels on their
subgroup (via the IMPACTS analysis), we found that zebra mussels negatively affected
all their subgroup members (Figure 2.4). Our full food web analysis also indicated that
zebra mussels negatively affected these taxa (Figure 2.1); however, the magnitudes of the
effects differed slightly in the subgroup analysis. The largest difference involved zebra
mussel inﬂuence upon themselves. The IMPACTS value changed from -0.33 in the full

food web (Figure 2.1) to -0.11 in the subgroup, representing a 67% change. Potentially

26

we see a lessened effect of zebra mussels upon themselves at the subgroup level because
detrital groups, including pelagic detritus and DOC, were not included in the analysis.
Zebra mussels prey heavily on detrital groups, negatively affecting themselves via
depletion of their food supply.

Although we cannot directly conduct an IMPACTS analysis of zebra mussels on
the other six subgroups (to conduct the analysis, zebra mussels would need to be present
in the subgroup network) we can indirectly detect zebra mussel inﬂuence in those
subgroups by considering impacts on individual taxa from our full food web analysis
(Figure 2.1). Unlike the (wholly negative) zebra mussel inﬂuence on taxa in their
subgroup, zebra mussel effects on taxa in other subgroups were mixed with no consistent
pattern between subgroups. The majority of negative effects were conﬁned to the zebra
mussel subgroup while some subgroups, including subgroups 2, 4, 5, and 6, exhibited net
positive effects of zebra mussels
Lindeman trophic analysis

The Lindeman trophic analysis identiﬁed six trophic levels in the zebra mussel
subgroup before invasion and nine trophic levels after invasion (Figures 2.5 and 2.6).
Before invasion, age-0 gizzard shad were the top predator in the subgroup and fed up to
the sixth trophic level; after invasion and with the addition of multiple ﬁsh to this
subgroup, adult walleye were the top predator and fed at the ninth trophic level. Zebra
mussels fed at the second trophic level; consequential to their invasion, trophic ﬂow
efﬁciency fell almost 10% at trophic level II as respirative losses more than tripled and
ﬂow loss to detritus almost doubled. Flow efﬁciencies at trophic levels IV and higher

increased subsequent to invasion.

27

Total respiration and production decreased in the zebra mussel subgroup after

invasion. Flow loss due to respiration was 424.1 gC rn'2 yr'l before invasion and 396.2
gC m'2 yr'1 after invasion (6% decrease), while production was 484.7 gC m.2 yr'l before

invasion and 401.0 gC rn'2 yr'1 after invasion (17% decrease). Subgroup production

constituted 78% of the full food web production before invasion, but only 68% after
invasion. Furthermore, subgroup respiration contributed 42% to the full food web before
invasion, and 51% after invasion.

Ecosystem indices

Similar to the analysis of the full food web, TST and development capacity fell

after zebra mussel invasion. Before invasion, TST and capacity were 1705.2 gC m'2 yr-1
and 7574.4 gC-bits rn'2 yr°l, respectively; after invasion, throughput and capacity

declined to 1415.8 gC rn'2 yr'l (a 17% decrease) and 6651.5 gC-bits m°2 yr'1 (3 12%

decrease), respectively. Unsealed capacity increased after invasion, from 4.4 to 4.7 bits,
a 7% increase. Unlike the full food web ecosystem analysis, relative ascendency
decreased over 3% while relative overhead increased by 1% in the subgroup after
invasion. Relative overhead on imports and exports decreased by 4% and 28%,
respectively, while relative ﬂow redundancies increased by 54% after invasion. These
results parallel the full food web analysis, although the increase in relative ﬂow
redundancies was substantially greater for the subgroup than the full food web (7%
increase). However, unlike the full food web, relative dissipative overhead increased by
4% in the subgroup after invasion. Finally, the subgroup constituted 64% of the full food

web TST and 57% of capacity before invasion, and 66% of TST and 60% of capacity

28

after invasion. Essentially, subgroup size and potential for development increased after
zebra mussel invasion relative to the full food web, making this subgroup a more

important part of the food web.

Discussion

Zebra mussels exerted a far-reaching inﬂuence on the Oneida Lake food web,
altering the membership of food web subgroups (question 1) and changing the magnitude
of carbon ﬂows within the full food web and subgroups (question 2). Our analyses
support the hypothesis that zebra mussels lead to the benthiﬁcation of their invaded
ecosystems by shunting energy from pelagic to benthic pathways and promoting
benthically associated species. Our research constitutes the ﬁrst test of this hypothesis
using ecosystem level measures. Furthermore, this research is the ﬁrst application of CA,
a social network analysis, in conjunction with ENA. Recent unions of methods from
ecology and sociology (e.g., Krause et al. 2003; Zhao and Frank 2003) reveal there is
value found in the convergence of these disciplines, especially when applied to food
webs. While SNA largely focuses on structural analyses (Mayhew 1980), ENA is a
functional analysis (U lanowicz 1986). However, Johnson et al. (2001) afﬁrm that ENA
and SNA are markedly similar mathematically and conceptually. The merging of these
two methods to understand the integration of ecosystem structure and ﬁmction seems a
natural extension. Our application of ENA in combination with CA offers a novel
analytical technique for understanding zebra mussel impacts on ecosystem processes.

We begin our discussion below with CA, and then place the structural ﬁndings within the

29

context of the full food web and subgroup ENA, emphasizing the contribution to our
knowledge of ecosystems.
Cohesion Analysis - Structure

Almost one-third of all taxa changed subgroups after invasion. Although the
difference in subgroup membership between the pre- and post-zebra mussel time stanzas
was not statistically signiﬁcant (despite 33% of all taxa shifting subgroups), we believe
these shifts are ecologically signiﬁcant based on the restructuring of the paths of carbon
ﬂow within subgroups. The zebra mussel subgroup underwent the greatest change,
increasing membership from twenty-four to twenty-nine taxa, including the addition of
zebra mussels as well as multiple ﬁsh and zooplankton. These shifts broadened the once
pelagic-based subgroup by increasing food chain length and creating important links via
benthic pathways. Although this subgroup underwent the greatest change after invasion,
the benthically associated subgroup also increased membership by one ﬁsh group, while
all other subgroups lost members. These subgroup shifts suggest that benthic pathways
gained importance as a result of zebra mussel invasion.

According to food web stability theory, a taxon that is not directly affected by a
disturbance event, such as exotic species invasion, can still be affected via the transfer of
effects over strong interactions (McCann et al. 2005). Within subgroups, the strong
interactions among members can transfer the effect of a disturbance throughout the
subgroup even if not all members are directly affected by the event. Conversely, taxa in
other subgroups will be either weakly impacted or not impacted as the effects must be
transferred through the weak interactions between groups. Thus taxa within the subgroup

invaded by zebra mussels are especially vulnerable to effects of this exotic species,

30

whereas taxa in other subgroups may be more sheltered from effects. Life stages of
walleye and yellow perch comprised a large proportion of the subgroup shifts after zebra
mussel invasion. Common subgroup membership offers structural underpinnings for
zebra mussel inﬂuence on juvenile yellow perch growth rate (Mayer et al. 2000) and
adult walleye abundance (Rutherford et al. 1999). Additionally, due to the tight coupling
of walleye and yellow perch populations in Oneida Lake (Rose et al. 1999), within-
subgroup inﬂuence of zebra mussels on these species can cascade to their corresponding
life stages in other subgroups, despite the buffering that subgroup structure may offer.
After invasion, subadult walleye moved to the subgroup containing piscivore and
invertivore taxa (subgroup 6), including cormorants. Common subgroup membership
gives structural support for Oneida Lake diet studies that suggest cormorants exert strong
predatory pressure on subadult walleye (F omey 1993; VanDeValk et al. 2002; Rudstam
et al. 2004). Since subadult walleye composed one-quarter of cormorant diet by weight
(Appendix 2.2) and cormorant biomass more than quadrupled from the 19808 to the
19908 (Appendix 2.1), we feel it is likely that cormorants, rather than zebra mussels,
inﬂuenced the shift of subadult walleye. However, despite strong cormorant predation
pressure on all life stages of yellow perch and walleye (totaling over two-thirds of
cormorant diet, Appendix 2.2), most life stages were found in benthic pathways after
invasion, despite the inﬂuence of an important pelagic predator.

Structural analyses also lend insight into the fundamental ecological structure of
Oneida Lake. In both time stanzas, one large subgroup dominated food web structure
while multiple smaller subgroups played less signiﬁcant roles. This result differs from

CA ﬁndings on the Chesapeake Bay by Krause et al. (2003) who identiﬁed two

31

subgroups (one benthic, the other pelagic) co-dorninating food web structure. Perhaps
structure differs between the systems because Oneida Lake is a shallow, well-mixed
ecosystem with only brief periods of thermal stratiﬁcation, while the Chesapeake Bay
maintains thermal stratiﬁcation from late spring to early fall (Bidle and Fletcher 1995),
creating distinct structure between the thermal regions. These ﬁndings potentially
suggest that food web structure is, at least in part, related to physical system structure.
Similar to the Chesapeake Bay analysis, bivalve taxa (zebra mussels in Oneida Lake;
clams and oysters in the Chesapeake Bay) shared subgroup membership with their
pelagic prey. The majority of carbon ﬂow in the zebra mussel subgroup originated in
phytoplankton and was immediately routed through zebra mussels, making these mussels
the main ﬂow nexus in the system linking pelagic and benthic pathways. Our study
suggests that this coupling of pelagic and benthic structure is a central inﬂuence of zebra
mussels in Oneida Lake.
Ecological Network Analysis - Function

Aquatic ecosystems worldwide are in the midst of large-scale ecological
alteration. To address ecosystem level change, we need quantiﬁable, objective criteria at
the whole-system level (Westra et al. 2000), especially with the contemporary emphasis
on ecosystem management (Christensen et a1. 1996). ENA is a valuable tool for
deciphering impacts of perturbations at the ecosystem level because it offers a
quantitative depiction of food web functioning, inclusive of all food web taxa (barring
data limitations). Ulanowicz (1996) makes predictions for ecosystem level response to
perturbation by drawing from Odum’s (1969) theory on ecosystem development.

Ulanowicz suggested that perturbed ecosystems will have less efficient trophic chains,

32

decreased system throughput, and decreased food web organization. Our analysis
supports Ulanowicz (1996) and afﬁrms research question 2: zebra mussels considerably
alter the magnitude of carbon ﬂow within ecosystems.

Our IMPACTS analysis suggested that zebra mussels have an overwhelmingly
negative effect on food web taxa, especially subgroup members. This analysis is a
rigorous way to determine perturbation effects since all food web paths, both direct and
indirect, are incorporated in the analysis. Indirect paths are especially important as they
may overwhelm direct interactions and even yield an opposite effect than a direct
exchange (Patten 1984). In our analysis, the majority of large effects were contained in
the zebra mussel subgroup, validating the assumption that subgroup members exert a
stronger inﬂuence over one another than non-subgroup members. The few positively
affected taxa tended to be benthically associated, yet some taxa with benthic life stages,
like yellow perch, exhibited wholly negative impacts. However, when interpreting
results of the IMPACTS analysis, it is important to bear in mind that we only conducted
the analysis using the post-zebra mussel invasion network; changes in species
interactions mediated by zebra mussels may have occurred between the time periods. For
example, if zebra mussel invasion alleviated deleterious feeding pressure of certain
predators on prey present in the pre-invasion time stanza, we might see zebra mussel
facilitation of some taxa upon doing a before and after comparison using other measures
besides IMPACTS. As an example, to reﬁne the IMPACTS analysis, we can consider
the throughput of subadult yellow perch, juvenile yellow perch, and juvenile walleyes
before and after invasion. Although the IMPACTS analysis indicated that zebra mussels

negatively inﬂuenced these life stages, their throughput increased after invasion, perhaps

33

due to changes elsewhere in the food web mediated by zebra mussels. Therefore, to fully
understand zebra mussel inﬂuence on the Oneida Lake food web, the IMPACTS analysis
must be used in conjunction with other functional analyses.

The zebra mussel subgroup is the most important subgroup in Oneida Lake. This
subgroup not only dominated food web structure, but also dominated function by
sequestering carbon ﬂow. After invasion, we found that the trophic chain increased by
three levels and the subgroup garnered more carbon throughput relative to the ﬁrll food
web. Additionally, the development capacity of the subgroup increased compared to the
full food web. These results suggest that this subgroup not only increased in functional
size, but also became a more complex and integrated part of the food web after invasion.
However, despite gaining functional importance, the subgroup contributed proportionally
more to food web ﬂow loss after invasion. Respirative ﬂow losses increased (9%) while
production decreased (almost 10%) relative to the full food web. Thus, not only do we
see evidence of an energy shunt to benthic pathways after zebra mussel invasion, but also
indication of energy ﬂow loss to dissipative paths and decreased food web efﬁciency.

The Lindeman trophic analysis allows further inspection of ﬂow efficiency at
each trophic level within the zebra mussel subgroup. After invasion, ﬂow efﬁciency for
trophic level I increased almost 17%, efﬁciency at trophic level II decreased almost 10%,
and the efﬁciency of the remaining trophic levels marginally changed. The driver of
increased efﬁciency at the ﬁrst trophic level was probably the decrease in phytoplankton
biomass following invasion. With less phytoplankton available for consumption, a
greater proportion of biomass passed into the grazing food chain, with less biomass lost

to detrital pathways. The efﬁciency decrease at the second trophic level was potentially

34

due to the high respirative loss of zebra mussels relative to production (Appendix 2.2). In
light of the subgroup results, we can conjecture trophic efﬁciency in the ﬁrll food web
even though we could not create the Lindeman trophic spine. After invasion,
phytoplankton biomass and throughput decreased, potentially increasing ﬂow efficiency
at trophic level I, as occurred in the subgroup. Although pelagic primary producers
exhibited decreased activity after invasion, other sources of primary production, such as

macrophytes and detritus (considered a primary source of carbon in ENA), gained

functional importance. Before invasion, macrophytes produced 8.0 gC m'2 yr'l,
compared to 9.0 gC m'2 yr'1 after invasion, a 13% increase. Detrital groups combined

produced 11.6 gC rn'2 yr'I before invasion and 65.1 gC m'2 yr'1 after invasion. Despite a

small absolute increase in carbon ﬂow, this change represented an over 460% increase in
detrital use, illustrating the importance of alternate sources of carbon, especially benthic,
after zebra mussel invasion.

Considering the entire food web, Ulanowicz (1996) predicted that that ecosystem
organization, as measured by ascendency, will decrease after a perturbation while
ecosystem disorganization, measured by overhead, will increase. To understand why
system overhead should increase, it is helpful to consider the components of overhead:
dissipative ﬂow loss due to respiration, ﬂow redundancies, imports to, and exports from
the system. Although these processes can be disadvantageous during benign conditions,
overhead can be advantageous if the system is perturbed in a novel fashion. Bondavalli
et al. (2000) described overhead as a “strength in reserve of degrees of freedom which the
system can call upon to adapt to a new threat.” In general, overhead increases after

perturbation due to reorganization of ﬂow structure while the ecosystem adapts. For

35

instance, as an exotic species becomes established in a system, the ecosystem may Shift
from a stable state to a ﬂux system, with concomitant ﬂow reorganization, interruption of
carbon cycling, and even loss of native species.

Considering this ﬂow of events common to exotic species introduction, we were
surprised to observe the full food web relative overhead value decrease after zebra mussel
invasion. Perhaps the food web exhibited increased organization due to the considerable
ﬂow asymmetry present after invasion. Zebra mussels conduct 10% of food web ﬂow,
potentially increasing organization by focusing ﬂow (and increasing AMI). However,
Ulanowicz’s (1996) perturbation theory held for the analysis of the zebra mussel
subgroup, which should contain the most pronounced inﬂuence of zebra mussels in the
food web (according to food web stability theory). Relative ascendency decreased, while
relative overhead increased in the subgroup, suggesting that the subgroup underwent
reorganization of carbon ﬂow as it accommodated zebra mussel presence (as predicted by
Ulanowicz’s theory). This ﬁnding presents compelling evidence for investigating food
web function at multiple structural levels. Despite differences in organization between
the subgroup and full food web, we found that (unsealed) deve10pment capacity increased
at both levels after invasion. The rise in capacity indicates that zebra mussels added a
layer of complexity to food web function. Complexity imparts multiple beneﬁts to
ecosystems, including more diversity of interconnections which allow alternate routes for
taxa to obtain energy in the face of ecological change (Pérez-Espaﬁa and Arreguin-
Sénchez 1999). Consequently, despite eliciting several negative effects on Oneida Lake,
including decreased food web efﬁciency and production, zebra mussel invasion conveyed

some beneﬁts to the ecosystem.

36

A limitation of ENA is variability in carbon ﬂow estimates is not incorporated
into the analysis. As a result, we cannot discern statistical signiﬁcance in food web
change with ENA. One of the main assumptions of ENA is that ecosystems are in a
condition of mass-balance. After constructing a food web network, taxa rarely meet this
assumption, as was the case in this analysis. Balancing introduces a degree of uncertainty
into the analyses, thus careful choice of methods is imperative. We acknowledge that our
balancing routines may have affected our results; however, we were careful to choose
balancing methods that yielded ecologically plausible networks. The other critical
assumption of this research was that any differences observed in food web structure and
function between time stanzas were due to zebra mussel invasion. Although Oneida
Lakes has been buffered from most exotic species introductions that plague the Great
Lakes (e.g., the spiny (Bythotrephes longimanus) and ﬁsh-hook (Cercopagis pengoi)
water ﬂeas, the round goby (Neogobius melanostomus), and quagga mussels), zebra
mussel invasion is not the only ecological change in recent years. For example,
cormorant biomass increased independent of zebra mussel invasion and a lake sturgeon
stocking program began in 1995. Although these events may have caused food web
alteration, we believe that zebra mussel invasion far outweighed other ecological changes
that occurred during our time stanzas. Not only did zebra mussels garner over 10% of

total system ﬂow, they also constituted over two-thirds of Oneida Lake’s living biomass
(gC m'z). These numbers alone suggest that zebra mussel introduction is undoubtedly

one the most signiﬁcant changes to Oneida Lake’s ecology in recent years. Given the
limitations of ENA, but considering the overwhelming presence of zebra mussels in

Oneida Lake, we are conﬁdent in the robustness of our results and conclusions.

37

Moreover, our research corroborates other work conducted on Oneida Lake as well as
supports research on the effects of zebra mussel invasion in other systems.

In conclusion, this research supports the work of Mills et al. (2003) who
hypothesized that zebra mussels lead to the benthiﬁcation and reorganization of their
invaded ecosystems. Our research presents the ﬁrst test of this hypothesis using network
analysis methods. Network analyses are valuable techniques for illuminating exotic
species impacts at the whole-system level while at the same time allowing for inspection
of impacts at the level of species or even life stage. We advocate the use of high
resolution data for all food web taxa, including microbial pathways (Allesina et al. 2005),
to gain a holistic understanding of ecosystem structure and function. As these data were
not all available for Oneida Lake, we acknowledge that our aggregation scheme and
choice of taxa may have affected results. However, our food web networks, with over
seventy taxa and life stages for each time stanza, represent one of the most in-depth
treatises of ENA food webs to date. Furthermore, the conﬂuence of network analyses
from multiple disciplines allowed us to look at ecosystem structure and function item a
new perspective. We suggest network analysis methods be applied to other ecosystems
that have experienced exotic species invasion to determine if the results presented here

are unique to Oneida Lake, or ubiquitous across invaded ecosystems.

Acknowledgements
We thank Stefano Allesina, Tyler Wagner, and Andrew Fayram for helpful
comments, the Bay of Quinte — Oneida Lake Comparative Modelling Project Workgroup,

Edward Mills and the staff at the Cornell University Biological Field Station for data

38

contributions and guidance, Anne Clites, Timothy Hunter, and Marten Koops for their
computational and programming assistance, and Cathy Darnell for her aid on graphics.

This work was supported by a grant from the Great Lakes Fishery Commission.

39

Table 2.1. List of food web taxa. Cisco were present in the pro-zebra mussel time stanza

but not the post-zebra mussel time stanza; lake sturgeon, zebra mussels, and

Camptocercus harpae were present in the post-zebra mussel time stanza, but not the pre-

zebra mussel time stanza.

 

No. Common Name Taxonomic Classiﬁcation No. Common Name Taxonomic Classiﬁcation
1 Cormorants Phalacrocorax auritus 40 lsopods Isopoda
2 Walleye Age 4+ Sander vitreus 41 Lecches Hirudinea
3 Walleye Age 1-3 Sander vitreus 42 Oligochaetes Oligochaeta
4 Walleye Age-0 Sander vitreus 43 Snails Gastropoda
5 Yellow Perch Age 3+ Perca ﬂavescens 44 Zebra Mussels Dreissena polymorpha
6 Yellow Perch Age 1-2 Percaﬂavescens 45 Alona species Alana species
7 Yellow Perch Age-0 Percaﬂavescens 46 Bosmina longirostris Bosmina longirostris
8 White Perch Age 1+ Morone americana 47 C amptocercus harpae Camptocercus harpae
9 White Perch Age-0 Morone americana 48 Ceriodaphnia quadrangula Ceriodaphnia quadrangula
10 Black Crappie Age 1+ Pomoxis nigromaculatus 49 Chydorus sphaericus Chydorus sphaericus
ll Bluegill Age 1+ Lepomis macrochirus 50 Daphnia galeata mendotae Daphnia galeata mendotae
12 Pumpkinsecd Age 1+ Lepomis gibbosus 51 Daphnia pulicaria Daphnia pulicaria
13 Rock Bass Age 1+ Ambloplites rupestris 52 Daphnia retrocurva Daphnia retrocurva
14 Panﬁsh Age-0 Centrarchidae 53 Diaphanosoma species Diaphanosoma species
15 Gizzard Shad Age 1+ Dorosoma cepedianum 54 Eubosmina coregoni Eubosmina coregoni
l6 Gizzard Shad Age-0 Dorosoma cepedianum 55 Sida crystallina Sida crystallina
17 Alewife Alosa pseudoharengus 56 Leptodora kindtii Leptodora kindtii
18 Brown Bullhead Ameiurus nebulosus 57 Acanthocyclops vernalis Acanthocyclops vernalis
l9 Burbot Lota Iota 58 Diacyclops thomasi Diacyclops thomasi
20 Channel Catﬁsh Ictalurus punctatus 59 Ergasilus species Ergasilus species
21 Cisco C oregonus artedii 60 Mesocyclops edax Mesocyclops edax
22 Common Carp Cyprinus carpio carpio 61 Epischura lacustris Epischura lacustris
23 Darters Etheostoma species 62 Leptodiaptomus minutus Leptodiaptomus minutus
24 Emerald Shiners Notropis athernoides 63 Skistodiaptomus Skistodiaptomus
25 Freshwater Drum Aplodinotus grunniens oregonensis oregonensis
26 Golden Shiners Notemigonus crysoleucas 64 Nauplii Copepoda
27 Lake Sturgeon Acipenserfulvescens 65 Rotifers Rotatoria
28 Log Perch Percina caprodes 66 Blue-green Algae Cyanophyceae
29 Mottled Sculpin Cottus bairdii 67 Diatoms Bacillariophyceae
30 Northern Pike Esox Iucr'us 68 Euglena Euglenophyceae
31 Red Horse Sucker Moxisoma species 69 Flagellates Cryptophyceae &
32 Smallmouth Bass Micropterus dolomieu Dinophyceae
33 Trout Perch Percopsis omiscomaycus 70 Golden Algae Chrysophyceae
34 White Bass Morone chrysops 71 Green Algae Chlorophyceae
35 White Sucker Catostomus 72 Epiphytes Epiphytes
commersonii 73 Macrophytes Macrophytcs
36 Amphipods Amphipoda 74 Periphytes Periphytes
37 Chironomids Chironomidae 75 Pelagic Detritus Pelagic Detritus
38 Clams Sphaeriidae 76 Sedimented Detritus Sedimented Detritus
39 Insects Arthropoda 77 DOC DOC

40

Table 2.2. Association between common subgroup membership and the occurrence of

ties between predators and prey (adapted from Frank 1995). The odds ratio method

maximizes the ratio AD : BC.

Different

Subgroup
Membership

Same

Tie Occurring

 

 

 

 

No Yes
Possible relations between
A B predators and prey in different
subgroups
Possible relations between
C D predators and prey in the same
subgroup
Unrealrz ed Realized Total possible relations
Interactions Interactions

 

 

 

41

 

Table 2.3. Ecosystem indices for the full Oneida Lake food web network before and after

zebra mussel invasion. The percent difference was calculated as:

 

 

P t - P
%Difference = _o_s__r£ x100% .
Pre
Pre-Zebra Mussels Post-Zebra Mussels % Difference
Index Value Value
Total system throughput (gC rn'2 yr'l) 2553-3 2143-6 -19.2
Development capacity (gC-bits rn'2 yr'l) 13315-7 1 1037-2 -17.1
Ascendency (gC-bits rn'2 yr'l) 33509 29263 -12.7
Total overhead (gC-bits m'2 yr") 9965.9 8110.9 -18.6
Overhead on imports (gC-bits m'2 yr'l) 2598-4 1373-0 -27.9
Overhead on exports (gC-bits m'2 yr'l) 0-4 0-3 -35.0
Dissipative overhead (gC-bits rn'2 yr'l) 3936-3 3203-3 -18.6
Redundancy (gC-bits 111-2 yr'l) 3430-3 3034-3 -1 1.6
Unsealed capacity (bits) 5.0 5.1 2.0
Ascendency / capacity (%) 25.2 26.5 5.4
Total overhead / capacity (%) 74.8 73.5 -1.8
Overhead on imports / capacity (%) 19.5 17.0 -13.0
Overhead on exports / capacity (%) 0.0 0.0 -21.6
Dissipative overhead / capacity (%) 29.6 29.0 -1 .8
Redundancy / capacity (%) 25.8 27.5 6.7

42

Table 2.4. Subgroups identiﬁed for the pre-zebra mussel invasion time stanza. * Refers

to taxa present in the pre-zebra mussel time stanza, but not the post-zebra mussel time

stanza.

Subgroup l: Planktivorous

 

 

 

 

 

 

No. Food Web No. Subgroup 2 Con't No. Subgroup 4 Con't
16 Gizzard Shad Age-0 8 White Perch Age 1+ 12 Pumpkinseed Age 1+
37 Chironomids 20 Channel Catﬁsh 13 Rock Bass Age 1+
42 Oligochaetes 22 Common Carp 23 Darters
46 Bosmina Iongirostris 25 Freshwater Drum 28 Log Perch
48 Ceriodaphnia quadrangula 35 White Sucker 29 Mottled Sculpin
49 Chydorus sphaericus 36 Amphipods 59 Ergasilus species
50 Daphnia galeata mendotae 39 Insects
51 Daphnia pulicaria 40 lsopods No. Subgroup 5: Piscivores
52 Daphnia retrocurva 41 Leeches . 2 Walleye Age 4+
53 Diaphanosoma species 43 Snails 3 Walleye Age 1-3
54 Eubosmina coregoni 56 Leptodora kindtii 4 Walleye Age-0
58 Diacyclops thomasi 72 Epiphytes 6 Yellow Perch Age 1-2
60 Mesocyclops edax 73 Macrophytes 7 Yellow Perch Age-0
61 Epischura lacustris 74 Periphytes 9 White Perch Age-0
62 Leptodiaptomus minutus 19 Burbot
63 Skistodiaptomus oregonensis Subgroup 3: Planktivores 30 Northern Pike
64 Nauplii No. & Zooplankton 32 Smallmouth Bass
65 Rotifers 17 Alewife 34 White Bass
66 Blue-green Algae 21 *Cisco
67 Diatoms 26 Golden Shiners Subgroup 6: Piscivores &
68 Euglena 33 Trout Perch No. Invertivores
69 Flagellates 45 Alana species 1 Cormorants
70 Golden Algae 55 Sida crystallina 14 Panﬁsh Age-0
71 Green Algae 57 Acanthocyclops vernalis 15 Gizzard Shad Age 1+
18 Brown Bullhead
Subgroup 2: Benthically No. Subgroup 4: Panﬁsh 24 Emerald Shiners
No. Associated 10 Black Crappie Age 1+ 31 Red Horse Sucker
5 Yellow Perch Age 3+ 11 Bluegill Age 1+ 38 Clams

43

Table 2.5. Subgroups identiﬁed for the post-zebra mussel invasion time stanza. * Refers

to taxa present in the post-zebra mussel time stanza, but not the pre-zebra mussel time

stanza. I Refers to taxa that changed subgroup membership after zebra mussel invasion.

Subgroup l: Planktivorous

Subgroup 2: Benthically

 

 

 

No. Food Web No. Associated No. Subgroup4 Con't
2 lWalleye Age 4+ 5 Yellow Perch Age 3+ 19 tBurbot
7 tYellow Perch Age-0 6 lYellow Perch Age 1-2 34 *White Bass
9 lWhite Perch Age-0 8 White Perch Age 1+ 59 Ergasilus species
16 Gizzard Shad Age-0 20 Channel Catﬁsh
24 tEmerald Shiners 22 Common Carp No. Subgroup 5: Piscivores
37 Chironomids 25 Freshwater Drum 4 Walleye Age-0
42 Oligochaetes 32 lSmallmouth Bass 23 TDar'ters
44 *Zebra Mussels 35 White Sucker 29 tMottled Sculpin
46 Bosmina longirostris 36 Amphipods 30 Northern Pike
49 Chydorus sphaericus 39 Insects 33 tTrout Perch
50 Daphnia galeata mendotae 40 lsopods
51 Daphnia pulicarr'a 41 Leeches Subgroup 6: Piscivores &
53 Diaphanosoma species 43 Snails No. Invertivores
54 Eubosmina coregoni 72 Epiphytes 1 Cormorants
56 fLeptodora kindtii 73 Macrophytes 3 lWalleye Age 1-3
57 tAcanthocyclops vernalis 74 Periphytes 10 lBlack Crappie Age 1+

58
60
61
62
63
64
65
66
67
68
69
70
71

Diacyclops thomasi
Mesocyclops edax
Epischura lacustris
Leptodiaptomus minutus
Skistodiaptomus oregonensis
Nauplii

Rotifers

Blue-green Algae
Diatoms

Euglena

Flagellates

Golden Algae

Green Algae

Subgroup 3: Planktivores

, & Zooplankton

 

No.

lPanﬁsh Age-0
Golden Shiners
lLog Perch
tClams

Alana species

Subgroup 4: Panﬁsh

15
18
31

Gizzard Shad Age 1+
Brown Bullhead
Red Horse Sucker

Subgroup 7: Miscellaneous

. Low Biomass

 

 

11
12
13

lBluegill Age 1+
Pumpkinseed Age 1+
Rock Bass Age 1+

44

17
27
47
48

52
55

tAlewife

‘Lake Sturgeon

*Camptocercus harpae

lCeriodaphnia
quadrangula

lDaphnia retrocurva

tSida crystallina

Table 2.6. Throughput of subgroups before and after zebra mussel invasion. Only six
subgroups were identiﬁed before zebra mussel invasion.

Pre-Zebra Mussels Post-Zebra Mussels

 

Throughput Throughput
Subgroup (gC m'2 yr'l) (gC 111-2 YI’J)
1 1705.2 1415.8
2 462.9 452.1
3 0.1 0.0
4 0.1 0.2
5 3.9 0.2
6 0.2 0.5
7 Not Present 0.3

45

Table 2.7. Ecosystem indices for the zebra mussel subgroup before and after zebra

mussel invasion. The percent difference was calculated as:

 

 

%Drﬂerence = M x100% .
Pre
Pre-Zebra Mussels Post-Zebra Mussels % Difference
Index Value Value Value
Total system throughput (gC m'2 yr'l) ”052 ”153 -l7.0
Development capacity (gC-bits rn'2 yr'l) 7574-4 5651-5 -12.2
Ascendency (gC-bits m'2 yr'l) 1347-3 1557-0 -15.2
Total overhead (gC-bits m.2 yr'l) 5726.7 5084.5 -11.2
Overhead on imports (gC-bits m"2 yr'l) 1836-3 1552-4 -15.5
Overhead on exports (gC-bits m.2 yrq) 1410-4 390-8 -36.8
Dissipative overhead (gC-bits m'2 er) 1523-1 1492-5 -8.3
Redundancy (gC-bits m.2 yr'l) 351-9 “43-3 34.8
Unscaled capacity (bits) 4.4 4.7 6.8
Ascendency / capacity (%) 24.4 23.6 -3.4
Total overhead / capacity (%) 75.6 76.4 1.1
Overhead on imports / capacity (%) 24.2 23.3 -3.7
Overhead on exports / capacity (%) 18.6 13.4 -28.1
Dissipative overhead / capacity (%) 21.5 22.4 4.4
Redundancy / capacity (%) 1 1.2 17.3 53.6

46

Figure 2.1. Zebra mussel impacts on the Oneida Lake food web, organized by subgroup.
The scale is relative: impacts above the zero line are positive impacts of zebra mussels
and impacts below the zero line are negative impacts of zebra mussels. Taxa numbers are
placed above or below each bar. Taxon 21 was not present after zebra mussel invasion;

taxa 75-77 were not used in the subgroup analysis. See Table 2.1 for taxa codes.

47

@5835
02

g

o 9:835

w

v anewnsm

m

N uncuwnnm

ﬂ @3835

 

1012de

3 03mm

48

Figure 2.2. Panel A: Crystalized sociogram for the pre-zebra mussel time stanza. Units
are relative distances based on the inverse of the density of interactions (see Frank 1996).
Subgroups 1 through 6 are plotted with the direction of feeding relationships represented
by arrows (e. g., subgroup 6 consumes members of subgroup 1, but not vice versa);
thickness of arrow indicates weight of feeding relationships. Panel B: Placement of taxa
within subgroups. Circles indicate subgroup boundaries and colors represent general
trophic groupings of taxa. Subgroup numbers are located to the upper right of all

subgroups.

49

_ 53585
8. 8. a c

 

 

 

 

 

355 635m I
835393.. B
gins—nooN E
835882: canon B

.3..— U

m 35¢ 8588.80 M

 

 

 

< .28“—

 

 

can-

com-

com.

On.

0
2 "06mm

3

on.

can

own

3 2:5

50

Figure 2.3. Crystalized sociogram for the post-zebra mussel time stanza. See Figure 2.2

for description of panels.

51

_ casein
on _ 8 _ an c on. 8 _ . an _ .

 

8n.

an-

SN.

8..

a o
Z [1018“;le

1.06.6 ._
@§ 3.

  

SN
35: 25.3 I
53338.3.— D
coins—QSN j o2
maﬁa—85>:— uEEom E
E D < ESE md ousmmm

 

 

m ESm 258500 a 8m

 

52

Figure 2.4. Zebra mussel impacts on subgroup members. The scale is relative: impacts
above the zero line are positive impacts of zebra mussels and impacts below the zero line

are negative impacts of zebra mussels.

53

_ asewnsm

 

1012de

em 2&5

54

Figure 2.5. Lindeman trophic spine for the pre-zebra mussel time stanza. Boxes with
Roman numerals represent the integer trophic levels; the number within each trophic box
is the percent efﬁciency of that trophic level at processing material. Arrows between the
trophic boxes are ﬂows in the grazer food chain, arrows leaving the top of trophic boxes
are exports, arrows entering the tOp of trophic boxes are imports, and arrows leaving the
bottom of trophic boxes are ﬂows to detritus, represented by the detrital box. The ground

symbol from electronic circuitry represents ﬂow loss due to respiration. All ﬂows are in

gC rn'2 yr".

55

v.o

:8.»

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

) tr > W H v 3.58
\r
723.. sex? 86 3d and 2: ems 2.2 3.2 8.3 $22 8.3m
4. A. 4. 4. 4| 4.
:86 :52 38a $3.» $8.4m $8.:
_> . > ll. 2 T... E . = A . _
I H 2:. a «H N: A, 4% E: H [F 8 3 a «H 8 3... H 4%
sex: vex: 92x3 ”-256... maxi So no}: «no 22: as 8.2: 3o

nm 2:3

56

Figure 2.6. Lindeman trophic spine for the post-zebra mussel time stanza. See Figure

2.5 for a description of the ﬁgure.

57

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

) or 4 >1 v .238
23 72564 2:. “.2562. rod Q.2522 v25: 62x? 26%
1.. I... -.I P .m 35.
o . I—l a . I—' o . l-I o . I—l BSA—0.5
>25 22 $2 $3 :8;
Toioef on 255.4 _ E> moss; => 255a . 3 mid
ﬂf h- v. m-
2-2%. a 2-2.8 m MW.2582 MW.253 m.25: 62x? 2:. w 23. m
> r .1 i 3.3
i
go 25 23 3o 3; 8.2 :2 8.42 3:: 2:8
320D . - u o n
.22.. w. 4.. 5.. .H. .4.
028: oh 2.23 .33 so: 2%.: 2.8.:
A ., > A >_ E = A . _
:6 82 8.2 22.2 8.2.3
85 :3 2:. a... 25 o; 3% a: 8.43 as

3. 23mm

58

References

Abarca-Arenas, L. G. and R. E. Ulanowicz. 2002. The effects of taxonomic aggregation
on network analysis. Ecol. Model. 149: 285-296.

Allesina, S. and C. Bondavalli. 2003. Steady state of ecosystem ﬂow networks: A
comparison between balancing procedures. Ecol. Model. 154: 221-229.

Allesina, S., C. Bondavalli, and U. M. Scharler. 2005. The consequences of the
aggregation of detritus pools in ecological networks. Ecol. Model. 189: 221-232.

Bailey, R. C., L. Grapentine, T. J. Stewart, T. Schaner, M. E. Chase, J. S. Mitchell, and
R. A. Coulas. 1999. Dreissenidae in Lake Ontario: Impact assessment at the
whole lake and Bay of Quinte spatial scales. J. Great Lakes Res. 25: 482-491.

Baxter, C. V., K. D. Fausch, M. Murakami, and P. L. Chapman. 2004. Fish invasion
restructures stream and forest food webs by interrupting reciprocal prey subsidies.
Ecologi. 85: 2656-2663.

Beekey, M. A., D. J. McCabe, and J. E. Marsden. 2004. Zebra mussel colonization of soft
sediments facilitates invertebrate communities. Fresh. Biol. 49: 535-545.

Bidle, K. D. and M. Fletcher. 1995. Comparison of free-living and particle-associated
bacterial communities in the Chesapeake Bay by stable low-molecular—weight
RNA analysis. Appl. Environ. Microbiol. 61: 944-952.

Bondavalli, C., A. Bodini, G. Rossetti, and S. Allesina. In press. Detecting stress at the
whole ecosystem level. The case of a mountain lake: Lake Santo (Italy).
Ecosystems.

Bondavalli, C., R. E. Ulanowicz, and A. Bodini. 2000. Insights into the processing of
carbon in the South Florida Cypress Wetlands: A whole-ecosystem approach
using network analysis. J. Biogeo. 27: 697-710.

Christensen, N. L., A. M. Bartuska, J. H. Brown, S. Carpenter, C. D'Antonio, R. Francis,
J. F. Franklin, J. A. MacMahon, R. F. Noss, D. J. Parsons, C. H. Peterson, M. G.
Turner, and R. G. Woodmansee. 1996. The report of the Ecological Society of

America Committee on the scientiﬁc basis for ecosystem management. Ecol.
Applic. 6: 665-691.

Christensen, V. and D. Pauly. 1992. ECOPATH II — a soﬁware or balancing steady-state
ecosystem models and calculating network characteristics. Ecol. Model. 61: 169-

185.

Crooks, J. A. 2002. Characterizing ecosystem-level consequences of biological invasions:
The role of ecosystem engineers. OIKOS. 97: 153-166.

59

Dettmers, J. M., M. J. Raffenberg, and A. K. Weis. 2003. Exploring zooplankton changes
in southern Lake Michigan: Implications for yellow perch recruitment. J. Great
Lake Res. 29: 355-364.

Drake, J. M. and J. M. Bossenbroek. 2004. The potential distribution of zebra mussels in
the United States. BioScience. 54: 931-941.

Fayram, A. H., Hansen, M. J ., and T. J. Ehlinger. In press. Characterizing changes in
maturity of lakes resulting from supplementation of walleye populations. Ecol
Model.

F inn, J. T. 1976. Measures of ecosystem structure and function derived from analysis of
ﬂows. J. Theor. Biol. 56: 363-380.

Fomey, J. L. September 1993. Some observations on cormorant-ﬁsh interactions in
Oneida Lake. American Fisheries Society — New York Chapter Newsletter. 8-13.

Frank, K. A. 1995. Identifying cohesive subgroups. Soc. Networks. 17: 27-56.

Frank, K. A. 1996. Mapping interactions within and between cohesive subgroups. Soc.
Networks. 18: 93-119.

Gaedke, U. 1995. A comparison of whole-community and ecosystem approaches
(biomass size distributions, food web analysis, network analysis, simulation
models) to study the structure, function and regulation of pelagic food webs. J.
Plankton Res. 17: 1273-1305.

Harmon, B. 1973. The structure of ecosystems. J. Theor. Biol. 41: 535-546.

Hansen, A.-M. and N. G. Hairston Jr. 1998. Food limitation in a wild cyclopoid copepod
population: Direct and indirect life history responses. Oecologia. 115: 320-330.

Heymans, J. J. and D. Baird. 2000. Network analysis of the northern Benguela ecosystem
by means of NETWRK and ECOPATH. Ecol. Model. 131: 197-119.

Heymans, J. J ., R. E. Ulanowicz, and C. Bondavalli. 2002. Network analysis of the South
Florida Everglades grarninoid marshes and comparison with nearby cypress
ecosystems. Ecol. Model. 149: 5-23.

Hubert, L. 1987. Assignment Methods in Combinatorial Data Analysis. Marcel Dekker.

Idrisi, N., E. L. Mills, L. G. Rudstam, and D. J. Stewart. 2001. Impact of zebra mussels
(Dreissena polymorpha) on the pelagic lower trophic levels of Oneida Lake, New
York. Can. J. Fish. Aquat. Sci. 58: 1430-1441.

Jackson, J. R., A. J. VanDeValk, T. E. Brooking, O. A. vanKeeken, and L. G. Rudstam.

60

2002. Growth and feeding dynamics of lake sturgeon, Acipenserﬁtlvescens, in
Oneida Lake, New York: Results from the ﬁrst ﬁve years of a restoration
program. J. Appl. Ichthyol. 18: 439-443.

Johannsson, O. E., R. Derrnott, D. M. Graham, J. A. Dahl, E. S. Millard, D. D. Myles,
and J. LeBlanc. 2000. Benthic and pelagic secondary production in Lake Erie

after the invasion of Dreissena spp. with implications for ﬁsh production. J. Great
Lake Res. 26: 31-54.

Johnson, J. C., S. P. Borgatti, J. J. Luczkovich, and M. G. Everett. 2001. Network role
analysis in the study of food webs: An application of regular role coloration. J.
Soc. Struct. 2: 1-15.

Jones, C. G., J. H. Lawton, and M. Shachak. 1994. Organisms as ecosystem engineers.
OIKOS. 69: 373-386.

Krause, A. E., K. A. Frank, D. M. Mason, R. E. Ulanowicz, and W. W. Taylor. 2003.
Compartments revealed in food-web structure. Nature. 426: 282-285.

Lindeman, R. L. 1942. The trophic-dynamic aspect of ecology. Ecology. 23: 399-418.

Mack, R. N., D. Simberloff, W. M. Lonsdale, H. Evans, M. Clout, and F. A. Bazzaz.
2000. Biotic invasions: Causes, epidemiology, global consequences, and control.
Ecol. Applic. 10: 689-710.

Marsden, J. E. and M. A. Chotkowski. 2001. Lake trout spawning on artiﬁcial reefs and
the effect of zebra mussels: Fatal attraction? J. Great Lakes Res. 27: 33-43.

Mayer, C. M., A. J. VanDeValk, J. L. Fomey, L. G. Rudstam, and E. L. Mills. 2000.
Response of yellow perch (Percaﬂavescens) in Oneida Lake, New York, to the
establishment of zebra mussels (Dreissena polymorpha). Can. J. Fish. Aquat. Sci.
57: 742-754.

Mayer, C. M., R. A. Keats, L. G. Rudstam, and E. L. Mills. 2002. Scale-dependent
effects of zebra mussels on benthic invertebrates in a large eutrophic lake. J. N.
Am. Benthol. Soc. 21: 616-633.

Mayhew, B. 1980. Structuralism vs. individualism, Part 1: Shadow boxing in the dark.
Social Forces. 59: 335-375.

McCann, K., J. Rasmussen, J. Umbanhowar, and M. Humphries. 2005. Role of space,
time, and variability in food web dynamics. In P. deRuiter, V. Wolters, and J.
Moore [eds.], Dynamic Food Webs: Multispecies Assemblages, Ecosystem
Development and Environmental Change. Academic Press.

McEliece, R. J. 1977. The Theory of Information and Coding. Addison-Wesley.

61

Mellina, E., J. B. Rasmussen, and E. L. Mills. 1995. Impact of zebra mussel (Dreissena
polymorpha) on phosphorus cycling and chlorophyll in lakes. Can. J. Fish.
Aquat.Sci. 52: 2553-2573.

Mills, E. L. and J. L. F omey. 1988. Trophic dynamics and development of freshwater
pelagic food webs, p. 11-30. In S. R. Carpenter [ed.], Complex interactions in lake
communities. Springer.

Mills, E. L., J. L. Fomey, M. D. Clady, and W.R. Schaffner. 1978. Oneida Lake, p. 367-
451. In J. A. Bloomﬁeld [ed.], Lakes of New York. Academic Press.

Mills, E. L., J. M. Casselman, R. Dermott, J. D. Fitzsimons, G. Gal, K. T. Holeck, J. A.
Hoyle, O. E. Johannsson, B. F. Lantry, J. C. Makarewicz, E. S. Millard, I. F.
Munawar, M. Munawar, R. O'Gorman, R. W. Owens, L. G. Rudstam, T. Schaner,
and T. J. Stewart. 2003. Lake Ontario: Food web dynamics in a changing
ecosystem (1970-2000). Can. J. Fish. Aquat. Sci. 60: 471-490.

Moloney, C. L. and J. G. Field. 1991. The size-based dynamics of plankton food webs. I.
A simulation model of carbon and nitrogen ﬂows. J. Plankton Res. 13: 1003-
1038.

Nalepa, T. F ., G. A. Lang, and D. L. Fanslow. 2000. Trends in benthic macroinvertebrate
populations in southern Lake Michigan. Verh. Internat. Verein. Limnol. 27: 2540-
2545.

Odum, E. P. 1969. The strategy of ecosystem development. Science. 164: 262-270.

Pauly, D., V. Christensen, J. Dalsgaard, R. Froese, and F. Torres Jr. 1998. Fishing down
marine food webs. Science. 279: 860-863.

Patten, B. C. 1984. Toward a theory of the quantitative dominance of indirect effects in
ecosystems. Verh. Ges. Okol. 13:271-284.

Patten, B. C., R. W. Bosserman, J. T. Finn, and W. G. Cale. 1976. Propagation of cause
in ecosystems. In B. C. Pannen [ed.], Systems Analysis and Simulation in Ecology,
Vol 4. Academic Press.

Pérez-Espaﬁa, H. and F. Arreguin-Sanchez. 1999. A measure of ecosystem maturity.
Ecol. Model. 199: 79-85.

Pimm, S. L. and J. H. Lawton. 1980. Are food webs divided into compartments? .1. Anim.
Ecol. 49: 879-898.

Pinnegar, J. K., J. L. Blanchard, S. Mackinson, R. D. Scott, and D. E. Duplisea. 2005.

Aggregation and removal of weak-links in food-web models: System stability and
recovery from disturbance. Ecol. Model. 184: 229-248.

62

Pothoven, S. A., T. F. Nalepa, P. J. Schneeberger, and S. B. Brandt. 2001. Changes in
diet and body condition of lake Whiteﬁsh in southern Lake Michigan associated
with changes in benthos. N Amer. J. Fish. Man. 21: 876-883.

Reid, D. F. and M. I. Orlova. 2002. Geological and evolutionary underpinnings for the
success of Ponto-Caspian species invasions in the Baltic Sea and North American
Great Lakes. Can. J. Fish. Aquat. Sci. 59: 1144-1158.

Rose, K. A., E. S. Rutherford, D. S. McDermot, J. L. Fomey, and E. L. Mills. 1999.
Individual based model of yellow perch and walleye populations in Oneida Lake.
Ecol. Monogr. 69: 127-154.

Rudstam, L. G., A. J. VanDeValk, C. M. Adams, J. T. H. Coleman, J. L. Fomey, and M.
E. Richmond. 2004. Cormorant predation and the population dynamics of walleye
and yellow perch in Oneida Lake. Ecol. Applic. 14: 149-163.

Rutherford, B. S., K. A. Rose, E. L. Mills, J. L. Fomey, C. M. Mayer, and L. G. Rudstam.
1999. Individual-based model simulations of a zebra mussel (Dreissena
polymorpha) induced energy shunt on walleye (Stizostedion vitreum) and yellow
perch (Percaﬂavescens) populations in Oneida Lake, New York. Can. J. Fish.
Aquat. Sci. 56: 2148-2160.

Shannon, C. E. 1948. A mathematical theory of communication. Bell System Tech. 27:
379-423.

Stevenson, R. J ., M. L. Bothwell, and R. L. Lowe. 1996. Algal Ecology: Freshwater
Benthic Ecosystems. Academic Press.

Stewart, T. J ., R. E. Lange, S. D. Orsatti, C. P. Schneider, A. Mathers, and M. E. Daniels.
1999. Fish community objective for Lake Ontario. Great Lakes Fishery
Commission Special Publication. 99-1.

Strayer, D. L., K. A. Hattala, and A. W. Kahnle. 2004. Effects of an invasive bivalve
(Dreissena polymorpha) on ﬁsh in the Hudson River estuary. Can. J. Fish. Aquat.
Sci. 61: 924-941.

Strayer, D. L., N. F. Caraco, J. J. Cole, S. Findlay, and M. L Pace. 1999. Transformation
of freshwater ecosystems by bivalves. BioScience. 49:19-27.

Teal, J. M. 1962. Energy ﬂow in the salt marsh ecosystem of Georgia. Ecology. 69: 1647-
1676.

Thorp, J. H. and A. F. Casper. 2003. Importance of biotic interactions in large rivers: An

experiment with planktivorous ﬁsh, dreissenid mussels and zooplankton in the St.
Lawrence River. River Res. Applic. 19: 265-279.

63

Ulanowicz, R. E. 1986. Growth and Development: Ecosystems Phenomenology. Springer
Verlag.

Ulanowicz, R. E. 1996. Trophic flow networks as indicators of ecosystem stress. In G. A.
Polis and K. O. Winemiller [eds], Food Webs: Integration of Patterns and
Dynamics. Chapman and Hall.

Ulanowicz, R. E. 1997. Ecology, The Ascendent Perspective. Columbia University Press.

Ulanowicz, R. E. and J. J. Kay. 1991. A package for the analysis of ecosystem ﬂow
networks. Environ. Soft. 6: 131-142.

Vanderploeg, H. A., T. F. Nalepa, D. J. Jude, E. L. Mills, K. T. Holeck, J. R. Liebig, I.A.
Grigorovich, and H. Ojaveer. 2002. Dispersal and emerging ecological impacts of

Ponto Caspian species in the Laurentian Great Lakes. Can. J. Fish. Aquat. Sci. 59:
1209-1228.

VanDeValk, A. J ., C. M. Adams, L. G. Rudstam, J. L. Fomey, T. E. Brooking, M. A.
Gerken, B. P. Young, and J. T. Hooper. 2002. Comparison of angler and

cormorant harvest of walleye and yellow perch in Oneida Lake, New York.
Trans. Am. Fish. Soc. 131: 27-39.

Werner, E. E. and J. F. Gilliam. 1984. The ontogenetic niche and species interactions in
size structured populations. Annu. Rev. Ecol. Syst. 15: 393-425.

Westra, L., P. Miller, J. R. Karr, W. E. Rees, and R. E. Ulanowicz. 2000. Ecological
integrity and the aims of the Global Integrity Project, p. 19-41. In Pimentel, D., L.
Westra, and R. F. Noss [eds], Ecological Integrity: Integrating Environment,
Conservation, and Health. Island Press.

Yodzis, P. and K. O. Winemiller. 1999. In search of operational trophospecies in a
tropical aquatic food web. Oikos. 87: 327-340.

Zhao, Y. and K. A. Frank. 2003. Factors affecting technology uses in schools: An
ecological perspective. AERJ. 40: 807-840.

Zorach, A. C. and R. E. Ulanowicz. 2003. Quantifying the complexity of ﬂow networks:
How many roles are there? Complexity. 8: 68-76.

64

CHAPTER THREE

Invasive Species Impacts on Ecosystem Structure and Function: A Comparison of the

Bay of Quinte, Canada, and Oneida Lake, USA, Before and After Zebra Mussel Invasion

Andrea L. Jaeger, Doran M. Mason, Ann E. Krause, Kenneth A. Frank, William W.

Taylor, and Scott D. Peacor

Abstract

To understand impacts of exotic species on ecosystem level properties, we
compared food web characteristics of two eutrophic ecosystems - the Bay of Quinte,
Lake Ontario (Canada), and Oneida Lake, New York (USA) - before and after zebra
mussel (Dreissena polymorpha) invasion using ecological network analysis (ENA) and a
social network analysis method, cohesion analysis (CA). ENA quantiﬁes ecosystem
function through an analysis of food web transfers, while CA assesses ecosystem
structure by organizing food web members into subgroups of strongly interacting
predators and prey. These methods detected direct and indirect impacts, changes in ﬂow
efﬁciency, and alterations of food web organization and ecosystem activity resulting from
zebra mussel invasion. In the Bay of Quinte, zebra mussel introduction increased
ecosystem grth (9%), stimulated benthic sources of production (e. g., macrophyte and
detrital production increased over 1000%), and disrupted subgroup group structure.
Previous research on Oneida Lake indicated zebra mussels diminished ecosystem growth

(19%), promoted benthic production (e. g., macrophyte and detrital production increased

65

13% and 460%, respectively), and altered subgroup composition (33%). Together, these
analyses suggested that zebra mussel inﬂuence was similar in ecosystems of comparable
trophic status, and that comparative studies may be useful for the prediction of effects in

other systems.

Introduction

Exotic species invasion is a critical driver of worldwide ecological change (Mills
et al. 1994). Exotic species have altered ecosystems by disrupting food web dynamics
(Chapter 2), biogeochemical cycles (Holeck et al. 2004), modifying habitats (Hall and
Mills 2000), and decreasing native biodiversity (Holeck et al. 2004). Invasive species
can also cause health risks and affect socio-economic systems by damaging agriculture,
commercial and recreational ﬁsheries, and fouling intake and nautical structures (Mills et
al. 1994; Facon et al. 2005). Invasions by dreissenid mussels, including zebra (Dreissena
polymorpha) and quagga (Dreissena bugensis) mussels, have been pervasive in North
America, multiple European nations, and Russia (Drake and Bossenbroek 2004).
Dreissenid mussels pose a considerable threat to aquatic environments, causing dramatic
direct and indirect effects on food webs (N oonburg et al. 2003).

Although dreissenid invasion has led to pronounced changes in aquatic
ecosystems, the severity and scope of impacts has varied between ecosystems. In the
Great Lakes (V anderploeg et al. 2002) and some inland waters of North America
(MacIsaac 1996; Idrisi et al. 2001 ), dreissenid invasion increased water clarity and light
penetration, which diverted energy from pelagic to benthic pathways (MacIsaac 1996;

Mayer et al. 2002; Mills et al. 2003). However, in shallow and/or turbulent ecosystems,

66

such as the Hudson River, Saginaw Bay (Lake Huron), and western Lake Erie,
resuspension of dreissenid pseudofeces via water column mixing resulted in lessened
effects on water clarity (Vanderploeg et al. 2002). Dreissenid invasion decreased
phytoplankton abundance and/or biomass in most ecosystems, including Saginaw Bay
(Nalepa et al. 1999), Green Bay (Lake Michigan) (Padilla et al. 1996), western Lake Erie
(Leach 1993), Oneida Lake (New York) (Idrisi et al. 2001), and the Hudson River
(Strayer et al. 1999); however, changes in phytoplankton resources did not uniformly
affect zooplankton communities in all ecosystems. Zooplankton production and/or
density decreased in Lake Erie, particularly the unstratiﬁed regions (Johannsson et al.
2000), and the Hudson River (Strayer et al. 1999). However, in Oneida Lake, zebra
mussel effects on zooplankton were marginal (Idrisi et al. 2001). Likewise modeling
studies on Green Bay (Padilla et al. 1996) and mesocosm experiments on the St.
Lawrence River (Thorp and Casper 2003) found similar results.

Dreissenid effects on higher trophic levels, including benthic invertebrates and
ﬁsh, were also mixed. Zebra mussel invasion negatively affected unionid clams in the
Great Lakes (Vanderploeg et al. 2002), inland lakes (MacIsaac 1996), and rivers (Strayer
et al. 1999). Non-mollusca benthic invertebrates declined in the Hudson River
subsequent to invasion (Strayer et a1. 1999), while in Lake Erie (Johannsson et al. 2000)
and Saginaw Bay (N alepa et al. 2003), benthic and macroinvertebrate biomass did not
decrease. Moreover, dreissenid inﬂuence on ﬁsh varied by ecosystem. Dreissenid
introduction might have indirectly beneﬁted benthic and littoral ﬁsh in Oneida Lake
(Rutherford et al. 1999; Jackson et al. 2002) and the Hudson River (Strayer et al. 2004);

however in Lake Michigan, dreissenids may have negatively affected ﬁsh through

67

modiﬁcation of spawning habitat (Marsden and Chotkowski 2001). F urtherrnore, young
ﬁsh, which may directly compete with dreissenids for zooplankton food resources, might
have been negatively impacted in Lake Michigan (Dettmers et al. 2003), but showed little
effect in Oneida Lake (Mayer et al. 2000) resultant from dreissenid invasion.

Although these studies indicate dreissenid mussels variably affect aquatic
ecosystems, there may be trends in ecosystem response. Comparative analyses could be
useful for elucidating these commonalities. For example, the effects of dreissenid
invasion may vary with ecosystem morphology, ecosystem size, limiting factors to
primary production, predator diets (Strayer et al. 2004), or along a trophic gradient
(Padilla et al. 1996). Identifying the similarities in invaded ecosystems would aid in not
only predicting which ecosystems might be susceptible to future invasions, but also how
those ecosystems might be affected (Drake and Bossenbroek 2004). To decipher
dreissenid impacts on ecosystems and draw comparisons between systems, we need a
comprehensive understanding of ecosystems, including population and community level
effects. Moreover, we need to incorporate the interrelationship between populations and
communities, i.e., how change at the population level affects the community, which in
turn regulates the population (Gaedke 1995). A major constraint to explicating these
processes both within and among ecosystems is the complexity of food web interactions,
especially indirect food web effects (Strayer et al. 2004).

One tool that is useful for holistically understanding and comparing ecosystems in
the face of environmental problems is network analysis (Gaedke 1995). Network
analysis examines ecosystems at multiple scales, including at the level of species-pair

interaction, trophic level, and whole food web (Heymans et al. 2002) through an analysis

68

of ecosystem structure and function. For network analysis, food webs are depicted as
networks of exchange by quantifying feeding interactions and energy ﬂow (Bondavalli et
al. 2000). Network analysis has been used to compare ecosystem properties before and
after exotic species invasion (Chapter 2), ecosystem dynamics between seasons (Baird
and Ulanowicz 1989; Bondavalli et al. 2000), differences in marine upwelling and
estuarine systems (Baird et al. 1991; Baird and Ulanowicz 1993), and aquatic ecosystems
with and without terrestrial linkages (Heymans et al. 2002). In light of the need to
comprehensively understand the effects of dreissenid invasion, we compared zebra
mussel impacts within and between two invaded ecosystems using network analysis.

The primary objective of this paper was to quantify zebra mussel impacts on
ecosystem structure and function, and to compare these characteristics between
ecosystems of similar trophic status, speciﬁcally by addressing the following questions:

1. Structure: Did zebra mussel invasion alter the membership of food webs and food
web subgroups (deﬁned as clusters of strongly interacting predators and prey) in
the Bay of Quinte, Lake Ontario (Canada) ecosystem?

2. Function: Did the magnitude of carbon ﬂow within food webs and food web
subgroups change as a result of zebra mussel invasion in the Bay of Quinte
ecosystem?

3. Comparison: Do systems of comparable trophic status respond similarly, with
respect to direction and magnitude of change, to zebra mussel invasion?

Using food web network analysis, we hypothesized that the Bay of Quinte would
respond similarly to Oneida Lake, New York (USA), a system of comparable ecology

and trophic status, subsequent to zebra mussel invasion. Previous network analysis

69

examination (Chapter 2) suggested zebra mussel invasion led to the benthiﬁcation (Mills
et al. 2003) of Oneida Lake, i.e., an energy shunt occurred that promoted benthic sources
of production and benthically-associated species. Therefore, we hypothesized that the
Bay of Quinte would undergo benthiﬁcation resultant from zebra mussel invasion, with
concomitant changes in ecosystem structure and function that promoted benthic

communities.

Methods

Study Site

The Bay of Quinte is a narrow, Z-shaped inlet on the northeastern portion of Lake
Ontario (Figure 3.1). The Bay of Quinte has three distinct morphological regions,
commonly referred to as the upper bay, middle bay, and lower bay, totaling
approximately 80 km in length (Diamond et al. 1994) and 257 km2 surface area (Minns
1995). A strong depth and trophic gradient exists in the Bay of Quinte, ranging from a
shallow (mean depth of 3.5 m), eutrophic environment in the upper bay to a deeper (mean
depth of 24.4 m), oligotrophic environment in the lower bay (Ridgway et al. 1990;
Nicholls et al. 2002), which connects the Bay of Quinte to Lake Ontario. The upper bay
is most similar in trophic status and physical characteristics to Oneida Lake (described in
Chapter 2); therefore we used only this region in our analysis. The upper bay has a
surface area of 134 km2 and stratiﬁes brieﬂy during the summer months (Strus and
Hurley 1992). Zebra mussels colonized the bay in 1993-1994, but were not established

until 1995 (N icholls et al. 2002). Because of the long-terrn history of limnological

7O

research on the Bay of Quinte (e. g., Hurley and Christie 1977) and Oneida Lake (e.g.,
Mills et al. 1978), ample data exist throughout the invasion history of zebra mussels to
study their effects within and between these systems.
Network Construction

We constructed weighted food web networks for the Bay of Quinte before and
after zebra mussel invasion and analyzed the networks using ecological network analysis
(ENA) (Ulanowicz 1986) and a social network analysis method, cohesion analysis (CA)
(Frank 1995; Krause et al. 2003; Chapter 2). We deﬁned the years 1978 to 1994 as the
pre-zebra mussel invasion time stanza and the years 1995 to 2002 as the post-invasion
time stanza. We created these networks using the same methodology as for Oneida Lake
(Chapter 2) and therefore, do not present details on network construction here. To make
the Bay of Quinte analysis comparable to Oneida Lake, we did not include the microbial
food web. The complete list of eighty food web species and aggregate groups are
presented in Table 3.1. Data used to create network ﬂows (i.e., the exchange matrix)
were collected from the primary literature, ﬁeld studies, and expert researchers on the
Bay of Quinte (including the Bay of Quinte - Oneida Lake Comparative Modelling
Project Workgroup). These parameters along with their sources are listed in Appendix
3.1. Finally, we mass-balanced our networks such that inputs equaled outputs for all taxa
(Heymans and Baird 2000). Appendix 3.2 presents the balanced networks.

Ecological Network Analysis

After we completed network construction, we analyzed Bay of Quinte ecosystem

structure (via CA) and function (via ENA) before and after zebra mussel invasion. We

used the software package EcoNetwrk (http://www.glerl.noaa.gov/EcoNetwrk/) to

71

conduct three ENA routines: 1) input / output analysis, 2) trophic level analysis, and 3)
the calculation of ecosystem indices. We provide a brief description of ENA methods
below; for greater detail see Ulanowicz (1986) and Ulanowicz (1997).

Input / output analysis (Harmon 1973; Patten et al. 1976) quantiﬁes the amount of
carbon supplied to any one taxon by another taxon over all direct and indirect linkages.
The analysis includes a routine called IMPACTS that quantiﬁes the relative effect of one
taxon on another via direct and indirect paths (Heymans and Baird 2000).

Trophic analysis reinterprets the web of predator-prey transfers in terms of the
Lindeman trophic chain concept (Lindeman 1942). Trophic analysis apportions the
activities of omnivores among a series of hypothetical integer trophic levels to create the
Lindeman spine, which is used to evaluate the efﬁciency of carbon ﬂow in the system
(Heymans and Baird 2000).

Ecosystem indices quantify system level properties such as growth and
development, and assess the vulnerability and resilience of an ecosystem to perturbation
(U lanowicz 1997). These indices are: total system throughput (TST), ascendency (A),
overhead (0), and development capacity (C). TST quantiﬁes ecosystem size (and
thereby growth) as the sum of all carbon ﬂows (gC m'2 yr'l) in the system. Ascendency
quantiﬁes the growth, development, and efﬁciency of ecosystem function (U lanowicz
1986) and is calculated by sealing the average mutual information (AMI) index (Shannon
1948; McEliece 1977), a measure of network organization, with TST: A = TST x AMI .
Overhead quantiﬁes the system’s functional inefﬁciencies (Heymans et al. 2002) as well
as the resiliency of a system to perturbation (Heymans and Baird 2000). There are four

primary contributors to overhead: imports (e.g., immigrations) and exports (e. g.,

72

emigrations and ﬁsheries harvest), respirative ﬂow loss, and redundant food web ﬂows
(i.e., multiple ﬂow paths connecting taxa). Overhead is calculated by scaling the
system’s conditional entropy (Ulanowicz 1986), a measure of network disorganization,

by TST: 0 = TST x Conditional Entropy. Development capacity is the upper bound on

ecosystem grth and development. Capacity subsumes both ascendency and overhead:
C=A+0.
Cohesion Analysis

Cohesion analysis identiﬁes subgroups in food webs based on strengths of feeding
relationships (Krause et al. 2003), where the maximization of an odds ratio is used as a
criterion to assign subgroup membership3. CA uses an algorithm to iteratively reassign
taxa to subgroups to maximize the odds that strong predatory interactions occur within
subgroups, versus between subgroups (Frank 1996). The intent of CA is to determine the
network structure that maximizes (strong) predator-prey interactions (realized
interactions) within subgroups while minimizing predator-prey interactions between
subgroups and taxa without connecting ﬂows (unrealized interactions) within subgroups
(Table 3.2).

Using the software Kliqueﬁnder (Frank 1995), we identiﬁed subgroups within the
Bay of Quinte food web networks. We tested the statistical signiﬁcance of our subgroups
against 1000 randomly generated re-combinations of our data (Frank 1996) and inspected
the structure of signiﬁcant subgroups. Although our ENA required balanced networks,
our CA did not. In order to avoid introducing uncertainty from ENA balancing

procedures, we used the unbalanced networks for CA. As a result, we could not include

 

3 Our use of the term “subgroup” is analogous to the Pimm and Lawton (1980) deﬁnition of food web
“compartment”. We use the term “subgroup” to avoid confusion between Pimm and Lawton (1980) and
Ulanowicz (1986) uses of the term “compartment”.

73

detrital groups in our CA because we derived detrital diet via balancing. Furthermore,
our CA required us to adjust the network data to meet the range of Kliqueﬁnder.
Kliqueﬁnder accepts ﬂow weights only within 5 orders of magnitude; our networks
exceeded this range both before (by 8 orders) and after (by 9 orders) invasion. We
encountered this problem in our Oneida Lake analysis and used the same method as

presented in Chapter 2 to adjust data. The ﬁnal adjustment scheme increased values less

than 1.0x10'6 gC m'2 yr"l to the minimum Kliqueﬁnder input, and values greater than 1.0

gC m'2 yr'l to the maximum Kliqueﬁnder input both pre- and post-zebra mussel invasion.

We summarized results of the CA as “crystallized sociograms” using
multidimensional scaling (Frank 1996) in SAS System for Windows. In these diagrams,
proximity of subgroups corresponds to: l) the strength of predator-prey relationships
spanning the subgroups (i.e., closely-spaced subgroups are connected by relatively
stronger interactions than distant subgroups); 2) the similarity of connections to other
subgroups; and 3) the subgroup’s importance to overall food web structure (i.e., centrally
located subgroups are more important to food web structure than peripherally located
subgroups). Similarly, taxa location within a subgroup indicates the strength of
connections between taxa and the importance of taxa to the subgroup.

After we identiﬁed network subgroups, we performed ENA on the largest
subgroup to evaluate ﬁinctional linkages. We maintained the same mass-balance in the
subgroup analysis as the full food web by treating all ﬂows to and from non-subgroup
taxa as imports and exports to the subgroup. Because detrital groups were not assigned to

subgroups, detritus could not be explicitly incorporated into the subgroup ENA.

74

Nevertheless, ﬂow to detritus was implicitly included by treating detrital ﬂow as an

export from the subgroup.

Results
Ecological Network Analysis - Entire Network

Input / output analysis

Zebra mussel impacts on the Bay of Quinte food web were predominantly
negative (Figure 3.2). Cormorants were positively affected, while effects on ﬁsh were
mixed. Benthic ﬁsh (e. g., ictalurids, carp and freshwater drum) and benthically
associated ﬁsh (e. g., adult panﬁsh) exhibited positive impacts, while pelagic ﬁsh (e.g.,
white perch, alewife and shiners) and some sportﬁsh (e. g., walleye and smallmouth bass)
were negatively affected. Round gobies showed the greatest positive impacts throughout
the entire food web. Effects on benthic invertebrate taxa were equally positive and
negative, with zebra mussels strongly negatively impacting themselves. Effects on
zooplankton and phytoplankton taxa were wholly negative and benthic plants were
marginally affected. Finally, zebra mussels positively inﬂuenced sedimented detritus,
while negatively inﬂuencing other detrital groups.
Lindeman trophic analysis

We were unable to conduct the Lindeman trophic analysis on the full food webs
due to computational limitations in the EcoNetwrk software resulting from network
complexity. However, despite limitations in our trophic analysis, we could nonetheless

analyze total food web ﬂow efﬁciency. Total production (i.e., ﬂow between predators

and prey plus the usable exports from the system) was 425.3 gC m"2 yr'l before zebra

75

mussel invasion and 624.3 gC m'2 yr'1 after, a 47% increase. Total ﬂow loss due to
respiration was 534.1 gC m'2 yr'l pre-invasion, and 510.9 gC m'2 yr.1 after invasion, a
4% decrease.
Ecosystem indices

The ecosystem analysis indicated that zebra mussel invasion caused moderate-to-
strong changes to ecosystem function (Table 3.3, Panel A). TST (i.e., ecosystem growth)
increased 10%, as did development capacity (i.e., ecosystem complexity) by 11%.
Concomitantly, ascendency (i.e., organization) increased (47%) while overhead (i.e.,
disorganization) decreased slightly (1%). In part, changes in capacity, ascendency, and
overhead were driven by increases in TST. To remove the eﬁects of TST scaling on
capacity, we simply divided capacity by TST. Unsealed capacity increased from 4.4 to
4.5 bits (2% increase). To remove TST scaling on ascendency and overhead, and look at
the proportion of organized ﬂow relative to disorganized ﬂow in the ecosystem, we
divided ascendency and overhead by development capacity, yielding “relative
ascendency” and “relative overhead”, respectively. Relative ascendency increased from
25% to 33% following zebra mussel invasion, while relative overhead decreased from
75% to 67%. Finally, considering the contributors to relative overhead, overhead on
imports, exports, and dissipative overhead decreased between 10 and 28%, while
redundancy increased 9%.

Cohesion Analysis

We identiﬁed six subgroups in the pre-invasion network and eight subgroups in

the post-invasion network. Even though the odds ratio was greater post-invasion (odds

ratio = 14.6) than pre-invasion (odds ratio = 12.7), the pre-invasion subgroups were

76

borderline statistically signiﬁcant (p < 0.07) and post-invasion subgroups were clearly not
statistically signiﬁcant (p > 0.5) (see Appendix 3.3 for a discussion of these results).
Therefore, only results for the pre-invasion network (Table 3.4) are described below. We
identiﬁed three mixed taxa groups: 1) a planktivorous food web group; 2) benthically
associated taxa; and 3) panﬁsh and zooplankton“. The remaining subgroups were largely
composed of piscivorous and invertivorous ﬁsh taxa. Interactions between (Panel A) and
within (Panel B) subgroups were summarized in a crystallized sociogram (Figure 3.3).
The planktivorous food web subgroup (subgroup l) was fundamental to Bay of Quinte
structure, sharing close interactions with all subgroups. Zooplankton and phytoplankton
were central to this subgroup and interactions were closely knit. The remaining
subgroups illustrated less dense interactions and more peripheral roles in the food web.
Ecological Network Analysis — Grouped Network

Since the post-invasion subgroups were non-signiﬁcant, we could not conduct the
input/output analysis at the subgroup level. Below we analyze the functional
characteristics of the planktivorous food web subgroup (pre-invasion) with the remaining
ENA methods. This subgroup dominated ecosystem structure (in terms of number of
taxa) and size (as quantiﬁed by TST) (Table 3.3, Panel B).
Lindeman trophic analysis

The Lindeman trophic analysis identiﬁed twelve trophic levels in the
planktivorous food web subgroup (Figure 3.4). Adult yellow perch, subadult, and
juvenile walleye were the top predators in this subgroup. Flow in the grazer chain

decreased substantially as trophic level increased, as did ﬂow to detritus and ﬂow loss

 

‘ Subgroup names were based on ecological descriptions that represent the majority of taxa in each
subgroup, but some taxa may not ﬁt the subgroup name.

77

due to respiration. Efﬁciency was greatest at trophic level II (21%), similar for trophic

levels I and 111 (5-6%), and lowest for all trophic levels IV and above. Total production

of the subgroup was 414.7 gC rn'2 yr'1 (97% of full food web) while total respiration was

198.3 gC m'2 yr'1 (37% of full food web).

Ecosystem indices
Similar to the full food web analysis, the planktivorous food web subgroup was

largely composed of disorganized ﬂow (Table 3.3, Panel C). Subgroup throughput
amounted to 1192.4 gC m'2 yr'l, constituting 52% of total food web ﬂow. Ascendency

represented 32% of development capacity, while overhead composed 68% of capacity.
Relative overhead on imports and dissipative ﬂow ranged between 18 and 23%, similar to
the full food web. However, relative overhead on exports (21%) was greater in the

subgroup; whereas relative overhead on redundant ﬂows (7%) was less in the subgroup.

Discussion

Exotic species invasion is a pervasive threat to aquatic ecosystems. As the rate of
invasions escalates (Holeck et al. 2004), it is essential that researchers understand
ecosystem response to invasion in order to successfully forecast and prevent further
spread (Drake and Bossenbroek 2004). In this study, we investigated exotic species
perturbation on the Bay of Quinte food web. Our analysis indicated that zebra mussels
exerted considerable inﬂuence in the Bay of Quinte by not only altering ecosystem
structure (question 1), but also affecting ecosystem function (question 2). Moreover, our
analyses supported the hypothesis that zebra mussels lead to the benthiﬁcation of their

invaded ecosystems. Below we begin our discussion with the CA structural ﬁndings, and

78

then place those results within the ENA functional context. Furthermore, we compare
(question 3) zebra mussel effects in the Bay of Quinte to previous research on Oneida
Lake (Chapter 2).

Cohesion Analysis — Structure

Structural effects of zebra mussel invasion on the Bay of Quinte were
pronounced, as evidenced by a complete disruption of food web subgroup structure.
Before invasion, the planktivorous food web subgroup - a primarily pelagic subgroup -
dominated structure. The centrality of this subgroup (Figure 3.3) parallels ﬁndings on
Oneida Lake where we identiﬁed a planktivorous subgroup constituting the majority of
structure. The prominence of these subgroups makes intuitive sense as both systems
were eutrophic and largely comprised of pelagic pathways before invasion. In Oneida
Lake, zebra mussels established in the planktivorous subgroup, linking this subgroup to
the benthos. However, in the Bay of Quinte, zebra mussel introduction entirely removed
subgroup structure. In effect, zebra mussel invasion homogenized the structure of Bay of
Quinte food web interactions.

Our method of subgroup identiﬁcation concentrated strong predator-prey
interactions within subgroups, leaving only weak interactions between subgroups.
According to food web stability theory, strong interactions can propagate the effects of a
disturbance event. In this manner, perturbations can greatly affect subgroup members,
but may not affect taxa in other subgroups which are connected through weak ties. In a
sense, subgroup structure provides a buffering effect against ecosystem perturbation
(Krause et al. 2003). In Oneida Lake, we found that the greatest effects of zebra mussel

invasion were restricted to taxa within the planktivorous subgroup, corroborating the

79

subgroup buffering effect. Conversely, as described above, zebra mussel invasion
overwhelmed subgroup structure in the Bay of Quinte. This result has two implications:
1) the effects of zebra mussel invasion must have been more severe in the Bay of Quinte
than Oneida Lake to have overcome the buffering effect of subgroup structure; and 2)
zebra mussel inﬂuence can be more expansive in the Bay of Quinte without the conﬁnes
of subgroup structure.
Ecological Network Analysis - Function

The IMPACTS analysis is a rigorous method to determine perturbation effects
over all food web paths, including direct and indirect routes. Indirect paths are especially
important as the net indirect effect may overwhelm direct interactions (Patten 1984). Our
IMPACTS analysis indicated parallel food web response to zebra mussel invasion in the
Bay of 'Quinte and Oneida Lake. The Bay of Quinte analysis suggested that zebra
mussels had largely negative effects on food web taxa, yet zebra mussels positively
affected some taxa, especially ﬁsh. In both the Bay of Quinte and Oneida Lake, benthic
ﬁsh and panﬁsh garnered positive impacts, although these effects were more pronounced
in the Bay of Quinte. Potentially inﬂuence was greater in the Bay of Quinte due to the
disruption of subgroup structure and the associated loss of subgroup buffering effects
resultant from zebra mussel invasion. Walleye, which declined during the 19903 in both
systems, showed negative effects for all life stages in both analyses. In Oneida Lake, the
decline of walleye may be partially attributable to double-crested cormorant predation
(Rudstam et al. 2004); however, cormorant predation pressure on walleye is not as
intense in the Bay of Quinte (Hoyle, J. A. pers. comm.; Appendix 3.2). Therefore,

declines in walleye abundance may be more ascribable to zebra mussel inﬂuence in the

80

Bay of Quinte than Oneida Lake, although commercial and recreational ﬁsheries may
also have contributed to declines of walleye in the Bay of Quinte (Appendix 3.2). The
strongest positive impact in the Bay of Quinte belonged to round gobies, a recent Ponto-
Caspian invader not present in Oneida Lake. Our Bay of Quinte research corroborates a
facilitative interaction between zebra mussels and round gobies (Simberloff and Von
Holle 1999; Ricciardi 2001), and suggests that Oneida Lake may be susceptible to round
goby establishment due its similarity in ﬁsh community response to zebra mussel
invasion. Considering the lower trophic levels, benthic invertebrate (mixed impacts),
zooplankton (all negative impacts), and phytoplankton (all negative impacts) taxa
exhibited similar response to invasion in both systems.

Changes in trophic ﬂow efﬁciency were similar in both systems, with the
exception of production. Production increased in the Bay of Quinte (47%) aﬁer invasion,
and decreased in Oneida Lake (5%). The increase in Bay of Quinte production was

largely due to greater primary production in benthic pathways, providing evidence for

benthiﬁcation. Macrophyte production increased from 2.9 to 33.4 gC rn'2 yr.1 (1048%

increase), while detrital production increased from 4.5 to 70.2 gC rn'2 yr'] (1462%

increase). Oneida Lake macrophyte and detrital production also increased (13% and
460%, respectively) but the growth of benthic production was offset by a decrease in
pelagic production. Respiration decreased in both the Bay of Quinte (4%) and Oneida
Lake (23%) after invasion. Moreover, trophic chains for the planktivorous food web
subgroup were similar in both systems pre-invasion. Although the trophic spine for the
Bay of Quinte (12 levels) was longer than Oneida Lake (6 levels), ﬂow efﬁciency by

trophic level decreased with increased trophic level in both systems, and was greatest at

81

trophic level II (21 % - Bay of Quinte; 24% - Oneida Lake). All ﬂows were substantially
greater at trophic level 1, indicating the importance of lower trophic levels to these
systems.

Drawing from Odtun’s (1969) theory of ecosystem development, Ulanowicz
(1996) made predictions for ecosystem level response to perturbation. Ulanowicz
suggested that perturbed ecosystems would exhibit decreased system throughput and
decreased food web organization (i.e., increased overhead) due to an interruption of the
ecological processes that Optimize efﬁcient functioning. For example, redundant food
web ﬂows, a substantial contributor to overhead, would increase after perturbation as an
ecosystem response to maintain food web connectance. Moreover, frequently perturbed
systems will adapt to harbor greater overhead values (Ulanowicz 1997). In this sense,
overhead is a “strength in reserve of degrees of freedom which the system can call upon
to adapt to a new threat” (Bondavalli et al. 2000).

Our analysis indicated that zebra mussel invasion perturbed the Bay of Quinte in a
different manner than predicted by Ulanowicz (1996). Contrary to theory, total system
throughput and ascendency increased after invasion. We attribute the difference in
perturbation response to the overwhelming presence of zebra mussels in the Bay of
Quinte. Zebra mussels garnered over 15% of TST and comprised 89% of living biomass.
Perhaps the food web exhibited increased organization due to this considerable ﬂow
asymmetry: focused ﬂow through zebra mussels would increase AMI, which in turn
increases ascendency. Ecosystem organization responded similarly in Oneida Lake
where zebra mussels also dominated ﬂow (10% of TST) and living biomass (67%).

Moreover, both systems were predominantly comprised of disorganized ﬂow (66-75%),

82

potentially indicative of frequent perturbation, such as exotic species invasion (Prout et
al. 1990) and changes in nutrient loading (Mills et al. 2003). Finally, zebra mussel
invasion increased development capacity in both systems, adding a layer of functional
complexity. Complexity beneﬁts ecosystems by promoting ﬂow diversity, which can
buffer future ecological change (Pérez-Espafia and Arreguin-Sanchez 1999) in these
systems.

A limitation of ENA is that variability in carbon ﬂow estimates is not
incorporated into the analysis. Therefore, we could not discern statistical signiﬁcance in
our ENA ﬁndings. Additionally, one of the primary assumptions of ENA is that the food
web is mass-balanced. As aquatic ecosystems are dynamic in space and time, this
assumption is rarely met. Balancing introduces a degree of uncertainty into ENA, which
makes careful choice of balancing methods and inspection of results for ecological
plausibility essential. The ﬁnal critical assumption of this research was that differences
in food web structure and function between the time stanzas were attributable to zebra
mussel invasion. Round gobies and Cercopagis pengoi also invaded the Bay of Quinte
during our time periods, and cormorant biomass increased substantially. Although these
changes may have altered food web structure and ﬁmction, we believe zebra mussel
introduction far outweighs all other ecological change during our time periods, as
evidenced by the dominance of zebra mussel ﬂow and biomass. Therefore, we are
conﬁdent in the robustness of our results.

In conclusion, zebra mussel invasion exerted a far-reaching inﬂuence on the Bay
of Quinte ecosystem. Although whole-system analysis is a formidable task due to the

complexity of ecosystem structure and function and paucity of long-term data in many

83

systems (Gaedke 1995), the extensive history of data collection by Bay of Quinte
researchers and our application of network analysis methods allowed us to decipher zebra
mussel impacts at the ecosystem level. Zebra mussel introduction not only caused
substantial changes to food web subgroup structure, but also altered food web function by
shunting energy from pelagic to benthic pathways. Moreover, zebra mussel effects were
similar in Oneida Lake, a system of comparable trophic status. These ﬁndings have
implications for the prediction of zebra mussel effects in other systems, making network
analysis comparisons across invaded ecosystems a valuable endeavor. As exotic species
invasion becomes an ever-increasing threat to aquatic ecosystems worldwide,

understanding ecosystem dynamics is of paramount importance.

Acknowledgements

We thank the Bay of Quinte — Oneida Lake Comparative Modelling Project
Workgroup for data contributions and guidance, Anne Clites, Timothy Hunter, and
Marten Koops for computational and programming assistance, and Cathy Darnell for aid
on graphics. This work was supported by a grant from the Great Lakes Fishery

Commission.

84

Table 3.1. List of food web taxa. Brook silverside, emerald shiners, largemouth bass,

round gobies, zebra mussels, and Cercopagis pengoi, were present in the post-zebra

mussel time stanza, but not the pre-zebra mussel time stanza.

No Common Name
Cormorants

Walleye Age 4+
Walleye Age 1-3
Walleye Age-0
Yellow Perch Age 1+
Yellow Perch Age-0
White Perch Age 1+
White Perch Age-0

9 Black Crappie 1+

10 Bluegill Age 1+

11 Lepomis species Age 1+
12 Pumpkinseed Age 1+
13 Rock Bass Age 1+
14 Sunﬁsh family Age 1+
15 Panfish Age-0

16 Alewife

17 American Eel

18 Brook Silverside

19 Brown Bullhead

20 Channel Catfish

21 Common Carp

22 Emerald Shiner

23 Freshwater Drum

24 Gizzard Shad

25 Johnny Darter

26 Largemouth Bass

27 Log Perch

28 Longnose Gar

29 Northern Pike

30 Round Goby

“qa‘MdKWNu—I

31 Smallmouth Bass
32 Spottail Shiner
33 Trout-perch

34 White Bass

35 White Sucker

36 Amphipods
37 Chironomids
38 Clams

39 Crayﬁsh

40 Insects

Taxonomic Classiﬁcation
Phalacrocarax auritus
Sander vitreus

Sander vitreus

Sander vitreus

Perca ﬂavescens
Perca ﬂavescens
Morone americana
Morone americana
Pomaxis nigramaculatus
Lepomis macrachirus
Lepomis genus
Lepomis gibbosus
Amblaplites rupestris
Centrarchidae family
Centrarchidae family
Alosa pseudaharengus
Anguilla rostrata
Labidesthes sicculus
Ameiurus nebulasus
lctalurus punctatus

C yprinus carpio carpio
Notropis athernaides
Apladinatus grunniens
Dorosoma cepedianum
Etheostoma nigrum
Micropterus salmaides
Percina caprodes
Lepisasteus osseus
Esax lucius

Neogobius
melanostomus
Micropterus dolomieu
Notropis hudsanius
Percopsis omiscomaycus
Morone chrysops

C atastamus
commersonii
Amphipoda order
Chironomidae family
Sphaeriidae family
Orconectes species
Arthropoda phylum

No Common Name
41 lsopods
42 Leeches
43 Oligochaetes
44 Snails
45 Zebra Mussels
46 Alana species
47 Basmina langirastris
48 Ceriadaphnia species
49 Chydoridae family
50 Daphnia

galeata mendotae
51 Daphnia pulicaria
52 Daphnia retrocurva
53 Eubasmina caregani
54 Sididae family

55 Large-bodied Cladocerans

56 Cercopagis pengoi

57 Leptodora kindtii

58 Acanthacyclaps vernalis
59 Diacyclops thomasi

60 Eucyclaps species

61 Mesocyclops species
62 Trapocyclaps extensus
63 Cyclopoida copepodites
64 Diaptomidae family

65 Temoridae family

66 Calanoida copepodites
67 Harpacticoida

68 Nauplii

69 Rotifers

70 Blue-green Algae

7| Diatoms

72 Flagellates

73 Golden Algae

74 Green Algae

75 Epiphytes

76 Macrophytes

77 Periphytes

78 Pelagic Detritus

79 Sedimented Detritus
80 DOC

85

Taxonomic Classification
Isopoda order
Hirudinea class
Oligochaeta class
Gastropoda class
Dreissena palymarpha
Alana species
Basmina langirastris
C eriadaphnia species
Chydoridae family
Daphnia

galeata mendotae
Daphnia pulicaria
Daphnia retrocurva
Eubasmina coregani
Sididae family
Large-bodied Cladocerans
C ercapagis pengoi
Leptodora kindtii
Acanthacyclaps vernalis
Diacyclops thomasi
Eucyclops species
Mesocyclops species
Trapacyclaps extensus
Cyclopoida copepodites
Diaptomidae family
Temoridae family
Calanoida copepodites
Harpacticoida

Nauplii

Rotifers
Cyanophyceae
Bacillariophyceae
Cryptophyceae &
Dinophyceae
Chrysophyceae
Chlorophyceae
Epiphytes
Macrophytes
Periphytes

Pelagic Detritus
Sedimented Detritus
DOC

Table 3.2. Association between common subgroup membership and the occurrence of
ties between predators and prey (adapted from Frank 1995). The odds ratio method
maximizes the ratio AD : BC.

Tie Occurring

 

 

No Yes
Possible relations between
Different A B predators and prey in different
Subgroup subgroups
Membership Possible relations between
Same C D predators and prey in the same

subgroup

 

Unrealized Realized

. . Total ossible relations
Interactions Interactions p

 

 

 

 

 

86

Table 3.3. Ecosystem indices for the full food web (Panel A), subgroup throughput
(Panel B), and ecosystem indices for subgroup 1 (Panel C). The percent difference was

calculated as: %Diﬂerence = Mx100% .

re

Panel A: Full Food Web Pre-Zebra Mussels Post-Zebra Mussels % Difference

 

 

 

 

 

Index Value Value Value
Total system throughput (gC m'2 yr'l) 2304.2 2505.4 8.7
Development capacity (gC-bits m.2 yr-l) 10160.5 112812 11.0
Ascendency (gC-bits m.2 yr'l) 2541-1 3726.8 46.7
Total overhead (gC-bits m‘2 yr") 7619.3 7554.4 -o.9
Overhead on imports (gC-bits rn'2 yr'l) 2594.2 2591.3 -0.1
Overhead on exports (gC-bits rn'2 yr!) 893.7 711-7 -20.4
Dissipative overhead (gC-bits rn'2 yr'l) 2096-5 1787-7 -14.7
Redundancy (gC-bits m'z yr") 2034.9 2463.7 21.1
Unsealed capacity (bits) 4.4 4.5 2.1
Ascendency / capacity (%) 25.0 33.0 32.1
Total overhead / capacity (%) 75.0 67.0 -10.7
Overhead on imports / capacity (%) 25.5 23.0 -10.0
Overhead on exports / capacity (%) 8.8 6.3 -28.3
Dissipative overhead / capacity (%) 20.6 15.8 -23.2
Redundancy / capacity (%) 20.0 21.8 9.0
Panel B: Subgroup TST Panel C: Subgroup 1 Indices Pre-Zebra Mussels

TST (gC m.2 yr'l) Index Value

31113819111? 1 1 192.4 Development capacity (gC-bits m.2 yr'l) 4041.3
SUbSTOUP 2 16.45 Ascendency (gC-bits m.2 yr'l) 1282-1
311138701113 3 0.20 Total overhead (gC-bits m.2 yr'1) 2759.2
SUbgTOUP 4 0.03 Overhead on imports (gC-bits m.2 er) 914.1
Subgroup 5 0.08 Overhead on exports (gC-bits m.2 yr'l) 83 8.8
Subgroup 6 0.06 Dissipative overhead (gC-bits rn'2 er) 727.2
Redundancy (gC-bits m.2 yr!) 2792
Unsealed capacity (bits) 3.4
Ascendency / capacity (%) 31.7
Total overhead / capacity (%) 68.3
Overhead on imports / capacity (%) 22.6
Overhead on exports / capacity (%) 20.8
Dissipative overhead / capacity (%) 18.0
Redundancy / capacity (%) 6.9

87

Table 3.4. Subgroups identiﬁed for the pre-zebra mussel invasion time stanza.

Subgroup 1: Planktivorous
No. Food Web

3 Walleye Age 1-3

4 Walleye Age-0

5 Yellow Perch Age 1+

7 White Perch Age 1+

8 White Perch Age-0
16 Alewife
24 Gizzard Shad
36 Amphipods
37 Chironomids
38 Clams
40 Insects
47 Basmina langirastris
48 Ceriodaphnia species
49 Chydoridae family
50 Daphnia galeata mendotae
51 Daphnia pulicaria
52 Daphnia retrocurva
53 Eubasmina caregani
54 Sididae family
57 Leptodora kindtii
58 Acanthocyclaps vernalis
59 Diacyclops thomasi
61 Mesocyclops species
62 Trapacyclops extensus
63 Cyclopoida copepodites
64 Diaptomidae family
66 Calanoida copepodites
68 Nauplii

No. Subgroup 1 Can't
69 Rotifers

70 Blue-green Algae
71 Diatoms

72 Flagellates

73 Golden Algae

74 Green Algae

76 Macrophytes

77 Periphytes

Subgroup 2: Benthically
No. Associated
2 Walleye Age 4+

17 American Eel
19 Brown Bullhead
21 Common Carp
35 White Sucker
41 lsopods

42 Leeches

43 Oligochaetes
44 Snails

75 Epiphytes

Subgroup 3: Panﬁsh &
No. Zooplankton
10 Bluegill Age 1+
11 Lepomis species Age 1+
14 Sunﬁsh family Age 1+
46 Alana species

88

No. Subgroup 3 Can't
55 Large-bodied Cladocerans
67 Harpacticoida

Subgroup 4: Piscivores &
No. Invertivores

 

1 Cormorants
13 Rock Bass Age 1+
15 Panﬁsh Age-0
27 Log Perch
31 Smallmouth Bass
32 Spottail Shiner

No. Subgroup 5: Piscivores
6 Yellow Perch Age-0
20 Channel Catﬁsh
23 Freshwater Drum
28 Longnose Gar
29 Northern Pike
33 Trout-perch
34 White Bass

No. Subgroup 6: Invertivores
9 Black Crappie 1+
12 Pumpkinseed Age 1+
25 Johnny Darter
39 Crayﬁsh
60 Eucyclaps species
65 Temoridae family

Figure 3.1. Map of the Bay of Quinte (Source: Carolyn Bakelaar, Department of

Fisheries and Oceans, Canada).

 

  

UPPER BAY Deseronto ,1
o
Belleville *- . 5;
. ' .3,
\ Trenton . ' -. . 'I V ’ Y5
‘ . Big Island Q 9
.a’ In 43'
' ’ w é
a Q 0
Q ' \I
N O
.3;
Pieton ’
0 Lake Ontario

 

 

 

 

 

 

 

 

 

89

Figure 3.2. Zebra mussel impacts on the Bay of Quinte food web. The scale is relative:
impacts above the zero line are positive impacts of zebra mussels and impacts below the
zero line are negative impacts of zebra mussels. Taxa numbers are placed above or

below each bar. See Table 3.1 for taxa codes.

90

 

06.

1012de

he

mm 2&2

91

Figure 3.3. Panel A: Crystalized sociogram for the pre-zebra mussel time stanza. Units
are relative distances based on the inverse of the density of interactions (see Frank 1996).
Subgroups 1 through 6 are plotted with the direction of feeding relationships represented
by arrows; thickness of arrow indicates weight of feeding relationships. Panel B:
Placement of taxa within subgroups. Circles indicate subgroup boundaries and colors
represent general trophic groupings of taxa. Subgroup numbers are located to the upper

right of all subgroups.

92

_ comm—8&5

 

 

aﬁa 938m I

82382.22 ﬂu

:otiuiooN j

33.50235 2555 D

in D

m _0§nm 95.85.50 ﬂ

 

< ESE

‘3 "P

z uorsuourrg

In

 

mN

 

.m .2de

93

Figure 3.4. Lindeman trophic spine for the pre-zebra mussel time stanza. Boxes with
Roman numerals represent the integer trophic levels; the number within each trophic box
is the percent efﬁciency of that trophic level at processing material. Arrows between the
trophic boxes are ﬂows in the grazer food chain, arrows leaving the top of trophic boxes
are exports, arrows entering the top of trophic boxes are imports, and arrows leaving the
bottom of trophic boxes are ﬂows to detritus, represented by the detrital box. The ground

symbol from electronic circuitry represents ﬂow loss due to respiration. All ﬂows are in

gC m"2 yr".

94

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

) Jr b L 3:28
2.223322an scion-2.2-2.282 h2.53-2.22 92.23.292.236 26%
1.. P 1.. P .m_u>o_
l—I l—I H I._| ciao-D
$82. $2.22 $82 $22 sod-.2
2-2.22.” / 53: 22.2. 222 =5 922.82 :> 2.82. 5 22.2.83.
~_-o_xo3~_.c2x2..m -.2x$2 2.282 2.222 2.32 2.5; 252
) h N, .r v macro
)
-2242 -2522” -2532 mg .82 can £2 9i 22$ 8.2:
3222 m m - N
.226. 4. .4... 4.. 4. 4.
22322 oh $22 $32 $36 $8: $2...
Alli Alll All.
2.2%... 2. > 22. >2 2% :2 8.8 = 822% 2

 

 

 

2 2

#01355 #otnmh-m

 

 

 

2 2

Goths-N ~-o_xam.N

 

 

amd and

 

 

 

 

and 86

 

 

22

Ave-ohm mad

2; 03mm

95

References

Baird, D., J. M. Glade, and R. E. Ulanowicz. 1991. The comparative ecology of six
marine ecosystems. Philos. Trans. R. Soc. Land. 333: 15-29.

Baird, D. and R. E. Ulanowicz. 1989. The seasonal dynamics of the Chesapeake Bay
ecosystem. Ecol. Monogr. 59: 329-364.

Baird, D. and R. E. Ulanowicz. 1993. Comparative study on the trophic structure, cycling
and ecosystem properties of four tidal estuaries. Mar. Ecol. Prog. Ser. 99: 221-
237.

Bondavalli, C., R. E. Ulanowicz, and A. Bodini. 2000. Insights into the processing of
carbon in the South Florida Cypress Wetlands: A whole-ecosystem approach
using network analysis. J. Biogeo. 27: 697-710.

Dettmers, J. M., M. J. Raffenberg, and A. K. Weis. 2003. Exploring zooplankton changes
in southern Lake Michigan: Implications for yellow perch recruitment. .1. Great
Lakes Res. 29: 355-364.

Diamond, M. L., D. Mackay, D. J. Poulton, and F. A. Stride. 1994. Development of a
mass balance model of the fate of 17 chemicals in the Bay of Quinte. J. Great
Lakes Res. 20: 643-666.

Drake, J. M. and J. M. Bossenbroek. 2004. The potential distribution of zebra mussels in
the United States. BioScience. 54: 931-941.

Facon, B., B. J. Genton, J. Shykoff, P. Jame, A. Estoup, and P. David. 2005. A general
eco-evolutionary framework for understanding bioinvasions. TREE. 21: 130-135-

F rank, K. A. 1995. Identifying cohesive subgroups. Soc. Networks. 17: 27-56.

Frank, K. A. 1996. Mapping interactions within and between cohesive subgroups. Soc.
Networks. 18: 93-119.

Gaedke, U. 1995. A comparison of whole-community and ecosystem approaches
(biomass size distributions, food web analysis, network analysis, simulation
models) to study the structure, function and regulation of pelagic food webs. J.
Plankton Res. 17: 1273-1305.

Hall, S. R. and E. L. Mills. 2000. Exotic species in large lakes of the world. Aq. Ecosys.
Health Man. 3: 105-135.

Hannon, B. 1973. The structure of ecosystems. J. Theor. Biol. 41: 535-546.

Heymans, J. J. and D. Baird. 2000. Network analysis of the northern Benguela ecosystem

96

by means of NETWRK and ECOPATH. Ecol. Model. 131: 197-119.
Heymans, J. J ., R. E. Ulanowicz, and C. Bondavalli. 2002. Network analysis of the South

Florida Everglades graminoid marshes and comparison with nearby cypress ecosystems.
Ecol. Model. 149: 5-23.

Holeck, K. T., E. L. Mills, H. J. MacIsaac, M. R. Dochoda, R. I. Colautti, and A.
Ricciardi. 2004. Bridging troubled waters: Biological invasions, transoceanic
shipping, and the Laurentian Great Lakes. BioScience. 54: 919-929.

Hurley, D. A. and W. J. Christie. 1977. Depreciation of the warmwater ﬁsh community in
the Bay of Quinte, Lake Ontario. .1. Fish. Res. Board Can. 34: 1849-1860.

Idrisi, N., E. L. Mills, L. G. Rudstam, and D. J. Stewart. 2001. Impact of zebra mussels
(Dreissena polymorpha) on the pelagic lower trophic levels of Oneida Lake, New
York. Can. J. Fish. Aquat. Sci. 58: 1430-1441.

Jackson, J. R., A. J. VanDeValk, T. E. Brooking, O. A. vanKeeken, and L. G. Rudstam.
2002. Growth and feeding dynamics of lake sturgeon, Acipenserfulvescens, in
Oneida Lake, New York: Results from the ﬁrst ﬁve years of a restoration
program. J. Appl. Ichthyol. 18: 439-443.

Johannsson, O. E-, R. Dermott, D. M. Graham, J. A. Dahl, E. S. Millard, D. D. Myles,
and J. LeBlanc. 2000. Benthic and pelagic secondary production in Lake Erie

after the invasion of Dreissena spp. with implications for ﬁsh production. J. Great
Lakes Res. 26: 31-54.

Krause, A. E., K. A. Frank, D. M. Mason, R. E. Ulanowicz, and W. W. Taylor. 2003.
Compartments revealed in food-web structure. Nature. 426: 282-285.

Leach, J. H. 1993. Impacts of the zebra mussel (Dreissena polymorpha) on water quality
and ﬁsh spawning reefs in western Lake Erie. In T. F. Nalepa and D. W.
Schloesser [eds.], Zebra Mussels: Biology, Impacts, and Control. Lewis
Publishers.

Lindeman, R. L. 1942. The trophic-dynamic aspect of ecology. Ecology. 23: 399-418.

MacIsaac, H. J. 1996. Potential abiotic and biotic impacts of zebra mussels on the inland
waters of North America. Amer. Zool- 36: 287-299.

Marsden, J. E. and M. A. Chotkowski. 2001. Lake trout spawning on artiﬁcial reefs and
the effect of zebra mussels: Fatal attraction? J. Great Lakes Res. 27: 33-43.

Mayer, C. M., A. J. VanDeValk, J. L. Fomey, L. G. Rudstam, and E. L. Mills. 2000.
Response of yellow perch (Percaﬂavescens) in Oneida Lake, New York, to the

97

establishment of zebra mussels (Dreissena polymorpha). Can. J. Fish. Aquat. Sci.
57: 742-754.

Mayer, C. M., R. A. Keats, L. G. Rudstam, and E. L. Mills. 2002. Scale-dependent
effects of zebra mussels on benthic invertebrates in a large eutrophic lake. J. N.
Am. Benthol. Soc. 21: 616-633.

McEliece, R. J. 1977. The T heory of Information and Coding. Addison-Wesley.

Mills, E. L., J. H. leach, J. T. Carlton, and C. L. Secor. 1994. Exotic species and the
integrity of the Great Lakes: Lessons from the past. BioScience. 44: 666-676.

Mills, E. L., J. L. Fomey, M. D. Clady, and W.R . Schaffner. 1978. Oneida Lake, p. 367-
451. In J. A. Bloomﬁeld [ed.], Lakes of New York. Academic Press.

Mills, E. L., J. M. Casselman, R. Dermott, J. D. Fitzsimons, G. Gal, K. T. Holeck, J. A.
Hoyle, O. E. Johannsson, B. F. Lantry, J. C. Makarewicz, E. S. Millard, I. F -
Munawar, M. Munawar, R. O'Gorman, R. W. Owens, L. G. Rudstam, T. Schaner,
and T. J. Stewart. 2003. Lake Ontario: Food web dynamics in a changing
ecosystem (1970—2000). Can. J. Fish. Aquat. Sci. 60: 471-490.

Minns, C. K. 1995. Approaches to assessing and managing cumulative ecosystem
change, with the Bay of Quinte as a case study: An essay. J. Aquat. Ecosyst-
Stress Recov. 4: 1-24.

Nalepa, T. F ., D. L. Fanslow, M. B. Lansing, and G. A. Lang. 2003. Trends in the benthic
macroinvertebrate community of Saginaw Bay, Lake Huron, 1987 to 1996:
Responses to phosphorus abatement and the zebra mussel, Dreissena polymorpha-
J. Great Lakes Res. 29: 14-33.

Nalepa, T. F. G. L. F ahnenstiel, and T. H. Johengen. 1999. Impacts of the zebra mussel
(Dreissena polymorpha) on water quality: A case study in Saginaw Bay, Lake
Huron. In R. Claudi and J. H. Leach [eds.], Nonindigenous Freshwater
Organisms: Vectors, Biology, and Impacts. Lewis Publishers.

Nicholls, K. H., L. Heintsch, and E. Carney. 2002. Univariate step-trend and multivariate

assessments of the apparent effects of P loading reductions and zebra mussels on
the phytoplankton of the Bay of Quinte, Lake Ontario. J. Great Lakes Res. 28: 15-
31. .

Noonburg, E. G., B. J. Shuter, and P. A. Abrams. 2003. Indirect effects of zebra mussels
(Dreissena polymorpha) on the planktonic food web. Can. J. Aquat. Sci. 60:
1353-1368.

Odum, E. P. 1969. The strategy of ecosystem development. Science. 164: 262-270.

98

Padilla, D. K., S. C. Adolph, K. L. Cottingham, and D. W. Schneider. 1996. Predicting
the consequences of dreissenid mussels on a pelagic food web. Ecol. Model. 85:
129-144.

Patten, B. C. 1984. Toward a theory of the quantitative dominance of indirect effects in
ecosystems. Verh. Ges. 0kol. 13: 271-284.

Patten, B. C., R. W. Bosserman, J. T. Finn, and W. G. Cale. 1976. Propagation of cause
in ecosystems. In B. C. Pannen [ed.], Systems Analysis and Simulation in Ecology,
Vol 4. Academic Press.

Pérez-Espaﬁa, H. and F. Arreguin-Se’mchez- 1999. A measure of ecosystem maturity.
Ecol. Model. 199: 79-85.

Pimm, S. L. and J. H. Lawton. 1980. Are food webs divided into compartments? J. Anim-
Ecol. 49: 879-898.

Prout, M. W., E. L. Mills, and J. L. Fomey. 1990. Diet, growth, and potential competitive
interactions between age-O white perch and yellow perch in Oneida Lake, New
York. Trans. Am. Fish. Soc. 119: 966-975.

Ricciardi, A. 2001. F acilitative interactions among aquatic invaders: Is an "invasional
meltdown" occurring the Great Lakes? Can. J. Fish. Aquat. Sci. 58: 2513-2525.

Ridgway, M. S., D. A. Hurley, and K. A. Scott. 1990. Effects of winter temperature and
predation on the abundance of alewife (Alosa pseudoharengus) in the Bay of
Quinte, Lake Ontario. J. Great Lakes Res. 16: 11-20.

Rudstam, L. G-, A. J. VanDeValk, C. M. Adams, J. T. H. Coleman, J. L. Fomey, and M-
E. Richmond. 2004. Cormorant predation and the population dynamics of walleye
and yellow perch in Oneida Lake. Ecol. Applic. 14: 149-163.

Rutherford, B. S., K. A. Rose, E. L. Mills, J. L. Fomey, C. M. Mayer, and L. G. Rudstam.
1999. Individual-based model simulations of a zebra mussel (Dreissena
polymorpha) induced energy shunt on walleye (Stizostedion vitreum) and yellow
perch (Percaﬂavescens) populations in Oneida Lake, New York. Can. J. Fish.

Aquat. Sci. 56: 2148-2160.

Shannon, C. E. 1948. A mathematical theory of communication. Bell System Tech. 27:
379-423.

Simberloff, D. and B. Von Holle. 1999. Positive interactions of nonindigenous species:
invasional meltdown? Biol. Inv. 1: 21-32.

Strayer, D. L-, K. A. Hattala, and A. W. Kahnle. 2004. Effects of an invasive bivalve
(Dreissena polymorpha) on ﬁsh in the Hudson River estuary. Can. J- Aquat. Sci.

99

61 : 924-941.

Strayer, D. L., N. F. Caraco, J. J. Cole, S. Findlay, and M. L Pace. 1999. Transformation
of freshwater ecosystems by bivalves. BioScience. 49:19-27.

Strus, R. H. and D. A. Hurley. 1992. Interactions between alewife (Alosa
pseudoharengus), their food, and phytoplankton biomass in the Bay of Quinte,
Lake Ontario. .1. Great Lakes Res. 18: 709-723.

Thorp, J. H. and A. F. Casper. 2003. Importance of biotic interactions in large rivers: An
experiment with planktivorous ﬁsh, dreissenid mussels and zooplankton in the St.
Lawrence River. River Res. Applic. 19: 265-279.

Ulanowicz, R. E. 1986. Growth and Development: Ecosystems Phenomenology. Springer
Verlag-

Ulanowicz, R. E. 1996. Trophic ﬂow networks as indicators of ecosystem stress. In G. A.
Polis and K. O. Winemiller [eds.], Food Webs: Integration of Patterns and
Dynamics. Chapman and Hall.

Ulanowicz, R. E. 1997. Ecology, The Ascendent Perspective. Columbia University Press.

Vanderploeg, H. A., T. F. Nalepa, D. J. Jude, E. L. Mills, K. T. Holeck, J. R. Liebig, I.A.
Grigorovich, and H. Ojaveer. 2002. Dispersal and emerging ecological impacts of
Ponto Caspian species in the Laurentian Great Lakes. Can. J. Fish. Aquat. Sci. 59:
1209-1228.

100

APPENDICES

101

Appendix 2.1

List of model inputs and data sources for the unbalanced pre- and post-zebra
mussel invasion networks. Diet proportions are not included to conserve space, but
sources of diet information are listed. N.P. stands for not present. Biomass units are g
m’z, wet weight (WW)- Conversions from wet weight to dry weight (DW), and dry
weight to carbon, are listed. P/B, C/B, and WE stand for production-to-biomass,
consumption-to-biomass, and respiration-to-biomass ratios, respectively, measured as
yr'l. Export includes migrations from the ecosystem and ﬁsheries harvest (g m'2 WW).
The abbreviation BQ-OL CMP Workgroup refers to the Bay of Quinte — Oneida Lake
Comparative Modelling Project Workgroup. The methods for this modeling project,
from which much of our data was drawn, are expected to be published in 2006 as a
Canadian Technical Report of Fisheries and Aquatic Sciences (Koops, M. A. pers-

com.)-

102

Appendix 2.1

 

No. Taxa Parameter Pre Value Post Value Reference(s)
1 Cormorants Biomass ww 1.73x10'4 5.23xm'4 BQ-OL CMP Workgroup
ww : ow 3.50x10'l 3.50x10'l Jorgenson 1979
DW : Carbon 4.50x10'l 4.50:.10'l Jorgenscn 1979
P/B 7.62x10'l 6.44x10'l BQ-OL CMP Workgroup
C/B 7.19x10l 7.18x10l BQ-OL CMP Workgroup
R/B 7.03x10l 7.03x10l BQ-OL CMP Workgroup
Diet . - BQ-OL CMP Workgroup
2 Walleye Age 4+ Biomass WW 1.89x10-l 8.24x10-2 BQ-OL CMP Workgroup
ww : ow 2.00:.10'l 2.00x10'l Jorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jorgenson 1979
P/B 4.78x10'l 3.2sxio'l BQ-OL CMP Workgroup
C/B 3.96 3.83 BQ-OL CMP Workgroup
R/B 2.99 2.99 BQ-OL CMP Workgroup
Export 1.35x10.2 5.88x10-3 BQ-OL CMP Workgroup
Diet . - BQ-OL CMP Workgroup
3 Walleye Age 1-3 Biomass ww 7.351.10'2 2.73x10'2 BQ-OL CMP Workgrouv
WW : DW 2.00x10"l 2.00x10-l Jargensen 1979
ow : Carbon 4.50x10'l 4.50x10-l Jargensen 1979
P/B 4.70x10'l 4.70sr10'1 BQ-OL CMP Workgroup
03 3.94 5.54 BQ-OL CMP Workgroup
R/B 3.86 3.86 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
4 Walleye Age-0 Biomass WW 3.49x10-3 3.74x10“3 BQ-OL CMP Workgroup
WW : DW 2.00x10.l 2.00x10.l Jargensen 1979
ow : Carbon 4.50x10'l 4.50:.10'l Jorgenson 1979
NB 2.42 2.42 BQ-OL CMP Workgroup
08 7.84 1.46x10l BQ-OL CMP Workgroup
R/B 9.89 9.89 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
5 Yellow Perch Age 3+ Biomass WW 1.50x10.l 7.94x10.2 BQ-OL CMP Workgroup
ww : DW 2.00:.10'l 2.00x10'l Jorgensen 1979
DW : Carbon 4.50x10'1 4.50x10'l Jorgenson 1979
P/B 3.99x10'l 5.93x10'l BQ-OL CMP Workgroup

103

Appendix 2.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
5 Yellow Perch Age 3+ C/B 3.8 4.19 BQ-OL CMP Workgroup
R/B 3.72 3.72 BQ-OL CMP Workgroup
Export 1.74x10'2 9.18x10'3 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
6 Yellow Perch Age 1-2 Biomass WW 2.26x10-2 3.37x10.2 BQ'OL CMP WOTkSTOUP
ww : ow 2.00x10'l 2,002.10“l Jorgenson 1979
DW : Carbon 4.50x10'l 4.50x10'l Jorgensen 1979
WE 3.99x10'l 5.93x10'l BQ-OL CMP Workgroup
C/B 3.8 4.19 BQ-OL CMP Workgroup
R/B 3.72 3.72 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
7 Yellow Perch Age-0 Biomass WW 2.02x10-2 3.92x10“2 BQ-OL CMP Workgroup
ww : DW 2.00x10'l 2.00m" Jorgenscn 1979
DW : Carbon 4.50x10.l 4.50x10'l Jargensen 1979
P/B 6.14 7.15 BQ-OL CMP Workgroup
C/B 1.53x10l 1.94x10l BQ-OL CMP Workgroup
R/B 1.68x10l 1.68x10l BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
8 White Perch Age 1+ Biomass WW 7.05x10.2 5.56x10.2 BQ-OL CMP Workgroup
ww : ow 2.00x10'l 2.00x10'I Jorgenson 1979
DW : Carbon 4.50x10'l 4.50x10'l Jorgenson 1979
P/B 5.01x10-l 5.86x10'l BQ-OL CMP Workgroup
C/B 4 4.18 BQ-OL CMP Workgroup
R/B 2.75 2.75 BQ-OL CMP Workgroup
Export 1.07x10'4 8.46x10'5 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
9 White Perch Age-0 Biomass WW 1.82x10.2 1.06x10.2 BQ'OL CMP Workgroup
WW : DW 2.00x10.l 2.00x10-l Jorgensen 1979
DW : Carbon 4.50x10.1 4.50x10.l Jorgensen 1979
P/B 4.8 4.8 BQ-OL CMP Workgroup
C/B 1.26x10l 1.28x10l BQ-OL CMP Workgroup
R/B 7.22 7.22 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup

104

Appendix 2.1 (con‘t)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
-4 -4
10 Black Crappie Age 1+ Biomass WW 4.70x10 4.70x10 BQ'OL CMP Workgroup
-1 -
WW : DW 2.00x10 2.00x10 1 Jorgcnsen 1979
-1 -1
DW : Carbon 4.50x10 4.50x10 Jorgensen 1979
-1 -1
P/B 7.08x10 7.08x10 BQ—OL CMP Workgroup
C/B 4.42 4.42 BQ—OL CMP Workgroup
R/B 2.77 2.77 BQ-OL CMP Workgroup
-5 -5
Export 3.24x10 3.24x10 BQ-OL CMP Workgroup
Diet - . BQ-OL CMP Workgroup
-4 .4
11 Bluegill Age 1+ Biomass ww 3.07x10 3.07x10 BQ-OL CMP Workgroup
-l -1
WW : DW 2.00x10 2.00x10 Jorgensen 1979
-1 -1
DW : Carbon 4.50x10 4.50x10 Jorgensen 1979
-1 -1
WE 6.12x10 6.12x10 BQ-OL CMP Workgroup
C/B 4.22 4.22 BQ-OL CMP Workgroup
R/B 2.77 2.77 BQ-OL CMP Workgroup
-5 -5
Export 5.76x10 5.76x10 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
-3 -3
12 Pumpkinseed Age 1+ Biomass WW 6.33x10 6.47x10 BQ-OL CMP Workgroup
-l -1
WW : DW 2.00x10 2.00x10 Jorgensen 1979
-l -1
DW : Carbon 4.50x10 4.50x10 Jorgensen 1979
-l -1
P/B 6.12x10 6.12x10 BQ-OL CMP Workgroup
C/B 4.22 4.22 BQ-OL CMP Workgroup
R/B 2.77 2.77 BQ-OL CMP Workgroup
-4 .4
Export 6.66x10 6.80x10 BQ-OL CMP Workgroup
Diet - . BQ-OL CMP Workgroup
-3 --3
13 Rock Bass Age 1+ Biomass WW 5.00x10 4.85x10 BQ-OL CMP Workgroup
-l -1
WW : DW 2.00x10 2.00x10 Jorgensen 1979
-l -1
DW : Carbon 4.50x10 4.50x10 Jorgensen 1979
-1 -1
P/B 5.15x10 5.15x10 BQ-OL CMP Workgroup
C/B 4.03 4.03 BQ-OL CMP Workgroup
R/B 2.77 2.77 BQ-OL CMP Workgroup
-5 -5
Export 2.60x10 2.52x10 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
-4 -5
14 Panﬁsh Age-0 Biomass WW 1.68x10 7.24x10 BQ-OL CMP Workgroup

105

Appendix 2.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
14 Panﬁsh Age-0 ww : DW 2.00:.10'l 2.00.110'l Jorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jorgensen 1979
P/B 1.5 1.5 1 BQ-OL CMP Workgroup
GB 6 1.19x10 BQ-OL CMP Workgroup
R/B 1.10x10l 1.10aml BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
15 Gizzard Shad Age 1+ Biomass WW 7-l8x10.3 7.58x10.3 BQ-OL CMP Workgroup
ww : DW 2.00x10-l 2.00:.10'l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
WE 1.43 1.43 BQ—OL CMP Workgroup
C/B 5.86 5.86 BQ-OL CMP Workgroup
R/B 2.59 2.59 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
16 Gizzard Shad Age-0 Biomass ww 3.54x10'l 8.9sxlo’2 BQ-OL CMP Workgroup
WW : DW 2.00x10.l 2.00x10-l Jargensen 1979
DW : Carbon 4.50x10-l 4.50x10-l Jergensen 1979
P/B 1.43 1.43 BQ-OL CMP Workgroup
C/B 5.96 5.96 BQ-OL CMP Workgroup
R/B 6.93 6.93 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
17 Alewife Biomass ww 1.04xlo'4 1.87xlo'2 BQ-OL CMP Workgroup
ww : DW 2.00x10"l 2.00x10-l Jorgensen 1979
DW : Carbon 4.50x10-l 4.50x10-l Jorgensen 1979
WE 8.65x10'l 8.89x10'l BQ-OL CMP Workgroup
C/B 4.68 4.68 BQ-OL CMP Workgroup
R/B 1.00x10l 1.00x10l BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
18 Brown Bullhead Biomass ww 1.06x10'2 1.101.10'2 BQ-OL CMP Workgroup
ww : DW 2.00x10'l zoos-10'l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
P/B 4.24x10'l 3.86x10'l BQ-OL CMP Workgroup
OR 3.85 3.77 BQ-OL CMP Workgroup
R/B 2.59 2.59 BQ-OL CMP Workgroup

106

Appendix 2.1 (con‘t)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
-5 -5
18 Brown Bullhead Export 3.55x10 3.69x10 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
-3 -3
19 Burbot Biomass WW 6.89x10 6.61x10 BQ-OL CMP Workgroup
-l -1
WW : DW 2.00x10 2.00x10 Jargensen 1979
-1 -
DW : Carbon 4.50x10 4.50x10 1 Jargensen 1979
-1 -1
WE 2.60x10 2.60x10 BQ-OL CMP Workgroup
C/B 3.52 3.52 BQ-OL CMP Workgroup
R/B 5.79 5.79 BQ—OL CMP Workgroup
-6 -6
Export 7.50x10 7.20x10 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
-2 -2
20 Channel Catﬁsh Biomass WW 6.11x10 6.16x10 BQ'OL CMP WorkgrouP
-1 -1
WW : DW 2.00x10 2.00x10 Jorgensen 1979
-1 -1
DW : Carbon 4.50x10 4.50x10 Jargensen 1979
-1 -1
P/B 2.79x10 2.17x10 BQ-OL CMP Workgroup
C/B 3.56 3.43 BQ-OL CMP Workgroup
R/B 2.59 2.59 BQ-OL CMP Workgroup
-4 -4
Export 2.04x10 2.06x10 BQ-OL CMP Workgroup
Diet . BQ-OL CMP Workgroup
-4
21 Cisco Biomass WW 9.27x10 N.P- BQ—OL CMP Workgroup
-1 -1
WW : DW 2.00x10 2.00x10 Jorgensen 1979
-l -1
DW : Carbon 4.50x10 4.50x10 Jorgensen 1979
WE 1.71 NP. BQ-OL CMP Workgroup
C/B 6.42 NP. BQ-OL CMP Workgroup
R/B 1.04 NP. BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
-2 -2
22 Common Carp Biomass WW 5.18x10 3.40x10 BQ-OL CMP Workgroup
-1 -1
WW : DW 2.00x10 2.00x10 Jorgensen 1979
-l -1
DW : Carbon 4.50x10 4.50x10 Jorgensen 1979
-1 -l
P/B 1.56x10 1.60x10 BQ-OL CMP Workgroup
C/B 3.33 3.33 BQ-OL CMP Workgroup
R/B 2.4 2.4 BQ-OL CMP Workgroup
-5 -6
Export 1.10x10 7.20x10 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup

107

Appendix 2.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
23 Darters Biomass WW 5.40x10-5 1.35x10.4 BQ-OL CMP Workgroup
ww : DW 2.00:.10'l 2.00x10"l Jorgensen 1979
DW : Carbon 4.50x10-l 4.50x10-l Jorgensen 1979
P/B 3.70x10'l 3.70:110'l BQ-OL CMP Workgroup
C/B 3.74 3.74 BQ-OL CMP Workgroup
R/B 2.59 2.59 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
24 Emerald Shiners Biomass WW 2.39x10“3 8.60x10-2 BQ-OL CMP Workgroup
ww : DW 2.00:.10'l 2.00x10-l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
P/B 1.71 1.71 BQ-OL CMP Workgroup
C/B 6.42 6.42 BQ-OL CMP Workgroup
R/B 5.83 5.83 BQ-OL CMP Workgroup
Diet - . BQ-OL CMP Workgroup
25 Freshwater Drum Biomass WW 5.71x10.2 1.03x10-l BQ-OL CMP Workgroup
WW : DW 2.00x10.l 2.00x10.l Jorgensen 1979
DW : Carbon 4.50x10-l 4.50x10'l Jergensen 1979
P/B 2.64x10.l 2.50x10-l BQ-OL CMP Workgroup
C/B 3.52 3.52 BQ-OL CMP Workgroup
R/B 2.57 2.57 BQ—OL CMP Workgroup
Export 2.16x10u4 3.91 x10.4 BQ—OL CMP Workgroup
Diet . - BQ-OL CMP Workgroup
26 Golden Shiners Biomass WW 1.77x10.3 5.40x10'5 BQ-OL CMP Workgroup
WW : DW 2.00x10.l 2.00x10.l Jorgensen 1979
DW : Carbon 4.50x10-l 4.50x10'l Jergensen 1979
P/B 1.71 1.71 BQ-OL CMP Workgroup
C/B 6.42 6.42 BQ-OL CMP Workgroup
R/B 5.83 5.83 BQ-OL CMP Workgroup
Diet . BQ-OL CMP Workgroup
27 Lake Sturgeon Biomass WW N.P. 5.92x10-3 BQ'OL CMP WOTRSTOUP
WW : DW 2.00x10.l 2.00x10.l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
P/B N.P. 2.00x10-l BQ-OL CMP Workgroup

108

Appendix 2.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
27 Lake Sturgeon C/B NP. 4 BQ-OL CMP Workgroup
R/B N.P. 3.3 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
28 Log Perch Biomass WW 2.70x10-5 6.30x10-5 BQ-OL CMP Workgroup
WW : DW 2.00x10.1 2.00x10-1 Jorgensen 1979
DW : Carbon 4.50x10'l 4.50:.10'l Jorgensen 1979
P/B 3.70x10'l 3.70xio" BQ-OL CMP Workgroup
C/B 3.74 3.74 BQ-OL CMP Workgroup
R/B 2.59 2.59 BQ—OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
29 Mottled Sculpin Biomass WW 9.00x10-b 9.00x10.6 BQ—OL CMP Workgroup
ww : DW 2.00x10-l 2.00x10" Jorgensen 1979
DW : Carbon 4.50x10-1 4.50x10'l Jorgensen 1979
P/B 3.70am"l 3.70x10'l BQ-OL CMP Workgroup
C/B 3.74 3.74 BQ-OL CMP Workgroup
R/B 2.59 2.59 BQ-OL CMP Workgroup
Diet . - BQ-OL CMP Workgroup
30 Northern Pike Biomass ww 7.11x10'4 7.11x10'4 BQ-OL CMP Workgrouv
WW : DW 2.00x10.l 2.00x10.l Jorgensen 1979
DW : Carbon 4.50:.10'l 4.50:.10'l Jergensen 1979
WE 2.01x10'l 1.98x10'I BQ-OL CMP Workgroup
C/B 3.4 3.4 BQ-OL CMP Workgroup
R/B 5.79 5.79 BQ-OL CMP Workgroup
Export 8.37x10'5 8.37xlo'5 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
31 Red Horse Sucker Biomass WW 5.29x10.3 6.72x10-3 BQ-OL CMP Workgroup
ww : DW 2.00x10-l 2.00x10-l Jorgensen 1979
ow : Carbon 4.50rtlo'l 4.5oxlo‘l Jorgensen 1979
P/B 3.70x10'l 3.70am"l BQ-OL CMP Workgroup
C/B 3.74 3.74 BQ-OL CMP Workgroup
R/B 2.59 2.59 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
32 Smallmouth Bass Biomass WW 4.56x10-2 4.87x10.2 BQ-OL CMP Workgroup

109

Appendix 2.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
32 Smallmouth Bass WW : DW 2.00x10.l 2.00x10.l Jargensen 1979
ow : Carbon 4.50x10-l 4.50x10'l Jargensen 1979
P/B 3.90x10'l 3.68x10'1 BQ—OL CMP Workgroup
C/B 5.36 5.36 BQ-OL CMP Workgroup
R/B 3.92 3.92 BQ-OL CMP Workgroup
Export 2.09x10'3 2.23x10'3 BQ—OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
33 Trout-perch Biomass WW 9.26x10.3 1.02x10-2 BQ-OL CMP Workgroup
ww ; DW 2.00x10-l 2.00x10-l Jorgensen 1979
DW : Carbon 4.50x10-l 4.50x10"l Jorgensen 1979
WB 1.35 1.46 BQ-OL CMP Workgroup
C/B 5.71 5.91 BQ-OL CMP Workgroup
R/B 3.19 3.19 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
34 White Bass Biomass WW 1.06x10-2 1.08x10.2 BQ-OL CMP Workgroup
WW : DW 2.00x10.l 2.00x10.l Jorgensen 1979
ow : Carbon 4.50x10"l 4.50x10'l Jergensen 1979
P/B 2.60x10.I 2.60x10.l BQ—OL CMP Workgroup
C/B 3.52 3.52 BQ-OL CMP Workgroup
R/B 5.79 5.79 BQ-OL CMP Workgroup
Export 2.40x10'4 2.45x10'4 BQ—OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
35 White Sucker Biomass WW 4.56x10.2 4.98x10.2 BQ-OL CMP Workgroup
WW : DW 2.00x10.l 2.001110-l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
WE 3.23x10'l 2.68x10'l BQ—OL CMP Workgroup
C/B 3.65 3.54 BQ-OL CMP Workgroup
R/B 2.59 2.59 BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
36 Amphipods Biomass WW 5.19x10-2 4.63x10.2 BQ-OL CMP Workgroup
WW : DW 1.67x10.l 1.67x10.l Jargensen 1979
DW : Carbon 4.17x10.l 4.17x10.l Jargensen 1979
P/B 5.7 5.7 BQ-OL CMP Workgroup

110

Appendix 2.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)

36 Amphipods C/B 3.02x10l 3.02x10l BQ-OL CMP Workgroup
R/B 4.26 4.26 Quigley et al. 2002
Diet . . BQ-OL CMP Workgroup

37 Chironomids Biomass ww 5.73x10'2 4.54x1o'2 BQ-OL CMP Workgroup
ww : ow 1.67x10'l 1.67x10'l Jorgensen 1979
DW : Carbon 4.62x10.l 4.62x10.l Jorgensen 1979
P/B 1.3lx10l 1.31x10l BQ-OL CMP Workgroup
C/B 6.24x10l 6.24x10l BQ-OL CMP Workgroup
R/B 4.5 4.5 Johnson and Brinkhur 1971
Diet . - BQ-OL CMP Workgroup

Krause 2004

38 Clams Biomass ww 7.19x10'4 4.45x10'4 BQ-OL CMP Workgrouv

WW : DW 1.67x10-l 1.67x10.l Jorgensen 1979

-1 -1
DW : Carbon 3.99x10 3.99x10 Jorgensen 1979

P/B 3.8 3.8 BQ-OL CMP Workgroup
C/B 2.44x10l 2.44x10l BQ-OL CMP Workgroup
R/B 1.03x10l 1.03x10l Johnson and Brinkhur 1971
Diet . . BQ-OL CMP Workgroup
Krause 2004
39 insects Biomass ww 6.88x10'3 6.88x10‘3 BQ-OL CMP Workgroun
ww : ow 1.67x10'l 1.67xio'l Jorgensen 1979

-l -1
DW : Carbon 4.46x10 4.46x10 Jergensen 1979

P/B 5.35 5.35 BQ-OL CMP Workgroup
C/B 3.18x10l 3.18x10l BQ-OL CMP Workgroup
R/B 1.33x10l 1.33x10l BQ-OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
Krause 2004
40 lsopods Biomass WW 7.25x10-3 1.38x10.2 BQ-OL CMP Workgroup
WW : DW 1.67x10-l 1.67x10-l Jorgensen 1979

-l -1
DW : Carbon 3.43x10 3.43x10 Jorgensen 1979

WE 5.7 5.7 BQ-OL CMP Workgroup
1 1

C/B 3.02x10 3.02x10 BQ-OL CMP Workgroup

R/B 4.26 4.26 Quigley et a1. 2002

111

Appendix 2.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
40 lsopods Diet . . BQ-OL CMP Workgroup
41 Leeches Biomass ww 3.29x10'3 4.38x111'3 BQ-OL CMP Workgroup
ww : ow 1.67x10'l 1.67x10'l Jorgensen 1979
ow : Carbon 4.83x10'l 4.83x10'l Jorgensen 1979
WB 5.35 5.35 BQ-OL CMP Workgroup
C/B 3.18x10l 3.18x10l BQ-OL CMP Workgroup
R/B 1.33x10l 1.33x10l BQ—OL CMP Workgroup
Diet . . BQ-OL CMP Workgroup
42 Oligochaetes Biomass WW 8.98x10-3 1.65x10.2 BQ-OL CMP Workgroup
ww : DW 1.67x10'l 1.67x10'l Jorgensen 1979
DW : Carbon 4.02x10.l 4.02x10-l Jargensen 1979
P/B 1.31x10l 1.31x10l BQ-OL CMP Workgroup
C/B 6.24x10l 6.24x10l BQ-OL CMP Workgroup
R/B 4.5 4.5 Johnson and Brinkhur 1971
Diet . . BQ-OL CMP Workgroup
Krause 2004
43 Snails Biomass WW 1.85x10.2 3.10x10-2 BQ-OL CMP Workgroup
WW : DW 1.67x10-l 1.67x10.l Jargensen 1979
ow : Carbon 3.99x10'l 3.99x10'l Jorgensen 1979
P/B 3.5 3.5 BQ—OL CMP Workgroup
C/B 1.33x10l 1.33x10l BQ-OL CMP Workgroup
RIB 1.8 1.8 BQ-OL CMP Workgroup
Diet . BQ-OL CMP Workgroup
Zebra Mussels Biomass ww N.P. 1.59x10l BQ-OL CMP Workgroup
WW : DW 1.67x10.l 1.67x10-l Jorgensen 1979
DW : Carbon 3.99x10.l 3.99x10.l Jargensen 1979
WE NP. 1.35 BQ-OL CMP Workgroup
C/B NB 8.6 BQ-OL CMP Workgroup
R/B NP. 4.15 Fanslow et al. 2001
Diet . . BQ-OL CMP Workgroup
45 Alona species Biomass WW 1.05x10-4 3.01x10-5 BQ-OL CMP Workgroup
WW : DW 1.67x10.l 1.67x10'l Jorgensen 1979
DW : Carbon 4.50x10-l 4.50x10.l Jorgensen 1979

112

 

Appendix 2.] (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
45 Alana species P/B 3.80x10l 3.80x10l BQ-OL CMP Workgroup
C/B 1.53x102 1.53x102 BQ-OL CMP Workgroup
R/B 1.86 1.86 Urabe and Watanabe 1989
Diet BQ—OL CMP Workgroup
Krause 2004
46 Basmina Biomass WW 2.59x10-2 2.01x10-2 BQ-OL CMP Workgroup
langirastris WW : DW 1.67x10-l 1.67x10.l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
WE 3.80x10l 3.80x10l BQ-OL CMP Workgroup
C/B 1.53x102 1.53x102 BQ-OL CMP Workgroup
R/B 1.86 1.86 Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
47 Camptocercus Biomass WW N.P. 1.26x10-4 BQ'OL CMP Workgroup
harpae WW : DW 1.67x10-l 1.67x10-I Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10-l Jargensen 1979
P/B N.P. 3.80x10l BQ-OL CMP Workgroup
C/B N.P. 1.53xlo2 BQ-OL CMP Workgroup
R/B NP. 1.86 Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
48 Ceriodaphnia Biomass WW 7.391(10-4 5.32x10.4 BQ-OL CMP Workgroup
quadrangula WW : DW 1.67x10.l 1.67x10-l Jorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jorgensen 1979
WE 3.80x10l 3.80x10l BQ-OL CMP Workgroup
C/B 1.53x102 1.53x102 BQ-OL CMP Workgroup
R/B 1.86 1.86 Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
49 Chydorus Biomass WW 1.16x10.2 2.57x10-2 BQ-OL CMP Workgroup
sphaericus WW : DW 1.67x10.l 1.67x10-l Jorgensen 1979
DW : Carbon 4.50x10'l 4.50xlo’l Jorgensen 1979
P/B 3.80x10i 3.80x10l BQ-OL CMP Workgroup

113

Appendix 2.] (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
49 Chydorus C/B 1.53x102 1.53x102 BQ-OL CMP Workgroup
sphaericus R/B 1.86 1.86 Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
50 Daphnia galeata Biomass WW 2.58x10.l 1.88x10-l BQ-OL CMP Workgroup
mendotae WW : DW 1.67x10.l 1.67x10"I Jargensen 1979
DW : Carbon 5.07x10.l 5.07x10-1 Jargensen 1979
P/B 3.80x10l 3.80x10l BQ-OL CMP Workgroup
C/B 1.53x102 1.53x102 BQ—OL CMP Workgroup
R/B 3.13x10l 3.13x10l Urabe and Watanabe1989
Diet BQ-OL CMP Workgroup
Krause 2004
51 Daphnia Biomass ww 3.15x1o'l 4.89x10'l BQ-OL CMP Workgroup
pulicaria ww : DW 1.67x10-l 1.67x10'l Jargensen 1979
DW : Carbon 5.07x10-l 5.07x10l Jargensen 1979
P/B 3.80x10l 3.80x10l BQ-OL CMP Workgroup
C/B 1.53x102 1.53x102 BQ-OL CMP Workgroup
R/B 3.13x10l 3.13x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
52 Daphnia Biomass WW 7.36x10»3 8.20x10-4 BQ-OL CMP Workgroup
retrocurva WW : DW 1.67x10'l 1.67x10'l Jorgensen 1979
DW : Carbon 5.07x10"1 5.07xlo'l Jorgensen 1979
WE 3.80x10l 3.80x10l BQ-OL CMP Workgroup
C/B 1.53x102 1.53x102 BQ-OL CMP Workgroup
R/B 3.13x10l 3.13x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
53 Diaphanosoma Biomass WW 9.11x10-3 9.02x10.3 BQ-OL CMP Workgroup
species WW : DW 1.67x10.l 1.6711110.l Jorgensen 1979
ow : Carbon 4.50x10'l 4.50x10'l Jergensen 1979
P/B 3.80x10l 3.80x10l BQ-OL CMP Workgroup
C/B 1.53x102 1.53x102 BQ-OL CMP Workgroup

114

Appendix 2.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
53 Diaphanosoma R/B 3-l3x10l 3.13x10l Urabe and Watanabe 1989
sPecies Diet BQ-OL CMP Workgroup
Krause 2004
54 Eubosmina Biomass ww 2.09x10'2 3.22xlo'3 BQ-OL CMP Workgroup
coregoni WW : DW 1.67x10.l 1.67x10-l Jorgensen 1979
DW : Carbon 4.50x10-l 4.50x10'l Jorgensen 1979
PB 3.80x10I 3.80x10l BQ-OL CMP Workgroup
C/B 1.53x102 1.53x102 BQ-OL CMP Workgroup
R/B 1.86 1.86 Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
55 Sida crystallina Biomass ww 3.27x10'5 7.42x10'5 BQ-OL CMP Workgroup
WW : DW 1.67x10-l 1.67x10.l Jorgensen 1979
DW : Carbon 4.50x10-l 4.50x10‘l Jorgensen 1979
WE 3.80x10l 3.80x10l BQ-OL CMP Workgroup
C/B 1.53x102 1.53x102 BQ—OL CMP Workgroup
R/B 3.13x10l 3.13x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
56 Leptodora kindtii Biomass WW 4.7lx10.4 1.57x10-3 BQ-OL CMP Workgroup
ww : ow 1.67x10'l 1.67xlo'l Jergensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jorgensen 1979
P/B 3.10x10l 3.10x10l BQ-OL CMP Workgroup
C/B 1.23x102 1.23x102 BQ-OL CMP Workgroup
R/B 2.59x‘I 2.59xlo" Hillbricht-llkowska and
Karabin 1970
Diet BQ—OL CMP Workgroup
Krause 2004
57 Acanthocyclops Biomass WW 1.67x10.5 3.54x10.3 BQ-OL CMP Workgroup
vernalis WW : DW 1.67x10-l 1.67x10“l Jorgensen 1979
DW : Carbon 4.36x10.l 4.36x10.l Jargensen 1979
WE 2.00x10l 2.00x10l BQ-OL CMP Workgroup
c713 8.20x10l 8.20x10] BQ-OL CMP Workgroup

115

Appendix 2.1 (con‘t)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
57 Acanthocyclops R/B 1.84x10l 1.84x10l Urabe and Watanabe 1989
vernalis Diet BQ-OL CMP Workgroup
Krause 2004
58 Diacyclops Biomass ww 1.26x10'l 5.42x10'2 BQ-OL CMP Workgroup
thomasi WW : DW 1.67x10-l 1.67x10-l Jorgensen 1979
DW : Carbon 4.36x10'l 4.36x10'l Jorgensen 1979
P/B 2.00x10l 2.00x10l BQ-OL CMP Workgroup
C/B 8.20x10l 8.20x10l BQ-OL CMP Workgroup
R/B 1.84x10l 1.84x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Hansen and Nelson 1998
59 Ergasilus species Biomass ww 2.13x10'4 2.41x10'5 BQ-OL CMP Workgroup
ww : DW 1.67x10'l 1.67x10'l Jergensen 1979
DW : Carbon 4.36xlo'l 4.36x10'l Jorgensen 1979
WE 2.00x10l 2.00x10l BQ-OL CMP Workgroup
C/B 8.20x10l 8.20x10l BQ-OL CMP Workgroup
R/B 1.84x10l 1.84x10l Urabe and Watanabe 1989
Diet BQ—OL CMP Workgroup
Hudson and Lesko 2002
60 Mesocyclops edax Biomass WW 5.65x10-2 4.99x10-2 BQ'OL CMP Workgroup
ww : DW 1.67x10'l 1.67x10'l Jorgensen 1979
DW : Carbon 4.36x10'l 4.36x10'l Jargensen 1979
WE 2.00x10l 2.00x10l BQ-OL CMP Workgroup
C/B 8.20x10l 8.20x10l BQ-OL CMP Workgroup
R/B 1.841110l 1.84x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
61 Epischura Biomass ww 3.68x10’2 5.25xio'2 BQ-OL CMP Workgroup
lacustris WW : DW 1.67x10-l 1.67x10-l Jorgensen 1979
ow : Carbon 4.36xio’l 4.36x10'l Jorgensen 1979
P/B 2.00x10l 2.00x10l BQ-OL CMP Workgroup
C/B 8.20x10l 8.20x10l BQ—OL CMP Workgroup
R/B 2.96x10l 2.96x10l Banse and Mosher 1980

116

Appendix 2.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
61 Epischura Diet . . BQ—OL CMP Workgroup
lacustris Krause 2004
62 Leptodiaptomus Biomass ww 7.34x10'2 6.85x10'2 BQ-OL CMP Workgroup
minutus WW : DW 1.67x10.l 1.67x10.l Jorgensen 1979
DW : Carbon 4.36x10'l 4.36x10'l Jargensen 1979
P/B 2.00x10l 2.001110l BQ-OL CMP Workgroup
C/B 8.20x10l 8.20x10l BQ'OL CMP Workgroup
R/B 2.96x10l 2.96x10l Banse and Mosher 1980
Diet - . BQ-OL CMP Workgroup
Krause 2004
63 Skistodiaptomus Biomass WW 1.00x10-l 1.07x10-l BQ—OL CMP Workgroup
oregonensis WW : DW 1.67x10.l 1.67x10.l Jorgensen 1979
DW : Carbon 4.36x10.l 4.36x10.l Jorgensen 1979
P/B 2.00x10l 2.00x10l BQ-OL CMP Workgroup
C/B 8.20x10l 8.20x10l BQ-OL CMP Workgroup
R/B 2.96x10l 2.96x10l Banse and Mosher 1980
Diet . - BQ-OL CMP Workgroup
Krause 2004
64 Nauplii Biomass WW 5.46x10.2 4.40x10.2 BQ-OL CMP Workgroup
ww : ow 1.67x10'l 1.67x10'l Jorgensen 1979
ow : Carbon 4.50xlo'l 4.50x10'l Jorgensen 1979
WE 2.00x10l 2.00x10l BQ-OL CMP Workgroup
C/B 8.20x10l 8.20x10l BQ—OL CMP Workgroup
R/B 1.16 1.16 Makarewicz and Likens 1979
Diet . . BQ-OL CMP Workgroup
Krause 2004
65 Rotifers Biomass WW 7.20x10.3 7.20x10.3 BQ-OL CMP Workgroup
ww : DW 1.67x10'l 1.67x10'l Jorgensen 1979
DW : Carbon 4.50x10-l 4.50x10.l Jorgensen 1979
P/B 5.20x10l 5.20x10l BQ-OL CMP Workgroup
C/B 2.08x102 2.08x102 BQ-OL CMP Workgroup
R/B 1.16 1.16 Makarewicz and Likens 1979
Diet . . BQ-OL CMP Workgroup

117

Appendix 2.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
65 Rotifers Die‘t Pennak 1978
66 Blue-green Algae Biomass WW 1.38 1.09 BQ—OL CMP Workgroup
-1 -1
WW : DW 3.60x10 3.60x10 Jorgensen 1979
-1 -1
DW : Carbon 4.60x10 4.60x10 Jargensen 1979
1 1
P/B 8.70x10 9.00x10 BQ-OL CMP Workgroup
C/B None None BQ-OL CMP Workgroup
R/B 7.28x10l 7.28x10l Biddanda and Cotner 2002
67 Diatoms Biomass WW 1.77 1.62 BQ-OL CMP Workgroup
-1 -1
WW : DW 3.30x10 3.30x10 Jorgensen 1979
-l -1
DW : Carbon 5.17x10 5.17x10 Jargensen 1979
1 1
WE 8.70x10 9.00x10 BQ-OL CMP Workgroup
C/B None None BQ-OL CMP Workgroup
R/B 7.28x10l 7.28x10l Biddanda and Cotner 2002
-2 -2
68 Euglena Biomass WW 3.48x10 2.25x10 BQ-OL CMP Workgroup
-1 -1
WW : DW 4.00x10 4.00x10 Jorgensen 1979
-l -1
DW : Carbon 4.81x10 4.81x10 Jorgcnsen 1979
1 1
P/B 8.70x10 9.00x10 BQ-OL CMP Workgroup
C/B None None BQ-OL CMP Workgroup
R/B 7.28x10l 7.28x10l Biddanda and Cotner 2002
-l -1
69 Flagellates Biomass WW 8.50x10 5.21x10 BQ-OL CMP Workgroup
-l -1
WW : DW 4.00x10 4.00x10 Jorgensen 1979
-1 -1
DW : Carbon 4.50x10 4.50x10 Jorgensen 1979
1 1
P/B 8.70x10 9.00x10 BQ-OL CMP Workgroup
C/B None None BQ-OL CMP Workgroup
R/B 7.28x101 7.28x10l Biddanda and Cotner 2002
-1 -2
70 Golden Algae Biomass WW 3.27x10 8.77x10 BQ-OL CMP Workgroup
-l -1
WW : DW 4.00x10 4.00x10 Jorgensen 1979
-1 -1
DW : Carbon 4.50x10 4.50x10 Jorgensen 1979
l l
P/B 8.70x10 9.00x10 BQ-OL CMP Workgroup
C/B None None BQ-OL CMP Workgroup
R/B 7.28x10l 7.28x10l Biddanda and Cotner 2002
-l -1
71 Green Algae Biomass WW 7.87x10 2.00x10 BQ-OL CMP Workgroup
- -1
WW : DW 4.30x10 1 4.30x10 Jorgensen 1979

118

Appendix 2.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
71 Green Algae DW : Carbon 5.05x10-l 5.05x10.l Jorgensen 1979
P/B 8.70x10l 9.001110l BQ-OL CMP Workgroup
C/B None None BQ-OL CMP Workgroup
RIB 7.28x10l 7.28x10l Biddanda and Cotner 2002
72 Epiphytes Biomass WW 9.56x10-l 9.56x10-l BQ—OL CMP Workgroup
WW : DW 1.201(10-l 1.20x10.l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10"l Jorgensen 1979
P/B 1.20x102 1.20x102 BQ-OL CMP Workgroup
C/B None None BQ—OL CMP Workgroup
R/B 1.00x102 9.67x10l Biddanda and Cotner 2002
73 Macrophytes Biomass WW 9.45x10.l 1.1 BQ-OL CMP Workgroup
ww : ow 1.20x10'l 1.20xio'l Jorgensen 1979
DW : Carbon 4.50x1o'l 4.50x10"l Jergensen 1979
NB 8.8 8.8 BQ-OL CMP Workgroup
C/B None None BQ-OL CMP Workgroup
R/B 7.36 7.12 Biddanda and Cotner 2002
74 Periphytes Biomass ww 1.23xlo'l 1.23x10'l BQ-OL CMP Workgroup
ww : ow 1.20xlo'l 1.20xio'l iorgensen 1979
DW : Carbon 4.50x10.l 4.501110.l Jorgensen 1979
P/B 2.65x10l 2.65x10l BQ-OL CMP Workgroup
08 None None BQ-OL CMP Workgroup
R/B 2.22x10l 2.15x10l Biddanda and Cotner 2002

119

References

Banse, K. and S. Mosher. 1980. Adult body mass and annual production/biomass
relationships of ﬁeld populations. Ecol. Monogr. 50: 355-379.

Biddanda, B. A. and J. B. Cotner. 2002. Love handles in aquatic ecosystems: The role of
dissolved organic carbon drawdown, resuspended sediments, and terrigenious
inputs in the carbon balance of Lake Michigan. Ecosystems. 5: 431-445.

Fanslow, D. L., T. F. Nalepa, and T. H. Johengen. 2001. Seasonal changes in the
respiratory electron transport system (ETS) and respiration of the zebra mussel,
Dreissena polymorpha in Saginaw Bay, Lake Huron. Hydrobiologia. 448: 61-70.

Hansen, A.-M., and G. H. Nelson Jr. 1998. Food limitation in a wild cyclopoid copepod
population: Direct and indirect life history responses. Oecologia. 115: 320-330.

Hillbricht-Ilkowska, A. and A. Karabin. 1970. An attempt to estimate consumption,
respiration, and production of Leptodora kindtii (Focke) in ﬁeld and laboratory
experiments. Polskie Arch. Hydrobiol. II. 17: 81-86.

Hudson, P. L., and Lesko, L. T. 2002. Free-living and parasitic copepods of the
Laurentian Great Lakes: Keys and details on individual species. Ann Arbor, MI:
Great Lakes Science Center. Published online at
<http://www.glsc.usgs.gov/greatlakescopepodsb.

Johnson, M. G. and R. O. Brinkhur. 1971. Production of benthic macroinvertebrates of
Bay of Quinte and Lake Ontario. J Fish. Res. Board Can. 28: 1699-1714.

J orgensen, S. E. 1979. Handbook of Environmental Data and Ecological Parameters.
Pergamon Press.

Krause, A. E. 2004. The role of compartments in food-web structure and changes
following biological invasions in southeast Lake Michigan. Ph.D. thesis.
Michigan State Univ.

Makarewicz, J. C. and G. E. Likens. 1979. Structure and function of the zooplankton
community of Mirror Lake, New Hampshire. Ecol. Monogr. 49: 109-127.

Pennak, R. W. 1978. Freshwater Invertebrates of the United States. 2nd ed. J. Wiley and
Sons, Inc.

Quigley, M. A., P. F. Landrum, W. S. Gardner, C. R. Stubbleﬁeld, and W. M. Gordon.
2002. Respiration, nitrogen excretion, and O:N ratios of the Great Lakes
amphipod Diporeia sp. NOAA Technical Memorandum GLERL-120.

Urabe, J. and Y. Watanabe. 1989. Inﬂuence of food density on respiration rate of two

crustacean plankters, Daphnia galeata and Basmina longirostris. Oecologia. 82:
362-3 6.

120

Appendix 2.2

Balanced exchange matrices for the pre- and post-zebra mussel invasion
networks. For clarity, the matrix was changed to list format. Flows units are gC m'2 yr'I

and all zero ﬂows were removed from the list. N.P., Prod., Cons., Resp-, Imp., and Exp.
stand for not present, production, consumption, respiration, imports, and exports,

respectively.

121

Appendix 2.2

 

 

122

Pre Post Pre Post

Predator Prey Exchange Exchange Predator Prey Exchange Exchange
1 2 8.20x10'4 2.66x10'3 2 5 2.59xlo'2 1.22x10'2
1 3 5.54x10'3 2.14x10'2 2 6 2.66x10'2 1.24x10'2
1 4 4.80x10'5 1.52x10'4 2 7 4.44x10'1 1.96x10'1
1 5 4.15x10'3 1.38x10'2 2 9 9.52x10'2 4.28x10'2
1 6 4.24x10'3 1.40x10'2 2 14 2.61x10'4 1.17x10'5
1 7 1.16x10'4 3.63x10'4 2 15 3.84x10'3 1.89x10'3
1 8 1.19xlo'3 3.96x10'3 2 16 1.21x10'l 5.41x10'2
1 10 5.45x10'5 1.88x10'4 2 18 3.17x10'3 1.42x10’3
1 11 5.34x10'5 1.84x10'4 2 19 1.92x10'2 9.08x10'3
1 12 5.40xio'4 1.93x10'3 2 20 3.40x10'3 1.65x10'3
1 13 5.50x10'4 1.90x10'3 2 21 2.93xlo'3 NP.

1 15 3.32x10'4 1.15x10'3 2 23 2.94x10'5 1.42x10'4
1 16 8.87x10'5 2.79x10'4 2 24 1.58x10'2 6.93x10'3
1 18 2.75x10'4 8.70x10-4 2 25 3.06x10"3 1.40x10"3
1 19 3.70x10'4 1.23x10'3 2 26 1.58x10'2 6.93x10'5
1 20 2.95x1o'4 1.01x10'3 2 28 2.92x10'5 1.42x10'5
1 21 9.94xio'6 NP. 2 29 3.01x10"5 1.42x10'5
1 23 2.55x10'6 8.71x10'5 2 3o 1.93x10'3 8.86x10'4
1 24 5.42x10'5 1.68x10'4 2 31 2.92x10'3 1.42x10'3
1 25 1.05x10'5 3.38x10'5 2 32 9.62x10'3 4.65x10'3
1 26 5.42x10'5 1.68x10'6 2 34 1.91x10'2 9.04x10'3
1 28 2.54x10'6 8.72x10'6 2 35 3.43x10'3 1.67x10’3
1 29 2.62x10'6 8.71x10'6 2 36 4.10x10'2 1.76x10'2
1 3o 3.71x10'5 1.20x10’4 2 37 1.84x10'l 8.02x10'2
1 31 2.54x10'4 8.71x10'4 2 39 1.15x10'2 6.33x10'4
1 32 5.83x10'4 1.98x10’3 2 4o 4.89x1o'3 2.82x10'3
1 33 1.69xlo'5 5.57x10'5 2 41 1.47x10'3 7.62x10'4
1 34 3.69x10'4 1.23x10'3 2 42 1.10xlo'l 6.07x10'2
1 35 2.97x10'4 1.02x10'3 2 44 NP. 8.68x10'4
1 39 8.05x10'5 3.09x10'5 2 46 8.15x10'5 2.82x10'5
1 41 1.02x10'5 3.71x10'5 2 48 2.52x10'6 0

2 4 2.58x10'2 1.16x10'2 2 49 6.25x10'5 5.75x10'5

Appendix 2.2 (con't)
Pre Post Pre Post

 

 

123

Predator Prey Exchange Exchange Predator Prey Exchange Exchange
2 50 9.09x10'4 2.76x10'4 3 41 5.86x10'4 3.55x10'4
2 51 1.11xlo'3 7.18x10“1 3 42 4.41xlo'2 2.82x10'2
2 52 2.59x10'5 1.20x10'6 3 44 NP. 2.65x10“4
2 53 2.48x10'5 1.14x10’5 3 46 4.36x10'5 1.74x10'5
2 54 1.12x10'4 7.21x10'6 3 48 1.35x10'6 0

3 4 1.03xlo'2 5.38x10'3 3 49 3.29x10'5 3.59x10'5
3 5 6.91x10'3 3.78x10'3 3 50 4.84x10'4 1.70x10'4
3 6 7.07x10'3 3.85x10'3 3 51 5.91xlo'4 4.43x104
3 7 1.84x10'l 9.48x10'2 3 52 1.38x10’5 0

3 9 3.80x10'2 1.99x10'2 3 53 1.33x10'5 6.98x10’6
3 14 1.04x10'4 5.43x10'6 3 54 5.91x10'5 4.51x10'6
3 15 1.53x1o'3 8.85x10'4 4 4 2.09x10'3 3.01x10'3
3 16 4.89xlo'2 2.48x10'2 4 7 1.1)8x1o'2 1.53x10'2
3 18 1.27x10'3 6.60x10'4 4 9 4.64x10'3 6.69x10'3
3 19 7.68x10'3 4.22x10'3 4 14 5.34x10"1 7.68x10'5
3 20 1.36x10'3 7.70x10“1 4 15 4.90x10’4 7.72x10.4
3 21 1.15x10'3 NP. 4 16 1.54xlo'3 2.20x10’3
3 23 1.18x10'5 6.60x10'5 4 18 4.04x10'4 5.82x10'4
3 24 6.29x10'3 3.22x10'3 4 19 2.23x10'4 3.38x10’4
3 25 1.22x10'3 6.52x10'4 4 20 4.34x10'4 6.75x10'4
3 26 6.29xlo'3 3.22x10'5 4 21 4.95x104 NP-

3 28 1.17xlo'5 6.61x10'6 4 23 3.75x10'6 5.82x10'5
3 29 1.21x10'5 6.60x10'6 4 24 2.68x10'3 3.77x10'3
3 3o 7.69x10'4 4.11x10'4 4 25 2.36x10'3 3.45x10'3
3 31 1.17xlo'3 6.60x10'4 4 26 2.68x10'3 3.77x10'5
3 32 3.83x10'3 2.16x10'3 4 28 3.73x10'6 5.83x10'6
3 34 7.65x10'3 4.20x10'3 4 29 3.85x10'6 5.82x10'6
3 35 1.37x10'3 7.78x10'4 4 3o 2.23x10'5 3.30x10'5
3 36 1.64x10'2 8.15x10'3 4 31 3.73x10'4 5.82x10'4
3 37 7.26xio'2 3.75x10'2 4 32 2.77x10'3 4.28x10'3
3 39 4.64x10'3 2.93x10'4 4 33 2.43x10'3 3.63x10'3
3 4o 1.94xlo'3 1.32x10'3 4 34 2.22x10'4 3.36x10'4

Appendix 2.2 (con't)

 

Pre Post

Predator Prey Exchange Exchange
4 35 4.37x10'4 6.81x10'4
4 36 7.26x10'4 1.00x10'3
4 37 4.27x10'3 5.97x10'3
4 39 8.93x10'5 1.57x10'5
4 4o 8.64x1o'5 1.60x10'4
4 41 1.13x10'5 1.89x10'5
4 42 2.57x10'3 4.53x10'3
4 45 1.06x10'6 0

4 46 1.52x10'4 1.69x10'4
4 47 NP. 1.68x10'6
4 48 4.72x10'6 5.41x10'6
4 49 1.16x10'4 3.43x10'4
4 50 1.70x10'3 1.65x10'3
4 51 2.07x10'3 4.30x10'3
4 52 4.85x10'5 7.21x10'6
4 53 4.65x10'5 6.84x10'5
5 60 1.59x10'2 9.61x10'3
4 54 2.09x10'4 4.30x10'5
4 56 3.09xlo'4 2.02x10'3
4 57 1.03x10'6 3.73x10'4
4 58 7.75xlo'3 5.71x10'3
4 59 1.91x10'5 4.07x10'6
4 60 3.45xlo'3 5.20x10'3
4 61 2.02xlo'3 4.88x10'3
4 62 3.40x10'3 5.27x10'3
4 63 4.64x10'3 8.19x10'3
5 4 1.37x10'3 7.91x10'4
5 7 3.87x10’2 2.20x10’2
5 9 2.65x10'3 1.53x10'3
5 15 1.94xlo’4 1.22x10'4
5 16 2.04x10'3 1.17x10'3
5 18 1.61x10'4 9.26x10'5

 

Pre Post

Predator Prey Exchange Exchange
5 20 1.72x10’4 1.07x10’4
5 21 8.10x10'5 NP.

5 23 1.49x10'6 9.26x10'6
5 24 4.44xlo'4 2.50x10'4
5 26 4.44xlo'4 2.51x10'6
5 28 1.49x10'6 0

5 29 1.53x10'6 0

5 31 1.49x10'4 9.27x10'5
5 33 7.93x10'3 4.75x10'3
5 35 1.74xlo'4 1.08x10'4
5 36 1.84x10'l 1.02x10'1
5 37 1.18x10'l 6.63x10'2
5 39 6.17x10'2 4.30x10-3
5 4o 2.18x10'2 1.60x10'2
5 41 7.76xlo'3 5.15x10'3
5 42 7.20x10-2 5.06x10'2
5 43 4.69x10'2 3.50x10'2
5 44 NP. 4.57x10'3
5 45 6.05x1o'5 9.24x10"6
5 46 8.85x10'3 3.93x10'3
5 47 NP. 3.86x10'5
5 48 2.73xlo'4 1.25x10'4
5 49 6.66x10'3 7.88x10'3
5 50 9.83x10'2 3.83x10'2
5 51 1.20x10'l 9.97x10'2
5 52 2.81xlo'3 1.67x10'4
5 53 2.71x10'3 1.59x10'3
5 54 1.20x10'2 9.89x10’4
5 55 1.25x10'6 1.31x10'5
5 56 2.82x10'2 7.51x10'2
5 57 4.75x10'b 6.88x10'4
5 58 3.57x10'2 1.05x10'2

124

Appendix 2.2 (con't)
Pre Post Pre Post
Predator Prey Exchange Exchange Predator Prey Exchange Exchange

 

 

51 1.75x10'2 4.16x10'2
-4 .
52 4.09x10 6.98x10 5
-4 -4
53 3.92x10 6.63x10
-3 -4
54 1.76x10 4.15x10

59 8.72x10'5 7.46x10'6
45 1.21x10'4 3.58x10’5
61 9.33x10'3 9.02x10'3
62 1.58x10'2 9.79x10'3

63 2.16x10'2 1.52x10'2 56 4.21x10'3 3.15x10'2
4 2.01x10'4 3.31x10'4 58 5.24x10'3 4.42x10'3
7 5.66x10'3 9.18x10'3 59 1.29xlo'5 3.14x10'6
9 3.86x10'4 6.38x10'4 60 2.33x10'3 4.03x1o'3
15 2.84x10'5 5.12x10'5 61 1.36x10'3 3.78x10'3
16 2.95x1o'4 4.85x1o'4 62 2.30x10'3 4.09x10'3
18 2.35x10'5 3.87xlo'5 63 3.14x10'3 6.35x10'3

36 9.70x10'2 1.04x10"l
37 9.92x10'2 1.07x10'l

20 2.52x10'5 4.48x10'5
-5
21 1.20x10 N.P.

24 6.49x10'5 1.05x10'4 39 2.51x10'2 3.41x10'3
26 6.48x10'5 1.05x10'6 4o 1.16x10'2 1.66x10'2
31 2.17x1o'5 3.87x10'5 41 3.18x10'3 4.10x10'3
33 1.16x10'3 1.99x10'3 42 5.96x10'2 8.14xlo'2

46 1.75x10'2 1.50x10'2
47 NP. 1.50x10’4
48 5.42x10'4 4.81x10'4
49 1.34x10'2 3.05x10'2
5o 1.95x10'l 1.47x1o'l
51 2.38x1o'l 38le0'1
52 5.57x10'3 6.41x10‘4
53 5.33x10'3 6.07x10'3
54 2.40x10'2 3.83x10'3
55 2.47x10'6 4.99x10'5
57 1.67x10'5 4.67x10'3
58 1.25x10'l 7.16x10'2
59 3.08x10'4 5.11x10'5
60 5.58x10'2 6.52x10'2
61 3.26x10'2 6.11xlo'2

35 2.54x10'5 4.52x10'5
36 2.68x10'2 4.24x10'2
37 1.74x10'2 2.78x10'2
39 8.92x10'3 1.80x10'3
4o 3.19x10'3 6.74x10'3
41 1.13x10'3 2.16x10'3
42 1.05x10'2 2.11xlo'2
43 6.76x10'3 1.46x1o'2
44 NP. 1.90xlo'3
45 8.92x10'6 3.88x10'6
46 1.29x10'3 1.64xlo'3
47 NP. 1.62x10'5
48 3.98x10'5 5.23x10'5
49 9.82x10'4 3.31x10'3
50 1.43xlo'2 1.60x10'2

O‘GGO‘O\O\O\O‘GO‘O‘OQO‘GO‘O‘O‘O‘O‘O\O\O\O\O\O\O\MMUixltlt
\l\l\1\l\1\l\1\l\)\)\l\l\l\l\l\l\l\l\l\lQ9QO‘O‘QO‘O‘O‘O5QG

125

Appendix 2.2 (con‘t)

 

Pre Post

Predator Prey Exchange Exchange
7 62 5.49xio'2 6.59x10'2
7 63 7.50x10'2 1.03x10'1
8 7 1.84x10'2 1.61x10'2
8 14 1.95xlo'4 1.73x10'5
8 16 2.21x10'2 1.95x10'2
8 19 2.911.10'3 2.73x10'3
8 21 4.51x10'4 NP.

8 24 2.40xlo'3 2.09x10'3
8 26 2.40x10'3 2.09x10'5
8 3o 2.91x10’4 2.66x10.4
8 34 2.90x10'3 2.72x10'3
8 36 1.54x1o'l 1.31xlo'l
8 37 7.66x10'2 66le0'2
8 39 2.82x10'2 3.09x10'3
8 4o 1.84xio'2 2.12x10'2
8 41 3.62x10'3 3.74x10'3
8 42 4.52x10'2 4.98x10'2
8 44 NP. 8.48x10'4
8 45 8.54x10'6 2.01x10'6
8 46 1.21x10'3 8.32x10'4
8 47 NP. 8.41x10'°
8 48 3.76x10'5 2.68x10'5
8 49 9.41x10'4 1.72x10'3
8 so 1.36x10'2 8.15x10'3
8 51 1.66xlo'2 2.12x10'2
8 52 3.87x10'4 3.55x10'5
8 53 3.67x10'4 3.35x10'4
8 54 1.69x10'3 2.15x10'4
8 56 5.10x10'3 2.04x10'2
8 58 6.25x10'3 2.85x10'3
8 59 1.55x10'5 2.06x10'6
8 60 2.78x1o'3 2.60x10"3

 

Pre Post
Predator Prey Exchange Exchange
8 61 1.62x10'3 2.42x10'3
8 62 2.71x10'3 2.59x10'3
8 63 3.70x10'3 4.03x10'3
9 36 2.03x10'2 1.20x10'2
9 37 1.88x10'2 1.14x10'2
9 39 2.61x10'2 1.96x10'3
9 4o 2.41x10'3 1.92x10'3
9 41 3.30x10-3 2.36x10'3
9 42 1.14x10'2 8.61x10'3
9 45 3.65x10'5 6.00x10'6
9 46 5.29x10'3 2.52x10'3
9 47 NP. 2.51x10'5
9 48 1.63x10'4 8.06x10'5
9 49 4.02x10‘3 5.12x10'3
9 50 5.88x10'2 2.46x10"2
9 51 7.18x10'2 6.41x10'2
9 52 1.68x10'3 1.07x10’4
9 53 1.61x10'3 1.02x10'3
9 54 7.21x10'3 6.42x10'4
9 56 2.74x10'3 7.80x10'3
9 57 6.83x10'6 1.07x10'3
9 58 5.14x10'2 1.63x10'2
9 59 1.26x10'4 1.17x10'5
9 6O 2.29x10'2 1.49x10'2
9 61 1.34xlo'2 1.39x10'2
9 62 2.26xlo'2 1.50x10'2
9 63 3.08x10'2 2.34x10'2
10 36 4.69x10'4 5.01x10'4
10 37 3.51x10'4 3.76x10'4
10 39 5.75x10'4 7.85xlo'5
10 4o 5.59x10'5 7.95x10'5
10 41 7.33x10'5 9.41x10'5

126

Appendix 2.2 (con‘t)

 

 

Pre Post Pre Post
Predator Prey Exchange Exchange Predator Prey Exchange Exchange
10 42 2.09x10’4 2.86x10'4 12 43 8.97x10'3 1.31x10"2
10 43 6.83x10'4 1.00x10'3 12 44 NP. 5.40xlo'3
10 44 NP. 4.15x10'4 12 45 1.41x10'6 0
10 46 1.56xlo'5 1.34xlo'5 12 46 2.04x10‘4 1.75x10'4
1o 49 1.20x10-5 2.71x10'5 12 47 NP. 1.74x10'6
10 50 1.74x10'4 1.31x10.4 12 48 6.32xlo'6 5.59x10'6
10 51 2.13x10'4 3.41x10'4 12 49 1.56x10'4 3.55x10'4
10 52 4.97x10'6 0 12 5o 2.27x10'3 1.71xlo'3
10 53 4.75x10'6 5.44x10'6 12 51 2.78x10'3 4.45x10'3
10 54 2.15x10'5 3.40x10'6 12 52 6.50x10'5 7.46x10'6
11 36 2.89x10'4 3.13m“1 12 53 6.23x10'5 7.08x10'5
11 37 2.17x10'4 2.35x1o'4 12 54 2.80x10'4 4.45x10'5
11 39 3.54x10'4 4.90x10'5 13 36 4.62x10'3 4.70x10"3
11 4o 3.45x10'5 4.97xlo'5 13 37 3.44x10'3 3.53x10'3
11 41 4.52x10'5 5.88x10'5 13 39 5.70x10'3 7.36x10'4
11 42 1.29x10'4 1.79x10'4 13 4o 5.50xlo'4 7.46x10’4
14 4o 2.59x10'5 1.23x10'5 13 41 7.23x10'4 8.83x10'4
11 43 4.18x10'4 6.26x104 13 42 2.07x1o'3 2.69x10'3
11 44 NP. 2.60x10'4 13 43 6.77x10'3 9.39x10'3
11 46 9.61x10'6 8.40x10'6 13 44 NP. 3.89x10'3
11 49 7.42x10'6 1.70x10'S 13 45 1.07x10'6 0
11 so 1.07xlo'4 8.20x10'5 13 46 1.54x10'4 1.26x1o'4
11 51 1.31xlo'4 2.13x10'4 13 47 NP. 1.25xio'6
11 52 3.07x10'6 0 13 48 4.77x10'6 4.02xio'6
11 53 2.92x10’6 3.40x10'6 13 49 1.18xlo'4 2.55x10'4
11 54 1.33x10'5 2.13x10'6 13 50 1.72xlo'3 1.23x10'3
12 36 6.12x10'3 6.53x10'3 13 51 2.10x10'3 3.20x10'3
12 37 4.56xlo'3 4.92x10'3 13 52 4.90x10'5 5.36x10’6
12 39 7.54x10'3 1.02x10'3 13 53 4.70x10'5 5.09x10'5
12 4o 7.29x10'4 1.04x10'3 13 54 2mm“1 3.19x10'5
12 41 9.57x10'4 1.23x10'3 14 36 2.17x10'4 7.73x1o‘5
12 42 2.74xlo'3 3.74xlo'3 14 37 2.03xlo'4 7.27xlo'5

127

Appendix 2.2 (con't)

 

Pre Post
Predator Prey Exchange Exchange
14 39 2.77x10’4 1.26x10'5
16 53 6.04x111'3 1.76x10'3
14 41 3.53x10'5 1.51x10'5
14 42 1.21x1o’4 5.52x10'5
14 46 5.64x10'5 1.62x10'5
14 48 1.75x10'6 0
14 49 4.33x10'5 3.27x10"5
14 50 6.29x10.4 1.58x10'4
14 51 7.68xlo'4 4.12x10'4
14 52 1.80x10'5 0
14 53 1.71x10'5 6.55x10'6
14 54 7.78x10'5 4.10xlo'6
14 56 2.98x10'S 4.99x10'5
14 58 5.52x10’4 1.04x10'4
14 59 1.36x10'6 0
14 60 2.45x10'4 9.53x10'5
14 61 1.43x10'4 8.93xio'5
14 62 2.41x10'4 9.66x10'5
14 63 3.29x10'4 1.50x10'4
15 5 4.68x10’4 5.94x10“1
15 6 4.80x10'4 6.05x10'4
15 7 4.88x10’4 5.79x10'4
15 8 5.59x10'4 7.15x1o'4
15 10 1.02x10'5 1.35xlo’5
15 11 9.94x10'6 1.32x10'5
15 12 1.01x10'4 1.39x10'4
15 13 1.03x10'4 1.37xlo'4
15 14 4.83x10'5 5.82xlo'6
15 16 7.18xlo'5 8.59x10’5
15 36 8.65x10'3 9.96xlo'3
15 37 1.30x10'2 1.52x10'2
15 38 1.69x10'5 2.11xlo'S

 

Pre Post
Predator Prey Exchange Exchange
15 39 1.25x10'2 1.88x10'3
15 4o 1.05x10'3 1.65x10'3
15 41 1.63x10'3 2.30x10'3
15 42 7.50x10'3 1.13x10'2
15 43 5.79xlo’3 9.43x10'3
15 44 NP. 8.40xlo'3
15 76 3.16x10'3 3.95x10’3
16 39 1.52xlo'3 5.30xlo'5
16 41 1.92x1o'4 6.36x10'5
16 45 1.35x10'4 1.03x10'5
16 46 1.97x10'2 4.35x10'3
16 47 NP. 4.31x10'5
16 48 6.10x10'4 1.39x10'4
16 49 1.49x1o'2 8.79x1o'3
16 50 2.19x10'l 4.25x10'2
16 51 2.68xlo'l 1.11x1o'l
16 52 6.26ir10'3 1.85x10'4
16 54 2.68x10'2 1.10x10'3
16 55 2.78x10'6 1.45x10'5
16 56 2.38x10'3 3.14x1o'3
16 57 4.18x1o'S 3.02x10"3
16 58 3.15x1o'l 4.62x10'2
16 59 7.69x10'4 3.28x10'5
16 60 1.40x10'1 4.21x10’2
16 61 8.20x10'2 3.95x10'2
16 62 1.39x10'l 4.28x10'2
16 63 1.89x10’l 6.65x1o'2
16 66 2.46x10-1~ 6.73x10'2
16 67 2.46x10'l 6.73x10'2
16 68 2.46x10'2 6.73x10'3
16 69 2.46x10'l 6.73xlo'2
16 7o 2.46x10'l 6.73x10'3

128

Appendix 2.2 (con't)

 

 

Pre Post Pre Post
Predator Prey Exchange Exchange Predator Prey Exchange Exchange
16 71 2.46x10'l 6.73x10'2 18 4o 1.08x111'3 1.65xlo'3
17 36 4.13x10'6 6.87x10.4 18 41 1.70x10'3 2.34x10'3
17 37 6.10x10'6 1.03xlo'3 18 42 7.89xlo'3 1.16x10’2
17 42 3.70x10'6 7.84x1o'4 18 43 6.21x10'3 9.83x1o'3
17 46 1.79x10'5 2.39x10'3 18 44 NP. 8.96x10'3
17 47 NP. 2.36x10'5 18 76 3.40xlo'3 4.25x1o'3
17 49 1.35xlo'5 4.82x10'3 19 3 7.52xlo’4 6.31x10'4
17 50 1.99x10'4 2.34xio'2 19 4 7.87x10'4 5.36x104
17 51 2.43x10’4 6.08x10'2 19 5 9.17x10'3 6.56x10'3
17 52 5.68x10'6 1.02x10'4 19 6 9.39x1o'3 6.68x10'3
17 53 5.49x1o'6 9.70x1o'4 19 7 7.63x10'3 5.13x10'3
17 54 2.43x10'5 6.04x10'4 19 8 4.33x10'3 3.13xlo'3
17 56 5.30x10'6 4.24x10'3 19 9 3.78x10'3 2.58x10'3
17 58 1.04xlo'4 9.21x10'3 19 10 4.04xlo'4 3.110x10'4
17 60 4.61xlo’5 8.40x10'3 19 11 3.95xlo'4 2.94x10'4
17 61 2.70x10'5 7.88x1o'3 19 12 4.00x10-3 3.09x10'3
17 62 4.57x10'5 8.54x10'3 19 13 4.08x10'3 3.04x10'3
17 63 6.24x10'5 1.33x10'2 19 14 5.29x10'4 3.61x10'5
18 5 4.87x10'4 6.11x10'4 19 15 5.57x10'4 4.18xlo'4
18 6 4.98x1o'4 6.22x10.4 19 16 2.88x10'3 1.94x10‘3
18 7 5.07x10'4 5.97x10'4 19 18 4.59x10’4 3.13x10“t
18 8 5.76x10'4 7.24x10’4 19 19 2.42x10'4 1.74x10'4
18 10 1.07x10'5 1.40x10'5 19 20 4.93x10'4 3.64x10’4
18 11 1.05x10'S 1.37x10'5 19 21 4.70x10"5 N.P.
18 12 1.06x10“t 1.44x10'4 19 22 6.41xlo'4 4.56xio'4
18 13 1.08x10'4 1.42x111’4 19 23 4.26x10'6 3.13xlo'5
18 14 5.02x10'5 6.00x10'6 19 24 2.54x10’4 1.69x10'4
18 16 7.62x10'5 9.14xlo'5 19 25 8.88x10'4 6.16x10'4
18 36 9.03x10'3 1.04x10'2 19 26 2.54xlo'4 1.69x10'6
18 37 1.33x10'2 1.53x10'2 19 28 4.24x10'6 3.13xlo'6
18 38 1.78x10'5 2.20xlo'5 19 29 4.37x10'6 3.1'3x1o'6
18 39 1.33x10'2 1.95x10'3 19 3o 2.43x10'5 1.70x10'S

129

Appendix 2.2 (con‘t)

 

 

Pre Post Pre Post
Predator Prey Exchange Exchange Predator Prey Exchange Exchange
19 31 4.24x10'4 3.13x10'4 21 46 2.69x10'4 N.P.
19 32 7.97x10'4 5.85x10'4 21 48 8.45x1o'6 hip.
19 33 91le0'4 6.50x10'4 21 49 2.23x10’4 NF.
19 34 2.41xlo“1 1.73x10'4 21 so 3.06x10'3 N.P.
19 35 4.97xlo'4 3.68x10'4 21 51 3.73x10'3 N.P.
19 39 1.45xlo'3 1.21x10'4 21 52 8.74xio'S hip.
19 41 1.85x10'4 1.46x10'4 21 53 7.92x10's N.P.
20 5 2.53x10'3 2.97xio'3 21 54 4.00x10'4 MP.
20 6 2.60x10"3 3.03x10'3 21 56 3.40x10'4 NP.
20 7 2.64x10'3 2.90x10'3 21 58 1.17x10'5 NR
20 8 3.01x10'3 3.55x1o'3 21 60 5.20x1o'6 N.P.
20 10 5.55x10'5 6.79xlo'5 21 61 2.99x10'6 hip.
20 11 5.43x10'5 6.65x10'5 21 62 4.88x10'6 N.P.
20 12 5.50x10'4 7.01x10'4 21 63 6.66x10-6 N.P.
20 13 5.61x10'4 6.88x1o'4 22 36 1.82x10'2 9.29x10'3
20 14 2.61x10'4 2.92x10'S 22 37 2.75x10'2 1.43x10'2
20 16 3.95x10'4 4.39x10‘4 22 38 2.40x10'3 1.32x10'3
20 36 4.70x10'2 5.03x10'2 22 39 1.47x10'3 9.73x10'5
20 37 6.95xlo'2 7.53x10"2 22 4o 2.18x10"3 1.51x10"3
20 38 9.23x10'5 1.1i7xio'4 22 41 1.90x10“t 1.18x10-4
20 39 6.89x10'2 9.48x1o'3 22 42 1.62x10'2 1.07x10'2
20 4o 5.63x10'3 8.13x10'3 22 43 2.61x10'2 1.86x10'2
20 41 8.84x10'3 1.15xlo'2 22 44 NP. 3.04x10'2
20 42 4.10x10'2 5.66xio’2 22 72 22le0'2 1.13xlo'2
20 43 3.21xlo'2 4.76x10'2 22 73 6.66x10-2 3.40x10'2
20 44 NP. 4.29xlo'2 22 74 22le0'3 1.13x10'3
20 76 1.75x10'2 2.03x10'2 22 76 2.59x10'3 1.43x10'3
21 4 1.04x10'5 N.P. 23 5 2.46x10'6 3.67xlo'5
21 7 1.00x10'5 NR 23 6 2.51x10'6 3.74xio'5
21 9 9.91xlo'6 hip. 23 7 2.56x10'6 3.59x10'5
21 16 7.16x10'6 N.P. 23 8 2.90x10'6 4.36x10'5
21 45 2.02x10'6 NF. 23 36 4.56x10'5 6.23xlo’4

130

Appendix 2.2 (con‘t)

 

 

Pre Post Pre Post
Predator Prey Exchange Exchange Predator Prey Exchange Exchange
23 37 6.65xlo'5 9.21x10'4 25 15 7.13x10'3 1.43x10'2
23 39 6.75x1o'5 1.17xlo’4 25 16 2.08x10'3 3.78x10'3
23 4o 5.43x10'6 9.93xlo'5 25 18 5.84x10'3 1.07x10'2
23 41 8.57x10"6 1.41m"4 25 20 6.29x10'3 1.25x10'2
23 42 4.00x10'5 6.99x10'4 25 21 8.69x10'5 NF.
23 43 3.17x10'5 5.90x1o'4 25 23 5.40xlo'S 1.07x10'3
23 44 hip. 5.37x10'4 25 24 4.62x1o’4 8.27x10'4
23 76 1.73x10'5 2.54x10'4 25 26 4.62x10'4 8.27x1o'6
24 4 6.31x10'5 9.93xio'4 25 28 5.38x10'5 1.07x1o'4
24 7 6.12x10'5 9.51x10'4 25 29 5.55xlo'5 1.07x10’4
24 9 6.06x10'5 9.58x10'4 25 31 5.38xlo’3 1.07x10'2
24 14 6.06x10'6 9.56x10'6 25 32 2.90x1o'3 5.72x10'3
24 16 4.64x10'5 7.30x10'4 25 33 8.35x1o'3 1.59xlo'2
24 45 1.17x10'5 4.86x10'5 25 35 6.34x10'3 1.26x10'2
24 46 1.69xlo’3 2.06x10'2 25 36 7.87x10’2 1.38x10'l
24 47 hip. 2.03x10'4 25 37 3.95x10'2 7.02x10'2
24 48 5.24x10'5 6.57xlo'4 25 39 1.34x10'2 3.03x10'3
24 49 1.29x10'3 4.15x10'2 25 4o 9.44x10'3 2.23x10'2
24 50 1.88x10-2 2.01x10'1 25 41 1.72x10'3 3.66xlo'3
24 51 2.30x10'2 5.24x10'l 25 42 2.33x10'2 5.28x10'2
24 52 5.38x10'4 8.78x10.4 25 43 2.17x10'3 5.26x10'3
24 53 5.17xlo’4 8.35x10'3 25 44 NP. 3.63x10'2
24 54 2.31x10'3 5.20x10'3 25 46 9.98x10'5 1.41x10’4
24 56 1.85xlo'3 1.33x1o'l 25 47 hip. 1.42x10'6
24 58 6.94x10'5 5.59x10'4 25 48 3.10x10'6 4.54x10'6
24 60 3.09x10'5 5.10x10'4 25 49 7.76x10'5 2.90xlo'4
24 61 1.81x10'5 4.79x10'4 25 50 1.12x10'3 1.38xlo'3
24 62 3.05x10'5 5.19x10'4 25 51 1.36x10'3 3.59x10'3
24 63 4.16x10'5 8.07x10'4 25 52 3.19xlo'5 6.02x10'6
25 7 9.27x10-2 1.67x10'l 25 53 3.02x10'5 5.67x10'5
25 9 4.13xlo'3 7.56x10'3 25 54 1.39x10'4 3.64xlo'S
25 14 7.80x10'4 1.43x10'4 26 4 4.66x10'5 0

131

Appendix 2.2 (con't)

 

Pre Post
Predator Prey Exchange Exchange
26 7 4.52x10'5 0
26 9 4.48x10'5 0
26 14 4.48x10'6 0
26 16 3.42x10'5 0
26 45 8.65x10'6 0
26 46 1.25x10'3 1.28x10'5
26 48 3.87x10'5 0
26 49 9.53xlo'4 2.59x1o'5
26 so 1.39x10'2 1.25x10'4
26 51 1.70x10'2 3.25xlo'4
26 52 3.97x10'4 0
26 53 3.81xlo’4 5.18x10'6
26 54 1.71xlo'3 3.24x10'6
26 56 1.37xio'3 8.28x10'5
26 58 5.13x10'5 0
26 60 2.28x10'5 0
26 61 1.34x10'5 0
26 62 2.25x10-5 0
26 63 3.07x10'5 0
27 7 hip. 1.97xlo’4
27 36 hip. sound3
27 37 hip. 4.05xio'3
27 39 hip. 1.02x1o'4
27 40 NP. 1.28xio'3
27 41 NP. 1.23x10'4
27 42 hip. 3.06xlo'3
27 43 hip. 9.42xlo'3
27 44 hip. 9.27x10'3
27 46 hip. 8.35xlo'6
27 49 hip. 1.70xlo'5
27 so hip. 8.16x1o’5
27 51 NP. 2.12x10'4

 

Pre Post
Predator Prey Exchange Exchange
27 53 NP. 3.37x10'6
27 54 hip. 2.14x1o'6
28 5 1.21x1o'6 3.42xio’6
28 6 1.24x1o'6 3.48xlo’6
28 7 1.26xlo'6 3.34xlo'6
28 8 1.43xio'6 4.06x10.6
28 36 2.24x10'5 5.80xlo'5
28 37 3.28x10'5 8.58x10’5
28 39 3.30x10'5 1.09m”5
28 4o 2.67xlo'6 9.26xlo'6
28 41 4.21x10'6 1.31x10'5
28 42 1.96xlo'5 15.51x10'5
28 43 1.54x10'5 5.50x10'5
28 44 hip. 5.00:.10'5
28 76 8.44xio'6 2.37x10'5
29 5 4.08x10'6 4.92x10'6
29 6 4.18xlo'6 5.01xlo'6
29 7 4.25x10'° 4.81x10'6
29 8 4.81xlo'6 5.84x10'6
29 36 7.57xio'5 8.36x10'5
29 37 1.11x10'4 1.23xio'4
29 39 1.12xio'4 1.57xlo'5
29 4o 9.02x10'6 1.33x10'S
29 41 1.42x10'5 1.89xlo'5
29 42 6.64x10’5 9.36x1o'5
29 43 5.25xio'5 7.92x10'5
29 44 hip. 7.21x10'5
29 76 2.87x10'5 3.42xlo'5
3o 3 7.50x10'5 sand5
30 4 7.84xlo'5 5.62xlo'5
3o 5 9.14x10'4 6.88x10'4
3o 6 9.35x10'4 7.01x1o'4

132

Appendix 2.2 (con't)

 

Pre Post
Predator Prey Exchange Exchange
30 7 7.61xlo'4 5.38x10'4
3o 8 4.31x10'4 3.28xio'4
3o 9 3.77x10'4 2.71xlo'4
3o 10 4.02x10'5 3.15x10'5
3o 11 3.94x10'5 3.09xlo'5
3o 12 3.99xlo'4 3.25xlo'4
3o 13 4.06x10'4 3.19xlo'4
3o 14 5.27xlo'5 3.78x10'6
3o 15 5.55x10'5 4.37xlo'5
3o 16 2.87x10'4 2.04xlo4
3o 18 4.58x10'5 3.28x10'5
3o 19 2.41xlo'5 1.82xio'5
3o 20 4.91xlo'5 3.82x10'5
3o 21 4.69xio'6 hip.
30 22 6.39x10'5 4.79xlo'5
3o 24 2.53xlo'5 1.78xlo'5
3o 25 8.85x10'5 6.46x10'5
3o 26 2.53x10'5 0
30 3o 2.42x10'6 1.78x10'6
3o 31 4.22xlo'5 3.29x10'5
3o 32 7.94xlo'5 6.13xlo'5
3o 33 9.09x10'5 6.80x10'5
3o 34 2.40x10'5 1.82xio'5
3o 35 4.95x10'5 3.86xlo'5
3o 39 1.45xlo'4 1.27xlo'5
3o 41 1.84xlo'5 1.53x10'5
31 5 2.41xio'4 3.65x10'4
31 6 2.47xlo'4 3.72x10'4
31 7 2.51xlo’4 3.57x10'4
31 8 2.84x1o'4 4.34xlo’4
31 10 5.32x10'6 8.36xlo'6
31 11 5.21x10'6 8.2ox10'6

 

Pre Post
Predator Prey Exchange Exchange
31 12 5.27x10's 8.63x10'5
31 13 5.37x10'5 8.47x10'5
31 14 2.49x10'5 3.59x10'6
31 16 3.80x10'S 5.45xlo'5
31 36 4.48x10'3 6.20x10'3
31 37 6.52x10'3 9.16x10'3
31 38 8.82x10'6 1.31x10'5
31 39 6.63x10'3 1.17x1o'3
31 4o 5.33x10‘4 9mm“1
31 41 8.41x10’4 1.40.110'3
31 42 3.93x10'3 6.95x10'3
31 43 3.11x10'3 5.87x10'3
31 44 hip. 5.34xlo'3
31 76 1.70x10'3 2.53x10'3
32 4 1.37x10'2 1.92x10'2
32 5 1.27xlo'2 1.88xlo’2
32 6 1.30xlo'2 1.92x10'2
32 7 9.11x10'2 1.26x10'l
32 9 2.62x10'2 3.70x10'2
32 15 1.94x10'3 3.01x10'3
32 16 2.97x10'2 4.16x10'2
32 18 1.59x1o'3 2.24x10'3
32 19 1.26x10'2 1.87x10'2
32 20 1.71xlo'3 2.62xlo'3
32 23 1.47xlo'5 2.25x10’4
32 28 1.46x10'5 2.25x10'5
32 29 1.51xlo'5 2.24xlo'5
32 3o 1.26xlo'3 1.82x1o'3
32 31 1.46xlo'3 2.25x1o’3
32 34 1.25xlo'2 1.86x10'2
32 35 1.73xlo'3 2.64x10'3
32 36 1.13xlo'2 1.52x1o'2

133

Appendix 2.2 (con't)

 

 

Pre Post Pre Post
Predator Prey Exchange Exchange Predator Prey Exchange Exchange
32 37 8.52x10'3 1.17xlo'2 33 61 1.21xlo'5 2.42x10'5
32 39 8.23x10'2 1.43x10'2 33 62 2.02x10'5 2.58xio'5
32 4o 1.35x10'3 2.47xlo'3 33 63 2.76xlo'5 4.02x10'5
32 41 1.06x10'2 1.73x10'2 34 3 7.73x1o'4 1.05xlo'3
32 42 5.03x10'3 8.77x1o'3 34 4 8.08x10'4 8.92x10'4
32 43 2.83x10'3 5.30x10"3 34 5 9.42x1o'3 1.09xio'2
32 44 hip. 1.68x10'2 34 6 9.64x10’3 1.11xlo'2
32 46 1.30x10'4 1.42xio'4 34 7 7.84x10'3 8.54x10'3
32 47 hip. 1.43x1o'6 34 8 4.44xlo'3 5.19xio'3
32 48 4.05x1o'6 4.57x1o'6 34 9 3.88x10'3 4.30xlo'3
32 49 1.01xlo'4 2.93x10'4 34 1o 4.15xio'4 5.00x104
32 so 1.46x10'3 1.39x10'3 34 11 4.06x10'4 4.90x10'4
32 51 1.78xlo'3 3.62x10'3 34 12 4.11xio'3 5.16x10'3
32 52 4.17xlo'5 6.06x10'6 34 13 4.19xio'3 5.06xlo'3
32 53 3.95x10'5 5.71x10'S 34 14 5.44x10'4 6.01x10'5
32 54 1.82x1o'4 3.67x1o'5 34 15 5.71x10'4 6.93x10'4
33 36 4.02xlo'2 4.56x10’2 34 16 2.97x10'3 3.25x10'3
33 37 2.25xio'2 2.60x10-2 34 18 4.72x10'4 5.21x10”4
33 39 4.15x10'4 6.07x10'5 34 19 2.49xlo'4 2.89xlo’4
33 4o 4.82x10'3 7.43x10'3 34 20 5.06x10'4 6.06xlo’4
33 41 5.33x10'5 7.37xio‘5 34 21 4.83x10'S hip.
33 42 1.32x10'2 1.95xlo'2 34 22 6.59x10'4 7.61x10'4
33 46 7.53x10'5 6.90xlo'5 34 23 4.37xio'6 5.22x10'5
33 48 2.34x1o'6 2.23x10'6 34 24 2.61x10'4 2.82x10“t
33 49 5.88x10'5 1.43x10'4 34 25 9.11x10'4 1.02xlo'3
33 50 8.44x10'4 6.76xio'4 34 26 2.61x10'4 2.82x10'6
33 51 1.03xlo'3 1.76x10'3 34 28 4.35x10’6 5.22x10'6
33 52 2.41x10"5 2.95x10"6 34 29 4.49xlo'6 5.22x10'6
33 53 2.28x10'5 2.77x10’5 34 3o 2.49x10’5 2.83xlo'5
33 54 1.06x10'4 1.79xlo'5 34 31 4.35xio'4 5.22x10'4
33 58 4.68x10'5 2.84xlo'5 34 32 8.18x10'4 9.72x10'4
33 60 2.08x10'5 2.59x10'5 34 33 9.37xlo'4 1.08x10'3

134

Appendix 2.2 (con't)

 

Pre Post
Predator Prey Exchange Exchange
34 34 2.48xlo'4 2.88x10'4
34 35 5.10xio'4 6.11x10'4
34 39 1.49xlo'3 2.02x10'4
34 41 1.90x10'4 2.43m“1
35 5 1.93xlo'3 2.47x10'3
35 6 1.98xlo'3 2.51x10'3
35 7 2.01x10'3 2.41x10'3
35 8 2.29x10'3 2.95xlo'3
35 10 4.24xlo'5 5.62xlo'5
35 11 4.14x10'5 5.51x10'5
35 12 4.20x10'4 5.81xlo'4
35 13 4.28x10'4 5.70x10'4
35 14 1.99x1o'4 2.42x10’5
35 16 3.01x10'4 3.63x1o'4
35 36 3.58x10'2 4.16x10'2
35 37 5.30x10'2 6.24x10'2
35 38 7.04x10'5 8.82x10'5
35 39 5.25xlo'2 7.86x10'3
35 4o 4.30x10-3 6.75x10'3
35 41 6.74xio'3 9.50x10'3
35 42 3.12x10'2 4.69x10'2
35 43 2.44xio'2 3.94xlo'2
35 44 hip. 3.55x10'2
35 76 1.34xlo'2 1.68xlo'2
36 36 1.53x10'l 1.37x1o'l
36 4o 1.87xlo'2 2.31x10'2
36 73 3.47xlo'I 3.13x10'l
36 74 2.35x10'l 2.11xlo'l
36 76 5.82x10'l 5.73xio'l
37 66 3.88xlo'l 3.61x10'l
37 67 3.88xio'l 3.61xlo'l
37 68 3.88x10'2 3.61x10'2

 

Pre Post
Predator Prey Exchange Exchange
37 69 3.88x10'l 3.61x10'l
37 7o 3.88x10'l 3.61x1o'2
37 71 3.88x10'l 3.61x10'l
37 74 1.31x10'l 1.22x10'l
37 76 1.93x10'l 2.00x10'1
38 67 3.37x10'3 2.69x10'3
38 7o 3.37x10'3 2.69x10'4
38 76 6.90xlo'3 6.03x1o'3
38 77 9.76x10'4 8.11xlo'4
39 36 7.27x10"3 3.21x10'3
39 37 4.62x10'2 2.10x10'2
39 38 6.84x10’4 3.27x10'4
39 39 2.26xio'2 1.30x10'3
39 4o 8.78x10’4 5.37x10'4
39 41 2.93x10'3 1.59x10'3
39 42 2.68x10'2 1.55x10'2
39 43 3.61xlo'3 2.25xlo'3
39 45 3.29x10'6 0
39 46 4.57x10’4 1.63x10'4
39 47 hip. 1.70xlo'6
39 48 1.43xio'5 5.34x10.6
39 49 3.62x10'4 3.48x10'4
39 50 5.15x10'3 1.60x10'3
39 51 6.28xlo'3 4.17x10'3
39 52 1.47x10'4 7.00x10'6
39 53 1.38x10'4 6.50x10'5
39 54 6.51x10'4 4.36x10'5
39 58 2.11x10'3 wand4
39 59 5.30x10'6 0
39 6O 9.39x10'4 4.61x10'4
39 61 5.45xlo'4 4.26x10'4
39 62 9.06x10'4 4.50xlo’4

135

Appendix 2.2 (con't)

 

Pre Post
Predator Prey Exchange Exchange
39 63 1.24x10"3 7.00x10'4
39 64 3.93x10'3 1.68x10'3
39 65 5.41x10'3 2.47x10'3
39 66 5.82x10'4 2.49xlo'4
39 67 5.82xlo'4 2.49x10’4
39 68 5.82x10'5 2.49x10'5
39 69 5.82x10'4 2.49x10'4
39 7o 5.82x10'4 2.49x1o'5
39 71 5.82xlo'4 2.49x10'4
39 72 8.73xlo'3 3.74xlo'3
39 73 1.92xlo'l 8.22xio'2
39 74 6.11xio'2 2.62x1o'2
39 76 8.21x10'2 3.88xlo'2
4o 36 2.05x10'2 3.76xlo'2
4o 40 2.53x10"3 6.58x10'3
4o 73 4.54x10'2 8.05xlo'2
4o 74 3.06x10'2 5.43x10'2
4o 76 7.68x10'2 1.53x10'l
41 36 4.31x10'3 6.18xlo'3
41 37 27le0'2 4.00x10'2
41 38 4.06xlo'4 6.29x10'4
41 39 1.34.110"2 2.50xlo'3
41 4o 5.19xlo'4 1.02xio'3
41 41 1.73x10'3 3.05x1o'3
41 42 1.59xio'2 2.97x1o'2
41 43 2.15x10'3 4.32xio'3
41 45 1.94x10'6 0
41 46 2.72x10'4 3.14x10'4
41 47 hip. 3.24xlo'6
41 48 8.45x10'6 1.02x10’5
41 49 2.13x10'4 6.61x10-4
41 so 3.05x10'3 3.08x10'3

 

Pre Post
Predator Prey Exchange Exchange
41 51 3.72x1o'3 8.02:110'3
41 52 8.70x10’5 1.34x10'5
41 53 8.19xlo' 1.26x104
41 54 3.83x10'4 8.29xlo'5
41 58 1.25xlo'3 9.65x10'4
41 59 3.12x10'6 0
41 60 5.55x10'4 8.79x104
41 61 3.22x10'4 8.16x1o'4
41 62 5.37x10'4 8.66x10'4
41 63 7.33x10’4 1.3sx10'3
41 64 2.35xlo'3 3.31x10'3
41 65 3.22x10'3 4.78xlo'3
41 76 4.90xlo'2 7.54x10'2
42 67 2.80x10'l 5.16x10'l
42 7o 2.80xio’l 5.16x10'2
42 74 3.15x10'2 5.80xlo'2
42 76 4.53x10'2 9.36xlo'2
43 72 6.31x10'2 9.00xlo'2
43 73 4.21x10'2 6.00x10'2
43 74 6.31x10' 9.00x10'2
43 76 4.93xlo'2 7.92xlo'2
44 66 hip. 1.51xlol
44 67 hip. 1.51x10l
44 68 hip. 1.51
44 69 hip. 1.51xiol
44 7o hip. 1.51
44 71 hip. 1.51xlol
44 75 hip. 2.788101
44 77 hip. 2.24x10l
45 66 1.76x10'3 5.92x1o'4
45 67 1.76x10'3 5.92x10'4
45 68 1.76x10'4 5.92x1o'5

136

Appendix 2.2 (con't)

 

Pre Post
Predator Prey Exchange Exchange
45 69 1.76x10'3 5.92x10'4
4s 70 1.76x10'3 5.92x10'5
45 71 1.76x10'3 5.92x10'4
45 75 1.17x10'3 3.95x10'4
46 66 4.36x10'l 3.95x10'l
46 67 4.36x10'l 3.95x10'l
46 68 4.36x10'2 3.95x10'2
46 69 4.36x10’l 3.95x10'l
46 7o 4.36x10'l 3.95x10'2
46 71 4.36x10'l 3.95x10'l
46 75 2.90.110'1 2.63x10'l
47 66 hip. 2.47x10'3
47 67 hip. 2.47x10'3
47 68 hip. 2.47x10'4
47 69 hip. 2.47x10'3
47 70 hip. 2.47x10'4
47 71 hip. 2.47x10'3
47 75 hip. 1.65x10'3
48 66 1.20x10"2 9.88x10'3
48 67 1.20x10'2 9.88x10’3
48 68 1.20x10'3 9.88x10'4
48 69 1.20x10'2 9.88x10'3
48 70 1.20x10'2 9.88x10'4
48 71 1.20x10'2 9.88x10'3
48 75 8.03x10'3 6.59x10'3
49 66 1.90x10'l 4.88x10'l
49 67 1.90x10'l 4.88x10'l
49 68 1.90x10'2 4.88x10'2
49 69 1.90x10'l 4.88x10'l
49 70 1.90x10'l 4.88x10'2
49 71 1.90x10'l 4.88x10'l
49 75 1.27x10'l 3.25x10"l

 

Pre Post
Predator Prey Exchange Exchange
50 66 4.96 4.27
so 67 4.96 4.27
so 68 4.96.110'1 4.27x10'l
so 69 4.96 4.27
so 70 4.96 4.27x10'1
50 71 4.96 4.27
so 75 3.31 2.85
51 66 6.06 1.11x10l
51 67 6.06 1.11.110l
51 68 6.06x10'l 1.11
51 69 6.06 1.11x10l
51 70 6.06 1.11
51 71 6.06 1.11x10l
51 75 4.04 7.4
52 66 1.42x10'l 1.86x10'2
52 67 1.42x10'l 1.86x10'2
52 68 1.42x10’2 1.86x10'3
52 69 1.42x10'l 1.86x10'2
52 70 1.42x10'l 1.86x10'3
52 71 1.42x10'l 1.86x10'2
52 75 9.45x10'2 1.24x10'2
53 66 1.72x10'l 1.95x10'l
53 67 1.72xlo'l 1.95x10'l
53 68 17le0'2 1.95x10'2
53 69 1.72x10'l 1.9sx10"
53 70 1.72x10'l 1.95x10'2
53 71 1.72x10'l 1.95x10'l
s3 75 1.15x10'l 1.30x10'I
s4 66 3.42x10'l 6.12x10'2
54 67 3.42x10'l 6.12x10'2
s4 68 3.42x10'2 6.12x10'3
54 69 3.42x10'l 6.12x10’2

137

Appendix 2.2 (con't)

 

 

Pre Post Pre Post
Predator Prey Exchange Exchange Predator Prey Exchange Exchange
54 70 3.42x10'l 6.12x10'3 57 65 3.57x10'4 8.54x10'2
54 71 3.42x10'1 6.1211102 57 68 8.30x10'6 1.89x10'3
54 75 2.28x10'l 4.08x10'2 57 69 8.30x10"5 1.89x10'2
55 66 6.19x10'4 1.60x10’3 57 70 8.30x10’5 1.89x10’3
55 67 6.19x10'4 1.60x10'3 57 71 8.30x10'5 1.89x10'2
55 68 6.19x10'5 1.60x10'4 58 46 1.44 6.78x10'l
55 69 6.19x10'4 1.60x10'3 58 48 4.53x10'2 2.24x10'2
55 7o 6.19x10'4 1.605.104 58 53 4.26x10'l 2.69x10'l
55 71 6.19x10’4 1.60x10'3 58 55 2.08x10'4 2.21x10'3
55 75 4.13x10'4 1.07x10'3 58 60 3.54x10'l 1.58x10'l
56 46 1.95x10'3 5.54x10'3 58 62 3.33x10'l 1.53x10'1
56 48 6.18x10'5 1.81x10'4 58 63 4.55x10'l 2.38x10'l
56 49 1.68x10'3 1.18x10'2 58 64 1.87 8.68x10’l
56 50 2.24x10'2 5.45x10'2 58 65 2.68 1.31
56 51 2.74.110'2 1.42x10'l 58 68 6.24x10'2 2.89x10'2
56 52 6.41x10‘4 2.37x10“1 58 69 6.24x10" 2.89x10'1
56 53 5.65x10'4 2.21x10'3 58 70 6.24x10'l 2.89x10'2
s6 54 3.02x10'3 1.48x10'3 58 71 6.24x10'l 2.89xlo'l
56 58 5.89x10'3 1.16x10'2 59 2 3.63:.10'3 4.45x10'4
56 59 1.54x1o'5 8.57x10'6 59 3 3.31x10'3 4.96x10'4
56 60 2.62x10'3 1.06x10'2 59 5 3.22x10’3. 4.04x10'4
56 61 1.49x10'3 9.81x10'3 59 6 3.31x10'3 4.13x10'4
56 62 2.40x10'3 1.04x10'2 59 10 4.16x10'4 5.47x10'5
56 63 3.28x10'3 1.61x10'2 59 11 4.05x10'4 5.35x10'5
56 64 3.59x10'4 1.51x10’3 59 12 4.12x10'3 5.67x10’4
57 46 l.92x10"4 4.43x10'2 59 13 1.40x10'3 1.85x10'4
57 48 6.02x1o'6 1.46x10'3 59 20 1.75x10'3 2.27x10’4
57 53 5.67xlo'5 1.75x10'2 59 32 1.77x10'3 2.28x10'4
57 60 4.70x10'5 1.03x10'2 60 46 6.41x10'1 6.22x10'l
57 62 4.43x10'5 9.97x10'3 6O 48 2.02x10'2 2.05x10'2
57 63 6.05x10'5 1.55x10'2 6O 53 1.89x10'l 2.46x10'l
57 64 2.49x10'4 5.67x10'2 6O 55 9.25x10'5 2.03x10'3

138

Appendix 2.2 (con't)

 

Pre Post
Predator Prey Exchange Exchange
60 62 4.65x10'l 4.60x10'l
60 64 8.28x10'l 7.94x10'l
6O 65 1.19 1.2
60 68 2.76x10'2 2.65x10'2
6o 69 2.76x10'l 2.6sx10'l
60 7o 2.76x10'l 2.65x10'2
6o 71 2.76x10'l 2.65x10'l
61 46 2.99x10'l 46le0'1
61 49 2.40x10'l 9.79x10'l
61 54 4.32x10'l 1.23x10'l
61 64 6.54x10'l 1.01
61 65 9.14x10'I 1.48
61 68 2.18x10'2 3.36x10'2
61 69 2.18x10'l 3.36x10'l
61 70 2.18xlo'l 3.36xlo'2
61 71 2.18x10'l 3.36x10'l
62 64 1.48 1.49
62 65 2.09 2.19
62 66 3.30x10'l 3.30x10'l
62 67 3.30x10'l 3.30x10'l
62 68 3.30x10'2 3.30x10'2
62 69 3.30x10'l 3.30x10'l
62 70 3.30x10'l 3.30x10'2
62 71 3.30x10'l 3.30x10'l
63 64 2.07 2.36
63 65 2.9 3.46
63 66 4.60x10”l 5.24x10'l
63 67 4.60x10'l 5.24x10'l
63 68 4.60x10'2 5.24x10'2
63 69 4.60x10'l 5.24x10'l
63 70 4.60x10'l 5.24x10'2
63 71 4.60x10'l 5.24x10'l

 

Pre Post
Predator Prey Exchange Exchange
64 67 1.77 2.09
64 68 1.77x10"l 2095.10"1
64 69 1.77 2.09
64 70 1.77 2.09x10'l
64 71 1.77 2.09
65 66 1.5 1.73
65 67 1.5 1.73
65 68 1.50x10'l 1.73x10'l
65 69 1.5 1.73
65 70 1.5 1.73x10'l
65 71 1.5 1.73
65 75 2.25 2.59
75 8 489.1103 4.49x10'3
75 17 2.24x10'5 4.09x10'3
75 66 5845.101 2.955110l
75 67 7.69x10l 5.41x10l
75 68 3.04x10'1 0
75 69 2.88x101 0
75 70 1.73 1.59
75 71 2.56x101 0
75 72 9.00x10l 8.56x10I
75 73 5.86 6.66
75 74 4.95x10'l 4.62x10'l
76 1 2.19x10'4 6.40x10'4
76 2 1.56x10'l 4.80x10'2
76 3 4.60x10'2 3.15x10’3
76 5 1.53x10'2 5.82x10'3
76 8 4.43x10'2 4.16x10'2
76 15 2.74x10'3 0
76 16 4.02x10'l 4.06x10'3
76 17 1.28x10'4 2.40x10'2
76 20 1.21x10'2 4.54x10'3

139

Appendix 2.2 (con't)

 

 

Pre Post Pre Post
Predator Prey Exchange Exchange Predator Prey Exchange Exchange
76 22 100on2 7.06x10'3 76 73 1.48 1.77
76 25 2.05x10'2 4.58x10'2 76 74 2 1.97
76 27 hip. 2.04x1o'3 77 45 9.29x10'4 2.49x10'4
76 32 7.02x10'3 1.36x10'2 77 47 hip. 1.04x10‘3
76 33 2.67x10'3 3.04x10'3 77 49 7.59x10'2 1.10x10'l
76 35 1.02x10'2 4.69x10'3 77 50 1.5 9.94x10'1
76 37 7.80x10'l 5.845.10’l 77 51 1.83 2.59
76 38 3.26x10'6 0 77 52 4.29x10'2 4.33x10'3
76 44 hip. 2.76x10l 77 54 1.36x10"l 1.38x10"2
76 45 8.35x10'3 2.37x10'3 77 55 1.62x10'4 0
76 47 hip. 9.91x10'3 77 56 2.66x10'3 0
76 49 6.82x10'l 1.05 77 57 5.87x10'5 1.27x10'2
76 so 1.35x10l 9.77 77 58 4.41x10'l 1.94x10’l
76 51 1.65x10l 2.54x10l 77 59 1.08x10'3 1.41x10'4
76 52 3.85x10'l 4.26x10'2 77 60 1.55x10'l 1.59x10'l
76 54 1.23 1.32x10'l 77 61 1.15x10'l 1.65x10'l
76 55 1.46x10'3 0 77 62 9.69x10'2 1.07x10'l
76 56 2.40x10'2 0 77 63 2.10x10’l 2.46x10'l
76 57 5.27x10'4 1.22x10'l 77 66 1.98x10l 9.06
76 58 3.97 1.87 77 67 2.60x10] 1.66x10l
76 59 9.69x10'3 1.33x10'3 77 68 1.03x10'1 0
76 60 1.4 1.53 77 69 9.76 0
76 61 1.03 1.6 77 70 5.87x10’l 4.88x10'l
76 62 8.70x10'l 1.05 77 71 8.66 0
76 63 1.89 2.42 prod. 1 2.19x10'4 6.40x10'4
76 66 1.97x10l 1.05x10l prod. 2 1.61x10'l 5.11x10'2
76 67 2.60x10l 1.92x10I prod. 3 5.64x10'2 2.68x10'2
76 68 1.03x1o'l o prod. 4 5.52x10'2 4.29x10’2
76 69 9.73 0 prod. 5 9341.102 8.00x10'2
76 70 5.85x10'l 5.64x10'l prod. 6 8.00x10'2 7.56x10'2
76 71 8.64 0 prod. 7 9.08x10’l 6.69x10'l
76 72 2.28x10l 2.28x10l Prod. 8 6.63x10'2 6.72x10'2

140

Appendix 2.2 (con't)

 

 

Pre Post Pre Post
Predator Prey Exchange Exchange Predator Prey Exchange Exchange
prod. 9 1.79x10'l 1.24x10'l prod. 41 6.04x10'2 7.45x10'2
prod. 10 1.45x10'3 1.23x10'3 prod. 42 5.53x10"l 5.87x10'l
prod. 11 1.42x10'3 1.21x10'3 prod. 43 1.79x10’l 2.32x10'l
prod. 12 1.44x10'2 1.27x10'2 prod. 44 hip. 2.78x10l
prod. 13 1.19x10'2 1.21x10'2 Prod. 45 9.68x10'3 2.74x10’3
prod. 14 3.60x10'3 4.33x10'4 prod. 46 2.44 1.86
prod. 15 1.94x10'2 2.34x10'2 prod. 47 hip. 1.15x10'2
prod. 16 6.37xlo'I 1.59x10'l prod. 48 6.73x10'2 4.62x10'2
prod. 17 1.50x10'4 2.81x10'2 prod. 49 1.04 2.26
prod. 18 1.37x10'2 1.75x10'2 prod. 50 1.57x10l 1.13x10l
prod. 19 4.3sx10'2 3.68x10'2 prod. 51 1.91x10l 2.95x10l
prod. 20 2.86x10'2 2.51x10'2 prod. 52 4.48x10’l 4.94x10'2
prod. 21 5.32x10'3 hip. prod. 53 6.34x1o'l 5.56x10’I
prod. 22 1.14x10'2 8.32x10'3 prod. 54 1.88 2.83x10’l
prod. 23 1.27x10'4 1.75x10'3 prod. 55 1.93x10'3 4.57x10'3
prod. 24 2.87x10’2 2.50x10'l prod. 56 7.32x10'2 2.77x10'l
prod. 25 2.91x10'2 5.30x10'2 prod. 57 6.60x10’4 1.47x10'l
prod. 26 2.87x10’2 1.78x10'4 prod. 58 4.96 2.25
prod. 27 hip. 2.04x10'3 prod. s9 1.21x10'2 1.60x10'3
prod. 28 1.26x10'4 1.75x10'4 prod. 60 2.15 2.02
prod. 29 1.30x10'4 1.75:110'4 prod. 61 1.29 1.92
prod. 30 4.36x10'3 3.59x10'3 prod. 62 2.01 1.95
prod. 31 1.26x10'2 1.75x10'2 prod. 63 2.89 3.18
prod. 32 3.02x10'2 3.42x10'2 prod. 64 6.91 6.58
prod. 33 2.45x10'2 3.12x10'2 prod. 65 9.8 9.73
prod. 34 4.33x10’2 3.66x10'2 prod. 66 1.13x102 8.37x10l
prod. 35 2.51x10'2 2.52x10'2 prod. 67 1.46x102 1.27x102
prod. 36 9.90x10'l 9.50x10'l prod. 68 2.32 3.76
Prod. 37 1.71 1.36 Prod. 69 6.65x10l 3.76x10l
prod. 38 3.70.110'3 2.53x10'3 prod. 70 2.13.1101 6.46
prod. 39 4.73xlo'l 6.17x10'2 prod. 71 6.10x10l 3.76x10l
prod. 40 1.19x10'l 1.87x10'l prod. 72 1.13x102 1.08x102

141

Appendix 2.2 (con't)

 

 

Pre Post Pre Post
Predator Prey Exchange Exchange Predator Prey Exchange Exchange
prod. 73 8.03 9 Cons. 28 1.45x10'4 3.88x10'4
prod. 74 3.05 2.99 Cons. 29 4.90.110'4 5.58x10'4
prod. 75 1.05x10l 4.14x10l Cons. 30 5.63x10'3 4.08x10'3
prod. 76 1.13 1.27 Cons. 31 2.90x10'2 4.14x10'2
prod. 77 9.76x10'4 2.24x10l Cons. 32 3.47x10'l 4.12x10'l
Cons. 1 2.04x10'2 7.07x10'2 Cons. 33 8.35x10'2 1.01x10'l
Cons. 2 1.2 5.34x10’l Cons. 34 5.80x10'2 6.47x10'2
Cons. 3 4.79x10'l 2.48x10'l Cons. 35 2.31x10'l 2.79x10'l
Cons. 4 6.93x10'2 9.64x10'2 Cons. 36 1.33 1.26
Cons. 5 9.45x10'l 5.97x10'l Cons. 37 2.3 1.84
Cons. 6 1.38x10'1 2.50x10'l Cons. 38 1.46x10'2 9.80x10'3
Cons. 7 1.14 1.27 Cons. 39 4.86x10'l 2.11x10'l
Cons. 8 4.35x10'l 3.87x10'l Cons. 40 1.76x10'1 3.32x10'l
Cons. 9 3.77x10'l 2.29x10'l Cons. 41 1.31x10'l 1.88x10'l
Cons. 10 2.86x10'3 3.36x10'3 Cons. 42 6.38x10'l 7.19x10'l
Cons. 1 1 1.76x10'3 2.10x10'3 Cons. 43 2.18x10'l 3.19x10'l
Cons. 12 3.74x10'2 4.38x10'2 Cons. 44 hip. 1.13x102
Cons. 13 2.831110'2 3.15x10'2 Cons. 45 1.02x10'2 2.88x10'3
Cons. 14 4.03x10'3 1.47x10'3 Cons. 46 2.51 1.92
Cons. 15 5.57x10’2 6.70x10'2 Cons. 47 hip. 1.20x10'2
Cons. 16 2.69 6.96x10'l Cons. 48 6.95x10'2 4.81x10'2
Cons. 17 8.15x10'4 1.48x10’l Cons. 49 1.1 2.38
Cons. 18 5.83x10'2 6.93x10'2 Cons. so 2.86x10l 2.08x10l
Cons. 19 5.65x10'2 3.89x10'2 Cons. 51 3.49x10l 5.40x10l
Cons. 20 3.031110'1 3.37x10'l Cons. 52 8.17x10'l 9.05x10'2
Cons. 21 8.27x10’3 hip. Cons. 53 9.91x10'l 9.48x10'l
Cons. 22 1.88x10’l 1.34x10'l Cons. 54 1.97 2.98x10'l
Cons. 23 2.95x10'4 4.16x10'3 Cons. 55 3.57x10'3 7.79x10'3
Cons. 24 5.05x10'2 9.42x10'l Cons. 56 7.38x10'2 2.78x10'l
Cons. 25 3.14x10'l 6.00x10'l Cons. 57 1.27x10'3 2.83x10'l
Cons. 26 3.73x10'2 5.85x10'4 Cons. 58 9.55 4.33
Cons. 27 hip. 3.58x10'2 Cons. 59 2.33x10'2 3.07x10'3

142

Appendix 2.2 (con't)

 

 

Pre Post Pre Post
Predator Prey Exchange Exchange Predator Prey Exchange Exchange
Cons. 60 4.19 3.93 Resp. 24 2.18x10'2 6.93x10'l
Cons. 61 3.21 4.79 Resp. 25 2.85x10'l 5.46x10'l
Cons. 62 5.26 5.06 Resp. 26 8.63x10'3 4.07x10'4
Cons. 63 7.32 8.02 Resp. 27 hip. 3.38x10'2
Cons. 64 7.24 6.7 Resp. 28 1.84x10'5 2.13x10'4
Cons. 65 9.91 9.84 Resp. 29 3.59x10'4 3.83x10'4
Cons. 75 2.88x102 1.78x102 Resp. 30 1.14x10'3 3.47x10“1
Cons. 76 1.34x102 1.30x102 Resp. 31 1.63x10'2 2.39x10'2
Cons. 77 6.955110I 3.07x10l Resp. 32 3.13x10'1 3.73x10'l
Resp. 1 2.02x10'2 7.00x10‘2 Resp. 33 5.90x10'2 7.03x10'2
Resp. 2 1.01 4.72x10" Resp. 34 1.43x10'2 2.77x10'2
Resp. 3 4.22x10'l 2.21x10'l Resp. 35 2.06x10'l 2.54x10'l
Resp. 4 1.40x10'2 5.35x10'2 Resp. 36 3.45x10'l 3.08x10'l
Resp. 5 8.24x10'1 5.01x10'l Resp. 37 5.96x10'l 4.78x10'l
Resp. 6 5.80.110"2 1.74x10'l Resp. 38 1.09x10'2 7.27x10’3
Resp. 7 2.31x10'l 6.04x10'l Resp. 39 1.33x10'2 1.49x10'l
Resp. 8 3.68x10'l 3.20x10'l Resp. 40 5.72x10'2 1.45x10'l
Resp. 9 1.97x10'l 1.05x10'l Resp. 41 7.10x10'2 1.14x10'l
Resp. 10 1.36x10'3 2.07x10'3 Resp. 42 8.50x10'2 1.32x10'l
Resp. 11 2.60x10'4 7.95x10.4 Resp. 43 3.85x10'2 8.74x10'2
Resp. 12 2.21x10'2 2.99x10'2 Resp. 44 hip. 8.56x10l
Resp. 13 1.64x10'2 1.93x10'2 Resp. 45 4.76x10'4 1.36x10'4
Resp. 14 4.36x10'4 1.04x10'3 Resp. 46 6.94x10'2 5.76xlo'2
Resp. 15 3.63x10'2 4.37x10'2 Resp. 47 hip. 5.67x10'4
Resp. 16 2.05 5.37x10'l Resp. 48 2.14x10'3 1.83x10'3
Resp. 17 6.65x10'4 1.20x10'l Resp. 49 5.24x10'2 1.16x10'l
Resp. 18 4.4sx10'2 5.17xlo'2 Resp. 50 1.29x10l 9.44
Resp. 19 1.30x10'2 2.08x10'3 Resp. 51 1.58x10l 2.45x10l
Resp. 20 2.74x10'l 3.11x10'l Resp. 52 3.70x10'l 4.11x10'2
Resp. 21 2.96x10'3 hip. Resp. 53 3.57x10'l 3.92x10'l
Resp. 22 1.76x10'l 1.26xlo'l Resp. 54 9.41x10'2 1.45x10'2
Resp. 23 1.68x10'4 2.41x10'3 Resp. 55 1.64x10'3 3.22x10'3

143

Appendix 2.2 (con't)

 

Pre Post
Predator Prey Exchange Exchange

Resp. 56 6.13x10’4 9.78x10'4
Resp. 57 6.09x10'4 1.36x10'l
Resp. 58 4.58 2.09
Resp. 59 1.12x10'2 1.48x10'3
Resp. 60 2.04 1.9
Resp. 61 1.92 2.87
Resp. 62 3.25 3.1 1
Resp. 63 4.43 4.84
Resp. 64 3.28x10'l 1.19x10"l
Resp. 65 1.10x10'l 1.14x10'l
Resp. 66 1.01x102 7.96x10l
Resp. 67 1.29x102 1.18x102
Resp. 68 2.53 1.64
Resp. 69 6.19x10‘ 3.79x10l
Resp. 7O 2.38x10l 6.38
Resp. 71 5.73x10l 1.46x10l
Resp. 72 9.56x10l 9.24x10l
Resp. 73 6.96 7.8
Resp. 74 2.73 2.64
Resp. 75 2.78x102 1.37x102
Resp. 76 1.33x102 1.29x102
Resp. 77 6.95x10l 8.36
Imp. 66 2.14x102 1.63x102
Imp. 67 2.75x102 2.45x102
Imp. 68 4.86 5 .4
Imp. 69 1.28x102 7.55x10l
Imp. 70 4.51x10l 1.28x10l
Imp. 71 1.18x102 5.22x10l
Imp. 72 2.08x102 2.01x102
Imp. 73 1.50x10I 1.68x10l
Imp. 74 5.79 5.63
Exp. 2 2.41x10'2 1.12x10'2

 

Pre Post
Predator Prey Exchange Exchange
Exp. 5 2.80x10'2 1.62x10'2
Exp. 8 2.03x10.4 1.77x10.4
Exp. 10 4.63x10'5 5.24x10'5
Exp. 11 8.06x10'5 9.15x10'5
Exp. 12 9.43x10'4 1.13x10'3
Exp. 13 3.75x10'5 4.13x10'5
Exp. 18 5.75x10'5 6.22x10'S
Exp. 19 1.20x10'5 1.26x10'5
Exp. 20 3.54x10'4 4.02x10'4
Exp. 22 1.56x10'5 1.11x10'5
Exp. 25 4.19x10'4 8.03x10'4
Exp. 30 1.34x10'4 1.43x10'4
Exp. 32 3.66x10'3 4.37x10'3
Exp. 34 3.83x10'4 4.27x10'4

144

Appendix 2.3

Determination of a re-centering scheme for cohesion analysis.

145

-10

Carbon ﬂows ranged from 8.26x10 to 8.25 gC m'2 yr"1 for the pre-zebra mussel

invasion network, a difference of 10 orders of magnitude; carbon ﬂows ranged from

-11

7.48x10 to 18.38 gC m.2 yr'1 for the post-zebra mussel invasion network, a difference

of 12 orders of magnitude. Kliqueﬁnder accepts ﬂow weights only within 5 orders of
magnitude (0 through 99,998); therefore, we had to adjust the range of network data. We

ﬁrst normalized the data to the lowest value in the network, e.g., for the pre-zebra mussel

time stanza, we divided all ﬂows by our lowest ﬂow estimate of 8.26x10'10 gC m'2 yr'l;

this changed our data range from 1 to 1.01x1010 gC m.2 yr'l. After normalization, the

data range still exceeded the input range for Kliquef'mder, so we further adjusted the data
by three re-centering schemes that involved: 1) changing the range of data by one order
of magnitude between the schemes; 2) assigning the maximum ﬂow weight (i.e., 99,998)
to ﬂows above the range of Kliqueﬁnder; and 3) assigning the minimum ﬂow weight
(i.e., 1) to non-zero ﬂows below the range of Kliqueﬁnder. Scheme one set the highest
ﬂows one order of magnitude above the upper range of Kliqueﬁnder (i.e., the highest
ﬂow and all other ﬂows of the same order of magnitude were assigned the maximum
weight; all other ﬂows fell below the upper range of Kliqueﬁnder). Scheme two set the
highest ﬂows two orders of magnitude above the upper range for Kliqueﬁnder, and
scheme three set the highest ﬂows three orders of magnitude above the upper range of
Kliqueﬁnder. As a result, the number of ﬂow weights exceeding both the upper and
lower input ranges of Kliqueﬁnder differed by scheme. These re-centering schemes
incorporated three assumptions. First, when adjusting the data, maintaining the
proportional range between ﬂow weights is more important than simply maintaining the

rank. For that reason we did not use a log- or similar transformation that would compress

146

one extreme of values relative to the other extreme (e. g., a log-transforrnation would
compress the high ﬂow range relative to the low ﬂow range). Second, for ENA, small
ﬂows (i.e., ﬂows less than one after normalization) are ecologically less signiﬁcant than
large ﬂows because of the quantiﬁcation of ecosystem activity as the throughput of
carbon. Therefore, we chose re-centering schemes that changed a greater number of
small ﬂows than large ﬂows, i.e., we assigned more small ﬂows to the minimum weight
than assigned large ﬂows to the maximum weight. Third, although we deem small flows
ecologically less signiﬁcant in this context, all non-zero ﬂows represent realized food
web connections. Therefore, we chose to retain small ﬂows in the network by assigning
the minimum weight instead of reducing them to zero.

To assess the impact of these re-centering schemes on our structural analysis, we
compared the Kliqueﬁnder subgroup identiﬁcation for each scheme in order to select the
most robust grouped network with which to conduct ENA. Kliqueﬁnder incorporates a
routine that compares subgroup membership of one network to the subgroup membership
of another network and calculates a Z-score to test the statistical signiﬁcance using the
Quadratic Assignment Procedure (QAP) method (Hubert 1987). For both the pre- and
post-zebra mussel invasion networks, all schemes yielded statistically similar subgroup
membership (p g 0.001 for all comparisons). Tables A21 and A22 present the Z-scores
and associated p-values for all comparisons. Since subgroup membership was similar for
all schemes, we chose the scheme that: 1) assigned fewer maximum values to ﬂow
weights above the range of Kliqueﬁnder relative to minimum values to ﬂow weights
below the range of Kliqueﬁnder (according to assumption two); and 2) assigned

maximum and minimum values to the fewest ﬂows overall. Following these criteria, we

147

chose to conduct all subsequent analyses using scheme two for both the pre- and post-

zebra mussel invasion networks.

148

Table A2.1. Results of the signiﬁcance test for differences between subgroup
membership by re-centering scheme for the pre-zebra mussel invasion time stanza. The

table displays Z-scores for each comparison, with the p-value in parentheses.

 

Scheme Scheme 1 Scheme 2 Scheme 3
Scheme 1 . 31.91 (DEG-001) 25.73 (1230.001)
Scheme 2 28.88 (pS0.001) - 28.91 (150.001)
Scheme 3 24.98 ((230-001) 28.91 (pS0.00I) -

149

Table A2.2. Results of the signiﬁcance test for differences between subgroup
membership by re-centering scheme for the post-zebra mussel invasion time stanza- The

table displays Z-scores for each comparison, with the p-value in parentheses.

 

Scheme Scheme 1 Scheme 2 Scheme 3
Scheme 1 . 28.13 (p30.001) 26.31 (p50.001)
Scheme 2 26.07 (p50.001) . 24.45 (050.001)
Scheme 3 27.76 (p30.001) 25.39 (pS0.001)

150

References

Hubert, L. 1987. Assignment Methods in Combinatorial Data Analysis. Marcel Dekker.

151

Appendix 3.1
List of model inputs and data sources for the unbalanced pre- and post-zebra

mussel invasion networks. Diet proportions are not included to conserve space, but

sources of diet information are listed. N.P. stands for not present. Biomass units are g m'

2, wet weight (WW) or dry weight (DW) (zooplankton taxa). Conversions from wet

weight to dry weight, and dry weight to carbon, are listed. P/B, C/B, and R/B stand for

production-to-biomass, consumption-to-biomass, and respiration-to-biomass ratios,

respectively, measured as yr'i. Export includes migrations from the ecosystem and

ﬁsheries harvest (g m'2 WW). The abbreviation BQ-OL CMP Workgroup refers to the

Bay of Quinte — Oneida Lake Comparative Modelling Project Workgroup. The methods
for this modeling project, from which much of our data was drawn, are expected to be
published in 2006 as a Canadian Technical Report of Fisheries and Aquatic Sciences

(Koops, M. A. pers. comm.)-

152

Appendix 3.1

 

No. Taxa Parameter Pre Value Post Value Reference(s)

1 Cormorants Biomass WW 1.40x10'3 5.90x10'3 BQ-OL CMP Workgroup
WW : DW 2.00x10'l 2.00x10'l Jargensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
P/B 6.00x10'l 6.00x10'l BQ-OL CMP Workgroup
C/B 8.58x10l 8.58x10l BQ-OL CMP Workgroup
R/B 8.39x10l 8.40x10l BQ-OL CMP Workgroup
Diet . BQ-OL CMP Workgroup

2 Walleye Age 4+ Biomass WW 4.16 9.43x10'l BQ-OL CMP Workgroup
WW : DW 2.00x10"l 2.00x10'l Jorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jargensen 1979
NB 2.77x10'l 2.77x10'l BQ-OL CMP Workgroup
C/B 3.64 3.64 BQ-OL CMP Workgroup
R/B 3.05 2.85 BQ-OL CMP Workgroup
Export 1.53x10'2 1.10x10'l BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup

Becker 1983

3 Walleye Age 1-3 Biomass WW 1.37 3. 101110.1 BQ-OL CMP Workgroup
WW : DW 2.00x10'l 2.00x10’1 Jargensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
WE 7.99x10'l 7.99x10'l BQ-OL CMP Workgroup
C/B 7.14 7.14 BQ-OL CMP Workgroup
R/B 4.94 4.74 BQ-OL CMP Workgroup
Export 2.97x10'2 9.99x10'3 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup

Becker 1983

4 Walleye Age-0 Biomass WW 1.02x10'l 2.31x10'2 BQ-OL CMP Workgroup
ww ; Dw 2.00x10'l 2.00x10'l Jorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jargensen 1979
pm 1.47 1.47 BQ-OL CMP Workgroup
C/B 2.05x10l 2.05x10l BQ-OL CMP Workgroup
R/B 1.61x10l 1.53x10l BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup

153

Becker 1983

Appendix 3.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
5 Yellow perch Biomass WW 7.00x10'l 2.35 BQ-OL CMP Workgroup
Age 1+ WW : DW 2.00x10.l 2.00x10.l Jorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jargensen 1979
pm 5.50x10'l 5.70x10'1 BQ-OL CMP Workgroup
C/B 4.1 4.14 BQ-OL CMP Workgroup
R/B 3.57 3.61 BQ—OL CMP Workgroup
Export 1.80x10'2 9.00x10'3 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
6 Yellow perch Biomass WW 3.71x10'2 1.33x10'l BQ-OL CMP Workgroup
Age-0 WW : ow 2.00x10'l 2.00x10'l Jargensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jargcnsen 1979
P/B 3.8 3.8 BQ-OL CMP Workgroup
C/B 1.54x10l 1.54x10l BQ-OL CMP Workgroup
R/B 1.41x10l 1.33x10l BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
7 White Perch Biomass WW 1.19 1.9 BQ-OL CMP Workgroup
Age 1+ WW 2 DW 2.00x10'l 2.00x10'l Jorgensen1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
WE 5.00x10'l 5.86x10'l BQ-OL CMP Workgroup
GB 4 4.18 BQ-OL CMP Workgroup
R/B 2.7 2.75 BQ-OL CMP Workgroup
Export 5.22x10'3 1.62x10'3 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
8 White perch Biomass WW 1.08x10'l 1.57x10'l BQ-OL CMP Workgroup
Age-0 WW : DW 2.00x10'l 2.00x10'l Jargenscn 1979
DW : Carbon 4.50x10'l 4.50x10'1 Jargensen 1979
NB 6 5.1 BQ-OL CMP Workgroup
C/B 2.06x10l 1.88x10l BQ-OL CMP Workgroup
R/B 1.83x101 1.11x10l BQ-OL CMP Workgroup
Diet BQ—OL CMP Workgroup

154

Appendix 3.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
8 Wt. Perch Age-0 Diet - . Becker 1983
9 Black Crappie Biomass WW 3.57x10'3 2.48x10'2 BQ-OL CMP Workgroup
Age 1+ WW : DW 2.00x10'l 2.00x10"l Jargensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
pm 7.08x10'l 7.08x10'l BQ-OL CMP Workgroup
C/B 4.24 4.24 BQ-OL CMP Workgroup
R/B 2.76 2.77 BQ-OL CMP Workgroup
Export 6.84x10'4 2.23x10'3 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
10 Bluegill Age 1+ Biomass WW 3.18x10'5 1.66x10'l BQ-OL CMP Workgroup
WW : DW 2.00x10" 2.00x10'l Jargensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
pm 6.12x10'l 6.12x10'l BQ-OL CMP Workgroup
03 4.24 4.24 BQ-OL CMP Workgroup
R/B 2.76 2.77 BQ-OL CMP Workgroup
Export 6.10x10'6 1.49x10-2 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
11 Lepomis species Biomass WW 1.10x10'5 1.17x10'3 BQ-OL CMP Workgroup
Age 1+ WW : DW 2.00x10'l 2.00x10'1 Jorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jorgenscn 1979
WE 6.12x10"l 6.12x10'l BQ-OL CMP Workgroup
C/B 4.24 4.24 BQ-OL CMP Workgroup
R/B 2.76 2.77 BQ-OL CMP Workgroup
Export 2.12x10'b 1.05x10“1 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
12 Pumpkinseed Biomass WW 2.211110-2 7.24x10.l BQ-OL CMP Workgroup
Age 1+ WW : DW 2.00x10'l 2.00x10'l Jorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jargenscn 1979
WE 6.12x10'l 6.12x10'l BQ-OL CMP Workgroup
C/B 4.24 4.24 BQ-OL CMP Workgroup

155

Appendix 3.1 (con‘t)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
12 Pumpkinseed R/B 2.76 2.77 BQ-OL CMP Workgroup
Age 1+ Export 4.25x10.3 6.52x10-2 BQ-OL CMP Workgroup
Diet - . BQ-OL CMP Workgroup
Becker 1983
13 Rock Bass Biomass WW 9.58x10'4 3.11x10'3 BQ-OL CMP Workgroup
Age 1+ WW : ow 2.00x10'l 2.00x10‘l iorgensen 1979
DW : Carbon 4.50x10”l 4.50x10"l Jargensen 1979
NB 5.15x10'l 5.15x10'l BQ-OL CMP Workgroup
C/B 4.24 4.24 BQ-OL CMP Workgroup
R/B 2.76 2.77 BQ-OL CMP Workgroup
Export 1.84x10'4 2.80x10'4 BQ—OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
14 Sunﬁsh family Biomass WW 4.51x10.5 2.46x10-3 BQ-OL CMP Workgroup
Age 1+ WW : DW 2.00x10.l 2.00x10.l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jargensen 1979
P/B 6.21x10-| 6-l3x10.l BQ-OL CMP Workgroup
C/B 4.24 4.24 BQ—OL CMP Workgroup
R/B 2.76 2.77 BQ-OL CMP Workgroup
Export 8.65x10'° 2.21x10'4 BQ—OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
15 Panﬁsh Age-0 Biomass WW 3.26x10'3 3.65x10'1 BQ-OL CMP Workgroup
WW : DW 2.00x10"l 2.00x10.l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
WE 6 8 BQ-OL CMP Workgroup
C/B 2.07x10l 2.45x10l BQ-OL CMP Workgroup
R/B 1.16x10l 1.16x10l BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
16 Alewife Biomass WW 1.61 4.50x10.l BQ-OL CMP Workgroup
WW : DW 2.00x10'l 2.00x10'l iorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979

156

Appendix 3.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
16 Alewife p/B 8.65x10'l 8.89x10'l BQ-OL CMP Workgroup
C/B 4.53 4.68 BQ-OL CMP Workgroup
RIB 2.86 2.95 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
17 American Eel Biomass WW 3.57x10-l 6.38x10.2 BQ-OL CMP Workgroup
WW : DW 2.00x10'l 2.00x10'l Jargensen 1979
DW : Carbon 4.50x10'1 4.50x10'l Jorgensen 1979
P/B 3.80x10'I 3.70x10'l BQ-OL CMP Workgroup
C/B 3.8 3.7 BQ-OL CMP Workgroup
R/B 2.66 2.94 BQ-OL CMP Workgroup
Export None 2.43x10’3 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
18 Brook Silverside Biomass WW hip. 6.85x10'5 BQ-OL CMP Workgroup
WW : DW hip. 2.00x10'l Jorgensen 1979
DW : Carbon hip. 4.50x10'l Jergensen 1979
P/B NP. 1.71 BQ-OL CMP Workgroup
C/B NP. 6.33 BQ-OL CMP Workgroup
R/B NP. 3.36 BQ-OL CMP Workgroup
Diet NP. BQ-OL CMP Workgroup
Becker 1983
19 Brown Bullhead Biomass WW 9.91x10'l 7.48x10”l BQ-OL CMP Workgroup
WW : ow 2.00x10'l 2.00x10'l Jargensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jorgensen 1979
WE 3.80x10'l 3.86x10'l BQ-OL CMP Workgroup
C/B 3.8 3.7 BQ-OL CMP Workgroup
R/B 2.66 2.94 BQ-OL CMP Workgroup
Export 4.3 9x10'2 2.60x10'2 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
20 Channel Catﬁsh Biomass WW 8.39x10.3 6.01x10.3 BQ-OL CMP Workgroup
WW : DW 2.00x10.l 2.00x10.l Jorgensen 1979

157

Appendix 3.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
20 Channel Catﬁsh DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
p/B 3.80x10'l 2.17x10"l BQ-OL CMP Workgroup
OR 3.8 3.7 BQ-OL CMP Workgroup
R/B 2.66 2.94 BQ-OL CMP Workgroup
Export 2.70x10’3 1.73x10'4 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
21 Common Carp Biomass WW 6.70x10.l 3.30x10.l BQ-OL CMP Workgroup
WW : DW 2.00x10'l 2.00x10'l Jargensen 1979
DW : Carbon 4.50x10’l 4.50x10'l Jergensen 1979
WE 1.56x10'l 1.60x10'l BQ-OL CMP Workgroup
C/B 3.33 3.33 BQ-OL CMP Workgroup
R/B 2.51 2.51 BQ-OL CMP Workgroup
Export 4.68x10'3 1.44x10'3 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
22 Emerald Shiner Biomass WW NP. 6.37x10“6 BQ-OL CMP Workgroup
WW : DW NP. 2.00x10.l Jargensen 1979
DW : Carbon hip. 4.50x10'l Jergensen 1979
P/B NP. 1.71 BQ-OL CMP Workgroup
C/B NP. 6.33 BQ—OL CMP Workgroup
R/B NP. 3.36 BQ-OL CMP Workgroup
Diet NP. BQ-OL CMP Workgroup
Becker 1983
23 Freshwater Drum Biomass WW 1.14x10'l 5.10x10’l BQ-OL CMP Workgroup
WW : DW 2.00x10'l 2.00x10'l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jargensen 1979
p/B 2.64x10'l 2.50x10'l BQ-OL CMP Workgroup
C/B 3.66 3.52 BQ-OL CMP Workgroup
R/B 2.67 2.57 BQ-OL CMP Workgroup
Export 9.90x10’4 3.96x10'3 BQ—OL CMP Workgroup
Diet BQ-OL CMP Workgroup

158

Becker 1983

Appendix 3.1 (con‘t)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
24 Gizzard Shad Biomass WW 4.20x10'l 4.50x10'l BQ-OL CMP Workgroup
WW : DW 2.00x10'l 2.00x10'l Jergensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jargensen 1979
WE 1.43 1.43 BQ-OL CMP Workgroup
C/B 5.96 5.96 BQ-OL CMP Workgroup
R/B 3.34 3.34 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
25 Johnny Darter Biomass WW 3.89x10'5 1.17x10'3 BQ-OL CMP Workgroup
WW : DW 2.00x10'l 2.00x10'l Jargensen 1979
ow : Carbon 4.50x10'l 4.50x10'l iargensen 1979
P/B 3.80x10'1 3.70x10'l BQ-OL CMP Workgroup
C/B 3.8 3.7 BQ-OL CMP Workgroup
R/B 2.66 2.94 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
26 Largemouth Bass Biomass WW N.P. 4.32x10-3 BQ-OL CMP Workgroup
WW : DW hip. 2.00x10"l Jargensen 1979
DW : Carbon hip. 4.50x10'I Jorgensen 1979
P/B hip. 3.08x10'l BQ—OL CMP Workgroup
C/B NP. 3.51 BQ-OL CMP Workgroup
R/B NP. 4.22 BQ-OL CMP Workgroup
Diet N.P. BQ-OL CMP Workgroup
Becker 1983
27 Log perch Biomass WW 8.70x10’5 1.72x10'3 BQ-OL CMP Workgroup
WW 2 DW 2.00x10'l 2.00x10'l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
P/B 3.80x10'l 3.70x10-l BQ-OL CMP Workgroup
C/B 3.8 3.7 BQ-OL CMP Workgroup
R/B 2.66 2.94 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
28 Longnose Gar Biomass WW 2.13x10-l 3.76x10-3 BQ-OL CMP Workgroup

159

Appendix 3.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
28 Longnose Gar WW : DW 2.00x10.l 2.00x10.l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10-l Jargensen 1979
WE 2.12x10'l 1.86x10'l BQ-OL CMP Workgroup
C/B 3.24 3.51 BQ-OL CMP Workgroup
R/B 2.36 4.22 BQ—OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
29 Northern Pike Biomass WW 9.17x10'2 1.80x10'2 BQ-OL CMP Workgroup
WW : ow 2.00x10'l 2.00x10'l Jorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jorgenscn 1979
WE 2.40x10'l 1.98x10'l BQ-OL CMP Workgroup
C/B 3.24 3.51 BQ—OL CMP Workgroup
R/B 2.36 4.22 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
30 Round Goby Biomass WW hip. 8.10x10'3 BQ-OL CMP Workgroup
WW : ow hip. 2.00x10'l Jorgenscn 1979
DW : Carbon NP. 4.50x10.l Jargensen 1979
NB NP. 1.33 BQ-OL CMP Workgroup
C/B NP. 5.78 BQ—OL CMP Workgroup
R/B NP. 3.3 BQ-OL CMP Workgroup
Diet NP. BQ-OL CMP Workgroup
Becker 1983
31 Smallmouth Bass Biomass WW 2.90x10.2 2.10x10.2 BQ-OL CMP Workgroup
WW : ow 2.00x10'l 2.00x10'l Jargensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jergensen 1979
NB 3.90x10'l 3.68x10'l BQ-OL CMP Workgroup
C/B 5.65 5.8 BQ-OL CMP Workgroup
R/B 4.13 4.24 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
32 Spottail Shiner Biomass WW 2.90x10'2 8.09x10'2 BQ-OL CMP Workgroup
WW : DW 2.00x10'l 2.00x10'l Jargensen 1979

160

Appendix 3.1 (con‘t)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
32 Spottail Shiner DW : Carbon 4.50x10.l 4.50x10.l Jargensen 1979
P/B 1.71 1.71 BQ-OL CMP Workgroup
C/B 6.33 6.33 BQ—OL CMP Workgroup
R/B 3.36 3.36 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
33 Trout-perch Biomass WW 3.70x10-2 1.81x10.2 BQ-OL CMP Workgroup
WW : DW 2.00x10'l 2.00x10'l Jargensen 1979
ow : Carbon 4.50x10'l 4.50x10"l Jorgensen 1979
P/B 1.35 1.46 BQ-OL CMP Workgroup
C/B 5.4 5.84 BQ-OL CMP Workgroup
R/B 2.97 3.21 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
34 White Bass Biomass WW 1.37x10'2 4.72x10'3 BQ-OL CMP Workgroup
WW : DW 2.00x10"l 2.00x10'l Jorgensen 1979
ow : Carbon 4.50x10'l 4.50x10'l Jargensen 1979
pm 3.80x10'l 3.70x10'l BQ—OL CMP Workgroup
C/B 3.8 3.7 BQ-OL CMP Workgroup
R/B 2.66 2.94 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
35 White Sucker Biomass WW 8.22x10-l 7.29x10-l BQ-OL CMP Workgroup
WW 1 DW 2.00x10'l 2.00x10'l iargensen 1979
DW : Carbon 4.50x10.l 4.50x10"l Jargensen 1979
P/B 3.80x10.l 2.68x10.I BQ-OL CMP Workgroup
C/B 3.8 3.7 BQ-OL CMP Workgroup
R/B 2.66 2.94 BQ-OL CMP Workgroup
Export 1.36x10'3 1.40x10'3 BQ-OL CMP Workgroup
Diet BQ-OL CMP Workgroup
Becker 1983
36 Amphipods Biomass WW 1.18 1.9 BQ-OL CMP Workgroup
WW : DW 1.67xio'l 1.67xlo'l iorgensen 1979

161

Appendix 3.1 (con‘t)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
36 Amphipods DW : Carbon 4.17x10-l 4.17x10.l Jorgensen 1979

WE 5.7 5.7 BQ-OL CMP Workgroup

C/B 3.02x10l 3.02x10I BQ-OL CMP Workgroup

RIB 4.26 4.26 Quigley et a1. 2002

Diet BQ-OL CMP Workgroup
37 Chironomids Biomass WW 2.05 1.15 BQ-OL CMP Workgroup

WW : DW 1.67x10'l 1.67x10'l iargensen 1979

DW : Carbon 4.62x10.l 4.62x10-l Jargensen 1979

P/B 1.45x10l 1.45x10l BQ-OL CMP Workgroup

C/B 6.93x10l 6.93x10l BQ-OL CMP Workgroup

RIB 4.5 4.5 Johnson and Brinkhur 1971

Diet . . BQ-OL CMP Workgroup
38 Clams Biomass WW 2.57x10-l 2.67x10.l BQ-OL CMP Workgroup

WW : DW 1.67x10'l 1.67x10'l Jargensen 1979

DW : Carbon 3.99x10.l 3.99x10.I Jorgensen 1979

NB 3.8 3.8 BQ—OL CMP Workgroup

C/B 2.44x10l 2.44x10l BQ-OL CMP Workgroup

RIB 1.03x10l 1.03x10l Johnson and Brinkhur 1971

Diet . - BQ-OL CMP Workgroup
39 Crayﬁsh Biomass WW 5.40x10"3 5.40x10'3 BQ-OL CMP Workgroup

WW : DW 1.67x10-1 1.67x10-l Jorgensen 1979

DW : Carbon 4.46x10.l 4.46x10.l Jorgensen 1979

P/B 1.2 1.2 BQ-OL CMP Workgroup

C/B 1.04x10l 1.04x10l BQ-OL CMP Workgroup

RIB 1.38x10l 1.38x10l BQ-OL CMP Workgroup

Diet BQ-OL CMP Workgroup
40 Insects Biomass WW 1.13 1.62 BQ-OL CMP Workgroup

WW : DW 1.67x10'l 1.67x10"I iorgensen 1979

DW : Carbon 4.46x10'l 4.46x10'1 Jorgensen 1979

P/B 5.6 5.6 BQ-OL CMP Workgroup

C/B 3.61x10l 3.61x10l BQ-OL CMP Workgroup

R/B 1.38x10l 1.38x10l BQ-OL CMP Workgroup

Diet BQ-OL CMP Workgroup

162

Appendix 3.] (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
41 lsopods Biomass WW 1.45x10'l 7.82x10'l BQ-OL CMP Workgroup

WW : DW 1.67x10-l 1.67x10-l Jorgensen 1979

DW : Carbon 3.43x10'I 3.43x10'l Jargensen 1979

P/B 5.7 5.7 BQ-OL CMP Workgroup

C/B 3.02x10l 3.02x10l BQ-OL CMP Workgroup

R/B 4.26 4.26 Quigley et al. 2002

Diet . . BQ-OL CMP Workgroup
42 Leeches Biomass WW 3.46x10’l 1.22x10'1 BQ—OL CMP Workgroup

WW : DW 1.67x10'l 1.67x10'l Jergensen 1979

DW : Carbon 4.83x10'l 4.83x10'l Jargenscn 1979

NB 2.2 2.2 BQ-OL CMP Workgroup

C/B 3.18x10l 6.3 BQ-OL CMP Workgroup

RIB 1.38x10l 1.38x10l 30-01. CMP Workgroup

Diet - . BQ-OL CMP Workgroup
43 Oligochaetes Biomass WW 5.64x10'l 6.43x10’l BQ-OL CMP Workgroup

WW : DW 1.67x10'l 1.67x10'l Jergcnsen 1979

DW : Carbon 4.02x10'l 4.02.110'l Jargensen 1979

p/B 6.2 6.2 BQ-OL CMP Workgroup

C/B 6.20x10l 6.20x10l BQ-OL CMP Workgroup

RIB 4.5 4.5 Johnson and Brinkhur 1971

Diet . . BQ-OL CMP Workgroup
44 Snails Biomass WW 4.48x10"l 9.13x10'l BQ-OL CMP Workgroup

WW : DW 1.67x10'l 1.67x10'l Jorgensen 1979

DW : Carbon 3.99x10'l 3.99x10'l Jorgcnsen 1979

WE 3.5 3.5 BQ-OL CMP Workgroup

C/B 1.33x10l 1.33x10l BQ-OL CMP Workgroup

RIB 1.8 1.8 BQ-OL CMP Workgroup

Diet . BQ-OL CMP Workgroup
45 Zebra Mussels Biomass WW NP. 1.04x103 BQ-OL CMP Workgroup

WW : DW NP. 1.67x10.l Jorgensen 1979

DW : Carbon NP. 3.99x10.l Jorgensen 1979

P/B NP. 1.35 BQ-OL CMP Workgroup

C/B hip. 8.6 BQ-OL CMP Workgroup

163

Appendix 3.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
45 Zebra Mussels RIB NP. 4.15 Fanslow et a1. 2001
Diet NP. BQ-OL CMP Workgroup
46 Alana species Biomass DW 7.54x10-4 2.42x10-3 BQ-OL CMP Workgroup
DW : Carbon 4.50x10‘1 4.50x10’l Jargensen 1979
PIB 5.50x10l 5.50x101 BQ-OL CMP Workgroup
C/B 2.00x102 2.00x102 BQ-OL CMP Workgroup
RIB 1.86 1.86 Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
47 Bosmina Biomass DW 1.06x10’l 8.47x10'2 BQ-OL CMP Workgroup
Iongirostris DW : Carbon 4.50x10'l 4.50x10'1 Jorgensen 1979
P/B 5.68x10l 5.68x10l BQ-OL CMP Workgroup
C/B 2.00x102 2.00x102 BQ-OL CMP Workgroup
RIB 1.86 1.86 Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
48 Ceriodaphnia Biomass DW 1.86x10'2 1.68xlo'2 BQ-OL CMP Workgroup
species DW : Carbon 4.50x10.l 4.50x10-l Jargensen 1979
P/B 7.57x10l 7.57x10l BQ-OL CMP Workgroup
C/B 2.00x102 2.00x102 BQ-OL CMP Workgroup
RIB 1.86 1.86 Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
49 Chydoridae family Biomass DW 6.53x10'2 1.61xlo'2 BQ-OL CMP Workgroup
DW : Carbon 4.50x10-l 4.50x10.l Jargensen 1979
p/B 5.16x10l 5.16x10l BQ-OL CMP Workgroup
C/B 2.00x102 2.00x102 BQ-OL CMP Workgroup
RIB 1.86 1.86 Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
50 Daphnia galeata Biomass DW 1.30x10-l 2.54x10.I BQ—OL CMP Workgroup
mendotae DW : Carbon 5.07x10.l 5.07x10.l Jorgensen 1979
P/B 4.21x10l 4.21x10l BQ-OL CMP Workgroup

164

Appendix 3.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
50 Daphnia galeata C/B 2.00x102 2.00x102 BQ-OL CMP Workgroup
mendotae R/B 3.13x10l 3.13x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
51 Daphnia pulicaria Biomass DW 2.66x10.3 4.85x10-4 BQ-OL CMP Workgroup
DW : Carbon 5.07x10.] 5.07x10“l Jorgensen 1979
WE 3.88x10l 3.88x10l BQ-OL CMP Workgroup
CIB 2.00x102 2.00x102 BQ-OL CMP Workgroup
RIB 3.13x10l 3.13x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
52 Daphnia Biomass DW 1.54x10-l 1.48x10-l BQ-OL CMP Workgroup
retrocurva DW : Carbon 5.07x10.l 5.07x10-l Jorgensen 1979
P/B 3.54x10l 3.54x10l BQ-OL CMP Workgroup
C/B 2.00x102 2.00x102 BQ-OL CMP Workgroup
RIB 3.13x10l 3.13x101 Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
53 Eubasmina Biomass DW 2.63x10'l 1.85x10'l BQ-OL CMP Workgroup
coregoni DW : Carbon 4.50x10.l 4.50x10-1 Jargensen 1979
PIB 6.83x10l 6.83x10I BQ-OL CMP Workgroup
CIB 2.00x102 2.00x102 BQ-OL CMP Workgroup
R/B 1.86 1.86 Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
54 Sididae family Biomass ow 1.86x10'2 3.72x10'2 BQ-OL CMP Workgroup
DW : Carbon 4.50x10-l 4.50x10.l Jorgensen 1979
P/B 5.50x10l 5.50x10l BQ-OL CMP Workgroup
C/B 2.00x102 2.00x102 BQ-OL CMP Workgroup
R/B 3.13x10l 3.13x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004

165

Appendix 3.1 (con‘t)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
55 Large-bodied Biomass DW 1.81x10-4 1-7lx10-3 BQ-OL CMP Workgroup
Cladocerans DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
P/B 5.50x10l 5.50x10l BQ-OL CMP Workgroup
C/B 2.00x102 2.00x102 BQ-OL CMP Workgroup
RIB 3.13x10l 3.13x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
56 Cercopagis Biomass DW NP. 1.79x10.4 BQ-OL CMP Workgroup
pengoi DW : Carbon NP. 4.50x10.l Jargensen 1979
P/B NP. 4.10x10l BQ-OL CMP Workgroup
CIB NP. 1.44x102 BQ-OL CMP Workgroup
RIB NP. 3.13x10l Urabe and Watanabe 1989
Diet NP. BQ-OL CMP Workgroup
Krause 2004
57 Leptodora kindtii Biomass DW 3.12x10.3 4.46x10-3 BQ—OL CMP Workgroup
DW : Carbon 4.50x10'l 4.50x10" Jorgensen 1979
P/B 4.40x10l 4.40x10l BQ—OL CMP Workgroup
CIB 1.44x102 1.44x102 BQ-OL CMP Workgroup
”3 “3"")! 3' ”"101 Hillbricht-Ilkowska and Karabin
1970
Diet BQ-OL CMP Workgroup
Krause 2004
58 Acanthocyclops Biomass DW 1.74x10'2 1.26x10'2 BQ-OL CMP Workgroup
vernalis DW : Carbon 4.36x10'l 4.36x10'l Jergensen 1979
WE 4.40x10l 4.40x10l BQ-OL CMP Workgroup
C/B 1.44x102 1.44x102 BQ-OL CMP Workgroup
RIB 1.84x10l 1.84x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
59 Diacyclops Biomass DW 2.41x10'3 1.69x10'3 BQ-OL CMP Workgroup
thomasi DW : Carbon 4.36x10-l 4.36x10.l Jargensen 1979
P/B 4.40x10l 4.40x10l BQ-OL CMP Workgroup
C/B 1.44x102 1.44x102 BQ-OL CMP Workgroup

166

Appendix 3.1 (con‘t)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
59 Diacyclops RIB 1.84x10l 1.84x10l Urabe and Watanabe 1989
thomasi Diet BQ-OL CMP Workgroup
Krause 2004
60 Eucyclops Biomass DW 5.97x10'4 9.22x10'4 BQ-OL CMP Workgroup
species DW : Carbon 4.36x10"l 4.36x10.l Jorgensen 1979
P/B 4.40x10l 4.40x10l BQ-OL CMP Workgroup
CIB 1.44x102 1.44x102 BQ-OL CMP Workgroup
RIB 1.84x10l 1.84)thl Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
61 Mesocyclops Biomass DW 2.99x10-2 4.39x10-2 BQ-OL CMP Workgroup
species DW : Carbon 4.36x10-l 4.36x10.l Jorgensen 1979
PIB 4.40x10I 4.40x10l BQ-OL CMP Workgroup
CIB 1.44x102 1.44x102 BQ-OL CMP Workgroup
RIB 1.8411110l 1.84x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
62 Tropocyclops Biomass DW 9.17x10'3 6.72x10'3 BQ-OL CMP Workgroup
extensus DW : Carbon 4.36x10.l 4.36x10.l Jorgensen 1979
PIB 4.40x10l 4.40x10l BQ-OL CMP Workgroup
C/B 1.44x102 1.44x102 BQ-OL CMP Workgroup
RIB 1.84x10l 1.84x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
63 Cyclopoida Biomass ow 1.63x10'l 1.02x10'I BQ-OL CMP Workgroup
copepodites DW : Carbon 4.36x10-l 4.36x10-l Jargensen 1979
P/B 4.40x10l 4.40x10I BQ-OL CMP Workgroup
CIB 1.44x102 1.44x102 BQ-OL CMP Workgroup
RIB 1.84x10l 1.84x10l Urabe and Watanabe 1989
Diet BQ-OL CMP Workgroup
Krause 2004
64 Diaptomidae Biomass DW 3.12x10'3 6.67x10'3 BQ-OL CMP Workgroup
family DW : Carbon 4.36x10'l 4.36x10'l Jorgensen 1979

167

Appendix 3.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
64 Diaptomidae P/B 4.40x10l 4.40x10l BQ-OL CMP Workgroup
family C/B 1.44x102 1.44x102 BQ-OL CMP Workgroup
R/B 2.96x10l 2.96x10l Banse and Mosher 1980
Diet BQ-OL CMP Workgroup
Krause 2004
65 Temoridae Biomass DW 1.65x10'3 6.49x10'4 BQ-OL CMP Workgroup
family DW : Carbon 4.36x10’l 4.36x10'l iorgensen 1979
WE 4.40x101 4.40x10l BQ-OL CMP Workgroup
C/B 1.44x102 1.44x102 BQ—OL CMP Workgroup
R/B 2.96x10l 2.96x10l Banse and Mosher 1980
Diet BQ-OL CMP Workgroup
Krause 2004
66 Calanoida Biomass ow 5.98x10'3 4.76x10'3 BQ-OL CMP Workgroup
copepodites DW : Carbon 4.36x10”l 4.36x10.l Jorgensen 1979
P/B 4.40x10l 4.40x10l BQ-OL CMP Workgroup
C/B 1.44x102 1.44x102 BQ-OL CMP Workgroup
R/B 2.96x10l 2.96x10l Banse and Mosher 1980
Diet BQ-OL CMP Workgroup
Krause 2004
67 Harpacticoida Biomass DW 9.80x10.6 6.05x10-5 BQ-OL CMP Workgroup
DW : Carbon 4.36x10'l 4.36x10'l Jargensen 1979
WE 4.40x10l 4.40x10l BQ-OL CMP Workgroup
C/B 1.44x102 1.44x102 BQ-OL CMP Workgroup
R/B 2.96x10l 2.96x10l Banse and Mosher 1980
Diet BQ-OL CMP Workgroup
Krause 2004
68 Nauplii Biomass DW 1.16x10'2 2.62x10'2 BQ-OL CMP Workgroup
DW : Carbon 4.361(10'l 4.36x10-l Jorgensen 1979
WE 4.401110l 4.40x10l BQ-OL CMP Workgroup
CIB 1.44x102 1.44x102 BQ-OL CMP Workgroup
RIB 1.16 1.16 Makarewicz and Likens 1979
Diet BQ-OL CMP Workgroup
Krause 2004

168

Appendix 3.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
69 Rotifers Biomass DW 1.60x10'2 1.60x10'2 BQ-OL CMP Workgroup
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
P/B 5.20x10l 5.20x10l BQ-OL CMP Workgroup
CIB 2.08x102 2.08x102 BQ-OL CMP Workgroup
RIB 1.16 1.16 Makarewicz and Likens 1979
Diet BQ-OL CMP Workgroup
Pennak 1978
70 Blue-green Algae Biomass WW 4.64 1.66 BQ-OL CMP Workgroup
WW : DW 3.60x10'l 3.60x10'l Jorgensen 1979
DW : Carbon 4.60x10'l 4.60x10'l iargensen 1979
P/B 1.76x102 2.46x102 BQ-OL CMP Workgroup
R/B 7.28x10l 7.28x10l Biddanda and Cotner 2002
71 Diatoms Biomass WW 8.45 7.29 BQ—OL CMP Workgroup
WW : DW 3.30x10'l 3.30x10'l Jergensen 1979
DW : Carbon 5.17x10'l 5.17x10'l Jorgensen 1979
P/B 1.76x102 2.46x102 BQ-OL CMP Workgroup
R/B 7.28x10l 7.28x10l Biddanda and Cotner 2002
72 Flagellates Biomass WW 8.45x10.l 5.31x10-l BQ-OL CMP Workgroup
WW : DW 4.00x10.l 4.00x10.l Jorgensen 1979
DW : Carbon 4.50x10.l 4.50x10.l Jorgensen 1979
P/B 1.76x102 2.46x102 BQ-OL CMP Workgroup
C/B None None None
R/B 7.28x10l 7.28x10l Biddanda and Cotner 2002
73 Golden Algae Biomass WW 1.93x10'l 1.50x10'l BQ-OL CMP Workgroup
WW : DW 4.00x10.l 4.00x10"l Jorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l iorgensen 1979
P/B 1.76x102 2.46x102 BQ-OL CMP Workgroup
RIB 7.28x10l 7.28x10l Biddanda and Cotner 2002
74 Green Algae Biomass WW 5.60x10.l 3.281110.l BQ-OL CMP Workgroup
WW : DW 4.30x10'l 4.30x10'l Jergensen 1979
DW : Carbon 5.05x10'l 5.05x10'l Jorgcnsen 1979
P/B 1.76x102 2.4611102 BQ-OL CMP Workgroup
RIB 7.28x10l 7.28x10l Biddanda and Cotner 2002

169

Appendix 3.1 (con't)

 

No. Taxa Parameter Pre Value Post Value Reference(s)
75 Epiphytes Biomass WW 670le1 6.26 BQ-OL CMP Workgroup
WW : DW 1.20x10'l 1.20x10'l Jorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jorgensen 1979
WE 1.20x102 1.20x102 BQ-OL CMP Workgroup
RIB 4.95x10l 3.54x10l Biddanda and Cotner 2002
76 Macrophytes Biomass WW 7.55 8.09x10l BQ-OL CMP Workgroup
WW : DW 1.20x10'l 1.20x10"l iorgensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jergensen 1979
WE 8.8 8.8 BQ-OL CMP Workgroup
RIB 3.64 2.6 Biddanda and Cotner 2002
77 Periphytes Biomass WW 3.24 2.05 BQ-OL CMP Workgroup
WW : DW 1.20x10'l 1.20x10"l Jargensen 1979
DW : Carbon 4.50x10'l 4.50x10'l Jorgensen 1979
WE 2.65x10l 2.65x10l BQ-OL CMP Workgroup
RIB 1.10x10l 7.85 Biddanda and Cotner 2002

170

References

Banse, K. and S. Mosher. 1980. Adult body mass and annual production/biomass
relationships of ﬁeld populations. Ecol. Monogr. 50: 355-379.

Becker, G. C. 1983. Fishes of Wisconsin. Univ. of Wisconsin Press: Madison.

Biddanda, B. A. and J. B. Cotner. 2002. Love handles in aquatic ecosystems: The role of
dissolved organic carbon drawdown, resuspended sediments, and terrigenious
inputs in the carbon balance of Lake Michigan. Ecosystems 5: 431-445.

Fanslow, D. L., T. F. Nalepa, and T. H. Johengen. 2001. Seasonal changes in the
respiratory electron transport system (ETS) and respiration of the zebra mussel,
Dreissena polymorpha in Saginaw Bay, Lake Huron. Hydrobiologia 448: 61-70.

Hillbricht-Ilkowska, A. and A. Karabin. 1970. An attempt to estimate consumption,
respiration, and production of Leptodora kindtii (Focke) in ﬁeld and laboratory
experiments. Polskie Arch. Hydrobiol. II 17: 81-86.

Johnson, M. G. and R. O. Brinkhur. 1971. Production of benthic macroinvertebrates of
Bay of Quinte and Lake Ontario. J. Fish. Res. Board Can. 28: 1699-1714.

J orgensen, S. E. 1979. Handbook of Environmental Data and Ecological Parameters.
Pergamon Press.

Krause, A. E. 2004. The role of compartments in food-web structure and changes
following biological invasions in southeast Lake Michigan. Ph.D. thesis.
Michigan State Univ.

Makarewicz, J. C. and G. E. Likens. 1979. Structure and flmction of the zooplankton
community of Mirror Lake, New Hampshire. Ecol. Monogr. 49: 109-127.

Pennak, R. W. 1978. Freshwater Invertebrates of the United States. 2'1d ed. J. Wiley and
Sons, Inc.

Quigley, M. A., P. F. Landrum, W. S. Gardner, C. R. Stubbleﬁeld, and W. M. Gordon.
2002. Respiration, nitrogen excretion, and O:N ratios of the Great Lakes
amphipod Diporeia sp. NOAA Technical Memorandum GLERL-120.

Urabe, J. and Y. Watanabe. 1989. Inﬂuence of food density on respiration rate of two

crustacean plankters, Daphnia galeata and Basmina longirostris. Oecologia 82:
362-3 68.

171

Appendix 3.2

Balanced exchange matrices for the pre- and post-zebra mussel invasion
networks. For clarity, the matrix was changed to list format. Flows units are gC m'2 yr'1

and all zero ﬂows were removed from the list. N.P., Prod., Cons., Resp., Imp., and Exp.
stand for not present, production, consumption, respiration, imports, and exports,

respectively.

172

Appendix 3.2
Pre Post Pre Post
Pred Prey Exchange Exchange Pred Prey Exchange Exchange

 

NNNNNNN

 

10 3.27x10'6 6.24x10'4
11 3.26x10'6 6.24x10'5
12 3.26x10'4 6.24x10'4
13 3.27x104 6.23x10'S
14 3.26x10'6 6.24x10'S
15 8.29x10'4 1.14x10'l
16 1.61x10'l 1.33x10'2
17 1.08x10'3 1.64x10'4

3 2.32x10'3 1.26x10'2
5 1.42x10'2 4.31x10'2
7 1.59x10'4 8.40x10'4
9 1.68x10'4 4.80x10'3
10 1.68x10’6 4.79x10'3
11 1.68x10'6 4.79x10'4
12 1.68x10'4 4.79x10'3
13 1.68x10'4 4.79x10’4

14 1.68x10'6 4.79:110'4 18 hip. 9.59x10'6
16 1.19x10'4 6.52x10'4 19 1.08x10'3 1.64x10'4
17 2.26x10'5 1.20x10'4 20 1.08x10'3 1.64x10'5
18 NP. 6.22x10’6 24 1.77x10'2 2.73x10'2

6 5

25 1.08x10' 1.64x10'
26 NP. 7.85x10'4
27 1.08x10’S 1.64x10'5
28 5.52x10'3 7.85x10'4
29 5.53x10'3 7.86x10'4
30 NP. 4.62x1o'4
31 1.96x10'3 7.52x104
32 3.26x10'3 9.60x10'4
33 9.02x10'3 1.73x10'4
34 1.08x10' 1.64x10'5
35 1.08x10'3 1.64x10'4
37 1.17x10'l 1.62x10'2
39 2.20x10'3 2.45x10'4
40 2.21x10'l 2.45x10'2
42 2.21x10'l 2.45x10'2
43 1.17x10'l 1.625.10'2
4 1.88x10'2 4.57x10'3
5 4.44x10'3 2.66x10'2
6 3.61x10'3 4.61x10'2
7 1.70x10'2 1.37x10'2

-5 -4
19 2.26x10 1.20x10
20 2.26x10'5 1.20x10'5
23 2.97x10'4 1.49x10'3
24 3.57x10'5 1.87x10'3
25 0 1.20x10'5
27 0 1.20x10'5
-5 -4

28 2.64x10 1.56x10
-5 .4

29 2.64x10 1.56x10
-5

30 NP. 9.35x10
31 7.12x10'4 6.53x10'4
- -4

32 1.19x104 6.22x10
34 2.26x10'5 1.20xlo'5
- -4

35 2.26x10S 1.20x10
7.52x10'3 1.14x10'3
- -3
3.92x10 2 5.99x10
- -2
2.44x10 2 4.16x10
9.54x10'3 2.71x10'2
1.96x10'l 2.72x10'2
9.55x10'2 2.71x10'2
-4 -4
3.26x10 6.25x10

3

WWNWNNNNNNNNNNNNNNNNNNNNNNNNNNNN

\OOOQO‘MébJ

173

Appendix 3.2 (con't)

 

 

174

Pre Post Pre Post
Pred Prey Exchange Exchange Pred Prey Exchange Exchange
3 8 6.59x10'2 3.58x10'2 3 57 6.93x10'3 8.76x10'4
3 9 6.90x10‘5 3.41x10’4 3 58 6.29x10"4 0
3 10 o 3.41x10'4 3 s9 6.29x10'4 0
3 11 0 3.41x10'5 3 60 6.29x10'6 0
3 12 6.89x10'5 3.41x10“t 3 61 6.30x10'4 0
3 13 6.90x10'5 3.40x10’5 3 62 6.29x10'4 0
3 14 0 3.41x10'5 3 63 6.30x10“1 0
3 16 3.00x10'2 1.72x10'3 3 64 6.29x10'5 0
3 18 NP. 5.71x10'6 3 65 6.30x10'4 0
3 24 3.08x10'3 1.14x10'2 3 66 6.29x10'4 0
3 26 NP. 3.07x10"4 3 68 6.29x10’4 0
3 28 1.03x10'3 3.07x10'4 4 4 9.65x10'4 2.18x10'4
3 29 1.03x10'3 3.08:.10’4 4 6 9.88x10'5 5.44x10’4
3 30 NP. 1.72x104 4 8 1.23x10'3 5.44x10'4
3 31 4.13x10’4 1.64x10'4 4 9 4.01x10'6 1.00x10'5
3 32 2.36xlo'4 5.72x10'4 4 10 o 9.99x10'6
3 33 3.13x10'3 1.72x10“t 4 12 4.01x10'6 9.98x10'6
3 37 4.19x10'2 6.07x10'3 4 13 4.02x10'6 0
3 39 3.01x10'4 4.42x10'5 4 15 1.45x10'4 1.09x10'2
3 40 3.01x10'2 4.41x10'3 4 16 1.0lx10'3 5.98x10'5
3 42 3.01x10'2 4.42x10' 4 17 1.10x10’4 2.33x10'
3 43 4.19x10'2 6.07x10'3 4 19 1.10x10'4 2.33x10'5
3 46 1.38x10' 0 4 20 1.10x10'4 2.33x10'6
3 47 1.38x10'3 0 4 24 9.89x10'5 3.10x10'4
3 48 1.38x10' 0 4 25 0 2.33x10'6
3 49 1.38x10'2 0 4 26 NP. 1.82x10'6
3 so 1.38x10'1 0 4 27 1.10x10'6 2.33x10'6
3 51 1.38x10'3 0 4 28 3.22x10’5 1.82x10'6
3 52 1.38x10'1 0 4 29 3.22x10'5 1.82x10’6
3 53 1.38x10'1 0 4 30 NP. 5.46x10'6
3 54 1.38x10'3 0 4 31 2.29x10'5 5.28x10'6
3 55 1.38x10'5 0 4 32 8.04x10'5 2.00x10'5

Appendix 3.2 (con't)

 

Pre Post

Pred Prey Exchange Exchange
4 34 1.10x10'4 2.33x10'6
4 35 1.10x10'4 2.33x10’5
4 36 0 1.47x10'4
4 37 23le0'3 3.08x10'4
4 39 1.21x10'5 1.03x10'
4 40 1.21x10'3 1.03x10'4
4 41 0 1.47x10'4
4 42 1.21x10'3 1.03x10“1
4 43 2.32x10'3 3.08x10'4
4 46 6.27x10'5 9.25x10'6
4 47 6.28x10'4 9.24x10'5
4 48 6.28x10“t 9.26x10'5
4 49 6.27x10'3 9.26x10’5
4 50 6.27x10'2 9.25x10'3
4 51 6.27x10“t 9.27x10'6
4 52 6.27x10'2 9.26x10'3
4 53 6.28x10'2 9.26x10'3
4 54 6.27x10“1 9.26x10'5
4 55 6.28x10'6 9.26x10'6
4 57 6.27x10'4 2.94x10“1
4 58 2.26x10'4 8.42x10'5
4 59 2.26x10'4 8.43x10'6
4 60 2.26x10'6 0

4 61 2.26x10"4 8.43x10'5
4 62 2.26x10'4 8.41x10'6
4 63 2.26x10"4 8.42x10"5
4 64 2.26x10'5 8.41x10'6
4 65 2.26x10'4 8.41x10'6
4 66 2.26x10-4 8.42x10'6
4 68 2.26x10'4 8.41x10'5
5 4 1.26x10'3 8.19x10'5
5 6 1.26x10'4 8.18x10'S

 

175

Pre Post
Pred Prey Exchange Exchange
5 7 1.26x10'3 8.20x10'5
5 8 1.05x10'3 8.19x10'5
5 9 1.75x10'5 1.37x10’5
5 10 0 1.37x10'5
5 11 0 1.37x10'6
5 12 1.75x10'5 1.37x10'5
5 13 1.75x10'5 1.37x10'6
5 14 0 1.37x10'6
5 15 5.26x10'4 8.20x10'3
5 16 1.26x10'3 8.18x10'5
5 17 6.31x10“1 5.97x10'5
5 19 6.32x10'4 5.97x10'5
5 20 6.31x10'4 5.98x10'6
5 24 1.26x10'4 8.19x10'5
5 25 0 5.97x10'6
5 27 6.31x10'6 5.97x10'6
5 30 NP. 4.27x10'6
5 32 3.51x10'5 2.73x10'6
5 34 6.32x10’4 5.97x10’6
5 35 6.31x10'4 5.97x10'5
5 36 6.58x10’3 4.35x10“1
5 37 2.61x10'2 1.75x10'3
5 38 1.26x10'3 8.21x10'5
5 39 3.02x10'5 2.08x10'6
5 40 3.02x10'3 2.08x10'4
5 41 6.58x10"3 4.34x10'4
5 42 3.02x10'3 2.08x10'4
5 43 2.61x10'2 1.75x10'3
5 44 1.26x10'3 8.20x10'5
5 45 NP. 8.69x10'l
5 46 6.42x10'5 4.34x10'6
5 47 6.43x10'4 4.33x10’5

Appendix 3.2 (con‘t)

 

Pre Post

Pred Prey Exchange Exchange
5 48 6.43x10.4 4.34x10'5
5 49 6.42x10'3 4.34x10'5
5 so 6.42x10'2 4.34x10'3
5 51 6.42x10'4 4.34x10'6
5 52 6.42x10'2 4.34x10'3
5 53 6.43x10'2 4.34x10'3
5 54 6.42x10'4 4.34x10'5
5 55 6.43x10'6 4.34x10'6
5 56 NP. 8.21x10'6
5 57 2.63x10'3 8.19x10'5
5 58 5.83x10'4 3.95x10'5
5 59 5.83x10'4 3.95x10'6
5 60 5.83x10'6 0

5 61 5.83x10'4 3.95x10'5
5 62 5.83x10'4 3.95x10'6
5 63 5.84x10'4 3.95x10'5
5 64 5.83x10'5 3.94x10'6
5 65 5.84x10'4 3.94x10'6
5 66 5.83x10'4 3.95x10'6
5 68 5.83x10’4 3.94x10'5
6 37 5.42x10“t 1.87x10'3
6 43 5.42x10'4 1.87x10'3
6 46 1.80x10'5 6.23x10'5
6 47 1.80x10'4 6.22x10'4
6 48 1.80x10'4 6.23x10'4
6 49 1.80x10‘3 6.24x10'4
6 50 1.80x10'2 6.23x10'2
6 51 1.80x10'4 6.24x10'5
6 52 1.80x10'2 6235.10"2
6 53 1.80x10'2 6.23x10'2
6 54 1.80xlo'4 6.23x10'4
6 55 1.80x10'6 6.23x10'5

 

176

Pre Post

Pred Prey Exchange Exchange
6 57 8.67x10’5 1.13x10“1
6 58 3.27x10'5 1.13x10“1
6 s9 3.27x10'5 1.13x10'5
6 60 o 1.13x10'6
6 61 3.27x10'5 1.13x10'4
6 62 3.27x10'5 1.13x10'5
6 63 3.27x10'5 1.13x10'4
6 64 3.27x10'6 1.13x10'5
6 65 3.28x10'5 1.13x10'5
6 66 3.27x10'5 1.13x10'5
6 68 3.27x10'5 1.13x10'4
7 36 1.06x10'2 1.24x10'2
7 37 7.36x10'2 8.67x10'2
7 39 2.77x10'5 3.33x10'5
7 40 2.77x10'3 3.33x10'3
7 41 1.06x10'2 1.24x10'2
7 42 2.77x10'3 3.33x10'3
7 43 7.36x10'2 8.67x10'2
7 46 1.06x10'4 1.24x10'4
7 47 1.06x10'3 1.24x10'3
7 48 1.06x10'3 1.24x10'3
7 49 1.06x10'2 1.24x10'3
7 50 1.06x10'l 1.24x10'1
7 51 1.06x10'3 1.24x10'4
7 52 1.06x10'l 1.24x10'1
7 53 1.06x10'1 1.24x10'1
7 54 1.06x10'3 1.24x10'3
7 55 1.06x10'5 1.24x10'4
7 56 NP. 2.38x10'4
7 57 5.28x10'3 2.38x10’3
7 58 9.59x10'4 1.13x10'3
7 59 9.59.110"4 1.13x10'4

Appendix 3.2 (con't)

 

Pre Post
Pred Prey Exchange Exchange
7 60 9.59x10'6 1.13x10'5
7 61 9.59x10'4 1.13x10'3
7 62 9.59x10'4 1.13x10'4
7 63 9.60x10'4 1.13x10'3
7 64 9.59x10'5 1.13x10'4
7 65 9.6lx10'4 1.13x10“1
7 66 9.59x10'4 1.13x10'4
7 67 0 1.13x10.6
7 68 9.59x10'4 1.13x10'3
8 37 3.93x10'3 3.82x10'3
8 43 3.93x10'3 3.82x10'3
8 46 7.85x10'5 7.63x10'5
8 47 7.86x10'4 7.62x10'4
8 48 7.86x10'4 7.63x10'4
8 49 7.85x10'3 7.64x10'4
8 50 7.85x10'2 7.63x10'2
8 51 7.86x10'4 7.64x10'5
8 52 7.86x10'2 7.63x10'2
8 s3 7.86x10'2 7.63x10'2
8 54 7.85x10'4 7.63x10’4
8 55 7.86x10'6 7.63x10'5
8 56 NP. 2.07x10'5
8 s7 5.60x10'4 2.07x10'4
8 58 4.77x10'4 4.61x10'4
8 s9 4.78x10'4 4.61x10'5
8 60 4.78x10'6 4.60x10'6
8 61 4.78x10“t 4.61x10'4
8 62 4.77x10'4 4.60x10'5
8 63 4.78x10'4 4.60x10'4
8 64 4.77x10'5 4.60x10'5
8 65 4.78x10'4 4.60x10'5
8 66 4.77x10'4 4.60x10'5

 

Pre Post
Pred Prey Exchange Exchange
8 68 4.78x10'4 4.60x10'4
9 4 1.89x10'6 0
9 8 1.89x10'6 0
9 15 1.89x10'6 1.84x10'5
9 36 7.37x10'5 8.36x10'6
9 37 3.10x10'5 3.51x10.6
9 4o 2.24x10'5 2.53x10'6
9 41 7.37x10'5 8.36x10'6
9 42 2.24x10'5 2.53x10'6
9 43 3.10x10'5 3.52x10'6
9 44 7.36x10'5 8.38x10'6
9 45 NP. 1.16x10'2
9 47 5.81x10'6 0
9 48 5.81x10'6 0
9 49 5.81x10'5 0
9 50 5.81x10'4 6.55x10'5
9 51 5.81x10'6 0
9 52 5.81x10'4 6.55x10'5
9 53 5.81x10'4 6.55x10'5
9 54 5.81x10'6 0
9 57 4.49x10'5 0
9 58 1.07x10'6 0
9 s9 1.07x10'6 0
9 61 1.07x10'6 0
9 62 1.07x10'6 0
9 63 1.07x10'6 0
9 65 1.07x10'6 0
9 66 1.07x10'6 0
9 68 1.07x10'6 0
10 4 0 1.02x10'6
10 6 0 1.02x10'6
10 8 0 1.02x10'6

177

Appendix 3.2 (con't)

 

Pre Post
Pred Prey Exchange Exchange
10 15 0 1.02x10'4
10 36 0 4.65x10'5
10 37 0 1.96x10'5
10 40 0 1.41x10'5
10 41 0 4.64x10'5
10 42 0 1.41x10'5
10 43 0 1.96x10'5
10 44 0 4.66x10'5
10 45 NP. 6.43x10'2
10 47 0 3.63x10'6
10 48 0 3.64x10'6
10 49 o 3.64x10'6
10 50 5.37x10'6 3.64x10'4
10 52 5.37x10'6 3.64x10'4
10 53 5.37x10'6 3.64x10'4
10 54 0 3.64x10'6
10 57 0 3.40x10'6
11 15 o 1.15x10'6
11 45 NP. 7.23xio'4
11 50 2.33x10'6 4.09x10'6
11 52 2.33x10'6 4.09x10'6
11 53 2.33x10'6 4.09x10'6
12 4 9.59x10'6 4.43x10'6
12 6 0 4.43x10'6
12 8 9.58x10'6 4.43x10'6
12 15 9.57x10'6 4.43x10'4
12 36 3.73x10'4 2.02x10'4
12 37 1.57x10'4 8.49x10'5
12 39 1.13x10'6 0
12 40 1.13x10'4 6.10x10'5
12 41 3.73x10'4 2.02x10'4
12 42 1.13x10'4 6.11x10'5

 

Pre Post
Pred Prey Exchange Exchange
12 43 1.57x10'4 8.50x10'5
12 44 3.73x10'4 2.02x10’4
12 45 NP. 2.79x10'l
12 46 2.94x10'6 1.58x10'6
12 47 2.94x10'5 1.58x10'5
12 48 2.94x10'5 1.58x10'5
12 49 2.94x10'4 1.58x10'5
12 50 2.94x10'3 1.58x10'3
12 51 2.94x10'5 1.58x10'6
12 52 2.94x1o'3 1.58x10'3
12 53 2.94x10’3 1.58x10'3
12 54 2.94x10'5 1.58x10'5
12 55 0 1.58x10'6
12 56 NP. 1.48x10'6
12 57 2.27x10'4 1.48x10'5
12 58 5.44x10'6 2.95x10'6
12 59 5.44x10'6 0
12 61 5.44x10'6 2.95x10'6
12 62 5.44x10'6 0
12 63 5.4sx10'6 2.95x10'6
12 65 5.45x10'6 0
12 66 5.44x10'6 0
12 68 5.44x10'6 2.95x10'6
13 15 0 2.29x10'6
13 36 2.85x10'5 1.04x10'6
13 37 1.20x10'5 0
13 4o 8.63x10'6 0
13 41 2.85x10"5 1.04x10'6
13 42 8.63x10'6 0
13 43 1.20x10'5 0
13 44 2.84x10'5 1.05x10'6
13 45 NP. 1.44x10'3

178

Appendix 3.2 (con‘t)

 

 

Pre Post Pre Post
Pred Prey Exchange Exchange Pred Prey Exchange Exchange
13 47 2.25x10'6 0 15 62 1.81x10'5 2.13x10“1
13 48 2.25x10'6 0 15 63 1.81x10'5 2.13x10'3
13 49 2.25x10'5 0 15 64 1.81x10'6 2.13x10’4
13 50 2.25x10"4 8.17x10'6 15 65 1.81x10'5 2.13x10'4
13 51 2.25x10'6 0 15 66 1.81x10'5 2.13x10'4
13 52 2.25x10'4 8.18x10'6 15 67 0 2.13x10’6
13 53 2.25x10’4 8.18x10’6 15 68 1.81x10'5 2.13x10'3
13 54 2.25x10"6 0 16 36 1.59x10'4 4.1sx10'S
13 57 1.73x10'5 0 16 37 1.59x10“t 4.14x10'5
14 15 0 1.83x10'6 16 41 1.59x10“1 4.15x10'5
14 45 NP. 1.15x10'3 16 43 1.59x10'4 4.14x10'5
14 50 6.90x10'° 6.53x10'6 16 46 2.09x10'4 5.38x10'5
14 52 6.90x10'6 6.54x10'6 16 47 2.09x10'3 5.37x10'4
14 53 6.90x10'6 6.53x10'6 16 48 2.09x10’3 5.38x10'4
15 37 2.24x10'5 2.64x10'3 16 49 2.09x10'2 5.39x10“t
15 43 2.24x10'5 2.64x10'3 16 50 2.09x10'l 5.38x10'2
15 46 1.99x10'6 2.35x10'4 16 51 2.09x10'3 5.39x10'5
15 47 1.99x10'5 2.34x10'3 16 52 2.09x10'l 5.39x10'2
15 48 1.99x10'5 2.35x10'3 16 53 2.09x10'l 5.38x10'2
15 49 1.99x10'4 2.35x10'3 16 54 2.09x10'3 5.38x10’4
15 50 1.99x10'3 2.3sx10'l 16 55 2.09x10'5 5.38x10'5
15 51 1.99x10'5 2.3sx1o'4 16 56 NP. 8.30x10'6
15 52 1.99x10'3 2.35x10'l 16 57 3.18x10'4 8.28x10'5
15 53 1.99x10'3 2.35x10'l 16 58 9.04x10’4 2.33x10'4
15 54 1.99x10'5 2.35x10'3 16 59 9.04x10’4 2.33x10'5
15 55 o 2.35x10-4 16 60 9.04x10'6 2.33x10'6
15 56 NP. 5.87x10'5 16 61 9.05x10'4 2.33x10'4
15 57 4.98.110'5 5.32x10’4 16 62 9.04x10'4 2.33x10'5
15 58 1.81x10'5 2.13x10'3 16 63 9.05x10-4 2.33x10'4
15 59 1.81x10'5 2.13x10'4 16 64 9.04x10'5 2.33x10'5
15 60 0 2.13x10'5 16 65 9.06x10’4 2.33x10'5
15 61 1.81x10'5 2.13x10'3 16 66 9.04x10'4 2.33x10'5

179

Appendix 3.2 (con't)

 

Pre Post
Pred Prey Exchange Exchange
16 68 9.04x10'4 2.33x10'4
17 16 1.70x10'3 1.99x10'5
17 17 1.52x10’4 2.58x10'6
17 19 1.52x10'4 2.58x10'6
17 20 1.52x10'4 0
17 27 1.52x10'6 0
17 34 1.52x10'4 0
17 35 1.52x10'4 2.58x10'6
17 36 1.53x10'2 2.58x10'4
17 37 2.35x10'2 3.97x10'4
17 38 1.17x10'3 1.99x10'5
17 39 7.79x10'5 1.32x10'6
17 40 7.79x10'3 1.32x10’4
17 41 1.53x10’2 2.58x10'4
17 42 7.79x10'3 1.32x10“t
17 43 2.35x10'2 3.97x10'4
17 44 1.17x10’3 1.99x10'5
17 45 NP. 1.99x10'2
18 50 NP. 1.36x10'5
18 52 NR 1.36x10'5
18 53 NP. 1.36x10'5
19 36 5.04x10'2 3.00x10'3
19 37 7.75x10'2 4.60x10'3
19 38 3.84x10'3 2.31x10'4
19 39 2.57x10'4 1.53x10'5
19 4o 2.57x10'2 1.53x10'3
19 41 5.04x10'2 3.00x10'3
19 42 2.57x10'2 1.53x10'3
19 43 7.74x10'2 4.61x10'3
19 44 3.84x10'3 2.31x10'4
19 45 NP. 2.31x10'l
20 16 1.25x10'4 1.75x10'6

 

Pre Post
Pred Prey Exchange Exchange
20 19 1.11x10'5 0
20 20 1.11x10'5 0
20 34 1.11x10'5 0
20 3s 1.11x10'5 0
20 36 1.12x10'3 2.27x10'5
20 37 1.73x10'3 3.48x10'5
20 38 8.57x10'5 1.75x10'6
20 39 5.72x10'6 0
20 40 5.72x10'4 1.16x10'5
20 41 1.12x10'3 2.27x10'5
20 42 5.72x10'4 1.16x10'5
20 43 1.73x10'3 3.49x10'5
20 44 8.57x10'5 1.75x10'6
20 45 NP. 1.75x10'3
21 36 1.03x10'2 1.33x10'5
21 37 1.03x10'2 1.33x10'5
21 38 1.44x10'2 1.86x10'5
21 39 7.16x10'6 0
21 4o 7.17x10'4 0
21 41 1.03x10'2 1.33x10'5
21 42 7.17x10'4 0
21 43 1.03x10'2 1.33x10'5
21 44 2.07x10'2 2.66x10’5
21 45 NP. 5.31x10'2
21 75 2.07x10'2 2.66x10'2
21 76 6.18x10'2 7.97x10’4
21 77 2.15x10'3 2.66x10'6
21 79 2.15x10'3 2.66x10'6
22 50 NP. 1.31x10'6
22 52 NP. 1.31x10'6
22 53 NP. 1.31x10'6
23 16 5.43x10'3 2.99x10'6

180

Appendix 3.2 (con't)

 

 

Pre Post Pre Post
Pred Prey Exchange Exchange Pred Prey Exchange Exchange
23 24 4.33x10'4 2.33x10'5 24 66 4.56x10'4 1.84x10'6
23 32 2.01x10'4 1.10x10'6 24 68 4.56x10'4 1.84x10'5
23 36 3.07x10'3 1.66x10'5 24 70 5.04x10'3 2.03x10’4
23 37 3.07x10'3 1.66x10'5 24 71 5.04x10'3 2.03x10'3
23 38 6.13x1o'3 3.33x10"5 24 72 5.03x10'3 2.03x10'4
23 39 2.01x10'6 0 24 73 5.04x10'4 2.03x10'5
23 4o 2.01x10'4 1.10x10'6 24 74 5.05x10'3 2.03x10'5
23 41 3.07x10'3 1.66x10'5 24 75 5.02x10'3 2.02x10'l
23 42 2.01x10'4 1.10x10'6 24 77 5.02x10'3 2.02x10'4
23 43 3.07x10'3 1.66x10'5 25 36 2.17x10'6 4.34x10'6
23 44 6.14x10'3 3.32x10'5 25 37 3.34x10'6 6.66x10'6
23 45 NP. 1.33x10'l 25 40 1.11x10'6 2.21x10'6
24 46 5.02x10'5 2.02x10'6 25 41 2.17x10'6 4.33x10'6
24 47 5.02x10'4 2.02x10'5 25 42 1.11x10'6 2.21x10'6
24 48 5.02x10'4 2.02x10'5 25 43 3.34x10'6 6.67x10'6
24 49 5.02x10'3 2.02x10'5 25 45 NP. 3.33x10‘4
24 50 5.02x10'2 2.02x10'3 26 3 NR 2.54x10’6
24 51 5.02x10'4 2.02x10'6 26 4 NR 2.54x10'6
24 52 5.02x10'2 2.02x10'3 26 s NP. 4.41x10'5
24 53 5.02x10'2 2.02x10'3 26 6 NR 2.48x10'5
24 54 5.02x10'4 2.02x10'5 26 7 NR 1.23x10'5
24 55 5.02x10'6 2.02x10'6 26 8 NR 1.235.10'5
24 56 NP. 0 26 9 NR 5.51x10'6
24 57 1.21x10'3 1.02x10'4 26 10 NP. 5.51x10'6
24 58 4.56x10'4 1.84x10'5 26 12 NP. 5.50x10'6
24 59 4.56x10'4 1.84xlo'6 26 15 NP. 1.71x10'3
24 6o 4.56x10'6 0 26 16 NP. 1.23x10'5
24 61 4.56x10'4 1.84x10'5 26 19 NP. 1.75x10'6
24 62 4.56x10'4 1.84x10'6 26 21 NP. 2.54x10'6
24 63 4.56x10'4 1.84x10'5 26 23 NP. 2.54x10'6
24 64 4.56x10'5 1.84x10'6 26 24 NP. 1.23x10'5
24 65 4.56x10'4 1.84x10'6 26 31 NP. 1.06x10'6

181

Appendix 3.2 (con't)

 

 

Pre Post Pre Post
Pred Prey Exchange Exchange Pred Prey Exchange Exchange
26 33 NP. 2.33x10'6 28 29 4.98x104 0
26 35 NP. 1.75x10'6 28 31 8.30x10'5 0
26 4o N.p. 4.09x10'6 28 32 2.77x10'4 0
26 42 NP. 4.10x10'6 28 33 4.15x10'4 2.14x10'6
27 36 7.34x10'6 6.31x10'6 28 34 1.31x10'3 0
27 37 1.13x10'5 9.69x10'6 28 35 1.31x10'3 1.61x10'6
27 40 3.74x10'6 3.21x10'6 28 39 4.15x10'5 0
27 41 7.33x10'6 6.31x10'6 28 40 4.15x10'3 3.76x10‘6
27 42 3.74x10'6 3.22x10'6 28 42 4.15x10'3 3.77x10'6
27 43 1.13x10'5 9.70x10'6 29 3 2.08x10’3 8.24x10'6
27 45 NP. 4.85x10'4 29 4 1.04x10'3 8.24x10'6
28 3 4.15x10'3 2.33x10'6 29 5 2.69x10'3 1.43x10'4
28 4 2.08x10'3 2.33x10'6 29 6 9.95x10'4 8.03x10'5
28 5 5.39x10'3 4.05x10'5 29 7 3.12x10'3 3.98x10'5
28 6 1.99x10'3 2.27x10'5 29 8 2.29x1o'3 3.97x10'5
28 7 6.24x10'3 1.13x10'5 29 9 6.92x10'6 1.79x10'5
28 8 4.57x10'3 1.13x10'5 29 10 0 1.79x10'5
28 9 1.38x10'5 5.07x10'6 29 11 0 1.79x10'6
28 10 0 5.07x10'6 29 12 6.92x10'6 1.79x10'5
28 12 1.38x10'5 5.06x10'6 29 13 6.93x10'6 1.79x10'6
28 13 1.38x10'5 0 29 14 0 1.79x10'6
28 15 1.25x10'3 1.57x10'3 29 15 6.22x10“1 5.56x10'3
28 16 7.89x10'3 1.13x10'5 29 16 3.95x10'3 3.97x10'5
28 17 1.31x10'3 1.61x10'6 29 17 6.52x10'4 5.69x10'6
28 19 1.31x10'3 1.61x10'6 29 19 6.52x10'4 5.70x10'6
28 20 1.31x10'3 0 29 20 6.52x10’4 0
28 21 2.08x10'3 2.33x10'6 29 21 1.04x10'3 8.24x10'6
28 23 8.30x10'4 2.33x10'6 29 23 4.15x10"4 8.24x10‘6
28 24 4.15x10'4 1.13x10'5 29 24 2.08x10'4 3.98x10'5
28 25 1.31x10'6 0 29 26 NP. 2.75x10'6
28 27 1.31x10'5 0 29 27 6.52x10'6 0
28 28 4.98x10'4 0 29 28 2.49x10'4 2.75x10'6

182

Appendix 3.2 (con't)

 

Pre Post
Pred Prey Exchange Exchange
29 29 2.49x10'4 2.75x10'6
29 31 4.15x10'5 3.43x10'6
29 32 1.39x1o'4 2.75x10'6
29 33 2.08x10'4 7.56x10'6
29 34 6.52x10'4 0
29 35 6.52x10'4 5.70x10'6
29 39 2.08x10'5 0
29 4o 2.08x10'3 1.33x10'5
29 42 2.08x10'3 1.33x10'5
30 45 NP. 3.68x10'3
30 50 NP. 3.05x10'6
30 52 NP. 3.06x10'6
30 53 NP. 3.06x10'6
31 4 2.19x10'4 1.68x10'5
31 5 2.11x10'3 1.54x10'4
31 6 3.17x10'4 2.50x10'4
31 7 1.06x10'3 8.40x10'5
31 8 1.06x10’3 8.39x10'5
31 9 3.66x10’5 2.55x10'6
31 10 0 2.55x10'6
31 12 3.66x10'5 2.55x10'6
31 13 3.66x10'5 0
31 15 1.06x10'3 8.40x10'3
31 16 1.26x10'3 7.63x10'5
31 17 3.02x10'4 2.36x10'5
31 19 3.02x10'4 2.36x10'5
31 20 3.02x10'4 2.36x10'6
31 24 2.19x10'5 1.68x10'5
31 25 0 2.36x10'6
31 27 3.02x10-6 2.36x10'6
31 30 NP. 1.53x10'6
31 31 9.97x10'5 1.53x10'°

 

Pre Post
Pred Prey Exchange Exchange
31 32 7.31x10'5 5.09x10'6
31 33 2.19x10'4 1.68x10'5
31 34 3.02x10'4 2.36x10'6
31 35 3.02x10'4 2.36x10'5
31 37 5.29x10'4 4.20x10'5
31 39 1.96x10'5 1.54x10'6
31 40 1.96x10'3 1.54x10'4
31 42 1.96x10'3 1.54x10'4
31 43 5.29x10'4 4.20x10'5
32 37 1.46xlo'4 3.56x10'4
32 43 1.46x10'4 3.57x10'4
32 46 4.87x10'6 1.19x10'5
32 47 4.87x10'5 1.19x10'4
32 48 4.87x10'5 1.19x10'4
32 49 4.87x10'4 1.19x10'4
32 50 4.87x10'3 1.19x10'2
32 51 4.87x10’5 1.19x10'5
32 52 4.87x10'3 1.19x10'2
32 53 4.87x10'3 1.19x10'2
32 54 4.87x10'5 1.19x10'4
32 55 0 1.19x10'5
32 56 . N.p. 2.38x10’6
32 57 9.75x10'5 2.38x10'4
32 58 7.97x10'6 1.9sx10'5
32 59 7.98x10'6 1.95x10'6
32 61 7.98x10'6 1.95x10'5
32 62 7.98x10'6 1.95x10'6
32 63 7.99x10'6 1.95x10'5
32 64 o 1.95x10'6
32 65 7.99x10'6 1.95x10'6
32 66 7.97x10'6 1.95x10'6
32 68 7.98x10'° 1.95x10'5

183

Appendix 3.2 (con't)

 

Pre Post
Pred Prey Exchange Exchange
33 36 4.90x10'3 1.64x10'3
33 37 4.90x10'3 1.64x10'3
33 39 1.63x10'5 5.49x10'6
33 40 1.63x10'3 5.48x104
33 41 4.90x10'3 1.64x10'3
33 42 1.63x10'3 5.49xio'4
33 43 4.90x10'3 1.64x10'3
34 16 9.56x10'5 1.31x10'6
34 19 8.54x10'6 0
34 34 8.54x10'6 0
34 35 8.54x10'6 0
34 36 8.60x10'4 1.70x10'5
34 37 1.33x10'3 2.62x10'5
34 38 6.56x10'5 1.31x10'6
34 39 4.38x10'6 0
34 40 4.38x10-4 8.67x10’6
34 41 8.60x10'4 1.70x10'5
34 42 4.38x10“4 8.68x10'6
34 43 1.33x10'3 2.62x10'5
34 44 6.57x10'5 1.31x10'6
34 45 NP. 1.31x10'3
35 36 3.62x10'2 2.54x10'3
35 37 5.57x10'2 3.90x10'3
35 38 2.77x10'3 1.96x10'4
35 39 1.85x10'4 1.30x10'5
35 4o 1.85x10'2 1.30x10'3
3s 41 3.62x10'2 2.54x10'3
35 42 1.85x10'2 1.30x10'3
35 43 5.57x10'2 3.91x10'3
35 44 2.77x10'3 1.96x10'4
35 45 NP. 1.96x10'l
36 36 3.82x10'2 9.35x10‘3

 

Pre Post
Pred Prey Exchange Exchange
36 76 2.14x10'l 1.05
36 77 1.45x10'l 7.08x10'2
36 79 2.99x10'l 1.46x10'l
37 70 6.43x10'l 1.29x10'l
37 71 6.43x10'l 1.29
37 72 6.42x10"l 1.29x10'l
37 73 6.43x10'2 1.29x10'2
37 74 6.44x10'I 1.29x10'2
37 77 1.81x10'l 3.63x10'2
37 79 2.17x10'l 4.35x10'2
38 70 2.56.110'2 1.45x10'2
38 71 2.56x10‘2 1.45x10'l
38 72 2.56x10'2 1.45x10'2
38 73 2.56x10'3 1.45x10'3
38 74 2.57x10'2 1.45x10'3
38 79 1.10x10'l 6.21x10’2
38 8o 1.79x10'2 1.01x10'2
39 37 5.83x10'4 3.57x10'4
39 38 3.49x10'5 2.15x10'5
39 39 1.94x10'6 1.19x10’6
39 40 1.94x10'4 1.19x10'4
39 42 1.94x10'4 1.19x10'4
39 44 5.82x10'4 3.58x10'4
39 7o 1.13x10-4 6.91x10'5
39 71 4.37x10'5 2.69x10'4
39 74 1.13x10'4 6.92x10'6
39 76 1.13x10'4 6.92x10'4
39 77 4.37x10'5 2.69x10'5
39 79 3.61x10'3 2.22x10'3
40 36 5.69x10'3 1.06x10'3
4o 37 2.00x10'2 3.74x10'3
40 4o 1.44x10'2 2.69x10'3

184

Appendix 3.2 (con't)

 

Pre Post

Pred Prey Exchange Exchange
40 42 1.44x10'2 2.69x10'3
40 43 4.31x10'3 8.06x10'4
4o 46 5.33x10'4 9.96x10'5
40 47 5.33x10'3 9.94x10'4
40 48 5.33x10'3 9.96x10'4
40 49 5.33x10'2 9.97x10'4
40 so 4.09x10'1 7.64x10'2
40 51 4.09x10"3 7.65x10'5
40 52 4.09x10'l 7.64x10'2
40 53 4.09x10'l 7.64x10'2
40 54 5.33x10'3 9.96x10’4
40 55 4.09x10"5 7.64x10'5
40 58 5.73x10'3 1.07x10'3
40 59 5.73x10'3 1.07x10'4
40 60 5.73x10"5 1.07x10'5
40 61 5.73x10'3 1.07x10'3
40 62 5.73x10'3 1.07x10'4
40 63 5.74x10'3 1.07x10'3
40 64 5.73x10'4 1.07x10'4
40 65 5.74x10'3 1.07x10'4
4o 66 5.73x10'3 1.07x10'4
40 67 0 1.07x10'6
40 68 5.73x10'3 1.07x10'3
40 69 1.96x10'3 3.67x10'3
40 7o 6.96x10'2 1.30x10’2
40 71 4.17x10"2 7.79x10"2
40 74 6.97x10'2 1.30x10'3
4o 75 9.85x10'3 1.84
40 76 6.95x10'2 1.30x10'l
40 77 4.17x10'2 7.80x10'3
4o 79 7.49x10'2 1.40x10'2
41 36 9.62x10'3 3.14xlo’3

 

Pre Post
Pred Prey Exchange Exchange
41 41 9.61x10'3 3.14x1o'3
41 76 5.39x10'2 3.52x10'l
41 77 3.64x10'2 2.38x10'2
41 79 7.53x10'2 4.91x10'2
42 37 7.23.110"3 7.57x10'4
42 38 7.21xlo'3 7.59x10'4
42 4o 3.62x10'3 3.79x10'4
42 42 3.62x10'3 3.80x10'4
42 43 4.63x10'l 4.85x10'2
42 44 2.39x10'l 2.51x10'2
43 77 1.62x10'l 6.88x10'2
43 79 9.19x10'l 3.90x10'l
44 75 9.88x10'2 3.20x10'l
44 76 6.58x10'2 2.14x10'3
44 77 9.88x10'2 3.20x10'4
44 79 6.59x10'2 2.14x10‘4
45 70 NP. 2.55x10l
45 71 NP. 2.55x102
45 72 NP. 2.55x10l
45 73 NP. 2.54
45 74 NP. 2.55
45 78 NP. 3.91x10l
45 80 NP. 2.94x101
46 7o 4.00x10'3 4.64x10'3
46 71 4.00x10'3 4.64x10'2
46 72 4.00x10"3 4.64x10'3
46 73 4.00x10"4 4.64x10'4
46 74 4.01x10'3 4.65x10'4
46 78 2.22x10'3 2.58x10'3
47 70 4.63x10'l 1.10x10'l
47 71 4.64x10'1 1.1
47 72 4.63x10’l 1.10x10'l

185

Appendix 3.2 (con't)

 

Pre Post

Pred Prey Exchange Exchange
47 73 4.64x10'2 1.10x10'2
47 74 4.64x10'l 1.10x10'2
47 78 2.58x10'l 6.14x10'2
48 70 9.13x10'2 3.65x10'2
48 71 9.14x10'2 3.65x10'l
48 72 9.13x10'2 3.66x10'2
48 73 9.13x10'3 3.65x10'3
48 74 9.15x10'2 3.66x10'3
48 78 5.07x10'2 2.03x10'2
49 70 3.24x1o'l 2.89x10'2
49 71 3.24x10'l 2.89x10'l
49 72 3.24x10'l 2.89x10'2
49 73 3.24x10'2 2.89x10'3
49 74 3.25x10'l 2.89x10’3
49 78 1.80x10'l 1.60x10'2
50 7o 9.68x10"l 7.10x10'l
50 71 9.69x10'l 7.1
50 72 9.67x10'l 7.10x10'l
50 73 9.68x10'2 7.10x10'2
50 74 9.70x10'l 7.11x10'2
50 78 5.38x10'I 3.95x10’l
51 7o 1.95x10'2 1.31x10'3
51 71 1.9sx10'2 1.31x10'2
51 72 1.95x10'2 1.31x10'3
51 73 1.95x10'3 1.31x10'4
51 74 1.95x10'2 1.31x10'4
51 78 1.08x10'2 7.24x10'4
52 70 1.05 3.73x10'l
52 71 1.05 3.73
52 72 1.05 3.73x10'l
52 73 1.05x10'l 3.73x10'2
52 74 1.05 3.73x10'2

 

Pre Post
Pred Prey Exchange Exchange
52 78 5.83x10'l 2.07x10'l
53 70 1.7 4.27x10'l
53 71 1.7 4.27
53 72 1.7 4.27x10'l
53 73 1.70x10'l 4.27x10'2
53 74 1.7 4.27x10'2
53 78 9.43x10'l 2.37x10'I
54 7o 1.44x10'l 7.65x10'2
54 71 1.44x10'l 7.65x10'l
54 72 1.44x10'l 7.65x10'2
54 73 1.44x10'2 7.65x10'3
s4 74 1.44x10'l 7.66x10'3
54 78 8.01x10'2 4.25x10'2
55 70 1.49x10'3 5.06x10'3
55 71 1.49x10’3 5.06x10"2
55 72 1.49x10'3 5.06x10'3
55 73 1.49x10’4 5.05x10’4
55 74 1.49x10'3 5.06x10’4
55 78 8.25x10'4 2.81x10'3
s6 58 NP. 1.25x10'3
56 59 NP. 1.25x10’4
s6 60 N.p. 1.25x10'5
56 61 NP. 1.25x10'3
56 62 N.p. 1.25x10’4
s6 63 NP. 1.25x10'3
56 64 N.p. 1.25x10'4
56 65 NP. 1.25x10'4
56 66 NP. 1.25x10'4
56 67 NP. 1.25x10'6
56 68 NP. 1.25x10'3
s7 46 3.32x10'5 4.80x10'5
57 47 3.32x10'4 4.79x10'4

186

Appendix 3.2 (con‘t)

 

Pre Post
Pred Prey Exchange Exchange
57 48 3.32x10'4 4.80x10'4
57 49 3.32x10'3 4.80x10'4
57 50 3.32x10'2 4.80x10'2
57 51 3.32x10'4 4.80x10'5
57 52 3.32x10'2 4.80x10'2
57 53 3.32x10'2 4.80x10'2
s7 54 3.32x10'4 4.80x10.4
57 55 3.32x10'6 4.80x10'5
57 58 7.55x10'5 1.09x10'4
57 59 7.55x10'5 1.09x10'S
57 60 0 1.09x10'6
57 61 7.55x10'5 1.09x10'4
57 62 7.55x10'5 1.09x10'5
57 63 7.56x10'5 1.09x10'4
57 64 7.55x10'6 1.09x10'5
57 6s 7.56x10'5 1.09x10'5
57 66 7.55x10'5 1.09x10'5
57 68 7.55x10'5 1.09x10'4
58 47 3.35x10'2 3.79x10'2
58 48 3.35x10'2 3.79x10'2
58 54 3.34x10'2 3.79x10'2
58 60 1.52x10'4 1.73x10'4
58 61 1.52x10'2 1.73x10'2
58 62 1.52x10'2 1.73x10'3
58 63 1.52x10'2 1.73x10'2
58 64 1.52x10'3 1.73x10’3
58 66 1.52x10'2 1.73x10'3
58 67 1.52x10’6 1.73x10'5
58 68 1.52x10'2 1.73x10'2
58 69 5.01x10'3 6.31x10'3
58 72 1.33x10'l 1.27x10'l
58 73 1.33x10'2 1.27x10'2

 

Pre Post
Pred Prey Exchange Exchange
58 74 1.33x10'l 1.27x10'2
59 47 4.41x10'3 5.10x10'3
59 48 4.41x10'3 5.11x10'3
59 54 4.40x10'3 5.11x10'3
59 60 2.00x10'5 2.33x10’5
59 61 2.00x10'3 2.33x10'3
59 62 2.00x10’3 2.32x10“1
59 63 2.00x10'3 2.33x10'3
59 64 2.00x10'4 2.32x10'4
59 66 2.00x10'3 2.33x10'4
59 67 0 2.33x10'6
59 68 2.00x10'3 2.32x1o'3
59 69 6.61x10'4 8.51x10’4
59 72 1.76x10'2 1.71x10'2
59 73 1.76x10'3 1.71x10'3
59 74 1.76x10'2 1.71x10'3
60 47 9.59x10'4 2.41x10'3
60 48 9.59x10'4 2.42x10'3
60 54 9.58x10'4 2.42x10'3
60 60 4.35x10'6 1.10x10'5
60 61 4.35x10'4 1.10x10'3
60 62 4.35x10'4 1.10x10’4
60 63 4.36x10'4 1.10x10'3
6O 64 4.35x10'5 1.10x10’4
60 66 4.35x10'4 1.10x10'4
60 67 0 1.10x10'6
60 68 4.35x10'4 1.10x10'3
60 69 1.44x10'4 4.02x10'4
6O 72 3.83x10’3 8.05x10'3
60 73 3.83x10'4 8.05x10’4
60 74 3.84x10'3 8.06x10’4
61 47 4.25x10'2 1.12x10'l

187

Appendix 3.2 (con't)

 

 

Pre Post Pre Post
Pred Prey Exchange Exchange Pred Prey Exchange Exchange
61 48 4.25x10'2 1.12x10'l 63 62 1.35x10'l 1.23x10’2
61 54 4.25x10'2 1.12x10'l 63 63 1.35x10'l 1.23x10'l
61 6o 1.93x10'4 5.06x10'4 63 64 1.35x10'2 1.23x10'2
61 62 1.93x10'2 5.06x10'3 63 66 1.35x10’l 1.23x10'2
61 63 1.93x10'2 5.06x10'2 63 67 1.35x10'5 1.23x10'4
61 64 1.93x10'3 5.06x10'3 63 68 1.3sx10'l 1.23x10'l
61 66 1.93x10'2 5.06x10'3 63 69 4.45x10'2 4.51x10'2
61 67 1.93x10'6 5.06x10'5 63 72 1.19 9.02x10'l
61 68 1.93x10'2 5.06x10'2 63 73 1.19x10'l 9.02x10'2
61 69 6.38x10'3 1.85x10'2 63 74 1.19 9.03x10'2
61 72 1.70xlo'l 3.71x10'l 64 68 1.91x10'3 1.93x10'3
61 73 1.70x10'2 3.71x10'2 64 69 6.31x10'4 7.05x10’4
61 74 1.70x10'l 37le0'2 64 70 1.68x10'2 1.41x10'2
62 47 1.90x10'2 1.68x10'2 64 71 1.68x10'2 1.41x10'l
62 48 1.90x10'2 1.68x10'2 64 72 1.68x10'2 1.41x10'2
62 54 1.90x10'2 1.68x10'2 64 73 1.68x10'3 1.41x10'3
62 60 8.65x10'5 7.64x10'5 64 74 1.68x10’2 1.41x10'3
62 61 8.66x10'3 7.65x10'3 65 68 1.70x10'3 2.40x10'4
62 63 8.66x10’3 7.64x10'3 65 69 5.60x10'4 8.78x10'5
62 64 8.65x10’4 7.63x10’4 65 71 1.50x10'2 1.76x10'2
62 66 8.65x10'3 7.64x10'4 65 72 1.50x10'2 1.76x10'3
62 67 o 7.64x10'6 65 73 1.50x10'3 1.76x10’4
62 68 8.65x10'3 7.63x10'3 65 74 1.50x10'2 1.76x10'4
62 69 2.86x10’3 2.80x10'3 66 68 7.15x10'3 1.27x10’3
62 72 7.61x10'2 5.60x10'2 66 69 2.36x10'3 4.64x10'4
62 73 7.61x10'3 5.60x10'3 66 70 6.29x10'2 9.29x10'3
62 74 7.63x10'2 5.61x10'3 66 71 6.30x10’2 9.29x10’2
63 47 2.96x10'l 2.70x10'l 66 72 6.29x10'2 9.29x10'3
63 48 2.96x10'l 2.71x10'l 66 73 6.29x10'3 9.29x10'4
63 54 2.96x10'l 2.71x10’l 66 74 6.30x10'2 9.31x10'4
63 60 1.35x10'3 1.23x10'3 67 70 5.55x10'5 1.18x10'4
63 61 1.35x10'l 1.23x10'l 67 71 5.56x10'5 1.18x10'3

188

Appendix 3.2 (con't)

 

 

Pre Post Pre Post
Pred Prey Exchange Exchange Pred Prey Exchange Exchange
67 72 5.55x10'5 1.18x10'4 79 2 5.68x10'2 1.36x10'2
67 73 5.56x10’6 1.18x10'5 79 3 8.62x10'2 9.09x10'3
67 74 5.56x10'5 1.18x10'5 79 7 0 6.78x10'2
67 79 5.55x10'5 1.18x10‘4 79 8 0 1.96x10'2
68 71 6.69x10'2 2.01x10'l 79 10 0 3.26x10'3
68 72 6.68x10'2 2.01x10'2 79 12 7.35x10'4 3.04x10'2
68 73 6.68x10'3 2.01x10'3 79 15 o 1.78x10'l
68 74 6.69x10'2 2.01x10'3 79 16 2.94x10'2 2.36x10'2
69 70 5.28x10'2 1.78x10'2 79 17 8.49x10'3 1.82x10'3
69 71 5.28x10'2 1.78x10'l 79 19 2.97x10'2 2.52x10'2
69 72 5.28x10'2 1.78x10'2 79 20 0 8.85x10'5
69 73 5.28x10'3 1.78x10'3 79 21 5.26x10'3 4.65x10'3
69 74 5.29x10'2 1.78x10'3 79 23 1.01x10'3 9.79x10'3
69 78 6.60x10'2 2.23x10'2 79 24 4.51x10'2 3.51x10'2
78 7 o 7.16x10'3 79 25 0 1.11x10'5
78 8 0 2.06x10'3 79 27 0 2.90x10'5
78 10 0 3.44x10'4 79 28 1.03x10'3 0
78 12 8.22x10'5 3.21x10'3 79 30 NP. 5.46x10"4
78 15 0 1.88x10'2 79 32 2.31x10‘3 9.59x10'3
78 16 3.70x10'3 2.81x10'3 79 33 0 2.06x10'3
78 21 5.89x10'4 0 79 34 0 1.27x10'4
78 32 2.59x10'4 1.01x10'3 79 35 2.41x10'2 1.70x10'2
78 45 NP. 2.57x10l 79 36 1.52x10'l 6.77x10'1
78 7o 6.93x10l 1.19x10l 79 37 1.85 1.12
78 71 1'.39x102 o 79 38 2.04x10’2 6.51x10'2
78 72 2.51 0 79 39 0 2.84x10’4
78 73 2.28 8.86x10'l 79 40 2.86x10'l 6.39x10'l
78 74 0 6.97 79 41 0 2.17x10'l
78 75 3.29 2.68x10l 79 43 o 8.50x10'2
78 76 1.96 2.52x10I 79 44 o 1.87x10'l
78 77 5.68x10'l 3.90x10'l 79 45 NP. 6.33x10l
79 1 1.30x10'5 5.48x10’5 79 46 1.50x10'2 5.22x10'2

189

Appendix 3.2 (con't)

 

 

Pre Post Pre Post
Pred Prey Exchange Exchange Pred Prey Exchange Exchange
79 47 1.49 8.16x10'l 80 51 3.75x10'3 6.23x10'4
79 49 1.19 3.21x10'l 80 52 1.29x10'l 1.28x10'l
79 50 1.14 4.01 80 53 6.62x10’l 3.46x10'l
79 51 3.31x10'2 7.65x10'3 80 55 4.33x10'4 2.99x10'3
79 52 1.14 1.57 80 56 NP. 2.09x10'4
79 53 5.85 4.24 80 57 4.37x10’3 5.94x10'3
79 55 3.83x10’3 3.67x10'2 80 58 3.19x10'2 1.67x10'2
79 56 NP. 2.56x10'3 80 59 3.22x10'3 2.27x10'3
79 57 3.86x10'2 7.29x10'2 80 6o 6.70:110'4 8.64x10'4
79 58 2.82x10'l 2.05x10'l 80 61 1.62x10'2 3.06x10'2
79 59 2.84x10'2 2.78x10'2 80 62 0 5.34x10'3
79 6O 5.92x10'3 1.06x10'2 80 63 2.66x10'l 9.98x10'2
79 61 1.43x10'l 3.75x10'l 80 64 1.24x10'3 5.11x10'3
79 62 o 6.55x10'2 80 65 1.76x10'3 8.28x10'4
79 63 2.35 1.22 80 66 0 2.48x10'3
79 64 1.09x10'2 6.27x10'2 80 67 1.40x10'5 4.27x10'5
79 65 1.55x10'2 1.02x10'2 80 69 2.13x10'2 1.15x10'2
79 66 0 3.04x10'2 8o 70 2.34x10l 3.05
79 67 1.24x10'4 5.23x10'4 80 71 4.70x10] 0
79 69 1.88x10'l 1.41x10'l 80 72 8.48x10'1 0
79 70 2.29x10l 4.16 80 73 7.71x10'l 2.28x10'l
79 71 4.61x101 0 80 74 0 1.79
79 72 8.32x10'1 0 prod. 1 1.30x10'5 5.48x10'5
79 73 7.56x10'l 3.11x10'1 prod. 2 5.68x10'2 1.36x10'2
79 74 0 2.44 prod. 3 1.02x10'l 2.29x10'2
79 75 8.16x10'l 7.06 prod. 4 6.36x10'2 1.09x10'2
79 76 4.86x10'l 6.64 prod. 5 5.33x10'2 1.12x10'l
79 77 2.26 1.64 prod. 6 1.67xlo'2 7.42x10'2
80 46 1.70x10'3 4.25x10’3 prod. 7 2.25x10'l 1.17x10'l
80 47 1.69x10'l 6.65x10'2 prod. 8 1.72x10'l 8.54x10'2
80 49 1.35x10'l 2.62x10'2 prod. 9 6.42x10'4 5.82x10'3
80 50 1.29x10'I 3.27x10'l prod. 10 6.43x10'6 9.42x10'3

190

Appendix 3.2 (con't)

 

 

Pre Post Pre Post

Pred Prey Exchange Exchange Pred Prey Exchange Exchange
prod. 11 6.42x10'6 5.81x10’4 prod. 43 9.11x10'l 2.65x10'l
prod. 12 1.46x10'3 3.94x10'2 prod. 44 2.76x10'l 2.13x10'l
prod. 13 6.43x10'4 5.81x10'4 prod. 45 NP. 9.08x10l
prod. 14 6.42x10'6 5.81x10'4 prod. 46 1.80x10'2 5.71x10'2
prod. 15 4.44x10'3 3.48x10'l prod. 47 2.07 1.33

prod. 16 2.47x10'1 4.23x10'2 prod. 48 4.10x10'l 4.52x10'l
prod. 17 1.27x10'2 2.22x10'3 prod. 49 1.45 3.55x10'l
prod. 18 NP. 2.19x10'5 prod. 50 2.45 5.04

prod. 19 3.40x10'2 2.56x10'2 prod. 51 4.87x10'2 8.98x10'3
prod. 20 4.27x10'3 1.29x10'4 prod. 52 2.45 2.4

prod. 21 8.96x10'3 4.66x10'3 prod. 53 7.69 5.29

prod. 22 NP. 2.18x10'6 prod. 54 4.09x10'l 4.52x10'l
prod. 23 2.55x10'3 1.13x10'2 prod. 55 4.38x10'3 4.04x10'2
prod. 24 6.72x10'2 7.61x10'2 prod. 56 NP. 3.11x10'3
prod. 25 4.28x10'6 5.14x10'5 prod. 57 6.11x10'2 8.37x10’2
prod. 26 NR 1.25x10'3 prod. 58 3.24x10'1 2.28x10'l
prod. 27 4.28x10'5 6.92x10'5 prod. 59 4.17x10'2 3.08x10'2
prod. 28 8.39x10'3 1.25x10'3 prod. 60 8.50x10'3 1.35x10'2
prod. 29 7.37x10'3 1.25x10'3 prod. 61 3.31x10'l 5.64x10"l
prod. 30 NP. 1.29x10'3 prod. 62 1.82x10'l 9.10x10'2
prod. 31 3.33x10'3 1.58x10'3 prod. 63 2.81 1.53

prod. 32 6.99x10'3 1.28x10'2 prod. 64 3.12x10'2 8.87x10'2
prod. 33 1.30x10'2 2.43x10'3 prod. 65 2.74x10'2 1.17x10'2
prod. 34 4.28x1o'3 1.67x10'4 prod. 66 1.91x10'l 5.37x10'2
prod. 35 2.84x10'2 1.74x10'2 prod. 67 1.57x10'4 7.74x10'4
prod. 36 3.46x10’l 7.11x10'l prod. 68 2.01x10'l 2.12x10'l
prod. 37 2.32 1.25 prod. 69 2.74x10'l 2.31x10'1
prod. 38 5.73x10'2 6.65x10'2 prod. 70 1.21x102 4.65x10l
prod. 39 3.22x10'3 6.49x10’4 prod. 71 2.38x102 2.74x102
prod. 40 6.26x10'l 6.78x10'l prod. 72 1.14x10l 2.89x10l
prod. 41 1.50x10'l 2.41x10'l prod. 73 4.53 4.31

prod. 42 3.40x10'l 3.96x10'2 prod. 74 7.32 1.41x10l

191

Appendix 3.2 (con't)

 

 

Pre Post Pre Post

Pred Prey Exchange Exchange Pred Prey Exchange Exchange
prod. 75 4.24 3.62x10l Cons. 27 4.59x10'5 5.24x10'4
prod. 76 2.91 3.34x10l Cons. 28 5.36x10'2 1.73x10'3
prod. 77 3.5 2.24 Cons. 29 2.68x10'2 6.10x10'3
prod. 78 2.71 4.01x10l Cons. 30 NP. 3.69x10'3
prod. 79 1.77 7.07x10'l Cons. 31 1.41x10'2 9.59x10'3
prod. 80 1.79x10'2 2.94x10l Cons. 32 1.58x10'2 3.72x10'2
Cons. 1 1.86x10'2 7.87x10'2 Cons. 33 2.29x10'2 7.67x1o'3
Cons. 2 1.26 3.74810'1 Cons. 34 5.51x10'3 1.42x10'3
Cons. 3 7.39x10'l 1.65x10'1 Cons. 35 2.27x10'l 2.12x10"
Cons. 4 2.11x10'l 4.27x10'2 Cons. 36 6.95x10'l 1.28

Cons. 5 2.92x10"l 8.97x10'l Cons. 37 3.03 1.65

Cons. 6 5.80x10'2 1.94x10'l Cons. 38 2.33x10'l 2.49x10'l
Cons. 7 5.19x10’l 5.90x10'l Cons. 39 5.62x10'3 4.26x10'3
Cons. 8 2.59x10'l 2.42x10"I Cons. 40 1.79 2.34

Cons. 9 2.21x10'3 1.19x10'2 Cons. 41 1.85x10'l 4.31x10'l
Cons. 10 2.04x10'5 6.58x10'2 Cons. 42 7.23x10'l 7.59x10‘2
Cons. 11 8.87x10'6 7.39x10'4 Cons. 43 1.08 4.59xlo'l
Cons. 12 1.12x10'2 2.86x10'l Cons. 44 3.29x10'l 3.22x10'l
Cons. 13 8.55x10’4 1.48x10'3 Cons. 45 NP. 3.79x102
Cons. 14 2.63x10'5 1.18x10'3 Cons. 46 1.86x10'2 5.92x10'2
Cons. 15 6.49x10'3 7.30x10'I Cons. 47 2.16 1.4

Cons. 16 6.65x10'l 1.65x10'l Cons. 48 4.25x10'l 4.66x10'l
Cons. 17 9.81x10'2 2.16x10'2 Cons. 49 1.51 3.68x10'l
Cons. 18 NP. 4.25x10'5 Cons. 50 4.51 9.05

Cons. 19 3.15x10'l 2.50x10'l Cons. 51 9.08x10"2 1.67x10'2
Cons. 20 7.19x10'3 1.89x10'3 Cons. 52 4.89 4.75

Cons. 21 1.65x10'l 8.06x10'2 Cons. 53 7.91 5.44

Cons. 22 NP. 4.10x10'6 Cons. 54 6.71x10'l 9.76x10'l
Cons. 23 3.10x10‘2 1.33x10'l Cons. 55 6.93x10'3 6.45x10'2
Cons. 24 1.93x10'l 2.11x10'l Cons. 56 NP. 5.63x10'3
Cons. 25 1.36x10'5 3.60x10'4 Cons. 57 1.05x10'l 1.46x10'l
Cons. 26 NP. 1.87x10'3 Cons. 58 4.63x10'l 3.30x10'l

192

Appendix 3.2 (con't)

 

 

Pre Post Pre Post

Pred Prey Exchange Exchange Pred Prey Exchange Exchange
Cons. 59 6.11x10'2 4.44x10'2 Resp. 19 2.37x10'l 1.98x10'l
Cons. 60 1.33x10'2 2.10x10'2 Resp. 20 2.26x10'4 1.59x10'3
Cons. 61 5.71x10'l 9.16x10'l Resp. 21 1.51x10'l 7.45x10'2
Cons. 62 2.55x10'l 1.45x10'l Resp. 22 NP. 1.92x10'6
Cons. 63 4.12 2.35 Resp. 23 2.75x10’2 1.18x10'l
Cons. 64 7.15x10'2 1.75x10'l Resp. 24 1.26x10'l 1.35x10'l
Cons. 65 4.87x10'2 2.00x10'2 Resp. 25 9.30x10'6 3.09x10'4
Cons. 66 2.68x10'l 1.15x10'l Resp. 26 NP. 6.20x10'4
Cons. 67 2.83x10'4 1.56x10'3 Resp. 27 3.13x10'6 4.55x10'4
Cons. 68 2.07x10'l 2.25x10'l Resp. 28 4.52x10'2 4.72x10'4
Cons. 69 2.83x10'l 2.40x10'l Resp. 29 1.94x10'2 4.85x10'3
Cons. 78 2.19x102 9.79x10l Resp. 30 NP. 2.40x10'3
Cons. 79 9.07x10l 1.02x102 Resp. 31 1.08x10'2 8.01x10'3
Cons. 80 7.36x10l 6.15 Resp. 32 8.76x10'3 2.44x10'2
Resp. 1 1.85x10'2 7.81x10'2 Resp. 33 9.88x10'3 5.24x10'3
Resp. 2 1.14 2.41x10'l Resp. 34 1.23x10'3 1.25x10'3
Resp. 3 6.07x10'l 1.32x10'l Resp. 35 1.97x10'l 1.93x10'l
Resp. 4 1.47x10'l 3.18x10'2 Resp. 36 3.50x10'l 5.64x10’l
Resp. 5 2.21x10'l 7.41x10'l Resp. 37 7.11x10'l 4.00x10'l
Resp. 6 3.84x10'2 1.20x10'l Resp. 38 1.76x10'l 1.82x10'l
Resp. 7 2.89x10'1 4.71x10’l Resp. 39 2.41x10'3 3.61x10'3
Resp. 8 8.75x10'2 1.57x10'l Resp. 40 1.16 1.66

Resp. 9 8.86x10'4 3.80x10'3 Resp. 41 3.53x10'2 1.90x10'l
Resp. 10 7.90x10'6 4.14x10'2 Resp. 42 3.83x10'l 3.63x10'2
Resp. 11 o 5.25x10'5 Resp. 43 1.70x10'l 1.94x10'l
Resp. 12 5.50x10'3 1.81x10'l Resp. 44 5.36x10'2 1.09x10'l
Resp. 13 2.85x10'5 6.1sx10'4 Resp. 45 NP. 2.88x102
Resp. 14 1.12x10'5 3.76x10“1 Resp. 46 6.32x10'4 2.03x10'3
Resp. 15 2.05x10'3 3.82x10'l Resp. 47 8.93x10'2 7.09x10'2
Resp. 16 4.14x10'l 1.20x10'l Resp. 48 1.56x10'2 1.41x10‘2
Resp. 17 8.53x10‘2 1.69x10’2 Resp. 49 5.48x10'2 1.35x10'2
Resp. 18 NP. 2.07x10'5 Resp. 50 2.06 4.02

193

Appendix 3.2 (con't)

 

Pre Post

Pred Prey Exchange Exchange
Resp. 51 4.21x10'2 7.70x10'3
Resp. 52 2.44 2.35

Resp. 53 2.21x10'l 1.55x10’l
Resp. 54 2.62x10'l 5.24x10'l
Resp. 55 2.55x10'3 2.41x10'2
Resp. 56 NP. 2.52x10’3
Resp. 57 4.39x10'2 6.28x10'2
Resp. 58 1.39x10'l 1.01x10'l
Resp. 59 1.94x10'2 1.36x10'2
Resp. 60 4.80x10'3 7.41x10'3
Resp. 61 2.40x10'l 3.52x10'l
Resp. 62 7.36x10'2 5.39x10'2
Resp. 63 1.31 8.18x10"
Resp. 64 4.03x10'2 8.60x10'2
Resp. 65 2.13x10'2 8.36x10'3
Resp. 66 7.70x10'2 6.14x10'2
Resp. 67 1.26x10'4 7.81x10'4
Resp. 68 5.87x10'3 1.32x10'2
Resp. 69 8.32x10'3 8.31x10'3
Resp. 70 5.60x10l 2.00x10l
Resp. 71 1.05x102 9.05x10l
Resp. 72 1.11x10l 6.96

Resp. 73 2.53 1.97

Resp. 74 8.85 5.18

Resp. 75 1.79 1.20x10l
Resp. 76 1.49 1.14x10l
Resp. 77 1.92 8.69x10'l
Resp. 78 2.12x102 3.91x10l
Resp. 79 4.65x10l 1.58x10l
Resp. 80 7.30x10l 3.34

Imp. 70 1.77x102 6.65x10l
imp. 71 3.43x102 3.65x102

 

Pre Post
Pred Prey Exchange Exchange
Imp. 72 2.25x101 3.59x10l
Imp. 73 7.06 6.28
imp. 74 1.62x10l 1.93x10I
Imp. 75 6.03 4.82x10l
Imp. 76 4.4 4.48x10l
Imp. 77 5.42 3.11
imp. 78 2.48x102 2.49x102
imp. 79 3.86x10l 3.03x10l
Imp. 80 7.08x10l 7.21x10l
Exp. 1 1.19x10'4 5.02x10'4
Exp. 2 6.13x10'2 1.19x10'l
Exp. 3 2.97xio'2 9.99x10'3
Exp. 5 1.80x10'2 4.44x10'2
Exp. 6 2.96x10'3 0
Exp. 7 5.23x10'3 1.62xio'3
Exp. 9 6.84x10-4 2.23x10.3
Exp. 10 6.10x10'6 1.49x10'2
Exp. 11 2.12x10'6 1.05x10'4
Exp. 12 4.25x10'3 6.52x10'2
Exp. 13 1.84x10’4 2.80x10'4
Exp. 14 8.65x10'6 2.21x10'4
Exp. 16 3.75x10'3 3.00x10'3
Exp. 17 0 2.43x10'3
Exp. 19 4.39x10'2 2.60x10'2
Exp. 20 2.70x10'3 1.73x10'4
Exp. 21 4.68x10'3 1.44x10'3
Exp. 23 9.89x10'4 3.96xio'3
Exp. 35 1.36x10'3 1.40x10'3
Exp. 78 2.53x102 2.68x102
Exp. 79 8.11x10l 1.16x102
Exp. 80 7.13x10l 4.55x10l

194

Appendix 3.3

Exploration of odds ratios from signiﬁcance testing

195

In our cohesion analysis of the Bay of Quinte food web networks, we identiﬁed
six borderline signiﬁcant subgroups pre-zebra mussel invasion (p = 0.07; odds ratio =
12.7) and eight non-signiﬁcant subgroups post-invasion (p = 0.5; odds ratio = 14.6).
Generally, larger odds ratios correspond to greater statistical signiﬁcance (i.e., smaller p-
values), and therefore, we were initially surprised that the post-invasion subgroups were
non-signiﬁcant. To explore this result, we ﬁrst plotted a histogram of the odds ratios
generated during Signiﬁcance testing for the pre- (Panel A) and post-invasion (Panel B)
networks to assess normality of the results (Table A3.1). Both distributions were slightly
left-skewed; however, for the purposes of this analysis, the distributions were acceptable.

Next, we examined the ﬂow topography. Flow was asymmetrically distributed
after invasion, with zebra mussels garnering over 15% of the total system ﬂow.
Additionally, the greatest weights on ﬂows were between zebra mussels and their prey
(Appendix 3.2), which centralizes (or focuses) the network. Frank (1995) generates a
predicted value of odds ratios from simulation data Showing that highly centralized
networks can yield large odds ratios. Frank demonstrates the process using networks
with unweighted data, where particular actors engage in a large number of interactions;
actors with many interactions (in an unweighted network) are analogous to actors
engaging in interactions with large weights (in a weighted network). As such, the post-
invasion Bay of Quinte network is highly centralized due to the dominance of zebra
mussels. Because of this, high odds ratios can be sustained even in the absence of
subgroups merely by locating zebra mussels and all their prey in a single subgroup.

Therefore, we conclude that the concentration of exchanges within subgroups for the

196

post-invasion network was not signiﬁcantly different from what would be found by

chance alone because of the extremely high centrality of the zebra mussels.

197

Table A3.1. Distribution of odds ratios pre- (Panel A) and post-zebra mussel invasion

(Panel B) used in Signiﬁcance testing.

 

Panel A 160
140 -

120 7

100

80

1

Count

60

l

1

4O

20

l

 

 

 

 

 

 

 

 

0 2 4 6 8 10 12 14 16
Odds Ratios

 

Panel B 160
140

l

120

l

100

80

Count

60

40

20

 

 

 

 

 

 

 

 

 

2 4 6 8 10 12 14 16 18 20 22
OddsRatios

198

References

Frank, K. A. 1995. Identifying cohesive subgroups. Soc. Networks. 17: 27-56.

199