Populations in seasonal environments



Most populations are in environments that change significantly throughout the year. How does this variation drive the variation we see in populations?
A painting in a
                            buddhist temple illustrating the four
                            seasons
A painting of the four seasons by Kanō Eitoku and his father Kanō Shōei
My work is looking at trying to assess the importance of within year environmental fluctuations on population abundances. The difficulty in this is trying to match the coarse observations we have of populations at the yearly timescale with high-resolution environmental data that can be obtained at the daily, or even hourly timescale.


 





Stochastic population dynamics



Populations are always subjected to random fluctuations in their environment. Can we learn about those environments from the patterns induced in the population time series?

For my PhD work with Jose Ponciano we looked at how single species models can account for complex environments using stochastic models. We built models that account for the probabilistic effects of interactions with other species and environmental factors. This approach is important for understanding how to model the impacts of complex ecosystems when you only have data on a single species within that system.






We used a wonderful experimental dataset courtesy of James Grover to test how well single species models can predict extinction events. We found that interactions between species can induce important changes in the variation of populations through time but that the probabilistic properties of these changes can be accounted for and they can improve predictions when using single-species time series.

Population abundances of Daphnia
                              Pulicaria
Time series of data from Ferguson et al., 2014





In another project we looked at how fluctuating environments interact with population model parameters to drive the variation we see in animal populations. We looked at how this variability could influence the population, either modifying the number of individuals that are born each year, or the number maximum population size. Populations that are primarily affected by variability in their maximum population size tend to be more stable.
Alpine Ibex
photo by Frederik Vandaele under the CCA 2.0 license
Alpine ibex are an example of a population that appears to have a maximum population size that is  significantly affected by the environment. Other studies have identified winter snow levels as the environmental factor driving much of this variation.