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Petaling Jaya, Malaysia

Wilting A.,Leibniz Institute for Zoo and Wildlife Research | Mohamed A.,WWF Malaysia | Hofer H.,Leibniz Institute for Zoo and Wildlife Research | Sollmann R.,North Carolina State University
ORYX | Year: 2012

Recently the Sunda clouded leopard Neofelis diardi was recognized as a separate species distinct from the clouded leopard Neofelis nebulosa of mainland Asia. Both species are categorized as Vulnerable on the IUCN Red List. Little is known about the newly identified species and, in particular, information from forests outside protected areas is scarce. Here we present one of the first density estimates calculated with spatial capture-recapture models using camera-trap data. In two commercial forest reserves in Sabah (both certified for their sustainable management practices) the density of the Sunda clouded leopard was estimated to be c. 1 per 100 km2 (0.84±SE 0.42 and 1.04±SE 0.58). The presence of the Sunda clouded leopard in such forests is encouraging for its conservation but additional studies from other areas, including protected forests, are needed to compare and evaluate these densities. © 2012 Fauna & Flora International. Source

Mohamed A.,WWF Malaysia | Mohamed A.,Universiti Malaysia Sabah | Sollmann R.,North Carolina State University | Bernard H.,Universiti Malaysia Sabah | And 5 more authors.
Journal of Mammalogy | Year: 2013

The small (2- to 7-kg) leopard cat (Prionailurus bengalensis) is the most common cat species in Asia. Although it occurs in a wide range of habitats and seems to adapt well to anthropogenic habitat changes, surprisingly little is known about this species in the wild. All studies have focused on protected areas, although a large proportion of Southeast Asian forests are timber concessions. During this study, we used large camera-trapping data sets (783 records of 124 individuals) from 3 commercially used forests to investigate consequences of different logging regimes on density and habitat associations of the leopard cat. We applied spatial capture-recapture models accounting for the location of camera-traps (on or off road) to obtain estimates of leopard cat density. Density was higher in the 2 more disturbed forest reserves (X̄ = 12.4 individuals/100 km2 ± 1.6 SE and 16.5 ± 2 individuals/100 km2) than in the sustainably managed forest (9.6 ± 1.7 individuals/100 km2). Encounter rates with off-road traps were only 3.6-9.1% of those for on-road traps. Occupancy models, which accounted for spatial autocorrelation between sampling sites by using a conditional autoregressive model, revealed that canopy closure and ratio of climax to pioneer trees had a significantly negative impact on leopard cat occurrence. Our results confirm that the leopard cat is doing well in modified landscapes and even seems to benefit from the opening of forests. With such flexibility the leopard cat is an exception among tropical rain-forest carnivores. © 2013 American Society of Mammalogists. Source

Sollmann R.,North Carolina State University | Mohamed A.,WWF Malaysia | Mohamed A.,Universiti Malaysia Sabah | Samejima H.,Kyoto University | Wilting A.,Leibniz Institute for Zoo and Wildlife Research
Biological Conservation | Year: 2013

Camera-traps are a widely applied to monitor wildlife populations. For individually marked species, capture-recapture models provide robust population estimates, but for unmarked species, inference is often based on relative abundance indices (RAI, number of records per trap effort), although these do not account for imperfect and variable detection. We use a simulation study and empirical camera-trapping data to illustrate how ecological and sampling-related factors can bias RAIs. Our simulations showed that (1) differences in detection between species led to bias in RAI ratios toward the more detectable species, especially at low detection levels, (2) species with larger home ranges were photographed more often, inflating RAIs, (3) species specific responses to different types of trap setup biased RAI ratios, and (4) changes in detection over time blurred true population trends inferred from RAIs. Empirical data for leopard cats Prionailurus bengalensis and common palm civets Paradoxurus hermaphroditus showed that traps set up along roads led to higher RAIs than off-road traps, but targeting roads increased detection more for leopard cats than for common palm civets. Comparing RAIs of Sunda clouded leopards Neofelis diardi and leopard cats with spatial capture-recapture based density estimates across sites, RAIs did not reflect differences in density. Analytical options for estimating density from camera-trapping data of unmarked populations are limited. Consequently, we fear that RAIs will continue to be applied. This is alarming, since these measures often form the basis for conservation and management decisions. We suggest considering alternative analytical and survey methods, especially when dealing with threatened species. © 2012 Elsevier Ltd. Source

Kanagaraj R.,Helmholtz Center for Environmental Research | Wiegand T.,Helmholtz Center for Environmental Research | Mohamed A.,WWF Malaysia | Mohamed A.,Universiti Malaysia Sabah | Kramer-Schadt S.,Leibniz Institute for Zoo and Wildlife Research
Raffles Bulletin of Zoology | Year: 2013

Knowing the distribution of species and the factors which determine it is a basic requirement for conservation efforts and developing management plans. Species distribution modelling (SDM) is a speedy and cost-effective tool for predicting species distributions, particularly for species in remote and inaccessible areas. This technique can be applied for example for poorly known small carnivore species in Southeast Asia, a biodiversity hot spot for mammals. SDM is used to gain ecological insights about the environmental factors that determine species distribution, and helps to identify the areas where a species can occur and where confl icts may arise. However, recent advances in statistical theory and computer processing have made SDM a somewhat complex, diverse, and confusing area of research. This review presents an overview over the different techniques of species distribution modelling, and databases needed to answer applied questions in carnivore conservation, particularly in the tropics. We guide the ecologist through different methods which have become established approaches in the scientifi c literature and through freely available resources on abiotic data (environmental layers) for conducting such studies. We summarise the steps involved in predictive species distribution modelling, where the (carnivore) occurrence data come from different resources (such as museum records, voluntary surveys, systematic surveys, etc.). Finally, we explore the applications of such predictions in carnivore conservation. © National University of Singapore. Source

Linkie M.,Fauna and Flora International | Guillera-Arroita G.,University of Kent | Smith J.,Panthera | Rayan D.M.,WWF Malaysia | Rayan D.M.,University of Kent
Integrative Zoology | Year: 2010

With only 5% of the world's wild tigers (Panthera tigris Linnaeus, 1758) remaining since the last century, conservationists urgently need to know whether or not the management strategies currently being employed are effectively protecting these tigers. This knowledge is contingent on the ability to reliably monitor tiger populations, or subsets, over space and time. In the this paper, we focus on the 2 seminal methodologies (camera trap and occupancy surveys) that have enabled the monitoring of tiger populations with greater confidence. Specifically, we: (i) describe their statistical theory and application in the field; (ii) discuss issues associated with their survey designs and state variable modeling; and, (iii) discuss their future directions. These methods have had an unprecedented influence on increasing statistical rigor within tiger surveys and, also, surveys of other carnivore species. Nevertheless, only 2 published camera trap studies have gone beyond single baseline assessments and actually monitored population trends. For low density tiger populations (e.g. <1 adult tiger/100 km2) obtaining sufficient precision for state variable estimates from camera trapping remains a challenge because of insufficient detection probabilities and/or sample sizes. Occupancy surveys have overcome this problem by redefining the sampling unit (e.g. grid cells and not individual tigers). Current research is focusing on developing spatially explicit capture-mark-recapture models and estimating abundance indices from landscape-scale occupancy surveys, as well as the use of genetic information for identifying and monitoring tigers. The widespread application of these monitoring methods in the field now enables complementary studies on the impact of the different threats to tiger populations and their response to varying management intervention. © 2010 ISZS, Blackwell Publishing and IOZ/CAS. Source

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