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通过多情景最大熵模型模拟预测柳枝稷在中国向北的分布范围扩张

Forecasting Northward Range Expansion of Switchgrass in China via Multi-Scenario MaxEnt Simulations.

作者信息

Xiang Yangzhou, Li Suhang, Yang Qiong, Ren Jun, Liu Ying, Luo Yang, Zhao Ling, Luo Xuqiang, Yao Bin, Guo Xinzhao

机构信息

School of Geography and Resources, Guizhou Education University, Guiyang 550018, China.

School of Biological Sciences, Guizhou Education University, Guiyang 550018, China.

出版信息

Biology (Basel). 2025 Aug 15;14(8):1061. doi: 10.3390/biology14081061.

DOI:10.3390/biology14081061
PMID:40906364
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12383612/
Abstract

Global warming is accelerating the poleward and upward shifts in climatically suitable ranges of species. (switchgrass) is recognized for its dual value in China's dual-carbon strategy: mitigating food-energy land competition and restoring marginal ecosystems. However, the accuracy of habitat projections is constrained by three limitations: reliance on North American provenance data, uncalibrated model parameters, and insufficient scenario coverage. To address these, 48 switchgrass occurrence records and 22 climatic-topographic variables were integrated. The MaxEnt model was optimized with ENMeval (RM = 4.0, FC = LQH) and coupled with three SSP scenarios (SSP1-2.6, SSP3-7.0, SSP5-8.5) to quantify habitat area changes and centroid shifts across China. The key findings were as follows: (1) The mean temperature of the coldest quarter (Bio11) and elevation were identified as the key limiting factors for the suitable distribution of switchgrass, with their corresponding optimal thresholds determined as -8.79 to 8.11 °C and 0 to 2893 m, respectively. (2) The current suitable habitat covers 583.58 × 10 km, concentrated in the North China Plain. (3) Under SSP5-8.5, the high-suitability habitat is projected to reach 229.44 × 10 km by the 2090s, with the centroid migrating 305 km northwestward to the Inner Mongolia-Jilin belt. This study highlights the climate-topography coupling that drives northward migration and proposes cold-tolerant cultivar development, priority zoning of marginal lands, and ecological corridor establishment to inform climate-smart biomass energy planning in China.

摘要

全球变暖正在加速物种气候适宜范围向极地和高海拔地区的转移。柳枝稷在中国的双碳战略中因其双重价值而受到认可:缓解粮食-能源用地竞争并恢复边缘生态系统。然而,栖息地预测的准确性受到三个限制:依赖北美种源数据、模型参数未校准以及情景覆盖不足。为解决这些问题,整合了48条柳枝稷出现记录和22个气候-地形变量。利用ENMeval(RM = 4.0,FC = LQH)对MaxEnt模型进行了优化,并与三种共享社会经济路径情景(SSP1-2.6、SSP3-7.0、SSP5-8.5)相结合,以量化中国各地栖息地面积变化和重心转移。主要研究结果如下:(1)最冷月平均温度(Bio11)和海拔被确定为柳枝稷适宜分布的关键限制因素,其相应的最佳阈值分别确定为-8.79至8.11℃和0至2893米。(2)当前适宜栖息地面积为583.58×10平方千米,集中在中国华北平原。(3)在SSP5-8.5情景下,到2090年代,高适宜性栖息地预计将达到229.44×10平方千米,重心向西北迁移305千米至内蒙古-吉林地带。本研究强调了驱动向北迁移的气候-地形耦合作用,并提出了耐寒品种培育、边缘土地优先分区以及生态廊道建设,以为中国气候智能型生物质能源规划提供参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/d708c0631733/biology-14-01061-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/3fdf660e2a90/biology-14-01061-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/6643fa6ff657/biology-14-01061-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/12810b095f1e/biology-14-01061-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/aa73c5e6daf5/biology-14-01061-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/e621adf0cf74/biology-14-01061-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/b0778cec70b6/biology-14-01061-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/1dbded475582/biology-14-01061-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/b3087fb000e3/biology-14-01061-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/d708c0631733/biology-14-01061-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/3fdf660e2a90/biology-14-01061-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/6643fa6ff657/biology-14-01061-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/12810b095f1e/biology-14-01061-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/aa73c5e6daf5/biology-14-01061-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/e621adf0cf74/biology-14-01061-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/b0778cec70b6/biology-14-01061-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/1dbded475582/biology-14-01061-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/b3087fb000e3/biology-14-01061-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/929e/12383612/d708c0631733/biology-14-01061-g009.jpg

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