title: Predicted rarity-weighted richness, a new tool to prioritize sites for species representation.
abstract: Lack of biodiversity data is a major impediment to prioritizing sites for species representation. Because comprehensive species data are not available in any planning area, planners often use surrogates (such as vegetation communities, or mapped occurrences of a well-inventoried taxon) to prioritize sites. We propose and demonstrate the effectiveness of predicted rarity-weighted richness (PRWR) as a surrogate in situations where species inventories may be available for a portion of the planning area. Use of PRWR as a surrogate involves several steps. First, rarity-weighted richness (RWR) is calculated from species inventories for aq% subset of sites. Then random forest models are used to model RWR as a function of freely available environmental variables for thatq% subset. This function is then used to calculate PRWR for all sites (including those for which no species inventories are available), and PRWR is used to prioritize all sites. We tested PRWR on plant and bird datasets, using the species accumulation index to measure efficiency of PRWR. Sites with the highest PRWR represented species with median efficiency of 56% (range 32%-77% across six datasets) whenq= 20%, and with median efficiency of 39% (range 20%-63%) whenq= 10%. An efficiency of 56% means that selecting sites in order of PRWR rank was 56% as effective as having full knowledge of species distributions in PRWR's ability to improve on the number of species represented in the same number of randomly selected sites. Our results suggest that PRWR may be able to help prioritize sites to represent species if a planner has species inventories for 10%-20% of the sites in the planning area.
authors.affiliation: Science and Mathematics Faculty College of Integrative Letters and Sciences Arizona State University Mesa AZ USA.
authors.forename: Fábio
authors.initials: F
authors.lastname: Albuquerque
authors.affiliation: School of Forestry Northern Arizona University Flagstaff AZ USA.
authors.forename: Paul
authors.initials: P
authors.lastname: Beier
keywords: conservation planning; prioritization; random forest; species representation; surrogacy