Camera Trapping and Occupancy Modeling
Camera traps are remotely activated cameras equipped with infrared, light beam or motion triggers. The technology allows scientists to ˇ°captureˇ± wild animals without disturbing them. The use of camera traps in the study of wildlife has become more common as technology has advanced and the need for non-invasive techniques has expanded. In addition to documenting the occurrence of a species, camera traps improve our understanding of habitat use, animal behavior, species interactions, species distribution, population dynamics, and species richness in a certain community. Go to this site to view a description of our vegetation and wildlife survey.
Our research team uses camera traps to survey wildlife in Fanjingshan National Nature Reserve, China. The data collected by camera traps are used to understand animal responses to human activities and environmental changes in the reserve. Such data will be used as an indicator of ecosystem, environmental, and habitat changes (e.g., restoration or degradation) that may arise from the implementation of programs in relation to payments for ecosystem services (PES).
The concept of occupancy links site-specific processes determining species occurrence with detection (e.g., via camera trapping) processes that govern observations of animal presence or absence. This is an appropriate method for estimation and inference about animal occurrence with imperfect detection (MacKenzie et al. 2002). Within the last ten years, occupancy modeling has emerged as a preferred alternative technique as it permits inference about animal occurrence over space and different habitat types, even for species that cannot be individually identified (MacKenzie et al. 2005, 2006). Occupancy is defined as the probability that a patch is occupied by a target species, and has been widely used to address basic ecological questions related to geographic distribution, habitat relationships, resource selection, and species interactions.
Our research team applies occupancy modeling to analyzing camera trapping data collected in Fanjingshan National Nature Reserve, China. By specifying models of site occupancy and detectability, we can estimate probability of occurrence of wildlife species at individual sites and infer effects of environmental characteristics and human activities on animal occurrence and species richness after accounting for variation in detectability. Below is a list of papers that provides background theories and applications of occupancy models.
Readings and References:
Chen, H.L., R.L. Lewison, L. An, Y.H. Tsai, D. Stow, L. Shi, and S. Yang (accepted). Assessing the effects of payments for ecosystem services programs on forest structure and species biodiversity. Biodiversity and Conservation.
Burton, A.C., E. Neilson, D. Moreira, A. Ladle, R. Steenweg, J.T. Fisher, E. Bayne, and S. Boutin (2015). Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes. Journal of Applied Ecology 52: 675¨C685.
Burton, A.C., M.K. Sam, C. Balangtaa, and J.S. Brashares (2012). Hierarchical multi-species modeling of carnivore responses to hunting, habitat and prey in a West African protected area. PLoS ONE 7(5): e38007.
Farris, Z.J., S.M. Karpanty, F. Ratelolahy, and M.J. Kelly (2014). Predator¨Cprimate distribution, activity, and co-occurrence in relation to habitat and human activity across fragmented and contiguous forests in northeastern Madagascar. International Journal of Primatology 35: 859-880.
MacKenzie, D.I., J.D. Nichols, G.B. Lachman, S. Droege, J.A. Royle, and C.A. Langtimm (2002). Estimating site occupancy rates when detection probabilities are less than one. Ecology 83: 2248-2255.
MacKenzie, D.I., J.D. Nichols, N. Sutton, K. Kawanishi, and L.L. Bailey (2005). Improving inferences in population studies of rare species that are detected imperfectly. Ecology 86(5): 1101-1113.
MacKenzie, D. I., J.D. Nichols, J.A., Royle, K.H. Pollock, L.L. Bailey, and J.E. Hines (2006).Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press: New York, NY.
OˇŻConnell, A.F., J.D. Nichols, and K.U. Karanth (editors) (2011). Camera traps in animal ecology: methods and analyses. Springer: New York, NY.
Royle, J.A., and J.D. Nichols (2003). Estimating abundance from repeated presence-absence data or points counts. Ecology 84(3): 777-790.
Royle, J.A., and R.M. Dorazio (2006). Hierarchical models of animal abundance and occurrence. Journal of Agricultural Biological and Environmental Statistics 11:249¨C263.
Srbek-Araujo, A.C., and A.G. Chiarello (2005). Is camera-trapping an efficient method for surveying mammals in Neotropical forests? A case study in south-eastern Brazil. Journal of Tropical Ecology 21: 121-125.
********** Text written by Dr. Hsiang Ling Chen with edits from Dr. Li An **********
Notes:
An related theme is to collect vegetation plot data, which is often combined with camera trapping data collection. Here please find an example. Below is information about our team's first attempt to collect camera trapping data (see the link below).
2008 Camera Trapping Test
