Clouded in mystery: the global trade in clouded leopards

D’Cruze, Neil; Macdonald, David W.

doi:10.1007/s10531-015-1010-9

Cited by 39 publications

(19 citation statements)

References 19 publications

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“…Illegal persecution and trade in skins and parts threaten clouded leopard survival (Nowell & Jackson, 1996;Nijman & Shepherd, 2015;Min et al, 2018). Rapid development, increasing human population, deforestation and habitat fragmentation, and ineffective protected area management add to the pressing threats to the clouded leopard across its range (Choudhury, 1993;D'Cruze & Macdonald, 2015;DeFries, Hansen, Newton, & Hansen, 2005;Rabinowitz, 1988). Against this background, a reliable estimate of the population is an important datum for the understanding of forest carnivore guilds in Southeast Asia and also important to underpin conservation planning (Murphy & Noon, 1992).…”

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confidence: 99%

Identifying important conservation areas for the clouded leopard Neofelis nebulosa in a mountainous landscape: Inference from spatial modeling techniques

Penjor

Macdonald

Wangchuk

et al. 2018

Ecology and Evolution

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The survival of large carnivores is increasingly precarious due to extensive human development that causes the habitat loss and fragmentation. Habitat selection is influenced by anthropogenic as well as environmental factors, and understanding these relationships is important for conservation management. We assessed the environmental and anthropogenic variables that influence site use of clouded leopard Neofelis nebulosa in Bhutan, estimated their population density, and used the results to predict the species’ site use across Bhutan. We used a large camera‐trap dataset from the national tiger survey to estimate for clouded leopards, for the first time in Bhutan, (1) population density using spatially explicit capture–recapture models and (2) site‐use probability using occupancy models accounting for spatial autocorrelation. Population density was estimated at trueD^normalBayesian=0.40 (0.10 SD) and trueD^maximum−likelihood=0.30 (0.12 SE) per 100 km2. Clouded leopard site use was positively associated with forest cover and distance to river while negatively associated with elevation. Mean site‐use probability (from the Bayesian spatial model) was trueψ^normalspatial=0.448 (0.076 SD). When spatial autocorrelation was ignored, the probability of site use was overestimated, trueψ^normalnonspatial=0.826 (0.066 SD). Predictive mapping allowed us to identify important conservation areas and priority habitats to sustain the future of these elusive, ambassador felids and associated guilds. Multiple sites in the south, many of them outside of protected areas, were identified as habitats suitable for this species, adding evidence to conservation planning for clouded leopards in continental South Asia.

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confidence: 99%

Identifying important conservation areas for the clouded leopard Neofelis nebulosa in a mountainous landscape: Inference from spatial modeling techniques

Penjor

Macdonald

Wangchuk

et al. 2018

Ecology and Evolution

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“…This shows a large mismatch between the existing protected area network and the most important forest habitats for this species, and argues for a large and ambitious expansion of protected areas, ideally prioritizing the highest ranked core areas and corridors. Furthermore, even within protected areas, management, law enforcement and level of corruption greatly varies across SE Asian countries (D'Cruze & Macdonald, 2015), and often severely degrades the effectiveness of protected areas.…”

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confidence: 99%

Prioritizing habitat core areas and corridors for a large carnivore across its range

Kaszta

Cushman

Macdonald

2020

Animal Conservation

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With increasing loss and fragmentation of habitats driving the emerging global extinction crisis, paired with limited resources for conservation, there is an immense need to identify and prioritize the most important areas for conservation actions. The goal of this study was to measure, map and rank core areas and corridors for mainland clouded leopard (a forest indicator species) across its entire range in Southeast Asia. We used an empirically based landscape resistance model developed from range-wide camera survey data, cumulative resistant kernel analysis to define core areas and least-cost network analysis to identify corridors for longdistance dispersal. We then ranked core areas based on their strength and size, and corridors based on their strength and the strength of core areas they connect. We found that the most important core areas and corridors are concentrated in Southeast Asia, largely in Myanmar, Laos and Malaysia. Myanmar contains nearly the entirety of the first and third highest ranked core areas, as well as the most important network of corridors in SE Asia. Almost the entire territory of Laos constitutes one large potential core area, ranked as the second most important across the clouded leopard's range. A large number (22) of very small (<8000 km 2) and fairly isolated core areas are in China. Only 24% of clouded leopard core areas and 17% of corridors are protected. This is the first example of using empirical models to prioritize conservation actions across the full range of a large carnivore. Our analysis identifies the location, size and connectivity of the most important remaining habitats of the clouded leopard across its range, which could provide quantitative guidance in the efforts to maximize the efficacy of regional conservation initiatives to conserve this species and the ecosystems it inhabits.

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“…Regardless of the report type, a misconception is that each row in the data represents an individual shipment or trade transaction (e.g., D'Cruze & Macdonald []), which is not the case. All data for the year concerning the same taxa, exporter, importer, and trade terms are aggregated in 1 row (UNEP‐WCMC ).…”

Section: Comparative Versus Gross or Net Trade Reportsmentioning

confidence: 99%