On the impact of earthquake-induced landslides on Red Panda Ailurus fulgens (Mammalia: Carnivora: Ailuridae) habitat in Langtang National Park, Nepal

In addition to the threats of human encroachment, infrastructure development, tourism activities, habitat fragmentation, and human-wildlife interactions, natural disasters also pose a threat to the habitat of endangered species such as the Red Panda. This study aims to assess the impact of the 2015 Gorkha earthquake-induced landslides on the Red Panda’s habitat in Langtang National Park (LNP), central Nepal Himalaya. Remote sensing and geographical information system were applied to estimate the potential and core habitats of the Red Panda, and collect information on earthquake-induced landslides. Field sampling and verification of remotely collected data were done within a year of the earthquake. Considering preferred vegetation types, elevation range, aspects, distance from water sources, and Red Panda presence points, an area of 214.34 km2 was estimated as the potential habitat of Red Panda in the Park. Thirty-nine landslides were identified in LNP triggered by the Gorkha earthquake, 14 of which occurred in the core Red Panda habitat. As a result of the earthquake-induced landslides, a significant decrease in tree density was observed in the areas affected by the landslides. Similarly, the bamboo cover was observed to be significantly lower in the areas affected by landslides compared to the unaffected adjacent areas. The average size of the landslide, causing damage to the Red Panda habitat was 0.8 ha. The potential habitat damaged by the earthquake-induced landslide was estimated to be 11.20 ha which is equivalent to the habitat required by one Red Panda. The findings could be useful in initiating restoration of the damaged Red Panda habitat in LNP.

Integrating Livestock Grazing and Sympatric Takin to Evaluate the Habitat Suitability of Giant Panda in the Wanglang Nature Reserve

Habitat suitability provides essential information for the management of protected species. However, studies that jointly consider the impacts of human disturbance and sympatric animals in habitat suitability assessments of giant panda are limited, which may overestimate the habitat status. To address this issue, we evaluated the habitat suitability of giant panda in Wanglang Nature Reserve by simultaneously investigating livestock grazing and sympatric takin via MAXENT, a new attempt at the assessment of the habitat suitability of giant panda. We focused on describing the habitat suitability of giant panda and determining the habitat overlap between livestock, takin, and panda to evaluate the impacts of livestock grazing and sympatric takin on the suitable giant panda habitat. Results revealed that only 16.33% of the area in Wanglang was suitable giant panda habitat, of which 67.66% was shared by livestock, and 97.99% of the remaining suitable panda habitat not shared by livestock was revealed to be shared by takin. The results indicate an unfavorable habitat status of giant panda in Wanglang, with the potential extensive habitat overlap between livestock, takin and panda exerting further pressure. Thus, to effectively protect giant pandas and their habitats, grazing activity should be controlled. Furthermore, to accurately protect sympatric animals, the monitoring of panda and takin activities in the overlapping areas must be maintained.

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.

Spatiotemporal Heterogeneity of Ecological Policy Compromises Human Well-Being and Giant Panda Habitat Conservation in Giant Panda National Park

Identifying how policy, socioeconomic factors, and environmental factors influence changes in human well-being (HWB) and conservation efficiency is important for ecological management and sustainable development, especially in the Giant Panda National Park (GPNP). In this study, we systematically analyzed the differences in the conservation status of the giant panda habitat and changes in HWB over 15 years in the GPNP, which includes six mountain sites, Minshan (MS), Qionglai (QLS), Xiaoxiangling (XXL), Liangshan (LS), Qinling (QL), and Daxiangling (DXL). Redundancy analyses were used to determine the factors contributing (policy, socioeconomic factors, and environmental factors) to HWB and giant panda habitat conservation (HC). In addition, using a structural equation model (SEM), we investigated the relationship between the aforementioned three factors and their direct and indirect effects on HWB and HC. The results indicated that there was spatiotemporal heterogeneity of HWB and HC in our study area. There was an increasing number of plant species as well as an increased number of giant panda in GPNP. Generally, HWB in 2015 showed an increasing trend compared with that in 2000. Socioeconomic factors (23.6%) have the biggest influence on HWB and HC, followed by policy (23.2%) and environmental factors (19.4%). Conservation policy had a significantly positive influence on HWB (0.52), while it negatively influenced HC (−0.15). Socioeconomic factors significantly negatively influenced HWB (−0.38). The formulation and implementation of policies to promote economic development will contribute to the protection of giant pandas and their habitat. Our results provide insight on the conservation status of the giant panda habitat, HWB, and factors influencing them in different mountain sites in the GPNP, as well as having implications for the future management of the GPNP.