2007
DOI: 10.1007/s10980-007-9077-7
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Spatial sensitivity of species habitat patterns to scenarios of land use change (Switzerland)

Abstract: Long-term societal trends which include decreasing population in structurally poorer regions and changes in agricultural policies have been leading to land abandonment in various regions of Europe. One of the consequences of this development includes spontaneous forest regeneration of formerly open-land habitats with likely significant effects on plant and animal diversity. We assess potential effects of agricultural decline in Switzerland (41,000 km 2) and potential impacts on the spatial distribution of seve… Show more

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Cited by 85 publications
(84 citation statements)
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“…Anthropogenic change of natural habitat is one of the major drivers of biodiversity loss and it has been studied extensively for a large range of taxa (Bolliger et al 2007). The most conspicuous element of habitat loss is the change in vegetation, and intact vegetation cover has been used before as a wilderness indicator (Bryant et al 1997).…”
Section: Wilderness Metricsmentioning
confidence: 99%
“…Anthropogenic change of natural habitat is one of the major drivers of biodiversity loss and it has been studied extensively for a large range of taxa (Bolliger et al 2007). The most conspicuous element of habitat loss is the change in vegetation, and intact vegetation cover has been used before as a wilderness indicator (Bryant et al 1997).…”
Section: Wilderness Metricsmentioning
confidence: 99%
“…At the landscape scale, agricultural land use can have either a positive or a negative effect on biodiversity and associated goods and services (Bolliger et al 2007). Regarding diversity in our study sites, both the landscape and stand scale analyses revealed that Musella was more diverse than Ventina.…”
Section: Wood Pasture Conservation Issuementioning
confidence: 99%
“…In general, different studies have demonstrated the importance of understanding and modelling the land use/cover change, to assess soil erosion and instability [6,7], to estimate carbon emissions from deforestation and forest degradation [8,9], to model water quality and quantity [10][11][12], to predict species habitat [13][14][15] , and on the intensity and size of wildfires [16].…”
Section: Introductionmentioning
confidence: 99%