期刊
APPLIED VEGETATION SCIENCE
卷 14, 期 2, 页码 242-255出版社
WILEY
DOI: 10.1111/j.1654-109X.2010.01114.x
关键词
Generalized additive model; Geostatistical methods; Italian peninsula; Random Forest; Regression tree analysis
资金
- Italian Ministry of Environment
- European Union [2152/2003]
- CONECOFOR (CONtrolloECOsistemi FORestali)
Question: What is the effect of climate change on tree species abundance and distribution in the Italian peninsula? Location: Italian peninsula. Methods: Regression tree analysis, Random Forest, generalized additive model and geostatistical methods were compared to identify the best model for quantifying the effect of climate change on tree species distribution and abundance. Future potential species distribution, richness, local colonization, local extinction and species turnover were modelled according to two scenarios (A2 and B1) for 2050 and 2080. Results: Robust Random Forest proved to be the best statistical model to predict the potential distribution of tree species abundance. Climate change could lead to a shift in tree species distribution towards higher altitudes and a reduction of forest cover. Pinus sylvestris and Tilia cordata may be considered at risk of local extinction, while the other species could find potential suitable areas at the cost of a rearrangement of forest community composition and increasing competition. Conclusions: Geographical and topographical regional characteristics can have a noticeable influence on the impact of predicted climate change on forest ecosystems within the Mediterranean basin. It would be highly beneficial to create a standardized and harmonized European forest inventory in order to evaluate, at high resolution, the effect of climate change on forest ecosystems, identify regional differences and develop specific adaptive management strategies and plans.
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