Körner, K. (corresponding author, Katrin.Koerner@uni-potsdam.de): Leibniz-Centre for Agricultural Landscape Research ZALF Muencheberg, Germany. Treydte, A.C. (firstname.lastname@example.org) & Jeltsch, F. (email@example.com): Potsdam University, Plant Ecology and Conservation Biology, Germany. Burkart, M. (firstname.lastname@example.org): Potsdam University, Botanical Garden, Germany.
Simulating direct and indirect effects of climatic changes on rare perennial plant species in fragmented landscapes
Article first published online: 8 JUN 2010
© 2010 International Association for Vegetation Science
Journal of Vegetation Science
Volume 21, Issue 5, pages 843–856, October 2010
How to Cite
Körner, K., Treydte, A. C., Burkart, M. and Jeltsch, F. (2010), Simulating direct and indirect effects of climatic changes on rare perennial plant species in fragmented landscapes. Journal of Vegetation Science, 21: 843–856. doi: 10.1111/j.1654-1103.2010.01191.x
Co-ordinating Editor: Dr Charles Canham.
- Issue published online: 1 SEP 2010
- Article first published online: 8 JUN 2010
- Received 25 January 2008; Accepted 4 September 2008.
- Climate change effects on extinction risk;
- Dynamic landscape;
- Gentiana pneumonanthe;
- Juncus atratus;
- Markov chain Monte Carlo parameter optimization;
- Plant metapopulation;
- Primula veris;
- Species sphere
Question: How does climate change influence plant species population dynamics, their time to extinction, and proportion of occupied habitats in a fragmented landscape?
Location: Germany and Central European lowland.
Methods: We apply a mechanistic general simulation model to test the response of plant functional types to direct and indirect effects of climate change. Three functional types were chosen to represent a set of well-studied perennial plant species: Juncus atratus, Gentiana pneumonanthe and Primula veris. We link local population dynamics within a heterogeneous, fragmented landscape context. “Species spheres”, i.e. multi-dimensional parameter ranges rather than single parameter realizations, based on field and literature data served as proxy for life stage transition parameters. Four climatic scenarios summarizing different cumulative weather effects on demographic rates and different local disturbance frequencies were run. The model predicts “time to extinction” (TE) and “proportion of occupied habitat” (POH) as regional indicators for species extinction risk.
Results: TE decreased for all species when weather conditions worsened, and even more so when the frequency of local destructive events additionally increased. However, management towards fewer disturbance events could buffer the negative effect of climate to some extent. The magnitude of these responses varied with species type. POH declined with an increase in bad weather as well as with increasing disturbance frequency. The better the climatic conditions, the less severe were disturbances on population performance.
Conclusions: The “species spheres” proved to be a valuable approach for predictive trends. As climate change usually also implies destructive events such as land-use change, flooding or fire, our model on local and regional extinction risks can support conservation issues and management actions.