Predicting resilience of ecosystem functioning from co-varying species' responses to environmental change
Predicting resilience of ecosystem functioning from co-varying species' responses to environmental change
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DOI：
10.1002/ece3.5679
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发表时间：
2019-10-01
影响因子：
2.6
通讯作者：
Oliver, Tom H.
中科院分区：
文献类型：
--
作者：
Greenwell, Matthew P.;Brereton, Tom;Oliver, Tom H.
了解环境变化如何影响生态系统功能传递对基础生态学和应用生态学至关重要。目前的研究方法侧重于单个环境驱动因素对社区的影响，由个体反应特征介导。数据的限制限制了扩大这种方法来预测多变量环境变化对生态系统功能的影响。我们提出了一种更全面的方法来确定生态系统功能的恢复能力，使用长期监测数据来分析多种历史环境驱动因素对物种种群动态的总体影响。通过评估物种对种群动态的共变，我们确定了哪些物种对环境变化的反应最同步，并将物种分配到“响应行会”中。然后，我们使用结合性状数据的“生产函数”来估计物种对生态系统功能的相对作用。我们量化了响应行会和生产功能之间的相关性，评估了生态系统功能对环境变化的恢复能力，在相同的功能行会中，物种的异步动态有望导致更稳定的生态系统功能。通过对英国40多年来收集的蝴蝶数据进行测试，我们发现三种生态系统功能（资源供应、野花授粉和审美文化价值）显得相对稳健，功能重要的物种分散在响应行业中，表明生态系统功能更稳定。此外，通过将遗传距离与反应行会联系起来，我们评估了对环境变化的反应的遗传性。本研究结果表明，基于系统发育推断蝴蝶种群对环境变化的响应是可行的，这为种群监测数据有限的稀有物种保护管理提供了有益的见解。我们的方法有望克服预测生态系统功能对环境变化的反应的僵局。量化共变物种对多变量环境变化的响应将使我们能够显著提高我们对生态系统功能弹性的预测，并使我们能够主动管理生态系统。
Understanding how environmental change affects ecosystem function delivery is of primary importance for fundamental and applied ecology. Current approaches focus on single environmental driver effects on communities, mediated by individual response traits. Data limitations present constraints in scaling up this approach to predict the impacts of multivariate environmental change on ecosystem functioning. We present a more holistic approach to determine ecosystem function resilience, using long-term monitoring data to analyze the aggregate impact of multiple historic environmental drivers on species' population dynamics. By assessing covariation in population dynamics between pairs of species, we identify which species respond most synchronously to environmental change and allocate species into "response guilds." We then use "production functions" combining trait data to estimate the relative roles of species to ecosystem functions. We quantify the correlation between response guilds and production functions, assessing the resilience of ecosystem functioning to environmental change, with asynchronous dynamics of species in the same functional guild expected to lead to more stable ecosystem functioning. Testing this method using data for butterflies collected over four decades in the United Kingdom, we find three ecosystem functions (resource provisioning, wildflower pollination, and aesthetic cultural value) appear relatively robust, with functionally important species dispersed across response guilds, suggesting more stable ecosystem functioning. Additionally, by relating genetic distances to response guilds we assess the heritability of responses to environmental change. Our results suggest it may be feasible to infer population responses of butterflies to environmental change based on phylogeny-a useful insight for conservation management of rare species with limited population monitoring data. Our approach holds promise for overcoming the impasse in predicting the responses of ecosystem functions to environmental change. Quantifying co-varying species' responses to multivariate environmental change should enable us to significantly advance our predictions of ecosystem function resilience and enable proactive ecosystem management.