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一项综合的高分辨率图谱显示,壳斗目和松柏目具有一致的生物多样性模式。

An integrated high-resolution mapping shows congruent biodiversity patterns of Fagales and Pinales.

机构信息

Department of Environmental System Science, ETH Zürich, Universitätstrasse 16, 8092, Zürich, Switzerland.

Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland.

出版信息

New Phytol. 2022 Jul;235(2):759-772. doi: 10.1111/nph.18158. Epub 2022 May 5.

DOI:10.1111/nph.18158
PMID:35429166
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9323436/
Abstract

The documentation of biodiversity distribution through species range identification is crucial for macroecology, biogeography, conservation, and restoration. However, for plants, species range maps remain scarce and often inaccurate. We present a novel approach to map species ranges at a global scale, integrating polygon mapping and species distribution modelling (SDM). We develop a polygon mapping algorithm by considering distances and nestedness of occurrences. We further apply an SDM approach considering multiple modelling algorithms, complexity levels, and pseudo-absence selections to map the species at a high spatial resolution and intersect it with the generated polygons. We use this approach to construct range maps for all 1957 species of Fagales and Pinales with data compilated from multiple sources. We construct high-resolution global species richness maps of these important plant clades, and document diversity hotspots for both clades in southern and south-western China, Central America, and Borneo. We validate the approach with two representative genera, Quercus and Pinus, using previously published coarser range maps, and find good agreement. By efficiently producing high-resolution range maps, our mapping approach offers a new tool in the field of macroecology for studying global species distribution patterns and supporting ongoing conservation efforts.

摘要

通过物种分布范围识别来记录生物多样性分布情况对宏观生态学、生物地理学、保护和恢复至关重要。然而,对于植物而言,物种分布范围图仍然稀缺且常常不够准确。我们提出了一种新的方法来在全球范围内绘制物种分布范围图,该方法结合了多边形绘制和物种分布模型(SDM)。我们通过考虑发生点的距离和嵌套性来开发多边形绘制算法。我们进一步应用了一种考虑多种建模算法、复杂度水平和伪不存在选择的 SDM 方法来以高空间分辨率绘制物种分布,并将其与生成的多边形相交。我们使用这种方法来构建来自多个来源的数据的 1957 种壳斗科和松科的分布范围图。我们构建了这些重要植物类群的高分辨率全球物种丰富度图,并记录了中国南部和西南部、中美洲和婆罗洲这两个类群的多样性热点。我们使用先前发表的较粗糙的分布范围图对两个代表性属,栎属和松属进行了验证,发现吻合度较好。通过高效地生成高分辨率的分布范围图,我们的绘制方法为宏观生态学领域提供了一种新工具,可用于研究全球物种分布模式并支持正在进行的保护工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9cd/9323436/b523a6083d53/NPH-235-759-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9cd/9323436/6fc05c2d1373/NPH-235-759-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9cd/9323436/ed7bbcb339d2/NPH-235-759-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9cd/9323436/f427c7fa6ad4/NPH-235-759-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9cd/9323436/b523a6083d53/NPH-235-759-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9cd/9323436/6fc05c2d1373/NPH-235-759-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9cd/9323436/ed7bbcb339d2/NPH-235-759-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9cd/9323436/f427c7fa6ad4/NPH-235-759-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9cd/9323436/b523a6083d53/NPH-235-759-g002.jpg

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