Habitat Potential Mapping of Marten (Martes flavigula) and Leopard Cat (Prionailurus bengalensis) in South Korea Using Artificial Neural Network Machine Learning

Analysis of Priority Conservation Areas Using Habitat Quality Models and MaxEnt Models

This study investigated core habitat areas for yellow-throated martens (Martes flavigula) and leopard cats (Prionailurus bengalensis), two endangered forest species sensitive to habitat fragmentation in Korea. Overlaying the InVEST-HQ and MaxEnt models, priority conservation areas were identified by analyzing gaps in currently protected areas. The InVEST-HQ model showed that habitat quality ranged from 0 to 0.86 on a scale from 0 to 1, and the majority of the most suitable areas on the Environmental Conservation Value Assessment Map, designated as grade 1, were derived correctly. The MaxEnt model analysis accurately captured the ecological characteristics of the yellow-throated marten and the leopard cat and identified probable regions of occurrence. We analyzed the most suitable yellow-throated marten and leopard cat habitats by superimposing the two results. Gap analysis determined gaps in existing protected areas and identified priority conservation areas. The core area (14.7%) was mainly distributed in forests such as the Baekdudaegan Mountains Reserve in regions such as Gyeongbuk, Gyeongnam, and Gangwon; 12.9% was outside protected areas, and only 1.8% was protected. The overlap results between protected and non-protected areas were compared with different land use types. Conservation priority areas were identified as those with more than 95% forest cover, offering an appropriate habitat for the two species. These findings can be used to identify priority conservation areas through objective habitat analysis and as a basis for protected area designation and assessment of endangered species habitat conservation, thereby contributing to biodiversity and ecosystem conservation.

The Minimal Impact of Anthropogenic Disturbances on the Spatial Activities of Leopard Cats in Xinlong, China

The habitat plays a crucial role in ensuring the survival of wildlife. However, the increasing disturbances caused by human activities present a substantial threat to habitats, especially for species such as the leopard cat (Prionailurus bengalensis), which is a significant small predator. Currently, research on leopard cats predominantly focuses on low-altitude regions within its distribution range, leaving plateau areas understudied. To enhance our understanding of the impact of human disturbances on leopard cat habitats, we undertook a study employing infrared camera trappings to monitor leopard cats' activity in Xinlong of southwestern China between 2015 and 2023. We analyzed the spatial distribution and habitat suitability of the leopard cats by utilizing ensemble species distribution models (ESDMs). Moreover, we employed two-species occupancy models to investigate the spatial interaction between leopard cats and human disturbances. The results indicated that (1) the potential suitable habitat area for leopard cats encompassed approximately 1324.93 km2 (14.3%), primarily located along the banks of Yalong river. (2) The distribution of suitable habitat was predominantly influenced by competitors, specifically the yellow-throated marten (YTM), accounting for 52.4% of the influence, as well as environmental factors such as distance to water (DTW) at 12.0% and terrain roughness index (TRI) at 10.0%. Human interference, including cattle presence (4.6%), distance to road (DTD, 4.9%), and distance to settlement (DTS, 3.5%), had a limited impact on the habitat distribution. (3) Within a 5 km radius, habitat suitability increased with proximity to human settlements. (4) Leopard cats exhibited spatial independence from humans and domestic cattle (species interaction factor (SIF) = 1.00) while avoiding domestic horses (SIF = 0.76 ± 0.03). The relatively minor impact of human disturbances in Xinlong could be attributed to traditional cultural practices safeguarding wildlife and the leopard cat's environmental adaptability. We recommend establishing a novel conservation paradigm based on the living dynamics of wildlife communities in Xinlong, thereby offering a more targeted approach to biodiversity preservation in the future.

A chromosome-level genome assembly of the yellow-throated marten (Martes flavigula)

The yellow-throated marten (Martes flavigula) is a medium-sized carnivore that is widely distributed across much of Asia and occupies an extensive variety of habitats. We reported a high-quality genome assembly of this organism that was generated using Oxford Nanopore and Hi-C technologies. The final genome sequences contained 215 contigs with a total size of 2,449.15 Mb and a contig N50 length of 68.60 Mb. Using Hi-C analysis, 2,419.20 Mb (98.78%) of the assembled sequences were anchored onto 21 linkage groups. Merqury evaluation suggested that the genome was 94.95% complete with a QV value of 43.75. Additionally, the genome was found to comprise approximately 39.74% repeat sequences, of which long interspersed elements (LINE) that accounted for 26.13% of the entire genome, were the most abundant. Of the 20,464 protein-coding genes, prediction and functional annotation was successfully performed for 20,322 (99.31%) genes. The high-quality, chromosome-level genome of the marten reported in this study will serve as a reference for future studies on genetic diversity, evolution, and conservation biology.

Association of Leopard Cat Occurrence with Environmental Factors in Chungnam Province, South Korea

This study was conducted to investigate the association of leopard cat (Prionailurus bengalensis) occurrences and environmental factors in Chungnam Province, South Korea, using two different analytical approaches for binomial responses: boosted regression trees and logistic regression. The extensive field survey data collected through the Chungnam Biotope Project were used to model construction and analysis. Five major influential factors identified by the boosted regression tree analysis were elevation, distance to road, distance to water channel/body, slope and population density. Logistic regression analysis indicated that distance to forest, population density, distance to water, and diameter class of the forest were the significant explanatory variables. The results showed that the leopard cats prefer the areas with higher accessibility of food resources (e.g., abundance and catchability) and avoid the areas adjacent to human-populated areas. The results also implied that boosted regression and logistic regression models could be used in a complementary manner for evaluating wildlife distribution and management.

First Discovery of Vespa velutina nigrithorax du Buysson (Hymenoptera: Vespidae), an Invasive Hornet in the Feces of the Yellow-Throated Marten in South Korea

Simple Summary

Invasive species can have serious economic and ecological effects. Biological controls are a way to reduce damage from invasive species. We collected 22 fecal samples from yellow-throated martens, which often prey on wasps in late autumn, from Mt. Onggangsan in Cheongdo, South Korea, to confirm the predation of the invasive alien hornet, Vespa velutina nigrithorax. Hornet debris was found in three samples, along with two native wasp species. The hornets were identified as one queen, four males, one female, and one individual whose caste was unclear. Therefore, because reproductive individuals were preyed upon, it is likely that yellow-throated marten predation could potentially be used for the biological control of invasive alien hornets.

Abstract

Yellow-throated martens (YTMs) are omnivores that often prey on wasps in late autumn in Korea. However, to the best of our knowledge, predation of the invasive alien species Vespa velutina nigrithorax (VVN) has not previously been investigated. In this study, YTM feces were collected and analyzed from Mt. Onggangsan, Sinwon-ri, Cheongdo, South Korea, where VVN density was high and YTMs were active. Surveys were conducted three times between October and December 2019, during which a total of 22 samples were collected. Debris from VVN was found in three samples, along with evidence of two indigenous wasps, Vespa crabro and Vespula koreensis. The VVN remains were identified as one queen, four males, one female, and one individual whose caste was unclear. Martens prey on wasps, owing to a sudden decrease in plant food sources from late autumn to early winter, mostly eating males and new queens attempting to mate. If VVN reproduction is prevented or disturbed by YTM predation, there may be potential biological control effects in areas with high VVN density. Further studies should be conducted to verify whether there is a practical biological control effect.

Spatial Mapping of the Groundwater Potential of the Geum River Basin Using Ensemble Models Based on Remote Sensing Images

This study analyzed the Groundwater Productivity Potential (GPP) of Okcheon city, Korea, using three different models. Two of these three models are data mining models: Boosted Regression Tree (BRT) model and Random Forest (RF) model. The other model is the Logistic Regression (LR) model. The three models are based on the relationship between groundwater-productivity data (specific capacity (SPC) and transmissivity (T)) and the related hydro-geological factors from thematic maps, such as topography, lineament, geology, land cover, and etc. The thematic maps which are generated from the remote sensing images. Groundwater productivity data were collected from 86 wells locations. The resulting GPP maps were validated through area-under-the-curve (AUC) analysis using wells data that had not been used for training the model. When T was used in the BRT, RF, and LR models, the obtained GPP maps had 81.66%, 80.21%, and 85.04% accuracy, respectively, and when SPC was used, the maps had 81.53%, 78.57%, and 82.22% accuracy, respectively. The LR model, which is a statistical model, showed the highest verification accuracy, also the other two models showed high accuracies. These observations indicate that all three models can be useful for groundwater resource development.

Biogeography of Korea's top predator, the yellow-throated Marten: evolutionary history and population dynamics

BACKGROUND

Peninsulas often harvest high genetic diversity through repeated southward migrations of species during glacial maxima. Studies addressing within-species evolutionary responses to climate fluctuations in northeast Asia are limited compared to other regions of the world, and more so in the Korean Peninsula. In this study, we conducted the first population-level study of the yellow-throated marten, Martes flavigula, from the Korean Peninsula, Russian, Taiwanese and Chinese localities in a biogeographic framework using mitochondrial (cyt-b, nd2, cr) and nuclear gene sequencing (ghr).

RESULTS

Bayesian analyses revealed a rather young population, with a split from the most recent common ancestor at around 125 kya. Martes flavigula likely colonized the Korean Peninsula from Mainland China through the Yellow Sea twice, ca. 60 kya and 20 kya. Korean martens diversified during the Late Pleistocene with at least two dispersal events out of Korea, towards the southwest to Taiwan (ca. 80 kya) and towards the North into Russia and eastern China; most likely after the Last Glacial Maxima (ca. 20 kya). We argue that the lack of population structure and mixed populations is possibly a consequence of the high dispersal capability of the species. The Bayesian skyline plot revealed a population decline within the last 5000 years, suggesting potential negative biotic and anthropogenic effects in the area. We find that local populations are not genetically differentiated, therefore no perceptible population structure within Korea was found.

CONCLUSIONS

The topography and geography of the Korean Peninsula has played a pivotal role in its colonization. Connections between the Korean Peninsula and the Mainland through sea-level drops of the Yellow Sea at times of glacial maxima and the high dispersal capability of M. flavigula adds to the lack of geographical structure in this species and the paraphyly of Korean lineages.

Exploration in Mapping Kernel-Based Home Range Models from Remote Sensing Imagery with Conditional Adversarial Networks

Kernel-based home range models are widely-used to estimate animal habitats and develop conservation strategies. They provide a probabilistic measure of animal space use instead of assuming the uniform utilization within an outside boundary. However, this type of models estimates the home ranges from animal relocations, and the inadequate locational data often prevents scientists from applying them in long-term and large-scale research. In this paper, we propose an end-to-end deep learning framework to simulate kernel home range models. We use the conditional adversarial network as a supervised model to learn the home range mapping from time-series remote sensing imagery. Our approach enables scientists to eliminate the persistent dependence on locational data in home range analysis. In experiments, we illustrate our approach by mapping the home ranges of Bar-headed Geese in Qinghai Lake area. The proposed framework outperforms all baselines in both qualitative and quantitative evaluations, achieving visually recognizable results and high mapping accuracy. The experiment also shows that learning the mapping between images is a more effective way to map such complex targets than traditional pixel-based schemes.