Species conservation actions are guided by available information on the biogeography of the protected species. In this study, we integrated the occurrence data of Siberian musk deer ( L.) collected from 2019 to 2021 with species distribution models to estimate the species' potential distribution in Northeast China. We then identified conservation priority areas using a core-area zonation algorithm. In addition, we analyzed core patch fragmentation using FRAGSTATS. Lastly, we identified potential connectivity corridors and constructed a potential protection network based on the least-cost path and the circuit theory. The results showed concentrations of in the northern Greater Khingan Mountains, the southeastern Lesser Khingan Mountains, and the eastern Changbai Mountains, with a potential distribution area of 127,442.14 km. Conservation priority areas included 41 core patches with an area of 106,306.43 km. Patch fragmentation mainly occurred in the Changbai Mountains and the Lesser Khingan Mountains. We constructed an ecological network composed of 41 core patches and 69 linkages for in Northeast China. The results suggest that the Greater Khingan Mountains represent the most suitable area to maintain the stability of populations in Northeast China. Considering the high habitat quality requirements of and its endangered status, we propose that the Chinese government accelerates the construction of the Greater Khingan Mountains National Park and the Lesser Khingan Mountains National Park and enlarges the Northeast China Tiger and Leopard National Park to address the fragmentation of protected areas and the habitat of .
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http://dx.doi.org/10.3390/ani12030260 | DOI Listing |
Ying Yong Sheng Tai Xue Bao
October 2024
Ministry of Education Key Laboratory of Sustainable Forest Ecosystem Management/School of Forestry, Northeast Forestry University, Harbin 150040, China.
Carbon balance of the tree layer in natural forests is affected by three carbon pools: tree growth, morta-lity, and recruitment. However, the dynamics of the sink of each carbon pool and the driving factors are still unclear. To this end, we used stepwise regression method and structural equation model to assess the effects of biotic (stand and diversity) and abiotic (soil, topography and climate) factors on three dynamic processes of carbon sinks, namely, stand growth, recruitment and mortality, in the natural forests of , based on the data from the seventh and eighth national continuous forest inventory of the Greater Khingan Mountains.
View Article and Find Full Text PDFJ Environ Manage
December 2024
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China. Electronic address:
Ecosystem services and their accounting frameworks have been extensively studied. Snow, as a special climatic product, can provides essential resources and services for human well-being and socioeconomic development which is often ignored. However, the services and value it provides have not been effectively evaluated.
View Article and Find Full Text PDFFront Microbiol
November 2024
Heilongjiang Huzhong National Nature Reserve, Huzhong, Greater Khingan Mountains Region, China.
Introduction: Epiphytic and endophytic fungi are primary decomposers of forest litter due to their complex species composition and metabolic functions. To clarify the community diversity of phyllospheric fungi and to explore nutrient loss and the role of fungal decomposition, we conducted a study on the decomposition of leaf litter during the 1-year decomposition of in the cold temperate zone.
Methods: Fungal diversity data were characterized via Single Molecule Sequencing (based on the Sequel II Sequencing System) and statistical analyses in R.
Huan Jing Ke Xue
November 2024
School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China.
Huan Jing Ke Xue
December 2024
Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, College of Forestry, Northeast Forestry University, Harbin 150040, China.
PM is an important indicator for measuring the degree of air pollution. Studying the space-time variation and the driving factors of spatial heterogeneity is important for controlling air pollution and improving regional air quality. Based on PM remote sensing data from 2000 to 2021, the Theil-Sen Median trend analysis, Mann-Kendall significant inspection, and spatial auto correlation were used to analyze the characteristics of space-time changes in PM concentration, and geographical detectors were combined with a multi-scale geographical weighted regression model to explore the key driver factor and its influence and direction of the impact and role of PM spatial differences.
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