Abstract
Summary Environmental impact assessments are important tools for predicting the consequences of development and changes in land use. These assessments generally use a small subset of total biodiversity – typically rare and threatened species and habitats – as indicators of ecological status. However, these indicators do not necessarily reflect changes in the many more widespread (but increasingly threatened) species, which are important for ecosystem functions. In addition, assessment of threatened species through field surveys is time‐consuming and expensive and, therefore, only possible at small spatial scales. In contrast, planning changes in land use over large spatial scales (e.g. national infrastructure projects) require assessment and prioritization of biodiversity over large spatial extents. Here, we provide a method for the assessment of biodiversity, which takes account of species diversity across larger spatial scales, based on occurrence records from 5553 species across 11 taxonomic groups. We compare the efficacy of the biodiversity‐based indicator we developed against one based on threatened species only and then use it to consider spatial and temporal patterns in ecological status across Great Britain. Finally, we develop a case study to investigate biodiversity status in regions proposed for shale gas extraction in Great Britain. Our results show a strong relationship between the ecological status of areas defined by all biodiversity versus only threatened species, although they also demonstrate that significant exceptions do exist where threatened species do not always accurately indicate the ecological status of wider biodiversity. Spatial and temporal analyses show large variation in ecological status across Great Britain both within the area made available for shale gas licensing and within individual environmental zones. In total, however, 63% of hectads across Britain have suffered a net reduction in our biodiversity‐based indicator since 1970. Synthesis and applications. We provide a method and develop a biodiversity‐based indicator for the assessment and prioritization of biodiversity at large spatial scales. We highlight the potential applications of this approach for the prioritization of areas that would benefit from conservation and restoration. We also emphasize the danger of insufficient consideration of more widespread species and not just rare and threatened species and habitats as indicators of ecological status when prioritizing large‐scale national infrastructure projects. Our method should be a useful tool to complement existing environmental impact assessment methods.
Highlights
The quantification and prioritization of biodiversity is a major challenge for conservation biologists and policymakers (Balmford et al 2005)
Environmental impact assessments are important tools for predicting the consequences of development and changes in land use. These assessments generally use a small subset of total biodiversity – typically rare and threatened species and habitats – as indicators of ecological status
These indicators do not necessarily reflect changes in the many more widespread species, which are important for ecosystem functions
Summary
The quantification and prioritization of biodiversity is a major challenge for conservation biologists and policymakers (Balmford et al 2005). In Great Britain (GB), environmental impact assessments (EIAs) and strategic environmental assessments (SEAs) are currently used to predict the environmental consequences of changes in land use on potential development sites (Slootweg & Kolhoff 2003; Kolhoff et al 2009). Major shortfalls of these assessments include the low priority given to biodiversity generally, and the focus on a small subset of priority species and habitats (Treweek 2001; Rajvanshi, Mathur & Slootweg 2009). Beyond the small subset of legally protected species, many previously widespread species are in decline; reporting on their status is important (Burns et al 2013), especially as these common species may underpin crucial ecosystem functions (Winfree et al 2015)
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