整合基因组数据和模拟,评估替代物种分布模型,改进冰川避难所和未来对气候变化反应的预测

IF 5.4 1区 环境科学与生态学 Q1 BIODIVERSITY CONSERVATION Ecography Pub Date : 2024-07-02 DOI:10.1111/ecog.07196
Sarah R. Naughtin, Antonio R. Castilla, Adam B. Smith, Allan E. Strand, Andria Dawson, Sean Hoban, Everett Andrew Abhainn, Jeanne Romero‐Severson, John D. Robinson
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引用次数: 0

摘要

气候变化对生物多样性构成威胁,目前尚不清楚物种能否适应或忍受新的环境,或迁移到有合适栖息地的地区。通过物种分布模型(SDMs)重建自上一次冰川极盛时期(LGM)以来因环境变化而发生的分布区迁移,可以为保护工作提供有用的数据。然而,不同的物种分布模型算法和气候重建通常会产生截然不同的模式,而且验证方法通常侧重于再现当前分布的准确性,从而限制了其对过去或未来预测的评估意义。我们利用两个气候模型、三个校准区域和四种建模算法构建的 24 个 SDM,为濒危北美绿白蜡树的历史适宜栖息地建立了模型。我们利用空间块交叉验证的当代数据对 SDM 进行了评估,并使用基于人口遗传耦合模拟的新型综合方法比较了替代模型的相对支持率。我们利用空间显式模型中 24 个 SDM 中每个模型的生境适宜性模拟了基因组数据集。然后使用近似贝叶斯计算(ABC),通过与经验种群基因组数据集的比较,评估替代 SDMs 的支持率。在使用空间交叉验证对当代出现的物种进行评估时,模型的表现非常相似,但近似贝叶斯计算模型选择分析始终支持基于CCSM气候模型、中间校准范围和广义线性建模算法的SDM。最后,我们预测了四种气候变化情景下青灰的未来分布范围。使用通过 ABC 筛选出的 SDM 进行的未来预测表明,该物种的适宜栖息地只会发生微小的变化,而一些被否决的 SDM 则预测会发生巨大的变化。我们的研究结果突显了应用其他分布建模算法可能产生的不同推论,并提供了一种在一组具有独立数据的相互竞争的 SDMs 中进行选择的新方法。
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Integrating genomic data and simulations to evaluate alternative species distribution models and improve predictions of glacial refugia and future responses to climate change
Climate change poses a threat to biodiversity, and it is unclear whether species can adapt to or tolerate new conditions, or migrate to areas with suitable habitats. Reconstructions of range shifts that occurred in response to environmental changes since the last glacial maximum (LGM) from species distribution models (SDMs) can provide useful data to inform conservation efforts. However, different SDM algorithms and climate reconstructions often produce contrasting patterns, and validation methods typically focus on accuracy in recreating current distributions, limiting their relevance for assessing predictions to the past or future. We modeled historically suitable habitat for the threatened North American tree green ash Fraxinus pennsylvanica using 24 SDMs built using two climate models, three calibration regions, and four modeling algorithms. We evaluated the SDMs using contemporary data with spatial block cross‐validation and compared the relative support for alternative models using a novel integrative method based on coupled demographic‐genetic simulations. We simulated genomic datasets using habitat suitability of each of the 24 SDMs in a spatially‐explicit model. Approximate Bayesian computation (ABC) was then used to evaluate the support for alternative SDMs through comparisons to an empirical population genomic dataset. Models had very similar performance when assessed with contemporary occurrences using spatial cross‐validation, but ABC model selection analyses consistently supported SDMs based on the CCSM climate model, an intermediate calibration extent, and the generalized linear modeling algorithm. Finally, we projected the future range of green ash under four climate change scenarios. Future projections using the SDMs selected via ABC suggest only minor shifts in suitable habitat for this species, while some of those that were rejected predicted dramatic changes. Our results highlight the different inferences that may result from the application of alternative distribution modeling algorithms and provide a novel approach for selecting among a set of competing SDMs with independent data.
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来源期刊
Ecography
Ecography 环境科学-生态学
CiteScore
11.60
自引率
3.40%
发文量
122
审稿时长
8-16 weeks
期刊介绍: ECOGRAPHY publishes exciting, novel, and important articles that significantly advance understanding of ecological or biodiversity patterns in space or time. Papers focusing on conservation or restoration are welcomed, provided they are anchored in ecological theory and convey a general message that goes beyond a single case study. We encourage papers that seek advancing the field through the development and testing of theory or methodology, or by proposing new tools for analysis or interpretation of ecological phenomena. Manuscripts are expected to address general principles in ecology, though they may do so using a specific model system if they adequately frame the problem relative to a generalized ecological question or problem. Purely descriptive papers are considered only if breaking new ground and/or describing patterns seldom explored. Studies focused on a single species or single location are generally discouraged unless they make a significant contribution to advancing general theory or understanding of biodiversity patterns and processes. Manuscripts merely confirming or marginally extending results of previous work are unlikely to be considered in Ecography. Papers are judged by virtue of their originality, appeal to general interest, and their contribution to new developments in studies of spatial and temporal ecological patterns. There are no biases with regard to taxon, biome, or biogeographical area.
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