Subgroup Contributed Talks

Meike Wittmann

Bielefeld University

"A new maximum-likelihood method to infer factors influencing establishment success of introduced species"

One of the most important goals in conservation biology and in the biology of introduced and invasive species is to understand why some small populations persist while others go extinct. Several factors play a potentially important role: 1) demographic and environmental stochasticity, 2) Allee effects, i.e. a reduction in the per-capita growth rate in small populations, for example due to mate-finding difficulties, and 3) propagule size, i.e. the initial number of individuals. It is known that both Allee effects and environmental stochasticity affect the relationship between propagule size and persistence probability in specific ways. Here I propose a new approach for the joint inference of the contributions of these two factors. The approach is based on a Markov chain model for population size with environmental stochasticity and Allee effects. The models without Allee effects or without environmental stochasticity are special cases of the general model. Given a data set for the persistence or extinction of populations of various sizes, the model parameters are estimated using a maximum-likelihood approach and then model choice is performed based on Akaike's information criterion. Using simulation studies, I explore the strengths and weaknesses of this approach. Finally, I apply the approach to published data sets on experimental introductions in the field or laboratory.

Candy Abboud

University of Glasgow

"Dating, localizing and predicting invasive-pathogen dynamics"

Prediction of invasive-pathogen dynamics is an essential step towards the assessment of eradication and containment strategies. Such predictions are performed using surveillance data and models grounded on partial differential equations (PDE), which form a framework often exploited to design invasion models. The framework allows the construction of phenomenological but concise models relying on mechanistic hypotheses. However, this may lead to models with overly rigid behaviour, in particular for describing phenomena in population biology. Hence, to avoid drawing a prediction relying on a single PDE-based model that would be prone to errors because of potential data-model mismatch, we propose to apply Bayesian model-averaging (BMA) for handling parameter and model uncertainties. Hence, we combine several competing spatio-temporal models of propagation for inferring parameters and drawing a consensual prediction of certain quantities of interest. This study is applied (i) to date and localize the invasion of Xylella fastidiosa, bacterium detected in Southern Corsica in 2015, France using post-introduction data, and (ii) to predict its future extent.

Bo Zhang

Oklahoma State University

"Species competition in heterogeneous environments with directed movement"

Understanding the mechanisms that promote species coexistence is a central topic in ecology. Predicting coexistence in heterogeneous environments where populations are linked by dispersal is a challenge that has attracted attention of ecologists. A particular body of theory, based on Lotka-Volterra-like equations, has focused on the effects of different relative dispersal rates in the absence of other differences in competing species, and has predicted that the slower disperser always outcompetes the faster one in environments where the limiting resources are heterogeneously distributed. However, this theory has never been rigorously tested empirically, and has generally only considered random diffusion. Here, we extended previous theory to include exploitable resources and an additional component of directed movement, proving qualitatively novel results, which we tested experimentally using laboratory populations of C. elegans. We revealed, both theoretically and emperically, that stable coexistence can occur when two competing species have identical directed components but different diffusive components to their movement. Our results advance understanding of coexistence theory and has important ecological implications, such as the essential of individuals obtaining clues of neighboring environments, to determine where to disperse in changing environments.