AKÇAKAYA LAB
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Population Dynamics


​We are interested in developing new methods for modeling population dynamics, estimating model parameters, analyzing population declines, and validating extinction risk estimates. Research in this areas has involved
  • A new approach to develop fully specified population models (complete with stage structure, stochasticity, and density dependence) from mark-recapture data (the method, including the source code, the data we analyzed, and sample results for one species, can be freely downloaded via github.com/Akcakaya/MAPS-to-Models);
  • A new method of global sensitivity analysis;
  • Linking models at different scales to develop "metamodels" for simulating complex dynamics of species interactions, diseases, and dispersal beavior (ongoing Research Collaboration Network project supported by NSF);
  • Estimating variability in survival rates and fecundities due to environmental fluctuations, by removing variance due to demographic stochastricity from total observed variance;
  • Showing that the theta-logistic model (used to describe how the growth rate of a population slows as abundance increases) is unreliable for modeling most census data;
  • Establishing that scalar population models (also known as count-based models) overestimate variability and risks of decline and extinction;
  • Demonstrating that the reddened spectra commonly seen in time series of population abundances can be due to measurement error and/or moderate density dependence;
  • Determining the predictive accuracy of the probabilistic predictions of population viability analysis, with a retrospective analysis;
  • Cataloging common mistakes in population modeling and suggesting ways to avoid them.
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