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Temporal fluctuation scaling in populations and communities
Author(s) -
Kalyuzhny Michael,
Schreiber Yishai,
Chocron Rachel,
Flather Curtis H.,
Kadmon Ronen,
Kessler David A.,
Shnerb Nadav M.
Publication year - 2014
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/13-0326.1
Subject(s) - statistical physics , power law , variance (accounting) , population , relative abundance distribution , series (stratigraphy) , term (time) , abundance (ecology) , econometrics , logarithm , ecology , scaling , macroecology , null hypothesis , scale (ratio) , mathematics , null model , statistics , biodiversity , geography , relative species abundance , physics , economics , biology , demography , mathematical analysis , sociology , paleontology , geometry , accounting , quantum mechanics , cartography
Taylor's law, one of the most widely accepted generalizations in ecology, states that the variance of a population abundance time series scales as a power law of its mean. Here we reexamine this law and the empirical evidence presented in support of it. Specifically, we show that the exponent generally depends on the length of the time series, and its value reflects the combined effect of many underlying mechanisms. Moreover, sampling errors alone, when presented on a double logarithmic scale, are sufficient to produce an apparent power law. This raises questions regarding the usefulness of Taylor's law for understanding ecological processes. As an alternative approach, we focus on short‐term fluctuations and derive a generic null model for the variance‐to‐mean ratio in population time series from a demographic model that incorporates the combined effects of demographic and environmental stochasticity. After comparing the predictions of the proposed null model with the fluctuations observed in empirical data sets, we suggest an alternative expression for fluctuation scaling in population time series. Analyzing population fluctuations as we have proposed here may provide new applied (e.g., estimation of species persistence times) and theoretical (e.g., the neutral theory of biodiversity) insights that can be derived from more generally available short‐term monitoring data.