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Individual-Based Model for the Dispersal of the South African Wild Dog Population in the Kwazulu-Natal Province

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Individual-Based Model for the Dispersal of the South African Wild Dog Population in the Kwazulu-Natal Province INDIVIDUAL-BASED MODEL FOR THE DISPERSAL OF THE SOUTH AFRICAN WILD DOG POPULATION IN THE KWAZULU-NATAL PROVINCE HUMBOLDT STATE UNIVERSITY By Elizabeth Grace Arnold A Thesis Presented to The Faculty of Humboldt State University In Partial Fulfillment Of the Requirements for the Degree Master of Science In Environmental Systems: Mathematical Modeling October, 2010 INDIVIDUAL-BASED MODEL FOR THE DISPERSAL OF THE SOUTH AFRICAN WILD DOG POPULATION IN THE KWAZULU-NATAL PROVINCE HUMBOLDT STATE UNIVERSITY By Elizabeth Grace Arnold Approved by the Master’s Thesis Committee: Dr. Diane Johnson, Major Professor Date Dr. Sharon Brown, Committee Member Date Dr. Micaela Szykman Gunther, Committee Member Date Dr. Steve Railsback, Committee Member Date Dr. Christopher Dugaw, Graduate Coordinator Date Dr. Jena´ Burges, Vice Provost Date ABSTRACT INDIVIDUAL-BASED MODEL FOR THE DISPERSAL OF THE SOUTH AFRICAN WILD DOG POPULATION IN THE KWAZULU-NATAL PROVINCE Elizabeth Grace Arnold The African wild dog (Lycaon pictus) is facing a high risk of extinction with fewer than 5,000 individuals living in fragmented landscapes. After an absence of nearly 50 years, several sub-populations of wild dogs have been reintroduced into isolated, fenced game reserves in the province of KwaZulu-Natal (KZN), South Africa. To better understand the effect of natural dispersal on the African wild dog population in KZN, we developed a spatially explicit individual-based model employing the software NetLogo. Wild dogs reintroduced into Phinda Munyawan Conservancy, Greater St. Lucia Wetland Park and Zu- luland Rhino Reserve had the greatest dispersal success while wild dogs reintroduced into Ithala Game Reserve, Ndumo Game Reserve and Tembe Elephant Park displayed the least successful dispersal and persistence. This information will aid researchers and wildlife managers in determining effective, cost-efficient management plans for the KZN wild dog population and can be further extended to all of South Africa. iii ACKNOWLEDGEMENTS First and foremost, I have to give many, many thanks to my committee members: Dr. Diane Johnson, Dr. Micaela Szykman Gunther, Dr. Steve Railsback and Dr. Sharon Brown. Without all of their help, knowledge, support and undying patience, I would not have com- pleted this project! Diane, thank you so much for stepping in and supporting me over the years. You have helped me with both my undergraduate and graduate degrees and I greatly appreciate all of the time you have spent meeting with me and helping me with my writing! Micaela, thank you for all of your help and inspiring me to study the African wild dogs. You have so much passion for the wild dogs that I can not help but get excited when we discuss them! Steve, thank you so much for your support with NetLogo. At times I needed to distract myself and play Frogger on NetLogo but I have really enjoyed learning about individual-based models and NetLogo! Finally, Sharon, you have been a great teacher, ad- visor, mentor and friend throughout all of this. Thank you so much for sticking with me! I can not express how much I appreciate all of your help and guidance throughout the years and through the distance. I know I have procrastinated long enough on my thesis but it is finally done! Thank you so very much to all of my committee members! I am also grateful for my fellow graduate students, friends and the Mathematics De- partment. I would also like to thank Bori and Chris for being great teachers and I enjoyed taking your classes in graduate school. To Jason Barnes and the GIS club, thank you very much for helping me with the GIS layers used in my model. Finally, I have to thank my parents for all of their help. They have supported me in so many ways throughout my collegiate career at HSU. Thanks for the car, Dad! iv TABLE OF CONTENTS ABSTRACT . iii ACKNOWLEDGEMENTS . iv TABLE OF CONTENTS . v LIST OF FIGURES . vi LIST OF TABLES . viii INTRODUCTION . 1 Causes of African Wild Dog Population Decline . 3 Conservation Efforts . 7 Appearance of the African Wild Dog . 12 Sociality and Group Structure . 13 Dispersal . 14 MODEL . 17 Individual-Based Model . 18 ODD Protocol . 19 Model Validation . 47 Sensitivity Analysis . 52 Experiments . 55 RESULTS . 57 DISCUSSION . 69 Future African Wild Dog Studies . 73 Literature Cited . 76 APPENDIX A . 79 APPENDIX B . 83 APPENDIX C . 87 v LIST OF FIGURES Figure Page 1 Location of KwaZulu-Natal, South Africa (WWF, 2010). 2 2 Past and current distributions of the African wild dog population (Woodroffe et al., 2004). 4 3 NetLogo display of the KZN environment. Game reserves are the green patches, rivers are the blue lines, roads are the brown lines, red circles are the villages and the KZN boundary lines are yellow lines. 10 4 The African wild dog, Lycaon pictus (Photo c M. Szykman Gunther). 12 5 Flow chart describing the disperser groups’ processes. 23 6 Flow chart describing the packs’ processes. 24 7 Percentage of disperser groups that joined an existing game reserve pack when the parameter ‘game-reserve-pack-radius’ was set to 1.25, 1.50 and 1.75 (Note: y-axis begins at 23.5 to emphasize the slight variation in the percentages). ................................. 33 8 Percentage of disperser groups that formed a new pack with another dis- perser group when the parameter ‘dispersergroup-radius’ was set to 1.00, 1.125 and 1.25 (Note: y-axis begins at 25 to emphasize the slight variation in the percentages)............................... 33 9 Percentage of wild dogs dying due to diseases when the parameter ‘village- radius’ was set to 0.33, 0.50, 0.75 and 1.00. 34 10 General example of a gamma probability density function with a mean of 30. α = 1.91 and β = 15.73. 36 11 Graphs of a disperser group’s fitness level traced for one year. a.) ‘movement- loss-percent’ = 8%. b.) ‘movement-loss-percent’ = 10%. c.) ‘movement- loss-percent’ = 15%. d.) ‘movement-loss-percent’ = 25%. 38 12 Average percentage of total wild dog pack formations tested at different values of the parameter ‘join-game-reserve-pack.’ . 41 vi 13 Average percentage of wild dogs dying due to dehydration tested at differ- ent values of the parameter ‘chance-of-water.’ . 42 14 Average percentage of disperser groups that formed a new pack when ‘join- game-reserve-pack’ was varied from 1% to 5%. a.) ‘join-game-reserve- pack’ = 1%. b.) ‘join-game-reserve-pack’ = 2%. c.) ‘join-game-reserve- pack’ = 3%. d.) ‘join-game-reserve-pack’ = 4%. e.) ‘join-game-reserve- pack’ = 5%. 58 15 Average percentage of disperser groups that joined an existing game reserve pack when ‘join-game-reserve-pack’ was varied from 1% to 5%. a.) ‘join- game-reserve-pack’ = 1%. b.) ‘join-game-reserve-pack’ = 2%. c.) ‘join- game-reserve-pack’ = 3%. d.) ‘join-game-reserve-pack’ = 4%. e.) ‘join- game-reserve-pack’ = 5%. 59 16 Average percentage of total wild dog pack formations (solid) versus the average percentage of wild dogs that died (open). 60 17 Average percentage of single disperser groups at the end of each model run. 61 18 Total combined average a.) time in days and b.) distance in km a disperser group traveled to form a new pack. 62 19 Total combined average a.) time in days and b.) distance in km a disperser group traveled to join an existing game reserve pack. 66 20 Dispersal success of only the reintroduced wild dogs. 68 vii LIST OF TABLES Table Page 1 Game reserve name, size, public or private ownership and the number of packs living in each game reserve in 2009. 11 2 State variables and their descriptions for the entity disperser groups. 20 3 State variables and their descriptions for entity packs. 21 4 State variables and their descriptions for the entity game reserve packs. 21 5 State variables and their descriptions for the entity KZN environment. 22 6 Model Parameter Name and Value(s). 30 7 Fitness levels and the corresponding probabilities of traveling 60 km or more. 37 8 Fitness levels and the corresponding probabilities of catching prey once a day. ...................................... 45 9 Sensitivity of parameters. 54 10 Frequency of where new packs were formed. 63 11 Game reserve origins of the disperser groups that formed a new pack. 64 12 Percentage of the time new packs reached given game reserve. 65 13 Game reserve origins of the disperser groups that joined an existing game reserve pack. 67 viii INTRODUCTION The African wild dog Lycaon pictus, often called the painted wolf, is among the most endangered large carnivores in Africa. There are fewer than 5,000 individuals remaining. Populations have rapidly declined over the last century and this decline has accelerated in the last 30 years (Woodroffe et al., 1997, 2004; Creel and Creel, 2002). The primary causes of this decline are increasingly fragmented landscapes combined with infectious diseases and diminishing prey populations (Woodroffe et al., 1997, 2004). Most of the 600 - 1,000 remaining packs of wild dogs have populations no longer sustainable. Currently the South African wild dog population has been limited to a single viable population in Kruger National Park, located in northeast South Africa (Woodroffe et al., 1997, 2004). The ongoing decline in the number of mature individuals resulting from decreasing populations has caused African wild dogs to be categorized as Endangered on the Inter- national Union for Conservation of Nature (IUCN) Red List (IUCN, 2010). The IUCN Species Survival Commission Canid Specialist Group has also designated African wild dogs as a high priority species for wildlife conservation. “African wild dogs are the only extant representatives of a distinct lineage of wolf-like canids and as a result of this phy- logenetic distinctiveness, they have a high conservation value” (Woodroffe et al., 1997).
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