QUANTIFYING PERIODIC, STOCHASTIC, AND CATASTROPHIC ENVIRONMENTAL VARIATION

Environmental variation plays a central role in regulating processes at all levels of ecological organization. Environmental data (e.g., temperature, rainfall, stream discharge, water chemistry) are typically easy to collect in large quantity, a requirement for many data-hungry time series tools. Unfortunately, these data are very rarely used effectively in ecology. Here we address this problem by outlining a suite of tools that can be used to quantify periodic, stochastic, and catastrophic variation in environmental conditions. We illustrate the application of these tools using long-term records of average daily discharge in 105 streams and rivers maintained by the U.S. Geological Survey on the NWIS (National Water Information System) web site. Specifically, we apply Fourier analysis to estimate the periodic (seasonal) and stochastic (interannual) components of variation in discharge. We then estimate the temporal autocorrelation structure of stochastic variation (i.e., noise color) in daily flows for ea...

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