Spatiotemporal patterns in distribution and abundance are a fundamental theme in ecology and applied fields such as biodiversity monitoring and conservation. However, two common problems are (i) limited spatial or temporal extent and (ii) interpretational challenges due to the complex observation process underlying most ecological field data. This may jeopardise inferences about distribution and population dynamics unless the main features of the observation process are well understood, so that their biasing effects can be removed.
The aim of this project is to develop an analytical framework for combining disparate data sets for large-scale spatiotemporal modelling of distribution and abundance which explicitly addresses all aspects of the observation process. We use data on avian distribution and abundance produced by four large and disparate surveys in Switzerland. With the help of Bayesian hierarchical models, we envision ‘reconstructing’ the spatial dynamics of distribution and abundance for up to 180 Swiss breeding bird species over 25+ years in a landscape demography approach.
Based on the foundation of our new analytical framework, in a follow-up study we plan to tackle important ecological and management problems, including demographic causes of population changes in the face of habitat and climate change, demographic community patterns and further topics on optimal monitoring. Our novel approach of merging disparate data sets in time or in space, and the rigorous accommodation of the observation processes in each data source, could lead the way to a much greater generality in population ecological studies and greatly refined inferences about distribution and abundance in biodiversity monitoring.
In collaboration with: