Review of field methods for monitoring Asian bears

Evaluation of physiological stress in free-ranging bears: current knowledge and future directions

Stress responses, which are mediated by the neurogenic system (NS) and hypothalamic-pituitary-adrenal (HPA) axis help vertebrates maintain physiological homeostasis. Fight-or-flight responses are activated by the NS, which releases norepinephrine/noradrenaline and epinephrine/adrenaline in response to immediate stressors, whilst the HPA axis releases glucocorticoid hormones (e.g. cortisol and corticosterone) to help mitigate allostatic load. There have been many studies on stress responses of captive animals, but they are not truly reflective of typical ranges or the types of stressors encountered by free-ranging wildlife, such as responses and adaptation to environmental change, which are particularly important from a conservation perspective. As stress can influence the composition of age and sex classes of free-ranging populations both directly and indirectly, ecological research must be prioritised towards more vulnerable taxa. Generally, large predators tend to be particularly at risk of anthropogenically driven population declines because they exhibit reduced behavioural plasticity required to adapt to changing landscapes and exist in reduced geographic ranges, have small population sizes, low fecundity rates, large spatial requirements and occupy high trophic positions. As a keystone species with a long history of coexistence with humans in highly anthropogenic landscapes, there has been growing concern about how humans influence bear behaviour and physiology, via numerous short- and long-term stressors. In this review, we synthesise research on the stress response in free-ranging bear populations and evaluate the effectiveness and limitations of current methodology in measuring stress in bears to identify the most effective metrics for future research. Particularly, we integrate research that utilised haematological variables, cardiac monitors and Global Positioning System (GPS) collars, serum/plasma and faecal glucocorticoid concentrations, hair cortisol levels, and morphological metrics (primarily skulls) to investigate the stress response in ursids in both short- and long-term contexts. We found that in free-ranging bears, food availability and consumption have the greatest influence on individual stress, with mixed responses to anthropogenic influences. Effects of sex and age on stress are also mixed, likely attributable to inconsistent methods. We recommend that methodology across all stress indicators used in free-ranging bears should be standardised to improve interpretation of results and that a wider range of species should be incorporated in future studies.

N-mixture model-based estimate of relative abundance of sloth bear (Melursus ursinus) in response to biotic and abiotic factors in a human-dominated landscape of central India

Reliable estimation of abundance is a prerequisite for a species' conservation planning in human-dominated landscapes, especially if the species is elusive and involved in conflicts. As a means of population estimation, the importance of camera traps has been recognized globally, although estimating the abundance of unmarked, cryptic species has always been a challenge to conservation biologists. This study explores the use of the N-mixture model with three probability distributions, i.e., Poisson, negative binomial (NB) and zero-inflated Poisson (ZIP), to estimate the relative abundance of sloth bears (Melursus ursinus) based on a camera trapping exercise in Sanjay Tiger Reserve, Madhya Pradesh from December 2016 to April 2017. We used environmental and anthropogenic covariates to model the variation in the abundance of sloth bears. We also compared null model estimates (mean site abundance) obtained from the N-mixture model to those of the Royle-Nichols abundance-induced heterogeneity model (RN model) to assess the application of similar site-structured models. Models with Poisson distributions produced ecologically realistic and more precise estimates of mean site abundance (λ = 2.60 ± 0.64) compared with other distributions, despite the relatively high Akaike Information Criterion value. Area of mixed and sal forest, the photographic capture rate of humans and distance to the nearest village predicted a higher relative abundance of sloth bears. Mean site abundance estimates of sloth bears obtained from the N-mixture model (Poisson distribution) and the RN model were comparable, indicating the overall utility of these models in this field. However, density estimates of sloth bears based on spatially explicit methods are essential for evaluating the efficacy of the relatively more cost-effective N-mixture model. Compared to commonly used index/encounter-based methods, the N-mixture model equipped with knowledge on governing biotic and abiotic factors provides better relative abundance estimates for a species like the sloth bear. In the absence of absolute abundance estimates, the present study could be insightful for the long-term conservation and management of sloth bears.