Objective
Patterns observed among twenty first century climate change imply a warmer and wetter climatic environment in the near to mid-term (50-150 years). Changes in climate results in changes in vegetation patterns as plant species shift there respective range. Subsequently, large-scale shifts in vegetation composition in response to climate change will impact upon vegetation dependent ecosystem functioning (structure and dynamics) and in-turn on the ecosystem services on which human societies depend. Understanding therefore how ecosystem functions respond to changing climate is extremely relevant for the development and implementation of successful European policy on climate change mitigation. This project will develop novel hybrid species distribution models (SDM) at national and European scales. The models will circumvent several limitations renowned with SDMs, through incorporating mechanistic simulations of species dispersal and establishment probabilities among a changing climate. Furthermore, these hybrid models will be validated, not by using the same spatial-temporal data but using an independent fine-scale temporal data-set. This unique and independent data originates from experimental field studies investigating impacts of warming and precipitation on Norwegian alpine vegetation. The model parametrization and validation phase of this project will result in a modeling framework that can be used to accurately forecast species range patterns and in-turn evaluate climate change impacts on ecosystems functions at the European-wide scale. .
Fields of science
- natural sciencescomputer and information sciencesdatabases
- humanitieslanguages and literatureliterature studiesliterary genresessays
- natural sciencesbiological sciencesecologyecosystems
- natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes
- natural sciencesearth and related environmental sciencesphysical geography
Programme(s)
Funding Scheme
MSCA-IF-EF-ST - Standard EFCoordinator
8000 Aarhus C
Denmark