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Finding regulation among seemingly unregulated populations: a practical framework for analyzing multivariate population time series for their interactions

文献类型: 外文期刊

作者: Zhou, Can 1 ; Fujiwara, Masami 1 ; Grant, William E. 1 ;

作者机构: 1.Texas A&M Univ, Dept Wildlife & Fisheries Sci, College Stn, TX 77840 USA

2.Chinese Acad Fishery Sci, East China Sea Fisheries Res Inst, Shanghai 200090, Peoples R China

关键词: Co-integration tests;Species interactions;Time series analysis;Top down and bottom up;Unit root process

期刊名称:ENVIRONMENTAL AND ECOLOGICAL STATISTICS ( 影响因子:1.119; 五年影响因子:1.304 )

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收录情况: SCI

摘要: The structure of ecological communities is often thought to be strongly influenced by population interactions. The interactions are often labeled as bottom-up and top-down control. Previous approaches to identify these processes often assume each population in the community is itself regulated. Therefore, each time series follows a stationary process. However, complex community structure and a lack of regulation in an individual population can result in inappropriate inferences based on traditional statistical approaches. Here, we introduce a statistical framework to analyze potentially non-stationary time series that are collectively regulated. We demonstrate the method with catch-per-unit-effort time series data of selected populations in the Gulf of Mexico. In the Gulf, we found that most of the time series data, which span 26 years, were non-stationary, thus individually unregulated. Species interaction patterns were location-dependent, but where brown shrimp interacted significantly with other species, we identified significant bottom-up forcing. On the other hand, we find almost no evidence of top-down forcing throughout the study areas.

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