Camera Traps in Animal Ecology (eBook)

Allan O’Connell is a research wildlife biologist with the U.S. Geological Survey’s Patuxent Wildlife Research Center in Maryland. His research concentrates on wildlife management issues for U.S. federal resource agencies. His cutting-edge work includes the design of multiple technique sampling and monitoring programs to assess biodiversity, the use of camera traps to estimate population parameters, and the investigation of effects of predators on isolated populations of endangered species. James Nichols is a senior scientist with the Patuxent Wildlife Research Center. He is an expert on capture–recapture sampling methods, population modeling, and adaptive management. He has authored or co-authored more than 350 scientific publications, including two books, four edited volumes, and nine monographs, on various aspects of wildlife population ecology. He is a recipient of the 2007 U.S. Presidential Rank Award for Meritorious Service and has received national recognition for his work from various universities, the U.S. Fish and Wildlife Service, U.S. Geological Survey, The Wildlife Society, American Statistical Association, and the U.S. Forest Service. Ullas Karanth is an internationally known conservation scientist (see www.wikipedia.org). Based in India, he is a senior conservation scientist for the Wildlife Conservation Society, where his long-term research has focused on the ecology and conservation of tigers and their prey. He has more than 70 scientific publications to his credit. His work has been featured in the world’s media including the New York Times, Time magazine, National Geographic, BBC, CNN, Discovery, and others. He is the recipient of the Sierra Club’s prestigious international EarthCare Award and the World Wildlife Fund’s J. Paul Getty Award for Conservation Leadership.

Preface 6
Acknowledgments 10
About the Editors 12
Contents 14
Chapter 1: Introduction 16
1.1 Evolution of Camera Trapping 16
1.2 Book Organization and Chapter Summaries 18
References 23
Chapter 2: A History of Camera Trapping 24
2.1 Introduction 24
2.2 Early Developments 25
2.3 The Modern Era 27
2.4 Forest Carnivores 30
2.5 Expanding Applications 31
References 37
Chapter 3: Evaluating Types and Features of Camera Traps in Ecological Studies: A Guide for Researchers 42
3.1 Introduction 42
3.2 Benefits and Problems with Camera Traps in the Field: A Review 43
3.3 Types of Camera Traps 44
3.3.1 Non-triggered Camera Systems 46
3.3.2 Triggered Camera Traps 46
3.4 Camera Trap Features and Trade-offs Among Them 47
3.4.1 System Components 48
3.4.2 Housing 48
3.4.3 Software and Programming 50
3.4.4 Power 51
3.4.5 Camera Types 52
3.4.6 Camera and Lighting Options 52
3.5 Discussion 54
3.5.1 Working with Camera Traps in the Field 54
3.5.2 Emerging Technology 54
References 56
Chapter 4: Science, Conservation, and Camera Traps 59
4.1 Introduction 59
4.2 Science 60
4.2.1 Approaches to Science 60
4.2.2 Science and Camera Traps 62
4.3 Management/Conservation 63
4.3.1 Structured Decision-Making: Introduction 63
4.3.2 Structured Decision-Making: Components 64
4.3.3 Sources of Uncertainty 65
4.3.4 Adaptive Resource Management 66
4.3.5 Management, Conservation, and Camera Trapping 67
4.4 Discussion 67
References 68
Chapter 5: Behavior and Activity Patterns 71
5.1 Introduction 71
5.2 Traditional Techniques of Studying Animal Behavior and Activity 71
5.3 Advantages and Implications for Using Camera Traps 72
5.4 Case Studies 73
5.4.1 Circadian Rhythms 73
5.4.2 Nest Predation 75
5.4.3 Foraging 75
5.4.4 Niche Partitioning and Social Systems 77
5.4.5 Habitat and Corridor Usage 77
5.4.6 Refugia and Reproduction 78
5.4.7 Statistical Analyses 78
5.5 Future Applications for Camera Traps in Behavior Studies 79
References 79
Chapter 6: Abundance, Density and Relative Abundance: A Conceptual Framework 84
6.1 Introduction 84
6.2 Estimation of Abundance 85
Closed Capture–Recapture Models 88
Open Capture–Recapture Models 92
Mixed Time Scale Model 94
Estimation of Density 95
Relative Abundance Indices 101
References 106
Chapter 7: Estimating Tiger Abundance from Camera Trap Data: Field Surveys and Analytical Issues 110
7.1 Introduction 110
7.1.1 Camera Trap Studies of Tigers: Natural History and Science 110
7.1.2 Tiger Ecology in Relation to Abundance Estimation Issues 111
7.2 Equipment and Field Practices 112
7.2.1 Camera Traps and Related Equipment 112
7.2.2 Choice of Trap Sites 114
7.2.3 Accurately Recording Data 114
7.3 Survey Design Considerations 116
7.3.1 Season, Survey Duration and Population Closure 116
7.3.2 Spacing and Placement of Traps 117
7.3.3 Adequate Coverage of the Sampled Area 119
7.4 Data Analysis: Issues and Examples 122
7.4.1 The Approach to Analysis of Tiger Photo-Capture Data 122
7.4.2 Testing for Population Closure 123
7.4.3 Model Selection and Estimation of Tiger Abundance 123
7.4.4 Estimating the Sampled Area Size and Tiger Densities 125
7.5 Camera Trapping Tigers: Some General Comments 126
References 127
Chapter 8: Abundance/Density Case Study: Jaguars in the Americas 131
Introduction 131
Study Sites 132
Survey Design and Data Analysis 135
Results 140
Discussion 148
References 151
Chapter 9Estimation of Demographic Parameters in a Tiger Population from Long-term Camera Trap Data 157
9.1 Introduction 157
9.2 Tiger Behavior and Demography in Relation to Monitoring Issues 158
9.3 Identification of Tigers and Assignment of Age-Sex Classes 160
9.4 Data Analysis Issues 160
9.4.2 Model Selection 163
9.4.3 Software Options 164
9.5 Population Dynamics of Tigers in Nagarahole, India 164
9.6 Utility of Camera Trap Data for Assessing Population Dynamics 169
References 171
Chapter 10: Hierarchical Spatial Capture–Recapture Models for Estimating Density from Trapping Arrays 174
10.1 Introduction 174
10.2 Background 177
10.3 Model Formulation 178
10.3.1 Observation Models 181
10.3.1.1 Model 1: The Poisson Model 181
10.3.1.2 Model 2: The Binomial Encounter Model 182
10.3.1.3 Model 3: The Multinomial Observation Model 183
10.4 Analysis of the Models 184
10.4.1 Poisson Detection Frequencies 184
10 4.1.1 Model Extensions and Reductions by Sufficiency 185
10.4.2 Model 2: Bernoulli Encounter Process 185
10.4.3 Analysis of Simulated Data 186
10.5 Model Extension: Unknown s and N 187
10.6 Unknown N: Data Augmentation 189
10.6.1 Implementation 191
10.7 Application to Nagarahole Tiger Data 192
10.8 Demographically Open Systems 194
10.9 Summary and Discussion 197
References 200
Chapter 11: Inference for Occupancy and Occupancy Dynamics 202
11.1 Introduction 202
11.2 Occupancy in Animal Ecology 203
11.3 Model Framework, Assumptions and Analytical Options 204
11.4 Study Designs for Occupancy Models 207
11.5 Suggestions for Presenting Results of Occupancy Analysis 208
11.6 Occupancy Estimation with Camera Trap Data: Model Extensions 209
11.6.1 Multiple Methods and Multiple Scales 210
11.6.2 Species Co-Occurrence and Resource Partitioning 211
11.7 Recent Advances 212
11.7.1 Multistate Occupancy Models 212
11.7.2 Occupancy Models with Spatially Clustered Subunits 212
11.8 Concluding Remarks 213
References 214
Chapter 12: Species Richness and Community Dynamics: A Conceptual Framework 217
12.1 Introduction 217
12.2 Inference About Single Sites 222
12.2.1 Static Community at a Single Site 222
12.2.2 Dynamic Community at a Single Site 226
12.3 Inference About Multiple Sites 228
12.3.1 Static Metacommunity 228
12.3.2 Dynamic Metacommunity 234
12.4 Design Considerations 235
References 238
Chapter 13: Estimation of Species Richness of Large Vertebrates Using Camera Traps: An Example from an Indonesian Rainforest 242
13.1 Introduction 242
13.2 Camera Traps and Species Lists 246
13.3 Estimating and Monitoring Species Richness: An Example from Indonesia 248
13.3.1 Observed and Estimated Species Richness 249
13.3.2 Relative Species Richness 252
References 259
Chapter 14: Camera Traps in Animal Ecology and Conservation: What’s Next? 262
14.1 Introduction 262
14.2 Uses of Camera Trap Data 262
14.3 Camera Trap Equipment and Photographic Data 264
14.4 Statistical Inference Methods 265
14.4.1 Abundance and Density 265
14.4.2 Occupancy 267
14.4.3 Species Richness 269
14.5 Conclusions 269
References 270
Index 273