整合社区再调查数据以推进全球变化研究。
Combining community resurvey data to advance global change research.
作者信息
Verheyen Kris, De Frenne Pieter, Baeten Lander, Waller Donald M, Hédl Radim, Perring Michael P, Blondeel Haben, Brunet Jörg, Chudomelova Markéeta, Decocq Guillaume, De Lombaerde Emiel, Depauw Leen, Dirnböck Thomas, Durak Tomasz, Eriksson Ove, Gilliam Frank S, Heinken Thilo, Heinrichs Steffi, Hermy Martin, Jaroszewicz Bogdan, Jenkins Michael A, Johnson Sarah E, Kirby Keith J, Kopecký Martin, Landuyt Dries, Lenoir Jonathan, Li Daijiang, Macek Martin, Maes Sybryn, Máliš Frantisek, Mitchell Fraser J G, Naaf Tobias, Peterken George, Petřík Petr, Reczyńska Kamila, Rogers David A, Schei Fride Hoistad, Schmidt Wolfgang, Standovár Tibor, Świerkosz Krzystof, Ujházy Karol, Van Calster Hans, Vellend Mark, Vild Ondřej, Woods Kerry, Wulf Monika, Bernhard-Römermann Markus
机构信息
Forest & Nature Lab, Department of Forest & Water Management, Ghent University, Geraardsbergsesteenweg 267, 9090 Melle-Gontrode, Belgium.
Forest & Nature Lab, Department of Forest & Water Management, Ghent University, Geraardsbergsesteenweg 267, 9090 Melle-Gontrode, Belgium,
出版信息
Bioscience. 2016 Dec 21;67(1):73-83. doi: 10.1093/biosci/biw150.
More and more ecologists have started to resurvey communities sampled in earlier decades to determine long-term shifts in community composition and infer the likely drivers of the ecological changes observed. However, to assess the relative importance of, and interactions among, multiple drivers joint analyses of resurvey data from many regions spanning large environmental gradients are needed. In this paper we illustrate how combining resurvey data from multiple regions can increase the likelihood of driver-orthogonality within the design and show that repeatedly surveying across multiple regions provides higher representativeness and comprehensiveness, allowing us to answer more completely a broader range of questions. We provide general guidelines to aid implementation of multi-region resurvey databases. In so doing, we aim to encourage resurvey database development across other community types and biomes to advance global environmental change research.
越来越多的生态学家开始重新调查几十年前采样的群落，以确定群落组成的长期变化，并推断观察到的生态变化的可能驱动因素。然而，为了评估多个驱动因素的相对重要性及其之间的相互作用，需要对来自跨越大型环境梯度的许多地区的重新调查数据进行联合分析。在本文中，我们说明了如何在设计中结合来自多个地区的重新调查数据来提高驱动因素正交性的可能性，并表明在多个地区反复进行调查可提供更高的代表性和全面性，使我们能够更全面地回答更广泛的问题。我们提供了一般指南，以帮助实施多地区重新调查数据库。通过这样做，我们旨在鼓励针对其他群落类型和生物群落开展重新调查数据库的开发，以推动全球环境变化研究。
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