期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2009
卷号：8
DOI：10.1088/1755-1315/8/1/012015
出版社：IOP Publishing
摘要：In this paper we examined the potential impacts of predicted climatic changes on the flora and vegetation in Denmark using data from a digital database on the natural vegetation of Europe. Climate scenarios A2 and B2 were used to find regions with present climatic conditions similar to Denmark's climate in the year 2100. The potential natural vegetation of Denmark today is predominantly deciduous forest that would cover more than 90% of the landscape. Swamps, bogs, and wet forest would be found under moist or wet conditions. Dwarf shrub heaths would be naturally occurring on poor soils along the coast together with dune systems and salt-marsh vegetation. When comparing the natural vegetation of Denmark to the vegetation of five future-climate analogue areas, the most obvious trend is a shift from deciduous to thermophilous broadleaved forest currently found in Southern and Eastern Europe. A total of 983 taxa were recorded for this study of which 539 were found in Denmark. The Sørensen index was used to measure the floristic similarity between Denmark and the five subregions. Deciduous forest, dwarf shrub heath, and coastal vegetation were treated in more detail, focusing on potential new immigrant species to Denmark. Finally, implications for management were discussed. The floristic similarity between Denmark and regions in Europe with a climate similar to what is expected for Denmark in year 2100 was found to vary between 48–78%, decreasing from North to South. Hence, it seems inevitable that climate changes of the magnitudes foreseen will alter the distribution of individual species and the composition of natural vegetation units. Changes, however, will not be immediate. Historic evidence shows a considerable lag in response to climatic change under natural conditions, but little is known about the effects of human land-use and pollution on this process. Facing such uncertainties we suggested that a dynamic strategy based on modeling, monitoring and adaptive management is adopted. Modeling techniques can be constantly improved, but will never be perfect and should therefore be linked to a fine-masked network of observatories to check model predictions and feed empirical data back into the models for calibration and further development.
