Abstract

To halt habitat loss, landscape planning and conservation management could benefit from a regional analysis of the spatially differing impacts caused by landscape changes. These impacts usually also differ according to the specific vulnerability of the affected biotopes, i.e., the characteristic assemblage of plants and animals on a particular site.A vulnerability map of biotopes will determine those with a high potential to be adversely affected and a low capacity to recover. The identification of vulnerability hot spots will provide guidance for potential protection and maintenance interventions.Following the interdisciplinary vulnerability concept, the analysis on a regional level (≈30,000 km2) was structured into biotope exposure, biotope sensitivity, and biotope adaptive capacity. It involved patch and group metrics to describe the vulnerability of terrestrial, (semi-) natural biotopes to landscape change.For the 32 biotope groups that were distinguished within this study, a relative ranking of vulnerability level is provided. At the level of biotope patches, spatial clusters and thematic clusters were identified. The biotopes dependent on high water availability, such as wet meadow, riparian habitat, and peatland were found to be particularly vulnerable. Moreover, herbaceous perennials, shrubland, groves, orchard meadows, and several pristine forest types also scored high, while the majority of forest biotope patches were less vulnerable to landscape change.The biotope vulnerability index applied on a regional scale provided a sound overview for conservation planning. Only a few biotope groups showed a homogenous vulnerability level across their associated patches, suggesting that management based on local contexts is needed for the majority of biotopes.

Highlights

  • The planetary boundary of biosphere integrity has clearly been exceeded (Rockstro€m et al, 2009; Steffen et al, 2015), and most international strategies to halt biodiversity losses have been far from successful (CBD, 2014)

  • Among all the biotope patches in Brandenburg, those not referring to terrestrial, natural biotope groups were excluded from the index calculation and the index was based on 362,217 patches

  • The patch-wise scores are displayed on a categorical scale of 5 levels according to the statistical distribution of the scores, which underlines their relative meaning. This means that each of the five vulnerability levels accounts for the same number of patches, a first glance at the vulnerability map may suggest otherwise, as the blue area dominates, indicating the patches with low vulnerability. This is due to the size effect, as larger biotope patches, generally speaking, have been less exposed to fragmentation, are less sensitive to landscape changes and, to a lesser extent, have a higher chance to have similar neighbouring biotopes for population exchange

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Summary

Introduction

The planetary boundary of biosphere integrity has clearly been exceeded (Rockstro€m et al, 2009; Steffen et al, 2015), and most international strategies to halt biodiversity losses have been far from successful (CBD, 2014). Habitat loss and fragmentation due to landscape change are generally considered to be the main drivers of the extinction of terrestrial species (Collinge, 2001), fragmentation per se has been overestimated as a biodiversity threat (Tscharntke et al, 2012). In already highly transformed landscapes, nature conservation managers seek to judge threats to the remaining natural and semi-natural areas and could benefit from an objective prioritization of vulnerable sites. Weißhuhn / Global Ecology and Conservation 20 (2019) e00771 vulnerability analysis of the concerned biotopes would tell which sites have the most need for protection or maintenance. The term biotope is almost synonymous with the more common term habitat. It emphasises that the biocoenosis is in the focus instead of a population. Plant species communities supplemented with some typical animal species are the major feature to distinguish biotope types from each other

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