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整合机理模型和经验模型预测结果,评估气候变化对北美西北部树种分布的影响。

Integrating mechanistic and empirical model projections to assess climate impacts on tree species distributions in northwestern North America.

机构信息

School of Environmental and Forest Sciences, University of Washington, Box 352100, Seattle, WA, 98195-2100, USA.

出版信息

Glob Chang Biol. 2017 May;23(5):2005-2015. doi: 10.1111/gcb.13570. Epub 2016 Dec 18.

DOI:10.1111/gcb.13570
PMID:27859937
Abstract

Empirical and mechanistic models have both been used to assess the potential impacts of climate change on species distributions, and each modeling approach has its strengths and weaknesses. Here, we demonstrate an approach to projecting climate-driven changes in species distributions that draws on both empirical and mechanistic models. We combined projections from a dynamic global vegetation model (DGVM) that simulates the distributions of biomes based on basic plant functional types with projections from empirical climatic niche models for six tree species in northwestern North America. These integrated model outputs incorporate important biological processes, such as competition, physiological responses of plants to changes in atmospheric CO concentrations, and fire, as well as what are likely to be species-specific climatic constraints. We compared the integrated projections to projections from the empirical climatic niche models alone. Overall, our integrated model outputs projected a greater climate-driven loss of potentially suitable environmental space than did the empirical climatic niche model outputs alone for the majority of modeled species. Our results also show that refining species distributions with DGVM outputs had large effects on the geographic locations of suitable habitat. We demonstrate one approach to integrating the outputs of mechanistic and empirical niche models to produce bioclimatic projections. But perhaps more importantly, our study reveals the potential for empirical climatic niche models to over-predict suitable environmental space under future climatic conditions.

摘要

实证和机理模型都被用于评估气候变化对物种分布的潜在影响,每种建模方法都有其优缺点。在这里,我们展示了一种利用实证和机理模型来预测物种分布受气候驱动变化的方法。我们结合了一个动态全球植被模型(DGVM)的预测结果,该模型基于基本植物功能类型模拟生物群落的分布,以及北美西北部六种树木的实证气候生态位模型的预测结果。这些综合模型输出结果包含了重要的生物过程,如竞争、植物对大气 CO 浓度变化的生理响应以及火灾,以及可能存在的物种特异性气候限制。我们将综合预测结果与仅来自实证气候生态位模型的预测结果进行了比较。总体而言,对于大多数模拟物种,我们的综合模型输出结果预测的气候驱动的潜在适宜环境空间损失大于仅来自实证气候生态位模型的预测结果。我们的结果还表明,利用 DGVM 输出结果细化物种分布对适宜栖息地的地理位置有很大影响。我们展示了一种整合机理和实证生态位模型输出结果以生成生物气候预测的方法。但更重要的是,我们的研究揭示了实证气候生态位模型在未来气候条件下可能过度预测适宜环境空间的潜力。

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