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Bagchi, S., Sharma, R. K., Bhatnagar, Y.V. (2020). Change in snow leopard predation on livestock after revival of wild prey in the Trans-Himalaya. Wildlife Biology, , 1–11.
Abstract: Human–wildlife conflict arising from livestock-losses to large carnivores is an important challenge faced by conservation. Theory of prey–predator interactions suggests that revival of wild prey populations can reduce predator’s dependence on livestock in multiple-use landscapes. We explore whether 10-years of conservation efforts to revive wild prey could reduce snow leopard’s Panthera uncia consumption of livestock in the coupled human-and-natural Trans-Himalayan ecosystem of northern India. Starting in 2001, concerted conservation efforts at one site (intervention) attempted recovery of wild- prey populations by creating livestock-free reserves, accompanied with other incentives (e.g. insurance, vigilant herding). Another site, 50km away, was monitored as status quo without any interventions. Prey remains in snow leopard scats were examined periodically at five-year intervals between 2002 and 2012 to determine any temporal shift in diet at both sites to evaluate the effectiveness of conservation interventions. Consumption of livestock increased at the status quo site, while it decreased at the intervention-site. At the intervention-site, livestock-consumption reduced during 2002–2007 (by 17%, p = 0.06); this effect was sustained during the next five-year interval, and it was accompanied by a persistent increase in wild prey populations. Here we also noted increased predator populations, likely due to immigration into the study area. Despite the increase in the predator population, there was no increase in livestock-consumption. In contrast, under status quo, dependence on livestock increased during both five-year intervals (by 7%, p=0.08, and by 16%, p=0.01, respectively). These contrasts between the trajectories of the two sites suggest that livestock-loss can potentially be reduced through the revival of wild prey. Further, accommodating counter-factual scenarios may be an important step to infer whether conservation efforts achieve their targets, or not.
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Durbach, I., Borchers, D., Sutherland, C., Sharma, K. (2020). Fast, flexible alternatives to regular grid designs for spatial
capture–recapture..
Abstract: Spatial capture–recapture (SCR) methods use the location of
detectors (camera traps, hair snares and live-capture traps) and the
locations at which animals were detected (their spatial capture
histories) to estimate animal density. Despite the often large expense
and effort involved in placing detectors in a landscape, there has been
relatively little work on how detectors should be located. A natural
criterion is to place traps so as to maximize the precision of density
estimators, but the lack of a closed-form expression for precision has
made optimizing this criterion computationally demanding. 2. Recent
results by Efford and Boulanger (2019) show that precision can be well
approximated by a function of the expected number of detected
individuals and expected number of recapture events, both of which can
be evaluated at low computational cost. We use these results to develop
a method for obtaining survey designs that optimize this approximate
precision for SCR studies using count or binary proximity detectors, or
multi-catch traps. 3. We show how the basic design protocol can be
extended to incorporate spatially varying distributions of activity
centres and animal detectability. We illustrate our approach by
simulating from a camera trap study of snow leopards in Mongolia and
comparing estimates from our designs to those generated by regular or
optimized grid designs. Optimizing detector placement increased the
number of detected individuals and recaptures, but this did not always
lead to more precise density estimators due to less precise estimation
of the effective sampling area. In most cases, the precision of density
estimators was comparable to that obtained with grid designs, with
improvement in some scenarios where approximate CV(¬D) < 20% and density
varied spatially. 4. Designs generated using our approach are
transparent and statistically grounded. They can be produced for survey
regions of any shape, adapt to known information about animal density
and detectability, and are potentially easier and less costly to
implement. We recommend their use as good, flexible candidate designs
for SCR surveys when reasonable knowledge of model parameters exists. We
provide software for researchers to construct their own designs, in the
form of updates to design functions in the r package oSCR.
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