Search Results (8)

The Northeast China Tiger and Leopard National Park (NCTLNP) is a critical habitat for the endangered Amur tiger and Amur leopard, making it a global biodiversity hotspot. This study explores how changes in landscape patterns have influenced habitat quality in the park, aiming to develop strategies for enhancing biodiversity conservation and ensuring the park’s long-term sustainability. From 2012 to 2017, habitat quality in the NCTLNP experienced a significant decline; however, the launch of the national park pilot program in 2017 resulted in improvements, particularly in core protected areas, where habitat quality increased and landscape fragmentation decreased. These findings indicate that the national park initiative reduced the degradation of habitat quality. Key landscape metrics, especially the Shannon Diversity Index (SHDI), were found to significantly affect habitat quality. Additionally, the interaction between SHDI and landscape contagion (CONTAG) played a pivotal role in shaping habitat quality over time. Areas with high SHDI and low CONTAG showed declines in habitat quality, pointing to the need for focused conservation efforts. This study offers valuable insights for policymakers seeking to improve habitat quality through targeted landscape management practices. Full article

The development of ecotourism in protected areas faces the challenge of balancing conservation and ecotourism. Ecotourism suitability assessments are essential tools for managing tourism in these areas. However, current assessments often overlook biological factors, leading to adverse effects on wildlife. This study uses the Northeast China Tiger and Leopard National Park as a case study to establish a comprehensive assessment system that integrates ecotourism suitability with tiger and leopard habitat suitability, thereby linking ecotourism with wildlife conservation. The primary research methods include ecotourism suitability analysis based on the entropy weight method and habitat suitability analysis using the MaxEnt model. Based on the zoning results of ecotourism and habitat suitability, a comprehensive ecotourism suitability zoning map was produced. This map indicates that areas of very high suitability account for 45.62% of the total area, covering approximately 6152.563 km², and are primarily located on the edges of village clusters. These areas can be prioritized for developing tourism infrastructure. The comprehensive ecotourism assessment system can balance the development of ecotourism with wildlife conservation, contributing significantly to the coordinated development of economic, social, and environmental objectives. Full article

The interconnected forest regions along the lower Tumen River, at the Sino-North Korean border, provide critical habitats and corridors for the critically endangered Amur Leopard (Panthera pardus orientalis). In this region, there are two promising corridors for leopard movement between China and North Korea: the Jingxin–Dapanling (JD) and Mijiang (MJ) corridors. Past studies have confirmed the functionality of the JD corridor, but leopards’ utilization of the MJ corridor has not yet been established or confirmed. In this study, we assessed the functionality of the MJ corridor. The study area was monitored using camera traps between May 2019 and July 2021. We also analyzed 33 environmental and vegetation factors affecting leopard survival and analyzed leopard movement. In the Mijiang area, the Amur leopard was mainly active in the region adjacent to the Northeast China Tiger and Leopard National Park and did not venture into area near the North Korean border. The complex forest structure allowed leopards to move into the Mijiang area. However, the high intensity of human disturbance and manufactured physical barriers restricted further southward movement. Therefore, human-induced disturbances such as grazing, mining, farming, logging, and infrastructure development must be halted and reversed to make the Mijiang region a functional corridor for the Amur leopard to reach the North Korean forest. This necessitates inter-governmental and international cooperation and is essential for the long-term survival of the Amur leopard. Full article

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. Full article

Camera traps are widely used in wildlife surveys and biodiversity monitoring. Depending on its triggering mechanism, a large number of images or videos are sometimes accumulated. Some literature has proposed the application of deep learning techniques to automatically identify wildlife in camera trap imagery, which can significantly reduce manual work and speed up analysis processes. However, there are few studies validating and comparing the applicability of different models for object detection in real field monitoring scenarios. In this study, we firstly constructed a wildlife image dataset of the Northeast Tiger and Leopard National Park (NTLNP dataset). Furthermore, we evaluated the recognition performance of three currently mainstream object detection architectures and compared the performance of training models on day and night data separately versus together. In this experiment, we selected YOLOv5 series models (anchor-based one-stage), Cascade R-CNN under feature extractor HRNet32 (anchor-based two-stage), and FCOS under feature extractors ResNet50 and ResNet101 (anchor-free one-stage). The experimental results showed that performance of the object detection models of the day-night joint training is satisfying. Specifically, the average result of our models was 0.98 mAP (mean average precision) in the animal image detection and 88% accuracy in the animal video classification. One-stage YOLOv5m achieved the best recognition accuracy. With the help of AI technology, ecologists can extract information from masses of imagery potentially quickly and efficiently, saving much time. Full article

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. Full article

Mammalian coat color is determined by heritable variations such as disease, nutrition, and hormone levels. Variation in animal coat color is also considered an environmental indicator and provides clues for the study of population genetics and biogeography. Records of abnormal coloration in the wild are rare, not only because it is often selected against, but also because of the difficulties in detection of the phenomenon. We used long-term camera-trapping data to first report abnormal coat coloration in yellow-throated marten (Martes flavigula) in China. Six types of abnormal coloration were found only in the Northeast Tiger and Leopard National Park, Northeast China, which were not reported in other regions in China. A total of 268 videos of Martes flavigula contained normal coloration, 455 videos of individuals of the species contained abnormal coloration, 437 contained the ‘gloving’ type (martens with de-pigmented front toes, paws or lower forelimbs), while the remaining other 18 videos contained five types (different degrees of white-spotting and dilution). The higher relative abundance index (0.428, ‘gloving’ to 0.329, normal) and wide distribution area of the ‘gloving’ type indicated that this abnormal coat coloration type is usual in Northeast China, which may reflect genetic variability in the local population. These records will contribute to further research on animal coat color and its corresponding adaptive strategy. Full article

Broad-spectrum beta-lactamase (BSBL)-producing Enterobacteriaceae impose public health threats. With increased popularity of zoos, exotic animals are brought in close proximity of humans, making them important BSBL reservoirs. However, not much is known on the presence of BSBLs in zoos in Western Europe. Fecal carriage of BSBL-producing Enterobacteriaceae was investigated in 38 zoo mammals from two Belgian zoos. Presence of bla-genes was investigated using PCR, followed by whole-genome sequencing and Fourier-transform infrared spectroscopy to cluster acquired resistance encoding genes and clonality of BSBL-producing isolates. Thirty-five putatively ceftiofur-resistant isolates were obtained from 52.6% of the zoo mammals. Most isolates were identified as E. coli (25/35), of which 64.0% showed multidrug resistance (MDR). Most frequently detected bla-genes were CTX-M-1 (17/25) and TEM-1 (4/25). Phylogenetic trees confirmed clustering of almost all E. coli isolates obtained from the same animal species. Clustering of five isolates from an Amur tiger, an Amur leopard, and a spectacled bear was observed in Zoo 1, as well as for five isolates from a spotted hyena and an African lion in Zoo 2. This might indicate clonal expansion of an E. coli strain in both zoos. In conclusion, MDR BSBL-producing bacteria were shown to be present in the fecal microbiota of zoo mammals in two zoos in Belgium. Further research is necessary to investigate if these bacteria pose zoonotic and health risks. Full article