Druckansicht der Internetadresse:

Lehrstuhl für Biogeografie

Prof. Dr. Carl Beierkuhnlein

Seite drucken
Jaeschke, A*; Bittner, T; Reineking, B; Beierkuhnlein, C: Model uncertainty in species distribution modelling considering a range of dispersal scenarios
Poster, Jahrestreffen des AK Biogeographie im Verband der Geographen an Deutschen Hochschulen (VGDH), Hamburg: 20.05.2011 - 22.05.2011

Currently, the effects of climate change on the distribution of species are inferred using bioclimatic envelope modelling assuming no or unrestricted dispersal. Although the truth lies between these two extremes both dispersal scenarios provide hints on where current suitable area might be lost and where future suitable area might be found. We hypothesize that the integration of species-specific dispersal distances would help to overcome these constraints. This requires data on dispersal distances and activity periods and therefore a pronounced knowledge on a species’ ecology. Here, we used European records of three Odonata species listed in the Annexes of the EU Habitats Directive, the climate model HadCM3 and the emission scenario A2 to estimate and map potential changes in occurrence up to 2035. We used an ensemble forecasting approach (BIOMOD), applying nine modelling algorithms. We considered observed species-specific dispersal distances based on literature information as well as artificial modelled distance steps (in a 10km raster) between no and unlimited dispersal. The aim is to assess the uncertainty of modelling algorithms in projecting potential suitable area based on observed dispersal distances. Depending on the observed specific dispersal ability and the corresponding specific maximum distance within reach of the species, the future projected change in occurrence differs between the modelling algorithms as well as between the species. Therefore, observed dispersal distances seem to be highly uncertain, reflecting in most cases single observations being not representative for the species’ dispersal ability. However, these observed data represent a valuable data basis and could help to restrict the overestimation of full dispersal scenarios, improving the development of targeted supporting measures for species’ persistence.
TwitterInstagramYoutube-KanalKontakt aufnehmen
Diese Webseite verwendet Cookies. weitere Informationen