LOCAL P E RCEPTIONS OF ENVIRONMENTAL IN SECURITY AND WILDLIFE CONSERVATION IN THE MNISI TRIBAL AUTHORITY, MPUMALANGA, SOUTH AFRICA By Parker Daniel Banas A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Fisheries and Wildlife Master of Science 2020 ABSTRACT LOCAL PERCEPTIONS OF ENVIRONMENTAL IN SECURITY AND WILDLIFE CONSERVATION IN THE MNISI TRIBAL AUTHORITY, MPUMALANGA, SOUTH AFRICA By Parker Daniel Banas Environmental in security is a relatively new expression within the broader space of security . Many contributors to local and global insecurity are also threats to environmental security which represent the interconnectedness and complexity of environmental insecurity. Local perceptions from local areas such as the Mnisi Tribal Authority (MTA) are often useful to decision - makers working to reduce harm from environmental insecurity. In order to understand the local perceptions of the MTA, I set three objectives for this research: i ) explore local perceptions of environmental insecurity and its perceived relationships with o ther forms of insecurity; ii ) compare and contrast local perceptions of risk associated with environmental and other forms of insecurity; iii ) e xplore relationships between factors influencing and being influenced by environmental insecurity. D ata were col lected with face to face interviews (N = 21 1 ) with residents of the Mnisi Tribal Authority in Mpumalanga, South Africa, in 2019. V ariables including village location, age, children in the household, land ownership status, and gender had a significant influ ence on in securities including environmental, food, and water . A mong study residents , environmental in security is influenced and affected by a range of variables . L ocal perceptions from the MTA and other local areas are crucial to understanding this relationship. Interpreting and analyzing the perceived risks at all levels can be a key to designing policies that aid in insecurity reduction at local, regional, and global levels . iii This thesis is dedicated to my Mother and Father along with the amazing people and wildlife in Mnisi Tribal Authority and South Africa. iv ACKNOWLEDGEMENTS Special thanks to Dr. Meredith Gore for giving me the opportunity to study within her lab and work and learn with her . W ithout this amazing opportunity, none of this would have been possible. I want to thank the Southern African Wildlife College including Prof. Alan Gardiner, Professor Mtungwa, Sboniso Ryan P hakathi, Ashwell Glasson, and all others who supported me, for allowing me to live and work at their beautiful campus during the summer of 2019 to conduct my research. Thank you to the Mnisi Tribal Authority for allowing me access to their breathtaking com munity and for the delightful hospitality that was shown to me at all times. Thank you to Dr. Jennifer Hodbod and Dr. Robert Montgomery for their consistent committee support. Thank you to the College of Agriculture and Natural Resources at Michigan State University for the funding provided during summer 2019 . Lastly, I want to acknowledge the constant love and support of my Mom and Dad, Melissa, and all of my close friends and family throughout this process. Special shout out to the Wednesday basketball cr ew , my graduate MSU IM Sports championship soccer and basketball teams, and my FW friends who helped me keep my sanity throughout the process. v TABLE OF CONTENTS LIST OF TABLES v ii KEY TO ABBREVIATIONS CHAPTER 1: ENVIRONMENTAL INSECURITY INTRODUCTION AND OVERVIEW WITHIN THE MNISI TRIBAL AUTHORITY, MPUMALANGA, SOUTH AFRICA . 1 1.1. INTRODUCTION .2 1.1.1. Security in the Anthropocene 1.2. CASE STUDY OVERVIEW 4 1.2.1. Research Design ..4 1.2.2. Mnisi Tribal Authority 5 1.2.3. Collaboration Partners ..7 1.2.4. Mnisi Tribal Authority questions about environmental insecurity 1.2.5. Thesis Structure ..8 1.3 MATERIALS AND METHODS 1.3.1. Community entry into Mnisi Tribal Authority lands 1.3.2. Ethics statement . 1 0 1.3.3. Questionnaire instrument 0 1.3.4. Sampling protocol 1 1.3.5. Technology and data storage .. 1 5 1.3.6. Index creation (latent variable creation) 5 1.3.7. Data analysis 6 CHAPTER 2: CONCEPTUALIZING ENVIRONMENTAL INSECURITY WITHIN A BROADER THREAT LANDSCAPE: INSIGHTS FROM THE MNISI TRIBAL AUTHOIRTY RESIDENTS 1 8 2.1 RESULTS 19 2.1.1. Demographics 19 2.1.2. Question 1: public perceptions of environmental 2 0 2.1.3. Question 2: deforestation in the MTA 2.1.4. Question 3: traditional crime and environmental crime 2.1.5. Question 4: public perceptions of natural phenomena risk . 25 2.1.6. Question 5: insight into environmental insecurity solutions 2.1.7. Question 6: poaching perceptions . 3 0 2.2 DISCUSSION 2.2.1. solutions 7 2.2.2. Natural phenomena (e.g., drought) 38 2.2.3. Poaching and traditional crime 40 2.2.4. Implications for education and other interventions . 4 3 2.2.5. Questions for f uture research 6 2.2.6. Study limitations .47 vi CHAPTER 3: LOCAL PERCEPTIONS ON THE CAUSES AND CONSEQUENCES OF ENVIRONMENTAL INSECURITY 3.1. I NTRODUCTION ...50 3.2. BACKGROUND 51 3.2.1. Objectives overview .52 3.3. DIFFERENT CONCEPTUALIZATION OF SECURITY .. 5 3 3.3.1. Environmental security . 5 3 3.3.2. Food security 4 3.3.3. Water security . 5 5 3.3.4. Crime security 6 3.3.5. Trust 7 3.3.6. Nature Myths .58 3. 4 . R ESULTS .59 3.4.1. Explore local perceptions of environmental insecurity, including perceived relationships with other forms of insecurity 3.4.2. Compare and contrast l ocal perceptions of risk associated with environmental and other forms of insecurity .. 6 0 3.4.3. Explore relationships between factors, including non - security factors and demographics, influencing and being influenced by environmental insec urity 3. 5 . DISCUSSION 3.5.1. O verview 70 3.5.2. Gender disparity: lack thereof 71 3.5.3. Gender , food insecurity, water insecurity, and deforestation ..72 3.5.4. Trust 75 3.5.5. Nature myths 76 3.5.6. Littering 78 3.5.7. Poaching ..79 3. 6. CONCLUSION ...81 A R EFERENCES 106 vii LIST OF TABLES Table 1: Sampling protocol list of villages within the in the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019) including population from the 2011 census (most recent available data), area size (km 2 3 Table 2: This study explored local perceptions (N = 211) of perception of risk associated with different types of cr ime in the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Ten villages comprised the study sample, with approximate equal parity (2% of the village population/km 2 Table 3: Means and standa Tribal Authority, Mpumalanga, South Africa (May July 2019). Means and standard deviations Tabl e 4: Ten threats to environmental security within the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Tsonga translation may be shortened for ease of reading. Mean and standard deviation presented for the 211 residents. Likert - type Scal e ranged from 1 - 10 with 1 . 22 Table 5: Local perceptions (N = 211) about the threat perception of deforestation in the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Included are Mean Squares (MS), Variance Components (VC), F tests (F), LRT (likelihood ratio test value) and respective p - values for threats of harms and environmental harms within the MTA community. Significant p - values 23 Table 6: Perceptions of effect and frequency of deforestation in the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Included are mean, standard deviation, and median for deforestation risk perceptions with in the MTA community. Likert - type scale was from 1 - 7 with 1 being lowest risk perception or frequency perception. 24 Table 7: Pearson correlation and statistical significance of traditional crimes and the environmental index within the Mni si Tribal Authority, Mpumalanga, South Africa and the surrounding area (May July 2019). Included are assault, burglary, drugs, murder, rape, and sexual assault 25 Table 8: Residents perceived risk and perceived worry a bout situations directly related to drought within the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Calculated mean, standard deviation, and median are included for each village within the questionnaire. A 7 - point Likert - type scale w . 2 7 Table 9: Pearson Correlations of seven insecurity indexes within the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Statistical significance is denoted with asterisks. 2 8 viii Table 10: Residents perceptions on trust within the Mnisi Tribal Authority, Mpumalanga, South Africa and the surrounding area (May July 2019). Inc luded are the mean, standard deviation, and median. A 7 - point Likert - type scale was used with 1 being completely disagree and 7 being completely agree with the statement 29 Table 11: Residents perceptions on trust by village withi n the Mnisi Tribal Authority, Mpumalanga, South Africa and the surrounding area (May July 2019). Included are the mean, .29 Table 12: Residents perceptions of frequency of individual animals being poached. The table is broken down by villages in the Mnisi Tribal Authority, Mpumalanga, South Africa (May - July . 3 2 Table 1 3 : Local perceptions (N = 211) measuring the perception of frequency of in dividual animals poached in and around the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Included are Mean Squares (MS), Variance Components (VC), F - tests (F), LRT (likelihood ratio test value) and respective p - values for perception o f individual poached animals within the Mnisi Tribal Authority. Significant p - 3 4 Table 1 4 : Pearson Correlations of five insecurity indexes related to environmental insecurity within the Mnisi Tribal Authority, Mpumala nga, South Africa (May July 2019). Statistical significance is denoted with asterisks. One asterisk for statistical significance at the 0.05 level and 59 Table 1 5 : Local percept ions (N = 211) about environmental factors in the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Included are Mean Squares (MS), Variance Components (VC), F tests (F), LRT (likelihood ratio test value) and respective p - values for threa ts of harms and environmental harms within the MTA community. Significant p - values are denoted ........................................................60 Table 1 6 : Perce ived risk ranking of ten threats to environmental security according to residents (N = 211) in the Mnisi Tribal Authority, Mpumalanga, South Africa (May ..61 Table 1 7 : Pearson Correlations of seven insecurity indexes within the Mnisi Tri bal Authority, Mpumalanga, South Africa (May July 2019). Statistical significance is denoted with asterisks. ....63 Table 18 : Residents perceptions on trust wi thin the Mnisi Tribal Authority, Mpumalanga, South Africa and the surrounding area (May July 2019). Included are the mean, standard deviation, and median. A 7 - point Likert - type scale was used .64 Table 19 : Residents perceptions o n trust by village within the Mnisi Tribal Authority, Mpumalanga, South Africa and the surrounding area (May July 2019). Included are the mean, 6 6 ix Table 2 0 : Local perceptions (N = 211) measuring the perception of frequency of individual animals poached in and around the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Included are Mean Squares (MS), Variance Components (VC), F - tests (F), LRT (likelihood ratio test value) and respective p - values for perception of individual poached animals within the Mnisi Tribal Authority. Significant p - 6 8 Table 2 1 the Mnisi Tribal Authority, Mpumalanga, South Africa (May - ..9 8 x KEY TO ABBREVIATIONS Greater Limpopo Transfrontier Conservation Area (GLTFCA) Kruger National Park (KNP) Likelihood Ratio Test (LRT) Mean Squares (MS) Mnisi Tribal Authority (MTA) Research Assistant (RA) Southern African Wildlife College (SAWC) Sustainable Development Goals (SDGs) Variance Component (VC) 1 CHAPTER 1 : ENVIRONMENTAL IN SECURITY INTRODUCTION AND OVERVIEW WITHIN THE MNISI TRIBAL AUTHORITY, MPUMALANGA, SOUTH AFRICA 2 1.1 INTRODUCTION 1.1.1. Security in the Anthropocene Security is a concept that has endured substantial change over the past 50 years, although it has remained central to geopolitics, foreign relations, interstate and intercommunity decision - making, and local governance (Miller, 2001; Detraz, 2009 ; Ellio t t, 2015). Experts rarely define security consistently, nor is it consistently perceived by demographic groups organized according to gender, wealth, status, age, ethnicity, or location (Brauch, 2015; Spring, 2009). The global ubiquity and local variation of t he security concept makes it both a highly important and complex issue for sustainable development (Spring, 2009; Hardt, 2012). I define security as the state of being free from constraints of danger, threat, harm or risk (Detraz, 2009; Hardt, 2012; Elliot t, 2015; Busby, 2018). Security may manifest in various forms and has developed from the traditional sense of national security focused on defenses against either domestic or international threats, to a global understanding that encompasses everything from having enough food to feed your family to being able to have the health resources provided to you by your local and national government when in need (Elliott, 2015; Mohammadpour et al., 2019). Traditional security is conceptualized as safety from crime, i ndependence from threat with the ability to feel safe, and the perception that one is secure in their surroundings (Boholm et al., 2016). In the past, security was said to be event driven (e.g., a car being stolen) (Miller, 2001; Romero, 2014 ). National se curity, the ability of nations to protect their borders from physical and other harms inflicted by others, emerged as a priority after 9/11/2001 (Spring et al. 2009). As the world has globalized through connected economies and online communities, the conce pt of security has broadened in scope (Ezeonu & Ezeonu, 2000; Miller, 2001; Hough, 201 8 ). Environmental security considers risks posed by and to the environment which threaten survival 3 of local populations (Gore et al., 2016; Busby, 2018; Meissner et al., have enough food, water, natural resources or shelter, it creates insecure situations that can directly or indirectly amplify other harms (Spring, 2009; Spring et al., 2009; Gore et al., 2016; Busby, 2018). Some environmental probl ems such as global climate change are slow - onset risks. The combined with the political dynamic in a region (Goodman, 2012). Clean water scarcity coupled wit h declines in marine biodiversity, for example, can stress growing human populations, often in places that are already facing weak governance systems (Rice & Garcia, 2011; Goodman, 2012). Implicitly, environmental security involves connections to national security because preventing threats to the environment providing security prevents threats to national security (Farbotko, 2018). For example, in 2009, the U.S. Navy formed The Task Force on Climate Change in response to changing climate conditions. Follow ing that, in 2010, the U.S. Department of Defense formally recognized climate change as a factor to consider when planning for national security risks (La Shier & Stanish, 2017). It is important for decision - makers to understand how environmental change au gments other risky conditions and how environmental impacts interact with other harms and threats in a particular location (Carter, 2018). Decision makers are pressed to plan appropriately to ensure security in diverse threat landscapes (Hezri & Hasan, 200 201 1 ). The notion of security is important for politics and foreign relations because it associates the label with prioritized spending and action and enables a commonality of purpose among diverse actors (Goodman, 2012). Nations invest heavily in defense spending in pursuit of national security; thus, there are many experts that offer a technical assessment of security risks, prevention mechanisms and probabilities. Environmental problems have been securitized leading to the 4 human dimensions of environmental change being more directly incorporated into science and policy decisions (Bennett et al., 2017; Christie et al., 2017). Human dimensions promote thinking - consideration of gender, vulnerability, risk perception and human geography (Decker et al., 2012; Bennett et al., 2017). Although there is now fairly broad agreement that security is important at a local level and a geopolitical level, there appears to be scant research quantifying and qualifying local perspectives on the topic, particularly regarding the environment (Spring et al. , 201 1 ; K ah ler & Gore, 2015; Gore et al. , 2016). Thus, efforts to plan, implement, and test programs and policies designed to enhance security for vulnerable people and places lack key information upon which to build evidence. To these ends, my thesis aims to build knowledge about local hereof, other forms of insecurity and potential factors such as age, gender, and living location. Three objectives of my thesis were to: i ) explore local perceptions of environmental insecurity, including perceived relationships with other forms of insecurity , ii ) compare and contrast local perceptions of risk associated with environmental and other forms of insecurity, and iii ) e xplore relationships between factors, including non - security factors and demographics, influencing and being influenced by environmental insecurity. 1.2 C ASE STUDY OVERVIEW 1.2.1 . Research Design I conducted research using a case study design. I chose the case study design because it can narrow down a broad field, is useful when researching an issue in an area that has not been research extensively, while also bringing an understanding to a complex theory looking at the 5 relationships between variables (Harrison et al., 2017; Yin, 2018 ). Case study design also applies to social science when looking at real - life situations and trying to expand the basis of research for future researchers (Yin, 20 18 ). However, g eneralizing the findings to a broader population can be difficult especially if certain findings only relate to the questioned population, small population samples can lead to missing data making interpretation of data difficult, constant expo sure to the interpret cause - and - effect relationships (Anastas, 1999; Gerring, 2004; Mills et al., 2010; Stake, 2010 ; Yin, 2018 ). I implemented a case study design because the three research objectives were broad, looked at relationships between variables, and looked to narrow down a broad range of research questions for future researchers. 1.2.2 . Mnisi Tribal Authority Within my thesis, I focus on the Mnis i Tribal Authority (MTA) residents and their perceptions and thoughts of environmental insecurity and various items potentially related to environmental insecurity. The MTA is in Bushbuckridge, Mpumalanga, South Africa near the Great Limpopo Transfrontier Conservation Area ( Berrian et al., 2016; Khunoana et al., 2019). The GLTFCA is a united conservation area across three international boundaries, South Africa, Zimbabwe, and Mozambique (Ntuli et al., 2019). Conservationists created the park in 2002 after be ing conceived in 1990 ( Chiutsi & Saarinen, 2017; Sundström et al., 2019) . The Great Limpopo ). The GLTFCA also contains private and state - owned conservation areas in South Africa and Zimbabwe (Gore et al., 2020 ; Peace Parks Foundation, 20 20 ). The GLTFCA has several goals 6 listed in the International Treaty (Gore et al., 2020). These include encouraging relations with different stakeholders and working to build up ecotourism in the area (Gore et al., 2020). Animals and plant life are copious in the GLTFCA, and in South Afri Park, which borders MTA lands ( Peace Parks Foundation, 2020 ). Anti - poaching remains a priority for the GLTFCA ( Sundström et al., 2019; Gore et al., 2020 ) . Theoretically , wildlife has the opportunity to be a great benefit to MTA residen ts (Snyman, 2017; Gumede & Nzama; 2019). Economies based on wildlife are associated with ecotourism and sustainable use provide benefits for communities when the community is involved and able to partake in the formation of the economies (Gumede & Nzama; 2 019; Litheko & Potgieter, 2020). Benefits may include, for example, economic, physical, or ecological impacts ( Spenceley & Goodwin, 2007; Sandbrook, 2010; Snyman, 2014 ). In addition, charismatic mega - fauna, along with other wildlife, has a potentially vit al role to play in attracting visitors for ecotourism in areas experiencing high rates of environmental insecurity , such as the MTA (Lindsey et al., 2007; Bhatt & Dhakal, 201 8 ). However, a range of risks are also associated with wildlife ( Ravenelle & Nyhus, 2017). Ecotourism also has risk associated with it. COVID - 19 has shown that ecotourism failing because of unforeseen circumstances can negatively impact local communities who rely on the income of international tourists as well as largel y negatively effecting conservation and anti - poaching efforts funded by tourism (De Bellaigue, 2020). In this region, livestock necessity is tied to the close proximity to wildlife areas (Berrian et al., 2016) . The cohabitation of humans, domestic animals, and wildlife is important for members of the MTA and is reflected in how conservation programs do in the region (Berrian et al., 2016). Over 50,000 people live in MTA lands , many of which use the environment for livelihoods and 7 sustenance (Lehohla, 2012; Berrian et al., 2016). The combination of variables can lead to many insecurities overlapping in the MTA. Environmental, water, and crime insecurity were a large priority of the MTA Board while all types of insecurity influenced the overall three research objectives. 1.2.3 . Collaboration P artners The MTA has a lengthy history of collaboration with the Southern African Wildlife College. The Southern African Wildlife College and the Mnisi Tribal Authority leaders invited Michigan State University to take part in the collaboration and help build understanding about local perceptions of environmental in security and its connection to other types of insecurity in the region. Security is an important issue in the areas bordering MTA lands. The villages comprising t he MTA are full of biodiversity. The interaction between conditions may affect insecurity. For example, firewood is a main energy source for many households (Findl a y & Twine, 20 1 8) . Firewood use is often a monetary savings strategy due to a lack of alternative livelihood options in the MTA (Findlay & Twine , 20 1 8) . Firewood strongly links to insecurity in the MTA because the main source of firewood is illegal deforestation. Deforestation has a much broader impact than just l osing wooded areas in the MTA as appraisals have found deforestation contributes to soil erosion, biodiversity loss, and degraded drinking water quality ( Uhunamure et al., 2016 ) . The Board of the MTA was interested in learning more about the environmental and other insecurities within their area and created priority questions to be addressed by the research . 1.2.4. Mnisi Tribal Authority Q uestions A bout E nvironmental I n security MTA leaders prioritized several questions and ideas relevant to environmental security in the region. 8 1) What is known about public perceptions of unique types of conservation/ environmental crimes within the MTA, including illegal littering, and poaching? 2) How is village crime associated with deforestation and other envir onmental crimes? 3) How can deforestation in the MTA be reduced and are there alternatives? 4) What is known about public perceptions of different types of natural phenomena such as drought within the MTA? 5) What kinds of solutions do you think you might sugges t (asking researcher) for the MTA given what you know about the situation and the data you collected from the MTA? 6) What does the data show that can help potentially reduce poaching in and around the MTA ? 1.2.5. Thesis Structure Residents of the MTA agreed on the 6 questions presented above without conjunction of the 3 research objectives presented earlier - I informed the MTA what my overall research interests were, and they created the 6 questions they thought would apply to the ir own needs. Their six questions did not inform my three objectives however, the three objectives helped influence the six questions and data used to analyze the MTA priority questions overlapped with the three thesis rch projects were pursued because the research team wanted - a key observation of the MTA was that many they derive the data. Therefore, this thesis builds on the same dataset but is formatted as two different products: Chapter 2 explores the six questions from the MTA and is formatted as a report for the MTA and SAWC as the primary audience . Chapter 3 is framed around the three research objectives and is written for a broad academic audience , with the content to be translated into a 9 peer - reviewed article after the thesis is approved. However, ther e is some repetition of data that appl ies to both the MT three research objectives. 1.3 MATERIALS AND METHODS 1.3.1. Community E ntry into Mnisi Tribal Authority L ands I collaborated with the Southern African Wildlife College (SAWC) and the Mnisi Tribal Authority (MTA) in Mpumalanga, South Africa for this research. I ascertained approval for community entry within the MTA once I met with the representatives of the MTA. T he MTA liaison working at the SAWC introduced me to the MTA Board of Directors, where they granted approval to conduct research with the surrounding villages. The MTA liaison leveraged pre - existing relationships with and helped hire the research assistants (RAs) through a college preparatory program at the SAWC. The MTA liaison and I conducted field work along with the RAs, creating a team of eight, of whom three RAs were male and five were female . I led a weeklong training session at the SAWC for the RAs a nd MTA liaison . Training included an overview and deep dive into the research and objectives, how to conduct proper structured interviews including a full read through of the questionnaire in English and Tsonga, KOBO Toolbox, responsible conduct in researc h, and the importance of following protocol to lower any forms of bias in the field. Data collection protocols started a pilot test. I asked RAs to perform test questionnaires with family and friends to make sure they felt comfortable with the instrument and then went through the questions myself with the RAs. Pilot testing also involved one day of field - based data collection. I supported consistency in data collection through daily meetings each morning to s may have come across in the field previously . I reviewed the survey data from the day before too, to discuss with the team and minimize mistakes 10 and inconsistencies. For example, RAs had different interpretations of the questions and we worked through th e entire questionnaire as a team to make sure every person agreed . I met with all interested MTA representatives (board members and stakeholders) prior to my departure back to Michigan State University, once data collection was completed and preliminary an alysis was conducted. A final meeting took place where I presented an overview of the data analysis, including results associated with the three thesis objectives and the six priority MTA questions. 1.3.2. Ethics S tatement Michigan State Review Board reviewed and determined the study (STUDY00002577) to be exempt under 45 CFR 46.104(d) 2(ii). At the start of all interviews, I required residents to consent verbally to take part in the questionnaire before any data collection started and to also consent prior to entering any personal property or homes . I provided written consent instructions in English and Tsonga for participant review. The introductory statement can be found in the Appendix along with copies of the questionnaire in English and Tsonga. recorded all residents as a numeric so no personal information and answers would link to their identity. 1.3.3. Questi onnaire I nstrument I planned the questionnaire for this study using KOBO Toolbox ( Kobo Toolbox, 2020 ). KOBO is a free, cloud - based system for researchers and humanitarians to collect fieldwork data. The questionnaire contained 149 questions. I organized a ll questions into different section s and each section had a brief explanatory introduction. The sections, in order as presented in the questionnaire were, Warm - up/introductions, Mnisi Tribal Authority, Harm Thoughts, Harm Response 1, Harm Response 2, Natur e Mythology, Food Security, Health Security, Water Security, 11 Environmental Security, Education and Employment, Trust, Traditional Crime Perspective, Activities, and Conclusion (Demographics) . I answer the six primary MTA questions using answers primarily from Harm Thoughts, Water Security, Environmental Security, Traditional Crime Perspective, and Activities while all sections were used to answer the three research objectives. Ten of the 149 questions were sociodemographic questions. Demographic variables included gender, village, age, occupation, employment status, years lived in the area, ethnicity, ownership of land, size of land in km 2 , and how many children were present in their household. All other questions were Likert - type scale questions. Likert - type questions were in either 7 - point or 10 - point scales to increase reliability of the questionnaire (Croasmun & Ostrom, 2011) . Seven - point Likert - type scales were used in the majority of the questions to allow for a neutral position while t en - poin t Likert - type scales were used to measure the risk that residents associated with environmental threats in the section titled Harm Thought s because even - numbered Likert - type scales force a resident to choose a position without the option for neutrality ( Br own, 200 0 ; Croasmun & Ostrom, 2011) . The SAWC provided a translator to translate the KOBO questionnaire from English to Tsonga and then from Tsonga to English to avoid any confusion in the field from RAs having to self - translate the questionnaire. All qu estionnaires were administered in Tsonga in the field with English being used for clarification if needed. RAs and the MTA liaison provided feedback on the questionnaire in both languages to make sure that RAs were not translating in the field differently than other RAs. Both versions can be found in the A ppendix ( p. 94 ) . 1.3.4. Sampling Protocol The MTA comprises 15 villages. I selected ten villages sampled in this study based on recommendations from and permissions granted by the MTA Board ( e.g. , traditional authority). 12 Village selection , recommended by the MTA, included a representation of different geographic proximities to the protected areas surrounding the MTA and population sizes of villages to encompass a wide variety of participation and opinions to create the most viable and accurate sample size possible (Moore et al., 2010) . Modified systematic quota sampling was used to achieve research objectives (Singleton et al. , 2005 ). This sampling is simple and direct. I based my modifications (quota sampling combined with systematic sampling) on a lack of available lists of residents in the population of the chosen villages and a desire to fill a male/female quota in our sample population (Singleton et al. , 2005). My goal was to d esign a sampling frame that reflected the target population, but I was also cognizant that this can be an unrealistic goal in conservation social science (Singleton et al. , 2005) . It was impractical for me to create an accurate list of the entire MTA popul ation . Thus, I recognize the sampling design represents the specific, known population with defined characteristics (see population description table). A key advantage of our sampling design was decreased bias by researchers in selection of cases which is an important mechanism of scientific control (Trochim, 2020) . I first calculated the population density of each village cluster by dividing the 2011 census p opulation (most recent population data obtainable) by the area size in km 2 (Frith, 2011 ; Lehohla, 2012 ; Statistics South Africa, 2020 ) (Table 1). I then calculated 2% of the population density for each village to derive a village quota to create a reasonab le sample size for the time I was able to spend in the country (Singleton et al., 2005). I divided each quota into a male and female ratio. Based on 2011 census data, females outnumbered males by 54% to 46%. When the calculated quota was an even number, I set our target sample as being half male and half female. Where the calculated quota was an odd number, I alternated between male and female to receive an extra 13 interview, according to the alphabetical order of the villages. The c alculated margin of error for this questionnaire was about 5.65%. Table 1: Sampling protocol list of villages within the in the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019) including population from the 2011 census (most recent available data), area size (km 2 ), population density, and quotas. Village Name Population Size (2011) Area Size (km 2 ) Population Density (people/km 2 ) 2% of population Male Quota Female Quota Clare A & B 2,772 2.49 1,113.25 22 11 11 Gottenburg 400 0.6 666.67 13 7 6 Hlavekisa 2,563 2.38 1076.89 22 11 11 Hluvukani 9,631 7.67 1255.67 25 12 13 Islington 4,560 5.82 783.51 16 8 8 Ludlow 5,766 7.06 816.71 16 8 8 Manyeleti 2,260 1.96 1153.06 23 12 11 Tintswalo Village 8,836 7.21 1224.99 25 1 3 12 Welverdiend 7,601 6.12 1241.99 25 13 12 Whitecity / Burlington 4,154 4.16 998.56 20 10 10 Total 39,707 4 5.47 873.26 207 10 4 10 3 After calculating the male/female quota sample size for each village, I used a random number generator to determine the order in which I would interview each village: Islington, Clare A & B, Welverdiend, Manyeleti, White City/ Burlington, Tintswalo Village , Gottenburg, Hlavekisa, Hluvukani, and Ludlow. The data collection team worked through this ordered list of villages daily and moved to the next village on the list when sampling concluded in a single village. Two villages were not interviewed on the same day except for extenuating circumstances (Singleton et al. , 2005 ). Within each village, I used systematic sampling to interview every K th person based on randomized start times of day ( e.g. , I used a random number generator to determine the start time of our interviewing between the hours of 0800 - 1200). Systematic sampli ng is when there is a 14 specified sampling interval (K) and also a random start (random time generator) chosen from the MTA population ( Burger & Silima, 20 06 ) . I chose ten as the sampling interval (K) based on Singleton et al. (2005) and randomized the initi al case with which I started on each research day. I instructed all RAs to only intercept residents on the street. I selected the Kth door ( i.e. , residence) when this was not possible and when no potential candidates were on the streets. If the Kth intervi ew was asked to be interviewed and denied the option, the next person of the correct gender bias including social desirability bias, I asked residents to take part in the questionnaire alone with only the RAs in the room (Grimm, 2010) . Social desirability bias happens when a participant in a study answers a question based on what they think others would deem socially acceptable (Grimm, 2010) . Each of th e eight RAs followed the same randomized start time, initial case, and sampling interval. Not all RAs were in the field each day because of personal and work conflicts. I randomly assigned half of the RAs present each day to interview males and half to int erview females . The and team leaders at SAWC were asked if they thought not aligning gender with candidates would lead to bias. They decided that less bias would happen from random sampling compared to gender paired sampling. If an odd number of RAs w ere taking part in the interviews for the day, I alternated between male and female having one extra interviewer. All RA teams started at different drop off locations within the village limits. The end location for all RAs was the village administrative of fice in each specific village. I remained in electronic messaging contact with RAs during participant interviews and halted research when village quotas were met. I was present in the field on all days of res earch . I kept RAs in pairs for safety protocol, meaning that both assistants were present in the room or on the street while we co nducted the questionnaire. 15 1.3.5 . Technology and Data Storage To achieve research objectives, I used the KOBO Toolbox Data Collection software application run on Android devices in the field with GPS coordination enabled. If needed, RAs used their persona l Android devices as a backup in case the original device failed or ran out of battery. The SAWC provided the primary collection instruments for the duration of the study. I backed up all data at the conclusion of each questionnaire day. I cleared all devi ces the SAWC owned clean of the data at the conclusion of the research. Each questionnaire including locating a resident, introductions, and conducting the full questionnaire took approximately 30 minutes to 1 hour to complete. 1.3.6. Index C reation ( L atent V ariable C reation ) I used an identical procedure for creating all summative indexes ( e.g. , latent variables ) (Saris & Gallhofer, 2014) . I chose summative indexes because I gave no additional weight to any question within an index ( Dillman et al., 2009; Triezenberg et al., 2014) . I assessed each in security concept using multiple items designed to form summative scales (Table 17 ) for each index and its component questions (Dillman et al., 2009; Triezenberg et al., 2014). I calculated alpha in SPSS to assess the internal consistency between the set of questions used to create each index ( Croasmun & Ostrom, 2011) . alpha looks at internal consistency between item responses to see if they have a correlation with each other while also looking at variance within a set of questions (Vaske, 2008 ; Croasmun & Ostrom, 2011 ). A minimum value of 0.60 is valid for internal consistency within indexes created with greater than 10 questions and as low as 0.50 for indexes created wi th less than 10 questions (Vaske, 2008 ; Nunnally & Bernstein , 2010 ; Pallant, 20 16 ) (see Appendix for indexes, variables, and a lpha rankings). 16 1.3.7. Data A nalysis Though several debates around which statistical tests provide the most accurate inferences for ordinal, Likert - type scales data, I chose parametric tests because they are robust against violations of statistical assumptions, as normality of the residuals, without being overly conservative (Norman, 2010) . In addition, researchers have found that parametric ( t - test) and non - parametric methods (Mann - Whitney test) produce very similar type I and type II error rates (Winter et al., 2010 ) . Lastly, ordinal data with 5 or more values within a question can be used as continuous data with no added harm to a statistical model (Johnson & Creech, 1983; Zumbo & Zimmerman, 1993; Norman, 2010; Sullivan & Artino, 2013). Based on that, I performed all analy z es using parametric approaches, specifically a Linear Mixed Model. I chose this model specifically due to the hierarchical structure (nesting) of my data, allowing me to take the different effect of the 10 villages into account (Fox, 2015; UCLA: Statistical Consulting Group, 2020). The analysis of each question/index was performed using the following Linear Mixed Model: where is the vector of responses; is a vector fixed effects associated to the age (continuous variables), ethnicity and - sex, land ownership status (owns the land or not), and employment status (employed or unemployed) of the res ident s; is the vector of the ran dom effect of townships (villages), with ; and is the vector of residuals, with . X and Z are the design matrices that associate fixed and random effects to the response variable. LRT and F - Tests were used to verify if the pred ictors have a significant impact on the response variable(s). Later, I checked the homoscedasticity and the normality of the residuals, and, if necessary, I normalized the data using the Box - Cox transformation of the data 17 and re - ran the model (Box & Cox, 1 964; Gurka et al., 2006; Osborne, 2010 ) . The model described above was fitted using the lme4 - R package (Bates et al., 2015). I also wanted to investigate whether certain aspects of in security are related to environmental risk. Simple linear regressions we re used to evaluate this as well as predictor variables impact on a particular questions outcome if further analysis was needed (Pak & Oh, 2010). These analyses were performed using SPSS v.26 (IBM Corp, 2019). 18 CHAPTER 2: CONCEPTUALIZING ENVIRONMENTAL IN SECURITY WITHIN A BROADER THREAT LANDSCAPE: INSIGHTS FROM THE MNISI TRIBAL AUTHORITY RESIDENTS 19 2.1 RESULTS The MTA Board collectively identified six priority questions. The questions were based off of the overall broad scope of the three research objectives and are discussed below broken down by each question. The goal of this chapter is for the results to be used by the MTA and their members for educ ational interventions. 2 . 1 .1. Demographics A total of 213 interviews from the ten different villages were completed more than the planned 207 (Table 1) because exact timing communication lacked in the field and a few extra interviews were conducted . I reduced the 213 interviews down to a total of 211 interviews (female n = 105, male n = 106) due to the fact that two resident s did not complete enough of the interview and/or stopped in the middle of the interview due to having to attend to pe rsonal matters. Sampling quotas for each village were still achieved (Table 2). Residents self - reported their employment status (no = 128, 60.7 0 %, yes = 83, 39.3 0 %). The majority of residents identified as Tsonga (n = 186, 88 . 1 0 %), however other ethnic groups were represented in the final sample including Pedi (n = 6, 2.8 0 %) Sotho (n = 16, 7.6 0 %), Swati (n = 1, 0 .5 0 %), Xhosa (n = 1, 0 .5 0 %), and Zulu (n = 1, 0 .5%). The majority of residents (n = 114, 54.3 0 %) did not own land. Table 2: This study explored local perceptions (N = 211) of perception of risk associated with different types of crime in the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Ten villages comprised the s tudy sample, with approximate equal parity (2% of the village population/km 2 ) between villages. Village Frequency of Interviews Percent of Interviews Clare A and B 22 10.4 Gottenburg 22 10.4 Hlavekisa 22 10.4 Hluvukani 25 11.8 Islington 18 8.5 Ludlow 16 7.6 Manyeleti 16 7.6 Tintswalo Village 25 11.8 20 Welverdiend 25 11.8 City/Burlington 20 9.5 Total 211 100 2 . 1 . 2 . Question 1: P ublic P erceptions of E nvironmental C rime first question focused on public perceptions of different types of environmental crime. Residents 3 ). Three villages ( i.e. , Got t enburg, Islington, and Welverdiend) consistently had an increased risk perception when compared to all villages. Two villages ( i.e. , White City/Burlington and Tintswalo Village) tended to have decreased risk perception compared to all villages. Averages of risk perception including all 10 environmental crimes ranged from 4.7 4 to 5.98 with an average risk perception rating of 5.49 measured on a 10 - point Likert - type scale . 21 Authority, Mpumalanga, South Africa (May July 2019). Means and standard deviations were calculated for all environmental threats presented to the residents. Village Cattle Theft Defores - tation Devel - opment Drought Erosion Littering on Land Littering in Water Mosquito/ Disease Over - grazing Poaching Clare A and B Mean 5.36 7.77 3.05 6.68 4.46 7.64 5.67 5.64 5.00 6.96 SD 3.43 2.78 2.34 3.30 2.96 2.72 3.44 2.54 3.65 2.65 Gottenburg Mean 5.86 8.36 4.00 7.27 5.24 6.59 5.55 5.32 5.00 6.46 SD 3.50 2.59 2.58 2.73 2.97 3.22 4.00 3.14 2.70 3.57 Hlavekisa Mean 3.64 7.30 1.27 6.55 5.41 6.68 4.59 4.90 6.68 3.23 SD 2.75 2.90 0.88 2.26 2.20 2.51 2.79 3.70 2.19 2.31 Hluvukani Mean 5.36 6.72 4.04 5.92 5.21 5.92 4.17 4.12 5.08 4.72 SD 3.03 2.75 2.42 2.68 2.48 2.40 2.33 2.52 2.94 2.61 Islington Mean 8.00 8.11 4.06 7.06 3.72 6.56 6.00 6.28 3.94 5.78 SD 2.77 2.42 3.39 3.05 3.08 4.05 3.07 3.32 3.13 3.10 Ludlow Mean 7.88 7.56 3.81 5.69 5.44 7.56 5.63 4.31 5.81 2.94 SD 3.16 2.94 2.56 3.09 3.18 2.53 3.72 3.20 3.35 2.38 Manyeleti Mean 4.94 7.69 2.06 6.40 4.00 5.44 3.63 4.56 4.19 4.50 SD 2.84 2.60 1.57 2.61 1.41 2.94 2.42 2.71 2.90 2.07 Tintswalo Village Mean 3.96 6.24 4.48 4.96 6.40 8.28 6.08 6.32 4.64 5.28 SD 2.89 3.11 2.47 3.03 3.73 2.44 3.14 3.08 3.19 3.31 Welverdien d Mean 5.20 8.52 5.20 7.44 4.29 8.24 4.88 4.76 6.16 5.12 SD 3.37 2.49 2.90 3.42 3.16 2.49 3.21 2.73 3.28 3.26 White City Mean 5.35 7.25 2.15 5.15 5.37 4.95 4.25 4.60 4.72 5.75 SD 3.69 3.11 1.42 2.87 2.34 3.12 3.70 3.39 3.29 3.39 Total Mean 5.43 7.53 3.49 6.32 5.00 6.85 5.06 5.10 5.17 5.13 SD 3.36 2.82 2.61 2.99 2.90 2.99 3.24 3.06 3.12 3.11 22 (VC = 1.1 1 , LRT = 6.8 3 , p < 0. 05), littering on land (VC = 0.87, LRT = 9.1 5 , p < 0.05 ), littering in water (VC = 0. 60 , LRT = 3.9 5 , p < 0.05 ), poaching (VC = 1.2 3 , LRT = 10.69, p < 0.05 ), and stock theft (VC = 0.3 8 , LRT = 6.94, p < 0.05 ). Age predicted risk perce ptions associated with cattle theft (MS = 116.49, F = 12.10, p < 0.05 ), deforestation (MS = 106.03, F = 14.44, p < 0.001 ), littering on land (MS = 73.83, F = 10.01, p < 0.05 ), and littering in water (MS = 154.07, F = 18.10, p < 0.05 ). Gender predicted perc eptions of cattle theft (MS = 42.72, F = 4.44, p < 0.05 ). Also, noteworthy land ownership significantly affected perceptions on land littering (MS = 44.46, F = 6.03, p < 0.05 ) with landowners having a smaller risk perception than non - landowners (B = - 1.20, SE = 0 .49, p < 0.05 ). 2 . 1 . 3 . Question 2 : D eforestation in the MTA second priority question was how deforestation on MTA lands could be more effectively addressed . Importantly, deforestation is illegal on MTA lands. Among the total sample, deforestation was rated as the highest of ten threat activities presented (M = 7.53, median = 9.00) (Table 4 ). Table 4: Ten threats to environmental security within the Mnisi Tr ibal Authority, Mpumalanga, South Africa (May July 2019). Tsonga translation may be shortened for ease of reading. Mean and standard deviation presented for the 211 residents. Likert - type Scale ranged from 1 - 10 with 1 being lowest perception of threat and 10 being the most. Environmental Risk Tsonga Translation Mean (SD) Range 1 - 10 Deforestation Ku tsemeleriwa ka nhova/Minsinya. 7.5 3 (2.8 2 ) Littering on L and Ku lahliwa ka thyaka laha swinga fanelangiki 6.85 (2.9 9 ) Drought Dyandza 6.3 2 (2.9 9 ) Cattle Theft Ku yiviwa ka tihomu 5.43 (3.3 6 ) Overgrazing Ku rimiwa ka ndhamu leyi tlulaka mpimo 5.1 7 (3.12) Poaching Ki hlotiwa ka swiharhi swingari enawini 5.1 3 (3.11) 23 Table 4 Mosquito/Disease Vuvabyi bya Malaria lebyi kumekaka ka tinsuna 5.10 (3.0 6 ) Littering in W ater Ku thyakisiwa ka mati 5.0 6 (3.24) Erosion Ku khukuriwa ka misava hi mpfula. 5.00 (2.90) Development Nhluvuko 3.4 9 (2.6 1 ) As outlined above, the Linear Mixed Model shows, among sociodemographic effects measured, the only significant variable that predicted risk perception associated with deforestation was age (MS = 106.03, F=14.44, p < 0.05 ) (Table 5). Exploring that in more detail, individuals under 35 years of age perceived the least threat from deforestation (M = 6.97) while individuals over 55 years reported the highest perceived risk of deforestation (M=8.68). For every ten years a residents age increased, average answers increased by 0 .72 points (B = 0 .07, SE = 0 .0 2 ). Table 5: Local perceptions (N = 211) about the threat perception of deforestation in the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Included are Mean Squares (MS), Variance Components (VC), F tests (F), LRT (likelihood ratio test value) and respective p - values for threats of harms and environmental harms within the MTA community. Significant p - values are denoted with * symbol. Deforestation Fixed Effects MS F P Age 106.03 14.45 0.00* Children in House 0.28 0.04 0.84 Gender 2.95 0.40 0.53 Employed 17.68 2.41 0.12 Owns land 16.43 2.24 0.14 Ethnicity 0.55 0.08 0.78 Random effects VC LRT P Village 0.22 1.10 0.30 Residual 7.34 The questionnaire also asked about f requency of activities within the MTA , including deforestation . Analysis exhibited that MTA residents village location had significance on perceived frequency of deforestation (VC = 0.196, LRT = 5.358, p < 0.05 ) , dichotomous when compared to risk perception from the threat of deforestation ( as shown in table 5: VC = 0.22, LRT 24 = 1.096, p > 0 .05). This is cr itical to note when implementing deforestation - related education in certain villages. A mean of 5.80 and a median of 7.00 was reported for perceived frequency of deforestation across villages (Table 6 ). Based on a simple linear regression, r esidents agreed that deforestation had a negative effect on their community , causing harm to the environment and local communities . Deforestation negatively effecting communities positively affected environmental in security risk perception (B = 0 . 53 , SE = 0 .0 3 p < 0.0001 ). Table 6 : Perceptions of effect and frequency of deforestation in the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Included are mean, standard deviation, and median for defor estation risk perceptions within the MTA community. Likert - type scale was from 1 - 7 with 1 being lowest risk perception or frequency perception. Deforestation H arms the E nvironment Deforestation has N egative I mpact on C ommunity Perceived F requency of De forestation Mean 5.83 4.81 5.80 1.80 2.2 3 1.6 8 Median 7.00 6.00 7.00 Lastly, deforestation influenced perception s of food in security. Residents who had an elevated risk perception of deforestation a lso had an elevated risk perception of food insecurity. Perception of d etrimental effects of deforestation to the environment had a positive effect on risk perception associated with food insecurity (B = 0 .18, SE = 0 .0 6 , p < 0.05 ) . 2 . 1 . 4. Question 3 : T raditional C rime and E nvironmental C rime third priority question focused on traditional crime in villages and the association with environmental crimes. Traditional crime perceptions measured included assault, d a significant effect on perceptions of assault (VC = 0 .38, LRT = 7.8 7 , p < 0.05 ), burglary (VC = 0 .30, LRT = 7.0 4 , p < 0.05 ), drug crimes (VC = 0 .36, LRT = 6.30, p < 0.05 ), and murder (VC = 0 .56, LRT = 8.7 3 , p < 0.05 ) i.e., all crimes other than rape a nd sexual assault . Across all villages, 25 residents perceived traditional crimes as concern s . Residents rated burglary (M = 5.75, SD = 1.71 median = 6.00) as the largest concern among traditional crimes followed by assault (M = 5.46, SD = 1.89, median = 6.00), drug crimes (M = 5.23, SD = 2.01, median = 6.00), sexual assault (M = 5.06, SD = 2.03, median = 6.00), rape (M = 4.98, SD = 2.09, median = 6.00), and murder (M = 4.98, SD = 2.30, median = 6.00). The mean response for all traditional crimes was 5.24 with a constant median of 6.00. Residents were l ess concerned about non - traditional crimes (M = 4.86) than traditional crimes . However, o ut of all crime concerns measured , defores tation ranked most concerning to residents (M = 5.80, median = 7.00). Other non - traditional crimes including cattle theft (M = 3.66, median = 3.00) and littering in water sources (M = 4.08, median = 4.00) were perceived to be less of a concern while crimes such as stock theft (M = 5.26, median = 6.00) and land littering (M = 5.50, median = 6.00) were perceived at about the same mean ranking as traditional crimes across all residents . Perception of concern with assault, burglary, murder, rape, and sexual ass ault were all significantly (positively) correlated with the environmental index (Table 7), but drugs were not. Table 7 : Pearson correlation and statistical significance of traditional crimes and the environmental index within the Mnisi Tribal Authority, M pumalanga, South Africa and the surrounding area (May July 2019). Included are assault, burglary, drugs, murder, rape, and sexual assault. Crime Assault Burglary Drugs Murder Rape Sexual Assault Correlation Coefficient .2 4 . 40 . 20 .2 4 .3 9 .2 7 Sig. (2 - tailed) .00 * .00 * . 03* .00 * .00 * .00 * 2 . 1 .5. Question 4 : P ublic P erceptions of N atural P henomena R is k phenomena such as drought. R esidents reported relatively high perceptions of risk associated with drought , with most agreeing to strongly agreeing that drought was a concern . Perceptions were 26 collected regarding drought harm (M = 6.55, median = 7.00), drought threat (M = 6.32, median = 6.00), ability to recover from drought (M =6.00 , median = 7.00), water for community crops (M = 5.40, median = 6.00), to water for per sonal crops (M = 5.27, median = 6.00) (Table 8). The age of residents significantly affected perceptions of worry convening recovery from drought (MS = 19.74, F = 9.61, p < 0.05 ). Starting at age 18, every year a resident s age increased , their risk perception increased by 0 .03 points related to drought recovery worry (B = 0 .03, SE = 0 .01, p < 0.05 ). Worrying about lack of water for community crops (MS = 51.13, F = 14.45, p < 0.05 ) was affected by age . Residents risk perception increase by 0 .05 points for every year older (B = 0 .05, SE = 0 .55, p < 0.05 ). Age significantly affected risk perceptions related to water for personal crops (MS = 79.80, F = 21.17, p < 0.05 ) with every year a resident was older increasing their risk perception by 0 . 06 points (B = 0 .06, SE = 0 .01, p < 0.05 ). One point is one full step up or down on the Likert - type scale (i.e., 1 to 2) . Also noteworthy was employment status, land ownership, and gender, all having significant effect on residents answers about drought risk perception . Employed residents had a decrease in risk perception by 0 .75 points compared to unemployed residents , landowners risk perception decreased by 0 .59 points while males had significantly lower risk perceptions with a decreased average risk perception of 0 .85 points. Gender also played a significant role in risk perception when looking at risk perceptions related to worry ing about lack of water for community crops . M ales once again ha d a decreased risk perception when compared t o females (B = - 0 .92, SE = 0 .27, p < 0 .001). 27 Tabl e 8: Residents perceived risk and perceived worry about situations directly related to drought within the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Calculated mean, standard deviation, and median are included for each village within the questio nnaire. A 7 - point Likert - type scale was used . Village Drought H arms the E nvironment Worry A bout L ack of W ater for P ersonal C rops Worry A bout L ack of W ater for C ommunity C rops Worry A bout D rought R ecovery Clare A and B Mean 6.4 1 5.36 5.3 2 5.3 2 0.59 1.9 7 1.7 3 1.70 Median 6.00 6.50 6.00 6.00 Gottenburg Mean 6.68 5.7 3 5.5 5 6.5 5 1.1 3 1.83 1.9 5 0.91 Median 7.00 7.00 6.00 7.00 Hlavekisa Mean 6.3 2 5.50 5.7 3 5.9 6 1.39 2.52 2.31 1.5 3 Median 7.00 7.00 7.00 6.50 Hluvukani Mean 6.80 5.28 5.64 6.40 0.50 2.35 2.0 4 0.8 7 Median 7.00 6.00 7.00 7.00 Islington Mean 6.94 5.82 5.7 8 6.1 7 0.2 4 1.9 8 1.7 7 1.82 Median 7.00 7.00 7.00 7.00 Ludlow Mean 6.06 5.9 4 5.6 9 6.1 9 1.91 2.0 2 2.44 1.5 2 Median 7.00 7.00 7.00 7.00 Manyeleti Mean 6.1 9 6.00 6.2 7 6.1 9 1.5 2 1.3 1 1.03 0.83 Median 7.00 7.00 7.00 6.00 Tintswalo Village Mean 6.84 4.16 4.56 5.80 0.37 2.0 8 2.18 1.7 1 Median 7.00 5.00 5.00 6.00 Welverdiend Mean 6.84 5.32 5.28 5.96 0.47 1.84 1.9 3 1.2 1 Median 7.00 6.00 6.00 6.00 White City/Burlington Mean 6.10 4.15 4.65 5.50 1.1 7 2.43 2.13 1.96 Median 7.00 4.50 5.00 6.00 Total Mean 6.55 5.2 7 5.40 6.00 1.0 4 2.1 3 2.0 2 1.4 7 Median 7.00 6.00 6.00 7.00 28 on their perceptions of risk associated with food in security (B = 0 .30, SE = 0 .06, p < 0.0001 ) as well as their worry about having a reliable source of water for n on - drinking purposes (B = 0 .3 8 , SE = 0 .0 6 , p < 0.0001 ). Residents reported that worrying about having enough water for their personal crops (B = 0 .3 6 , SE = 0 .05, p < 0.0001 ) and their communities having enough water for their crops (B = 0 .29, SE = 0 .0 6 , p < 0.0001 ) both had a positive effect on perceptions of food in security. Lastly, worrying about recovering from drought had a positive effect on food in security risk perception (B = 0 .30, SE = 0 .08, p < 0.0001 ). 2 . 1 .6. Question 5 : I nsight i nto E nvironmental I nsecurity S olutions The fifth priority question posed by the MTA focused on translating insight from the data collected into potential educational and intervention solutions for betterment of MTA residents. With regards to trust , I asked re sidents their thoughts on trust and related subjects within their community and surrounding areas. The trust index was positively correlated with the environmental index ( r (211) = 0 . 15 , p < 0.05 ), with trust also being positively correlated with education and employment as well as negatively correlated with poaching (Table 9). Table 9 : Pearson Correlations of seven in security indexes within the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Statistical significance is denoted with asterisks. One asterisk for statistical significance at the 0.05 level and two for the 0.01 level. Crime Education and Employment Environmental Food Poach - ing Trust Water Crime 1 0.07 0.38 ** 0.19 ** 0.20 ** 0.10 0 . 20 ** Education and Employment 0.07 1 0.00 - 0.09 0.03 0.24 ** 0.07 Environmental 0.38 ** 0.00 1 0.48 ** 0.15 * 0.15 ** 0.59 ** Food 0.19 ** - 0.09 0.48 ** 1 0.01 0.12 0.47 ** Poaching 0 . 20 ** 0.03 0.15* 0.01 1 - 0.15 * 0.08 Trust 0.10 0.24 ** 0.15 ** 0.12 - .015 * 1 0.10 Water 0.20 ** 0.07 0.59 ** 0.47 ** 0.08 0.10 1 29 Trust, and concepts related to trust, such as corruption and integrity were associated with very high - risk perception rankings throughout the MTA. Residents ranked worrying about corruption (M = 5.92, = 1.73, median = 7.00) as the largest singular trust issue while also showing a large distrust in local government (M = 2.97, = 2.13, median = 2.00) and national government (M = 3.64, = 2.314, median = 3.00). Residents ranked trust in rangers in the surrounding protected areas and game reserves (M = 4.97, = 2.00, median = 5.00) significantly higher (Table 10). Table 10: Residents perceptions on trust within the Mnisi Tribal Authority, Mpumalanga, South Africa and the surrounding area (May July 2019). Included are the mean, standard deviation, and median. A 7 - point Likert - type scale was used with 1 being completely disagree and 7 being completely agree with the statement. Factors Corruption Worry Local Govt. Trust Local Police Integrity Nat. Govt. Trust Ranger Trust Trust (general) Trust Index Mean 5.9 2 2.9 7 3.15 3.64 4.9 7 4.49 4.1 9 1.73 2.1 3 2.12 2.31 1.99 2.3 7 1.2 2 Median 7.00 2.00 3.00 3.00 5.00 5.00 4.00 Worry about corruption had a positive effect on environmental in security risk perception (B = 0 . 30 , SE = 0 .0 4 , p < 0 .0001). Lastly, trust varied by village (Table 11). Table 11: Residents perceptions on trust by village within the Mnisi Tribal Authority, Mpumalanga, South Africa and the surrounding area (May July 2019). Included are the mean, standard deviation, and median for all villages measured. Village Corrupt . Worry Local Govt. Trust Local Police Integrity Nat. Govt. Trust Ranger Trust Trust Trust Index Clare A and B Mean 6.2 3 2.4 1 3.18 2.68 5.3 2 5.00 4.1 4 1.19 1.7 1 2.06 2.0 1 1.70 1.95 1.2 4 Median 7.00 2.00 2.50 2.00 5.50 5.50 4.08 Gottenburg Mean 5.36 3.09 3.0 5 3.36 4.86 4.9 1 4.1 1 2.38 1.95 1.9 9 1.9 9 1.8 9 2.2 5 1.1 5 Median 7.00 3.00 3.00 3.00 5.00 5.50 4.00 Hlavekisa Mean 5.2 3 3.00 3.9 6 4.59 5.7 3 4.77 4.5 5 2.2 5 2.4 9 2.6 3 2.59 1.88 2.56 1.32 Median 7.00 2.00 4.00 5.50 7.00 7.00 4.75 Hluvukani Mean 6.32 3.00 2.80 3.40 4.52 4.84 4.1 5 1.2 2 2.02 2.12 2.5 2 2.2 4 2.34 1.1 9 30 Median 7.00 2.00 2.00 2.00 5.00 6.00 4.1 7 Islington Mean 6.33 3.11 3.22 3.2 8 4.3 9 4.6 7 4.1 7 1.1 4 2.6 8 2.6 7 2.63 2.40 2.8 1 1.69 Median 7.00 1.50 1.50 2.00 4.00 6.50 3.1 7 Ludlow Mean 6.3 8 3.6 9 3.6 3 4.1 9 5.31 3.1 3 4.3 9 0.9 6 2.0 6 2.06 2.2 3 2.02 2.09 1.1 5 Median 7.00 3.50 3.50 4.50 6.50 3.00 4.50 Manyeleti Mean 5.75 3.06 2.6 9 3.75 5.25 4.9 4 4.24 1.61 2.46 1.8 9 2.62 1.48 2.4 9 1.39 Median 6.00 2.00 2.00 3.00 5.00 6.50 3.9 2 Tintswalo Village Mean 6.16 2.32 3.28 3.68 4.84 4.72 4.1 7 1.21 1.70 1.86 2.1 2 1.84 2.01 1.10 Median 7.00 2.00 3.00 4.00 5.00 5.00 4.33 Welverdiend Mean 6.24 3.20 2.72 3.68 5.16 4.16 4.19 1.69 2.2 4 2.09 2.1 2 2.1 2 2.5 3 1.05 Median 7.00 3.00 2.00 4.00 6.00 4.00 4.00 White City/Burlingt on Mean 5.10 3.10 3.10 3.95 4.35 3.45 3.84 2.4 3 2.15 1.86 2.3 1 2.08 2.35 1.0 6 Median 6.50 3.00 3.00 4.00 4.00 2.50 3.6 7 Total Mean 5.9 2 2.9 7 3.15 3.64 4.9 7 4.49 4.1 9 1.73 2.1 3 2.12 2.31 1.99 2.3 7 1.2 2 Median 7.00 2.00 3.00 3.00 5.00 5.00 4.00 2 . 1 .7. Question 6 : P oaching P erceptions The final priority question posed by the MTA focused on perceptions of wildlife poaching in and around the MTA. Study residents reported perceptions on ten species known to inhabit MTA lands and the surrounding area . There was significant variation across individual villages (VC = 0 .1 3 , LRT = 8.2 1 , p < 0.05 ) on perception of frequency (Table 12) . Across all villages sampled, the top four species perceived to be poached were rhino ( Ceratotherium simum and Diceros bicornis ) (M = 4.10), impala ( Aepyceros melampus ) (M = 2.59), elephant ( Loxodonta africana ) (M = 2.11), and pangolin ( Manis temmenickii ) (M = 2.04) (Table 1 2 ). Across all villages sampled, the three species perceived to be poached least frequently were wild dog ( Ly caon pictus) (M = 1.64), leopard ( Panthera pardus ) (M = 1.73), and hyena ( Hyaena brunnea ) (M = 1.85). 31 Residents from Gottenburg (M = 2.98, SD = 1.85, median = 2.70), Tintswalo Village (M = 2.48, SD = 1.47, median = 1.90), and White City/Burlington (M = 2.48, SD = 1.47, median = 1.80) perceived poaching rates to be higher compared to other villages. Gottenburg and White City/Burlington had higher frequency perceptions than all o ther villages. Participants had lower perceptions of poaching frequency in Hlavekisa (M = 1.60, SD = 1.04, median = 1.20), Islington (M = 1.77, SD = 1.547, median = 1.00), and Clare A and B (M = 1.81, SD = 1.14, median = 1.40), ranking under the average of all villages (M = 2.17). Residents were asked about their perceived environmental harms associated with poaching. Residents age (MS = 8.030, F = 5.009, p < 0.05 ), children living in their household (MS = 8.263, F = 5.155, p < 0.05 ), and land ownership status (MS = 7.846, F = 5.155, p < 0.05 ) all had significant influence on their perceptions. Risk perception of the threat to their local community attributed to poaching was influenced by age (MS = 29.059, F = 10.661, p < 0.05 ), children living in their household (MS = 16.494, F = 6.051, p < 0.05 ), and ethnicity (MS = 17.218, F = 6.317, p < 0.05 ). 32 Table 12: Residents perceptions of frequency of individual animals being poached. The table is broken down by villages in the Mnisi Tribal Authority, Mpumalanga, South Africa (May - July 2019 ) Village Elephant Hyena Impala Leopard Lion Pangolin Python Rhino Vulture Wild Dog Total Clare A and B Mean 1.46 1.36 1.59 1.41 1.46 1.36 1.67 4.41 1.86 1.55 1.81 Std. Deviation 0.91 0.90 0.96 0.96 1.06 0.90 1.20 2.06 1.28 1.18 1.14 Median 1.00 1.00 1.00 1.00 1.00 1.00 1.00 5.00 1.00 1.00 1.40 Gottenburg Mean 2.82 2.36 3.59 2.36 2.27 3.27 2.91 5.14 2.91 2.18 2.98 Std. Deviation 1.89 1.62 2.36 1.59 1.72 1.96 1.88 2.05 1.93 1.53 1.85 Median 3.00 2.00 3.50 2.00 1.00 4.00 2.50 5.50 2.50 1.00 2.70 Hlavekisa Mean 1.91 1.14 1.96 1.48 1.29 1.41 1.55 3.10 1.05 1.14 1.60 Std. Deviation 1.38 0.66 1.65 1.08 0.90 1.05 1.06 1.73 0.22 0.66 1.04 Median 1.00 1.00 1.00 1.00 1.00 1.00 1.00 3.00 1.00 1.00 1.20 Hluvukani Mean 2.08 1.56 2.32 1.40 1.08 2.29 1.75 4.56 2.00 1.38 2.04 Std. Deviation 1.35 1.04 1.44 0.87 0.28 1.52 1.11 1.61 1.41 0.77 1.14 Median 1.00 1.00 2.00 1.00 1.00 1.50 1.00 5.00 1.00 1.00 1.55 Islington Mean 1.53 1.67 2.11 1.29 1.35 1.77 1.67 2.78 2.11 1.39 1.77 Std. Deviation 1.46 1.65 2.11 0.77 0.10 1.79 1.33 2.37 2.03 0.98 1.46 Median 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Ludlow Mean 2.31 2.13 2.50 1.94 1.94 2.06 2.13 3.00 1.81 1.81 2.16 Std. Deviation 1.54 1.50 1.71 1.44 1.44 1.39 1.41 1.51 1.33 1.33 1.46 Median 1.00 1.00 1.50 1.00 1.00 1.00 1.00 3.50 1.00 1.00 1.30 Manyeleti Mean 2.25 2.38 3.00 1.38 1.38 1.44 2.00 3.69 1.44 1.31 2.03 Std. Deviation 1.39 1.59 1.86 1.03 1.03 1.03 1.55 2.18 1.21 0.87 1.37 Median 2.00 1.50 3.00 1.00 1.00 1.00 1.00 4.00 1.00 1.00 1.65 33 Tintswalo Village Mean 2.72 2.08 3.40 2.16 2.16 2.35 2.17 4.56 2.38 2.21 2.62 Std. Deviation 2.05 1.41 1.98 1.43 1.46 1.43 1.81 2.38 1.61 1.41 1.70 Median 2.00 1.00 4.00 1.00 1.00 2.00 1.00 5.00 1.00 1.00 1.90 Welverdiend Mean 1.76 1.92 2.12 1.72 1.60 2.20 1.84 4.16 1.64 1.52 2.05 Std. Deviation 1.33 1.55 1.48 1.51 1.35 1.66 1.34 2.15 1.22 1.23 1.48 Median 1.00 1.00 2.00 1.00 1.00 1.00 1.00 5.00 1.00 1.00 1.50 White City/Burlington Mean 2.21 2.10 3.40 2.05 1.90 2.00 2.16 4.90 2.10 1.75 2.46 Std. Deviation 1.72 1.41 2.01 1.43 1.45 1.37 1.30 1.48 1.29 1.21 1.47 Median 1.00 1.00 3.50 1.00 1.00 1.00 2.00 5.00 1.50 1.00 1.80 Total Mean 2.11 1.85 2.59 1.73 1.65 2.04 1.98 4.11 1.95 1.64 2.17 Std. Deviation 1.57 1.38 1.87 1.28 1.27 1.53 1.45 2.09 1.48 1.18 1.51 Median 1.00 1.00 2.00 1.00 1.00 1.00 1.00 4.00 1.00 1.00 1.40 34 Older viewpoint s on poaching harming the environment increased by 0 . 2 0 points for every ten years (B = 0 .02, SE = 0 .0 1 , p < 0.05 ) and increased their perception of harm to their community by 0 .38 points for every ten years (B = 0 .0 4 , SE = 0 .01, p < 0.05 ). Having children in the household decreased their perception of harm to the environment due to poaching (B = - 0 .10, SE = 0 .0 5 , p < 0.05 ) and decreased their perception of harm to their location community (B = - 0 .1 5 , SE = 0 .06, p < 0.05 risk perception of poaching harm to the environment (B = - 0 .49, SE = 0 .22, p < 0.05 ), while identifying as Tsonga had the opposite effect, significantly increasing a res idents risk perception of harm to their community (B = 0 . 90 , SE = 0 .36, p <.05). P oaching was positively correlated with crime perceptions (Table 1 3 ). Table 1 3 : Local perceptions ( N = 211) measuring the perception of frequency of individual animals poached in and around the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Included are Mean Squares (MS), Variance Components (VC), F - tests (F), LRT (likelihood ratio test value) and respective p - values for perception of individual poac hed animals within the Mnisi Tribal Authority. Significant p - values denoted with *. Elephant Poaching Hyena Poaching Fixed Effects MS F P MS F P Age 4.05 1.80 0.18 0.41 0.24 0.62 Children in House 2.10 0.9 4 0.3 4 2.7 6 1.6 2 0.2 1 Gender 3.2 7 1.45 0.2 3 1.49 0.87 0.35 Employed 0.7 1 0.3 2 0.5 8 0.2 1 0.12 0.7 3 Owns L and 0.12 0.05 0.8 2 2.0 9 1.22 0.27 Ethnicity 1.5 1 0.67 0.41 0.00 0.00 0. 10 Random effects VC LRT P VC LRT P Village 0.1 4 2.9 7 0.0 9 * 0.12 3.6 1 0.0 6 * Residual 2.2 5 1.7 1 Impala Poaching Leopard Poaching Fixed Effects MS F P MS F P Age 0.03 0.01 0.92 1.1 8 0.77 0.38 Children in House 0.81 0.2 7 0.6 1 1.2 8 0.83 0.36 Gender 17.3 7 5.73 0.0 2 * 0.37 0.24 0.62 Employed 0.2 6 0.0 9 0.77 0.21 0.1 4 0.71 Owns L and 1.6 4 0.54 0.46 2.40 1.5 7 0.21 35 Ethnicity 1.1 4 0.3 8 0.54 0.59 0.3 9 0.5 4 Random effects VC LRT P VC LRT P Village 0.38 10.0 1 0.00 * 0.11 4.04 0.04 * Residual 3.0 3 1.53 Lion Poaching Pangolin Poaching Fixed Effects MS F P MS F P Age 1.86 1.2 9 0.2 6 0.0 1 0.00 0.95 Children in House 0.10 0.0 7 0.79 5.05 2.35 0.1 3 Gender 0.9 1 0.6 3 0.4 3 2.0 1 0.93 0.3 4 Employed 1.9 7 1.36 0.2 5 0.6 3 0.29 0.59 Owns L and 1.3 3 0.9 2 0.3 4 0.20 0.09 0.76 Ethnicity 1. 60 1.10 0. 30 0.00 0.00 0.96 Random effects VC LRT P VC LRT P Village 0.1 1 4.5 9 0.03 * 0.25 8.74 0.00 * Residual 1.4 5 2.15 Python Poaching Rhino Poaching Fixed Effects MS F P MS F P Age 0.01 0.0 1 0.94 0.8 5 0.21 0.6 5 Children in House 0.8 8 0.42 0.5 2 0.8 2 0.20 0.65 Gender 4.4 4 2.14 0.1 5 4.80 1.20 0.2 8 Employed 0.01 0.0 1 0.94 1.62 0.4 1 0.5 3 Owns L and 0.01 0.0 1 0.94 2.7 4 0.68 0.4 1 Ethnicity 0.5 4 0.26 0.61 0.00 0.00 0.9 9 Random effects VC LRT P VC LRT P Village 0.07 1.12 0.2 9 0.5 3 8.95 0.00 * Residual 2.0 7 4.00 Vulture Poaching Wild Dog Poachi ng Fixed Effects MS F P MS F P Age 0.4 5 0.2 2 0.64 0.01 0.0 1 0.92 Children in House 0.38 0.1 9 0.6 7 0.0 1 0.0 1 0.9 4 Gender 5.8 1 2.83 0.09 0.0 6 0.04 0.8 4 Employed 0.29 0.14 0.7 1 0.00 0.00 0.98 Owns L and 0.8 7 0.42 0.5 2 0.01 0.01 0.9 2 Ethnicity 0.4 8 0.23 0.63 0.01 0.0 1 0.93 Random effects VC LRT P VC LRT P Village 0.15 4.1 4 0.04 * 0.0 8 2.96 0.0 9 * Residual 2.05 1.3 6 36 37 38 39 40 41 42 43 44 45 46 47 2 . 2 .6. Study L imitations 48 As previously mentioned, previous research looking into local perceptions of risk perception focusing on environmental security is scant. This factor makes comparing this research to previous research without making some educated leaps difficult. Sample size could be a limiting factor in d ata analysis and the projection of results across other populations. However, a factor in choosing a L inear M ixed M odel analysis approach was the ability to generalize these findings to similar villages or groups of people . However, study design and sample size may be a limiting factor in generalizing results from this study to other populations similar to the MTA. 49 CHAPTER 3 : LOCAL PERCEPTIONS ON THE CAUSES AND CONSEQUENCES OF ENVIRONMENTAL I NSECURITY 50 3 .1 INTRODUCTION Climate change, increasing global population, and environmental variation such as the rapid drying of rivers and lakes, and depletion of aquifers, can all lead to increased socio - ecological stress causing environmental insecurity (Rice & Garcia, 2011; Car l ton et al., 2016; Busby, 2018) . These stresses can be dynamic and interac t with national and other types of in security such as food and water (Goodman, 2012). Environmental insecurity is not only a cause of biodiversity decline and social instability but also a consequence (Gore et al., 2016). Environmental security is not a un iversally defined term, although it consistently manifests across socio - ecological systems and is a widespread policy aim (Zurlini & Muller, 2008). The concept typically refers to people having enough nutritious food, sufficient water, and natural resource s to live and prosper ( Detraz, 2009 ; Spring, 2009; Elliott, 2015; Gore et al., 2016). As the world ha s blurred boundaries between conservation governance and national defense sectors, the scientific field of environmental security has emerged to support de cision - making ( Hezri & Hasan, 2006; Goodman, 2012). Obtaining a state of environmental security, especially at a local level, is complicated by insufficient evidence about how local people perceive and respond to environmental insecurity (Goodman, 2012). Environmental security can link to other forms of security ( Detraz, 2009 ; Spring, 2009; Elliott, 2015; Gore et al., 2016 ; Busby, 2018 ) . For example, f ood security connects to environmental security directly with the expansion of energy use, production, and consumption by (Naylor et al., 20 07 ). For example, biofuels growth can affect food security by affecting agricultural development patterns , which can affect prices in the markets (Naylor et al., 2007). However, the literature appears to be lacking evidence exploring relationships between types of security ( e .g. , environmental security, food security, poaching, water security) , with most literature 51 looking at a singular security and factors affecting it (Rice & Garcia, 2011; Loftus, 2015). Us i n g local perceptions to address the gap between the interactions of in security could help improve policies to address all environmental insecurities (Ntuli et al., 2019) . This chapter aims to help to fill in knowledge gaps about the relationship between various forms of insecurity. I aim to root out the main causes of insecurity, find relationships between factors, and assist local people and policy makers with new local insecurity information. It addresses individual factors suc h as local perceptions of nature mythology and environmental in security along with an understanding about environmental insecurity and its relationship to other forms of insecurity. Local communities are key to this understanding, as they experience both t he causes and consequences of environmental insecurity (Baird et al., 2009; Gore et al., 2016; Ntuli et al., 2019) . 3 .2 BACKGROUND Other studies in South Africa have focused on environmental security factors such as food and nutrition (Govendar et al., 20 16; Bakari & Ahmadi, 2018). These studies highlight the utility of incorporating local perspective s . Locally, such insight can give communities taking part in the research because it helps give them a voice. Scientifically, these studies help gain theoretical insight that could inform more effective decision making (Gore et al., 2016). The current relationship between distinct types of security may undermine economic performance, good Interpretatio n of l ocal perspectives have the potential to root out the main cause of security issues while assisting policy makers in creating laws that not only help the local people but also help the country in terms of the economy, national security, and its wildli fe (Gore et al., 2016). 52 3 .2. 1 . Objectives O verview The goal of this chapter is to explore local perceptions about the causes and consequences of environmental insecurity within the Greater Mnisi Tribal Authority Region (MTA), Mpumalanga, South Africa. Gi ven the evolution of environmental security literature from a conservation perspective, I wanted to focus this research on conservation related environmental insecurity. I chose the MTA because it exhibits high levels of biodiversity and is surrounded by p rivate game reserves and national parks (including directly next to Kruger National Park) which are leading the global push in conservation efforts . I am interested in environmental insecurity outcomes in such r egions and studying other forms of insecurity interactions in such areas . The three research objectives were to: i ) explore local perceptions of environmental insecurity, including perceived relationships with other forms of insecurity; ii ) compare and contrast loc al perceptions of risk associated with environmental and other forms of insecurity; iii ) Explore relationships between factors, including non - security factors and demographics, influencing and being influenced by environmental insecurity. To contextualize the objectives, I first describe the literature offering different conceptualizations of security. An in - depth overview of multiple factors in environmental i n security is utilized to give a broad overview of the complex nature of the subject. I then presen t key results from analysis designed to support each of the three objectives and conclude with a discussion about noteworthy points for conservation decision making that explicitly considers conservation social science. 53 3 .3 DIFFERENT CONCEPTUALIZATIONS OF SECURITY 3 .3.1 . Environmental S ecurity Environmental security is a contemporary concept ( Graeger, 1996 ). Definitions differ significantly depending on the context of the conversation. Certain themes emerge including people need to have access to an adequate amount of food, water , and natural resources to live (Spring, 2009; Gore et al., 2016; Busby, 2018). Themes also include having the ability to pay for and have contact and access to sources of natural resources that are healthy (Spring et al., 200 9; Busby, 2018). Included in this is the ability to recover from natural disasters that cause social and economic problems for those involved and even those that are indirectly involved. Environmental security takes into account how changes to the environment can negatively affect national security, its effects on armed conflict, and threat to human security (Elliott, 2015). For all countries, environmental changes are a national security problem (Elliott, 2015 ; Nellemann et al., 2016 ) . Problematically, traditional pressures and threats to a nation are the predominant focus when thinking about environmental security (Barnett, 2020). For example, governments will focus on the violence betwee n social groups that erupts from natural resource depletion while labeling it strictly as conflict but will not focus on the cause of the conflict , the natural resource resources as their primary source of livelihood ( Norfolk, 2004 ; Twyman & Slater, 2005; Balbi et al., 2019). As natural resourc es change, often decreasing, because of human interaction, environmental security will become deeper entrenched in human security and policymakers will need to focus on the viewpoints of local people to help solve the crisis (Elliot t , 2015). Previous research rarely touches on the concept of interconnectedness (Barnett, 2020). Global interconnectedness makes environmental security c omplex, especially when looking at 54 crime, poaching, and political instability that all stem from environmental insecurity. For example, a person in a rural, resource - dependent village, poaches an animal (crime in security and poaching) because they do not h ave access to food (food insecurity). They also need a source of water because reliable local or federal government to help them out with health supplies if their children or themselves were to get ill ( lack of trust and governmental in security). The single act of poaching connects globally when that poached animal is trafficked and shipped , for example via an airport in Africa with criminal syndicate shipping routes to a large buyer where ivory has been known to be purchased illegally on the black market (Wasser et al., 2018). Environmental security has developed into a concept that revolves around inte rconnectedness with many moving parts and can affect parties worldwide. I outline key forms of security within this interconnected framing below. 3 .3.2 . Food Security F ood security is defined as physical, social and economic access to sufficient, safe and nutritious food that meets their dietary FAO et al. , 20 19, p. 186) . We can then think of food insecurity as the failure and inability t o access those secure and nutritious foods to grow (Govender et al., 2016). More pertinent to my research, other groups have recently created new definitions stating that food and nutrition insecurity is the absence of wholesome food that the human body needs to grow and mature properly, while finding a direct relationship between food insecurity and poverty (World Health Organization, 2000; Poppy et al., 2014; Ag ar wal, 2018). This absence can relate to access or lack of money to purchase goods suc h as food (Govender et al. , 20 16 ). 55 Along with poverty, rapidly increasing population growth is linked to food insecurity (Walker, 2016). Up to 2015, t here has been recent progress with food security globally with global undernourishment steadily dropping f rom 14.5% in 2005 to 10.6% in 2015 , but positive change is often limited to regions and countries where the birth rate and fertility rates are low (Walker, 2016 ; FAO et al., 2019 ) . However, since 2015, food insecurity and the amount of undernourished peopl e globally is rising ( FAO et al., 2019). The International Food Policy Research Institute (IFPRI) published the Global Hunger Index (GHI) in 2015 and showed that the largest, and the most food insecure, of all the highest GHI scores were found in Sub - Sahar an Africa and South Asia (Walker, 2016). Fast forward to today, Sub - Saharan Africa and South Asia are still the highest scores ranked on the 2019 Global Hunger Index by Severity (Grebmer et al., 2019). 3 .3.3 . Water Security Concurrent with food security, water security is a pressing global issue that has been prioritized by the global sustainable development community (Bogardi et al., 2012) . Water security is a broad term encompassing ensuring healthy water related ecosystems, that all people are able to access safe water that is cost effective, and also lessening the water - related risks to people such as drought. (Grey & Sadoff, 2007; Bogardi et al., 2012 ; Meissner et al., 2018). Water security is pertinent as t he United Nations estimate s the re will be a rapid increase in the global population facing water scarcity issues , with possibly 700 million people being relocated due to water scarcity issues by the year 2030 ( Hameeteman, 2013; Olson, 2013 ; UN - Water , 2020 ). W ater security is a major factor in Africa , with the Seychelles and South Africa among the most secure countries , while Malawi and Madagascar are the least secure ( H o lmatov et al., 2017 ; Meissner et al., 2018). Water security is complex and much like food security, it is tied to a multitude of variables such as age and sex . In addition, like other types of security, water security 56 is defined depending on the source . Water security in the MTA might be defined much differently than it is in in Cape Town or Johannesburg , which is why it is important to use local perceptions to relieve water insecurity. 3 .3.4 . Crime Security Within my thesis, t here are two categories of crime in security outlined : traditional crime including burglary, drug crimes, murder, and rape, and environmental crime including deforestation (illegal wood taking), water and land littering, and poaching. Poaching, one of many global environmental crimes and traditional crime are directly linked (Collins et al., 2017; Wasser, et al. 2018). Environmental crime is increasing daily on a global scale and has a reach that is further than natural resource and habitat destruction including access to food, water, and shelter and potential ly affecting crime rates (Nellemann et al., 2016 ; York, 2019 ). Not only does organized traditional crime lead to environmental degradation, it also can threaten legitimized governments (Zimmerman, 2003) . Offenders can weaken a stable political system, put stress on their local and legal economy, and most times directly or indirectly, bring corruption to society and developing countries (Zimmerman, 2003). Organized crime is often associated with the drug trade, but it has just as large of an impact within po aching and the illicit trade of animals and animal parts (Van Uhm, 2016; Wasser et al., 2018). Powerful groups conduct organized crime with many layers that enlist the use of corruption and tactful trade routes to pull off their schemes and jobs (Wasser et al., 2018). There are many examples of organized crime within the illicit animal trade, such as the use of airports and organized crime channels to export goods from country to country (Wasser et al., 2018). Thinking about environmental issues and natural resources in terms of security is a relatively new concept that should receive more merit and educational interventions, as it plays a 57 large role in the illicit animal trade (Hariohay et al., 2019; Naro et al., 2020). Douglas & Alie (2014) bring up the co ncept of viewing natural resources as high - value resources that can have destabilizing effects on wildlife industries and influencing global and national security . High - value resources are those that might deliver revenues, usually substantial in their nat ural states. Examples can include oil, uranium, and diamonds (Douglas & Alie, 2014). W hen managed properly, these with interventions such as ecotourism , help with national security, and can even raise living standards (Lujala & Rustad, 201 1 ). However, some suggest that the opposite effect happens , and these high - value resources cause more issues than were originally present (Douglas & Alie, 2014). Undermining economic performance and environmental governance is connected with wildlife. Wildlife can speed up unstable government incentives and possibly weaken and destabilize economic development ( UNEP , 2009). This can overall influence accountability, weaken development, including when t here is an exposure to economic shock, and impact corruption and environmental policies (Douglas & Alie, 2014). 3.3.5 . Trust Trust is a crucial part of any community, group, or institution. This is especially true of post - apartheid South Africa where man y believe that South Africa may develop like other liberated, post - colonial countries, where the actions of the liberators eventually turn ed into the government bodies strictly based o n what they did for the liberation movement (Friedman, 1999; Askvik, 200 8). Previous studies show that trust in the South African Government is related to a residents identity linked to race, party preference, nationalism, and political integration while also being linked to performance, leading one to believe that a combined approach in evaluating trust may be the best approach ( Mishler & Rose, 2002; Askvik, 2008). 58 Trust can also lead to n on - payment in local authorities , much like the MTA , leading to forms of insecurity because payments are not being remitted ( Fjeldstad, 2004 ) . Political legitimacy theory suggests that proper tax payments are greatly influenced by a residents trust in their government (Fauvelle - Aymar, 199 9 ; Tyler, 2006 ; Kirchler et al., 2008; Ali et al., 2014). Legitimacy comes from the trust t hat the government will act for the common good (Ali et al ., 2014). Compliance may come from three different aspects of trust, i ) trust that the government will use the revenue for the services that the residents want and expect ii ) trust that the governme nt will collect and distribute the revenue fairly , and iii ) trust that other residents will take part and pay their share of the taxes or fees ( Fjeldstad, 2004 ). These concepts of trust all play into the trust that interacts with the assembly of in security concepts within the MTA and are important to note. 3.3.6 . Nature Myths Risk perceptions can affect attitudes about biodiversity, trust in local management and government agencies, and partiality towards types of risk management (Muter et al., 2013; Gore et al., 2016) . Cultural theory of risk plays a large roll in assessing local perceptions of responses to conservation, biodiversity exploitation, and insecurity in a bottom - up approach (Douglas, 1978; Gore et al., 2016). There are four categories within cultural theory based on various cultural attributes including egalitarian, fatalistic, hierarchical, or individualistic (Douglas, 1978; Gore et al., 2016) . There are four responses that are seen based on cultural theory that include M yths structed myths about nature (Douglas & Wildavsky, 1983; Dake, 1992; Gore et al., 2016). These myths are internalized by people, reshaped , and then influence their thoughts about nature, conservation, and environmental problems (Dake, 1992). These perceptio ns by local residents can help policy 59 makers assess agreement to future and current insecurity interventions to see how they will be responded to at a local level (Gore et al., 2016). 3 . 4 RESULTS 3 . 4 .1. Explore L ocal P erceptions of E nvironmental I nsecurity, I ncluding P erceived R elationships w ith O ther F orms of I nsecurity The first objective was to characterize other forms of insecurity connected to environmental insecurity, including the relationships between them (e.g., crime in security, food in security, water in security, trust in security, and poaching). All residents recognized environmental insecurity as some threat in the MTA (M = 4.87, range: 0 - 7, SD = 0.85). Table 1 4 displays th e correlations between the above factors. Envir onmental in security is correlated with crime in security r (211) = 0 .3 8 , p < 0 .01 , food in security r (211) = 0 . 48 , p < 0 .01 , poaching r (211) = 0 .15, p < 0.05 , trust in security r (211) = 0 . 15 , p < 0.05 , and water in security r (211) = 0 . 59 , p < 0 .01 . Table 1 4 : Pearson Correlations of five in security indexes related to environmental in security within the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Statistical significance is denoted with asterisks. One asterisk for statistical significan ce at the 0.05 level and two for the 0.01 level. Figures in bold font are significant. Crime Environmental Food Poaching Trust Water Crime 1 0.38 ** 0.19 ** 0.20 ** 0.10 0.20 ** Environmental 0.38 ** 1 0.48 ** 0.15 * 0.15 ** 0.59 ** Food 0.19 ** 0.48 ** 1 0.01 0.12 0.47 ** Poaching 0.20 ** 0. 15* 0.01 1 - 0.15 * 0.08 Trust 0.10 0.15 ** 0.12 - 0.15 * 1 0.10 Water 0.20 ** 0.59 ** 0.47 ** 0.08 0.10 1 Individual demographic factors did not play a large role in influencing residents risk perceptions on environmental in security. Table 1 5 displays the six fixed factors and one random factor that went into data analysis. The only factors that had significan 60 was their age, employment status, and ownership of land status. With every year that a resident was older in the MTA, their risk perception on environmental in security increased by 0.35 points per year. Village location played had means that overall risk perception of environmental in security across the MTA is consistent with a mean of 4.66 and standard deviation of 0.94. Table 1 5 : Local perceptions (N = 211) about envir onmental factors in the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Included are Mean Squares (MS), Variance Components (VC), F tests (F), LRT (likelihood ratio test value) and respective p - values for threats of harms and environmen tal harms within the MTA community. Significant p - values are denoted with *. Environmental Index Fixed Effects MS F P Age 26.50 36.21 0.00* Children in House 0.92 1.26 0.26 Gender 0.56 0.77 0.38 Employed 3.22 4.40 0.04* Owns L and 7.41 10.12 0.00* Ethnicity 2.49 3.40 0.67 Random E ffects VC LRT P Village 0.00 0.00 1.00 Residual 1.24 Lastly, water in security in the MTA positively correlates with crime in security, environmental in security, and food in security. Data from residents in the MTA exhibited a strong correlation r (211) = 0 .47, p < 0 .01) between water in security and food in security which could be taken into account when creating education and interventions. 3 . 4 .2. Compare and C ontrast L ocal P e rceptions of R isk A ssociated with E nvironmental and O ther F orms of I nsecurity Explorations of th is relationship revealed that increased risk perceptions of poaching threatening local communities (B = 0 . 29 , SE = 0 .0 4 , p < 0.05) and poaching harming the environment (B = 0 . 2 9 , SE = 0 .0 5 , p < 0.05) influenced risk perceptions within the environmental 61 in security index. V illage location impacted the poaching index (LRT = 8.20, VC = 0.13, p < 0.05) . T he top three most threatening harms to the MTA community as perceived by the MTA residents were drought, deforestation, and littering on land while development within the MTA was perceived to be the least threatening (Table 1 6 ). Table 1 6 : Perceived risk ranking of ten threats to environmental security according to residents (N = 211) in the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Environmental Risk Tsonga Translation Mean (SD) Range 1 - 10 Deforestation Ku tsemeleriwa ka nhova/Minsinya. 7.53 (2.82) Littering on land Ku lahliwa ka thyaka laha swinga fanelangiki 6.85 (2.99) Drought Dyandza 6.32 (2.99) Cattle theft Ku yiviwa ka tihomu 5.43 (3.36) Overgrazing of cattle Ku rimiwa ka ndhamu leyi tlulaka mpimo 5.17 (3.12) Poaching of wildlife Ki hlotiwa ka swiharhi swingari enawini 5.13 (3.11) Mosquitoe s (disease vector) Vuvabyi bya Malaria lebyi kumekaka ka tinsuna 5.10 (3.06) Littering in water Ku thyakisiwa ka mati 5.06 (3.24) Erosion of soil Ku khukuriwa ka misava hi mpfula. 5.00 (2.90) Development Nhluvuko 3.49 (2.61) Residents deforestation ha d a negative impact on their community (M = 4.81, SD = 2.23) had a positive impact on perceptions of concern about environmental in security (B = 0 . 53 , SE = 0 .0 3 , p < 0 .0001) that deforestation harms the environment (B = 0 . 14 , SE = 0 .04, p <.05). Residents age ( p < 0.05 , F = 4.41, MS = 21.25) and ethnicity ( p < 0.05 , F = 3.56, MS = 17.16) also factored into their perception on the negative impact of deforestation to their community. 62 Littering on land was a highly rated threat by residents (M = 6.85, SD = 2.99). The effect of pollution and littering on land had a positive effect on environmental in security. Residents also worried that they did not have a reliable way of disposing of trash legally. Village location affected the results (LRT = 5.91, VC = 0 .29, p < 0.05). R esidents showed pollution (littering/trash) had a negative impact on their communities (M = 5.88, SD = 1.55). Age affected percept ions (F = 7.60, MS = 17.47, p < 0.05) and these overall perceptions had a positive impact on overall environmental in security within the MTA. Last, higher perceived frequency of land littering positively affected risk perception of environmental in security (B = 0 . 22 , SE = 0 .0 4 , p < 0.0 1 ). Perceived frequency (p < 0.05, F = 6.04, MS = 15.77), and if the participant was a landowner (p < 0.05, F = 7.06, MS = 18.45). Along with land littering, littering in water, which was not ranked as highly (Table 1), but which still was thought of as a threat, also had a positive effect on environmental in security (B = 0 . 33 , SE = 0 . 33 , p < 0.0 1 ). 3 . 4 .3 . Explore R elationships B etween F actors , I ncluding N on - security F actors and D emographic s I nfluencing and B eing I nfluenced by E nvironmental I nsecurity All residents recognized environmental insecurity as some threat in the MTA (M = 4. 66 , range: 0 - 7, SD = 0. 94 ), while gender revealed insignificant differences (Female M = 4.94, Male M = 4.81) in perception. A majority of residents (81.52%) acknowledged biodiversity exploitation because of deforestation was happening frequently. Of those approximately 82%, more than half acknowledged deforestation happened every day. In the form of poaching (M = 2.1 8 , range: 0 - 7, SD = 1.14), residents perceived biodiversity exploitation to be much lower than deforestation. Although g ender was not statistically significant, there was a sizeable difference between 63 perceptions of men (M = 2.34, SD = 1.23) and women (M = 2.02, SD = 1.01) in perceptions of poaching frequency . Only one index was noteworthy when looked at through the lens of gender - risk perception related to water in secur ity (p < 0.05, F = 8.38, MS = 14.42) . G ender did not have any significance related to crime, education and employment, environment, food, poaching, and trust. Risk perception related to running out of food, not being able to afford food, worrying about not having money to purchase food, and having to eat less because of lack of food were all not affected while the wish for more food was the only significant result with women wishing for the ability to have more food than men (p < 0.05, F = 4.60, MS = 14.24) . Trust was a key comp on ent of O bjective 3 . I asked residents their thoughts on trust and related subjects within their community and surrounding areas. The trust index was positively correlated with the environmental index ( r (211) = 0 . 15 , p < 0 .0 5 ), with trust also being positively correlated with education and employment as well as negatively correlated with poaching (Table 1 7 ). Table 1 7 : Pearson Correlations of seven in security indexes within the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Statistical significance is denoted with asterisks. One asterisk for statistical significance at the 0.05 level and two for the 0.01 level. Crime Education and Employment Environmental Food Poaching Trust Water Crime 1 0.07 0.38 ** 0.19 ** 0.20 ** 0.10 0 . 20 ** Education and Employment 0.07 1 0.00 - 0.09 0.03 0.24 * * 0.07 Environmental 0.38 ** 0.00 1 0.48 ** 0.15* 0.15 * * 0.59 ** Food 0.19 ** - 0.09 0.48 ** 1 0.01 0.12 0.47 ** Poaching 0 . 20 ** 0.03 0.15* 0.01 1 - 0.15 * 0.08 Trust 0.10 0.24 ** 0.15 ** 0.12 - .015 * 1 0.10 Water 0.20 ** 0.07 0.59 ** 0.47 ** 0.08 0.10 1 64 Trust, and concepts related to trust, such as corruption and integrity were associated with very high - risk perception rankings throughout the MTA. Residents ranked worrying about corruption (M = 5.92, = 1.73, median = 7.00) as the largest singular trust issue meaning that out of all risk perceptions studied MTA residents felt that corruption in the MTA was the most worrisome. MTA residents also show ed a large distrust in local government (M = 2.97, = 2.13, median = 2.00) and national gov ernment (M = 3.64, = 2.314, median = 3.00). Residents ranked trust in rangers in the surrounding protected areas and game reserves (M = 4.97, = 2.00, median = 5.00) significantly higher (Table 1 8 ) . Table 1 8 : Residents perceptions on trust within the Mnisi Tribal Authority, Mpumalanga, South Africa and the surrounding area (May July 2019). Included are the mean, standard deviation, and median. A 7 - point Likert - type scale was used. Factors Corruption Worry Local Govt. Trust Local Police Integrity Na t. Govt. Trust Ranger Trust Trust (general) Trust Index Mean 5.92 2.97 3.15 3.64 4.97 4.49 4.19 1.73 2.13 2.12 2.31 1.99 2.37 1.22 Median 7.00 2.00 3.00 3.00 5.00 5.00 4.00 Worrying about corruption had a positive effect on environmental in security risk perception (B = 0 .1 6 , SE = 0 .03, p < 0.0001 ). Lastly, trust varied by village (Table 1 9 ). When exploring the relationship between environmental insecurity and myths of nature (i.e. , beliefs that nature finds balance or that the environment is random) , residents agreed that the environment and nature is random (64%, n = 135, M = 5.03, SD = 1.77) and that the environment always finds a way back to balance (55%, n = 115, M = 4.65 , SD = 1.96). A majority (93%, n = 197, M = 6.30, SD = 1.309) of residents felt that environmental harms are unacceptable and need to be stopped while also accepting that there are environmental harms and the justifications to manage those harms (79%, n = 166, M = 5.78, SD = 1.59). I asked if they would ignore 65 answers were split in opinion, with less than a majority on either side (M = 3.8 0 , SD = 2.31). However, a majority of residents disagreed that environmental harms create new opportunities for creativity, innovation, and development (54%, n = 114, M = 3.44, SD = 2.14) and that harms are best ignored or avoided (59%, n = 126, M = 3.36, S D = 2.37). 66 Table 19 : Residents perceptions on trust by village within the Mnisi Tribal Authority, Mpumalanga, South Africa and the surrounding area (May July 2019). Included are the mean, standard deviation, and median for all villages measured. Village Corruption Worry Local Govt. Trust Local Police Integrity Nat. Govt. Trust Ranger Trust Trust ( Gen. ) Trust Index Clare A and B Mean 6.23 2.41 3.18 2.68 5.32 5.00 4.14 1.19 1.71 2.06 2.01 1.70 1.95 1.24 Median 7.00 2.00 2.50 2.00 5.50 5.50 4.08 Gottenburg Mean 5.36 3.09 3.05 3.36 4.86 4.91 4.11 2.38 1.95 1.99 1.99 1.89 2.25 1.15 Median 7.00 3.00 3.00 3.00 5.00 5.50 4.00 Hlavekisa Mean 5.23 3.00 3.96 4.59 5.73 4.77 4.55 2.25 2.49 2.63 2.59 1.88 2.56 1.32 Median 7.00 2.00 4.00 5.50 7.00 7.00 4.75 Hluvukani Mean 6.32 3.00 2.80 3.40 4.52 4.84 4.15 1.22 2.02 2.12 2.52 2.24 2.34 1.19 Median 7.00 2.00 2.00 2.00 5.00 6.00 4.17 Islington Mean 6.33 3.11 3.22 3.28 4.39 4.67 4.17 1.14 2.68 2.67 2.63 2.40 2.81 1.69 Median 7.00 1.50 1.50 2.00 4.00 6.50 3.17 Ludlow Mean 6.38 3.69 3.63 4.19 5.31 3.13 4.39 0.96 2.06 2.06 2.23 2.02 2.09 1.15 Median 7.00 3.50 3.50 4.50 6.50 3.00 4.50 Manyeleti Mean 5.75 3.06 2.69 3.75 5.25 4.94 4.24 1.61 2.46 1.89 2.62 1.48 2.49 1.39 Median 6.00 2.00 2.00 3.00 5.00 6.50 3.92 Tintswalo Village Mean 6.16 2.32 3.28 3.68 4.84 4.72 4.17 1.21 1.70 1.86 2.12 1.84 2.01 1.10 Median 7.00 2.00 3.00 4.00 5.00 5.00 4.33 Welverdiend Mean 6.24 3.20 2.72 3.68 5.16 4.16 4.19 1.69 2.24 2.09 2.12 2.12 2.53 1.05 Median 7.00 3.00 2.00 4.00 6.00 4.00 4.00 White City/Burlingt on Mean 5.10 3.10 3.10 3.95 4.35 3.45 3.84 2.43 2.15 1.86 2.31 2.08 2.35 1.06 Median 6.50 3.00 3.00 4.00 4.00 2.50 3.67 Total Mean 5.92 2.97 3.15 3.64 4.97 4.49 4.19 1.73 2.13 2.12 2.31 1.99 2.37 1.22 Median 7.00 2.00 3.00 3.00 5.00 5.00 4.00 67 Study residents reported perceptions of poaching on ten species known to inhabit MTA lands and the surrounding area. Across all villages sampled, the top four species perceived to be poached were rhino ( Ceratotherium simum and Diceros bicornis ) (M = 4.10), impala ( Aepyceros melampus ) (M = 2.59), elephant ( Loxodonta africana ) (M = 2.11), and pangolin ( Manis temmenickii ) (M = 2.04) (Table 11). Across all villages sampled, the three species perceived to be poached least frequently were wild dog ( Lycaon pictus ) (M = 1.64), leopard ( Panthera pardus ) (M = 1.73), and hyena ( Hyaena brunnea ) (M = 1.85). There was significant variation across individual villages (VC = 0 .1 3 , LRT = 8.2 1 , p < 0 .05) on perception of frequency (Table 12, 13). Residents from Gottenburg (M = 2.98, SD = 1.85, median = 2.70), Tint swalo Village (M = 2.48, SD = 1.47, median = 1.90), and White City/Burlington (M = 2.48, SD = 1.47, median = 1.80) perceived poaching rates to be higher compared to other villages. Gottenburg and White City/Burlington had significantly higher frequency per ceptions than all other villages. Participants had lower perceptions of poaching frequency in Hlavekisa (M = 1.60, SD = 1.04, median = 1.20), Islington (M = 1.77, SD = 1.547, median = 1.00), and Clare A and B (M = 1.81, SD = 1.14, median = 1.40), with resi perceptions ranking under the average of all villages (M = 2.17). Residents were asked about their perce ptions of environmental harms associated with poaching. Residents age (MS = 8.03, F = 5.0 1 , p < 0 .05), children living in their household (MS = 8 .26, F = 5.1 6 , p < 0.05 ), and land ownership status (MS = 7.8 5 , F = 5.1 6 , p < 0 .05) all had significant influence on their perceptions. Risk perception of the threat to their local community attributed to poaching was influenced by age (MS = 29.0 6 , F = 10. 66, p < 0 .05), children living in their household (MS = 16.49, F = 6.05, p < 0 .05), and ethnicity (MS = 17.21, F = 6.31, p < 0 .05). Older viewpoint s on poaching harming the environment increased by 0 .20 points for 68 every ten years (B = 0 .02, SE = 0 .0 1 , p < 0 .05) and increased their perception of harm to their community by 0 .38 points for every ten years (B = 0 .0 4 , SE = 0 .01, p < 0 .05). Having children in the household decreased their perception of harm to the environment due to poaching (B = - 0 .10, SE = 0 .0 5 , p < 0 .05) and decreased their perception of harm to their location community (B = - 0 .1 5 , SE = 0 .06, p < 0 .05). Land ownership had the same effect, perception of poaching harm to the environment (B = - 0 .49, SE = 0 .22, p < 0 .05), while identifying as Tsonga had the opposite effect, significantly increasing a residents risk perception of harm to their community (B = 0 . 90 , SE = 0 .36, p < 0 .05). Also, noteworthy, poaching was positively correlated with crime perceptions (Table 2 0 ). Table 2 0 : Local perceptions ( N = 211) measuring the perception of frequency of individual animals poached in and around the Mnisi Tribal Authority, Mpumalanga, South Africa (May July 2019). Included are Mean Squares (MS), Variance Components (VC), F - tests (F), LRT (likelihood ratio test value) and respective p - values for perception of individual poached animals within the Mnisi Tribal Authority. Significant p - values denoted with *. Elephant Poaching Hyena Poaching Fixed Effects MS F P MS F P Age 4.05 1.80 0.18 0.41 0.24 0.62 Children in House 2.10 0.94 0.34 2.76 1.62 0.21 Gender 3.27 1.45 0.23 1.49 0.87 0.35 Employed 0.71 0.32 0.58 0.21 0.12 0.73 Owns L and 0.12 0.05 0.82 2.09 1.22 0.27 Ethnicity 1.51 0.67 0.41 0.00 0.00 0.10 Random E ffects VC LRT P VC LRT P Village 0.14 2.97 0.09 * 0.12 3.61 0.06 * Residual 2.25 1.71 Impala Poaching Leopard Poaching Fixed Effects MS F P MS F P Age 0.03 0.01 0.92 1.18 0.77 0.38 Children in House 0.81 0.27 0.61 1.28 0.83 0.36 Gender 17.37 5.73 *0.02 0.37 0.24 0.62 Employed 0.26 0.09 0.77 0.21 0.14 0.71 Owns L and 1.64 0.54 0.46 2.40 1.57 0.21 Ethnicity 1.14 0.38 0.54 0.59 0.39 0.54 Random E ffects VC LRT P VC LRT P 69 Village 0.38 10.01 0.00 * 0.11 4.04 0 .04 * Residual 3.03 1.53 Lion Poaching Pangolin Poaching Fixed Effects MS F P MS F P Age 1.86 1.29 0.26 0.01 0.00 0.95 Children in House 0.10 0.07 0.79 5.05 2.35 0.13 Gender 0.91 0.63 0.43 2.01 0.93 0.34 Employed 1.97 1.36 0.25 0.63 0.29 0.59 Owns L and 1.33 0.92 0.34 0.20 0.09 0.76 Ethnicity 1.60 1.10 0.30 0.00 0.00 0.96 Random E ffects VC LRT P VC LRT P Village 0.11 4.59 0.03 * 0.25 8.74 0.00 * Residual 1.45 2.15 Python Poaching Rhino Poaching Fixed Effects MS F P MS F P Age 0.01 0.01 0.94 0.85 0.21 0.65 Children in House 0.88 0.42 0.52 0.82 0.20 0.65 Gender 4.44 2.14 0.15 4.80 1.20 0.28 Employed 0.01 0.01 0.94 1.62 0.41 0.53 Owns L and 0.01 0.01 0.94 2.74 0.68 0.41 Ethnicity 0.54 0.26 0.61 0.00 0.00 0.99 Random E ffects VC LRT P VC LRT P Village 0.07 1.12 0.29 0.53 8.95 0.00 * Residual 2.07 4.00 Vulture Poaching Wild Dog Poaching Fixed Effects MS F P MS F P Age 0.45 0.22 0.64 0.01 0.01 0.92 Children in House 0.38 0.19 0.67 0.01 0.01 0.94 Gender 5.81 2.83 0.09 0.06 0.04 0.84 Employed 0.29 0.14 0.71 0.00 0.00 0.98 Owns L and 0.87 0.42 0.52 0.01 0.01 0.92 Ethnicity 0.48 0.23 0.63 0.01 0.01 0.93 Random E ffects VC LRT P VC LRT P Village 0.15 4.14 0.04 * 0.08 2.96 0.09 * Residual 2.05 1.36 70 3 . 5 DISCUSSION 3. 5 .1 . Overview From climate change being recognized as a national security threat by the U.S. Department of Defense in 2010 to COVID - 19 redefining water, food, and biodiversity exploitation security issues, environmental security is long - lasting and will have an enduring impact on lives (La Shier & Stanish, 2017; Wilkinson & Tellez - Chavez, 2020). Understanding the assessed risks and perceived risks associated with these various types of insecurities at all levels will be key to supporting policies and policymakers that ai d in risk reduction. Many outcomes associated with environmental in security such as biodiversity loss are irreversible once they reach a certain threshold, making it imperative to understand the perceptions of local people to help in problem - solving and ed ucational interventions (Gore et al., 2016; Naro et al., 2020). and insecurity to the forefront of discussions about policy decisions, conservation decisions, and national security (United Nations Department of Economic and Social Affairs, 2020) . The 17 global action towards a more sustainable tomorrow ( Fullman et al. , 2017 ; Fourie, 2018; Wong & van der Heijden , 2019 ; United Nations Department of Economic and Social Affairs , 2020). One challenge facing individual - South Africa adopted a National Development Plan (NDP) in September 2012, before the UN organized the SDGs (National Planning Commission: South Africa, 2012) latch onto the SDGs . H owever , securities, are complex in that they have many measurem ents that assess them while we tie them into different factors such as age and gender. 71 3. 5 .2 . Gender D isparity : L ack T hereof Gender theory postulates that security is linked to the enablement of each person , and to the abilities to foster constructive environments of where insecurity is not present ( Hoogensen & Stuvøy , 2006 ). R esearch associated with environmental security risks which try to answer empirical questions regarding the effects of environmental security and its connection to oth er variables, taking into account the perceptions of local people being affected, is not commonplace. - one can conjecture that gender is important to reducing insecurity ( United Nation s Department of Economic and Social Affairs, 2020 ) . The disadvantages women of the world face do not operate in isolation and are related to factors such as location and wealth. These combinations of factors create various and substantial disadvantages for women from clean water , educational advancement and access , and employment opportunities ( UN Women & DE , 2019). Current research suggests that risk perceptions about environmental degradation are heightened in women when compared to men , and there are strong associations between gender disparity and food insecurity ( Sundström et al., 2019; Aziz et al., 2020 ). studied population. Gender did not play a significant role in the crime, education and employment, environment, food, poaching, and trust indexes . Previous research in the same area has shown that women are less likely to condemn commercial poaching and less willing to participate in anti - poach ing interventions ( Sundström et al., 2019). It was noteworthy to see that gender did not return as a significant result more often. I would have also thought I would see some major disparities in items like deforestation , as women are the primary collectors for their households (Agrawal, 2001). 72 I think a p lausible reason for gender not playing a larger role is because the communities are very close knit, leading to common perceptions on many variables. 3. 5 . 3 . Gender, F ood I ns ecurity , W ater I n security, and D eforestation Women play a central role in efforts to achieve food security, particularly at the household level ( Agarwal, 2018 ). Food security is consistent access to food that properly provides nutrition t o every person (Tibesigwa & Visser, 2016). Women are the dominant food producers, managers and consumers and they allocate a disproportionate amount of their time in processing and preparing food ( Agarwal, 2018 end on access to land and depends on diverse social norms. Women when compared to men usually have less bargaining power which can lead to disadvantages in the way they are able to contribute to a household (Kiewisch, 2015). It also depend s on laws that are created by males that give privilege and prime access of land to males ( Agarwal, 2018 ). Land ownership statistics from various countries illustrate these imbalances between men and women. For example, in Ghana, women own just 10 % of household lan ds, and in Kenya women own 5 % of the land ( Agarwal, 2018 ). Within Sub - Saharan Africa, South Africa has the largest percentage of female - headed households (e.g., 42%) while the range for other parts of Africa are as low as 9.5% and as high as 29.5% (Tibesi gwa & Visser, 2016). The sizable economy of South Africa contributes to a satisfactory supply of food when assessed at a national level, but when local and household level statistics are assessed, food insecurity statistics are much higher (Tibesigwa & Vi sser, 2016). The impacts from climate change women at local levels, it may magnify these impacts, as they already face many vulnerabilities that men do not (Ti besigwa & Visser, 2016). We also know men are closely connected with efforts to 73 overcome child malnutrition and increase access to nutritional crops (Tibesigwa & Visser, 2016). Malnutrition and food insecurity at the household level affect child survival r ates, while they have found overall nutrition and health have all to be greater when women own assets and derive their own income ( Bhattarai et al., 2015; Agarwal, 2018 ). Climate change - allocation of time dedicated to these aforem entioned household activities will probably further complicate successful , sustainable development. In at least these regards, it is unsurprising that attaining SDG 5 is considered being worthwhile in its connections to other sustainable development issues ( Agarwal, 2018 ). T he MTA B oard members brought up the possibility of a dam for the MTA to aid in water insecurity reduction . They acknowledged the lack of water and energy leading to insecurity while speaking about how it was a large burden on the MTA which would correlate to previous research showing that an overall decrease in water use led to increased perceived depression scores (Workman & Ureksoy, 2017). The main issue addressed by the MTA was a lack of governmental support and funding , which backs up the current literature noting that water resource management needs a highly integrated approach to aid in sustainable devel opment ( Ikhlayel & Nguyen, 2017 ; Fourie, 2018). The SDG s are working to achieve water related accomplishments with SDG 6. SDG 6 focused on clean water and sanitation for all. Target 6.1 and 6.3 focus on worldwide and fair sources of water for all while al so incorporating the reduction of pollution and littering in water sources ( United Nations Department of Economic and Social Affairs , 2020 ) . Target 6.6 focuses on water - related ecosystems aiming to achieve protection and restoration by 2030. The goals are efforts to reduce water insecurity and needs at a local level can have unintended environmental 74 he needed cross - style analysis (Bhaduri et al., 2016). The interconnectedness of pressures on depletion of natural resources can have unwanted consequences on the water system globally. Actions at the local level to reduce water insecurity may cause greater stress at regional and global levels (Bhaduri et al., 2016). Along with water security, the MTA cannot safeguard food security without the cooperation and a sens e of proprietorship from all levels of government (Fourie, 2018). Food insecurity is increasing in many places around the world due to climate change and other causes , including in South Africa (Masipa, 2017) . Due to in c onclusive deforestation data in South Africa, I looked at other deforestation data from countries such as Cameroon. Cameroon is home to approximately 22 million hectares (ha) of tropical forests, which are about the size of Mexico ( World Resources Institute , 2017) . Since 2003, 3.3 millio n ha of those forests have been cut, directly resulting in food insecurity because deforestation and land degradation are key contributors and links to food insecurity ( World Resources Institute , 2017; Ngome et al., 2019). Findings showed that food insecur ity decreased in areas where deforestation had yet to happen, while areas that were moderately and extremely deforested had raised levels of food insecurity , and overall that household food insecurity increases with increased deforestation (Ngome et al., 2 019). Deforestation is a large threat to the MTA based on local perceptions. Food insecurity is also a large problem with many residents wishing for more food, not being able to purchase nutritional food, and not eating at certain meals to make sure that o go hungry. With a lack of alternative energy sources for household electrification and cooking, there is no end in sight for wood burning as the primary source of fuel for MTA households. 75 With all of these factors, food in se curity could keep increasing with the constant increase in deforestation linked to wood burning. There is a recognition that alternative sources of energy for the MTA are warranted . Concurrent with fears and perceptions felt in the MTA over deforestation, food in security is a multifaceted issue and is a crucial factor when looking to lessen environmental insecurity. When addressing food insecurity, it could be handled by going further than working to address increased food production or decreased poverty level. The policy could change to include natural resource management aspects along with the promotion of nutrition education in addition to increasing financial inputs to food product ion and distribution among others (Ngome et al. , 2019). 3. 5 .4. Trust Working on interventions to increase trust between the MTA and its citizens, notably a very difficult task to accomplish, would not only possibly help communication for furthering a posi tive community, it c ould positively affect food and water security and lessen perceptions of risk associated with drought and other naturally occurring disasters (Fourie, 2018). This could happen because trust research shows that residents are more likely to pay their taxes if they trust that their government is acting in their best interest ( Fjeldstad, 2004 ; Askvik, 2008) . With increased payment remittance, the MTA could use funding for new small hydro systems to eliminate water in security (eliminating dro ught risk perception and natural disaster risk perception), new nutritional food intervention programs, and other educational and intervention systems to help the community . Within the MTA and according to participating residents , there seems to be a disconnect between the people and the government, based on the perception of trust outlined above. Trust in local and national municipalities was relatively low among residents . One aspect of a disconnect 76 that is demonstrated by the dam is that this is an idea from the MTA Board and not the people. Yes, the MTA Board members are community members, but they are also elected officials who could have multiple agendas leading them to believe in a ce rtain intervention. However, the current negative perceived disconnect has the potential to be a positive within the MTA . There are connections between trust and other forms of in , such as the correlation to education and employment risk perceptions and exploring options for positive change in both categories . On the one hand, these connections make figuring out and deciphering in security issues challenging, yet, on the other hand it can help in insecurity red uction. Insecurity reductions can theoretically be reduced quicker and more efficiently due to these connections. For example, p erceptions of risk of environmental in security and trust are positively correlated r ( 211) = 0 . 15 , p < 0.05 . Data suggests that f environmental in security issues are resolved in the MTA, this could increase trust in local and national governments. Also, if trust increases, this could help increase environmental security. In turn, this could lead to on time remitt ance of tax payments and people caring more and trusting more in their government . Additional research would equivocate these relationships. The interconnectedness flows through the MTA and it is up to the MTA to utilize it to their advantage. 3. 5 . 5. Nature M yths It is typical to perceive greater risk associated when things are involuntary, catastrophic in scale, severe, worrying, or unfamiliar (Gore et al., 2007; Hanisch - Kirkbride et al., 2013 ; Gore et al., 2016). It is not surprising that drought was highly rated, and development ( e.g., road and infrastructure development in their community) was perceived as having a low risk , as South Africa was in a drought during the entirety of the research . However, development could have been ranked l ow on the risk perception scale due to want of new roads and development within 77 the community and lack of experience with development. While data collection was taking place, there were large development projects happening in the MTA. New roads were being built to lessen the drive and commute time between certain locations. Even though the construction was noisy and intrusive at the time s , many residents in conversations voiced their appreciation which could also lead to the risk perception being low. Note worthy is the fact that deforestation and littering on land were the top two highest perceived risks out of the ten environmental harms presented to residents . Neither deforestation nor littering on land fit in the frame of involuntary and catastrophic, as both are man - made and voluntary. A majority (93%, n = 197, M = 6.30, SD = 1.309) of residents felt that environmental harms are unacceptable and need to be stopped while also accepting that there are environmental harms and the justifications to manage th ose harms (79%, n = 166, M = 5.78, SD = 1.59). This is extremely important and could help the MTA in reduce perceived and assessed insecurity. Based on data collected as part of this thesis, more than 9 out of 10 residents felt that environmental harms wer e unacceptable. However, just driving around the MTA, one witnesses constant littering, trash fires, pollution, and other environmental crimes. There is a disconnect between the opinions of the residents and their actions which could be due to social desir ability bias and wanting to not be perceived as saying the wrong answer (Grimm, 2010). However, there could be other causes of this such as a l ack of support felt by the residents from the local and national government. In unrecorded conversations, residents explained that there is nowhere to put the trash and there is ties, and we have place is on the ground and out the car window. There is an opportunity increase governmental support in the MTA. 78 3. 5 . 6 . Littering Perceptions of litter and littering behavior are important to und erstand because most times the populations that are littering the most are part of and close to important conservation sites (Carmi, 2019). Also, littering that does not directly happen in a certain area can affect other areas because of wind and water mov ements (Watts et al., 2017). Behaviorally, littering usually has a negative connotation while being antisocial, unhealthy, and unpleasant to observe (Kort et al., 2008; Carmi, 2019). Litter and the act of littering have obvious health effects such as broke n glass in the streets and public areas leading to cuts and infections, while the mix of material in food littering can lead to disease and bacteria being spread (Carmi, 2019). Littering also can reduce public appeal, potentially highly important in the MT A if the land is to be used for conservation areas, private game reserves, or other alternative opportunities for income. Last, and potentially most important in this context, is that littering can affect crime rates along with the ability to endanger and kill wildlife ( Barnes et al., 2009 ; Campbell et al., 2014 ; Carmi, 2019). Littering can affect crime rates in two major ways. First, because of the sight of the refuse, it announces that residents of an area will tolerate violations of the social order and will most likely not speak up and intercede to stop crime or conduct that goes against the law (Muñoz - Cadena et al., 2012; Carmi, 2019). Second, because of the unappealing and chaotic local environment, many people will stay inside of their dwellings furthering a lack of relationships with neighbors and personal ownership of pu blic places which can lead to loss of social control. Sometimes, these situations can inspire behavior leading to increased crime rates, with neighbors refusing to help preserve publicly held spaces in their community (Muñoz - Cadena et al., 2012; Carmi, 201 9). My results suggest that people who believe littering to be a large threat to their community perceive increased frequency of traditional crimes. These relationships could help reduce crime 79 rates and supporting interventions to crime reduction within t he MTA due to the correlation between littering and crime in the MTA. The global community needs to be made aware of threats like littering and other variables related to environmental in security. Awareness is the first step in combating and lessening envi ronmental in security in local communities to the global community. 3. 5 . 7. Poaching The areas surrounding conservation areas such as the MTA are poached heavily (Massé, 2019; Witter & Satterfield, 2019 ). Poaching has become a huge factor in the global criminal economy. Poaching is a phenomenon inadequately addressed by conservation biology alone in part investm ents, educational programs, public - Lebombo Conservancy, illustrate some aspects of the local dimensions of environmental in security ( International Anti - Poaching Foundation , n.d. ). In 2015, local villagers severely attacked two rangers while transporting alleged poachers to a holding cell. A history of distrust between rangers, villagers, and poachers helped fuel the violence (Massé, 2019). If policy makers do not take into account , the actual reality of situations and only take into account the situation as they perceive it, it will not take care of environmental security issues (Brookfield, 1969; Baird et al ., 2009) The human violence surrounding wildlife poaching helps illustrate the relationship between environmental and traditional forms of security. As seen in India and Botswana, state actors are creating policies, without integrating local perceptions, t hat have implications on environmental security, specifically around poaching (Lopes, 2014; Mogomotsi & Madigele, 2017). Shoot - to - kill policies are policies that allow for the use of deadly force by rangers and officers if a poacher is seen or does not coo perate in an incident. These policies are often considered an extreme form of 80 governance (and often a human rights violation), but they seem to be more widely adopted over time (Messer, 2010; Lopes, 2014). These policies are not always viewed as good gover nance because they go above and beyond the traditional fines and jail terms and use lethal tactics to decrease poaching (Duffy et al., 2019). Such types of policies continue to be implemented though because they can generate specific conservation outcomes. But what if these policies do not get at the root of why environmental insecurity/poaching is occurring? Poaching in the MTA is a complex problem to address . T his being a case study with only one year of data does not mean this data is representative of poaching everywhere. However, in my research , there were factors such as age, children living in the household, and land ownership that played a large role in poaching pe rceptions and could be a jumping off point. Younger MTA residents showed less concern for the harm that poaching was having on their community as well as perceiving the frequency of poaching to be lower overall when compared with the older generation. Amon g study participants, h aving more children in a household and owning land also decreased the perception that poaching was harming the community. I nterventions in the MTA could be directed towards a younger generation. Many MTA residents stated that they wo uld like to own their own business. There are potential connections between anti - poaching, conservation, and the surrounding game reserves in which younger MTA residents could take advantage of. Education on the possibility of ecotourism and other related business endeavors could lessen the appeal to poach. Poaching is lucrative; however, it is extremely dangerous and not a reliable, steady source of income. In the future , research could investigate a more in depth look at the variables and work towards sol utions that could be beneficial to the wildlife as well as the MTA residents . Further research could include looking specifically at individual effects within the MTA to see how they really affect poaching and poaching rates in the MTA. 81 3. 8 CONCLUSION Environmental in security in the MTA is a is a multifaceted and interconnected concept. It influences and is influenced by other forms of in security. However, it is not significantly affected by individual factors such as village location. Deforestation, li ttering, and drought all contributed to increased risk perception and need of interventions. Gender predicted very few differences regarding environmental in security and was also insignificant in most measurements taken other than water in security. Nature myth perceptions could influence willingness to take part in interventions, while trust needs to be worked on and cultivated in the MTA for those interventions to become plausible. P oaching frequency is significantly affected by village location and should be looked into further in conjunction with crime statistics. Lastly, a ge, children in the household, and ethnicity influenced perceptions that poaching threatened the local community. Environmental in security is extremely interconnected with ot her forms of in security and countless factors affect and are affected by it. There is an opportunity to conduct a broad study of environmental in security that includes local perceptions , along with the assistance of other viewpoints to get the full picture. Within my research, the theme of interconnectedness emerged regarding environmental in security. These themes included food, water, trust, poaching, and crime (traditional and environ mental). Within these subunits of environmental in security, multiple demographic factors influenced risk perception associated with each subunit. These included age, number of children within a household, biological sex, if a person was currently employed (job security), ownership of land, ethnicity, and what village they lived in and where this was located compared to certain landmarks such as Kruger National Park. We should therefore look at insecurity as both individual components and collectively to get the full picture of environmental in security. Looking at 82 securities individually, they can be assessed differently, providing a perspective to potential solutions and intervention creations. When taken as a single entity, we can analyze variables to see i f individual factors are affecting each type of in security, which might affect change on another i nsecurity threat positively. I base all the possibilities of ideas and interventions presented on risk perceptions and questions remain that need to be empiri cally studied further by the scientific community, taking into account the local perspective. Local communities are impacted strongly by securitization policies (Balzacq et al., 2016; Gore et al., 2016). Securitization is when an issue is understood not only as a political subject and talking point, but as a threat to a referent object, while this politicization can sometimes justify the use of extreme measures on the beh alf of national security (Scott, 2012; Taureck, 2006). There is insufficient understanding about perceptions of these local communities who experience insecurity and who are directly impacted by policies and programs designed to reduce insecurity. Previous studies have primarily looked at the relationships between land use and various factors such as economic constraints (Baird et al., 2009). While this is useful, decision makers need local perceptions to aid in arbitrating the influence these factors have on decision makers (Baird et al., 2009). - makers operating in an environment base their decisions on the environment as they perceive it, not as it is. The action resulting from (Brookfield, 1969; Baird et al., 2009). This statement rings true today and this lack of understanding can inhibit design and evaluation of effective interventions designed to help communities affected by environmental insecurity (Gore et al., 2016). Socio demographic information will aid local perspectives ( e.g. age, employment status, gender, income). Global and regional perspectives can overshadow local 83 perspectives and can make creating policy to help in insecurity lessening even more difficult (Gore et al., 2016). This research is a first step in understanding how local perspectives interact with global policy and interventions to help with the growing environmental insecurity globally. 84 APPENDIX 85 APPENDIX Local Risk Perceptions Questionnaire 2019: Mnisi Tribal Authority, Mpumalanga, South Africa Is verbal consent granted? Warm Up/Introduction (This first set of questions are examples of the types of questions I will be using.) On a scale of 1 to 7, with 1 being completely disagree and 7 being completely agree, please tell me how much you agree with the following statement. Morogo should be served at all meals. My favorite sport is fútbol (soccer). M nisi Tribal Authority (This set of questions asks your personal experience within local Mnisi Tribal Authority society and culture. Please tell me the extent to which you agree with each statement pertaining to the last full year which is 365 days. Nature means the environment, the Earth, or the living world and includes people.) My ideal job would be my own business. It is important to preserve our customs and cultural heritage. Important questions for our society should not be decided by experts but by th e people. Having order in my community is unpopular. I worry about conflicts between social groups in my community. In a family, adults and children should have the same influence in decisions. It is important to me that in the case of important decisions in my family that everyone is asked. We have to accept the limits in our life if we want or not. There is no use in doing things for other people -- you only get it in the neck in the long run. Institutions (an established organization or corporation (such as a bank or university) especially of a public character) should be organized in a way that everybody can influence important decisions. I don't join clubs of any kind. The freedom of the individual should not be limited for reasons of preventing crime. T he police should have the right to listen to private conversations when investigating crime. When I have problems, I solve them on my own. An intact (where both biological parents are present in the home) family is the basis of a functioning society. I pre fer clear instructions from my superiors about what to do. If you don't currently have a superior, think about a time that you had a superior. For example: in school. Order in my community is an important virtue. I would not participate in civil action (A civil action is an action that is brought to enforce, redress or protect a private or civil right. It is a non - criminal litigation) groups because the ones in power do only allow what they like. I prefer tasks where I work something out on my own. Harm T houghts (The following questions ask how certain environmental harms compare to each other. Environmental harms are threats, risks, hazards, or chances. Environment is the natural world including nature, people, plants, animals, water, and all living thing s. Please think about the last full year when answering) 86 Harvesting of non - dry wood (all wood other than wood that has fallen due to natural causes) poses harms to the environment. Drought poses harms to the environment. Political crises' pose harm to my community. Poaching poses a threat to my local community. Poaching poses harms to the environment. Snaring poses harms to the environment. Snaring poses harm to my community. Please rank the following harms in order of least to most threatening within my community and the areas surrounding my community, with least threatening being #1 and most threatening being #10. Cattle Theft Development Drought Erosion Illegal Logging (Deforestation) Littering/Pollution of the Land Littering/Pollution of the Water Mosq uitoes (spread of disease) Overgrazing Poaching Harm Response 1 (People who are responsible have many ways in which they can go about managing harms to the environment, or nature. These questions ask your experience with different management reactions. P lease think about the last full year when answering.) I accept there are environmental harms and the justifications to manage those harms. Environmental harms are unacceptable and need to be stopped. I try not to know about environmental harms because ther e is nothing I can do about them. Environmental harms create new opportunities for creativity, innovation, and development. Harm Response 2 (This set of questions focuses on your experience with how different types of harm should be coped with. By cope, I mean respond in a systematic way. Please think of the last year when answering these questions.) Harms are best ignored (avoided). Harms are best deterred (stopped). Harms are best adapted to (modified). Harms are best welcomed (accepted). Nature Mythology (This set of questions focuses on your thoughts of the environment/nature. Please think about the last full year when answering.) The environment/nature always finds its way back to a balance. Small changes made by people have very big impacts on the environment/nature. The environment/nature forgives events to a certain point. The environment/nature is random. 87 Food Security (This set of questions focuses on the food that you and members of your family eat. By food, I mean grains, legumes, vegeta bles, meat and fish that you can cook. Please think about the last full year when answering.) I worry that my family may run out of food before I have money to buy food again. I worry that I may not be able to afford to buy adequate food. I wish I could bu y more food if I had more money. My family has run out of food because we do not have more money to buy food. I eat less than I want to because I do not have enough money to buy food. Have the children of your family, according to you, not had enough to ea t because you do not have enough money to buy food? Has your family ever eaten the same type of food for several consecutive days because you do not have enough money to buy different food? Do you have enough money to buy healthy and nutritious food for th e children of your family? Sometimes a person's body weight drops because of not eating enough. Has your body weight dropped in the last year because of the lack of food? Health Security (This set of questions focuses on your thoughts of health services a nd traditional medicines. Please think about the last full year when answering.) If someone in my community gets sick, they have reliable governmental medical support to rely on. I worry about becoming infected with HIV. The government provides the necess ary and needed health services to my community. The use of animals and animal parts is acceptable for use in traditional medicine practices. Traditional medicine is a reliable option to solving illness and medical issues. Water Security (This set of questions focuses on the water that you consume as well as the water you use for crop production and non - drinking purposes. Please think about the last full year when answering.) I worry about having a reliable supply of drinking water. I worry about havin g a reliable source of water used for non - drinking purposes. I worry about potential human - wildlife conflict at local water sources. I worry about having enough water for my personal crops. I worry about my community having enough water for their crops. I worry about potential wildlife contamination at local water sources. I worry about how healthy the rivers are. Environmental Security (This set of questions focuses on your experiences with natural resources as well as environmental factors that that affe ct your daily lives. Please think about the last full year when answering.) I worry about having a reliable source of natural resources to live. I worry about environmental crime in my community. I worry about having healthy land to grow food on. I worry a bout my ability to recover from drought. I have a reliable source of energy. I can rely on my government to provide continuous, reliable energy. I have reliable protection from disease. 88 My community believes we can rely on our national government. I have r eliable natural resources to live. The Mnisi Tribal Authority, as a whole, is good at protecting nature. I have a reliable way of disposing of trash legally. I worry about deforestation (the illegal taking of wood) having a negative impact on my communit y. I worry about pollution (littering/trash) having a negative impact on my community. I have a reliable way of acquiring energy for my household other than wood burning. Education and Employment (This set of questions focuses on your thoughts on educati onal opportunities and employment opportunities. Please think about the last full year when answering. The surrounding wildlife institutions provide my community opportunities for employment. I worry about either keeping my job or losing my job. I feel well prepared to enter the workforce. The educational opportunities provided to my children prepare them well for eventual employment. I have opportunities for legal employment. I have the opportunity to advance my education. Trust (This set of questions looks at your thoughts on trust within your community and surrounding areas. Please think about the last full year when answering.) A person is better off if he/she doesn't trust anyone. I have a trustworthy national government. I trust that my l ocal police acts with integrity. I worry about corruption in my community. I have a trustworthy local government. I trust the rangers in the surrounding protected areas and game reserves. Traditional Crime Perspective (These next questions focus on your perspective about traditional crimes in your community. These questions focus on your community and not you specifically. Please think about the last full year when answering.) I worry about crime in my community. Traditional crime, for example, theft and violence, in my community should be addressed prior to crime involving the environment. Traditional crime is more detrimental to my community when compared to environmental crime. I am concerned about assault in my community. According to SAPS, assault co nsists of unlawfully and intentionally applying force to the person of another; inspiring a belief in another person that force is immediately to be applied to him or her. I am concerned about burglary in my community. Burglary is the criminal offense of b reaking and entering a building illegally for the purpose of committing a crime. I am concerned about drug related crimes in my community. I am concerned about rape in my community. According to SAPS, rape consists of intentional unlawful sexual intercours e with a woman without her consent. I am concerned about sexual assault in my community. Sexual assault is the illegal sexual contact that usually involves force upon a person without consent or is inflicted upon a person 89 who is incapable of giving consent (as because of age or physical or mental incapacity) or who places the assailant (such as a doctor) in a position of trust or authority I am concerned about stock - theft in my community. According to SAPS, theft consists of the unlawful appropriation of mo veable corporeal property belonging to another with intent to deprive the owner permanently of the property. I am concerned about murder in my community. According to SAPS, murder is the unlawful and intentional killing of a human being. Activities (The f ollowing questions ask your experience with how often the following activities happen in this area. We will be using a scale of 1 to 7. 1 being absolutely none and 7 being every day. Be assured I am not asking how much or whether YOU do these activities, simply how much you think these activities are happening here. I am not interested in self - incrimination and I AM NOT law enforcement. Please think about the last year when answering these questions.) How much cattle theft happens in my community? How mu ch illegal taking of wood happens in my community? How much littering, on the land, happens in my community? How much littering, in the water, happens in my community? How much elephant poaching happens in the area surrounding my community? How much hyena poaching happens in the area surrounding my community? How much impala poaching happens in the area surrounding my community? How much leopard poaching happens in th e area surrounding my community? How much lion poaching happens in the area surrounding my community? How much pangolin poaching happens in the area surrounding my community? How much python poaching happens in the area surrounding my community? How mu ch rhino poaching happens in the area surrounding my community? How much vulture poaching happens in the area surrounding my community? How much wild dog poaching happens in the area surrounding my community? Conclusion (These final questions focus on your background. This information will be private and will NEVER be associated with your responses.) Age: Primary Job: Years lived in area: Ethnicity/Tribe (Please list all): Owner of Land (yes or no)? Size of Land (km) Sex: [0 = male] [1= female] Number o f children currently living in household: Township/Village/Area: Other Comments: 90 Full Questionnaire (Tsonga) Mpfumelelo wo vulavula wu nyikiwile: Masungulo (ntlawa wa swivutiso leswo sungula I xikombiso xa swivutiso leswi ndzinga ta swi tirhisa eka nkambelo - vutivi (interview) leyi) kombela undzi byela leswaku u pfumel elana ku fikela kwini na switetimendhe leswi ngata landzela. Ntlangu lowu ndzi wu rhandzaka ngopfu I bolo ya milenge. Vuhosi bya ka Mnisi (Ntlawa lowu wa swivutiso wu kambisisa matitwelo Ndzi kombela u ndzi byela leswaku u pfumelelana ku fikela kwihi ni switetimendhe leswi landzelaka hinkwaswo. Switetimendhe leswi landzelaka swi kongomisiwe ek a lembe leri kumekaka laha misaveni ku katsa na vanhu. Swina nkoka ku hlayisa ndlela ya xinto yo en dla swilo na ndhavuko wa hina. Swivutiso swa nkoka leswi kongomaneke na rixaka ra hina aswi fanelanga ku bohiwa hivanhu la vanga na ntokoto. Swifanele ku boiwa hi vini va ndzhawu. Ku va swilo swi famba kahle emugangeni wa wena aswi tolovelekanga. Ndza vile risiwa hi ntlimbano lowu nga kona exikari ka ti nxaka - nxaka ta vanhu emugangeni wa mina. Endyamgwini, lavakulu ni lavatsongo vafanele ku va ni vutihlamuleri byo ringana eku tekeni ka swiboho. Swina nkoka eka mina leswaku endyangwini waka hina unwana ni unw ana a vutisiwa mavonelo ya yena loko swita ekutekeni ka swiboho swa nkoka. ni loko swi ngahi tsakisi. - hikuva loko nka rhi wu famba va to tshamela ku ku karhata. kota ku va xiphemu xo teka swiboho ehenhla ka swona. Andzi ngheneleli eka mintlawa yihi kumbe yihi. Ntshuxeko wa munhu aw u fanelanga wu pimiwa hikokwalaho ko ringesa ku hunguta vugevenga. Loko ndziri na ti nkingha ndzi ti ahlulela tona ndziri ndzexe. Ndyangu lowu khomaneke I masungulo ya rixaka leri tirhaka kahle/leri ngata kota ku tirha hi ndlela leyinene. Ndzi tsakela swileriso leswi nga erivaleni eka va rhangeri va mina hi leswi ndzi faneleke ku swi endla. (Loko unga ri na murhangeri ehleketa hinkarhi lowu awu ri na murhangeri, Xikombiso; exi kolweni.) Swina nkoka kuva swilo swi famba kahle emugangeni wa mina. 91 Andzinge ngheneleli xitereko, hikuva lava fambisaka tiko va endla ntsena ku rhandza ka vona. Ndzi tsakela mintiro leyi ndziti ahlulelaka swilo/swiphiqo ndziri ndzexe. Miehleketo yo onha (Swivutiso leswi landzelaka swikambisisa leswaku maonhelo yo karhi ya mbango ya yelana njhani.Ku onhiwa ka mbango i vuxungeti, vuchavisi, vunghozi kumbe ku teka machansi. Mbango I misava katsaka ku katsa vanhu, swihlahla, swiharhi, mati na swilo hinkwaswo leswi hanyaka. Ndzi kombela u ehleketa hi lembe leri hundzeke hinkwar o loko u hlamula swivutiso lesi landzelalaka) Ku rhotiwa ka tihunyi to tsakama swi xungeta ku onha mbango. Dyandza ri xungeta ku onha mbango. Tinkingha ta tipolitiki ti xungeta ku kavanyeka rihanyo e mugangeni wa mina. Ku hlota lokungariki nawini ku xunge ta rihanyo emugangeni wa mina. Ku hlotiwa ka swiharhi swingari enawini swi nga onha mbango. Ku rhiyiwa/phasiwa ka swiharhi swi nga onha mbango. Ku rhiyiwa/phasiwa ka swiharhi swi nga onha emugangeni wa mina. Kala tinkingha leti landzelaka u sungula hi let i ti nga ta nghozi swinene mugangeni wa wena wena na ti ndhawu leti nga ku suhi na wona. Leti nga chaviseki ngopfu ti nyike #1 leti chavisaka ngopfu ti nyike #10. Ku yiviwa ka tihomu. Nhluvuko Dyandza. Ku khukuriwa ka misava hi mpfula. Ku tsemeleriwa ka n hova/Minsinya. Ku lahliwa ka thyaka laha swinga fanelangiki/ ku thyakisiwa ka moya hi ku hisetela swilo. Xikombiso..moya lowu sukaka eti femeni. Vuvabyi bya Malaria lebyi kumekaka ka tinsuna. Ku rimiwa ka ndhawu leyi tlulaka mpimo. Ku hlotiwa ka swiharhi swingari enawini. Nhlamulo ya nxungeto #1 (Vanhu lava nga ni vutilamuleri lebyinene vani tindlela to tala to lawula ku vavisiwa ka mbango kumbe ntumbunuko. Swivutiso leswi swi kambisisa matitwelo ya wena hi vurangeri byo hambana hambana lebyi unga hlangana na byona. Ndzikombela u ehleketa hi lembe leri hundzeke hinkwaro loko u karhi u hlamula swivutiso leswi) Ndza pfumela leswaku swi kona leswi onhaka mbango , na tindlela to swi lawula tikona. Swionha mbango aswi amukeleki, swi fanele kusiveriwa. Ndza ringesa ku va ndzi nga tivi nchumu hi swilo leswi onhaka mbango hikuva andzi nge endli nchumu ku swi sivela. Swilo leswi onhaka mbango switisa kucinca, nhluvuko na tindlela to endla mintirho. 92 Nhamulo ya nxungeto #2 (swivutiso leswi landzelaka swi kongomane na matitwelo ya wena leswaku kunga endliwa yini hi minxungeto le yinga kona yo hambana - hambana.Loko ndzikuku nga endliwa yini ndzi ringesa ku hlamusela leswo; hi nga angula njhani hi xitepe - hixitepe? Leswi se ndzi nga vutisa hi minxungeto yo hambana - hambana eka swakudya, Ntumbunuko, ku hlayiseka ka wena na mati, upfumelelana ku fikela kwihi na switetimendhe leswi landzelaka? Swi nga antswa ngopfu loko minxunge to leyi yi nga tekeriwi enhlokweni. Swi nga antswa ngopfu loko minxungeto leyi yo herisiwa. Swi nga antswa ngopfu minxungeto leyi yo toloveriwa. Swi nga antswa ngopfu loko minxungeto leyi yo amukeriwa. Swivuriso swa ntumbunuko (Swivutiso leswi landzelaka swi langutisisa eka maehleketelelo ya wena hi mbango/ntumbunuko. Ndzi kombela u ehleketa hi lembe leri nga hundza hinkwaro loko u karhi u hlamula swivutiso leswi) Ku cinca ku tsongo loku ku endliwaka hi vanhu ku na swita - ndzhaku leswikulu eka ntumbunuko/mbango. Ntumbunuko/mbango a wu twisiseki. Ku tiyisiseka ka swakudya (swivutiso leswi landzelaka swi langutisisa swakudya leswi wena na va le ndyangwini wa wena mi dyaka swo na. Swakudya leswi swi katsa, tiboncisi, matsavu, nyama na tihlampfi leswi mi swi swekaka. Ndzi kombela u ehleketa hi lembe leri nga hundza hinkwaro loko u karhi u hlamula swivutiso leswi) Ndza vilerisiwa hileswaku ndyangu wa mina wunga heleriwa hi swakud ya ndzi ngase kuma mali Ndza vileririwa hileswaku swinga endleka ndzi nga swi koti ku xava swakudya swo ringana ndyangu wa mina. Andzita xava swakudya swo tala loko andziri mali yo tala nyana. Ndyangu wa mina wu Ndzi dya swakudya switsongo hikuva andzina mali yo ringanela yo xava swakudya. pfumaleka ka mali yo xava sw ko pfumaleka ka mali yo xava swakudya? u nyuhela ka munhu ka ehla hikuva va a nga dyi swakudya swo ringanela. Wunga va wa wena miri wu ehlile eka lembe leri nga undza hi kokwalaho ko pfumala swakudya? Ku tiyisiseka ka taRihanyo (swivutiso leswi landzelaka swilangutisisa maehleketelelo ya wena hi vukorhokeli bya swarihanyo na mimirhi ya xinto. Ndzi kombela u ehleketa hi lembe leri nga hundza hinkwaro loko u karhi u hlamula swivutiso leswi) 93 Loko munhu a vabya emugangeni wa mina, byi kona kukorhokeli bya mfumo bya rihanyo lebyi Ndza vilerisiwa leswaku ndzi nga tluleriwa/ngheneriwa hi vuvabyi bya HIV. Mfumo wu hi nyika kukorhokeli lebyi faneleke ni lebyi pfumalekaka e mugangeni lowu ndzi tshamaka ka wona. Ku tirhisiwa ka swiharhi na swirho swa swona eku endleni ka mirhi ya xinto s wa pfumeleleka emugangeni wa mina. Mimirhi ya xinto yi tshembhekile ku herisa mavabyi na tinkingha ta mimirhi. Ku tiyisiseka ka vukorkokeli bya mati (swivutiso leswi landzelaka swilangutisisa mati lawa u matirhisaka ku nwa no sweka na mati lawa u wa tirhi sweka. Ndzi kombela u ehleketa hi lembe leri nga hundza hinkwaro loko u karhi u hlamula swivutiso leswi) Ndza vilerisiwa hi ku kuma vukorhokeli bya mati yo nwa lebyi tshembhekeke. Ndza vilerisiwa hi ku kuma vukorhokeli bya Ndza vilerisiwa hi ku kavanyetana ka vanhu na ntumbunuko lokoswita eka timhaka ta mati. Ndza vilela loko ndzi hleketa leswaku ndzi ngaka ndzi nga vi na mati yo enela yo cheleta swibyariwa swa mina. Ndza vilela loko ndzi hleketa leswaku muganga wa hina wunga tshuka wu nga vi na mati yo enela yo cheleta swibwariwa. Ndza vilela loko ndzi hleketa leswaku swiharhi/ntumbunuko wu nga kuma mati lawa nga tengangiki/mati yoka manga basangiki ku suka eka vukorhokeri bya mati la ha mugangeni wa hina. Ndza vilerisiwa hi mabaselo/rihanyo ra minkova. Ku hlayiseka ka mbango (swivutiso leswi landzelaka swi lagnutisisa matitwelo ya wena hi wena masiku hinkwawo. Ndzi kombela u ehleketa hi lembe leri nga hundza hinkwaro loko u karhi u hlamula swivutiso leswi) Ndza vilela loko ndzi hleketa leswaku ndzi ngaka ndzi ngavi na switirhisiwa swa ntumbunuko leswi nga kotaka ku ndzi pfuna ku hanya. Ndza vilerisiwa hi swiendlo swo ka swi ngari enawini leswi onhaka ntumbunuko emugangeni wa mina. Ndza vilela loko ndzi hleketa leswaku ndzinga pfumala misava yo nona yo byala ka yona swakudya. Ndza vilerisiwa loko ndzi hleketa leswaku swi nga tshika swi ndzi tikela ku ya emahlweni na vutomi endzhaku ka dyandza. Ndzi na mphakelo wa gezi wo tshembheka. Mfumo wa mina wu tshembhekile ku ndzi nyika mphakelo wa gezi lowu nga kavanyetiweki minkarhi hi nkwayo. Ndzina nsivelo lowu tshembhekeke eka switsongwa - tsongwana. Muganga wa mina wa tshembha leswaku hinga langusela swo tala eka mfumo wa tiko ra hina. Ndzina switirhisiwa leswitsembhekeke swa ntumbunuko leswi ndzi pfunaka ku hanya. Vuhosi byaka Mnisi hi nkwabyo bya swi kota ku sirhelela ntumbunuko hindlela ya leyinene. 94 Ndzi na n dlela leyi tshembhekeke yo lahla thyaka ku ya hi nawu. Ndza vilerisiwa hi ku tsemeleriwa ka swihlala ( swinga ri enawini) hikuva swita tisa swita - ndzhaku swo ka swi ngari kahle emugangeni wa mina. Ndza vilerisiwa hi ku thyakisiwa/ ku lahleteriwa ka thyaka hi ndlela leyi nga amukelekeki, ku swi nga tisa swita - ndzhaku swo ka swi kari kahle emugangeni wa mina. Ndzina ndlela yo tshembheka yo tisa gezi endlwini ya mina handle ko tirhisa ndzilo(tihunyi). Dyondzo na Vuthori (swivutiso leswi landzelaka swi languti sisa miehleketo ya wena loko swita eka tidyaondzo dyondza na ti timhaka ta mintirho. Ndzi kombela u ehleketa hi lembe leri hundzeke hi nkwaro loko u karhi u hlamula swivutiso leswi) Swikolo swa ntumbunuko leswi nga ekusuhi na muganga wa mina swa hi pfuna hi mintirho ni dyondzo. Ndzi ti twa ndzi ti lulamiserile ku sungula ku tirha. Tidyondzo leti nyikiwaka vana va mina ti ta va pfuna no ku valulamisela ku sungula ku tirha kunga ri khale. Ndza tshemba leswaku ndzi ta tirha to tirha mintirho leyi nga enawini . Ndzi tona tindlela to yisa emahlweni tidyondzo tamina. Ku tshembheka (swivutiso leswi landzelaka swi langutisisa matitwelo ya wena hi vutshembheki lebyi nga kona emugangeni wa wena ni miganga leyi kumekaka eku suhi.Ndzi kombela u ehleketa hi lembe leri hundzeke loko ukarhi u hlamula) Swa antswa kuva munhu anga tshembhi munhu. Mfumo wa mina wu tshembhekile. Maphorisa ya le kusuhi na mina ya tirha hi ku tshembheka. Ndza vilerisiwa hi vu kungundzwana lebyi nga emugangeni wa mina. Mfumo wale kusuhi ( masipala) na mina wu tshembhekile. Ndzi tshembha valayisi va swiharhi na ntumbunuko (Rangers) lava tirhaka emintangeni leyi nga kusui na muganga wa mina. swi langutisisa m atitwelo ya wena hi vugevenga lebyi nga kona emugangeni wa wena. Swivutiso leswi swi kongomisiwile eka muganga wa wena hinkwawo hayi eka wena. Ndzi kombela u ehleketa hi lembe leri hundzeke loko ukarhi u hlamula) Ndza vilerisiwa hi vugevenga lebyinga emug angeni wa mina. Swina nkoka ngopfu ku lwisana na vu gevenga bya tiko hi nga se lwisana na vugevenga bya mbango/ntumbunuko emugangeni wa mina. Vugevenga bya tiko (Vukhamba, Ku onha) swi fanele ku ahluriwa hi ngase sungula ku ahlula ka onhiwa ka mbangu. Vuge venga byale tikweni byi onha swinene emugangeni wa mina ku tlula vugevenga bya mbango. Ndzi vilerisiwa swinene hi ku sukeriwa ka vanhu emugangeni wa mina. Hikuya hi nawu wa maphorisa ya laha afrika - to hambana - hambana. 95 Ndzivilerisiwa ngopfu hi ku tshoviwa etindlwini laha mugangeni wamina.Ku tshova I ku nghena etindlwini ta vanhu handle ka mpfumelelo wa vona hi xikongomelo xo yiva kumbe ku onha etindlwini ta vona. Ndzi vilerisiwa hiswi dzidziharisi emu gangeni wa mina Ndza vilerisiwa hi ku pfinyiwa ka vavasati emugangeni wa mina, Hikuya hi nawu wa maphorisa laha tikweni, ku pfinya I ku endla swa masangu ni wansati handle ka mpfumelelo wa yena. Ndza vilerisiwa hi ku vavisiwwa ka vanhu hi swa masangu. Ku v avisiwa hi swa masangu i kuva munhu a endla timhaka ta masangu handle ka mpfumelelo na munhu loyi anga swi koteki ku nyika mpfumelelo. Ndza vilerisiwa hi ku yiviwa ka timpahla e mugangeni wa mina, hikuya hi maphorisa ku yiviwa ka timpahla I ku teka nhundzu ya munhu anga ku nyikanga mpfumelelo. Ndza vilerisiwa hiku dlayiwa ka vanhu emugangeni wa mina.Hikuya hi nawu wa maphorisa Swiendlo (Swivutiso leswi landzelaka swi vutisisa hi kuya hi vutivi bya wena leswaku sw iendlo lesi swi humelela kangani emugangeni lowu. Hi ta tirhisa xikalo xo sukeka ka #1 ku fika ka #7.#1 yi hamusela leswaku aswi humeleli, #7 yihlamusela leswaku swihumelela masiku hinkwawo. Ndza tiyisisa leswaku andzi vutisi kumbe kuhlamusela leswaku wena wa endla swiendlo leswi ndzinga taswi vutisa. Ndzi vutisa leswaku u ehleketa leswaku swiendlo leswi swi nga va swi humelela kangani emugangeni wa wena? Andzi lavi kutiva hi nawu lowu u wu tluleke/tlulaka andzi tirhi ku bohisa milawu. Ndzi kombela u hleket a hi lembe leri hundzeke loko u hlamula swivutiso leswi.) Ku yiviwa ka tihomu emugangeni wa mina ku humelela kangani? Kurhoteriwa ka tihunyi swingari enawini swi humelela kangani emugangeni wa mina? Ku thyakisiwa ka misava hiku lahleteriwa ka thyaka swihu melela ku fikela kwini emugangeni wa mina? Ku thyakisiwa ka mati swi humelela ku fikela kwini emugangeni wa mina? Ku hlotiwa ka tindlopfu handle ka pfumelelo ku humelela kangani emintangeni leyi kumekaka kusuhi na muganga wa mina? Ku hlotiwa ka swipena handle ka mpfumelelo swi humelela kangani emintangeni leyi kumekaka kusuhi na muganga wa mina? Ku hlotiwa ka tinghala handle ka mpfumelelo swi humelela kangani emintangeni leyi kumekaka kusuhi na muganga wa mina? Ku hlotiwa ka tiyingwe handle ka mp fumelelo swi humelela kangani emintangeni leyi kumekaka kusuhi na muganga wa mina? Ku hlotiwa ka tihumba handle ka mpfumelelo swi humelela kangani emintangeti leyi leyi kumekaka kusuhi na muganga wamina? Ku hlotiwa ka tinyoka handle ka mpfumelelo swi humel ela kangani emintangeni leyi kumekaka kusuhi na muganga wa mina? Ku hlotiwa ka timhelembe handle ka mpfumelelo swi humelela kangani emintangeni leyi kumekaka kusuhi na muganga wa mina? Ku hlotiwa ka swinyenyana handle ka mpfumelelo swi humelela kangani emi ntangeni leyi kumekaka kusuhi na muganga wa mina? Ku hlotiwa ka timbyana ta nhova handle ka mpfumelelo swi humelela kangani emintangeni leyi kumekaka kusuhi na muganga wa mina? 96 Mahetelelo (swivutiso leswi swi langutisisa vuxoko - - xoko lebyi byi tava bya xihundla nakambe byi nge hlanganisiwi na tinhlamulo ta wena) Malembe : Utirhayini/Ntirho wa wena : I Malembe mangani u tshama emugangeni lowu : Rixaka : Xiave/ Misava yi kule ku fika kwihi ?(KM) : Vununa/Vusati : (0 =Wanua) (1= Wansati) : Nomboro ya vana la va ha tshamaka kaya ka wena : Vito ra Muganga/Tiko ra wena: 97 Crime: I worry about crime in my community Traditional crime, for example, theft and violence, in my community should be addressed prior to crime involving the environment. Traditional crime is more detrimental to my community when compared to environmental cri me. I am concerned about assault in my community. I am concerned about burglary in my community. I am concerned about drug related crimes in my community. I am concerned about rape in my community. I am concerned about sexual assault in my community. I am concerned about stock - theft in my community. I am concerned about murder in my community. Education and Employment: The surrounding wildlife institutions provide my community opportunities for employment I feel well prepared to enter the workfo rce The educational opportunities provided to my children prepare them well for eventual employment. I have opportunities for legal employment I have the opportunity to advance my education. Environmental: I worry about having a reliable source of nat ural resources to live. I worry about environmental crime in my community. I worry about having healthy land to grow food on. I worry about my ability to recover from drought. I have a reliable source of energy. I have reliable natural resources to liv e. I worry about deforestation having a negative impact on my community. I worry about pollution (littering/trash) having a negative impact on my community. I have a reliable way of acquiring energy for my household other than wood burning. Food: I worry that my family may run out of food before I have money to buy food again. I worry that I may not be able to afford to buy adequate food. I wish I could by more food if I had more money. My family has run out of food because we do not have more money to buy food. I eat less than I want to because I do not have enough money to buy food. Poaching: Elephant poaching Hyena poaching 98 Impala poaching Leopard poac hing Lion poaching Pangolin poaching Python poaching Rhino poaching Vulture poaching Wild dog poaching Trust: I have a trustworthy national government. I trust that my local police acts with integrity I have a trustworthy local government I trust the rangers in the surrounding protected areas and game preserves. Water: I worry about having a reliable supply of drinking water. I worry about having a r eliable source of water used for non - drinking purposes. I worry about potential human - wildlife conflict at local water sources. I worry about having enough water for my personal crops. I worry about my community having enough water for their crops. I wor ry about potential wildlife contamination at local water sources. I worry about how healthy rivers are. Table 2 1 analysis of the Mnisi Tribal Authority, Mpumalanga, South Afri ca (May July 2019) Index Alpha # of Questions Crime .884 10 Education and Employment .661 5 Environmental .617 9 Food .860 5 Poaching .901 10 Trust .615 5 Water .833 7 99 Ethics Statement (English) (Fill in) reviewed and approved all methods and procedures used in this research. Prior to all participation during the study, all participants were read an introduction that p resented a general synopsis of the research and asked for verbal consent. This was available in either English or Tsonga depending on the request of the potential participant. The statement read as follows, name is (fill in with current interviewer nam Wildlife College. I would like to talk to you about your opinions about the Mnisi Tribal Authority and the South African environm ent because you live in an area of South Africa that is near a world - renowned conservation area and multiple protected areas, some of which are used by people for their daily lives. Sometimes the environment is conserved as a park. I am trying to understan d what local people think about the environment and human activities that can affect the human - environment relationships to improve the relationship for people and the environment. There are no wrong answers to the questions that I will ask. Your participa tion will help researchers understand the relationship between environmental security, natural resource use, and the lives of local people. Results from this study will be summarized in a report and presented in person or electronically to the Mnisi Tribal Authority, Southern African Wildlife College, and Michigan State University with the goal to help the lives of local people and wild animals. The researcher that I work for, works at a university in the United States that sets rules about how I do my res earch. Some of these rules are that personal information such as your name will never be associated with your responses. Also, the information you share with me is private 100 and under your control. I will only give your interview a number. I will take any in formation you are willing to share with me back to my university and study the entire group of interviews I obtain, as opposed to individual interviews. The location of this village will not be named in association with your name. The money to support this study comes from their university, Michigan State University; they support international sustainable development science. You may choose not to participate in the interview at any time. You may also choose to not answer a particular question of the inter view. If you do not understand the question, please ask and I will be happy to explain in greater detail. You must be at least 18 years of age to participate in this interview. By saying "Yes I understand" you are telling me that you are at least 18 years of age and want to participate. The entire interview should take about 30 minutes of verbally consent to participate in the study before data collection comm enced. 101 Research Questionnaire Introduction in English South Africa Mnisi Tribal Authority Research June/July 2019 the Southern African Wildlife College. I would like to talk to you about your opinions about the Mnisi Tribal Authority and the South African environment because you live in an area of South Africa that is near a world - renowned conservation area and multip le protected areas, some of which are used by people for their daily lives. Sometimes the environment is conserved as a park. I am trying to understand what local people think about the environment and human activities that can affect the human - environment relationships to improve the relationship for people and the environment. There are no wrong answers to the questions that I will ask. Your participation will help researchers understand the relationship between environmental security, natural resource us e, and the lives of local people. Results from this study will be summarized in a report and presented in person or electronically to the Mnisi Tribal Authority, Southern African Wildlife College, and Michigan State University with the goal to help the liv es of local people and wild animals. The researcher that I work for, works at a university in the United States that sets rules about how I do my research. Some of these rules are that personal information such as your name will never be associated with y our responses. Also, the information you share with me is private and under your control. I will only give your interview a number. I will take any information you are willing to share with me back to my university and study the entire group of interviews I obtain, as opposed to individual interviews. The location of this village will not be named in 102 association with your name. The money to support this study comes from their university, Michigan State University; they support international sustainable deve lopment science. You may choose not to participate in the interview at any time. You may also choose to not answer a particular question of the interview. If you do not understand the question, please ask and I will be happy to explain in greater detail. You must be at least 18 years of age to participate in this interview. By saying "Yes I understand" you are telling me that you are at least 18 years of age and want to participate. The entire interview should take about 30 minutes of your time. Do you hav e any questions before we get started? 103 Research Questionnaire Introduction in Tsonga Ndzavisiso lowu kongomisiweke eka Vuhosi Byaka Mnisi eAfrika Dzonga Khotavuxika/Mawuwani 2019. eMICHIGAN STATE UNIVERSITY .Hina vambirhi hi tirhisana na Southern African Wildlife byaka Mnisi na ndzhawu ya Africa Dzonga, hikuva mitsham a emugangeni kumbe eka xiphemu xa Afrika - Dzonga lexi nga ekusuhi na ntanga/mintanga leyi tivekaka misava hinkwayo hi ku ango wu hlayisiwa hindlela yo hundzuriwa ntanga lowu sirheleriweke. Ndzi ringeta ku twisisa leswaku vanhu lava tshamaka eka ndzhawu leyi va ehleketa yini hi mbango na swiendlo swa vanhu leswi swi kanganyisaka vuxaka exikarhi ka vanhu na mbango, leswi ndz i swi endlela ku kota ku kuma tindlela to antswisa vuxaka exikarhi ka vanhu na mbango. Akuna tinhlamulo to ka ti ngari tona eka swivutiso leswi ndzingata swi vutisa. Ku nghenelela ka wena swita pfuna valavisisi ku twisisa vuxaka exikarhi ka kuhlayisa mban go, ku tirhisiwa ka switirhisiwa leswi hi swi kumaka eka ntumbunuko na vutomi bya vanhu lava hanyaka eka muganga lowu. Mbuyelo wa ndzavisiso lowu wuta komisiwa eka xiviko wu tlhela wu nyikiwa Vuhosi byaka Mnisi ,Southern African Wildlife College na Yunivh esithi ya Michigan. Xiviko lexi xita tisiwa Kunene eka vanhu lava xa ndzavisiso na xiviko iku pfuna vanhu lava hanyaka eka ndzhawu leyi na Swiharhi. Yunivhesiti ley i ndzi tirhaka eka yona eUnited States yi ndzi vekele milawu leyi ndzi faneleke ku yi landzelela loko ndzi karhi ndzi endla xiviko lexi. Yinwana ya milawu leyi hi leswaku 104 vuxoko - xoko bya wena byo fana na mavito ndzi nga byi paluxi eka tinhlamulo ta wena, na vuxokoxoko lebyi unga ta ndzi nyika byona byi ta va xihundla byi thlela byi tirhisiwa hi leswi wena u swi lavisaka xi swona. Ndzi ta nyika ntsena nkambelo - vutivi (interview) ya wena nomboro. Ndzi ta thlelela na vuxokoxoko hinkwabyo lebyi u unga ta ndzi nyika byona eYunivhesithi ya Michigan laha ndzi ngata fika ndzi langutisisa vuxoko - xoko hinkwabyo lebyi - xoko bya munhu - wihi.Mali leyi seketelaka ndzavisiso lowu yi huma eYunivhesithi ya mina kunga Michigan State University;Yunivesithi ya Michigan yi seketela ku antswisiwa ka sayense leyi pfunaka nhluvuko wa misava hinkwayo. Unga hlawula ku ka unga ha vi xiphemu xa ndzavis iso lowu nkarhi wihi na wihi.Unga hlawula ku ka u nga hlamuli swinwana swivutiso swa ndzavisiso lowu. Loko xivutiso unga xi twisisi ndzi kombela u ndzi byela ndzi ta tsakela ngopfu kuku hlamusela xona hi vuenti. U boheka ku vana Khume - nhungu(18) wa malembe - nhungu wa malembe kumbe ku tlurisa na swona u lava ku nghenelela eka ndzavisiso lowu. Kuva u hlamula swivutiso leswi hinkwaswo swi yi ta te ka kwalomu ka Makume Ntlhanu (25) wa ti minetse ta nkarhi wa wena. Una swivutiso hingase sungula? 105 Likert - Type Scale 1. Absolutely None/Never 2. Rarely 3. Occasionally 4. Not Sure 5. Frequently 6. Very Frequently 7. Every Day Environmental Harms Likert - Type Scale 1. Least Threatening 10. Most Threatening 106 REFERENCES 107 REFERENCES Agarwal, B. (2018). Gender equality, food security and the sustainable development goals. Current Opinion in Environmental Sustainability , 34 , 26 32. https://doi.org/10.1016/j.cosust.2018.07.002 Agrawal, A. (2001). State formation in community spaces? Dec entralization of control over forests in the Kumaon Himalaya, India. Journal of Asian Studies , 9 - 40. taxation in Kenya, Tanzania, Uganda, and South Africa . World Development , 64 (March 2013), 828 842. https://doi.org/10.1016/j.worlddev.2014.07.006 Almanie, T., Mirza, R., & Lor, E. (2015). Crime Prediction Based on Crime Types and Using Spatial and Temporal Criminal Hotspots. International Journal of Data Mi ning & Knowledge Management Process , 5 (4), 01 19. https://doi.org/10.5121/ijdkp.2015.5401 Anastas, J. W. (1999). Research design for social work and the human services . New York: Columbia University Press. Anderson, S. F., Kelley, K., & Maxwell, S. E. (2017). Sample - Size Planning for More Accurate Statistical Power: A Method Adjusting Sample Effect Sizes for Publication Bias and Uncertainty. Psychological Science , 28 (11), 1547 1562. https://doi.org/10.1177/0 956797617723724 Ansar, A., Flyvbjerg, B., Budzier , A., & Lunn, D. (2014). Should we build more large dams? The actual costs of hydropower megaproject development. Energy Policy , 69 , 43 56. https://doi.org/10.1016/j.enpol.2013.10.069 Askvik, S. (2008). Trust in the post - apartheid government of South Afri ca: The roles of identity and policy performance. Commonwealth and Comparative Politics , 46 (4), 516 539. https://doi.org/10.1080/14662040802461257 Ayling , J. (2013). What Sustains Wildlife Crime? Rhino Horn Trading and the Resilience of Criminal Networks. Journal of International Wildlife Law and Policy , 16 (1), 57 80. https://doi.org/10.1080/13880292.2013.764776 Aziz, N., Nisar, Q. A., Koondhar, M. A., Me empowerment and food security nexus in rural areas of Azad Jammu & Kashmir, Pakistan: By giving consideration to sense of land entitlement and infrastructural facilities. Land Use Policy , 94 . https://doi.o rg/10.1016/j.landusepol.2020.104529 South Africa: Policy implication for drought risk reduction. International Journal of Disaster Risk Reduction , 20 (October), 39 50. https://doi.org/10.1016/j.ijdrr.2016.10.007 108 Baird, T. D., Leslie, P. W., & McCabe, J. T. (2009). The effect of wildlife conservation on local perceptions of risk and behavioral response. Human Ecology , 37 (4), 463 474. https://doi.org/10.1007/s10745 - 009 - 9264 - z Baiyegunhi, L. J. S., & Makwangudze, K. E. (2013). Home Gardening and Food Security Status of HIV/AIDS Affected Households in Mpophomeni, KwaZulu - Natal Province, South Africa. Journal of Human Ecology , 44 (1), 1 8. https://doi.org/10.1080/09709274.2013.11906637 Bakari, S., & Ahmadi, A. (2018). Why is South Africa Still a Developing Country? International Academic Journal of Economics , 05 (02), 1 19. https://doi.org/10.9756/iaje/v5i2/181001 P., & Villa, F. (2019). Human dependence on natural resources in rapidly urbanising South African regions. Environmental Research Letters , 14 (4). https://doi.org/10.1088/1748 - 9326/aafe43 isited: theory and cases. International Relations , 30 (4), 494 531. https://doi.org/10.1177/0047117815596590 Barnes, D. K. A., Galgani, F., Thompson, R. C., & Barlaz , M. (2009). Accumulation and fragmentation of plastic debris in global environments. Philosophical Transactions of the Royal Society B: Biological Sciences , 364 (1526), 1985 1998. https://doi.org/10.1098/rstb.2008.0205 Barnett, J. (2020). Environmental Se curity. International Encyclopedia of Human Geography , 247 251. https://doi.org / 10.1016/b978 - 0 - 08 - 102295 - 5.10789 - 9 Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting Linear Mixed - Effects Models Using lme4. Journal of Statistical Software , 67 (1). https://doi.org/10.18637/jss.v067.i01 Bennett, N. J., Roth, R., Klain, S. C., Chan, K., Christie, P., Clark, D. A., Cullman, G., Curran, D., Durbin, T. J., Epstein, G., Greenberg, A., Nelson, M. P., Sandlos, J., Stedman, R., Teel, T. L., Thomas, R., Veríssimo, D., & Wyborn, C. (2017). Conservation social science: Understanding and integrating human dimensions to improve conservation. Biological Conservation , 205 , 93 108. https://doi.org/10.1016/j.biocon.2016.10.006 Berrian, A. M., van Rooyen, J., Martínez - López, B., Knobel, D., Simpson, G. J. G., Wilkes, M. S., & Conrad, P. A. (2016). One Health profile of a community at the wildlife - domestic animal interface, Mpumalanga, South Africa. Preventive Veterinary Medicine , 130 , 119 128. https://doi.org/10.1016/j.prevetmed.2016.06.007 Bhaduri, A., Bogardi, J., Siddiqi, A., Voigt, H., Vörösmarty, C., Pahl - Wostl , C., Bunn, S. E., Shrivastava, P., Lawford, R., Foster, S., Kremer, H., Renaud, F. G., Bruns, A., & Osuna, V. R. (2016). Achieving sustainable development goals from a water perspective. Frontiers in Environmental Science , 4 (OCT). https://doi.org/10.3389/ fenvs.2016.00064 109 Bhatt, D. P., & Dhakal, T. N. (2018). Effectiveness of Ecotourism: A case of Chitwan National Park. Journal of Advanced Academic Research , 4 (1), 136 141. https://doi.org/10.3126/jaar.v4i1.19527 Bhattarai, B., Beilin, R., & Ford, R. (2015 ). Gender, Agrobiodiversity, and Climate Change: A Study of Adaptation Practices in the Nepal Himalayas. World Development , 70 , 122 132. https://doi.org/10.1016/j.worlddev.2015.01.003 Bogardi, J. J., Dudgeon, D., Lawford, R., Flinkerbusch, E., Meyn, A., P ahl - Wostl, C., Vielhauer, K., & Vörösmarty, C. (2012). Water security for a planet under pressure: Interconnected challenges of a changing world call for sustainable solutions. Current Opinion in Environmental Sustainability , 4 (1), 35 43. https://doi.org/1 0.1016/j.cosust.2011.12.002 Boholm, M., Möller , N., & Hansson, S. O. (2016). The Concepts of Risk, Safety, and Security: Applications in Everyday Language. Risk Analysis , 36 (2), 320 338. https://doi.org/10.1111/risa.12464 Box, G. E., & Cox, D. R. (1964). An analysis of transformations. Journal of the Royal Statistical Society: Series B (Methodological) , 26 (2), 211 - 243. Brauch H.G. (2015) Environmental and Energy Security: Conceptual Evolution and Potential Applications to European Cross - Border Energy Supply Infrastructure. In: Culshaw M., Osipov V., Booth S., Victorov A. (eds) Environmental Security of the European Cross - Border Energy Supply Infrastructure. NATO Science for Peace and Security Series C: Environmental Security. Springer, Dordrecht. https://doi.org/10.1007/978 - 94 - 017 - 9538 - 8_10 Brookfield, H. C. (1969). On the environment as perceived. Progress in geography , 1 , 51 - 80. Brown, J. D. (2000). What issues affect Likert - scale questionnaire formats. Shiken: JALT Testing & Evaluation SIG Newsletter , 4 (1) , 27 - 30 . Burger, A., & Silima, T. (20 06 ). Sampling and Sampling Design. Journal of Public Administration , 41 (3), 656 668. https://doi.org/10.1017/CBO9781107415324.004 Busby, J. (2018). Environmental security. The Oxford Handbook of International Security , 2001 , 47 1 486. https://doi.org/10.1093/oxfordhb/9780198777854.013.31 Campbell, M. L., Paterson de Heer, C., & Kinslow , A. (2014). Littering dynamics in a coastal industrial setting: The influence of non - resident populations. Marine Pollution Bulletin , 80 , 179 185. https://doi.org/10.1016/j.marpolbul.2014.01.015 Carlton, J. S., Mase, A. S., Knutson, C. L., Lemos, M. C., Haigh, T., Todey, D. P., & Prokopy, L. S. (2016). The effects of extreme drought on climate change beliefs, risk perceptions, and adaptation attitudes. Climatic Change , 135 (2), 211 226. https://doi.org/10.1007/s10584 - 015 - 1561 - 5 110 Carmi, N. (2019). On Social Distress, Littering and Nature Conservation: The Case of Jisr A - Zarka. Coastal Management , 47 (4), 347 361. https://doi.org/10.1080/08920753.2019.1598223 Carter, N. (2018). The Politics of the Environment: Ideas, Activism, Policy (3rd ed.). Cambridge, United Kingdom: Cambridge University Press. https://doi.org / 10.1017/9781108642163 Ceppi , S. L., & Nielsen, M. R. (2014). A comparative study on bushmeat consumption patterns in ten tribes in Tanzania. Tropical Conservation Science , 7 (2), 272 287. https://doi.org/10.1177/194008291400700208 Chakravarty, S., Ghosh, S. K., Suresh, C. P., Dey, A . N., & Shukla, G. (2012). G lobal P erspectives on S ustainable F orest M anagement (C. Akais Okia (ed.)). InTech. https://doi.org/10.5772/33342 Chakravarty, S., Ghosh, S. K., Suresh, C. P., Dey, A. N., & Shukla, G. (2012). G lobal P erspectives on S Sustainable F orest M anagement Deforestation: Causes, Effects and Control Strategies . https://doi.org/10.5772/33342 Chiutsi, S., & Saarinen, J. (2017). Local participation in transfrontier tourism: Case of Sengwe community in Great Limpopo Transfrontier Co nservation Area, Zimbabwe. Development Southern Africa , 34 (3), 260 275. https://doi.org/10.1080/0376835X.2016.1259987 Christie, P., Bennett, N. J., Gray, N. J., Aulani Wilhelm, T., Lewis, N., Parks, J., Ban, N. C., Gruby, R. L., Gordon, L., Day, J., Taei, S., & Friedlander, A. M. (2017). Why people matter in ocean governance: Incorporating human dimensions into large - scale marine protected areas. Marine Policy , 84 (September), 273 284. https://doi.org/10.1016/j.marpol.2017.08.002 Collins, A., Cox, C., & Pa mment, N. (2017). Culture, Conservation and Crime: Regulating Ivory Markets for Antiques and Crafts. Ecological Economics , 135 , 186 194. https://doi.org/10.1016/j.ecolecon.2017.01.018 Croasmun, J. T., & Ostrom, L. (2011). Using Likert - Type Scales in the S ocial Sciences. Journal of Adult Education , 40 (1), 19 22. https://doi.org/10.1007/s10640 - 011 - 9463 - 0 Dake, K. (1992). Myths of Nature: Culture and the Social Construction of Risk. Journal of Social Issues , 48 (4), 21 37. https://doi.org/10.1111/j.1540 - 4560.1992.tb01943.x De Bellaigue, C. (2020, June 18). The End of Tourism?. The Guardian . https://www.theguardian.com/travel/2020/jun/18/end - of - tourism - coronavirus - pandemic - travel - industry. Decker, D. J., Riley, S. J., & Sie mer, W. F. (2012). Human d imensions of wildlife management (2nd ed.). Baltimore, MD: Johns Hopkins University Press. Detraz , N. (2009). Environmental security and gender: Necessary shifts in an evolving debate. Security Studies , 18 (2), 345 369. https://doi.org/10.1080/09636410902899933 111 Dilger, M., Orasche, J., Zimmermann, R., Paur, H. R., Diabaté, S., & Weiss, C. (2016). Toxi city of wood smoke particles in human A549 lung epithelial cells: the role of PAHs, soot and zinc. Archives of Toxicology , 90 (12), 3029 3044. https://doi.org/10.1007/s00204 - 016 - 1659 - 1 Dillman, D. A., Smyth, J. D., & Christian, L. M. (2009). Internet, mail , and mixed - mode surveys: The tailored design method (3rd ed.). Hoboken, NJ: John Wiley & Sons. https://doi.org/10.1177/1049731509359779 Douglas, L. R., & Alie, K. (2014). High - value natural resources: Linking wildlife conservation to international conflict, insecurity, and development concerns. Biological Conservation,171 , 270 - 277. https:// doi:10.1016/j.biocon.2014.01.031 Douglas, M. (1978). Cultural Bias (Occasional Paper No. 35. Royal Anthropological Institute of Great Britain and Ireland). London: Royal Anthropological Institute . Douglas, M., & Wildavsky, A. (1983). Risk and culture: An essay on the selection of technological and environmental dangers . Univ of California Press. https://doi.org/10.1525/9780520907393 Du ffy, R., Massé, F., Smidt, E., Marijnen, E., Büscher, B., Verweijen, J., Ramutsindela, M., Simlai, T., Joanny, L., & Lunstrum, E. (2019). Why we must question the militarisation of conservation. Biological Conservation , 232 (September 2018), 66 73. https://doi.org/10.1016/j.biocon.2019.01.013 Ehsani, N., Vörösmarty, C. J., Fekete, B. M., & Stakhiv, E. Z. (2017). Reservoir operations under climate change: Storage capacity options to mitigate risk. Journal of Hydrology , 555 , 435 446. https://doi.org/1 0.1016/j.jhydrol.2017.09.008 Elliott, L. (2015). Human security/environmental security. Contemporary Politics , 21 (1), 11 24. https://doi.org/10.1080/13569775.2014.993905 Ezeonu, I. C., & Ezeonu, F. C. (2000). The environment and global security. Environm entalist , 20 (1), 41 48. https://doi.org/10.1023/A:1006651927333 Faber, J., & Fonseca, L. M. (2014). How sample size influences research outcomes. Dental Press Journal of Orthodontics , 19 (4), 27 29. https://doi.org/10.1590/2176 - 9451.19.4.027 - 029.ebo FAO, IFAD, UNICEF, WFP & WHO. (2019). The State of Food Security and Nutrition in the World 2019 . Safeguarding against economic slowdowns and downturns (Publication). Rome, FAO. Retrieved August 3, 2020, from http://www.fao.org/3/ca5162en/ca5162en.pdf#page=30 License: CC BY - NC - SA 3.0 IGO. Farbotko, C. (2018). Climate change and national security: an agenda for geography. Australian Geographer , 49 (2), 247 253. https://doi.org/10.1080/00049182.2017.1 385119 Fauvelle - Aymar, C. (1999). The political and tax capacity of government in developing countries. Kyklos , 52 (3), 391 413. https://doi.org/10.1111/j.1467 - 6435.1999.tb00224.x 112 Findlay, S., & Twine, W. (2018). Chiefs in a Democracy: A Case Study of the Regulating Firewood Harvesting in Post - Apartheid South Africa. Land , 7 (1), 35. https://doi.org/10.3390/land7010035 Fjeldstad , O. - H. (2004). What has trust got to do with it? Non - payment of service charges in local authorities in South Africa. Journal of Modern African Studies , 42 (4), 539 562. https://doi.org/10.1010/S0022278X04000394 Sustainable Development Goals: Guidelines from the Policy Coherence for Development movement. Sustainable Development , 26 (6), 765 771. https://doi.org/10.1002/sd.1745 Fox, J. (2015). Applied Regression Anal ysis and Generalized Linear Models (3rd ed.). SAGE Publications, Inc. Friedman, S. (1999). Agreeing to differ: African democracy, its obstacles and prospects. Social Research , 66 (3), 825 858. Frith, A. (2011). Census 2011. https://census2011.adrianfrith.com/. Fullman, N., Barber, R. M., Abajobir, A. A., Abate, K. H., Abbafati, C., Abbas, K. M., Abd - Allah, F., Abdulle, A. M., Abera, S. F., Aboyans, V., Abu - Raddad, L. J., Abu - Rmeileh , N. M. E., Adedeji, I. A., Adetokunboh, O., Afshin, A., Agrawal, A., Agrawal, S., Kiadaliri, A. A., basis of past trends of the health - related Sustainable Develop ment Goals in 188 countries: An analysis from the Global Burden of Disease Study 2016. The Lancet , 390 (10100), 1423 1459. https://doi.org/10.1016/S0140 - 6736(17)32336 - X Garbero, R. (2017, May 9). Criminologists have much to offer in examining wildlife crim es [web log]. https://blogs.biomedcentral.com/on - biology/2017/05/09/criminologists - have - much - to - offer - in - examining - wildlife - crimes/. Gerring, J. (2004). What Is a Case Study and What Is It Good for? Published by: American Political Science Association Wha t Is a Case Study and What Is It Good for? American Political Science Review , 98 (2), 341 354. Goodman, S. (n.d.). What is environmental security? [Interview by T. O'Callahan]. Retrieved 2020, from https://insights.som.yale.edu/insights/what - is - environment al - security. Gore, M. L., Hübschle, A., Botha, A. J., Coverdale, B. M., Garbett, R., Harrell, R. M., Krüeger, S., Mullinax, J. M., Olson, L. J., Ottinger, M. A., Robinson, H. S., Shaffer, L. J., Thompson, L. J., van den Heever, L., & Bowerman, W. W. (2020 ). A conservation criminology - based desk assessment of vulture poisoning in the Great Limpopo Transfrontier Conservation Area. Global Ecology and Conservation , 23 , 1 16. https://doi.org/10.1016/j.gecco.2020.e01076 113 Gore, M. L., Lute, M. L., Ratsimbazafy, J. H., & Rajaonson, A. (2016). Local Perspectives on Environmental Insecurity and Its Influence on Illegal Biodiversity Exploitation. Plos One , 11 (4). https://doi.org /1 0.1371/journal.pone.0150337 Gore, M. L., Ratsim bazafy, J. H., Rajaonson, A., & Kahler, J. (2016). Public perceptions of poaching risks in a biodiversity hotspot: Implications for wildlife trafficking interventions. Journal of Trafficking, Organized Crime and Security , 2 (1). https://www.researchgate.net /publication/305224010 Govender, L., Pillay, K., Siwela, M., Modi, A., & Mabhaudhi, T. (2016). Food and Nutrition Insecurity in Selected Rural Communities of KwaZulu - Natal, South Africa Linking Human Nutrition and Agriculture. International Journal of Env ironmental Research and Public Health , 14 (1), 17. https://doi.org / 10.3390/ijerph14010017 Graeger, N. (1996). Environmental Security? Journal of Peace Rese ar ch , 33 (1), 109 116. https://doi.org/10.1177%2F0022343396033001008 Grebmer , K. V., Bernstein, J., Patterson, F., Wiemers, M., Cheilleachair, R. N., Foley, C., . . . Helvetas. (2019). Global Hunger Index. The Challenge of Hunger and Climate Change (Publication). Dublin/Bonn: Helvetas. Grey, D., & Sadoff, C. W. (2007). Sink or Sw im? Water security for growth and development. Water Policy , 9 (6), 545 571. https://doi.org / 10.2166/wp.2007.021 Grimm, P. (2010). Social desirability bias. Wiley international encyclopedia of marketing . https://doi.org/10.1002/9781444316568.wiem02057 Gumede, T. K., & Nzama, A. T. (2019). Ecotourism as a mechanism for local economic development: The case of communities adjacent to the Oribi Gorge Nature Reserve, KwaZulu - Natal, South Africa. African Journal of Hospitality, Tourism and Leisure , 8 (4), 1 19 . Gurka, M. J., Edwards, L. J., Muller, K. E., & Kupper, L. L. (2006). Extending the Box - Cox transformation to the linear mixed model. Journal of the Royal Statistical Society. Series A: Statistics in Society , 169 (2), 273 288. https://doi.org/10.1111/j.14 67 - 985X.2005.00391.x . Hameeteman, E. (2013). Future Water (In)security: Facts, Figures, and Predictions (pp. 1 - 15, Rep.). Global Water Institute. Hanisch - Kirkbride, S. L., Rile, S. J., & Gore, M. L. (2013). Wildlife disease and risk perception. Journal of Wildlife Diseases , 49 (4), 841 849. https://doi.org/10.7589/2013 - 02 - 031 Hardt J.N. (2012) Critical Deconstruction of Environmental Security and Human Sec urity Concepts in the Anthropocene. In: Scheffran J., Brzoska M., Brauch H., Link P., Schilling J. (eds) Climate Change, Human Security and Violent Conflict. Hexagon Series on Human and Environmental Security and Peace, vol 8. Springer, Berlin, Heidelberg 114 Hariohay, K. M., Ranke, P. S., Fyumagwa, R. D., Kideghesho, J. R., & Røskaft, E. (2019). Drivers of conservation crimes in the Rungwa - Kizigo - Muhesi Game Reserves, Central Tanzania. Global Ecology and Conservation , 17 , e00522. https://doi.org/10.1016/j.gecco.2019.e00522 Harrison, H., Birks, M., Franklin, R., & Mills, J. (2017, January). Case study research: Foundations and methodological orientations. In Forum Qualitative Sozialforschung/Forum: Qualitative Social Research (Vol. 18, No. 1) . Henry, L. (2017). Understanding Food Insecurity Among College Students: Experience, motivation, and local solutions. Annals of Anthropological Practice , 41 (1), 6 19. https://doi.org/10.1111/napa.12108 Henry, L. (2017). Understanding Food Insecurity Among College Students: Experience, motivation, and local solutions. Annals of Anthropological Practice , 41 (1), 6 19. https://doi.org/10.1111/napa.12108 Hezri, A. A., & Hasan, M. N. (2006). Towards sustainab le development? The evolution of environmental policy in Malaysia. Natural Resources Forum , 30 (1), 37 50. https://doi.org/10.1111/j.1477 - 8947.2006.00156.x Holmatov, B., Lautze, J., Manthrithilake , H., & Makin, I. (2017). Water security for productive economies: Applying an assessment framework in southern Africa. Physics and Chemistry of the Earth , 100 , 258 269. https://doi.org/10.1016/j.pce.2017.04.007 Hoogensen, G., & Stuvøy, K. (2006). Gender, resistance and human security. Security Dialogue , 37 (2), 207 228. https://doi.org/10.1177/0967010606066436 Hough, P. (2018). Understanding global security (3rd ed.). Routledge Taylor & Francis Group. Houghton, R. A. (2012). Carbon emissions and the driv ers of deforestation and forest degradation in the tropics. Current Opinion in Environmental Sustainability , 4 (6), 597 603. https://doi.org/10.1016/j.cosust.2012.06.006 Huang, L., & Chen, S. F. (2020). What makes tree poachers give up? A case study of for estry law enforcement in Taiwan. Environmental Conservation , 47 (1), 67 73. https://doi.org/10.1017/S0376892919000377 IBM Corp. (2019). IBM SPSS Statistics for Mac . Armonk, NY: IBM Corp. Ikhlayel , M., & Nguyen, L. H. (2017). Integrated Approaches to Water Resource and Solid Waste Management for Sustainable Development. Sustainable Development , 25 (6), 467 481. https://doi.org/10.1002/sd.1683 Institute for Work and Health. (2008, August). Sample si ze and power . Research Excellence Advancing Employee Health. https://www.iwh.on.ca/what - researchers - mean - by/sample - size - and - power. 115 International Anti - Poaching Foundation. Greater Lebombo Conservancy (GLC) Mozambique . IAPF. https://www.iapf.org/greater - l ebombo - conservancy/. Johnson, D. R., & Creech, J. C. (1983). Ordinal Measures in Multiple Indicator Models: A Simulation Study of Categorization Error. American Sociological Review , 48 (3), 398 407. https://doi.org/10.2307/2095231 Kahler, J. S., & Gore, M. L. (2015). Local perceptions of risk associated with poaching of wildlife implicated in human - wildlife conflicts in Namibia. Biological Conservation , 189 , 49 58. https:// doi .org/ 10.1016/j.biocon.20 15.02.001 Kaunda, C. S., Kimambo, C. Z., & Nielsen, T. K. (2012). Potential of small - scale hydropower for electricity generation in Sub - Saharan Africa. ISRN Renewable Energy , 2012 . https://doi.org/10.5402/2012/132606 Khunoana, E., Madikizela, B., Erhabor, J., Nkadimeng, S., Arnot, L., Wyk, I. V., & Mcgaw, L. (2019). A survey of plants used to treat livestock diseases in the Mnisi community, Mpumalanga, South Africa, and investigation of their antimicrobial activity. South African Journal of Botany , 126 , 21 29. https://doi.org/10.1016/j.sajb.2019.07.026 Kiewisch, E. (2015). Looking within the household: A study on gender, food security, and resilience in cocoa - growing communities. Gender and Development , 23 (3), 497 513. https://doi.org/10.1080/13552074.2015.1095550 Kim, M., Xie, Y., & Cirella, G. T. (2019). Sustainable transformative economy: Community - based ecotourism. Sustainability (Switzerland) , 11 (18), 1 15. https://doi.org/10.3390/su11184977 Kirchherr, J., Pohlner , H., & Charles, K. J. (2016). Cleaning up the big muddy: A meta - synthesis of the research on the social impact of dams. Environmental Impact Assessment Review , 60 , 115 125. https://doi.org/10.1016/j.eiar.2016.02.007 Kirchler, E., Hoelzl, E., & Wahl, I. ( Journal of Economic psychology , 29 (2), 210 - 225. https://doi.org/10.1016/j.joep.2007.05.004 Knapp, E. J. (2012). Why poaching pays: A summary of risks and benefits illegal hunters face in Western Serengeti, Tanzania. Tropical Conservation Science , 5 (4), 434 445. https://doi.org/10.1177/194008291200500403 Kobo Toolbox. (2020). Data Collection Too ls for Challenging Environments . https://www.kobotoolbox.org/. Koelble, T. A. (2011). Ecology, economy and empowerment: Eco - tourism and the game lodge industry in South Africa. Business and Politics , 13 (1). https://doi.org/10.2202/1469 - 3569.1333 116 Korkovelos, A., Mentis, D., Siyal, S. H., Arderne, C., Rogner, H., Bazilian, M., Howells, M., Beck, H., & De Roo, A. (2018). A geospatial assessment of small - scale hydropower potential in sub - saharan Africa. Energies , 11 (3100). https://doi.org/10.3390/en11 113100 Kort, Y. A. W. De, Mccalley, L. T., & Midden, C. J. H. (2008). Persuasive Trash Cans: Activation of Littering Norms by Design. Environment and Behavior , 40 (6), 870 891. https://doi.org/ 10.1177/0013916507311035 Kotze, P. (2020, July 1). As South Africa eases lockdown, eco - tourism community fears for future. Reuters . https://www.reuters.com/article/safrica - tourism - health - coronavirus/feature - as - south - africa - eases - lockdown - eco - tourism - community - fears - for - future - idUS L8N2DM255. La Shier, B., & Stanish, J. (2017, December 20). Issue Brief: The National Security Impacts of Climate Change. Retrieved May 6, 2020, from https://www.eesi.org/papers/view/issue - brief - the - national - security - impacts - of - climate - change Lehohla, P. (2012). Census 2011 Municipal report KwaZulu - Natal. Pretoria, South Africa . The New York Times . https://www.nytimes.com/2014/08/24/opinion/sunday/large - dams - just - arent - worth - the - cost.ht ml?_r=1. Lindsey, P. A., Alexander, R., Mills, M. G. L., Romañach, S., & Woodroffe, R. (2007). Wildlife viewing preferences of visitors to protected areas in South Africa: Implications for the role of ecotourism in conservation. Journal of Ecotourism , 6 (1), 19 33. https://doi.org/10.2167/joe133.0 Litheko, A., & Potgieter, M. (2020). Development a nd Management o f Ecotourism Small Business Enterprises: North West Province, South Africa . 6 (2004), 1 8. Loftus, A. (201 5 ). Water (in)security: securing the right to water. The Geographical Journal , 181 (4), 350 356. https://doi.org / 10.1111/geoj.12079 Loibooki, M., Hofer, H., Campbell, K. L. I., & East, M. L. (2002). Bushmeat hunting by communities adjacent to the Serengeti National Park, Tanzani a: The importance of livestock ownership and alternative sources of protein and income. Environmental Conservation , 29 (3), 391 398. https://doi.org/10.1017/S0376892902000279 Lopes, A. A. (2014). Civil unrest and the poaching of rhinos in the Kaziranga Nat ional Park, India. Ecological Economics,103 , 20 - 28. https://doi.org / 10.1016/j.ecolecon.2014.04.006 Lujala, P., & Aas Rustad , S. (2011). High - value natural resources: A blessing or a curse for peace? Sustainable Development Law & Policy , 12 (1), 19 22, 56 57. https://doi.org/10.4324/9781849775786 117 Lynn, B. (2019, November 25). Deadly Drought in Southern Africa Leaves Millions Hu ngry . VOA. https://learningenglish.voanews.com/a/deadly - drought - in - southern - africa - leaves - millions - hungry/5176127.html. Malleson, N., & Andresen, M. A. (2015). Spatio - temporal crime hotspots and the ambient population. Crime Science , 4 (1). https://doi.org /10.1186/s40163 - 015 - 0023 - 8 Marteache, N., & Pires, S. F. (2019). Choice Structuring Properties of Natural Resource Theft: An Examination of Redwood Burl Poaching. Deviant Behavior , 41 (3), 311 328. https://doi.org/10.1080/01639625.2019.1565518 Masipa, T. S. (2017). The impact of climate change on food security in South Africa: Current realities and challenges ahead. Jàmbá: Journal of Disaster Risk Studies , 9 (1), 1 - 7. http://dx.doi.org/10.4102/jamba.v9i1.411 Massé, F. (2019). Anti - amidst a poaching crisis. Geoforum , 98 , 1 14. https://doi.org / 10.1016/j.geoforum.2018.09.011 McKittrick, M. (2008). Landscapes of power: Ownership and identity on the Middle Kavango River, Namibia. Journal of Southern African Studies , 34 (4), 785 802. https://doi.org/10.1080/03057070802456755 Meissner, R., Steyn, M. , Moyo, E., Shadung, J., Masangane, W., Nohayi, N., & Jacobs - Mata, I. (2018). South African local government perceptions of the state of water security. Environmental Science and Policy , 87 (April), 112 127. https://doi.org/10.1016/j.envsci.2018.05.020 Mes ser, K. D. (2010). Protecting endangered species: When are shoot - on - sight policies the only viable option to stop poaching? Ecological Economics,69 (12), 2334 - 2340. https://doi.org / 10.1016/j.ecolecon.2010.06.017 Meyfroidt, P. (2018). Trade - offs between en vironment and livelihoods: Bridging the global land use and food security discussions. Global Food Security , 16 , 9 16. https://doi.org/10.1016/j.gfs.2017.08.001 Miller, B. (2001). The concept of security: Should it be redefined? Journal of Strategic Studies , 24 (2). https://doi.org/10.1080/01402390108565553 Mills, A. J., Durepos, G., & Wiebe, E. (2010). Encyclopedia of case study research . Los Angeles: SAGE Publications. https://doi.org/10.4135/9781412957397 Mishler, W., & Rose, R. (2002). Learning and re - learning regime support: The dynamics of post - communist regimes. European Journal of Political Research , 41 (1), 5 36. https://doi.org/10.1111/1475 - 6765.00002 118 Mogomotsi, G. E. J., & Madigele, P. K. (2017). Li ve by the gun, die by the gun: An Analysis of - to - - poaching strategy. South African Crime Quarterly , 60 . https://doi.org/10.17159/2413 - 3108/2017/v0n60a1787 Mohammadpour, P., Mahjabin, T., Fernandez, J., & Grady, C. (2019). From national indices to regional action An Analysis of food, energy, water security in Ecuador, Bolivia, and Peru. Environmental Science and Policy , 101 (August), 291 301. https://doi.org/10.1016/j.envsci.2019.08.014 Moore, J. E., Cox, T. M., Lewi son, R. L., Read, A. J., Bjorkland, R., McDonald, S. L., Crowder, L. B., Aruna, E., Ayissi, I., Espeut, P., Joynson - Hicks, C., Pilcher, N., Poonian, C. N. S., Solarin, B., & Kiszka, J. (2010). An interview - based approach to assess marine mammal and sea tur tle captures in artisanal fisheries. Biological Conservation , 143 (3), 795 805. https://doi.org/10.1016/j.biocon.2009.12.023 Moran, E. F., Lopez, M. C., Moore, N., Müller, N., & Hyndman, D. W. (2018). Sustainable hydropower in the 21st century. Proceedings of the National Academy of Sciences of the United States of America , 115 (47), 11891 11898. https://doi.org/10.1073/pnas.1809426115 Muller, M. (2019, November 15). Mismanagement threatens water supply more than climate change in South Africa . Q uartz Africa. https://qz.com/africa/1749099/how - mismanagement - is - making - the - 2019 - drought - in - africa - worse/. Munang, R., & Mgendi, R. (2014, December 30). Soil: the sustainable alternative to oil income in Africa. The Guardian . https://www.theguardian.com/g lobal - development - professionals - network/2014/dec/30/soil - the - sustainable - alternative - to - oil - income - in - africa. Muñoz - Cadena, C. E., Lina - Manjarrez, P., Estrada - Izquierdo , I., & Ramón - Gallegos, E. (2012). An approach to litter generation and littering practices in a Mexico City neighborhood. Sustainability , 4 (8), 1733 1754. https://doi.org/10.3390/su4081733 Muter, B. A., Gore, M. L., & Riley, S. J. (2013). Social contagio n of risk perceptions in environmental management networks. Risk Analysis , 33 (8), 1489 1499. https://doi.org/10.1111/j.1539 - 6924.2012.01936.x Naro, E. M., Maher, S. M. L., Muntifering , J. R., Eichenwald, A. J., & Clark, S. G. (2020). Syndicate recruitment, perceptions, and problem solving in Namibian rhinoceros protection. Biological Conservation , 243 (March), 108481. https://doi.org/10.1016/j.biocon.2020.108481 National Planning Commi ssion: South Africa. (2012). (publication). National Development Plan 2030: Our Future - Make it Work (pp. 1 489). Boksburg, South Africa: Sherino Printers. Naylor, R. L., Liska, A. J., Burke, M. B., Falcon, W. P., Gaskell, J. C., Rozelle, S. D., & Cassma n, K. G. (2007). The ripple effect biofuels, food security, and the environment. Environment , 49 (9), 30 43. https://doi.org/10.3200/ENVT.49.9.30 - 43 119 Nellemann, C., Henriksen, R., Kreilhuber, A., Stewart, D., Kotsovou, M., Raxter, P., Barrat, S., & Mrema, E . (2016). The Rise of Environmental Crime A Growing Threat To Natural Resources Peace, Development And Security. In UNEP . https://doi.org/10.18356/cdadb0eb - en Ngome, P. I. T., Shackleton, C., Degrande, A., Nossi, E. J., & Ngome, F. (2019). Assessing hou sehold food insecurity experience in the context of deforestation in Cameroon. Food Policy , 84 , 57 65. https://doi.org / 10.1016/j.foodpol.2019.02.003 Niranjan, R., & Thakur, A. K. (2017). The toxicological mechanisms of environmental soot (black carbon) a nd carbon black: Focus on Oxidative stress and inflammatory pathways. Frontiers in Immunology , 8 (JUN), 1 20. https://doi.org/10.3389/fimmu.2017.00763 Norfolk, S. (2004). (working paper). Examining access to natural resources and linkages to sustainable livelihoods: A Case Study of Mozambique (pp. 1 76). Livelihood Support Programme. Advances in Health Sciences Education , 15 (5), 625 632. https://doi.org/10.1 007/s10459 - 010 - 9222 - y Ntsebeza, L. (2002). Decentralisation and Natural Resource Management in Rural South Africa: Problems and Prospects, ISACP Bi - Annual Conference, Victoria Falls, Zimbabwe, 17 - 21 June 2002. http://dlc.dlib.indiana.edu/dlc/bitstream/han dle/10535/1345/ntsebezal290502.pdf?sequence=1 Ntuli, H., Jagers, S. C., Linell, A., Sjöstedt, M., & Muchapondwa, E. (2019). Factors influencing case of the Great Limpopo Trans - frontier Conservation Area. Biodiversity and Conservation , 28 (11), 2977 3003. https://doi.org/10.1007/s10531 - 019 - 01809 - 5 Nunnally, J. C., & Bernstein, I. H. (2010). Psychometric theory . Tata McGraw - Hill Ed. Progress in Human Geography , 35 (4), 542 549. https://doi.org/10.1177/0309132510377573 Olson, A. (2013, June 13). U.N.: World population to reach 8.1B in 2025. USA Today . https://www.usatoday.com/story/news/world/2013/06/13/un - world - population - 81 - billion - 2025/2420989/. Opperman, J. (2018, August 10). The Unexpectedly Large Impacts o f Small Hydropower. Forbes . https://www.forbes.com/sites/jeffopperman/2018/08/10/the - unexpectedly - large - impacts - of - small - hydropower/#6e6e06557b9d Ortmann, G. F., & King, R. P. (2007). Agricultural cooperatives II: Can they facilitate access of small - scale farmers in South Africa to input and product markets? Agrekon , 46 (2), 219 244. https://doi.org/10.1080/03031853.2007.9523769 120 Osborne, J. W. (2010). Improving your data transformations: Applying the Box - Cox transformation. Practical Assessment, Research and Evaluation , 15 (12). https ://doi.org/10.7275/qbpc - gk17 Pak, S. Il, & Oh, T. H. (2010). Correlation and simple linear regression. Journal of Veterinary Clinics , 27 (4), 427 434. https://doi.org/10.1007/978 - 3 - 319 - 89993 - 0_6 Pallant, J. (2016). Spss Survival Manual: A Step by Step Guide to Data Analysis Using Ibm Spss (6th ed.). McGraw - Hill Education. Palmer, M. A. (2010). Beyond Infrastructure. Nature , 467 , 534 535. https://doi.org/10.1038/467534a Peace Parks Foundation. (2020). Great Limpopo. Retrieved August 7, 2020, from https://www.peaceparks.org/tfcas/great - limpopo/ POP Center. Situational Crime Prevention . Situational Crime Prevention | ASU Center for Problem - Oriented Policing. https://popcenter.asu.edu/content/situational - crime - prevention - 0. Poppy, G. M., Jepson, P. C., Pickett, J. A., & Birkett, M. A. (2014). Achieving food and environmental security: New approaches to close the gap. Philosophical Transactions of the Royal Soc iety B: Biological Sciences , 369 (1639). https://doi.org/10.1098/rstb.2012.0272 Pröpper, M., & Vollan, B. (2013). Beyond awareness and self - governance: Approaching Kavango - life choices. Land , 2 (3), 392 418. https://doi.org/10.3390/land20 30392 Ravenelle, J., & Nyhus, P. J. (2017). Global patterns and trends in human wildlife conflict compensation. Conservation Biology , 31 (6), 1247 1256. https://doi.org/10.1111/cobi.12948 Refisch, J. What COVID - 19 means for ecotourism. other. https://www. unenvironment.org/news - and - stories/story/what - covid - 19 - means - ecotourism. Rice, J. C., & Garcia, S. M. (2011). Fisheries, food security, climate change, and biodiversity: Characteristics of the sector and perspectives on emerging issues. ICES Journal of Ma rine Science , 68 (6), 1343 1353. https://doi.org/10.1093/icesjms/fsr041 Romero, D. (2014). Insecurity or perception of insecurity? Urban crime and dissatisfaction with life: Evidence from the case of Bogotá. Peace Economics, Peace Science and Public Policy , 20 (1), 169 208. https://doi.org/10.1515/peps - 2013 - 0057 Sandbrook, C. G. (2010). Putting leakage in its place: The significance of retained tourism revenue in the local context in rural Uganda. Journal of International Development: The Journal of the Development Studies Association , 22 (1), 124 - 136 . https://doi.org/10.1002/ji d Saris, W. E., & Gallhofer, I. N. (2014). Design, evaluation, and analysis of questionnaires for survey research . John Wiley & Sons. https:// 10.1002/9781118634646 121 Scott, S. V. (2012). The securitization of climate change in world politics: How close have we come and would full securitization enhance the efficacy of global climate change policy? Review of European Community and International Environmental Law , 21 (3), 220 230. https://doi.org/10.1111/reel.12008 Shriar, A. J. (2002). Food security and land use deforestation in northern Guatemala. Food Policy , 27 (4), 395 414. https://doi.org/10.1016/S0306 - 9192(02)00046 - 5 Singleton, R., & Straits, B. C. (2005). Approaches to social research (4th ed.). Oxford Univ. Press. Skinner, J. (2014, December 9). Dams in Africa: Combining national and local development [web log]. https://www.iied.org/dams - africa - combining - national - local - development. Snyman, S. (2014). The impact of ecotourism employment on rural household incomes and social welfare in six southern African countries. Tourism and Hospitality Research , 14 (2), 37 52. https://doi.org/10.1177/1467358414529435 Snyman, S. (2017). The role of private sector ecotourism in local socio - economic development in southern Africa. Journal of Ecotourism , 16 (3), 247 268. https://doi.org/10.1080/14724049.2016.1226318 Spenceley, A., & Goodwin, H. (2007). Nature - based tourism and poverty alleviation: Impa cts of private sector and parastatal enterprises in and around Kruger National Park, South Africa. Current Issues in Tourism , 10 (2 - 3), 255 - 277. https://doi.org/10.2167/cit305.0 Spring, Ú. O. (2009). A HUGE Gender Security Approach: Towards Human, Gender, and Environmental Security. Hexagon Series on Human and Environmental Security and Peace Facing Global Environmental Change , 1157 1181. https://doi.org / 10.1007/978 - 3 - 540 - 68488 - 6_90 Spring, Ú. O., Brauch, H. G., & Dalby, S. (2009). Linking Anthrop ocene, HUGE and HESP: Fourth Phase of Environmental Security Research. Hexagon Series on Human and Environmental Security and Peace Facing Global Environmental Change , 1277 1294. https://doi.org / 10.1007/978 - 3 - 540 - 68488 - 6_98 Stake, R. E. (2010). The art of case study research . Thousand Oaks, CA: Sage Publ. https://doi.org/10.1177/135638909600200211 Statistics South Africa. (2020). 2011 South Africa Census . Statistics South Africa. http://www.statssa.gov.za/. Strickland - Munro, J. K., Moore, S. A., & Freitag - Ronaldson, S. (2010). The impacts of tourism on two communities adjacent to the Kruger National Park, South Africa. Development Southern Africa , 27 (5), 663 678. https://doi.org/10.1080/0376835X.2010.522829 122 Sullivan, G. M., & Artino Jr, A. R. (2013). Analyzing and interpreting data from Likert - type scales. Journal of graduate medical education , 5 (4), 541 - 542. http://dx.doi.org/10.4300/JGME - 5 - 4 - 18 Sundström, A., Linell, A., Ntuli, H., Sjöstedt , M., & Gore, M. L. (2019). Gender differences in poaching attitudes: Insights from communities in Mozambique, South Africa, and Zimbabwe living near the great Limpopo. Conservation Letters , November 2019 , 1 8. https://doi.org/10.1111/conl.12686 Taureck, R. (2006). Securitization theory and securitization studies. Journal of International Relations and Development , 9 (1), 53 61. https://doi.org/10.1057/palgrave.jird.1800072 Thornton, A. (2008). Beyond the Metropolis: Small Town Case Studies of Urban and Peri - urban Agriculture in South Africa. Urban Forum , 19 (3), 243 262. https://doi.org/10.1007/s12132 - 008 - 9036 - 7 Tibesigwa, B., & Visser, M. (2016). Assessing Gender Inequality in Food Security among Small - holder Farm Households in urban and rural South Africa. World Development , 88 , 33 49. https://doi.org/10.1016/j.worlddev.2016.07.008 Tilley, N., & Sidebottom, A. (2014). Situational Crime Prevention. In G. Bruinsma & D. Weisb urd (Eds.), Encyclopedia of Criminology and Criminal Justice (pp. 4864 4874). Springer New York. https://doi.org/10.1007/978 - 1 - 4614 - 5690 - 2_549 Triezenberg, H. A., Gore, M. L., Riley, S. J., & Lapinski , M. K. (2014). Perceived Risks from Disease and Management Policies: An Expansion and Testing of a Zoonotic Disease Risk Perception Model. Human Dimensions of Wildlife , 19 (2), 123 138. https://doi.org/10.1080/10871209.2014.844288 Trochim, W. M.K. (2020, April 14). The Research Methods Knowledge Base. Retrieved August 3, 2020, from https://conjointly.com/kb/. Twongyirwe, R., Mfitumukiza, D., Barasa, B., Naggayi, B. R., Odongo, H., Nyakato, V., & Mutoni, G. (2019). Perceived effects of drought on ho usehold food security in South - western Uganda: Coping responses and determinants. Weather and Climate Extremes , 24 , 100201. https://doi.org / 10.1016/j.wace.2019.100201 Twyman, C., & Slater, R. (2005). Hidden livelihoods?: Natural resource - dependent liveli hoods and urban development policy. Progress in Development Studies , 5 (1), 1 15. https://doi.org/10.1191/1464993405ps097oa Tyler, T. R. (2006). Psychological perspectives on legitimacy and legitimation. Annual Review of Psychology , 57 , 375 400. https://doi.org/10.1146/annurev.psych.57.102904.190038 UCLA: Statistical Consulting Group. (2020). Introduction to Linear Mixed Model s . Introduction to SAS. https://stats.idre.ucla.edu/other/mult - pkg/introduction - to - linear - mixed - models/. 123 Uhunamure, S. E., Musyoki, A., & Nethengwe , N. S. (2016). Emissions and deforestation associated with household fuel wood use - a case of the Thulamela local municipality, South Africa. Africa Insight , 45 (4), 109 128. UN - Water. (2020). Water Scarcity . United Nations. https://www.unwater.org/water - facts/scarcity/. UNEP. (2009). From Conflict to Peacebuilding: The Role of Natural Resources and the Environment . United Nations Environment Program. United Nations Department of Economic and Social Affairs. (2020). The 17 Goals . United Nations: Department of Economic and Social Affairs Sustainable Development. https://sustainabledevelopment.un.org/?menu=1300. United Nations Entity for Gender Equality and the Empowerment of Women (UN Women), & Department of Economic and Soc ial Affairs (DESA). (2019). Progress on the Sustainable Development Goals: The gender snapshot 2019 (pp. 1 - 24, Rep.). New York, NY: UN Women Headquarters. Van Uhm, D. P. (2016). The illegal wildlife trade: Inside the world of poachers, smugglers and traders (Vol. 15). Springer. https://doi.org/10.1007/978 - 3 - 319 - 42129 - 2 Vaske, J. J. (2008). Survey research and analysis: applications in parks, recreation, and human dimensions . State College, PA: Venture Publ. Vörösmarty , C. J., McIntyre, P. B., Gessner, M. O., Dudgeon, D., Prusevich, A., Green, P., Glidden, S., Bunn, S. E., Sullivan, C. A., Liermann, C. R., & Davies, P. M. (2010). Global threats to human water security and river biodiversity. Nature , 467 (7315), 555 561. https://doi.org/10.1038/nature09440 Vu, T. B., Im, E. I., Hayashi, K., & Torio, R. (2017). Cyclones, Deforestation, and Production of Food Crops in Vietnam. Economics of Disasters and Climate Change , 1 (3), 245 262. https://doi.org/10.1007/s41885 - 017 - 0010 - 5 Walker, R. J. (2016). Population Growth and its Implications for Global Security. American Journal of Economics and Sociology , 75 (4), 980 1004. https://doi.org / 10.1111/ajes.12161 Wasser, S. K., To agra rkelson, A. , Winters, M., Horeaux, Y., Tucker, S., Otiende, M. Y., . . . Weir, B. S. (2018). Combating transnational organized crime by linking multiple large ivory seizures to the same dealer. Science Advances,4 (9). https://doi.org / 10.1126/sciadv.aat0625 Watts, A. J. R., Porter, A., Hembrow, N., Sharpe, J., Galloway, T. S., & Lewis, C. (2017). Through the sands of time: Beach litter trends from nine cleaned north cornish beaches. Environmental Pollution , 228 , 416 424. https://doi.org/10.1016/j.envpol.2017.05.016 124 Watts, S. (2003). The effects of communal land resource management on forest conservation in northern and north - eastern Namibia. Development Southern Africa , 20 (3), 337 359. https://doi.org/10.1080/037683503200 0108167 Wentzel, M., & Pouris, A. (2007). The development impact of solar cookers: A review of solar cooking impact research in South Africa. Energy Policy , 35 (3), 1909 1919. https://doi.org/10.1016/j.enpol.2006.06.002 West, A. (2019, June 30). Hydropowe Power . https://www.powermag.com/hydropower - is - vital - to - africas - future/. Wilkinson, D., & Tellez - Chavez, L. (2020, April 1 6 ). How COVID - 19 Could Impact the Climate Crisis. https://fpif.org/how - covid - 19 - could - impact - the - climate - crisis/ Winchester, N., Ledvina, K., Strzepek, K., & Reilly, J. M. (2018). The impact of water scarcity on food, bioenergy and deforestation. Australian Journal of Agricultural and Resource Economics , 62 (3), 327 351. https://doi.org/10.1111/1467 - 8489.12257 Winter , J. C. F. De, De Winter, J. C. F., & Dodou, D. (2010). Five - point Likert items: t test versus Mann - Whitney - Wilcoxon. PRACTICAL ASSESSMENT, RESEARCH & EVALUATION , 11. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.650.3292 Witter, R., & Satterfie - related Geoforum , 101 , 275 284. https://doi.org/10.1016/j.geoforum.2018.06.003 Wong, R., & van der Heijden, J. (2019). Avoidance of c onflicts and trade - offs: A challenge for the policy integration of the United Nations Sustainable Development Goals. Sustainable Development , 27 (5), 838 845. https://doi.org/10.1002/sd.1944 Workman, C. L., & Ureksoy , H. (2017). Water insecurity in a syndemic context: Understanding the psycho - emotional stress of water insecurity in Lesotho, Africa. Social Science & Medicine , 179 , 52 60. https://doi.org / 10.1016/j.socscimed.2017.02.026 World Health Organization. (2000). WHO Multicountry Study on Improving Household Food and Nutrition Security for the Vulnerable: South Africa: a qualitative study on food security and caring patterns of vulnerable young children in South Africa (No. WHO/NHD/00.4). Worl d Health Organization World Health Organization. (2015). Health in 2015: From MDGs to SDGs (Rep.). Retrieved 2020, from https://apps.who.int/iris/bitstream/handle/10665/200009/9789241565110_eng.pdf World Resources Institute. (2017, May 1). Cameroon . https://www.wri.org/our - work/project/governance - forests - initiative/cameroon. 125 Yadav, I. C., & Devi, N. L. (2018). Biomass burning, regional air quality, and climate change. Earth Systems and Environmental Sciences. Edition: Encyclopedia of Enviro nmental Health. Elsevier. https://doi.org/10.1016/B978 - 0 - 12 - 409548 - 9.11022 - X . Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (Vol. 6). Thousand Oaks, CA: SAGE Publications , Inc . York, N. (2019, November 18). Environmental crimes increasingly linked to violence, insecurity. Retrieved from http://www.thenewhumanitarian.org/news/2013/10/03/environmental - crimes - increasingly - linked - violence - insecurity . Zafra - Calvo, N., Lobo, J. M., Prada, C., Nielsen, M. R., & Bur gess, N. D. (2018). Predictors of elephant poaching in a wildlife crime hotspot: The Ruvuma landscape of southern Tanzania and northern Mozambique. Journal for Nature Conservation , 41 (November 2017), 79 87. https://doi.org/10.1016/j.jnc.2017.11.006 Zimmerman, M. E. (2003). The black market for wildlife: Combating transnational organized crime in the illegal wildlife trade. Vanderbilt Journal of Transnational Law, 36(5), 1657 - 1690. Zohdi, N. (2007). Strategies to Enhance Environmental Security in Transition Countries. In R. Hull, B. Constantin - Horia, & N. Goncharova (Eds.), Strategies to Enhance Environmental Security in Transition Countries . https://apps.webofknowledge.com/full_record.do?product=UA&search_mode=GeneralSearch&q id=1&SID=R 27kAxFVKlL3lENQ3Pk&page=4&doc=154&cacheurlFromRightClick=no Zumbo, B. D., & Zimmerman, D. W. (1993). Is the selection of statistical methods governed by level of measurement? Canadian Psychology/Psychologie Canadienne, 34 (4), 390 400. https://doi.org/10.1 037/h0078865 Zurlini, G., & Müller, F. (2008). Environmental security. In Encyclopedia of Ecology (pp. 1350 1356). Elsevier B.V. https://doi.org/10.1093/oxfordhb/9780198777854.013.31