Czúcz, B. (corresponding author, email@example.com), Csecserits, A. (firstname.lastname@example.org), Botta-Dukát, Z. (email@example.com), Kröel-Dulay, G. (firstname.lastname@example.org), Szabó, R. (email@example.com), Horváth, F. (firstname.lastname@example.org) & Molnár, Z. (email@example.com): Institute of Ecology and Botany of the Hungarian Academy of Sciences, H-2163 Vácrátót, Alkotmány u. 2-4
SPECIAL FEATURE: ECOINFORMATICS
An indicator framework for the climatic adaptive capacity of natural ecosystems
Version of Record online: 28 JAN 2011
© 2011 International Association for Vegetation Science
Journal of Vegetation Science
Special Issue: Special feature: Ecoinformatics and Global Change: Edited by Jürgen Dengler, Jörg Ewald, Ingolf Kühn & Robert K. Peet
Volume 22, Issue 4, pages 711–725, August 2011
How to Cite
Czúcz, B., Csecserits, A., Botta-Dukát, Z., Kröel-Dulay, G., Szabó, R., Horváth, F. and Molnár, Z. (2011), An indicator framework for the climatic adaptive capacity of natural ecosystems. Journal of Vegetation Science, 22: 711–725. doi: 10.1111/j.1654-1103.2011.01251.x
Co-ordinating Editor: Jörg Ewald
- Issue online: 6 JUL 2011
- Version of Record online: 28 JAN 2011
- Received 2 June 2010, Accepted 21 November 2010
- Climate change;
- Climatic refugia;
- Dispersal capacity;
- Landscape ecology;
- Landscape index;
- Old-field regeneration;
- Species distribution models;
- Vulnerability assessment
Questions: Can the climatic adaptive capacity of natural ecosystems be estimated with using landscape indicators based on vegetation or land-cover data? Can species distribution model (SDM) outputs be enhanced using such indicators? What are the data requirements and optimal parameter values of potential indicators?
Location: Indicator framework: unspecified. Case study: Kiskunság, Hungary.
Methods: (1) We define a general framework for handling adaptation in ecological climate change impact assessments based on IPCC definitions. (2) As a part of this general framework, we propose an indicator framework consisting of two specific indicators (landscape connectivity and landscape diversity index) to estimate adaptive capacity of ecosystems to climate change. (3) Using old-field regeneration as a proxy process, we test the proposed indicators, perform sensitivity analysis to optimize them and detect limits of their applicability.
Results: Landscape metrics could provide significant information on regeneration success of old-fields. A combination of large-scale connectivity and local diversity had the highest explanatory power, with connectivity being clearly superior. The tested indicator framework can be applied on the basis of commonly available land-cover data sets. Ecological factors (like dispersal distances) are more important determinants of indicator performance than technical parameters or data resolution, provided minimum data quality is given. The dispersal distance of characteristic species of the Kiskunság forest–steppe region was ∼1 to 8 km during the last one to four decades.
Conclusions: The results convincingly show that relatively simple and tractable metrics can effectively indicate the landscape-specific capacity of ecosystems to adjust to climatic changes. We argue that the use of adaptive capacity indicator frameworks consisting of simple but ecologically meaningful indicators should accompany every policy-oriented SDM study.