Big cats kill more livestock when wild prey reaches a minimum threshold

Khorozyan, Igor; Ghoddousi, Arash; Soofi, Mahmood; Waltert, Matthias

doi:10.1016/j.biocon.2015.09.031

Cited by 143 publications

(139 citation statements)

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“…However, carnivores can reside in human landscapes, be it at lower densities than in wildlife areas as a result of human‐wildlife conflict (Inskip & Zimmermann, 2009). In some cases carnivores might even be attracted to human landscapes because of the availability of domestic and wild prey (Khorozyan, Ghoddousi, Soofi, & Waltert, 2015; Linnell et al., 2005) and anthropogenic food sources (Cozzi et al., 2016), or because it acts as a refuge from competitors (van der Meer, Fritz, Blinston, & Rasmussen, 2014). As the global human population continues to increase, it is crucial to understand if, and how, carnivores and people can coexist (Carter & Linnell, 2016; Oriol‐Cotterill, Macdonald, Valeix, Ekwanga, & Frank, 2015).…”

Section: Introductionmentioning

confidence: 99%

Living on the edge: Multiscale habitat selection by cheetahs in a human‐wildlife landscape

Klaassen

Broekhuis

2018

Ecology and Evolution

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Animals select habitats that will ultimately optimize their fitness through access to favorable resources, such as food, mates, and breeding sites. However, access to these resources may be limited by bottom‐up effects, such as availability, and top‐down effects, such as risk avoidance and competition, including that with humans. Competition between wildlife and people over resources, specifically over space, has played a significant role in the worldwide decrease in large carnivores. The goal of this study was to determine the habitat selection of cheetahs (Acinonyx jubatus) in a human‐wildlife landscape at multiple spatial scales. Cheetahs are a wide‐ranging, large carnivore, whose significant decline is largely attributed to habitat loss and fragmentation. It is believed that 77% of the global cheetah population ranges outside protected areas, yet little is known about cheetahs’ resource use in areas where they co‐occur with people. The selection, or avoidance, of three anthropogenic variables (human footprint density, distance to main roads and wildlife areas) and five environmental variables (open habitat, semiclosed habitat, edge density, patch density and slope), at multiple spatial scales, was determined by analyzing collar data from six cheetahs. Cheetahs selected variables at different scales; anthropogenic variables were selected at broader scales (720–1440 m) than environmental variables (90–180 m), suggesting that anthropogenic pressures affect habitat selection at a home‐range level, whilst environmental variables influence site‐level habitat selection. Cheetah presence was best explained by human presence, wildlife areas, semiclosed habitat, edge density and slope. Cheetahs showed avoidance for humans and steep slopes and selected for wildlife areas and areas with high proportions of semiclosed habitat and edge density. Understanding a species’ resource requirements, and how these might be affected by humans, is crucial for conservation. Using a multiscale approach, we provide new insights into the habitat selection of a large carnivore living in a human‐wildlife landscape.

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Section: Introductionmentioning

confidence: 99%

Living on the edge: Multiscale habitat selection by cheetahs in a human‐wildlife landscape

Klaassen

Broekhuis

2018

Ecology and Evolution

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“…In addition to wild prey, the tigers are known to prey on domestic livestock. When wild prey, especially medium and large-sized ungulates, become scarce due to population decline or seasonal migrations or human intervention, felids increase predation on livestock to survive (Zhang et al 2013;Baker et al 2008;Khorozyan et al 2015). Because this predation inflicts economic loss on rural livelihoods, tiger populations are severely damaged by retaliatory and preventive persecution (Khorozyan et al 2015).…”

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confidence: 99%

“…When wild prey, especially medium and large-sized ungulates, become scarce due to population decline or seasonal migrations or human intervention, felids increase predation on livestock to survive (Zhang et al 2013;Baker et al 2008;Khorozyan et al 2015). Because this predation inflicts economic loss on rural livelihoods, tiger populations are severely damaged by retaliatory and preventive persecution (Khorozyan et al 2015). This increasing human-carnivore conflict particularly impacts small households near protected areas, challenging the synergy between rural development and biodiversity conservation (Khorozyan et al 2015;Reddy and Yosef 2016).…”

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confidence: 99%

“…Because this predation inflicts economic loss on rural livelihoods, tiger populations are severely damaged by retaliatory and preventive persecution (Khorozyan et al 2015). This increasing human-carnivore conflict particularly impacts small households near protected areas, challenging the synergy between rural development and biodiversity conservation (Khorozyan et al 2015;Reddy and Yosef 2016).…”

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confidence: 99%

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Diet of Bengal Tigers (Panthera tigris tigris) in Chitwan National Park, Nepal

Bhandari¹,

Chalise²,

Pokharel³

2017

European Journal of Ecology

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We studied the diet of the Bengal tigers (Panthera tigris tigris) in Chitwan National Park, Nepal, by identifying 109 prey items from 85 tiger scats. Tigers in this region fed upon eight different mammal species. Chital (Axis axis) was the major prey with a frequency of 45% of the Tigers’ diet. The occurrence of other prey species included sambar (Cervus unicolor, 23%), wild pig (Sus scrofa, 15%), hog deer (Axis porcinus, 9%), barking deer (Muntiacus muntjak, 4%), and gaur (Bos gaurus, 2%). Tigers also hunted livestock, but this prey comprised a small component of the relative biomass (buffalo 5% and cow 2%). Our study suggests that the tiger depends mostly upon wild prey for its subsistence in the Chitwan National Park, but will also sporadically hunt livestock.

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“…These psychological aspects can lead to the best (or just good enough) strategy to follow while foraging. In fact, a too-low expectation can even trigger drastic changes in the usual hunting habits, as recently reported for big felines (36).…”

Section: A New Explanation For Lévy Flightsmentioning

confidence: 64%

Subjective expectation of rewards can change the behavior of smart but impatient foragers

Luz

Raposo

Viswanathan

2016

Proc. Natl. Acad. Sci. U.S.A.

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Search efficiency can be a matter of life and death in biological encounter processes. Animals that fail to explore their environments efficiently suffer heightened risk of earlier death (1). Some theoretical aspects of foraging are closely related to the random search problem of determining the best strategy for optimizing the search when (i) targets are distributed in unknown spatial locations and (ii) learning and other skills (such as long-range ability to detect prey) do not significantly alter the choice of long-term strategy. Also, it is well known (1) that foragers that learn usually outperform foragers that do not. However, it is not yet well established how foraging patterns change when foragers are cognitively complex. In PNAS, Namboodiri et al. (2) propose an interesting framework to understand possible changes in such spatial patterns.Their plausible premise, assuming a smart forager, is that the searcher can attempt to improve future outcomes by determining, through exploratory trial and error, a good strategy. The forager searches by sampling the environment and using "different step lengths so as to maximize the ability to detect differences in reward distributions associated with each step length." The model by Namboodiri et al. (2) predicts that animals attempting to learn optimally from their landscapes will have asymptotically power law-distributed move lengths x. Essentially, such a probability density function (PDF) pðxÞ arises as a consequence of a built-in temporal discounting function DðtÞ, which, according to many behavioral experiments (ref. 2 and also below), should have a "hyperbolic-like" functional form proportional to ð1 + t=c μ Þ −μ , where t is the delay time for access to the reward. The case μ = 1 is often called the hyperbolic discounting function and c μ=1 represents a proper scaling for the underlying dynamics (2). What makes their contribution interesting is that these power law tails are also predicted by the so-called Lévy flight foraging hypothesis (3, 4), proposed to describe random searches in which features i and ii above hold true. The Virtues of ImpatienceTemporal discounting is ubiquitous (5, 6). It is the preference for a reward now or soon rather than the same (or even a somewhat higher) reward later. In economics, temporal discounting is conventionally assumed to be exponential, which is the basis of compound interest (6). For example, if the rate of inflation is fixed, cash devalues exponentially. Empirical studies of discounting choices made by real animals showed that exponential discounting is not necessarily standard (7-13). Many animals seem to use hyperbolic discounting, humans included.Specifically, for a discounting function DðtÞ in the form mentioned above, the reward is discounted very rapidly in the near future, but then more slowly in the distant future (and with a higher rate for larger μ and smaller c μ ). The reasons for preferring hyperbolic over exponential discounting are the subject of intense debate (6, 14). However, we point out that livin...

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Big cats kill more livestock when wild prey reaches a minimum threshold

Cited by 143 publications

References 51 publications

Living on the edge: Multiscale habitat selection by cheetahs in a human‐wildlife landscape

Living on the edge: Multiscale habitat selection by cheetahs in a human‐wildlife landscape

Diet of Bengal Tigers (Panthera tigris tigris) in Chitwan National Park, Nepal

Subjective expectation of rewards can change the behavior of smart but impatient foragers

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