Conflicts between wildlife and humans, particularly among residents living within and adjacent protected areas, represent a pervasive global conservation challenge. Effectively addressing these conflicts has become a critical issue for both biodiversity conservation and regional sustainable development. The establishment of Northeast Tiger and Leopard National Park has significantly promoted the population recovery of Amur tigers (Panthera tigris altaica), Amur leopards (Panthera pardus orientalis), and other sympatric species. However, wildlife population growth has been accompanied by a significant increase in crop-raiding incidents by ungulates, posing a dual challenge to local livelihoods and conservation management. To quantify these risks and identify their drivers, our study focuses on the Hunchun River Basin within Northeast Tiger and Leopard National Park, which includes 25 administrative villages across three town. By integrating UAV remote sensing and camera trap monitoring, with generalized linear models (GLMs) and maximum entropy modelling (MaxEnt), to systematically quantify economic losses caused by wildlife-related incidents, we also analyzed spatio-temporal patterns of human-wildlife conflict; revealed the driving factors of crop damage extent; and mapped high- and low-risk regions for human-wildlife conflict across the study area. The results showed that: (1) In 2024, the areas of soybean and maize damaged by wildlife in the Hunchun River Basin reached 38.08 ha and 43.58 ha, respectively, with direct economic losses estimated between 801,500 and 1,217,600 CNY; human-wildlife conflict exhibited distinct seasonal patterns and spatial heterogeneity. (2) Conflict species show a typical nocturnal pattern, avoiding peak daytime human activity and entering farmland to forage during the late-night hours. (3) Fencing, distance from forest edges, and forest Aspect were key factors influencing the extent of crop damage. The northeastern part of the study area was high-risk area for human-wildlife conflict, requiring priority management and control. Our study innovatively proposes a high-precision, scalable approach for quantifying human-wildlife conflict, effectively addressing the inherent subjectivity limitations of traditional questionnaire surveys. It provides a scientific basis for predicting and precisely mitigating human-wildlife conflict risks in the study area. At the same time, our study contributes to addressing the core issue of ‘human-wildlife coexistence’ in Northeast Tiger and Leopard National Park and offers both theoretical and practical support for the long-term stability of the social–nature system in protected areas.

Reliable and accurate individual data is crucial for the conservation and recovery of endangered Amur tigers. With the growing volume of data accumulated from camera traps in recent years, deep learning has emerged as an effective tool for wildlife detection and identification. While several studies have focused on Amur tiger reidentification, most rely on relatively ideal datasets and may not be suitable for practical monitoring. Less work has been done in the open-world scenario. To fill this gap, we focused on 16 wild Amur tigers in the Northeast Tiger and Leopard National Park, and (1) constructed two datasets more aligned with the wild environment, containing 1,121 and 34,691 images respectively; (2) designed a two-stage re-identification pipeline that includes the segmentation and classification steps; (3) proposed a fusion module based on representation and metric learning to improve performance. After comparing various deep learning backbones, we chose DDRNet-39 and ConvNeXt-small to test this pipeline, which yielded an accuracy of 95.49% on the test set. Using a case study on home range and dispersal behavior, we illustrated how our approach could assist in population monitoring and spatio-temporal analyses of Amur tigers, as well as other species with distinctive coat patterns. Future researches can proceed to enhance this approach by expanding datasets or integrating multimodal data, further promoting its applications in the real world.

The aim of this study is to enhance the classification accuracy of mammalian hair scale images using deep learning techniques, particularly SimCLR (Simple Framework for Contrastive Learning of Visual Representations) pretraining with unlabeled data, providing reliable technical support for species identification. We created a mammalian scanning electron microscope image dataset of 9,953 valid images of 33 mammal species. Four segmentation models-U-Net, SegNet, DeepLabV3+, and Segment Anything Model (SAM)-were evaluated for performance. SAM achieved the highest segmentation accuracy overall, although minor errors were still observed in the delineation of scales with clearly defined edges. SimCLR was pretrained on 2 datasets: one containing all 33 species, and a subset of 25 species with over 200 images per species. These models achieved Top-1 accuracies of 94.64% and 94.40%, exceeding ResNet-50, EfficientNet_b0, and ViT-B/16 trained from scratch, comparable to transfer learning (pretrained on ImageNet) results of ResNet-50 and EfficientNet_b0, and superior to that of ViT-B/16. Score-CAM visualizations revealed that the network's attention was focused on image regions that correspond to the morphological features traditionally used for species identification, demonstrating strong biological interpretability. Additionally, t-SNE visualizations confirmed the model's ability to effectively distinguish between different species. Cosine distance-based clustering of species-specific scale features further highlighted interspecies similarity patterns and commonly misclassified species pairs. The results demonstrate that deep learning models, particularly with the integration of SimCLR pretraining, are highly effective in classifying mammalian hair scales, providing a reliable method for species identification.

The plastisphere, as a microbial niche on plastics, exacerbates ecological risks to biodiversity in critical habitats like the Northeast Tiger and Leopard National Park, a sanctuary for endangered Amur tigers (Panthera tigris altaica) and leopards (Panthera pardus orientalis). However, existing research has paid limited attention to the characteristics of the plastisphere within protected areas and its potential threats. Focusing on water sources frequently utilized by sika deer (Cervus nippon), a keystone prey species, this study characterizes plastisphere bacterial across plastic types (PET, PP, PE) and uses (pesticide bags, plastic bags, fishing nets) via 16S rRNA sequencing. Results revealed: (1) Plastisphere bacterial diversity significantly exceeds surrounding water, driven by stochastic assembly; (2) Functional taxa mediating carbon/nitrogen cycling (e.g. Leptolyngbya, Novosphingobium, Methylobacterium) are enriched on plastics, surpassing water/soil abundances; (3) The bacterial communities on PET and pesticide bags exhibited significantly greater enrichment in functional pathways associated with pathogens and antibiotic resistance genes (ARGs), indicating a higher ecological risk; (4) Source tracking identifies plastisphere and soil as the dominant contributors to sika deer gut microbiota, indicating direct microbial exchange. These interactions elevate infection risks for sika deer and apex predators, threatening food chain integrity. Our findings highlight the urgent need to incorporate plastic pollution control into conservation strategies for endangered species, particularly in ecologically sensitive regions, which has significant implications for the future development and management of national park systems. This study provides novel scientific insights into plastisphere-driven ecological threats and advocates for sustainable habitat management to mitigate cascading impacts on biodiversity.

Leopards Panthera pardus are top predators that play a crucial role in maintaining ecosystem balance and stability by exerting top-down control on prey species populations through direct predation. Despite their wide distribution, in recent years leopard populations have become endangered in many regions due to increasing anthropogenic activity. Studying the feeding habits of endangered species provides insight into their survival from the perspective of their trophic niche and can help identify factors contributing to their decline, aiding in the development of targeted conservation strategies. In this study, the North China leopard (P. p. japonensis) and Amur leopard (P. p. orientalis) were selected as the study objects. A total of 97 fecal samples were collected throughout their typical habitats, 83 of which were confirmed as originating from leopards using molecular identification. DNA metabarcoding identified 13 prey species for the North China leopard and 15 for the Amur leopard, with small- and medium-sized prey (< 37 kg) comprising over 75% of biomass intake. Among all the prey species, roe deer (Capreolus pygargus) provided the highest biomass contribution—41.69% for the North China leopard and 29.2% for the Amur leopard. In addition, the frequent occurrence of domestic dogs (Canis familiaris) in their diet (>5.8%) highlights the impact of anthropogenic activities on leopard feeding habits. To support leopard conservation, it is recommended to protect all prey species within reserves and reduce anthropogenic interference in these habitats.

“Effectively conserved and managed” is an important component of the Kunming-Montreal Global Biodiversity Framework. Human activities continue to affect protected areas (PAs) worldwide, and reconciling biodiversity conservation with resource utilization represents a significant challenge for PA research. The Northeast China Tiger and Leopard National Park (TLNP) is a typical region of conflict between conservation restrictions and local livelihood. We employed Korean pine (Pinus koraiensis) seed collection activity in the TLNP as an illustrative example, utilizing maximum entropy model and spatial analysis to simulate suitable amur tiger (Panthera tigris altaica) habitat and human-tiger conflict risk areas during seed collection, to investigate approaches for enhancing the construction effects of PAs through delineating function zones. Results indicated that Korean pine contracting was ongoing in approximately one-third of core protected zones, reflecting high-intensity forest resource utilization. Suitable habitat for amur tiger covered 57.9 % of the park’s total area, and 23.7 % was affected by seed collection areas, which implied seed collection may alter tiger habitat use and exacerbate regional human-tiger conflict risks. Furthermore, we divided the Korean pine resource management function zones into four subzones, with differentiated management measures implemented. In addition, we proposed strategies for balancing conservation and development, including constructing collaborative governance systems, exploring pathways for ecological value transformation, and reinforcing the construction of early warning and monitoring systems. This study aims to provide a scientific foundation for underforest resource management in the TLNP and to serve as a reference for zoning planning of PAs in other regions.

The sett is a crucial resource for badgers, serving various functions and significantly influencing their spatial ecology. The selection of sett sites is also a complex behavior. While there have been extensive ecological studies on the European badger (Meles meles), little is known about the Asian badger (Meles leucurus), particularly in China, making it difficult to evaluate their current survival status and establish conservation strategies. Therefore, we conducted a pioneering ecological study on the Asian badger, focusing on local population density and habitat selection within the Northeast Tiger and Leopard National Park, NE China. First, we surveyed badger setts in the study area and set camera traps to capture videos of badgers and estimate the number of individuals. The estimated badger density based on the main sett distribution (1.40 sett /km2) and group size (average of 3.01 ± 1.82 individuals per sett) was 4.21 ± 2.55 badgers /km2. Second, we set up random points in the study area and measured 12 habitat factors of 67 random point quadrats and 67 badger sett quadrats to establish which factors affect the habitat selection of badgers. Statistical tests, random forest algorithm, and generalized linear model were used to explain the sett selection criteria of Asian badgers. Statistical tests indicated a highly significant difference in slope (p < 0.01) and a significant difference in tree distance and aspect (p < 0.05) between sett quadrats and random point quadrats. After correction for multiple testing according to Holm, we found that differences in tree distance and aspect lost their statistical significance. However, the random forest algorithm and generalized linear model showed that the selection of sett location was influenced by tree distance, slope, and aspect. We conclude that badgers exhibit a preference for setts located near trees, steep slopes, and orientations facing north and northwest (316–45°). This is the first assessment of the abundance and sett selection of the Asian badger at the local population scale from Chinese nature reserves, providing new insights into the population ecology and habitat selection of the Asian badger in China, and assisting in the development of relevant conservation strategies and management.

The gut microbiota plays an important role in the immunology, physiology and growth and development of animals. However, currently, there is a lack of available sequencing data on the gut microbiota of Asian badgers. Studying the gut microbiota of Asian badgers could provide fundamental data for enhancing productivity and immunity of badgers’ breeding, as well as for the protection of wild animals. In this study, we first characterized the composition and structure of the gut microbiota in the large intestines of wild and captive Asian badgers during summer and winter by sequencing the V3-V4 region of the 16S ribosomal RNA gene. A total of 9 dominant phyla and 12 genera among the bacterial communities of the large intestines exhibited significant differences. Our results showed that Firmicutes and Proteobacteria were the most predominant in both wild and captive badgers, regardless of the season. Romboutsia, Streptococcus and Enterococcus may represent potential sources of zoonoses, warranting further attention and study. Our findings indicated that the diversity and availability of food resources were the most important influencing factors on the gut microbiota of Asian badgers, providing fundamental data for the protection and conservation of wild animals. Variation in the gut microbiota due to season, age and sex in both wild and captive Asian badgers should be considered in future research directions. Furthermore, combined multi-omics studies could provide more information for wild animal conservation, and enhancing our understanding of the molecular mechanism between the microbiota and host.

1. Accurate estimates of wildlife distributions and population persistence are essential for conservation programs. Occupancy models that account for detection probability have been used to characterize the occupancy and habitat selection of imperilled species. However, failure to distinguish between true-presence and pseudo-presence associated with territorial behaviour can result in the overestimation of the occupancy probability of target species in unsuitable habitats, and this can have major implications for the development of conservation strategies. 2. For highly territorial wildlife species requiring high-quality habitat for survival, occasional ‘Presence’ in unsuitable areas might be related to dispersal or migration, but this does not reflect actual occupancy and habitat use. ‘True-Presence’ and ‘Pseudo-Presence’ should be distinguished for target species to better reflect their actual occupancy and habitat use. 3. To investigate the effect of ‘True-Presence’ and ‘Pseudo-Presence’ on wildlife occupancy estimation, we developed a modified model (M m ) that considers the territorial behaviour of the Amur tiger in northeast China, which distinguished between ‘True-Presence’ and ‘Pseudo-Presence’. We compared two models, M m and M 0 (conventional occupancy model), and assessed model performance using goodness-of-fit evaluation, detection and occupancy probability, and favourable variable selection. 4. We found that M m , which has fewer favourable variables, is more powerful than M 0 for estimating detection and occupancy probability, as well as characterizing the effect of various factors on the habitat use of Amur tigers. Furthermore, M m significantly reduced the overestimation of occupancy probability outside the home range compared with M 0 , and detection probability estimates did not significantly differ between M 0 and M m . Finally, M m provided more empirical habitat selection variables for the Amur tiger. 5. Our results revealed how ‘True-Presence’ and ‘Pseudo-Presence’ affect the occupancy probability and habitat selection of Amur tigers. Our method improves the accuracy of occupancy models; it can also be used to characterize the habitat selection and distribution of wildlife species and be applied to other territorial species.

东北豹,拉丁学名Panthera pardus orientalis,中文名东北豹、远东豹,英文名Amur leopard、Far eastern leopard.隶属于脊椎动物门、哺乳纲、食肉目、猫科、豹属.东北豹的主要栖息地为温带针阔混交林.东北豹是典型的领地型动物,1只雄豹的领地通常与数只雌豹的领地重叠.

The Chinese Loess Plateau has been the cradle of Chinese civilization and the main human settlement in China for thousands of years, where anthropogenic activities are believed to have deeply eroded natural landscapes. After decades of minimal leopard sighting in forests of northern China, due to serious human interference, we recently discovered that the leopard population is recovering. This finding provides hope for successful biodiversity conservation in human-dominated ecosystems. To understand the mechanism of leopard return into such a highly fragmented landscape, we applied the concept of ecological networks (ENs) to identify key factors promoting leopard restoration and quantify the ecological links among habitats. We first determined the existence of a healthy leopard population in the study area based on the size of its home range and presence of breeding individuals. We then innovatively used the relationship between species richness and top predators to generate ENs, and found that the connectivity of ENs had a significant positive interaction with leopard survival. Our study validates the effectiveness of establishing ecologically connected habitats for leopard protection, and highlights the importance of applying ENs for conservation planning in highly fragmented ecosystems. This study provides a successful case for the protection of top predators in human-dominated landscapes.

The Eurasian otter Lutra lutra is a generalist carnivore that is widely distributed in many aquatic ecosystems. Based on its inherent attributes of opportunistic foraging behaviour and broad dietary range, it is naturally considered a potential sampler of the diversity of aquatic vertebrates. To test the ability and efficiency of otters as a diversity sampler, we used DNA metabarcoding to investigate the composition in vertebrates of the diet of otters that inhabit a forest stream area in northeast China. Twenty vertebrate prey taxa were detected in 98 otter spraints. Otter diet mainly comprised aquatic fishes (59.4%) and amphibians (39.0%). We also used traditional approaches to investigate fish communities at 60 sampling sites in the same area to determine the relationship between fish population composition in the environment and otter diet. The comparison revealed that 28 species of fish were distributed in this area, of which five are simultaneously detected in otter spraints. This indicates that molecular analysis of the diet of otters is not an ideal approach for investigating fish diversity, at least when using the 12SV5 primer pair. Based on a review of the available molecular research on otter diet, we conclude that the low species resolution may be due to the presence of many closely-related prey species in native habitats and lack of suitable barcodes. Considering the remarkable power of diet metabarcoding analysis in capturing elusive and rare species, it represents an approach that can compensate for the defects associated with fishing methods and we suggest that it can be used as an auxiliary means of measuring traditional fish diversity.

The Asian golden cat (Catopuma temminckii) is the most varied wild cat species in terms of coat color. Understanding coat pattern variation will help to elucidate the mechanisms behind it as well as its relationship with the environment. We conducted long-term (2013–2021) monitoring of Asian golden cats in the Yarlung Zangbo Grand Canyon National Nature Reserve, Tibet, using camera traps at 283 points over 89,991 camera days. A total of 620 cat photos were recorded, including 344 (55.48%) with recognizable color patterns. Vector graphics of the coat patterns were extracted from the field image data, which revealed 10 color types in the ratio common: cinnamon: reddish-brown long hair: ocelot: blackening: melanistic: gray: brown: brown short hair: pure black = 123:76:57:35:22:8:7:7:5:4. The genes for coat pattern variation are widespread in the Asian golden cat population and are relatively stable. The increase in population size intraspecific competition has led to the tail break phenotype in individual cats. The gene encoding for tail breakage in Asian golden cats remains unknown. This study provides basic information for understanding faunal diversity in the Eastern Himalayan biodiversity hotspot and serves as a reference for studies on the formation mechanisms for feline color pattern diversity.

Microplastic pollution has emerged as a significant global environmental issue, raising considerable concern. To assess the biological impacts of microplastics, precise quantification within organisms is essential. Fluorescence intensity is a common method for measuring microplastics, but biological sample digestion—a crucial pre-treatment step—can potentially degrade the microplastics, affecting fluorescence readings and causing discrepancies between measured and actual values. This study investigates six widely used digestive agents: KOH, naoh, H2O2, HNO3, HNO3: hcl, and HNO3: HClO4. The effects of these digestion methods on microplastic fluorescence intensity and surface morphology were evaluated to determine the most effective protocol. The results indicate that KOH digestion (100 g·L-1, 60℃) has the least impact on fluorescence intensity and preserves the microplastics' surface morphology, whereas the other five methods caused varying degrees of fluorescence reduction and surface damage (such as aggregation, bubbles, scratches, and depressions). Furthermore, the KOH digestion method achieved a recovery rate of ≥96.3%±0.5% when used to extract microplastics from biological samples, demonstrating its suitability for analyzing fluorescent microplastics in such samples.

Forest-related measurements have become widely used in conservation. Established indicators typically measure the extent of forested areas; however, the complex challenges facing wildlife conservation, while further examination of the forest condition itself is much needed to tackle complex problems by applying accumulated knowledge from forest ecology to the practice of wildlife conservation. This study describes an attempt to link forest stand dynamics and wildlife conservation by considering the value of different forest structures in maintaining plant and animal populations and in particular the Amur tiger. We discuss which forest stand structures are associated with Amur tigers and then illustrate a forest management plan focused on promoting habitat for Amur tiger (Panthera tigris altaica) in areas with human settlements. Our study demonstrates the feasibility of managing forest stand structures for Amur tiger conservation outcomes using forest management decision-support tools.

Exploring the processes of interspecific relationships is crucial to understanding the mechanisms of biodiversity maintenance. Visually detecting interspecies relationships of large mammals is limited by the reconstruction accuracy of the environmental structure and the timely detection of animal behavior. Hence, we used backpack laser scanning (BLS) to reconstruct the high-resolution three-dimensional environmental structure to simulate the process of a predator approaching its prey, indicating that predator tigers would reduce their visibility by changing their behavior. Wild boars will nibble off about 5m of branches around the nest in order to create better visibility around the nest, adopting an anti-predation strategy to detect possible predators in advance. Our study not only points out how predator–prey relationships are affected by visibility as the environment mediates it, but also provides an operable framework for exploring interspecific relationships from a more complex dimension. Finally, this study provides a new perspective for exploring the mechanisms of biodiversity maintenance.

Diet analysis is essential to fully understand the biology of a species and its function within the ecosystem, as well as being key in identifying food web interactions and the population dynamics of predators and prey. The understanding of the diet of small to mid-sized carnivores remains generally lacking or uninformative due to the inability for taxonomic resolution based on morphology. The yellow-throated marten (Martes flavigula), Eurasian river otter (Lutra lutra), and Siberian weasel (Mustela sibirica) are three important Mustelidae species in ecosystems of northeast China. Based on fecal DNA and a next-generation sequencing (NGS) approach, we analyzed the vertebrate prey of these three sympatric Mustelidae. Prey included 7 mammalian taxa, 10 fishes, 2 birds, and 2 amphibians, with 85% of the taxa assigned to the species level. In total, twenty-one vertebrate prey taxa were identified from seven yellow-throated martens, eight Eurasian river otters, and two Siberian weasels. Concerning identified dietary species, 10 taxa were consumed by yellow-throated martens, 14 by Eurasian river otters, and 4 by Siberian weasels. Some prey species were identified in more than one species. Amphibians and fishes were the most dominant Eurasian river otter prey categories, whereas Eurasian badger (Meles leucurus), birds, and rodents were the main yellow-throated marten prey; amphibians and rodents were largely contained in Siberian weasel prey. Among prey items, Dybowski’s frog (Rana dybowskii) and Korean field mouse (Apodemus peninsulae) were identified in all three Mustelidae species but our analyses suggest potential diet preferences among Mustelidae species. Future studies should focus on understanding the trophic relationships of these three Mustelidae species, providing valuable information for their conservation planning.

Geopolitical borderlands are politically sensitive areas and biodiversity hotspots, strictly controlled by the government and military. How to ensure political security, while protecting the biodiversity in borderlands is a problem for ecologists and governments. In this study, the nest site selection of the wild boar Sus scrofa was a case study in the Sino-Russia borderland to understand the survival strategy of wild life under anthropogenic pressure. We investigated (a) how the spatial distribution of anthropogenic pressure and wild boar nests in the borderland and (b) how anthropogenic pressure and the border influence on the wild boars’ nest site selection. The Getis-Ord Gi* analysis was used to analyze the distribution patterns of wild boar nest sites and anthropogenic pressures in the borderland, the Structural Equation Models was used to explore the influence of border, roads, settlements, agricultural land, grassland and anthropogenic pressure on wild boars’ nest site selection. The results indicated that wild boar nest sites are close to the border, roads and agricultural land and away from settlements and grassland. Regardless of the combination of anthropogenic pressure, wild boars make the most advantageous choice and prefer to be closer to the borderland. We speculated that military control played a vital role in borderlands for animal protection under anthropogenic pressure. Wild boars benefit from the prohibition of anthropogenic persecution due to military control. Compared with existing measures, we suggest a different protection/wildlife management strategy, what we need to do may be to prohibit anthropogenic persecution rather than perform other human interventions to protect animals. However, for a species with trouble potential, we need to base our conservation strategies on the recovery of top predators, and play the community control role of top predators to avoid the occurrence of trouble.