Recommended guiding principles for reporting on camera trapping research

Abstract

Camera traps are used by scientists and natural resource managers to acquire ecological data, and the rapidly increasing camera trapping literature highlights how popular this technique has become. Nevertheless, the methodological information reported in camera trap publications can vary widely, making replication of the study difficult. Here we propose a series of guiding principles for reporting methods and results obtained using camera traps. Attributes of camera trapping we cover include: (i) specifying the model(s) of camera traps(s) used, (ii) mode of deployment, (iii) camera settings, and (iv) study design. In addition to suggestions regarding best practice data coding and analysis, we present minimum principles for standardizing information that we believe should be reported in all peer-reviewed papers. Standardised reporting enables more robust comparisons among studies, facilitates national and global reviews, enables greater ease of study replication, and leads to improved wildlife research and management outcomes.

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References

  1. Ahumada JA, Silva CEF, Gajapersad K, Hallam C, Hurtado J, Martin E, Mcwilliam A, Mugerwa A, O’Brien T, Rovero F, Sheil D, Spironello WR, Winarni N, Andelman SJ (2011) Community structure and diversity of tropical forest mammals: data from a global camera trap network. Philos Trans R Soc B 366:2703–2711

    Article  Google Scholar 

  2. Arzberger P, Schroeder P, Beaulieu A, Bowker G, Casey K, Laaksonen L, Moorman D, Uhlir P, Wouters P (2004) An international framework to promote access to data. Science 303:1777–1778

    PubMed  Article  Google Scholar 

  3. Bengsen A, Butler J, Masters P (2011) Estimating and indexing feral cat population abundances using camera traps. Wildl Res 38:732–739

    Article  Google Scholar 

  4. Breitenmoser U, Breitenmoser-Würsten C, Molinari P, Ryser A, von Arx M, Molinari-Jobin A, Zimmermann F, Siegenthaler A, Angst C, Weber J (2005) Balkan lynx field book. KORA and Cat Specialist Group

  5. Carthew SM, Slater E (1991) Monitoring animal activity with automated photography. J Wildl Manag 55:689–692

    Article  Google Scholar 

  6. Cassey P, Blackburn TM (2006) Reproducibility and repeatability in ecology. Bioscience 56:958–959

    Article  Google Scholar 

  7. Caughley G, Sinclair ARE (1994) Wildlife ecology and management. Blackwell Science, Oxford

  8. Claridge AW, Misfud G, Dawson J, Saxon MJ (2004) Use of infrared digital cameras to investigate the behaviour of cryptic species. Wildl Res 31:645–650

    Article  Google Scholar 

  9. Claridge AW, Paull DJ, Barry SC (2010) Detection of medium-sized ground-dwelling mammals using infrared digital cameras: an alternative way forward? Aust Mammal 32:165–171

    Article  Google Scholar 

  10. Cutler TL, Swann DE (1999) Using remote photography in wildlife ecology: a review. Wildl Soc Bull 27:571–581

    Google Scholar 

  11. De Bondi N, White JG, Stevens M, Cooke R (2010) A comparison of the effectiveness of camera trapping and live trapping for sampling terrestrial small-mammal communities. Wildl Res 37:456–465

    Article  Google Scholar 

  12. Engeman RM (2005) Indexing principles and a widely applicable paradigm for indexing animal populations. Wildl Res 32:203–210

    Article  Google Scholar 

  13. Fegraus EH, Lin K, Ahumada JA, Baru C, Chandra S, Youn C (2011) Data acquisition and management software for camera trap data: a case study from the TEAM Network. Ecol Inform 6:345–353

    Article  Google Scholar 

  14. Gerber B, Karpanty S, Kelly M (2012) Evaluating the potential biases in carnivore capture–recapture studies associated with the use of lure and varying density estimation techniques using photographic-sampling data of the Malagasy civet. Popul Ecol 54(1):43–54

    Article  Google Scholar 

  15. Glen AS, Dickman CR (2003) Monitoring bait removal in vertebrate pest control: a comparison using track identification and remote photography. Wildl Res 30:29–33

    Article  Google Scholar 

  16. Glen AS, Cockburn S, Nichols M, Ekanayake J, Warburton B (2013) Optimising camera traps for monitoring small mammals. PLoS One 8(1–7):e67940

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  17. Guil F, Agudín S, El-Khadir N, Fernandez-Olalla M, Figueredo J, Domínguez F, Garzon P, Gonzalez G, Muñoz-Igualada J, Oria J, Silvestre F (2010) Factors conditioning the camera-trapping efficiency for the Iberian lynx (Lynx pardinus). Eur J Wildl Res 56:633–640

    Article  Google Scholar 

  18. Harmsen BJ, Foster RJ, Silver SC, Ostro LET, Doncaster CP (2009) Spatial and temporal interactions of sympatric jaguars (Panthera onca) and pumas (Puma concolor) in a Neotropical forest. J Mammal 90(3):612–620

    Article  Google Scholar 

  19. Henschel P, Ray JC (2003) Leopards in African rainforests: survey and monitoring techniques. Wildlife Conservation Society, New York

    Google Scholar 

  20. Hooijmans CR, de Vries R, Leenaars M, Curfs J, Ritskes-Hoitinga M (2011a) Improving planning, design, reporting and scientific quality of animal experiments by using the Gold Standard Publication Checklist, in addition to the ARRIVE guidelines. Br J Pharmacol 162:1259–1260

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  21. Hooijmans CR, De Vries R, Leenaars M, Ritskes-Hoitinga M (2011b) The gold standard publication checklist (GSPC) for improved design, reporting and scientific quality of animal studies. Lab Anim 45:61

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  22. Jackson RM, Roe JD, Wangchuk R, Hunter DO (2005) Surveying snow leopard populations with emphasis on camera trapping: a handbook. Snow Leopard conservancy

  23. Karanth KU (1995) Estimating tiger (Panthera tigris) populations from camera-trap data using capture: recapture models. Biol Conserv 71:333–338

    Article  Google Scholar 

  24. Karanth KU, Nichols JD (1998) Estimation of tiger densities in India using photographic captures and recaptures. Ecology 79:2852–2862

    Article  Google Scholar 

  25. Kays RW, Slauson KM (2008) Remote cameras. In: Long RA, MacKay P, Zielinski WJ, Ray JC (eds) Noninvasive survey methods for carnivores: methods and analyses. Island Press, Washington

    Google Scholar 

  26. Kays R, Tilak S, Kranstauber B, Jansen PA, Carbone C, Rowcliffe JM, Fountain T, Eggert J, He Z (2010) Monitoring wild animal communities with arrays of motion sensitive camera traps. Int J Res Rev Wirel Sensor Netw 1:19–29

    Google Scholar 

  27. Kelly MJ, Holub EL (2008) Camera trapping of carnivores: trap success among camera types and across species, and habitat selection by species, on Salt Pond Mountain, Giles County, Virginia. Northeast Nat 15:249–262

    Article  Google Scholar 

  28. Kross SM, Nelson XJ (2011) A portable low-cost remote videography system for monitoring wildlife. Methods Ecol Evol 2:191–196

    Article  Google Scholar 

  29. Larrucea ES, Brussard PF, Jaeger MM, Barrett RH (2007) Cameras, coyotes, and the assumption of equal detectability. J Wildl Manag 71:1682–1689

    Article  Google Scholar 

  30. Legg CJ, Nagy L (2006) Why most conservation monitoring is, but need not be, a waste of time. J Environ Manag 78:194–199

    Article  Google Scholar 

  31. MacKenzie DI, Nichols JD, Lachman GB, Droege S, Andrew Royle J, Langtimm CA (2002) Estimating site occupancy rates when detecting probabilities are less than one. Ecology 83:2248–2255

    Article  Google Scholar 

  32. Maffei L, Noss AJ (2008) How small is too small? Camera trap survey areas and density estimates for ocelots in the Bolivian Chaco. Biotropica 40:71–75

    Google Scholar 

  33. Magoun AJ, Valkenburg P, Pedersen DN, Long CD, Lowell RE (2011) Wolverine images: using motion detection cameras for photographing, identifying, and monitoring Wolverines. Blurb Creative

  34. McCoy JC, Ditchkoff SS, Steury TD (2011) Bias associated with baited camera sites for assessing population characteristics of deer. J Wildl Manag 75:472–477

    Article  Google Scholar 

  35. Meek PD (2010) Remote camera monitoring of the Hastings river mouse (Pseudomys oralis): Trial of a novel technique for monitoring populations. Unpublished Report for Gondwana Rainforests of Australia

  36. Meek PD, Pittet A (2012) User-based design specifications for the ultimate camera trap for wildlife research. Wildl Res 39:649–660

    Article  Google Scholar 

  37. Meek PD, Ballard AG, Fleming PJS (2012a) An introduction to camera trapping for wildlife surveys in Australia. Invasive Animals CRC, Canberra

    Google Scholar 

  38. Meek PD, Zewe F, Falzon G (2012b) Temporal activity patterns of the swamp rat (Rattus lutreolus) and other rodents in north-eastern New South Wales, Australia. Aust Mammal 34:223–233

    Article  Google Scholar 

  39. Meek PD, Fleming PJS, Ballard G, Banks PB, Claridge AW, McMahon S, Sanderson J, Swann DE (2014) Putting contemporary camera trapping in focus. In: Meek PD, Ballard AG, Banks PB, Claridge AW, Fleming PJS, Sanderson JG, Swann DE (eds) Camera trapping in wildlife research and management. CSIRO, Melbourne

    Google Scholar 

  40. Mormann B, Woods G (2010) Setting up for a Survey. In: Thomas LJ (ed) Deer Cameras - The Science of Scouting. Quality Deer Management Association, Bogart, pp 122–133

    Google Scholar 

  41. Nelson JE, Scroggie MP (2009) Remote cameras as a mammal survey tool: survey design and practical considerations. Arthur Rylah Institute for Environmental Research Unpublished report number 2009/36. Department of Sustainability and Environment, Heidelberg, Victoria

  42. Nichols JD, Bailey LL, O’Connell AF Jr, Talancy NW, Campbell Grant EH, Gilbert AT, Annand EM, Husband TP, Hines JE (2008) Multi-scale occupancy estimation and modelling using multiple detection methods. J Appl Ecol 45:1321–1329

    Article  Google Scholar 

  43. Nichols JD, Karanth KU, O’Connell AF (2011) Science, conservation and camera traps. In: O’Connell AF, Nichols JD, Karanth KU (eds) Camera traps in animal ecology: methods and analyses. Springer, New York

    Google Scholar 

  44. O’Brien TG (2011) Abundance, density and relative abundance: a conceptual framework. In: O’Connell AF, Nichols JD, Karanth KU (eds) Camera traps in animal ecology: methods and analyses. Springer, New York

    Google Scholar 

  45. O’Brien TG, Kinnaird MF (2011) Density estimation of sympatric carnivores using spatially explicit capture–recapture methods and standard trapping grid. Ecol Appl 21:2908–2916

    Article  Google Scholar 

  46. O’Brien TG, Kinnaird MF, Wibisono HT (2003) Crouching tigers, hidden prey: sumatran tiger and prey populations in a tropical forest landscape. Anim Conserv 6:131–139

    Article  Google Scholar 

  47. O’Brien TG, Baillie JEM, Krueger L, Cuke M (2010) The wildlife picture index: monitoring top trophic levels. Anim Conserv 13:335–343

    Article  Google Scholar 

  48. O’Connell AF, Nichols JD, Karanth KU (2011) Camera traps in animal ecology methods and analyses. Springer, New York

    Google Scholar 

  49. Organisation for Economic Co-operation and Development (OECD) (2002) Frascati manual 2002: proposed standard practice for surveys on research and experimental development. The measurement of scientific and technological activities. OECD, Paris

    Google Scholar 

  50. Paull DJ, Claridge AW, Barry SC (2011) There’s no accounting for taste: bait attractants and infrared digital cameras for detecting small to medium ground-dwelling mammals. Wildl Res 38:188–195

    Article  Google Scholar 

  51. Reif V, Tornberg R (2006) Using time-lapse digital video recording for a nesting study of birds of prey. Eur J Wildl Res 52:251–258

    Article  Google Scholar 

  52. Roberts CW, Pierce BL, Braden AW, Lopez RR, Silvy NJ, Frank PA, Ransom D (2006) Comparison of camera and road survey estimates for white-tailed deer. J Wildl Manag 70:263–267

    Article  Google Scholar 

  53. Rovero F, Marshall AR (2009) Camera trapping photographic rate as an index of density in forest ungulates. J Appl Ecol 46:1011–1017

    Article  Google Scholar 

  54. Rovero F, Zimmerman F, Berzi D, Meek PD (2013) Which camera trap type and how many do I need? A review of camera features and study designs for a range of wildlife research applications Hystrix. Ital J Mammal 24:9–17

    Google Scholar 

  55. Rowcliffe JM, Field J, Turvey ST, Carbone C (2008) Estimating animal density using camera traps without the need for individual recognition. J Appl Ecol 45:1228–1236

    Article  Google Scholar 

  56. Royle JA, Link WA (2006) Generalised site occupancy models allowing for false positive and false negative errors. Ecology 87:835–841

    PubMed  Article  Google Scholar 

  57. Sanderson JG, Harris G (2014) Automatic camera trap data organization, storage, and analysis without entering data by hand from a keyboard. In: Meek PD, Ballard AG, Banks PB, Claridge AW, Fleming PJS, Sanderson JG, Swann DE (eds) Camera trapping in wildlife research and management. CSIRO, Melbourne

    Google Scholar 

  58. Sanderson JG, Trolle M (2005) Monitoring elusive mammals. Am Sci 93:148–155

    Article  Google Scholar 

  59. Schipper J (2007) Camera-trap avoidance by Kinkajous (Potos flavus): rethinking the “non-invasive” paradigm. Small Carniv Conserv 36:38–41

    Google Scholar 

  60. Séquin ES, Jaeger MM, Brussard PF, Barrett RH (2003) Wariness of coyotes to camera traps relative to social status and territory boundaries. Can J Zool 81:2015–2025

    Article  Google Scholar 

  61. Silver S (2004) Assessing jaguar abundance using remotely triggered cameras. Wildlife Conservation Society, Bronx

    Google Scholar 

  62. Silver SC, Ostro LET, Marsh LK, Maffei L, Noss AJ, Kelly MJ, Wallace RB, Gomez H, Ayala G (2004) The use of camera traps for estimating jaguar (Panthera onca) abundance and density using capture/recapture analysis. Oryx 38:148–154

    Article  Google Scholar 

  63. Smith JK, Coulson G (2012) A comparison of vertical and horizontal camera trap orientations for detection of potoroos and bandicoots. Aust Mammal 34:196–201

    Article  Google Scholar 

  64. Sutherland WJ, Armstrong D, Butchart SHM, Earnhardt JM, Ewen J, Jamieson I, Jones CG, Lee R, Newbery P, Nichols JD, Parker KA, Sarrazin F, Seddon PJ, Shah N, Tatayah V (2010) Standards for documenting and monitoring bird reintroduction projects. Conserv Lett 3:229–235

    Article  Google Scholar 

  65. Swann DE, Hass CC, Dalton DC, Wolf A (2004) Infrared-triggered cameras for detecting wildlife: an evaluation and review. Wildl Soc Bull 32:357–365

    Article  Google Scholar 

  66. Swann DE, Kawanishi K, Palmer J (2011) Evaluating types and features of camera traps in ecological studies: guide for researchers. In: O’Connell AF, Nichols JD, Karanth KU (eds) Camera traps in animal ecology: methods and analyses. Springer, New York

    Google Scholar 

  67. TeamNetwork (2011) Terrestrial vertebrate protocol implementation manual. Tropical ecology assessment and monitoring network

  68. Tobler MW (2013) Camera Base 1.6. http://www.atrium-biodiversity.org/tools/camerabase/

  69. Tobler MW, Powell GVN (2013) Estimating jaguar densities with camera traps: problems with current designs and recommendations for future studies. Biol Conserv 159:109–118

    Article  Google Scholar 

  70. Tobler MW, Carrillo-Percastegui SE, Leite Pitman R, Mares R, Powell G (2008) An evaluation of camera traps for inventorying large- and medium-sized terrestrial rainforest mammals. Anim Conserv 11:169–178

    Article  Google Scholar 

  71. Wegge P, Pokheral CP, Jnawali SR (2004) Effects of trapping effort and trap shyness on estimates of tiger abundance from camera trap studies. Anim Conserv 7:251–256

    Article  Google Scholar 

  72. Weingarth K, Zimmermann F, Knauer F, Heurich M (2013) Evaluation of six digital camera models for the use in capture-recapture sampling of Eurasian Lynx (Lynx lynx). Waldökol Landsch Forsch Naturschutz 13:87–92

    Google Scholar 

  73. Welbourne D (2013) A method for surveying diurnal terrestrial reptiles with passive infrared automatically triggered cameras. Herpetol Rev 44:247–250

    Google Scholar 

  74. Williams BL, Holtfreter RW, Ditchkoff SS, Grand JB (2011) Efficiency of time-lapse intervals and simple baits for camera surveys of wild pigs. J Wildl Manag 75:655–659

    Article  Google Scholar 

  75. Wilson RR, Young JK, Shivik JA (2011) Coyote capture vulnerability relative to space use and trap density. J Wildl Manag 75:721–725

    Article  Google Scholar 

  76. Zewe F, Meek P, Ford H, Vernes K (2014) A vertical bait station for black rats (Rattus rattus) that reduces bait take by a sympatric native rodent. Aust Mammal 36:67–73

    Article  Google Scholar 

  77. Zimmermann F, Breitenmoser-Würsten C, Breitenmoser U (2007) Importance of dispersal for the expansion of a Eurasian lynx (Lynx lynx) population in a fragmented landscape. Oryx 41:358–368

    Article  Google Scholar 

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Acknowledgments

We would like to recognise the role of the following organisations whose support helped augment the preparation of this manuscript; The Winston Churchill Memorial Trust, The Australasian Wildlife Management Society and the NSW Royal Zoological Society. Thank you to James D. Nichols and Andrew Bengsen who provided constructive comments on this manuscript. Marcella Kelly, Karen Hodges and an anonymous referee made several changes to this manuscript.

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Correspondence to P. D. Meek.

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Communicated by Karen E. Hodges.

Appendix

Appendix

List of standard camera trap terms (from Meek et al. 2012a; Rovero et al. 2013) with additional definitions

Alignment:

Term used to describe the placement of a camera and the cardinal direction, it can be two dimensional thus a horizontal (standard placement—lens perpendicular to the ground) or vertical (lens facing downwards at the ground) alignment as well as a horizontal-cardinal direction

Burst mode:

A camera trap setting that allows continuous images to be taken following a trigger event, see also rapidfire

Camera trap:

A term used to describe a camera that captures images of wildlife using heat and motion sensing, time lapse, mechanical, seismic sensors or an active infra red sensor system

Camera trap set:

Connotation of a trap ‘set’ which describes the immediate area where camera/s are placed, can be more than one camera per set

Camera trap array:

The number of camera traps set in a certain pattern and defined location, referring to more than one camera trap at a study area

CF card:

The acronym for Compact Flash cards, a mass storage device used by older camera traps, virtually all new models (at the time of publication) now use SD cards

Covert surveillance:

Use of cameras set to catch illegal actions by people

Delay:

A program function available on some models. This setting has many forms but typically allows the user to set a period of time where the camera trap is inactive or ‘hibernating’ before or between images

Depth of field:

This refers to the aperture setting and its effect on the focus of objects in the front and rear of the image. Not often adjustable in camera traps

Detection zone:

The area in which a camera trap is able to detect the heat signature and motion of a target

Event:

The period of time between independent triggers of distinct individuals, regardless of the number of images, to the last image in a sequence

False Positive:

Incorrectly detecting an animal or species when none is present

False Negative:

Failure to detect an animal or species when in fact it is present

Focal point:

Usually the centre of the image (if the image is composed correctly), the subject of interest, the lure, pathway or track centre or bait device

Field of view:

The area captured in a image, usually between 35° and 45°

Fresnel lens:

A lens used by camera traps to direct infrared energy onto the passive infrared (PIR) sensor. These lenses are commonly seen in lighthouses and cause refraction of light

Incandescent:

A white flash (xenon) used by some camera traps, now mostly superseded by white LED

LED:

An abbreviation for light-emitting diode, a form of light source used in modern white flash cameras

Lures:

A generic term referring to an attractant used to encourage animals to investigate a specific point within the detection zone. Lures may be auditory, olfactory, visual, or some combination of these in nature

Night Mode:

This setting is available in some camera traps and allows the device to be set to maximise clarity at night by reducing the illumination power and increasing the speed of the shutter, thus reducing blur

PIR sensor:

Passive detectors of infrared light

Rapidfire:

A camera trap setting that allows images to be taken continuously following a trigger event—see also burst mode

SD card:

The acronym for Secure Digital cards. A removable digital storage medium that is currently the standard in camera traps

Sensitivity:

A setting, often adjustable, that reflects the camera’s response to heat in motion for PIR sensors. Higher sensitivity is associated with more images, and lower sensitivity with fewer images. Increased sensitivity, however, does not guarantee detection of a target

Sequence:

A series of still images or video taken in rapid succession but separated by a time interval less than the set independence interval and forming an animated record of a triggering event

Time lapse:

A program function available on some camera traps. The time-lapse function, or similar function, typically allows a user to prescribe times of day and/or night when the camera is inactive, regardless of activity within the detection zone. Some time-lapse cameras do not have a PIR and, instead, capture images at prescribed times or intervals

Time lapse camera:

Camera traps that do not have a PIR sensor and can be programmed to take images at predetermined times throughout the day regardless of any triggers

Time to first trigger:

The speed of the camera from detection by the PIR sensor to the first image captured

Trigger or Capture speed:

The time difference between detecting heat in motion and capturing an image. Also known as response time. Slower trigger speed (i.e. more time elapsing between trigger and image capture) may decrease the likelihood of capturing a target

Walk test:

A program function available on some camera traps. Walk test, or similar, can be used to identify where a camera will respond to heat in motion. Consequently, it can be used to ‘focus’ the camera’s detection zone, as desired

White LED:

A white flash consisting of white LED’s in an array similar to an infra red array that illuminates the subject at night in full colour and is faster than xenon flash technology

Xenon flash:

An incandescent or white flash that illuminates the subject at night in full colour

Synonyms for camera traps:

Remote camera, remotely activated monitoring camera, trail camera, spy camera, wildlife camera, camera trap, remote-sensing camera, sensor camera, remote sensing camera, remotely-triggered camera, game camera, photo-trapping, sensor camera, heat-and-motion sensing camera

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Meek, P.D., Ballard, G., Claridge, A. et al. Recommended guiding principles for reporting on camera trapping research. Biodivers Conserv 23, 2321–2343 (2014). https://doi.org/10.1007/s10531-014-0712-8

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Keywords

  • Remote cameras
  • Trail cameras
  • Camera trap guidelines
  • Ecological monitoring
  • Camera trap methodology