Camera Trapping for Wildlife Research

By Luigi Boitani

Camera trapping is a powerful and now widely used tool in scientific research on wildlife ecology and management. It provides a unique opportunity for collecting knowledge, investigating the presence of animals, or recording and studying behaviour. Its visual nature makes it easy to successfully convey findings to a wide audience.

This book provides a much-needed guide to the sound use of camera trapping for the most common ecological applications to wildlife research. Each phase involved in the use of camera trapping is covered:

- Selecting the right camera type
- Set-up and field deployment of your camera trap
- Defining the sampling design: presence/absence, species inventory, abundance; occupancy at species level; capture-mark-recapture for density estimation; behavioural studies; community-level analysis
- Data storage, management and analysis for your research topic, with illustrative examples for using R and Excel
- Using camera trapping for monitoring, conservation and public engagement.

Each chapter in this edited volume is essential reading for students, scientists, ecologists, educators and professionals involved in wildlife research or management.

• Language: English
• Publisher: Pelagic Publishing
• Release date: Jun 18, 2016
• ISBN: 9781784270643

Book preview

Camera Trapping for Wildlife Research

Camera Trapping for Wildlife Research

Edited by

Francesco Rovero and Fridolin Zimmermann

DATA IN THE WILD

Pelagic Publishing | www.pelagicpublishing.com

Published by Pelagic Publishing

www.pelagicpublishing.com

PO Box 725, Exeter EX1 9QU, UK

Camera Trapping for Wildlife Research

ISBN 978-1-78427-048-3 (Pbk)

ISBN 978-1-78427-063-6 (Hbk)

ISBN 978-1-78427-064-3 (ePub)

ISBN 978-1-78427-065-0 (Mobi)

ISBN 978-1-78427-066-7 (PDF)

Copyright © 2016 Francesco Rovero and Fridolin Zimmermann

This book should be cited as Rovero, F. and Zimmermann, F. (2016) Camera Trapping for Wildlife Research. Exeter: Pelagic Publishing, UK.

All rights reserved. No part of this document may be produced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise without prior permission from the publisher. While every effort has been made in the preparation of this book to ensure the accuracy of the information presented, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Pelagic Publishing, its agents and distributors will be held liable for any damage or loss caused or alleged to be caused directly or indirectly by this book.

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A catalogue record for this book is available from the British Library.

The data in this book belong to the authors of the corresponding chapters and any further analyses or publications should not be undertaken without the approval of the authors.

RECONYX and Hyperfire are trademarks of RECONYX Inc., for more information visit www.reconyx.com. Cuddeback is a trademark of Non Typical, Inc., for more information visit www.http://cuddeback.com. ArcGis is a trademark of Esri Inc., for more information visit http://www.esri.com. Excel is a trademark of the Microsoft Corporation, for more information visit www.microsoft.com.

Cover image: Leopard (Panthera pardus) camera trapped in lowland rainforest in the Udzungwa Mountains of Tanzania (Rasmus Gren Havmøller and Francesco Rovero).

Contents

About the editors

About the contributors

Foreword

Preface

Acknowledgements

Online resources

1. Introduction

Francesco Rovero and Fridolin Zimmermann

1.1 A brief history of camera trapping

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

2. Camera features related to specific ecological applications

Francesco Rovero and Fridolin Zimmermann

2.1 Introduction

2.2 Camera trap systems

2.3 Camera features to consider when choosing models

2.4 Camera performance in relation to study designs

2.4.1 Faunal inventories

2.4.2 Occupancy studies (species and community-level)

2.4.3 Capture–recapture

2.4.4 Behavioural studies

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

2.6 Limitations and future developments of camera technology

3. Field deployment of camera traps

Fridolin Zimmermann and Francesco Rovero

3.1 Pre-field planning

3.2 Setting camera traps in the field

3.2.1 Site selection and placement

3.2.2 Trail settings

3.2.3 Checklist of actions to activate the camera trap

3.2.4 Checking and retrieving camera traps

3.2.5 Checklist of actions when checking and removing the camera trap

3.3 After the fieldwork

4. Camera trap data management and interoperability

Eric Fegraus and James MacCarthy

4.1 Introduction

4.2 Camera trap data

4.2.1 Camera trap conceptual components

4.3 Managing camera trap data: Wild.ID

4.3.1 Setting up a camera trap project

4.3.2 Processing camera trap data

4.3.3 Retrofitting legacy camera trap data

4.3.4 Additional camera trap data management tools

4.4 Camera trap data interoperability

4.5 Wildlife Insights – the camera trap data network

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

5. Presence/absence and species inventory

Francesco Rovero and Daniel Spitale

5.1 Introduction

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

5.3 Sampling design

5.4 Sampling completeness

5.5 Case study

5.5.1 Raw data format (.CSV file)

5.5.2 Importing data in R

5.5.3 Deriving sampling effort, events and species’ list

5.5.4 Naïve occupancy

5.5.5 Species accumulation

5.5.6 Activity pattern

5.5.7 Presentation and interpretation of results

5.6 Conclusions

6. Species-level occupancy analysis

Francesco Rovero and Daniel Spitale

6.1 Introduction

6.2 Theoretical framework and modelling approach

6.2.1 Basic single-season model

6.2.2 Covariate modeling and assessing model fit

6.2.3 Multi-season occupancy models

6.3 Sampling design

6.4 Survey effort and sampling completeness

6.4.1 Deciding the best number of sites and sampling duration

6.4.2 Post-hoc discretisation of sampling duration in sampling occasions

6.5 Case study

6.5.1 Single-season occupancy analysis

6.5.2 Multi-season occupancy analysis

6.6 Conclusions

7. Capture–recapture methods for density estimation

Fridolin Zimmermann and Danilo Foresti

7.1 Introduction

7.2 Equipment and field practices

7.2.1 Camera traps

7.2.2 Focal species and other members of its guild

7.2.3 Camera trap sites and camera trap placement

7.3 Survey design

7.3.1 Season, survey duration and demographic closure

7.3.2 Spatial sampling and geographic closure

7.4 Case study: the Eurasian lynx

7.4.1 Analytical steps during field work

7.4.2 Dates and times in R

7.4.3 Analysis with secr

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

7.5 Conclusions

8. Behavioural studies

Fridolin Zimmermann, Danilo Foresti and Francesco Rovero

8.1 Introduction

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

8.3 Application of camera trapping in behavioural studies

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

8.5 Diel activity pattern and activity pattern overlap between species

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

8.5.2 Overlap between pairs of activity patterns

8.6 Case studies

8.6.1 Marking behaviour studies in Eurasian lynx and brown bear

8.6.2 Comparison of activity patterns

8.7 Conclusions

9. Community-level occupancy analysis

Simone Tenan

9.1 Introduction

9.2 Measuring biodiversity while accounting for imperfect detection

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

9.3.1 Case study

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

9.4.1 Case study

9.5 Conclusions

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

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

10.1 Introduction

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

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

10.2.2 Goals and targets of a national monitoring system for wildlife

10.2.3 Design of a national monitoring system

10.2.4 Implementation

10.2.5 Cost components

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

10.3.1 African golden cats in Bwindi Impenetrable Forest, Uganda

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

10.4 Conclusions

11. Camera traps and public engagement

Paul Meek and Fridolin Zimmermann

11.1 Introduction

11.2 Principles in citizen science

11.2.1 Categories of public participation in scientific research

11.2.2 General approaches to programme development

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

11.3.1 Data collection and identification

11.3.2 Data management and cyber-infrastructure

11.4 Examples of camera trap citizen science projects

11.5 What is the future of citizen science camera trapping?

11.5.1 Training

11.5.2 Data integrity

11.5.3 Motivation, engagement and retention in citizen science

11.5.4 Cultural sensitivity and privacy

11.5.5 Technology and e-innovations in camera trapping

11.6 Conclusions

Appendices

Glossary

Index

About the editors

Francesco Rovero ([e-mail]) is an ecologist and conservation scientist with a PhD in animal ecology. He is currently the Curator for Tropical Biodiversity at MUSE – Science Museum in Trento, Italy. He has conducted ecological research since the early 2000s on tropical rainforest mammals and made extensive use of camera trapping for his research, with focus on ecological modelling and applications of this tool to the long-term monitoring of species and communities. In 2005 he discovered, using camera traps, a new species of mammal, the grey-faced sengi or elephant shrew, in the remote forests of the Udzungwa Mountains in Tanzania. He has also been involved in camera trapping studies on large mammals in the eastern Alps, the Amazon and Mongolia.

Fridolin Zimmermann ([e-mail]) is a carnivore conservation scientist with a PhD on Eurasian lynx conservation and ecology. He is currently coordinator of the large carnivore monitoring in Switzerland at Carnivore Ecology and Wildlife Management (KORA). He made extensive use of camera trapping for his research, since 2002 focusing mainly on abundance and density estimations of Eurasian lynx in different reference areas across Switzerland. He provided his expertise in several Eurasian lynx camera trapping projects abroad, including the Bavarian forest, Scandinavia, the Balkans, the Carpathian Mountains, southwestern Asia and the Himalayas. He has also been involved in Eurasian lynx radiotelemetry projects in the Jura Mountains and northwestern Swiss Alps and live captures of animals for translocation programmes.

About the contributors

Jorge A. Ahumada, Tropical Ecology, Assessment & Monitoring Network, Conservation International, 2011 Crystal Drive, Suite 500, Arlington, VA 22202 USA ([e-mail]). Jorge is an ecologist by training and the Executive Director of the Tropical Ecology Assessment and Monitoring Network (TEAM) at Conservation International.

Eric Fegraus, Tropical Ecology, Assessment & Monitoring Network, Conservation International, 2011 Crystal Drive, Suite 500, Arlington, VA 22202 USA ([e-mail]). Eric has a hybrid environmental and IT background and is interested in the design and development of technical tools and products relevant to the natural and social sciences.

Danilo Foresti, Ufficio della caccia e della pesca, Repubblica e Canton Ticino, Via F. Zorzi 13, 6500 Bellinzona, Switzerland; KORA, Thunstrasse 31, 3074 Muri bei Bern, Switzerland ([e-mail]). Danilo is a research assistant in the public administration of Ticino, Switzerland. His professional activity includes the management of fishery resources, the restoration of aquatic habitats and the monitoring of terrestrial wildlife.

Johanna Hurtado Astaiza, Organization for Tropical Studies, La Selva Biological Station, 676-2050 Puerto Viejo de Sarapiqui, Costa Rica ([e-mail]). Johanna is a conservation biologist and the TEAM Costa Rican Site manager. Her research focus is on terrestrial vertebrate monitoring and management.

James MacCarthy, Tropical Ecology, Assessment & Monitoring Network, Conservation International, 2011 Crystal Drive, Suite 500, Arlington, VA 22202 USA ([e-mail]). Jimmy is a conservation biologist and data manager that is interested in improving conservation decisions through the use of science and technology.

Paul Meek, New South Wales Department of Primary Industries, University of New England, Suite 5, Level 1, Coffs Harbour, NSW, Australia. ([e-mail]). Paul is a terrestrial ecologist with an interest in vertebrate pest management, his research focus is on Australian predator ecology and population monitoring techniques.

Badru Mugerwa, Institute of Tropical Forest Conservation (ITFC), Mbarara University of Science and Technology (MUST), Mbarara, Uganda, PO Box. 44, Kabale, Uganda; Department of Biology, Western University, 1151 Richmond Street, London, Ontario, Canada, N6A 5B7; Wildlife Conservation Research Unit (WildCRU), University of Oxford, UK. The Recanati-Kaplan Center, Tubney House, Abingdon Road, Tubney, Abingdon OX13 5QL, UK ([e-mail]). Badru is a conservation biologist whose research investigates the role of human presence/activity on wildlife behavior and their conservation in human-dominated landscapes.

Timothy G. O’Brien, Wildlife Conservation Society, Bronx, NY 10460 ([e-mail]). Tim is an ecologist and statistician with a wide range of interests, including hornbills, large cats, and monitoring of mammal communities.

Daniel Spitale, Tropical Biodiversity Section, MUSE – Museo delle Scienze, Corso del Lavoro e della Scienza 3, 38122 Trento Italy ([e-mail]). Daniel is an ecologist with broad interests including statistic, bryology, limnology, biogeography and community ecology. He is both a freelance researcher working for different institutions and an environmental consultant.

Simone Tenan, Vertebrate Zoology Section, MUSE – Museo delle Scienze, Corso del Lavoro e della Scienza 3, 38122 Trento Italy ([e-mail]). Simone is a quantitative ecologist focused on ecological applications in the general areas of population dynamics, community ecology, and conservation biology.

Foreword

Whether you are trying to assess the population abundance of an elusive mammal or you are chasing evidence of the presence of a very rare species, it is likely that the level of frustration will run high as you try to read the environment for signs, tracks, sounds and other clues of the species’ presence. No matter how good we are as field biologists or trackers, our capacity to read the environment is often extremely limited. Even when we manage to infer the presence of a species, we are likely to remain frustrated by the weakness of the indirect evidence provided by a sign and its sporadic occurrence. Clearly, it is difficult to build a robust sampling scheme on this sort of scanty information. Reading animal signs in the field is an art built with experience and practice. The hunters of traditional societies such as the pygmies of the Congo basin or the Yanomami in the Orinoco/Amazon region can often ‘see’ an animal (age, sex, behaviour) from insignificant signs as if the real animal had been observed and photographed. Even if we were good trackers like those hunters, we would remain unable to design a scientifically sound sampling scheme.

Camera traps are the new tools available to field biologists providing eyes wherever we wish to have them, for any time and under any condition. They give us access to a wealth of information that was largely inaccessible using the old invasive and noninvasive techniques of species detection. Camera traps have dramatically revolutionised field biology. We need to go back to the history of radiotelemetry, its first attempts in the 1960s and its recent technological flourishing, to find a parallel of discovery and development. Radiotelemetry suddenly enabled the study of animal movements that had remained inaccessible to other field techniques and provided biologists with a simple method to track elusive animals in any habitat type and under any climatic conditions. Camera trapping is equally revolutionary and field biology will no longer be the same as this method gains in technical improvements and is supported by a wealth of analytical tools.

This book is exactly what all field biologists need to have to learn about the current state of development of the technique, its main applications and the type of data that can be obtained. Not all applications are straightforward; some are very complex and need to be used with much attention to the underlying assumptions and caveats, especially those aimed at assessing abundance and occupancy. The eruption in the number of scientific papers based on camera traps is the best evidence of the refreshing flow of datasets and hypotheses that biologists have been able to build using this tool.

However, there is more than science that is benefiting from camera traps. Probably the most important outcome of the use of this new technique is the enormous contribution to biodiversity conservation. From searching for rare species, to assessing population trends and sizes, to long-term monitoring of population status, camera traps are a precious tool that has allowed us to collect a new wealth of data critical for conservation assessment and planning. In this book, there are many examples of new species and rare species found using camera traps, an invaluable support to the efforts to identify critical areas for conservation.

The authors are among the foremost world authorities in using camera trapping both for scientific research and for conservation applications. They have produced a book planned and written to explain the details of the technique to novices and experts. It is not a textbook but a real handbook that guides users through all the steps, from choosing the right camera to designing a sampling scheme depending on the objective, to collecting, organising and analysing data. I expect this book to be a primary source of inspiration and guide to the correct use of camera trapping. As such, it is a precious contribution to conservation.

Prof. Luigi Boitani

University of Rome Sapienza

Preface

It is widely acknowledged that scientific progress has relied on new technology as much as on new ideas to observe nature in the attempt to understand its processes. In the context of the study of wildlife, it is not an exaggeration to consider the subject of this book – camera trapping, the use of automatic cameras taking images of passing animals – as a milestone technology that has advanced the field. Indeed, the use of camera traps has introduced a completely new way to detect wildlife and has led to major discoveries, among which are the discoveries of new species of mammals. An added value of camera trapping is represented by the powerful communicative message of the images themselves: striking ‘moments’ of elusive and rare fauna from anywhere in the planet that can be used to boost conservation awareness worldwide. Indeed several NGOs and conservation agencies have adopted this tool for outreach programmes via the Web and social media. Similarly, camera trapping is emerging as a powerful tool in citizen science, encouraging participation by community members and groups to contribute to the collection of ecological data in their landscapes.

The wide application of camera trapping in science, along with its popularity, has concomitantly raised the need for guidance on the sound use of this tool, from selecting the right camera type among the vast and diverse range of models available on the market, to determine the sampling design, and analysing data potentially using inferential approaches. The importance of such guidance is enhanced by the fact that camera trapping became a very attractive and perhaps even trendy tool; however, it is not obviously always the best method for studying wildlife. As with any other research tools, a clear vision of the research question must precede the choice of the most adequate methodology that enables the scientific question to be answered. Moreover, there is growing integration of camera trapping with different, complementary methodologies (genetic sampling, telemetry, etc.).

On these grounds, this book aims to address comprehensively the multitude of phases involved in the use of camera trapping for scientific research and ecological inference, hence it covers topics from choosing the suitable camera trap model to defining the sampling design, and from the field deployment of camera traps to data management and data analysis for a selection of major types of studies. These latter two steps, and especially data management, are particularly overlooked in the current literature and yet are very relevant given the impressive growth in data collected by modern, digital camera traps. It is precisely the combination of these various and equally important topics into one volume that makes this book unique in the current literature.

The book addresses in great detail the key and most common ecological applications to wildlife research (species’ inventory, occupancy, capture–recapture, community assessment, behavioural studies). While it deliberately does not attempt to present the full array of applications of camera trapping, we believe the knowledge provided to implement these major applications will provide researchers with the fundamental skills for a broader range of uses.

The target spectrum of readers is accordingly comprehensive: students, scientists and professionals involved in wildlife research and management.

Francesco Rovero and Fridolin Zimmermann

Acknowledgements

The editors are sincerely grateful to all contributors who joined this project with such enthusiasm and devoted their time to make the book as comprehensive and advanced as possible. They are also grateful to the external reviewers for their valuable comments on selected chapters, and to Professor Luigi Boitani for the foreword.

Francesco Rovero wishes to thank Nigel Massen of Pelagic Publishing, who proposed the book project to him in the first place, and to Fridolin Zimmermann for accepting with enthusiasm to co-edit it, hence embarking on a very fruitful, friendly and enlightening collaboration. He is also grateful to several colleagues who over the years have collaborated on camera trapping projects in Tanzania and elsewhere on the planet, from South America to Mongolia. Among these are Duccio Berzi and Gianluca Serra, ‘pioneers’ of camera trapping in Italy; Jim Sanderson for his visit in 2002 to the Udzungwa Mountains that triggered years of camera trapping to come, and Trevor Jones for collaborating since the very first camera traps in those forests were set; and Sandy Andelman and Jorge Ahumada for their support in establishing and running a TEAM Network site in the Udzungwa. A big thanks also goes to several collaborators and field technicians who worked on camera trapping projects in Tanzania for more than a decade, especially Emanuel Martin, Arafat Mtui and Ruben Mwakisoma. The making of the book occupied many working hours and Francesco wishes to thank the Director of MUSE – Museo delle Scienze (Trento, Italy), Michele Lanzinger, for being always supportive of his work; this project also took a lot of evenings of family time, and for these much gratitude goes to Claudia.

Fridolin Zimmermann is very grateful to Francesco Rovero for inviting him on this co-editing and writing adventure, as well as for his friendship, availability, great efficiency and competence. All this has contributed to a very enriching experience. He is also beholden to Francesco and Claudio Augugliaro for giving him the opportunity to spend two weeks in Mongolia to set camera traps for snow leopards, which gave him fresh (Mongolian) air and new motivation for the last stage of book writing. Special thanks to Urs and Christine Breitenmoser, heads of Carnivore Ecology and Wildlife Management (KORA), for their trust over the years, and to all members of the KORA team, game-wardens and volunteers involved in lynx monitoring in Switzerland over the years. He is indebted to several colleagues for stimulating ideas and discussions during camera trapping projects, meetings and workshops, especially Paul Meek, André Pittet, Stefan Suter and Kirsten Weingarth. He is grateful to the Federal Office for the Environment (FOEN), especially Reinhard Schnidrig and Caroline Nienhuis, and the cantonal hunting administrations for supporting lynx monitoring over the years. Finally, Fridolin thanks his family and friends, and especially his wife Laure, for support of all kinds and understanding, and for bearing the burden of this book for too many months.

Online resources

Free resources are available online to support your use of this book. Please visit:

http://www.pelagicpublishing.com/camera-trapping-for-wildlife-research-resources.html

1. Introduction

Francesco Rovero and Fridolin Zimmermann

Camera trapping is the use of remotely triggered cameras that automatically take images and/or videos of animals or other subjects passing in front of them. This technology is changing rapidly, largely driven by market demands in the northern hemisphere, with a large proportion of the buyers being recreational hunters. The majority of commercially available camera trap models are passive infrared digital cameras triggered by an infrared sensor detecting a differential in heat and motion between the background temperature and a moving subject, such as animals, people, or even a vehicle, passing in front of them (see Chapter 2). Camera trapping as a scientific tool is widely used across the globe especially to study medium-to-large terrestrial mammals and birds, but is increasingly being also applied to other faunal targets, for example arboreal mammals (e.g. Goldingay et al. 2011), semi-aquatic mammals (e.g. river otter Lontra canadensis; Stevens et al. 2004), small mammals (e.g. Oliveira-Santos et al. 2008) and herpetofauna (e.g. Pagnucco et al. 2011). Moreover, a new type of underwater camera trap was recently designed (Williams et al. 2014) using stereo-cameras, which greatly increase the amount of quantitative data that can be extracted from images (i.e. fish size, position and orientation). The first underwater tests have successfully illustrated the potential of this technology to reveal new insights into marine organisms.

Over the last 15 years, and in particular since 2006, there has been an exponential increase in the number of published scientific studies that used camera trapping. The number of publications per year that used camera trapping increased from less than 50 during 1993–2003 to more than 200 during 2004–2014 with a relative peak of 234 in 2012 (Figure 1.1). This vast and impressive increment in the use of this tool has been accompanied by the widening of wildlife research applications, from basic faunal inventories to focal species studies, from behavioural studies to advanced, inferential studies in numerical ecology (Rovero et al. 2010; O’Connell et al. 2011; Meek et al. 2012; McCallum 2013; reviews in Rovero et al. 2013; Royle et al. 2013a).

1.1 A brief history of camera trapping

We briefly review the key steps in the advent of camera trapping since its first applications; more detailed accounts of the history of camera trapping can be found elsewhere (Sanderson and Trolle 2005; Kucera and Barrett 2011).

Figure 1.1 The number of camera trap articles published per year according to Web of Science queries for research domains ‘sciences technology’ and research areas ‘zoology’ and topics ‘camera trap’, ‘infrared triggered camera’, ‘trail camera’, ‘automatic camera’, ‘photo trap’, ‘remotely triggered camera’ and ‘remote camera’.

Camera trapping was invented in the late 1890s by George Shiras III, a lawyer and passionate naturalist who perfected a way of photographing wildlife at night with a large-format camera and a hand-operated flash. Shiras soon gained considerable acclaim for his stunning night photographs of deer and other animals (Sanderson and Trolle 2005). The first camera trap photos were taken when Shiras set up his camera so that he could take a picture remotely by pulling on a long trip-wire. Eventually, he arranged the trip-wire so that an animal triggered the camera, hence taking its own pictures. His articles in the National Geographic Magazine from 1906 to 1921 created considerable interest in wildlife photography (Shiras 1913). Subsequently, in the late 1920s, Shiras taught Frank M. Chapman (then Curator of Ornithology at the American Museum of Natural History in New York) how to use camera traps for his research work in the tropical rainforest of Barro Colorado Island in Panama. Chapman used Shiras’s camera traps to capture images of the diverse and, at that time, poorly known fauna, including tapirs (Tapirus bairdii), ocelots (Leopardus pardalis) and pumas (Puma concolor). For many years, Chapman was one of the few researchers to use camera traps.

Several decades passed before researchers rediscovered camera traps as a tool, and Seydack (1984) was probably the first to use automatic camera traps to study rainforest mammals. He collected data for inventorying species as well as to estimate bushbuck abundance and identify individual leopards in Africa. Griffiths and van Schaik (1993) used camera traps to study rainforest mammals in Indonesia, and realised the potential of this method to detect species’ presence and to study the behaviour, activity patterns and abundance of elusive mammals (Griffiths and van Schaik 1993; van Schaik and Griffiths 1996). Meanwhile, Karanth begun to use camera traps to identify individual tigers in Nagarahole National Park, India (Karanth 1995). His success with applying capture–recapture models to estimate population density from camera trap data (Karanth and Nichols 1998) led the way for camera trapping coupled with inferential statistics to become a powerful methodology for wildlife research.

Hunters, especially in the USA, began using camera traps in the late 1980s to search for trophy deer and other big-game species. This created a small industry resulting in an increasing range of camera trap models spanning a range of prices. At the same time, technology advanced quickly and modern camera traps soon became relatively small, waterproof plastic enclosures integrating all essential parts into one system (infrared sensor, digital camera, and flash).

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

Camera trapping is considered a non-invasive method that generally causes a minimum of disturbance to the study animals. While the presence of camera traps, the noise in the ultra-infrasonic range emitted by some models (Rovero et al. 2013; Meek et al. 2014), the smell signature of humans on the unit (Muñoz et al. 2014) and the flash (see below and Chapter 2 for details) could potentially modify the behaviour of passing animals, these potential sources of disturbance are clearly not comparable to those from faunal detection methods that require trapping and handling of animals. The majority of camera models and study types deploy LED flashes, which produce a red glow that is more or less visible to animals depending on the camera model (but see Chapter 2 for details); xenon white flashes, in contrast, produce an instantaneous and intense white light. The potential disturbance to animals of these types of flashes is discussed in the specific study designs (Chapters 5–9).

Camera traps work day and night and can be left unattended in the field for several weeks and even months. Such automatism not only allows for intensive and prolonged data collection over large and potentially remote areas, but makes the traps suited to study animals that are rare, elusive, and only live in remote areas. Camera trapping has also proved more efficient at detecting diurnal species compared to line transects as sighting rates with the latter may be too low, making robust assessments difficult and/or not cost efficient (e.g. Rovero and Marshall 2009).

The vital advantage of camera trapping in comparison to indirect methods used to record the presence of medium-sized to large terrestrial mammals (e.g. dung and track counts) is that photographs provide objective records (‘hard fact’), or evidence, of an animal’s presence and enable identification of the species. In addition, camera trapping provides information on activity pattern (from the day and time imprinted in the image) and species coexistence (Monterroso et al. 2014), on behaviour, and on the pelage characteristics that in turn can enable individual identification (see Chapter 7).

Taken together, these aspects make camera trapping a cost-efficient method for faunal detection in spite of the initial capital investment needed to purchase the equipment (e.g. Silveira et al. 2003; Rovero and Marshall 2009; De Bondi et al. 2010). Importantly, moreover, they make camera trapping relatively easy to deploy, and hence highly suitable to standardisation, as shown, for example, by the Tropical Ecology, Assessment and Monitoring (TEAM) network (http://www.teamnetwork.org), which implements a protocol of intensive sampling of terrestrial vertebrates simultaneously in (currently) 17 sites across the tropics.

The high efficiency of camera trapping to inventory communities of medium to large, predominantly terrestrial mammals and birds has been shown by a number of studies. For example, camera trapping involving a survey effort of 1,035–3,400 camera trap days detected 57–86% of the total number of species known to exist in the respective community of tropical forest mammals (review in Rovero et al. 2010; Rovero et al. 2014). An assessment of carnivores in the Udzungwa Mountains of Tanzania detected 15 species through camera trapping while only 9 were detected through other methods (observations, road killings, scats, and other signs; De Luca and Mpunga 2005). In a grassland area in central Brazil, Silveira et al. (2003) found camera trapping to be the most appropriate method for mammal inventory in all environmental conditions, allowing for rapid assessment of the community and its conservation status.

Camera trapping has also been instrumental in discovering new species, such as the giant sengi, or elephant-shrew Rhynchocyon udzungwensis discovered in Tanzania in 2005 (Rovero and Rathbun 2006) or the hairy-nosed otter Lutra sumatrana from Sabah, that had been deemed extinct. Similarly, camera trapping continues to reveal new range records of elusive species (e.g. Jackson’s mongoose Bdeogale jacksoni and Abbott’s duiker Cephalophus spadix in montane forests of Tanzania: Rovero et al. 2005; De Luca and Rovero 2006) and documents the expansion of species into new areas (e.g. Amur leopard Panthera pardus orientalis in China, golden jackal Canis aureus in Switzerland; Figure 1.2).

Several recent studies have compared the efficiency of capture–recapture studies to estimate the density of naturally marked animals (see Chapter 7) based on camera trapping versus genetic identification of scats. Hence, Janecka et al. (2011) conducted snow leopard (Panthera uncia) surveys in the Gobi Desert of Mongolia and showed that the abundance estimated from non-invasive genetic surveys was inflated because of methodological (i.e. inability to age and thus exclude juveniles, inadequate sampling strategy, the persistence of scat in cold, dry environments making it difficult to differentiate older from recent scats) and biological reasons (i.e. deposition of scats by multiple snow leopards on common sites). Similarly Anile et al. (2014) studied the wildcat (Felis silvestris silvestris) in Italy and found that spatially explicit capture–recapture analyses based on scat collection gave the highest and also less precise density estimates because of the lower number of captures and recaptures compared to camera trapping.

The efficiency of camera trapping for estimating the density and abundance of naturally marked and territorial animals through capture–recapture analysis is such that this approach replaces telemetry, one of the traditional methods used to estimate density through determining home range size (e.g. Karanth and Nichols 1998; Zimmermann et al. 2013; Anile et al. 2014). Telemetry requires trapping of animals for collaring, and following a representative proportion of the population is highly time consuming; therefore telemetry, unlike camera trapping-based density estimation, does not enable a rapid assessment of the population size, which might in fact change over the course of capture campaign.

Even though attempts have been made to use camera trapping to estimate home range size (e.g. Gil-Sánchez et al. 2011), bio-logging (i.e. the use of miniaturised animal-attached tags for logging and/or relaying of data about an animal’s movements, behaviour, physiology and/or environment; Rutz and Hays 2009), which includes telemetry, is