Climate Change Data Portal
| DOI | 10.1111/gcb.17227 |
| How useful are genomic data for predicting maladaptation to future climate? | |
| 发表日期 | 2024 |
| ISSN | 1354-1013 |
| EISSN | 1365-2486 |
| 起始页码 | 30 |
| 结束页码 | 4 |
| 卷号 | 30期号:4 |
| 英文摘要 | Methods using genomic information to forecast potential population maladaptation to climate change or new environments are becoming increasingly common, yet the lack of model validation poses serious hurdles toward their incorporation into management and policy. Here, we compare the validation of maladaptation estimates derived from two methods-Gradient Forests (GFoffset) and the risk of non-adaptedness (RONA)-using exome capture pool-seq data from 35 to 39 populations across three conifer taxa: two Douglas-fir varieties and jack pine. We evaluate sensitivity of these algorithms to the source of input loci (markers selected from genotype-environment associations [GEA] or those selected at random). We validate these methods against 2- and 52-year growth and mortality measured in independent transplant experiments. Overall, we find that both methods often better predict transplant performance than climatic or geographic distances. We also find that GFoffset and RONA models are surprisingly not improved using GEA candidates. Even with promising validation results, variation in model projections to future climates makes it difficult to identify the most maladapted populations using either method. Our work advances understanding of the sensitivity and applicability of these approaches, and we discuss recommendations for their future use. image |
| 英文关键词 | climate change; climate maladaptation; genomic offset; machine learning |
| 语种 | 英语 |
| WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
| WOS类目 | Biodiversity Conservation ; Ecology ; Environmental Sciences |
| WOS记录号 | WOS:001194408900001 |
| 来源期刊 | GLOBAL CHANGE BIOLOGY
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| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/287746 |
| 作者单位 | University of British Columbia; University of British Columbia; University of Calgary; University of British Columbia; Laval University; Laval University; Natural Resources Canada; Canadian Forest Service |
| 推荐引用方式 GB/T 7714 | . How useful are genomic data for predicting maladaptation to future climate?[J],2024,30(4). |
| APA | (2024).How useful are genomic data for predicting maladaptation to future climate?.GLOBAL CHANGE BIOLOGY,30(4). |
| MLA | "How useful are genomic data for predicting maladaptation to future climate?".GLOBAL CHANGE BIOLOGY 30.4(2024). |
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