Habitat overlap between Asiatic black bear Ursus thibetanus and red panda Ailurus fulgens in Himalaya

Climate and land use/land cover changes increasing habitat overlap among endangered crested ibis and sympatric egret/heron species

Climate and land use/land cover (LULC) changes have far-reaching effects on various biological processes in wildlife, particularly interspecific interactions. Unfortunately, interspecific interactions are often overlooked when assessing the impacts of environmental changes on endangered species. In this study, we examined niche similarities and habitat overlaps between wild Crested Ibis and sympatric Egret and Heron species (EHs) in Shaanxi, China, using Ecological niche models (ENMs). We aimed to forecast potential alterations in habitat overlaps due to climate and LULC changes. The results showed that although EHs possess a broader niche breadth compared to the Crested Ibis, they still share certain niche similarities, as indicated by Schoener's D and Hellinger's I values exceeding 0.5, respectively. Notably, despite varying degrees of habitat reduction, the shared habitat area of all six species expands with the changes in climate and LULC. We suggest that with the climate and LULC changes, the habitats of sympatric EHs are likely to suffer varying degrees of destruction, forcing them to seek refuge and migrate to the remaining wild Ibis habitat. This is primarily due to the effective conservation efforts in the Crested Ibis habitat in Yangxian County and neighboring areas. Consequently, due to the niche similarity, they will share and compete for limited habitat resources, including food and space. Therefore, we recommend that conservation efforts extend beyond protecting the Crested Ibis habitat. It is crucial to control human activities that contribute to LULC changes to safeguard the habitats of both Crested Ibis and other sympatric birds.

Landscape-level habitat connectivity of large mammals in Chitwan Annapurna Landscape, Nepal

The populations of many species of large mammals occur in small isolated and fragmented habitat patches in the human-dominated landscape. Maintenance of habitat connectivity in the fragmented landscapes is important for maintaining a healthy population of large mammal. This study evaluated the landscape patches and their linkages on two carnivores (leopard and Himalayan black bear) and seven prey species (northern red muntjac, chital, sambar, wild pig, Himalayan goral, rhesus macaque, and langur) between Chitwan National Park (CNP) and Annapurna Conservation Area (ACA) by using the least-cost path (LCP) approach and the Linkage Mapper tool in ArcGIS. A total of 15 habitat patches (average area 26.67 ± 12.70 km2) were identified that had more than 50% of the total studied mammals. A weak relation among the habitat patches was found for chital and sambar (Cost-weighted distance [CWD]: Euclidean distance EucD >100), showed poor connectivity between the habitat patches, while ratio of CWD and EucD was low (i.e., low LCP) between majority of the patches for muntjac, wild pig and leopard hence had potential functional connectivity along the landscape. Similarly, low LCP between the habitat patches located in the mid-hills was observed for Himalayan goral and Himalayan black bear. Furthermore, the multi-species connectivity analysis identified the potential structural connectivity between the isolated populations and habitat patches. Therefore, these sites need to be considered connectivity hotspots and be prioritized for the conservation of large mammals in the landscape.

Identifying risk zones and landscape features that affect common leopard depredation

Human-wildlife conflict (HWC) is a pressing issue worldwide but varies by species over time and place. One of the most prevalent forms of HWC in the mid-hills of Nepal is human-common-leopard conflict (HLC). Leopard attacks, especially in forested areas, can severely impact villagers and their livestock. Information on HLC in the Gorkha district was scarce, thus making it an ideal location to identify high-risk zones and landscape variables associated with such events. Registered cases were collected and reviewed from the Division Forest Office (DFO) during 2019-2021. Claims from DFO records were confirmed with herders and villagers via eight focus group discussions. To enhance modeling success, researchers identified a total of 163 leopard attack locations on livestock, ensuring a minimum distance of at least 100 meters between locations. Using maximum entropy (MaxEnt) and considering 13 environmental variables, we mapped common leopard attack risk zones. True Skill Statistics (TSS) and area under receiver-operator curve (AUC) were used to evaluate and validate the Output. Furthermore, 10 replications, 1,000 maximum iterations, and 1000 background points were employed during modeling. The average AUC value for the model, which was 0.726 ± 0.021, revealed good accuracy. The model performed well, as indicated by a TSS value of 0.61 ± 0.03. Of the total research area (27.92 km2), about 74% was designated as a low-risk area, 19% as a medium-risk area, and 7% as a high-risk area. Of the 13 environmental variables, distance to water (25.2%) was the most significant predictor of risk, followed by distance to road (16.2%) and elevation (10.7%). According to response curves, the risk of common leopard is highest in the areas between 1.5 to 2 km distances from the water sources, followed by the closest distance from a road and an elevation of 700 to 800 m. Results suggest that managers and local governments should employ intervention strategies immediately to safeguard rural livelihoods in high-risk areas. Improvements include better design of livestock corrals, insurance, and total compensation of livestock losses. Settlements near roads and water sources should improve the design and construction of pens and cages to prevent livestock loss. More studies on the characteristics of victims are suggested to enhance understanding of common leopard attacks, in addition to landscape variables. Such information can be helpful in formulating the best management practices.

Asiatic Black Bear-Human Conflict: A Case Study from Guthichaur Rural Municipality, Jumla, Nepal

Our study assessed patterns of Asiatic black bear (Ursus thibetanus)-human conflicts within the Guthichaur rural municipality, Jumla, Nepal. Through semi-structured interviews with villagers, focus group discussions (FGDs), and key informant interviews (KIIs), we gathered black bear-human conflict information from 2009 to 2019. We identified three primary types of black bear-human interactions: crop damage, livestock depredation, and human injuries. Of these, crop damage (77.03%) emerged as the most prevalent issue. Notably, peak occurrences were observed during autumn (September-October) typically between 9 PM and 3 AM. Livestock depredations were more frequent during nighttime in April-August, with cows/ox (70.12%) being the most depredated animal. Our data also revealed five recorded cases of black bear attacks on humans, which transpired from September to October, primarily in farmland areas in varying years. Despite a prevailing negative perception of bears, a notable level of support exists for their conservation efforts among local communities. Furthermore, these conflicts could be mitigated by reinforcing indigenous crop protection methods and implementing targeted mitigation strategies, as observed in other regions with successful black bear-human interaction management.

Habitat suitability of four threatened Himalayan species: Asiatic black bear, common leopard, musk deer, and snow leopard

Background

Biodiversity conservation is becoming challenging day by day. For this, it is essential to understand the distribution, habitat, and impact of anthropogenic activities on animals at risk. We assessed the suitable habitats and anthropogenic impacts on Asiatic black bears, common leopards, musk deer, and snow leopards in and outside the protected areas of Gandaki Province, Nepal.

Methods

We collected the presence locations of Asiatic black bears, common leopards, musk deer, and snow leopards based on scats and other signs. We employed the Maximum Entropy (MaxEnt) tool to identify suitable habitats of our studied species and their anthropogenic impacts on them.

Results

The total suitable habitat of the common leopard was found to be 6,052 km2, followed by the Asiatic black bear (5,819 km2), snow leopard (4,447 km2), and musk deer (1,690 km2) in Gandaki Province. Most of the areas of suitable habitat for common leopards and Asiatic black bears were outside the protected areas, and for musk deer and snow leopards were inside the protected areas. Elevation was the most important variable determining habitat suitability of Asiatic black bear, common leopard, and musk deer, whereas the distance to water was the most important variable determining habitat suitability of snow leopard. Asiatic black bears, common leopards, and musk deer face significant anthropogenic impacts, but snow leopards face some anthropogenic impacts.

Conclusion

Managing these animals' habitats inside and outside protected areas is essential. Hence, biodiversity conservation and livelihood opportunities should be balanced in the Himalayas on a win-win basis.

Predicting suitable habitat of swamp deer (Rucervus duvaucelii) across the Western Terai Arc Landscape of Nepal

Over the last few years, intensifying human impact and the deterioration of natural habitats have severely restricted the global distribution of large herbivores. Rucervus duvaucelii, commonly recognized as the swamp deer, is a habitat-specialist endemic large herbivore of the Indian Subcontinent. It is classified as vulnerable by the IUCN and listed in CITES Appendix I due to a steep decline in its population, which is primarily due to anthropogenic causes. In Nepal, the last remaining population of this species is confined to limited pocket areas within the western Terai Arc Landscape. We explored potential habitat for swamp deer across this landscape using species distribution modelling through the MaxEnt algorithm by using 173 field-verified presence points alongside six anthropogenic, four topographic, and four vegetation-related variables. Our study found that out of the total study area (9207 km²), only 6% (590 km²) was suitable for swamp deer. Approximately 45% of suitable habitat was incorporated within protected areas, with Shuklaphanta National Park harboring the largest habitat patch. The suitability of habitat was discovered to be positively associated with low-elevation areas, areas near water sources, and areas far from settlements, implying the need to conserve water sources and minimize the extension of anthropogenic pressure for their long-term conservation. Additionally, we suggest the implications of a swamp deer-centric conservation strategy, with an emphasis on increasing connectivity through the corridors and landscape-level population connectivity through trans-boundary conservation initiatives between Nepal and India. Moreover, considering large herbivores' high vulnerability to extinction, similar researche incorporating anthropogenic factors is of the utmost importance to produce vital information on habitat suitability for conserving other regionally and globally endemic, habitat-specialized herbivores.

Species coexistence and niche interaction between sympatric giant panda and Chinese red panda: A spatiotemporal approach

The giant panda (Ailuropoda melanoleuca) and the Chinese red panda (Ailurus styani) are distributed in the same region in the mountain forest ecosystem on the eastern edge of the Qinghai Tibet Plateau and share the same food sources. In order to understand how sympatric giant pandas and Chinese red pandas maintain interspecific relationships to achieve stable coexistence, we used species distribution models and diurnal activity rhythms to analyze the spatial and temporal niche characteristics of giant pandas and Chinese red pandas in the Daxiangling Mountain system based on 187 camera traps data. The results show that: (1) In the Daxiangling Mountains, the total area of suitable habitats for giant pandas and Chinese red pandas is 717.61 km2 and 730.00 km2, respectively, accounting for 17.78% and 18.25%, respectively, of the study area. (2) The top five environmental factors contributing to the model of giant panda and Chinese red panda are precipitation seasonality, temperature seasonality, distance to the road, and elevation and vegetation type. (3) The total overlapping area of suitable habitats for giant pandas and Chinese red pandas is 342.23 km2, of which the overlapping area of highly suitable habitats is 98.91 km2. The overlapping index of suitable habitats is 0.472, and the overlapping index of highly suitable habitats is 0.348, which indicates that the two achieve spatial niches are separated to achieve stable coexistence. (4) The overlapping index of the daily activity rhythm of giant panda and Chinese red panda is 0.87, which is significantly different (p < .05). The existence of Chinese red panda will significantly affect the daily activity rhythm of giant panda (p < .001). This research can provide scientific reference for the researches about population and habitat protection of giant pandas and Chinese red pandas, so as to understand the driving mechanism of resource allocation and population dynamics of sympatric species.

Understanding Species–Habitat Associations: A Case Study with the World’s Bears

Habitat modeling is one of the most common practices in ecology today, aimed at understanding complex associations between species and an array of environmental, bioclimatic, and anthropogenic factors. This review of studies of seven species of terrestrial bears (Ursidae) occupying four continents examines how habitat models have been employed, and the functionality of their predictions for management and conservation. Bear occurrence data have been obtained at the population level, as presence points (e.g., sign surveys or camera trapping), or as locations of individual radio-collared animals. Radio-collars provide greater insights into how bears interact with their environment and variability within populations; they are more commonly used in North America and Europe than in South America and Asia. Salient problematic issues apparent from this review included: biases in presence data; predictor variables being poor surrogates of actual behavioral drivers; predictor variables applied at a biologically inappropriate scale; and over-use of data repositories that tend to detach investigators from the species. In several cases, multiple models in the same area yielded different predictions; new presence data occurred outside the range of predicted suitable habitat; and future range projections, based on where bears presently exist, underestimated their adaptability. Findings here are likely relevant to other taxa.

Predictively modelling the distribution of the threatened brush-tailed rock-wallaby (

Abstract Context Species Distribution Models (SDM) can be used to investigate and understand relationships between species occurrence and environmental variables, so as to predict potential distribution. These predictions can facilitate conservation actions and management decisions. Oxley Wild Rivers National Park (OWRNP) is regarded as an important stronghold for the threatened brush-tailed rock-wallaby (Petrogale penicillata), on the basis of the presence of the largest known metapopulation of the species. Adequate knowledge of the species’ ecology and distribution in OWRNP is a key objective in the national recovery plan for the species occurring in the Park. Aims To model distribution using key GIS-derived environmental factors for the brush-tailed rock-wallaby in OWRNP and to ground-truth its presence through field surveys in areas of high habitat suitability. Methods We used Maxent to model the distribution of the brush-tailed rock-wallaby within OWRNP on the basis of 282 occurrence records collected from an online database, elicitation of informal records from experts, helicopter surveys and historic records. Environmental variables used in the analysis were aspect, distance to water, elevation, geology type, slope and vegetation type. Key results Vegetation type (37.9%) was the highest contributing predictor of suitable habitat, whereas aspect (4.8%) contributed the least. The model produced an area under the curve (AUC) of the receiver operating characteristic (ROC) of 0.780. The model was able to discriminate between suitable and non-suitable habitat for brush-tailed rock-wallabies. Areas identified in our model as being highly suitable yielded eight new occurrence records during subsequent ground-truthing field surveys. Conclusions Brush-tailed rock-wallaby distribution in OWRNP is primarily associated with vegetation type, followed by distance to water, elevation, geology, slope and aspect. Field surveys indicated that the model was able to identify areas of high habitat suitability. Implications This model represents the first predicted distribution of brush-tailed rock-wallaby in OWRNP. By identifying areas of high habitat suitability, it can be used to survey and monitor the species in OWRNP, and, thus, contribute to its management and conservation within the Park.

Impact of climate change on Asiatic black bear (Ursus thibetanus) and its autumn diet in the northern highlands of Pakistan

Approximately 20%-30% of plant and animal species are at risk of extinction by the end of the 21st century owing to climate change. Range shifts and range contractions in plant species will dramatically affect the distribution of animals relying on them for food and shelter. The negative impacts of climate change on forested landscapes of the northern highlands of Pakistan (NHP) could change the species composition and distribution. The Asiatic black bear (Ursus thibetanus), a forest-dwelling species, primarily depends on plants for foraging, and is assumed to be affected by climate change in NHP. Scat analyses and indigenous knowledge from Machiara National Park revealed the maximum consumption of Quercus species (natural food) and Zea mays (human grown food) by the Asiatic black bear in autumn season. We collected the occurrence data of the Asiatic black bear and its commonly used food (three Quercus spp.) in the NHP. We used the MaxEnt model to simulate current and future (in 2050 and 2070) distribution of the species under RCP4.5 (medium carbon emission scenario) and RCP8.5 (extreme carbon emission scenario). The results predict range reduction and extreme fragmentation in the habitats of all the Quercus spp. Besides, a dramatic decrease in the suitable (SH) and very highly suitable (HSH) habitats was predicted in the future. Range shift and range reduction of Quercus spp. may interrupt the denning chronology of Asiatic black bears, escalate the human-black bear conflicts and local extirpation of the species. Given the extent and magnitude of climate change, it will likely not be enough to focus solely on the conservation of the Asiatic black bear. We need more dynamic planning aiming at mitigating the effect of climate change in forested landscapes including the Quercus forests.

Mapping habitat suitability for Asiatic black bear and red panda in Makalu Barun National Park of Nepal from Maxent and GARP models

Habitat evaluation is essential for managing wildlife populations and formulating conservation policies. With the rise of innovative powerful statistical techniques in partnership with Remote Sensing, GIS and GPS techniques, spatially explicit species distribution modeling (SDM) has rapidly grown in conservation biology. These models can help us to study habitat suitability at the scale of the species range, and are particularly useful for examining the overlapping habitat between sympatric species. Species presence points collected through field GPS observations, in conjunction with 13 different topographic, vegetation related, anthropogenic, and bioclimatic variables, as well as a land cover map with seven classification categories created by support vector machine (SVM) were used to implement Maxent and GARP ecological niche models. With the resulting ecological niche models, the suitable habitat for asiatic black bear (Ursus thibetanus) and red panda (Ailurus fulgens) in Nepal Makalu Barun National Park (MBNP) was predicted. All of the predictor variables were extracted from freely available remote sensing and publicly shared government data resources. The modeled results were validated by using an independent dataset. Analysis of the regularized training gain showed that the three most important environmental variables for habitat suitability were distance to settlement, elevation, and mean annual temperature. The habitat suitability modeling accuracy, characterized by the mean area under curve, was moderate for both species when GARP was used (0.791 for black bear and 0.786 for red panda), but was moderate for black bear (0.857), and high for red panda (0.920) when Maxent was used. The suitable habitat estimated by Maxent for black bear and red panda was 716 km2 and 343 km2 respectively, while the suitable area determined by GARP was 1074 km2 and 714 km2 respectively. Maxent predicted that the overlapping area was 83% of the red panda habitat and 40% of the black bear habitat, while GARP estimated 88% of the red panda habitat and 58% of the black bear habitat overlapped. The results of land cover exhibited that barren land covered the highest percentage of area in MBNP (36.0%) followed by forest (32.6%). Of the suitable habitat, both models indicated forest as the most preferred land cover for both species (63.7% for black bear and 61.6% for red panda from Maxent; 59.9% black bear and 58.8% for red panda from GARP). Maxent outperformed GARP in terms of habitat suitability modeling. The black bear showed higher habitat selectivity than red panda. We suggest that proper management should be given to the overlapping habitats in the buffer zone. For remote and inaccessible regions, the proposed methods are promising tools for wildlife management and conservation, deserving further popularization.

Factors affecting livestock depredation by snow leopards (Panthera uncia) in the Himalayan region of Nepal

The snow leopard (Panthera uncia) found in central Asia is classified as vulnerable species by the International Union for Conservation of Nature (IUCN). Every year, large number of livestock are killed by snow leopards in Nepal, leading to economic loss to local communities and making human-snow leopard conflict a major threat to snow leopard conservation. We conducted formal and informal stakeholder's interviews to gather information related to livestock depredation with the aim to map the attack sites by the snow leopard. These sites were further validated by district forest office staffs to assess sources of bias. Attack sites older than 3 years were removed from the survey. We found 109 attack sites and visited all the sites for geo location purpose (GPS points of all unique sites were taken). We maintained at least a 100 m distance between attack locations to ensure that each attack location was unique, which resulted in 86 unique locations. A total of 235 km² was used to define livestock depredation risk zone during this study. Using Maximum Entropy (MaxEnt) modeling, we found that distance to livestock sheds, distance to paths, aspect, and distance to roads were major contributing factors to the snow leopard's attacks. We identified 13.64 km² as risk zone for livestock depredation from snow leopards in the study area. Furthermore, snow leopards preferred to attack livestock near livestock shelters, far from human paths and at moderate distance from motor roads. These identified attack zones should be managed both for snow leopard conservation and livestock protection in order to balance human livelihoods while protecting snow leopards and their habitats.

Accessing habitat suitability and connectivity for the westernmost population of Asian black bear (Ursus thibetanus gedrosianus, Blanford, 1877) based on climate changes scenarios in Iran

Climate change, as an emerging phenomenon, has led to changes in the distribution, movement, and even risk of extinction of various wildlife species and this has raised concerns among conservation biologists. Different species have two options in the face of climate change, either to adopt or follow their climatic niche to new places through the connectivity of habitats. The modeling of interpatch landscape communications can serve as an effective decision support tool for wildlife managers. This study was conducted to assess the effects of climate change on the distribution and habitat connectivity of the endangered subspecies of Asian black bear (Ursus thibetanus gedrosianus) in the southern and southeastern Iran. The presence points of the species were collected in Provinces of Kerman, Hormozgan, and Sistan-Baluchestan. Habitat modeling was done by the Generalized Linear Model, and 3 machine learning models including Maximum Entropy, Back Propagation based artificial Neural Network, and Support Vector Machine. In order to achieve the ensemble model, the results of the mentioned models were merged based on the method of "accuracy rate as weight" derived from their validation. To construct pseudo-absence points for the use in the mentioned models, the Ensemble model of presence-only models was used. The modeling was performed using 15 habitat variables related to climatic, vegetation, topographic, and anthropogenic parameters. The three general circulation models of BCC-CSM1, CCSM4, and MRI-CGCM3 were selected under the two scenarios of RCP2.6 and RCP8.5 by 2070. To investigate the effect of climate change on the habitat connections, the protected areas of 3 provinces were considered as focal nodes and the connections between them were established based on electrical circuit theory and Pairwise method. The true skill statistic was employed to convert the continuous suitability layers to binary suitable/unsuitable range maps to assess the effectiveness of the protected areas in the coverage of suitable habitats for the species. Due to the high power of the stochastic forest model in determining the importance of variables, this method was used. The results showed that presence/absence models were successful in the implementation and well distinguished the points of presence and pseudo-absence from each other. Based on the random forests model, the variables of Precipitation of Driest Quarter, Precipitation of Coldest Quarter, and Temperature Annual Range have the greatest impact on the habitat suitability. Comparing the modeling findings to the realities of the species distribution range indicated that the suitable habitats are located in areas with high humidity and rainfall, which are mostly in the northern areas of Bandar Abbas, south of Kerman, and west and south of Sistan-Baluchestan. The area of suitable habitats, in the MRI-CGCM3 (189731 Km2) and CCSM4 (179007 Km2) models under the RCP2.6 scenario, is larger than the current distribution (174001 Km2). However, in terms of the performance of protected areas, the optimal coverage of the species by the boundary of the protected areas, under each of the RCP2.6 and RCP8.5 scenarios, is less than the present time. According to the electric circuit theory, connecting the populations in the protected areas of Sistan-Baluchestan province to those in the northern Hormozgan and the southern Kerman would be based on the crossing through the heights of Sistan-Baluchestan and Hormozgan provinces and the plains between these heights would be the movement pinch points under the current and future scenarios. Populations in the protected areas of Kerman have higher quality patch connections than that of the other two provinces. The areas such as Sang-e_Mes, Kouh_Shir, Zaryab, and Bahr_Aseman in Kerman Province and Kouhbaz and Geno in Hormozgan Province can provide suitable habitats for the species in the distribution models. The findings revealed that the conservation of the heights along with the caves inside them could be a protective priority to counteract the effects of climate change on the species.

Suitable habitat of wild Asian elephant in Western Terai of Nepal

BACKGROUND

There is currently very little available research on the habitat suitability, the influence of infrastructure on distribution, and the extent and connectivity of habitat available to the wild Asian elephant (Elephas maximus). Information related to the habitat is crucial for conservation of this species.

METHODS

In this study, we identified suitable habitat for wild Asian elephants in the Western Terai region of Nepal using Maximum Entropy (MaxEnt) software.

RESULTS

Of 9,207 km2, we identified 3194.82 km2 as suitable habitat for wild Asian elephants in the study area. Approximately 40% of identified habitat occurs in existing protected areas. Most of these habitat patches are smaller than previous estimations of the species home range, and this may reduce the probability of the species continued survival in the study area. Proximity to roads was identified as the most important factor defining habitat suitability, with elephants preferring habitats far from roads.

CONCLUSIONS

We conclude that further habitat fragmentation in the study area can be reduced by avoiding the construction of new roads and connectivity between areas of existing suitable habitat can be increased through the identification and management of wildlife corridors between habitat patches.

An assessment of human impacts on endangered red pandas (Ailurus fulgens) living in the Himalaya

Anthropogenic factors play an important role in shaping the distribution of wildlife species and their habitats, and understanding the influence of human activities on endangered species can be key to improving conservation efforts as well as the implementation of national strategies for sustainable development. Here, we used species distribution modeling to assess human impacts on the endangered red panda (Ailurus fulgens) in high-altitude regions of Nepal. We found that the distance to paths (tracks used by people and animals), livestock density, human population density, and annual mean temperature were the most important factors determining the habitat suitability for red pandas in Nepal. This is the first study that attempts to use comprehensive environmental and anthropogenic variables to predict habitat suitability for the red pandas at a national level. The suitable habitat identified by this study is important and could serve as a baseline for the development of conservation strategies for the red panda in Nepal.

Suitable habitat prediction of Sichuan snub-nosed monkeys (Rhinopithecus roxellana) and its implications for conservation in Baihe Nature Reserve, Sichuan, China

As an endemic primate species with one of the highest priorities in wildlife conservation in China, Sichuan snub-nosed monkeys (Rhinopithecus roxellana) have undergone a sharp decline and range reduction in recent centuries. Here, we used maximum entropy modelling (MaxEnt) integrated with four types of environmental variables, including three biological climate variables (Bio17, precipitation of the driest quarter; Bio6, min. temperature of the coldest month; and Bio2, mean diurnal range), three topographic variables (altitude, slope, and aspect), two anthropogenic variables (Human Footprint Index and human disturbance), and three vegetation-related variables (enhanced vegetation index, normalized difference vegetation index, and Wet Index) to identify the spatial distribution of suitable habitats for Sichuan snub-nosed monkeys in Baihe Nature Reserve (BNR), which is located in the Minshan Mountains. The average training AUC of our model performance is 0.929 ± 0.003. The model predicted 9.6 km² of high suitability habitats and 14.1 km² of moderate suitability habitats for Sichuan snub-nosed monkeys, adding up to only 11.7% of the total area of concern for the study in the BNR. The top four variables ranked in the model (altitude, Human Footprint Index, human disturbance, and Bio17) accounted for relative gain contributions of 23.3%, 19.3%, 14.2%, and 13.4%, respectively. The predicted suitable habitats were confined to an altitude range of 1971-3198 m, Human Footprint Index of mainly 3-5 values, low human disturbance (mainly livestock), and precipitation of the driest (or coldest) quarter of 9-22 mm. Additionally, the suitable habitats were mainly distributed in the core zone (36.1%), buffer zone (26.8%), and experimental zone (29.5%). The remaining habitats (7.6%) were distributed in the 0.5-km buffer zone of the reserve border. The predicted suitable habitats indicated limited suitable habitat space for the Sichuan snub-nosed monkeys, with most of the suitable habitat distributed outside the core zone in the BNR. Our findings highlighted that human activities in all three functional zones could be the most negative factor on suitable habitat distribution of Sichuan snub-nosed monkeys in the BNR.