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连接分布模型与个体变异的气候生物地理学。

Climate biogeography of linking distribution models and individual variation.

作者信息

Yim Christina, Bellis Emily S, DeLeo Victoria L, Gamba Diana, Muscarella Robert, Lasky Jesse R

机构信息

Department of Biology, Pennsylvania State University, University Park, USA.

Department of Computer Science, Arkansas State University, Jonesboro, USA.

出版信息

J Biogeogr. 2024 Apr;51(4):560-574. doi: 10.1111/jbi.14737. Epub 2023 Oct 3.

DOI:10.1111/jbi.14737
PMID:38596256
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11000247/
Abstract

AIM

Patterns of individual variation are key to testing hypotheses about the mechanisms underlying biogeographic patterns. If species distributions are determined by environmental constraints, then populations near range margins may have reduced performance and be adapted to harsher environments. Model organisms are potentially important systems for biogeographical studies, given the available range-wide natural history collections, and the importance of providing biogeographical context to their genetic and phenotypic diversity.

LOCATION

Global.

TAXON

("Arabidopsis").

METHODS

We fit occurrence records to climate data, and then projected the distribution of Arabidopsis under last glacial maximum, current, and future climates. We confronted model predictions with individual performance measured on 2,194 herbarium specimens, and we asked whether predicted suitability was associated with life-history and genomic variation measured on ~900 natural accessions.

RESULTS

The most important climate variables constraining the Arabidopsis distribution were winter cold in northern and high elevation regions and summer heat in southern regions. Herbarium specimens from regions with lower habitat suitability in both northern and southern regions were smaller, supporting the hypothesis that the distribution of Arabidopsis is constrained by climate-associated factors. Climate anomalies partly explained interannual variation in herbarium specimen size, but these did not closely correspond to local limiting factors identified in the distribution model. Late-flowering genotypes were absent from the lowest suitability regions, suggesting slower life histories are only viable closer to the center of the realized niche. We identified glacial refugia farther north than previously recognized, as well as refugia concordant with previous population genetic findings. Lower latitude populations, known to be genetically distinct, are most threatened by future climate change. The recently colonized range of Arabidopsis was well-predicted by our native-range model applied to certain regions but not others, suggesting it has colonized novel climates.

MAIN CONCLUSIONS

Integration of distribution models with performance data from vast natural history collections is a route forward for testing biogeographical hypotheses about species distributions and their relationship with evolutionary fitness across large scales.

摘要

目的

个体变异模式是检验关于生物地理模式潜在机制假说的关键。如果物种分布由环境限制因素决定,那么分布范围边缘附近的种群可能表现较差,并适应更恶劣的环境。鉴于现有的涵盖广泛区域的自然历史标本集,以及为其遗传和表型多样性提供生物地理背景的重要性,模式生物对于生物地理学研究可能是重要的系统。

地点

全球。

分类单元

(“拟南芥”)。

方法

我们将出现记录与气候数据进行拟合,然后预测了拟南芥在末次盛冰期、当前和未来气候条件下的分布。我们将模型预测结果与在2194份植物标本上测得的个体表现进行对比,并探讨预测的适宜性是否与在约900份自然种质上测得的生活史和基因组变异相关。

结果

限制拟南芥分布的最重要气候变量是北部和高海拔地区的冬季寒冷以及南部地区的夏季炎热。来自北部和南部栖息地适宜性较低地区的植物标本较小,支持了拟南芥分布受气候相关因素限制的假说。气候异常部分解释了植物标本大小的年际变化,但这些与分布模型中确定的局部限制因素并不紧密对应。最晚开花的基因型在适宜性最低的地区不存在,这表明较慢的生活史仅在更接近实际生态位中心的地方才可行。我们确定了比之前认识到的更靠北的冰川避难所,以及与之前种群遗传学研究结果一致的避难所。已知在基因上有差异的低纬度种群受未来气候变化威胁最大。我们将适用于某些地区而非其他地区的原生分布范围模型应用于拟南芥最近殖民的范围,结果显示预测效果良好,这表明它已在新的气候条件下殖民。

主要结论

将分布模型与来自大量自然历史标本集的表现数据相结合,是检验关于物种分布及其与大规模进化适应性关系的生物地理假说的一条前进道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b81/11000247/89b6eae0826b/nihms-1934385-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b81/11000247/2f54ebe3927a/nihms-1934385-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b81/11000247/2d57419f56d9/nihms-1934385-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b81/11000247/9f1ebd52c6d2/nihms-1934385-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b81/11000247/97242d188645/nihms-1934385-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b81/11000247/89b6eae0826b/nihms-1934385-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b81/11000247/2f54ebe3927a/nihms-1934385-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b81/11000247/2d57419f56d9/nihms-1934385-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b81/11000247/9f1ebd52c6d2/nihms-1934385-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b81/11000247/97242d188645/nihms-1934385-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b81/11000247/89b6eae0826b/nihms-1934385-f0006.jpg

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