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Predicting Connectivity, Population Size and Genetic Diversity of Sunda Clouded Leopards Across Sabah, Borneo

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Predicting Connectivity, Population Size and Genetic Diversity of Sunda Clouded Leopards Across Sabah, Borneo Landscape Ecol (2019) 34:275–290 https://doi.org/10.1007/s10980-018-0758-1 (0123456789().,-volV)(0123456789().,-volV) RESEARCH ARTICLE Predicting connectivity, population size and genetic diversity of Sunda clouded leopards across Sabah, Borneo Andrew J. Hearn . Samuel A. Cushman . Benoit Goossens . Joanna Ross . Ewan A. Macdonald . Luke T. B. Hunter . David W. Macdonald Received: 23 April 2018 / Accepted: 9 November 2018 / Published online: 16 January 2019 Ó The Author(s) 2019 Abstract quantify the differences in connectivity metrics from Context The Sunda clouded leopard is vulnerable to an empirically optimized model of landscape resis- forest loss and fragmentation. Conservation of this tance with one based on expert opinion. species requires spatially explicit evaluations of the Methods We investigated connectivity metrics for effects of landscape patterns on genetic diversity, Sunda clouded leopards across Sabah, based on an population size and landscape connectivity. empirically optimised, movement based model, and an Objectives We sought to develop predictions of expert-opinion derived model. We used simulation Sunda clouded leopard population density, genetic modelling to predict and compare the patterns and diversity and population connectivity across the state causes of differences in the local neighbourhood of Sabah, Malaysian Borneo. We also wished to population density, distribution, and genetic diversity A. J. Hearn (&) Á J. Ross Á E. A. Macdonald Á B. Goossens D. W. Macdonald Sustainable Places Research Institute, Cardiff University, Wildlife Conservation Research Unit (WildCRU), 33 Park Place, Cardiff CF10 3BA, UK Department of Zoology, University of Oxford, Oxford, UK L. T. B. Hunter e-mail: [email protected] Panthera, New York, NY, USA S. A. Cushman US Forest Service, Rocky Mountain Research Station, 2500 S Pine Knoll Dr, Flagstaff, AZ 86001, USA B. Goossens Danau Girang Field Centre, c/o Sabah Wildlife Department, Wisma Muis, 88100 Kota Kinabalu, Sabah, Malaysia B. Goossens Sabah Wildlife Department, Wisma Muis, 88100 Kota Kinabalu, Sabah, Malaysia B. Goossens Organisms and Environment Division, School of Biosciences, Cardiff University, Sir Martin Evans Building, Museum Avenue, Cardiff CF10 3AX, UK 123 276 Landscape Ecol (2019) 34:275–290 across the two different resistance maps, at two populations, however, there is substantial uncertainty dispersal distances. about all of these parameters. Results The empirical model produced higher esti- In the vast majority of applications expert-opinion mates of population size, population density, genetic has been used to parameterize resistance surfaces diversity and overall connectivity than the expert- (Spear et al. 2010; Zeller et al. 2012). This has opinion model. The overall pattern of predicted potentially serious limitations given that expert-opin- connectivity was similar between models. Both mod- ion is of unknown quality and may often fail to reflect els identified a large patch of core habitat with high accurately the resistance experienced by animals when predicted connectivity in Sabah’s central forest region, moving across the landscape (e.g., Shirk et al. 2010; and agreed on the location and extent of the main Wasserman et al. 2010; Shirk et al. 2015). This is isolated habitat fragments. particularly true of many threatened species, for which Conclusions We identified clear relationships even a basic understanding of their ecology is often between landscape composition and configuration lacking. A number of methods have been developed to and predicted distribution, density, genetic diversity estimate landscape resistance empirically using and connectivity of Sunda clouded leopard popula- genetic (e.g., Cushman et al. 2006; Shirk et al. 2010; tions. Core areas are comprised of large and unfrag- Castillo et al. 2014) and movement (e.g., Blazquez- mented forest blocks, and areas of reduced forest cover Cabrera et al. 2016; Cushman et al. 2016; Zeller et al. comprise barriers among patches of predicted remain- 2017, 2018) data. These approaches have the advan- ing habitat. tage that they are directly estimated using data from the key processes of interest. Indeed, when compared Keywords Clouded leopard Á Connectivity Á with expert-opinion or habitat suitability based mea- UNICOR Á CDPOP Á Fragmentation Á Habitat loss sures, resistance surfaces directly estimated from movement and genetic data have shown superior performance (e.g., Shirk et al. 2010; Wasserman et al. 2010; Mateo Sa´nchez et al. 2014, 2015; Zeller et al. Introduction 2018). Movement and genetic data are often lacking for many threatened species, however, and are typi- In the face of accelerating global habitat loss and cally very costly to acquire. In the absence of such fragmentation there is an increasing need to predict empirical data, expert opinion based estimates of accurately how changes to landscape structure affect landscape resistance may therefore provide a useful the population connectivity of threatened species initial prediction of population connectivity, particu- (Spear et al. 2010; Zeller et al. 2012; Cushman et al. larly for those species for which a basic understanding 2013a). Such insights can provide a foundation upon of habitat associations is available (e.g., Riordan et al. which to develop effective conservation action 2015; Moqanaki and Cushman 2016). (Chetkiewicz et al. 2006). At its core, population The forests of Borneo host one of the richest connectivity is the product of the movement of biological assemblages on Earth, yet the island is also individual organisms across a landscape, the surface a global hotspot of forest loss and degradation of which varies in its resistive qualities. Such move- (Gaveau et al. 2014; Cushman et al. 2017). These ments are shaped by the compounding influences of anthropogenic driven changes to Borneo’s forests are the composition and structure of the landscape (Zeller exemplified by the Malaysian state of Sabah, which et al. 2013), the distribution and density of the occupies the northern part of the island. In 2010, forest population (Cushman 2006), and the specific dispersal accounted for 47.5% of the state’s land area traits of the species (e.g., Abrahms et al. 2017). Of (35,006 km2), following a rapid decline from 78.6% these, the complex interplay between a species’ in 1973, representing the highest deforestation rate of dispersal characteristics and landscape features is all the political units on Borneo during this period arguably the most important factor mediating land- (Gaveau et al. 2014). Selective logging activities have scape resistance and subsequent population connec- been the primary driver of forest degradation through- tivity (Spear et al. 2010; Zeller et al. 2012). In most out the state, and the subsequent conversion of these degraded forests to mono-culture plantations, chiefly 123 Landscape Ecol (2019) 34:275–290 277 that of oil palm (McMorrow and Talip 2001), remains connectivity across the entire island of Borneo. They the principal driver of forest loss (Gaveau et al. 2014). estimated that between 2000 and 2010 the proportion In 2015 oil palm plantations accounted for around of landscape connected by dispersal had fallen by 21% of land area (15,442 km2) in 2015 (Malaysian approximately 24% and the largest patch size had Palm Oil Board 2016). Understanding the impact of declined by around 30%, leading to a 13% decline in such changes to species of conservation concern clouded leopard numbers. Macdonald et al.’s (2018) remains a research priority. analysis, however, was based on an expert-opinion Individual species responses to logging regimes derived model of Sunda clouded leopard resistance to vary, but research is increasingly showing that selec- movement, and so warrants empirical testing. In tively logged Bornean forests can retain considerable addition, conservation is conducted at the regional levels of pre-disturbance biodiversity (e.g., Meijaard scale by state and provincial governments and thus et al. 2005; Costantini et al. 2016), as well as the effective planning of such action requires the devel- capacity to serve as corridors for less disturbance opment of connectivity predictions at these spatial tolerant species moving between intact forest frag- scales. ments. The establishment of industrial scale planta- In this paper we had two main objectives. First, we tions of oil palm Elaeis guineensis, however, can lead sought to extrapolate the Hearn et al. (2018) empirical to dramatic declines in species richness (e.g., Fitzher- resistance model to predict population density, genetic bert et al. 2008) and greatly inhibit connectivity of diversity and population connectivity for Sunda forest dependent species (e.g., Hearn et al. 2018). clouded leopards across the full extent of Sabah. Thus, for species of conservation concern on Borneo Second, we wished to quantify the differences in there is an urgent need for connectivity modelling to predicted population density, genetic diversity and assess impacts of landscape change to inform the population connectivity obtained from the Hearn et al. development of effective conservation strategies. (2018) empirically optimized and the Macdonald et al. The Sunda clouded leopard Neofelis diardi is the (2018) expert-opinion resistance surfaces at the full apex carnivore on the Sundaic islands of Borneo and Sabah extent. We hypothesised that (H1) the empirical Sumatra, where it is threatened with extinction (Hearn resistance model would produce higher estimates
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