Anthropogenic disturbance and habitat loss for the red-listed Asiatic black bear (Ursus thibetanus): Using ecological niche modeling and nighttime light satellite imagery

Biological Conservation 191 (2015) 400–407

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Anthropogenic disturbance and habitat loss for the red-listed Asiatic black bear (Ursus thibetanus): Using ecological niche modeling and nighttime light satellite imagery Luis E. Escobar a, Muhammad Naeem Awan b,c, Huijie Qiao d,⁎ a

Center for Global Health and Translational Science, State University of New York Upstate Medical University, Syracuse, NY, USA Himalayan Nature Conservation Foundation, Muzaffarabad, Azad Kashmir 13100, Pakistan c Department of Zoology, University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan d Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101 China b

a r t i c l e

i n f o

Article history: Received 8 January 2015 Received in revised form 23 June 2015 Accepted 27 June 2015 Available online xxxx Keywords: Ecological niche model Disturbance Habitat loss Land use change Nighttime lights Ursus thibetanus

a b s t r a c t Habitat loss is a critical factor driving extinction of biodiversity worldwide, with models of future land use anticipating increases in rates of destruction of native habitats worldwide. The Asian black bear (Ursus thibetanus) is a red-listed species with a broad geographic range that has been fragmented dramatically by land use change. Remaining populations of U. thibetanus occupy diverse habitats, ranging from highlands to coastal regions. We integrated ecological niche models (ENMs) with nighttime satellite imagery to identify areas suitable for U. thibetanus after anthropogenic alteration. We found that at least 10% of the potential distributional area for the species is not suitable owing to urban or suburban encroachment. U. thibetanus seems to persist in highland areas, characterized by low temperature and high precipitation, whereas humans concentrate in lowlands and less-extreme climatic conditions. ENMs based solely on climate frequently overestimate suitable areas available for species; nighttime light imagery offers a robust alternative to refining estimates of species' ranges, designing protected areas and corridors, prioritizing threatened species, and determining areas of human–wildlife conflict across broad areas. Our approach is transferable to other taxa and contexts, and should be considered in conservation planning and policy implementation. © 2015 Elsevier Ltd. All rights reserved.

1. Introduction Most endangered species are threatened by multiple factors, but habitat loss is generally implicated as a principal cause of biodiversity loss worldwide (Sodhi and Ehrlich, 2010). Habitat loss reduces prey populations and other resources for species, and can also increase frequency of human–wildlife conflicts, which represent significant threats to wildlife worldwide (Woodroffe et al., 2005). While relatively undisturbed ecosystems exist, they are now often heavily fragmented and isolated by agriculture, urban, and industrial activities (Caro et al., 2012; Convention on Biological Diversity, 2010). A recent evaluation of macro-economic effects on current land use patterns predicts that land cover change will continue into the future, with dramatic increases in urbanization and peri-urban development (van Asselen and Verburg, 2013). Consequently, identifying priority sites for conservation characterized by minimal human conflict that would require minimal direct investment of effort and resources for effective protection is critical (Myers et al., 2000).

⁎ Corresponding author. E-mail addresses: [email protected] (L.E. Escobar), [email protected] (M.N. Awan), [email protected] (H. Qiao).

http://dx.doi.org/10.1016/j.biocon.2015.06.040 0006-3207/© 2015 Elsevier Ltd. All rights reserved.

The Asiatic black bear (Ursus thibetanus) has a broad geographic distribution across southern Asia, including eastern Russia, northern India, and northeastern China (Servheen, 1990). The species' distribution was originally continuous across all or parts of China, Pakistan, India, Japan, and Nepal, and south into Myanmar and the Malay Peninsula. China contains the largest portion of the species' range (Garshelis and Steinmetz, 2008), but uncertainty exists about its abundance in this country (Liu et al., 2009). Fossil remains of U. thibetanus have been found as far west as Germany and France, but the modern distribution of the species is limited to Asia (Garshelis and Steinmetz, 2008). The species tends to focus activities in areas with abundant corn, beechnuts, walnuts, chestnuts, hazelnuts, or pine seeds (Garshelis and Steinmetz, 2008; Hwang et al., 2002), although its diet also includes meat from ungulates, which they either kill or scavenge (Hwang et al., 2002) (Fig. 1). A hyperphagia state before hibernation has been reported in natural and rural areas, with changes in diet during this period (Baruch-Mordo et al., 2013; Malcolm et al., 2014). Even given its apparent ecological plasticity and current national and international protection, the species appears to be declining rapidly (Garshelis and Steinmetz, 2008). Competition for space and resources and fear of negative encounters on the part of local people has resulted in increasing numbers of human–bear conflicts (Awan, 2014; Charoo

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Fig. 1. Current populations of Ursus thibetanus. Red areas represent the current distribution of the bear according to IUCN (2014). Black squares denote occurrence data from GBIF and VertNet that were used for model evaluation. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

et al., 2009; Chauhan, 1989; Kubo and Shoji, 2014; Malcolm et al., 2014). U. thibetanus is critically endangered in several countries in Asia (Garshelis and Steinmetz, 2008), owing to habitat loss, trade of body parts (e.g., skin and claws), live cub trade for bear baiting (i.e., illegal fights with dogs), dancing bears, and bile farms (Garshelis and Steinmetz, 2008; Livingstone and Shepherd, 2014; Malcolm et al., 2013). 1.1. Species range and distributional modeling Effective conservation planning for U. thibetanus must, in the long term, consider the species' entire geographic range (Charoo et al., 2009; Nawaz, 2008; Servheen, 1990). Current distributional maps, however, lack detail and resolution (IUCN, 2014). Modeling the species' ecological niche provides a robust and useful method by which to delimit detailed geographic ranges, guide research, and establish priority areas for conservation (Anderson and Martínez-Meyer, 2004; Elia et al., 2015; Poo-Muñoz et al., 2014). Ecological niche modeling (ENM) associates environmental values with species' occurrences in a multivariate analysis, identifying the set of environmental combinations that are suitable for the species and corresponding potential geographic ranges (Peterson et al., 2011). In this study, we explore the potential distribution of U. thibetanus, and assess how its distributional extent may change given current anthropogenic disturbance regimes. This exploration identifies areas where populations of U. thibetanus have the most potential to survive in the long term. 2. Materials and methods 2.1. Ecological niche modeling Ecological niches are defined under the BAM framework, where B (i.e., Biotic) represents the geographic areas presenting the appropriate sets of interacting species (e.g., prey, competitors), A (i.e., Abiotic) represents areas that present suitable environmental conditions (e.g., climate), and M (i.e., Movement) represents the areas accessible to the species over relevant time periods (Peterson et al., 2011;

Soberón and Peterson, 2005). Hence, the occupied distributional area (Go) of a species is defined as the areas Go = A ∩ B ∩ M. Here, we generated a detailed map of U. thibetanus' potential distribution using ENM, which we discuss more fully below. We defined the calibration area as equivalent to M based on previous knowledge on the species and its dispersal potential (Barve et al., 2011), as follows. First, we used a proposed map of the historical range of U. thibetanus as a proxy of the geographic areas where the species was known or believed to have resided in the past (Garshelis and Steinmetz, 2008). Then, as an estimation of the minimum dispersal potential of the species in mainland, we measured the width of the narrow area of the species' range in the Himalayan Mountains corridor (Garshelis and Steinmetz, 2008). The resulting distance, 250 km, was used as a buffer around the historical range of U. thibetanus. The known historical range buffered by our hypothesis of the movement capacity of the species was the final M area used for model calibration. Considering the extent of our M area (i.e., continental), our A component consisted of coarse-scale climatic and topographic variables. Specifically, we included 15 “bioclimatic” layers plus elevation, all at ~ 4.6 km (2.5′) spatial resolution. The climatic data included annual mean temperature, mean diurnal range of temperature, isothermality, temperature seasonality, maximum temperature of warmest month, minimum temperature of coldest month, temperature annual range, mean temperatures of warmest and coldest quarters, annual precipitation, precipitation of wettest and driest months, precipitation seasonality, and precipitation of wettest quarter (Hijmans et al., 2005). To avoid model overfit, we reduced the number and correlation of environmental variables used for model calibration via a principal component analysis (Peterson et al., 2011), in which we retained the first 6 components for ENM calibration. These data layers summarized 99.99% of total variance in the original environmental variables (Supplementary material S1). We calibrated the niche model based on the present-day distribution of U. thibetanus. We represented the species' distribution using 3000 random points distributed across the species' present-day distributional area, covering 1.34 × 106 km2, as proposed by the International Union for Conservation of Nature (Garshelis and Steinmetz, 2008). This

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step allowed us to capture environmental conditions suitable for present-day populations of U. thibetanus (Fig. 1). Niche modeling was implemented using Maxent software, version 3.3.3.k (Phillips et al., 2006). Maxent is a presence-background ENM program that has performed well in associating species occurrence data with environmental features (Elith et al., 2006). The algorithm (i.e., maximum entropy) searches for the most uniform probability distribution of species' occurrences, subject to the constraint of environmental values in the area (Elith et al., 2011; Phillips et al., 2006). The following settings were used: 100 bootstrap permutations to capture model variability, 20% of random occurrences for model testing, and logistic output as the suitability index. The median of the 100 models was used as the best hypothesis of the potential distribution of U. thibetanus. From the suitability index, we generated a binary map using as a threshold the highest value that included 95% of calibration points (i.e., E = 5% omission error) (Peterson et al., 2008, 2011). To assess predictive performance of our model, we collected actual U. thibetanus occurrence data. These additional observations were gathered from natural history museum databases, including data derived via the Global Biodiversity Information Facility (http://www.gbif.org/) and VertNet (http://www.vertnet.org) (Constable et al., 2010; Flemons et al., 2007). Occurrences were placed on the binary map to establish omission error rates and develop a cumulative binominal test of the statistical significance of model predictions (Peterson et al., 2011). 2.2. Anthropogenic perturbation The ecological niche model predicts the species' potential distribution with respect to climate and topography (Peterson et al., 2011). To account for all factors in the BAM framework, however, we explored whether adding a biotic interaction (e.g., human–bear) could refine our predictions of the present-day potential distribution of the species. Hence, we explored the interaction between U. thibetanus distribution and anthropogenic disturbance. Anthropogenic disturbance was characterized in the form of a recent nighttime light satellite image at ~ 0.75 km resolution matching our field work period, collected by the

VIIRS sensor, Suomi NPP satellite during 9 days in April and 13 days in October 2012 (available at http://1.usa.gov/1FQvs5r). The nighttime light information was captured by the day–night band of the sensor that detects light from visible to infrared. We used the first of the three bands that composes this image, with reflectance values ranging from 0 (dark) to 255 (cities). Although some nighttime light may reflect wildfires, we assumed that most or all values derived from human perturbation in the form of artificial light from cities, and settlements. Interactions between U. thibetanus and anthropogenic disturbance were estimated using recent field data of the species' occurrence across northern Pakistan. This area was selected because of long-term reports of the species in the Pir-Chinasi and Pir-Hasimar mountains, Kashmir Himalaya, Pakistan (73.48°–73.72° E, 34.22°–34.40° N). The region is part of the Western Himalayan biodiversity hotspot, with a subtropical highland climate (Awan, 2014), represented by sub-tropical Chir pine forest, mixed coniferous forests, and sub-alpine/alpine pastures. Human populations in the area depend on subsistence agriculture and livestock. Human–wildlife conflicts in the area are frequent in light of an abundance of bears and close ties that the native people have to the land (Awan, 2014). Field observations allowed us to estimate a proxy of the level of anthropogenic disturbance that U. thibetanus can withstand, as follows. First, we searched for U. thibetanus tracks in the field between June–September 2012 (Fig. 2). The study area was divided into 17 grids (5 × 5 km) and 10 points were randomly established within a 50 m radius each to generate a survey plot (Awan, 2014). In total, we established 170 survey plots, and each plot was visited once for evidence of U. thibetanus, including footprints, marks on trees, feces, or feeding platforms (Fig. 2). Tracks were georeferenced in the form of single latitude and longitude coordinates for each site with signs of U. thibetanus. Using these data, we determined nighttime light reflectance values; the highest nighttime light reflectance value associated with occurrence tracks was used as a pragmatic criterion to define a threshold representing the light level above which the species avoids artificial light. This threshold was applied to the nighttime light image across the entire study area to reclassify it to binary: currently suitable (i.e., below the threshold) and currently unsuitable areas (i.e., light

Fig. 2. Ursus thibetanus tracks found in field surveillance. A. Claw-marks on tree; B. footprint; C. feces; D. feeding platform.

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values above the threshold). Additionally, after considering both environmental suitability and human disturbance factors, we explored the association between the Maxent suitability index and nighttime light values to seek areas that are most suitable and least perturbed. All analyses were carried out using ArcGIS version 9.3 (ESRI, 2009), NicheA 3.0 (Qiao et al., 2015), and R 3.1.2 (R Core Team, 2012). 3. Results 3.1. Ecological niche modeling A total of 61 additional occurrences was used to assess the predictive power of the ecological niche model (Supplementary material S3). The model did not omit any of these occurrences, and yet the thresholded prediction covered only 36.73% of the study area, suggesting high model predictivity (omission error = 0%; P b 0.001). The binary suitability map generated from the niche model suggested a potential distribution for U. thibetanus that covers 13.1 × 106 km2 (Supplementary material S4). 3.2. Anthropogenic perturbation In total, we found 46 sites with U. thibetanus sign as part of our field surveillance (Figs. 2 and 3; Supplementary material S5). The coordinates of these tracks were used to establish the tolerance threshold of U. thibetanus to anthropogenic disturbance (Fig. 3; Supplementary material S5 and Supplementary material S6). Nighttime light values in the occurrences ranged between 2 and 66 with an average of 9.9. The highest nighttime light value associated with U. thibetanus tracks was used to remove areas with high anthropogenic disturbance above this threshold, which reduced the predicted suitable area to 11.8 × 106 km2 of presentday potential distribution (Supplementary material S7). As a result, the

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original niche model based on climate and topography was reduced by 9.97% when we considered artificial light as a proxy of human presence and potential for conflicts (Fig. 4; Supplementary material S7). When light was accounted for in the model, climatically-suitable areas for U. thibetanus at low elevations (i.e., b500 m), with precipitation levels of 500–1500 m were no longer available to the species (Fig. 5). The areas that remained habitable for the species were those at high elevations, with low temperature values and very low or very high precipitation levels. Distributional areas characterized by temperatures N10 °C were reduced considerably, as such conditions usually coincided with human presence. Our exploration of associations between environmental suitability and anthropogenic disturbance revealed continuous corridors in the form of areas that are both highly suitable climatically and that have low human disturbance (Fig. 6). 4. Discussion We combined ENM with artificial (nighttime) light information from remote sensing data to refine a model of the potential distribution of U. thibetanus. Our model was generated using range data derived from IUCN extent of occurrence summaries (Garshelis and Steinmetz, 2008), tested using natural history museum data (Constable et al., 2010; Flemons et al., 2007), and refined based on detections in onground field work in Pakistan. 4.1. Present-day occurrence and conservation According to the IUCN (2014) map of present-day U. thibetanus extent of occurrence, current populations of the species occur in small areas of southern, western, and northern Pakistan; northern Nepal; and in India in the northernmost parts of the country (Srinagar, Himachal Pradesh, Uttarakhand, Assam, Nagaland, Meghalaya, Manipur, and Mizoram). In

Fig. 3. Nighttime light image. Ursus thibetanus' potential distribution according to the climate and elevation-based ecological niche model (red line), as related to background levels of artificial light ranging from low (black) to high (white). Inserted, close-up of data on Ursus thibetanus' occurrence (green points) found in the course of our field studies in northern Pakistan. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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Fig. 4. Ecological niche model for Ursus thibetanus. Potential distribution based on areas climatically suitable for the Asian black bear (Ursus thibetanus; red) and areas environmentally unsuitable (gray) are shown across the study area (dotted line). Several areas environmentally suitable are currently occupied by human settlements and were classified as unsuitable due to anthropogenic perturbation (i.e., human–wildland interface non-tolerable by the species; see Materials and methods); such areas are denoted in yellow. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Bangladesh, the species is found in the southern part of the Chittagong Division; its range also covers small portions of central Bhutan and Burma; isolated patches in Thailand, Cambodia, and Laos; northern South Korea; central North Korea; and parts of Japan and Taiwan. On the Chinese mainland, U. thibetanus populations can be found in Sichuan, Shaanxi, Guangxi, Jilin, and Heilongjiang provinces, and in a small portion of northern Hunan. Russia holds populations in Khabarovsk Krai, Primorsky Krai, and a vast area in the Jewish Autonomous Oblast (Fig. 1; Supplementary material S2). Habitat loss from logging, expansion of human settlements, roads, and hydro-power stations, combined with hunting for skins, paws, and especially gall bladders, represent the chief threats to this species (Garshelis and Steinmetz, 2008; Malcolm et al., 2014). Besides habitat loss, the species may not occupy the entire geographic extent of climatically suitable areas owing to local-scale biological interactions, such as poaching by humans, low food availability, and disease (Maher et al., 2010; Malcolm et al., 2014). Current evidence suggests that the species is not restricted to protected areas, often venturing beyond park boundaries to look for resources, thus increasing the risk of poaching (Malcolm et al., 2014) or another conflicts with humans. According to Garshelis and Steinmetz (2008), U. thibetanus occupies diverse forested habitats, but habitat degradation and hunting have reduced populations by 50% over the past 30 years. This rate of population reduction is predicted to continue in coming decades unless effective conservation plans are implemented (Garshelis and Steinmetz, 2008).

(Fig. 1 vs. Fig. Supplementary material S7). In fact, the species is isolated in small populations scattered across Asia. In our study, constructing a model of the species' potential distribution using climate data only failed to describe realistically the areas available to the species under present-day land cover conditions. While abiotic factors like climate and topography limit species' distributions at coarse scales (Soberón, 2007), incorporating land cover and vegetation indices has improved the predictive power of niche models significantly (Waltari et al., 2014; Zimmermann et al., 2007). That said, however, ENMs based solely on land cover variables will not identify areas that were suitable in previous times (i.e., before land use change). Consequently, remote sensing imagery can be used in a post-processing step to create more detailed and up-to-date maps of species' present-day potential distributions. Combining climate with remote sensing data will improve ability to generate ENMs that describe historical ranges in the form of potential distribution maps (i.e., ENMs based on climate) and present-day suitable areas (i.e., ENM based on climate + nighttime light data). While ENM is growing in importance in ecology and conservation (Franklin, 2009; Peterson et al., 2011), few studies report using nighttime light satellite imagery in conservation applications (Escobar, 2013; Mazor et al., 2013). The technique, however, represents an effective approach, and a useful alternative to land use data derived from vegetation indices for examining factors in biodiversity loss. 4.3. Anthropogenic perturbation

4.2. Ecological niche modeling The ENM result predicted suitable areas in areas outside the historical range summarized by the IUCN (Garshelis and Steinmetz, 2008). Considering the present-day range of U. thibetanus, we found that the species occupies only 10.3% of its present-day potential distribution

When our ENMs were refined using nighttime light information, we found that areas with suitable environmental conditions were reduced for U. thibetanus owing to inter-specific competition with humans; this effect represents an example of the B component in the BAM framework (Soberón and Peterson, 2005). Removing areas with anthropogenic

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degradation in Dhaka. We found anthropogenic disturbance above the estimated threshold for U. thibetanus in large areas in Bangkok and Chiang Mai, Thailand; and near Ho Chi Minh City and Phan Thiet, Vietnam. Dramatic anthropogenic disturbance was evident in Sichuan, Chongqing, Hubei, Hunan, Guangdong, Fujian, a large part of Taiwan, Jiangsu, Shanghai, Zhejiang, Beijing, Tianjin, Shandong, Liaoning, Jilin, and Heilongjiang in China; also we found extensive disturbance in Tokyo, Nagoya, Osaka, Okayama, and Fukuoka, in Japan. On the other hand, the Russian far east (Jewish Autonomous Oblast) showed high connectivity of suitable areas. While protected areas may provide some level of protection to U. thibetanus, protected areas where the species occurs are usually confined to high elevations with extreme conditions (e.g., higher elevations of the Tibetan Plateau; Liu et al., 2009). Human encroachment in to the edges of such areas may impact the long-term survival of the species and explain its slow rates of recovery after population declines. Very generally, populations living under ideal environmental conditions have higher reproductive rates, abundances, and genetic diversity compared to populations living under more extreme environmental conditions (Lira-Noriega and Manthey, 2014; Martínez-Meyer et al., 2012). Hence, protected areas should be designed to consider the ideal environmental conditions for the species in question (Manthey et al., 2015). Our exploration of the most climatically-suitable areas that are also the least perturbed anthropogenically may provide insight into how anthropogenic disturbance affects isolation in bears (Malcolm et al., 2014; Noyce and Garshelis, 2014; Fig. 6). Conserving areas suitable for U. thibetanus may have important additional conservation benefits for other sympatric threatened species, like the Sun Bear (Helarctos malayanus; Steinmetz et al., 2011).

4.4. Complexities of biotic interactions

Fig. 5. Ursus thibetanus distribution in relation to selected environmental variables. Suitable pixels according to the ecological niche model (black line) and reduction of areas with anthropogenic disturbance (gray shading). Elevation in meters above sea level (top), temperature in degrees Celsius (middle), and annual precipitation in millimeters (bottom).

disturbance from the niche model result left ~90% of suitable areas remaining; the areas removed are occupied by human settlements. Human settlements generally are not placed at sites with extreme environmental conditions (e.g., low or high precipitation, high elevation, extreme temperatures; Fig. 5), leaving such areas in Asia for U. thibetanus to occupy. Habitat loss owing to human encroachment was most intense in low-elevation areas (i.e., b500 m), but existed to some degree across the entire distributional potential of U. thibetanus (Figs. 4 and 6). Human perturbation was most severe in Islamabad (Pakistan). In India, we found marked habitat loss in northern Haryana, and Delhi, Lucknow, Tinsukia, and Kolkata; Bangladesh showed habitat

Although we found that nighttime lights data derived from remote sensing may prove useful in identifying viable areas for biodiversity conservation, tolerance of human presence may be irregular, speciesspecific, and even place-specific. Consequently, this threshold should be developed for each species considering that some taxa may be more or less tolerant to anthropogenic disturbance than U. thibetanus. Additionally, tolerance to human disturbance in bears may change across the year in response to the bears' natural history and reproductive cycle, and seasonal variation in vegetation, in landscapes with poor natural food production or during the hyperphagia state. Under these varied circumstances, bears shift to alternative anthropogenic food sources and forage closer to human settlements, increasing their tolerance to human interference (Baruch-Mordo et al., 2013; Malcolm et al., 2014), but also increasing the probability of negative interactions Thus, in this study, the threshold value may reflect bears' tolerance of human-modified habitat in the summer rainy season examined in our field work, and the more general extrapolation to the entire species' range year-round should be interpreted with caution. Bears, however, are affected during exploration of human modified habitats. Empirical evidence demonstrates that U. thibetanus' stress increases with low food availability, less forest cover, and human presence (Malcolm et al., 2014). Population models for Ursus americanus revealed that bears are less attracted to human settlements when high-quality natural habitat is available (Lewis et al., 2014). An important caveat, however, is that human attitudes regarding presence of bears are heterogeneous at local scales, with both positive and negative attitudes in zones surrounding the same protected areas (Kubo and Shoji, 2014). Nighttime light data from satellite imagery certainly does not capture all forms of anthropogenic disturbance associated with artificial light, including that associated with roads. For example, at fine scales, road density negatively impacts occurrence of Ursus arctos, generating changes in activity patterns (Ordiz et al., 2014). Other, more parametized, techniques to identify thresholds of nighttime light

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Fig. 6. Ursus thibetanus model of environmental suitability and anthropogenic disturbance. Map of the linear association of the suitability index and the night-light time satellite image reflectance values. Areas with high environmental suitability and low values of artificial light (red) can be considered as priority areas for conservation and potential habitat corridors for the species. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

tolerance, may provide different threshold values and, in consequence, different estimates of present-day suitable area.

to design protected areas, prioritize threatened species based on habitat loss and rates of decline, and determine areas of human–wildlife conflict.

4.5. Final remarks Based on our overall results, we consider this species as a habitat generalist, since it tolerates proximity to human settlements and a broad range of climatic and land use conditions. The status of U. thibetanus as an habitat generalist has been previously proposed, similar to that of U. americanus in North America (Lewis et al., 2014; Malcolm et al., 2014). Thus, threats to conservation of U. thibetanus are expressed at, and should be managed at, fine geographic scales (Lewis et al., 2014). Use of the word “suitable” should be carefully delimited when the goal is to model species' geographic distributions for conservation purposes. ENMs that aim to prioritize areas for biological conservation based only on climate variables should be re-evaluated critically, as such models may identify suitable areas that are unavailable or inimical to the species at local scales (e.g., Bernardo-Silva et al., 2012 and PooMuñoz et al., 2014). Efforts to conserve broad-ranging species should consider climatic suitability and reduce these models using metrics of anthropogenic disturbance. In conclusion, conservation of U. thibetanus should be simultaneously focused on areas with low human perturbation and ideal environmental conditions. Including anthropogenic disturbance as a factor in conservation analyses produces more realistic models of suitable areas for a species, while satellite imagery allows development of such models at broad scales. Nighttime light imagery offers a robust source of information on artificial light as a proxy for human occupancy to refine estimates of areas suitable for a species, which are ultimately used

Acknowledgments Special thanks to A. Townsend Peterson for providing comments. Erin Saupe and Abby Morrison improved the English of an early version. The authors would like to thank the three anonymous reviewers for their voluntary suggestions and constructive critics that improved this manuscript. LEE's research was supported by the Global Emerging Infectious Disease Surveillance and Response System (GEIS) grant P0435_14_UN to Mark E. Polhemus. HQ was supported by the National Natural Sciences Foundation of China (grant 31100390). Appendix A. Supplementary data Supplementary data associated with this article can be found in the online version, at http://dx.doi.org/10.1016/j.biocon.2015.06.040. These data include the Google maps of the most important areas described in this article. References Anderson, R., Martínez-Meyer, E., 2004. Modeling species' geographic distributions for preliminary conservation assessments: an implementation with the spiny pocket mice (Heteromys) of Ecuador. Biol. Conserv. 116, 167–179. http://dx.doi.org/10. 1016/S0006-3207(03)00187-3. Awan, M.N., 2014. Occupancy and Conflict Patterns of Asiatic Black Bear (Ursus thibetanus) in Pir-Chinasi/Pir-Hasimar Mountains, Muzaffarabad, Azad Jammu and Kashmir, Pakistan. University of Azad Jammu and Kashmir.

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Glossary ENM: Ecological Niche Modeling SDM: Species Distribution Modeling IUCN: International Union for Conservation of Nature Km: kilometers