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利用栖息地质量模型和最大熵模型分析优先保护区

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

作者信息

Jeong Ahmee, Kim Minkyung, Lee Sangdon

机构信息

Department of Environmental Science and Engineering, Ewha Womans University, Seoul 03760, Republic of Korea.

出版信息

Animals (Basel). 2024 Jun 4;14(11):1680. doi: 10.3390/ani14111680.

DOI:10.3390/ani14111680
PMID:38891727
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11171180/
Abstract

This study investigated core habitat areas for yellow-throated martens () and leopard cats (), 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.

摘要

本研究调查了黄喉貂( )和豹猫( )的核心栖息地,这两种濒危森林物种对韩国的栖息地破碎化很敏感。通过叠加InVEST-HQ模型和MaxEnt模型,通过分析当前保护区的缺口来确定优先保护区。InVEST-HQ模型显示,栖息地质量在0到1的范围内为0至0.86,环境保护价值评估图上大多数最合适的区域(被指定为1级)都被正确推导出来。MaxEnt模型分析准确地捕捉到了黄喉貂和豹猫的生态特征,并确定了可能的出现区域。我们通过叠加这两个结果来分析最适合黄喉貂和豹猫的栖息地。缺口分析确定了现有保护区的缺口,并确定了优先保护区。核心区域(14.7%)主要分布在庆北、庆南和江原道等地的太白山脉保护区等森林中;12.9%在保护区之外,只有1.8%得到保护。将保护区和非保护区之间的重叠结果与不同土地利用类型进行了比较。确定保护优先区域为森林覆盖率超过95%的区域,为这两个物种提供了适宜的栖息地。这些发现可用于通过客观栖息地分析确定优先保护区,并作为保护区指定和濒危物种栖息地保护评估的基础,从而有助于生物多样性和生态系统保护。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/3dca55c90193/animals-14-01680-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/da2194ec3985/animals-14-01680-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/9b59204d5d35/animals-14-01680-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/825858251e96/animals-14-01680-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/a1a99995fdf2/animals-14-01680-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/dd482c4fddb3/animals-14-01680-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/af3221f0f941/animals-14-01680-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/efaa89ad7772/animals-14-01680-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/3dca55c90193/animals-14-01680-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/da2194ec3985/animals-14-01680-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/9b59204d5d35/animals-14-01680-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/825858251e96/animals-14-01680-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/a1a99995fdf2/animals-14-01680-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/dd482c4fddb3/animals-14-01680-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/af3221f0f941/animals-14-01680-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/efaa89ad7772/animals-14-01680-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2069/11171180/3dca55c90193/animals-14-01680-g008.jpg

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本文引用的文献

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Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools.全球对 2030 年城市扩张的预测及其对生物多样性和碳储量的直接影响。
Proc Natl Acad Sci U S A. 2012 Oct 2;109(40):16083-8. doi: 10.1073/pnas.1211658109. Epub 2012 Sep 17.
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Ensemble forecasting of species distributions.物种分布的集合预报
Trends Ecol Evol. 2007 Jan;22(1):42-7. doi: 10.1016/j.tree.2006.09.010. Epub 2006 Sep 29.
Animals (Basel). 2024 Sep 12;14(18):2644. doi: 10.3390/ani14182644.