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DOI | 10.1371/journal.pone.0146053 |
Quantifying the Adaptive Cycle | |
Angeler, David G.1,2; Allen, Craig R.3; Garmestani, Ahjond S.4; Gunderson, Lance H.5; Hjerne, Olle1; Winder, Monika1 | |
发表日期 | 2015-12-30 |
ISSN | 1932-6203 |
卷号 | 10期号:12 |
英文摘要 | The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994-2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems. |
语种 | 英语 |
WOS记录号 | WOS:000367510500127 |
来源期刊 | PLOS ONE
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来源机构 | 美国环保署 |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/61387 |
作者单位 | 1.Stockholm Univ, Dept Ecol Evolut & Plant Sci, SE-10691 Stockholm, Sweden; 2.Swedish Univ Agr Sci, Dept Aquat Sci & Assessment, SE-75007 Uppsala, Sweden; 3.Univ Nebraska, US Geol Survey, Nebraska Cooperat Fish & Wildlife Res Unit, Lincoln, NE 68583 USA; 4.US EPA, Natl Risk Management Res Lab, Cincinnati, OH 45268 USA; 5.Emory Univ, Dept Environm Sci, Atlanta, GA 30322 USA |
推荐引用方式 GB/T 7714 | Angeler, David G.,Allen, Craig R.,Garmestani, Ahjond S.,et al. Quantifying the Adaptive Cycle[J]. 美国环保署,2015,10(12). |
APA | Angeler, David G.,Allen, Craig R.,Garmestani, Ahjond S.,Gunderson, Lance H.,Hjerne, Olle,&Winder, Monika.(2015).Quantifying the Adaptive Cycle.PLOS ONE,10(12). |
MLA | Angeler, David G.,et al."Quantifying the Adaptive Cycle".PLOS ONE 10.12(2015). |
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