globalchange  > 气候减缓与适应
DOI: 10.1111/ele.12876
Scopus记录号: 2-s2.0-85037976226
论文题名:
Probing the limits of predictability: data assimilation of chaotic dynamics in complex food webs
作者: Massoud E.C.; Huisman J.; Benincà E.; Dietze M.C.; Bouten W.; Vrugt J.A.
刊名: Ecology Letters
ISSN: 1461023X
EISSN: 1461-0248
出版年: 2018
卷: 21, 期:1
起始页码: 93
结束页码: 103
语种: 英语
英文关键词: Data assimilation ; ecological models ; ecosystems ; food webs ; forecast horizons ; plankton ; predator-prey
英文摘要: The daunting complexity of ecosystems has led ecologists to use mathematical modelling to gain understanding of ecological relationships, processes and dynamics. In pursuit of mathematical tractability, these models use simplified descriptions of key patterns, processes and relationships observed in nature. In contrast, ecological data are often complex, scale-dependent, space-time correlated, and governed by nonlinear relations between organisms and their environment. This disparity in complexity between ecosystem models and data has created a large gap in ecology between model and data-driven approaches. Here, we explore data assimilation (DA) with the Ensemble Kalman filter to fuse a two-predator-two-prey model with abundance data from a 2600+ day experiment of a plankton community. We analyse how frequently we must assimilate measured abundances to predict accurately population dynamics, and benchmark our population model's forecast horizon against a simple null model. Results demonstrate that DA enhances the predictability and forecast horizon of complex community dynamics. © 2017 John Wiley & Sons Ltd/CNRS
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/107527
Appears in Collections:气候减缓与适应

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作者单位: Department of Civil and Environmental Engineering, University of California Irvine, Irvine, CA, United States; Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, Netherlands; Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands; Department of Earth and Environment, Boston University, Boston, MA, United States; Institute for Advanced Study, University of Amsterdam, Amsterdam, Netherlands; Department of Earth System Science, University of California Irvine, Irvine, CA, United States

Recommended Citation:
Massoud E.C.,Huisman J.,Benincà E.,et al. Probing the limits of predictability: data assimilation of chaotic dynamics in complex food webs[J]. Ecology Letters,2018-01-01,21(1)
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