Do we need to unfriend a few friends? Free‐ranging dogs affect wildlife and pastoralists in the Indian Trans‐Himalaya

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Abstract

Dogs Canis lupus familiaris, among canids, have emerged as the most successful predators and facultative scavengers, and have prevented other carnivores from approaching human habitats through intraguild competition. Over time with increasing population and livestock predation, they have become a matter of concern for pastoralists. The present study was conducted to understand the patterns of free‐ranging dogs' predation on livestock and wildlife, from 2015 to 2017 in Changthang Wildlife Sanctuary (CWLS), Ladakh, India. Information was collected on (a) dog populations in 10 sites using polygon search in Spatially Explicit Capture‐Recapture framework and block count, (b) their diet using scat analysis ( n = 205) and (c) perceptions of pastoralists towards dogs through questionnaire‐based interviews ( n = 210). Dog densities varied between 10 and 310 individuals/100 km ² and were high in and around human habitations. A major part of their diet constituted of livestock (74.29%) and wild species (13.06%). Among wild prey species, birds (4.49%), lagomorphs (3.67%), rodents (2.45%) and Tibetan wild ass (1.63%) had high occurrence in dog diet. The local people admitted that dogs pose a threat to livestock and wildlife. As unowned free‐ranging dogs harm livestock and wildlife, about 40% of the respondents had negative perceptions towards them. The perception varied with occupation and pastoralists were more negative than non‐pastoralists ( P < 0.001). We suggest that effective mechanisms need to be identified or developed to manage dog populations in ecologically and economically sensitive areas to minimise the threats and safeguard the endangered wildlife and local livelihoods.

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Estimating the Global Burden of Endemic Canine Rabies

Katie Hampson, Laurent Coudeville, Tiziana Lembo … (2015)

Background Rabies is a notoriously underreported and neglected disease of low-income countries. This study aims to estimate the public health and economic burden of rabies circulating in domestic dog populations, globally and on a country-by-country basis, allowing an objective assessment of how much this preventable disease costs endemic countries. Methodology/Principal Findings We established relationships between rabies mortality and rabies prevention and control measures, which we incorporated into a model framework. We used data derived from extensive literature searches and questionnaires on disease incidence, control interventions and preventative measures within this framework to estimate the disease burden. The burden of rabies impacts on public health sector budgets, local communities and livestock economies, with the highest risk of rabies in the poorest regions of the world. This study estimates that globally canine rabies causes approximately 59,000 (95% Confidence Intervals: 25-159,000) human deaths, over 3.7 million (95% CIs: 1.6-10.4 million) disability-adjusted life years (DALYs) and 8.6 billion USD (95% CIs: 2.9-21.5 billion) economic losses annually. The largest component of the economic burden is due to premature death (55%), followed by direct costs of post-exposure prophylaxis (PEP, 20%) and lost income whilst seeking PEP (15.5%), with only limited costs to the veterinary sector due to dog vaccination (1.5%), and additional costs to communities from livestock losses (6%). Conclusions/Significance This study demonstrates that investment in dog vaccination, the single most effective way of reducing the disease burden, has been inadequate and that the availability and affordability of PEP needs improving. Collaborative investments by medical and veterinary sectors could dramatically reduce the current large, and unnecessary, burden of rabies on affected communities. Improved surveillance is needed to reduce uncertainty in burden estimates and to monitor the impacts of control efforts.

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Spatially explicit maximum likelihood methods for capture-recapture studies.

D. L. Borchers, M G Efford (2008)

Live-trapping capture-recapture studies of animal populations with fixed trap locations inevitably have a spatial component: animals close to traps are more likely to be caught than those far away. This is not addressed in conventional closed-population estimates of abundance and without the spatial component, rigorous estimates of density cannot be obtained. We propose new, flexible capture-recapture models that use the capture locations to estimate animal locations and spatially referenced capture probability. The models are likelihood-based and hence allow use of Akaike's information criterion or other likelihood-based methods of model selection. Density is an explicit parameter, and the evaluation of its dependence on spatial or temporal covariates is therefore straightforward. Additional (nonspatial) variation in capture probability may be modeled as in conventional capture-recapture. The method is tested by simulation, using a model in which capture probability depends only on location relative to traps. Point estimators are found to be unbiased and standard error estimators almost unbiased. The method is used to estimate the density of Red-eyed Vireos (Vireo olivaceus) from mist-netting data from the Patuxent Research Refuge, Maryland, U.S.A. Estimates agree well with those from an existing spatially explicit method based on inverse prediction. A variety of additional spatially explicit models are fitted; these include models with temporal stratification, behavioral response, and heterogeneous animal home ranges.