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预计在21世纪末的高排放情景下,东非主要牧场草种的分布将发生重大变化。

Major distribution shifts are projected for key rangeland grasses under a high-emission scenario in East Africa at the end of the 21 century.

作者信息

Messmer Martina, Eckert Sandra, Torre-Marin Rando Amor, Snethlage Mark, González-Rojí Santos J, Hurni Kaspar, Beyerle Urs, Hemp Andreas, Kibet Staline, Stocker Thomas F

机构信息

Climate and Environmental Physics, University of Bern, Sidlerstrasse 5, Bern, 3012 Bern, Switzerland.

Oeschger Centre for Climate Change Research, University of Bern, Sidlerstrasse 5, Bern, 3012 Bern, Switzerland.

出版信息

Commun Earth Environ. 2024;5(1):600. doi: 10.1038/s43247-024-01731-x. Epub 2024 Oct 17.

DOI:10.1038/s43247-024-01731-x
PMID:39430422
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11486655/
Abstract

Grassland landscapes are important ecosystems in East Africa, providing habitat and grazing grounds for wildlife and livestock and supporting pastoralism, an essential part of the agricultural sector. Since future grassland availability directly affects the future mobility needs of pastoralists and wildlife, we aim to model changes in the distribution of key grassland species under climate change. Here we combine a global and regional climate model with a machine learning-based species distribution model to understand the impact of regional climate change on different key grass species. The application of a dynamical downscaling step allows us to capture the fine-scale effects of the region's complex climate, its variability and future changes. We show that the co-occurrence of the analysed grass species is reduced in large parts of eastern Africa, and particularly in the Turkana region, under the high-emission RCP8.5 scenario for the last 30 years of the 21 century. Our results suggest that future climate change will alter the natural resource base, with potentially negative impacts on pastoralism and wildlife in East Africa.

摘要

草原景观是东非重要的生态系统,为野生动物和牲畜提供栖息地和牧场,并支持畜牧业,而畜牧业是农业部门的重要组成部分。由于未来草原的可利用性直接影响牧民和野生动物未来的迁徙需求,我们旨在模拟气候变化下关键草原物种分布的变化。在这里,我们将全球和区域气候模型与基于机器学习的物种分布模型相结合,以了解区域气候变化对不同关键草种的影响。动态降尺度步骤的应用使我们能够捕捉该地区复杂气候的精细尺度效应、其变异性和未来变化。我们表明,在21世纪最后30年的高排放RCP8.5情景下,东非大部分地区,特别是图尔卡纳地区,分析的草种共生现象减少。我们的结果表明,未来气候变化将改变自然资源基础,可能对东非的畜牧业和野生动物产生负面影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af4f/11486655/38a04744be91/43247_2024_1731_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af4f/11486655/4ffe328583ec/43247_2024_1731_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af4f/11486655/9ba16ae6c8df/43247_2024_1731_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af4f/11486655/38a04744be91/43247_2024_1731_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af4f/11486655/4ffe328583ec/43247_2024_1731_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af4f/11486655/9ba16ae6c8df/43247_2024_1731_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af4f/11486655/38a04744be91/43247_2024_1731_Fig3_HTML.jpg

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