@article {110789, title = {Comparison of methods for estimating density and population trends for low-density Asian bears}, journal = {GLOBAL ECOLOGY AND CONSERVATION}, volume = {35}, year = {2022}, month = {06/2022}, abstract = {

Populations of bears in Asia are vulnerable to extinction and effective monitoring is critical to measure and direct conservation efforts. Population abundance (local density) or growth (lambda) are the most sensitive metrics to change. We discuss the value in implementing spatially explicit capture-recapture (SCR), the current gold standard for density estimation, and open population SCR (OPSCR) to monitor changes in density over time. We provide guidance for designing studies to provide estimates with sufficient power to detect changes. Because of the wide availability of camera traps and interest in their use, we consider six density estimation methods and their extensions developed for use with camera traps, with specific consideration of assumptions and applications for monitoring Asian bears. We conducted a power analysis to calculate the precision in estimates needed to detect changes in populations with reference to IUCN Red List criteria. We performed a systematic review of empirical studies implementing camera trap abundance estimation methods and considered sample sizes, effort, and model assumptions required to achieve adequate precision for population monitoring. We found SCR and OPSCR, reliant on "marked" individuals, are currently the only methods with enough power to reliably detect even moderate to major (20-80\%) declines. Camera trap methods with unmarked individuals rarely achieved precision sufficient to detect even large declines (80-90\%), although with some exceptions (e.g., situations with moderate population densities, large number of sampling sites, or inclusion of ancillary local telemetry data. We describe additional estimation options including line transects, direct observations, monitoring age-specific survival and reproductive rates, and hybrid/integrated methodologies that may have potential to work for some Asian bear populations. We conclude monitoring changes in abundance or density is possible for most Asian bear populations but will require collaboration among researchers over broad spatial extents and extensive financial investment to overcome biological and logistical constraints. We strongly encourage practitioners to consider study design and sampling effort required to meet objectives by conducting simulations, power analyses, and assumption checks prior to implementing monitoring efforts, and reporting standardized dispersion measures such as coefficients of variation to allow for assessment of precision. Our guidance is relevant to other low-density and wide-ranging species.

}, doi = {10.1016/j.gecco.2022.e02058}, author = {Morin, Dana J. and Boulanger, John and Bischof, Richard and Lee, David C. and Ngoprasert, Dusit and Fuller, Angela K. and McLellan, Bruce and Steinmetz, Robert and Sharma, Sandeep and Garshelis, Dave and Gopalaswamy, Arjun and Nawaz, Muhammad Ali and Karanth, Ullas} } @article {26656, title = {Bayesian Methods for Estimating Animal Abundance at Large Spatial Scales Using Data from Multiple Sources}, journal = {Journal of Agricultural, Biological and Environmental Statistics}, volume = {22}, year = {2017}, month = {06/2017}, pages = {111{\textendash}139}, abstract = {

Estimating animal distributions and abundances over large regions is of primary interest in ecology and conservation. Specifically, integrating data from reliable but expensive surveys conducted at smaller scales with cost-effective but less reliable data generated from surveys at wider scales remains a central challenge in statistical ecology. In this study, we use a Bayesian smoothing technique based on a conditionally autoregressive (CAR) prior distribution and Bayesian regression to address this problem. We illustrate the utility of our proposed methodology by integrating (i) abundance estimates of tigers in wildlife reserves from intensive photographic capture{\textendash}recapture methods, and (ii) estimates of tiger habitat occupancy from indirect sign surveys, conducted over a wider region. We also investigate whether the random effects which represent the spatial association due to the CAR structure have any confounding effect on the fixed effects of the regression coefficients.

}, author = {Dey, S and Delampady, M and Parameshwaran, Ravishankar and Samba Kumar, N and Srivathsa, Arjun and Karanth, Ullas} } @article {3567, title = {Determiants of dry season habitat use by Asian elephants in the Western Ghats of India}, journal = {Journal of Zoological}, volume = {298}, year = {2016}, month = {March 2016}, pages = {169{\textendash}177}, abstract = {

Large herbivores respond to seasonal changes in resource availability through habitat selection. Understanding variations in habitat choice is crucial for targeting conservation efforts, particularly for endangered, wide-ranging species, such as the Asian elephant. We assessed patterns and determinants of elephant habitat use during the dry season, a period of resource limitation in tropical deciduous forests, in the Western Ghats of Karnataka, India. We collected detection/non-detection data on elephant signs under an occupancy sampling framework, using spatially replicated surveys on foot along forest trails to estimate probabilities of habitat use by elephants. Each of our 97 sites (sampling units) was a grid cell of 11.75 km2 area. Data were analysed using an occupancy model, which estimated detection probabilities for signs, while explicitly addressing the potential spatial dependence between sign detections on adjacent replicates. Using covariates that are likely to influence resource use, we made ecological predictions about dry season habitat use by elephants across the study area of 1850 km2. The site-level probabilities of habitat use by elephants ranged from inline image The estimated replicate level detection probability was inline image We found that distance to rivers was the best predictor of elephant habitat use, in dry season, demonstrating the overarching importance of riparian habitats in the landscape for the species. Artificial water holes established by wildlife managers do not appear to influence elephant habitat use, which is likely a result of abundant and near-uniform distribution of such water holes across the study area. The sign survey-based occupancy modelling approach provides a basis for reliable cost-effective assessment of spatial distribution and habitat use by elephants and other large herbivores. Such assessments are essential for effective conservation management of large herbivores.

}, doi = {10.1111/jzo.12298}, url = {http://onlinelibrary.wiley.com/doi/10.1111/jzo.12298/abstract}, author = {Lakshminarayanan, N. and Karanth, K.K. and Goswami, V.R. and Vaidyanathan, S. and Karanth, Ullas} }