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Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models

机译:预测气候变化下的灭绝风险:将随机种群模型与动态生物气候生境模型耦合

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摘要

Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.
机译:物种对气候变化的反应可能受到可用栖息地的变化,种群过程,物种相互作用以及人口与景观动态之间相互作用的影响。当前评估这些反应的方法无法提供关于这些影响的综合视图,因为它们处理栖息地的变化或种群动态,但很少涉及两者。在这项研究中,我们将栖息地适应性模型的时间序列与空间上明确的随机种群模型联系在一起,以探索在全球气候多样性不断变化的南非非洲羊yn中稳定和变化的气候情景下影响植物物种种群生存力的因素。结果表明,生活史,干扰机制和分布方式之间的复杂相互作用介导了气候变化下物种灭绝的风险。与静态生物气候栖息地建模方法相比,我们新颖的机械方法可以更全面,直接地评估未来的生物反应,并最终支持开发更有效的保护策略,以减轻由于气候变化造成的生物多样性损失。

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