Temporal fluctuation scaling in populations and communities

Michael Kalyuzhny, Yishai Schreiber, Rachel Chocron, Curtis H. Flather, Ronen Kadmon, David A. Kessler, Nadav M. Shnerb

Research output: Contribution to journalArticlepeer-review

52 Scopus citations


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.

Original languageEnglish
Pages (from-to)1701-1709
Number of pages9
Issue number6
StatePublished - Jun 2014


  • Birds
  • Demographic noise
  • Environmental stochasticity
  • Population abundance variance
  • Sampling error
  • Taylor's law
  • Temporal variance
  • Trees
  • Variance-mean relations


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