Large-scale spatial synchrony in red squirrel populations driven by a bottom-up effect.

Spatial synchrony between populations emerges from endogenous and exogenous processes, such as intra- and interspecific interactions and abiotic factors. Understanding factors contributing to synchronous population dynamics help to better understand what determines abundance of a species. This study focuses on spatial and temporal dynamics in the Eurasian red squirrel (Sciurus vulgaris) using snow-track data from Finland from 29 years.

A Spatio-Temporally Explicit Random Encounter Model for Large-Scale Population Surveys.

Random encounter models can be used to estimate population abundance from indirect data collected by non-invasive sampling methods, such as track counts or camera-trap data. The classical Formozov-Malyshev-Pereleshin (FMP) estimator converts track counts into an estimate of mean population density, assuming that data on the daily movement distances of the animals are available. We utilize generalized linear models with spatio-temporal error structures to extend the FMP estimator into a flexible Bayesian modelling approach that estimates not only total population size, but also spatio-temporal variation in population density.

Disease ecology. Ecological and evolutionary effects of fragmentation on infectious disease dynamics.

Ecological theory predicts that disease incidence increases with increasing density of host networks, yet evolutionary theory suggests that host resistance increases accordingly. To test the combined effects of ecological and evolutionary forces on host-pathogen systems, we analyzed the spatiotemporal dynamics of a plant (Plantago lanceolata)-fungal pathogen (Podosphaera plantaginis)relationship for 12 years in over 4000 host populations. Disease prevalence at the metapopulation level was low, with high annual pathogen extinction rates balanced by frequent (re-)colonizations.