期刊
ECOLOGY LETTERS
卷 13, 期 1, 页码 21-31出版社
WILEY
DOI: 10.1111/j.1461-0248.2009.01393.x
关键词
Autoregressive-moving average; autoregressive model; Global Population Dynamics Database; linear model; non-stationarity; population regulation; return to equilibrium; time-series analysis
类别
资金
- NSF [MSPA-CSE 0434329, DEB 0415670, DEB 0816613]
How strongly natural populations are regulated has a long history of debate in ecology. Here, we discuss concepts of population regulation appropriate for stochastic population dynamics. We then analyse two large collections of data sets with autoregressive-moving average (ARMA) models, using model selection techniques to find best-fitting models. We estimated two metrics of population regulation: the characteristic return rate of populations to stationarity and the variability of the stationary distribution (the long-term distribution of population abundance). Empirically, longer time series were more likely to show weakly regulated population dynamics. For data sets of length >= 20, more than 35% had characteristic return times > 6 years, and more than 29% had stationary distributions whose coefficients of variation were more than two times greater than would be the case if they were maximally regulated. These results suggest that many natural populations are weakly regulated. Ecology Letters (2010) 13: 21-31.
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