Temporal environmental fluctuations exert strong controls on biodiversity. Regular, predictable environmental oscillations should promote coexistence of a great number of species over a given timeframe, through temporal niche diversification. More recently, seasonality has been invoked to explain general phenomena such as species coexistence, latitudinal diversity gradients, and migratory dynamics of birds. A common theme among these studies is that species diversity and community turnover is determined by a balance between temporal environmental variability (seasonality) and the reliability of this variability (predictability). Drawing on tools from wavelet analysis and information theory, we provide a framework for understanding how the seasonality and predictability of an environment interact to shape local biodiversity. We use this framework to generate predictions about temporal biodiversity using examples from regions spanning a rainfall seasonality gradient. Seasonal differences in rainfall can exert a strong physical control on the environment in stream systems. Thus, using datasets from Mediterranean-climate California, Sonoran Desert Arizona and New Zealand, we illustrate these concepts with stream invertebrate community dynamics.
Results/Conclusions
Wavelet analysis enabled the differentiation of dominant weather cycles between the three regions through both the strength of annual wavelet power spectrum and regularity of significant annual cycles. Through ordinations of invertebrate communities, we found that community fluctuation ranged from strongly oscillatory in highly-seasonal Mediterranean streams to random fluctuations in aseasonal New Zealand streams. These patterns were reflected in temporal beta-diversity metrics, with considerably higher temporal turnover, but not nestedness in more seasonal streams. Our framework and demonstrated case study have implications for both basic science and management of ecosystems spanning gradients of climatic variability. These include the importance of timing of sampling; the effects of changes to natural seasonality regimes on biota; and the utility of the quantitative metrics employed for detecting climate change trends on biodiversity.