Ecological networks, a challenge for territorial planning - the case of Region Abruzzo, Italy

被引:0
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作者
van der Sluis, T
Pedroli, B
Baveco, H
Corridore, G
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Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
This paper presents the result of an analysis of the ecological network for Regione Abruzzo (central Italy). The aim of this analysis is (1) to identify the functional ecological network at present, and (2) to identify opportunities to optimise the ecological network. The landscape-ecological model LARCH was used to analyse habitat distribution in relation to wildlife populations, and sustainability of these populations. In addition, also the model METAPHOR was used, to assess viability of the population of Brown Bear (Ursus arctos) for Regione Abruzzo, and the movement model SmallSteps, to obtain an estimate of patch-based landscape connectivity for this species. For the LARCH analysis four ecosystem types were selected, which cover the most important natural habitat types in the study area: woodland, wetland, grassland, scrubland-and steppe. To assess whether these-ecosystem types might function for specific wildlife species, seven species were selected which can be considered representative for these ecosystems. For these species it was assessed whether the ecosystem still functions as an ecological network. As an example the results for one species, the hedgehog (Erinaceus europaeus), are presented. It is shown that there is still ample habitat to support larger wildlife populations in this part of Italy. A preview is made of-potential next steps. Similar projects, in preparation or done elsewhere in Italy (Regio ne Emilia-Romagna, Umbria, and Sicily), call now for the design of a comprehensive ecological network for the whole of Italy, with the Apennines as the backbone for this network. This network should be consolidated as soon as possible, with all required legal actions and protection. Finally what the next step should be for the development of an ecological network for all of Italy is explored.
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页码:69 / 79
页数:11
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