Ecosystem Services as a Common Language for Coastal Ecosystem-Based Management

Abstract:  Ecosystem-based management is logistically and politically challenging because ecosystems are inherently complex and management decisions affect a multitude of groups. Coastal ecosystems, which lie at the interface between marine and terrestrial ecosystems and provide an array of ecosystem services to different groups, aptly illustrate these challenges. Successful ecosystem-based management of coastal ecosystems requires incorporating scientific information and the knowledge and views of interested parties into the decision-making process. Estimating the provision of ecosystem services under alternative management schemes offers a systematic way to incorporate biogeophysical and socioeconomic information and the views of individuals and groups in the policy and management process. Employing ecosystem services as a common language to improve the process of ecosystem-based management presents both benefits and difficulties. Benefits include a transparent method for assessing trade-offs associated with management alternatives, a common set of facts and common currency on which to base negotiations, and improved communication among groups with competing interests or differing worldviews. Yet challenges to this approach remain, including predicting how human interventions will affect ecosystems, how such changes will affect the provision of ecosystem services, and how changes in service provision will affect the welfare of different groups in society. In a case study from Puget Sound, Washington, we illustrate the potential of applying ecosystem services as a common language for ecosystem-based management.     

Importance of Accounting for Detection Heterogeneity When Estimating Abundance: the Case of French Wolves

Abstract: Assessing conservation strategies requires reliable estimates of abundance. Because detecting all individuals is most often impossible in free‐ranging populations, estimation procedures have to account for a <1 detection probability. Capture–recapture methods allow biologists to cope with this issue of detectability. Nevertheless, capture–recapture models for open populations are built on the assumption that all individuals share the same detection probability, although detection heterogeneity among individuals has led to underestimating abundance of closed populations. We developed multievent capture–recapture models for an open population and proposed an associated estimator of population size that both account for individual detection heterogeneity (IDH). We considered a two‐class mixture model with weakly and highly detectable individuals to account for IDH. In a noninvasive capture–recapture study of wolves we based on genotypes identified in feces and hairs, we found a large underestimation of population size (27% on average) occurred when IDH was ignored.