Temporal fluctuation scaling in populations and communities

Authors

Michael Kalyuzhny, Hebrew University of Jerusalem
Yishai Schreiber, Bar-Ilan University
Rachel Chocron, Hebrew University of Jerusalem
Curtis H. Flather, USDA Forest Service
Ronen Kadmon, Hebrew University of Jerusalem
David A. Kessler, Bar-Ilan University
Nadav M. Shnerb, USDA Forest ServiceFollow

ORCID IDs

nadav.shnerb@gmail.com

Document Type

Article

Date of this Version

2014

Citation

Ecology, 95(6), 2014, pp. 1701–1709.

Comments

U.S. government work.

Abstract

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.