Rohr Jason R, Raffel Thomas R, Blaustein Andrew R, Johnson Pieter T J, Paull Sara H, Young Suzanne
Integrative Biology, University of South Florida, Tampa, FL 33620, USA.
Department of Biological Science, Oakland University, Rochester, MI 48309-4401, USA.
Conserv Physiol. 2013 Aug 26;1(1):cot022. doi: 10.1093/conphys/cot022. eCollection 2013.
Controversy persists regarding the contributions of climate change to biodiversity losses, through its effects on the spread and emergence of infectious diseases. One of the reasons for this controversy is that there are few mechanistic studies that explore the links among climate change, infectious disease, and declines of host populations. Given that host-parasite interactions are generally mediated by physiological responses, we submit that physiological models could facilitate the prediction of how host-parasite interactions will respond to climate change, and might offer theoretical and terminological cohesion that has been lacking in the climate change-disease literature. We stress that much of the work on how climate influences host-parasite interactions has emphasized changes in climatic means, despite a hallmark of climate change being changes in climatic variability and extremes. Owing to this gap, we highlight how temporal variability in weather, coupled with non-linearities in responses to mean climate, can be used to predict the effects of climate on host-parasite interactions. We also discuss the climate variability hypothesis for disease-related declines, which posits that increased unpredictable temperature variability might provide a temporary advantage to pathogens because they are smaller and have faster metabolisms than their hosts, allowing more rapid acclimatization following a temperature shift. In support of these hypotheses, we provide case studies on the role of climatic variability in host population declines associated with the emergence of the infectious diseases chytridiomycosis, withering syndrome, and malaria. Finally, we present a mathematical model that provides the scaffolding to integrate metabolic theory, physiological mechanisms, and large-scale spatiotemporal processes to predict how simultaneous changes in climatic means, variances, and extremes will affect host-parasite interactions. However, several outstanding questions remain to be answered before investigators can accurately predict how changes in climatic means and variances will affect infectious diseases and the conservation status of host populations.
关于气候变化通过其对传染病传播和出现的影响而对生物多样性丧失的贡献，争议仍然存在。这场争议的原因之一是，很少有机制性研究探讨气候变化、传染病与宿主种群数量下降之间的联系。鉴于宿主 - 寄生虫相互作用通常由生理反应介导，我们认为生理模型可以促进预测宿主 - 寄生虫相互作用将如何应对气候变化，并且可能提供气候变化 - 疾病文献中一直缺乏的理论和术语上的连贯性。我们强调，尽管气候变化的一个标志是气候变率和极端情况的变化，但关于气候如何影响宿主 - 寄生虫相互作用的许多研究都强调了气候平均值的变化。由于这一差距，我们强调天气的时间变率，再加上对平均气候反应的非线性，可以用来预测气候对宿主 - 寄生虫相互作用的影响。我们还讨论了与疾病相关的种群数量下降的气候变率假说，该假说认为温度不可预测性增加可能会给病原体带来暂时优势，因为它们比宿主更小且新陈代谢更快，从而在温度变化后能够更快地适应。为支持这些假说，我们提供了关于气候变率在与壶菌病、枯萎综合征和疟疾等传染病出现相关的宿主种群数量下降中所起作用的案例研究。最后，我们提出了一个数学模型，该模型提供了一个框架，用于整合代谢理论、生理机制和大规模时空过程，以预测气候平均值、方差和极端情况的同时变化将如何影响宿主 - 寄生虫相互作用。然而，在研究人员能够准确预测气候平均值和方差的变化将如何影响传染病以及宿主种群的保护状况之前，仍有几个突出问题有待解答。
