Conservation planning for retention, not just protection

Most protected area (PA) planning aims to improve biota representation within the PA system, but this does not necessarily achieve the best outcomes for biota retention across regions when we also consider habitat loss in areas outside the PA system. Here, we assess the implications that different PA expansion strategies can have on the retention of species habitat across an entire region. Using retention of forest habitat for Colombia's 550 forest-dependent bird species as our outcome variable, we found that when a minimum of 30% of each species' habitat was included in the PA system, a pattern of PA expansion targeting areas at highest deforestation risk (risk-prevention) led to the retention, on average, of 7.2% more forest habitat per species by 2050 than did a pattern that targeted areas at lowest risk (risk-avoidance). The risk-prevention approach cost more per km2 of land conserved, but it was more cost-effective in retaining habitat in the landscape (50%-69% lower cost per km2 of avoided deforestation). To have the same effectiveness preventing habitat loss in Colombia, the risk-avoidance approach would require more than twice as much protected area, costing three times more in the process. Protected area expansion should focus on the contributions of PAs to outcomes not only within PA systems themselves, but across entire regions.

Correction: Batch-produced, GIS-informed range maps for birds based on provenanced, crowd-sourced data inform conservation assessments

[This corrects the article DOI: 10.1371/journal.pone.0259299.].

Integrating habitat-masked range maps with quantifications of prevalence to estimate area of occupancy in IUCN assessments

Estimates of species geographic ranges constitute critical input for biodiversity assessments, including those for the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species. Area of occupancy (AOO) is one metric that IUCN uses to quantify a species' range, but data limitations typically lead to either under- or overestimates (and unnecessarily wide bounds of uncertainty). Fortunately, existing methods in which range maps and land-cover data are used to estimate the area currently holding habitat for a species can be extended to yield an unbiased range of plausible estimates for AOO. Doing so requires estimating the proportion of sites (currently containing habitat) that a species occupies within its range (i.e., prevalence). Multiplying a quantification of habitat area by prevalence yields an estimate of what the species inhabits (i.e., AOO). For species with intense sampling at many sites, presence-absence data sets or occupancy modeling allow calculation of prevalence. For other species, primary biodiversity data (records of a species' presence at a point in space and time) from citizen-science initiatives and research collections of natural history museums and herbaria could be used. In such cases, estimates of sample prevalence should be corrected by dividing by the species' detectability. To estimate detectability from these data sources, extensions of inventory-completeness analyses merit development. With investments to increase the quality and availability of online biodiversity data, consideration of prevalence should lead to tighter and more realistic bounds of AOO for many taxonomic groups and geographic regions. By leading to more realistic and representative characterizations of biodiversity, integrating maps of current habitat with estimates of prevalence should empower conservation practitioners and decision makers and thus guide actions and policy worldwide.