Marine ecology progress series | |
Quantitative argument for long-term ecological monitoring | |
, Adrienne Lee1  , David Dannecker1  , Gerald M. Pao2  Alfredo Giron-Nava3  , Chase C. James3  , Bethany Kolody3  , Hao Ye3  , Andrew F. Johnson3  , Maitreyi Nagarkar3  , David G. Johns3  | |
[1] Division of Biological Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA;Salk Institute for Biological Studies, 10010 N Torrey Pines Road, La Jolla, CA 92037, USA;Scripps Institution of Oceanography, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA | |
关键词: Long-term monitoring; Predictability; Nonlinearity; Time series; Population dynamics; Ecological data; | |
DOI : 10.3354/meps12149 | |
学科分类:海洋学与技术 | |
来源: Inter-Research | |
【 摘 要 】
Although it seems obvious that with more data, the predictive capacity of ecological models should improve, a way to demonstrate this fundamental result has not been so obvious. In particular, when the standard models themselves are inadequate (von Bertalanffy, extended Ricker etc.) no additional data will improve performance. By using time series from the Sir Alister Hardy Foundation for Ocean Science Continuous Plankton Recorder, we demonstrate that long-term observations reveal both the prevalence of nonlinear processes in species abundances and an improvement in out-of-sample predictability as the number of observations increase. The empirical results presented here quantitatively demonstrate the importance of long-term temporal data collection programs for improving ecosystem models and forecasts, and to better support environmental management actions.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201902186757327ZK.pdf | 254KB | download |