Even though our societies rely on ecosystem functions such as basic production and carbon sequestration, we lack a comprehensive understanding of the relative roles of the direct effects of global change on ecosystem functions contrasted with effects mediated by biodiversity changes. Additionally, more research is needed on how such changes vary in space and time as well as between different ecosystems.
Associate Professor Vanhatalo’s new ERC funded project “Predictive Understanding of the effects of Global Change on Ecological Communities and Ecosystem Functions” uses statistical and mathematical methods to address the critical need to reconcile the existing theoretical and experimental understanding with findings from large-scale observational data from various ecosystems.
Specifically, the project aims to develop statistical and mathematical models to describe the distribution of species and ecosystem functions in space and time, and to develop a computational toolbox for assessing such models. The methods and models will then be applied in the analysis of long-term observational datasets to help further our knowledge of the processes that influence the distribution of ecosystem functions and biodiversity.
Such predictive tools that estimate changes in biodiversity and ecosystem functions in a spatiotemporally explicit fashion are crucial for instance in the implementation of environmental accounting as a method of biodiversity preservation.
Associate Professor Jarno Vanhatalo is a statistician specialised in the development of Bayes methods as well as computational solutions for the analysis of long-term datasets. He is the head of the Environmental and Ecological Statistics group and the Deputy Director of the Research Centre for Ecological Change, a research consortium that studies how global change affects ecosystems. Associate Professor Vanhatalo and his research team have made significant contributions to joint species distribution models and ecological risk assessment methods. Furthermore, they have thoroughly quantified uncertainties in ecological understanding as well as the impact of such uncertainties on spatiotemporally explicit risk management of Arctic oil transportation.