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Harvard Forest Symposium Abstract 2013

• Title: How important is "colored" stochasticity for plant population dynamics?
• Primary Author: Elizabeth Crone (Tufts University)
• Additional Authors: Aaron Ellison (Harvard University); Anne Jakalaniemi (University of Oulu, Thule Institute, Oulanka Reseach Station); Rui Zhang (Harvard Forest)
• Abstract:

  Environmental stochasticity is an important driver population and evolutionary dynamics. In many cases, stochasticity is also the primary driver of extinction risk and subsequent population viability. Most stochastic population models are based on the assumption of “white”noise, i.e., stochasticity that is uncorrelated through time. However, actual environmental stochasticity is likely to be “colored” (autocorrelated) through time. This project was motivated by a surprising result from metaanalysis of demographic matrix models: Temporal variation in plant population growth rates is characterized by “blue” noise (negative autocorrelations between successive years), in contrast to the typical assumption of white noise in stochastic population models, and also in contrast to theoretical and empirical arguments in favor of “red” (positively autocorrelated) noise in animal populations.
  
  
  
  To better understand this result, we are, first, developing statistical approaches for estimating autocorrelations from short time series with observation error. These analyses are extensions of generalized linear mixed models. Using these tools, we are evaluating three forms of autocorrelation in demographic time series: First, we are testing the prevalence of costs of reproduction in demographic time series, i.e., blue noise due to low survival, growth and/or fecundity following years in which plants produce many seeds. Second, we are evaluating the dynamics of plants in dynamic environments such as banks of meandering riviers, i.e., red noise due to succession and disturbance. To the extent that costs of reproduction are important drivers of other vital rates, we cannot consider variation in demographic parameters of plants, such as growth and carbon fixation, in the absence of reproduction. To the extent that plant population dynamics are driven by rapid environmental changes, we cannot consider plant demography in the absence of environmental drivers. Case studies from this project illustrate situations in which these issues hold, as well as tools for evaluating their general importance in other systems.
  
  
  
  This project also involves training workshops in mixed models for ecologists.
  
  

• Research Category: Biodiversity Studies
  Conservation and Management
  Physiological Ecology, Population Dynamics, and Species Interactions