By Timothy G. O’Brien, Wildlife Conservation Society, 2300 Southern Blvd, Bronx NY 10460 USA

Article 29 of the Nagoya Protocol mandates all signatories to the Convention on Biological Diversity (CBD) to monitor their implementation of CBD obligations and document progress toward Aichi 2020 targets. Given the multi-dimensional character of biodiversity, a single, comprehensive metric is clearly not feasible. Rather we rely on a range of factors to measure the status and conservation of biodiversity. Pereira et al, (2013) proposed a list of essential biodiversity variables (EBVs) to enable the study, reporting and management of biodiversity change.

Three EBVs of particular interest to wildlife biologists and conservationists are species distribution, population abundance, and taxonomic diversity. Global trend dashboards using such data include the Wild Bird Index, the Living Planet Index and the Wildlife Picture Index. The Wildlife Picture Index uses data from camera trap images to generate trends in species abundance and distribution. Camera trap data can, of course, also be used to assess trends in species composition and taxonomic diversity.  Automated camera traps remotely sense the passage of moderate sized wildlife, are especially useful for monitoring terrestrial and semi-terrestrial mammals and birds, and are, therefore, an excellent method for gathering data on EBVs.

Camera trapping as a research and monitoring tool has evolved significantly over the past 10 years. Camera traps have become more durable, functional and considerably less expensive. Tried and tested survey designs are publicly available for estimating density and distribution of specific species (targeted sampling) or optimized for multi-species (systematic sampling). There is a large body of theory, analytical techniques and software for the credible determination of abundance, density, relative abundance, point abundance, occupancy, and species richness using camera trap data. Most of these metrics allow for variability in the detectability of different species in different habitats. This is a key requisite for developing accurate trends. A decade long experiment, the Tropical Ecology Assessment and Monitoring Network (TEAM: www.TEAMNetwork.org) has demonstrated the usefulness of shared camera trap datasets, derived from common survey methods, for informing us about trends in communities of tropical forest terrestrial birds and mammals, a component of biodiversity poorly represented in most biodiversity assessments. Promisingly, the use of camera traps in ecological research and conservation is growing exponentially. Between 2006 and 2013, Burton et al (2015) found that use of camera traps doubled every 2.9 years, and generated data from more than 20,000 trap locations worldwide. This is certainly an underestimate because Steenweg et al (2017) report 8,494 camera trap deployments by a very small sample of 16 researchers. The government of India, alone, deployed 9,735 camera traps in 2014 for their national survey of tigers. Today, conservation NGOs rely heavily on camera trapping to monitor wildlife in protected areas and to study rare or elusive species. As an indication of global use, I found 152 camera trap articles from 42 countries published in the first 5 months of 2017. The Wildlife Conservation Society has ongoing camera trap programs in more than 25 countries.

Camera trap studies are capable of generating a huge amount of by-catch. That is images and data on non-target species that are recorded but never used because the images do not address the research question or the objective of the study. By-catch data represent an invaluable treasure trove for biodiversity monitoring that is currently under-utilized. The fate of by-catch images varies. Data summaries and analyses are at times published, but rarely are the underlying data made public for others to use. Some researchers do not even transcribe the by-catch information because of the time and effort involved in sorting through and identifying species in thousands of images. Others simply file and forget. As a result, these data are lost to others that might be interested in the by-catch.

Impediments to sharing camera trap data or providing open access to data are fading fast. Recently, Forrester et al. (2016) published an open metadata standard for camera trap data. Meek et al. (2014) give advice on how to report camera trap methods and results so that others can replicate or use the study more effectively. Websites and software are available to help researchers classify images and manage images and metadata. Zooniverse has produced crowd-sourcing software to facilitate species identification from images. The TEAM Network provides free software for managing camera trap projects, images and metadata, as have a number of researchers (e.g CamTrapR, CameraBase). Recently two websites have launched, eMammal and Wildlife Insights, which make it easy for camera trappers to archive and share their data online in a secure environment.  This is an important advancement, because reducing the effort to upload camera trap data, and making online access public are critical for making global camera trap data available to the conservation community via biodiversity websites hosted by VertNet, GBIF and GEOBON.

As conservationists and researchers, we are often funded from donors, foundations and taxpayer dollars. We, therefore, have an obligation to make the best use of the data we collect. This means publishing the results of our work, sharing our camera trap data – including information on by-catch, and collaborating at the national, regional and global level to leverage our work. Biodiversity conservation needs our data to measure progress toward CBD-Aichi 2020 goals. We should not be arguing about data-sharing. Rather, we should borrow an idea from John F. Kennedy, ask not what camera trapping can do for you, ask what you can do for global camera trapping.

Forrester, T., O’Brien, T., Fegraus, E., Jansen, P.A., Palmer, J., Kays, R., Ahumada, J., Stern, B. and McShea, W. (2016). An open standard for camera trap data. Biodiversity Journal: Methods. Doi:10.3897/BDJ.4.e10197.

Meek, P.D., Ballard, G., Claridge, A., Kays, R., Moseby, K., O’Brien, T., O’Connell, A., Sanderson, J., Swann, D.E., Tobler, M. and Townsend, S. (2014). Recommended guiding principles for reporting on camera trapping research. Biodiversity and Conservation doi:10.1007/s10531-014-0712-8.

Pereira, H.M., Ferrier, S., Walters, M., Geller, G.N., Jongman, R.H.G., Scholes, R.J., Bruford, M.W., Brummitt, N., Butchart, S.H.M., Cardoso, A.C., Coops, N.C., Dulloo, E., Faith, D.P., Freyhof, J., Gregory, R.D., Heip, C., Höft, R., Hurtt, G., Jetz, W., Karp, D.S., McGeoch, M.A., Obura, D., Onoda, Y., Pettorelli, N., Reyers, B., Sayre, R., Scharlemann, J.P.W., Stuart, S.N., Turak, E., Walpole, M. and Wegmann, M. (2013). Essential biodiversity variables. Science 339(6117): 277-278.

Steenweg, R., Hebblewhite, M., Kays, R., Ahumada, J., Fisher, J.T., Burton, C., Townsend, S.E., Carbone, C., Rowcliffe, J.M., Whittington, J., Brodie, J., Royle, J.A., Switalski, A., Clevenger, A.P., Heim, N. and Rich, L.N. (2017). Scaling up camera traps: monitoring the planet’s biodiversity with networks of remote sensors. Frontiers in Ecology and Environment 15(1): 26-34. doi:10.1002/fee.1448