Quantitative argument for long-term ecological monitoring

Alfredo Giron-Nava, Chase C. James, Andrew F. Johnson, David Dannecker, Bethany Kolody, Adrienne Lee, Maitreyi Nagarkar, Gerald M. Pao, Hao Ye, David G. Johns, George Sugihara

Research output: Contribution to journalArticle

21 Citations (Scopus)
3 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)269-274
Number of pages6
JournalMarine Ecology Progress Series
Volume572
Early online date31 May 2017
DOIs
Publication statusPublished - 2017

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