Contents

About the editors

About the contributors

Foreword

Preface

Acknowledgements

Online resources

1.Introduction

Francesco Rovero and Fridolin Zimmermann

1.1A brief history of camera trapping

1.2Efficiency of camera trapping and advantages over other wildlife detection methods

2.Camera features related to specific ecological applications

Francesco Rovero and Fridolin Zimmermann

2.1Introduction

2.2Camera trap systems

2.3Camera features to consider when choosing models

2.4Camera performance in relation to study designs

2.4.1Faunal inventories

2.4.2Occupancy studies (species and community-level)

2.4.3Capture–recapture

2.4.4Behavioural studies

2.5Review of currently available camera trap models and comparative performance tests

2.6Limitations and future developments of camera technology

3.Field deployment of camera traps

Fridolin Zimmermann and Francesco Rovero

3.1Pre-field planning

3.2Setting camera traps in the field

3.2.1Site selection and placement

3.2.2Trail settings

3.2.3Checklist of actions to activate the camera trap

3.2.4Checking and retrieving camera traps

3.2.5Checklist of actions when checking and removing the camera trap

3.3After the fieldwork

4.Camera trap data management and interoperability

Eric Fegraus and James MacCarthy

4.1Introduction

4.2Camera trap data

4.2.1Camera trap conceptual components

4.3Managing camera trap data: Wild.ID

4.3.1Setting up a camera trap project

4.3.2Processing camera trap data

4.3.3Retrofitting legacy camera trap data

4.3.4Additional camera trap data management tools

4.4Camera trap data interoperability

4.5Wildlife Insights – the camera trap data network

4.6The future: more repositories, better data management and analytical services

5.Presence/absence and species inventory

Francesco Rovero and Daniel Spitale

5.1Introduction

5.2Raw descriptors: naïve occupancy and detection rate as a relative abundance index

5.3Sampling design

5.4Sampling completeness

5.5Case study

5.5.1Raw data format (.CSV file)

5.5.2Importing data in R

5.5.3Deriving sampling effort, events and species’ list

5.5.4Naïve occupancy

5.5.5Species accumulation

5.5.6Activity pattern

5.5.7Presentation and interpretation of results

5.6Conclusions

6.Species-level occupancy analysis

Francesco Rovero and Daniel Spitale

6.1Introduction

6.2Theoretical framework and modelling approach

6.2.1Basic single-season model

6.2.2Covariate modeling and assessing model fit

6.2.3Multi-season occupancy models

6.3Sampling design

6.4Survey effort and sampling completeness

6.4.1Deciding the best number of sites and sampling duration

6.4.2Post-hoc discretisation of sampling duration in sampling occasions

6.5Case study

6.5.1Single-season occupancy analysis

6.5.2Multi-season occupancy analysis

6.6Conclusions

7.Capture–recapture methods for density estimation

Fridolin Zimmermann and Danilo Foresti

7.1Introduction

7.2Equipment and field practices

7.2.1Camera traps

7.2.2Focal species and other members of its guild

7.2.3Camera trap sites and camera trap placement

7.3Survey design

7.3.1Season, survey duration and demographic closure

7.3.2Spatial sampling and geographic closure

7.4Case study: the Eurasian lynx

7.4.1Analytical steps during field work

7.4.2Dates and times in R

7.4.3Analysis with secr

7.4.4Abundance and density estimation in conventional (i.e. non-spatial) capture–recapture models

7.5Conclusions

8.Behavioural studies

Fridolin Zimmermann, Danilo Foresti and Francesco Rovero

8.1Introduction

8.2Advantages and disadvantages of camera trapping compared to other technologies used to study animal behaviour

8.3Application of camera trapping in behavioural studies

8.4The importance of choosing the site in relation to a variety of study aims

8.5Diel activity pattern and activity pattern overlap between species

8.5.1Definition and assumptions of the activity level measured by means of camera traps

8.5.2Overlap between pairs of activity patterns

8.6Case studies

8.6.1Marking behaviour studies in Eurasian lynx and brown bear

8.6.2Comparison of activity patterns

8.7Conclusions

9.Community-level occupancy analysis

Simone Tenan

9.1Introduction

9.2Measuring biodiversity while accounting for imperfect detection

9.3Static (or single-season) multi-species occupancy models

9.3.1Case study

9.4Dynamic (or multi-season) multi-species occupancy models

9.4.1Case study

9.5Conclusions

10.Camera trapping as a monitoring tool at national and global levels

Jorge A. Ahumada, Timothy G. O’Brien, Badru Mugerwa and Johanna Hurtado

10.1Introduction

10.2A national monitoring system for wildlife: from idea to a functioning system

10.2.1A global model for national monitoring: The TEAM Camera Trap Network

10.2.2Goals and targets of a national monitoring system for wildlife

10.2.3Design of a national monitoring system

10.2.4Implementation

10.2.5Cost components

10.3How a wildlife monitoring system can improve protected area effectiveness: examples from the TEAM Network

10.3.1African golden cats in Bwindi Impenetrable Forest, Uganda

10.3.2Effects of hunting at the Volcán Barva transect, Costa Rica

10.4Conclusions

11.Camera traps and public engagement

Paul Meek and Fridolin Zimmermann

11.1Introduction

11.2Principles in citizen science

11.2.1Categories of public participation in scientific research

11.2.2General approaches to programme development

11.3Citizen science research process with a special focus on camera trapping studies

11.3.1Data collection and identification

11.3.2Data management and cyber-infrastructure

11.4Examples of camera trap citizen science projects

11.5What is the future of citizen science camera trapping?

11.5.1Training

11.5.2Data integrity

11.5.3Motivation, engagement and retention in citizen science

11.5.4Cultural sensitivity and privacy

11.5.5Technology and e-innovations in camera trapping

11.6Conclusions

Appendices

Glossary

Index