Prioritizing sites for conservation based on similarity to historical baselines and feasibility of protection - Traci Popejoy; Charles R. Randklev; Thomas M. Neeson; Caryn C. Vaughn (Conservation Biology, 2018)
The concept of shifting baselines in conservation science implies advocacy for the use of historical knowledge to inform these baselines but does not address the feasibility of restoring sites to those baselines. In many regions, conservation feasibility varies among sites due to differences in resource availability, statutory power, and land‐owner participation. We used zooarchaeological records to identify a historical baseline of the freshwater mussel community's composition before Euro‐American influence at a river‐reach scale (i.e., a kilometer stretch of river that is abiotically similar) in the Leon River of central Texas (U.S.A.). We evaluated how the community reference position and the feasibility of conservation might enable identification of sites where conservation actions would preserve historically representative communities and be likely to succeed. We devised a conceptual model that incorporated community information and landscape factors to link the best conservation areas to potential cost and conservation benefits. Using fuzzy ordination, we identified modern mussel beds that were most like the historical baseline. We then quantified housing density and land use near each river reach identified to estimate feasibility of habitat restoration. Using our conceptual framework, we identified reaches of high conservation value (i.e., contain the best mussel beds) and where restoration actions would be most likely to succeed. Reaches above Lake Belton were most similar in species composition and relative abundance to zooarchaeological sites. A subset of these mussel beds occurred in locations where conservation actions appeared most feasible. Our results show how to use zooarchaeological data (biodiversity data often readily available) and estimates of conservation feasibility to inform conservation priorities at a local spatial scale.