Planning for Climate Change: Identifying Minimum-Dispersal Corridors for the Cape Proteaceae

Abstract:  Climate change poses a challenge to the conventional approach to biodiversity conservation, which relies on fixed protected areas, because the changing climate is expected to shift the distribution of suitable areas for many species. Some species will persist only if they can colonize new areas, although in some cases their dispersal abilities may be very limited. To address this problem we devised a quantitative method for identifying multiple corridors of connectivity through shifting habitat suitabilities that seeks to minimize dispersal demands first and then the area of land required. We applied the method to Proteaceae mapped on a 1-minute grid for the western part of the Cape Floristic Region of South Africa, to supplement the existing protected areas, using Worldmap software. Our goal was to represent each species in at least 35 grid cells (approximately 100 km²) at all times between 2000 and 2050 despite climate change. Although it was possible to achieve the goal at reasonable cost, caution will be needed in applying our method to reserves or other conservation investments until there is further information to support or refine the climate-change models and the species' habitat-suitability and dispersal models.     

The Consistency of Extinction Risk Classification Protocols

Abstract:  Systematic protocols that use decision rules or scores are seen to improve consistency and transparency in classifying the conservation status of species. When applying these protocols, assessors are typically required to decide on estimates for attributes that are inherently uncertain. Input data and resulting classifications are usually treated as though they are exact and hence without operator error. We investigated the impact of data interpretation on the consistency of protocols of extinction risk classifications and diagnosed causes of discrepancies when they occurred. We tested three widely used systematic classification protocols employed by the World Conservation Union, NatureServe, and the Florida Fish and Wildlife Conservation Commission. We provided 18 assessors with identical information for 13 different species to infer estimates for each of the required parameters for the three protocols. The threat classification of several of the species varied from low risk to high risk, depending on who did the assessment. This occurred across the three protocols investigated. Assessors tended to agree on their placement of species in the highest (50–70%) and lowest risk categories (20–40%), but there was poor agreement on which species should be placed in the intermediate categories. Furthermore, the correspondence between the three classification methods was unpredictable, with large variation among assessors. These results highlight the importance of peer review and consensus among multiple assessors in species classifications and the need to be cautious with assessments carried out by a single assessor. Greater consistency among assessors requires wide use of training manuals and formal methods for estimating parameters that allow uncertainties to be represented, carried through chains of calculations, and reported transparently.     

Correlations among Extinction Risks Assessed by Different Systems of Threatened Species Categorization

Abstract:  Many different systems are used to assess levels of threat faced by species. Prominent ones are those used by the World Conservation Union, NatureServe, and the Florida Game and Freshwater Fish Commission (now the Florida Fish and Wildlife Conservation Commission). These systems assign taxa a threat ranking by assessing their demographic and ecological characteristics. These threat rankings support the legislative protection of species and guide the placement of conservation programs in order of priority. It is not known, however, whether these assessment systems rank species in a similar order. To resolve this issue, we assessed 55 mainly vertebrate taxa with widely differing life histories under each of these systems and determined the rank correlations among them. Moderate, significant positive correlations were seen among the threat rankings provided by the three systems (correlations 0.58–0.69). Further, the threat rankings for taxa obtained using these systems were significantly correlated to their rankings based on predicted probability of extinction within 100 years as determined by population viability analysis (correlations 0.28–0.37). The different categorization systems, then, yield related but not identical threat rankings, and these rankings are associated with predicted extinction risk.