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Robyn S. Wilson

Publications and source records attributed to Robyn S. Wilson.

4 recordsLinked to original sources

Advancing outreach effectiveness to improve conservation practice adoption

Agricultural conservation practices are central to achieving Chesapeake Bay watershed restoration goals, yet long-term adoption remains challenging even when practices are technically effective and financial assistance is available. Adoption is not a single decision, but a staged and context-dependent process. Awareness and willingness to commitment, implementation, and persistence, are all important. Progress along this pathway is influenced by interacting factors such as knowledge, attitudes, beliefs, social norms, trust, perceived risk, farm characteristics, and practical constraints. Improving adoption requires outreach strategies that respond to the specific factors limiting progress at each stage rather than relying on a one-size-fits-all approach.

Chesapeake Bay watershed↗

Hurdles to developing quantitative decision support for Endangered Species Act resource allocation

The U.S. Fish and Wildlife Service oversees the recovery of many species protected by the U.S. Endangered Species Act (ESA). Recent research suggests that a structured approach to allocating conservation resources could increase recovery outcomes for ESA listed species. Quantitative approaches to decision support can efficiently allocate limited financial resources and maximize desired outcomes. Yet, developing quantitative decision support under real-world constraints is challenging. Approaches that pair research teams and end-users are generally the most effective. However, co-development requires overcoming “hurdles” that can arise because of differences in the mental models of the co-development team. These include perceptions that: (1) scarce funds should be spent on action, not decision support; (2) quantitative approaches are only useful for simple decisions; (3) quantitative tools are inflexible and prescriptive black boxes; (4) available data are not good enough to support decisions; and (5) prioritization means admitting defeat. Here, we describe how we addressed these misperceptions during the development of a prototype resource allocation decision support tool for understanding trade-offs in U.S. endangered species recovery. We describe how acknowledging these hurdles and identifying solutions enabled us to progress with development. We believe that our experience can assist other applications of developing quantitative decision support for resource allocation.

Frontiers in Conservation Science↗

Endangered species recovery: A resource allocation problem

Many nations have laws to identify and protect imperiled species and their ecosystems. In the United States, actions taken under the Endangered Species Act (ESA) have prevented many extinctions, but few listed species have recovered to the point where they can have the ESA protections removed ( 1 , 2 ). One reason for this [among many ( 3 )] is a shortfall in funding, raising a conundrum for agencies responsible for species recovery: Should resources be allocated toward species facing imminent extinction or species whose long-term survival can most benefit from investment? Some argue that the latter strategy is ethically unsound because it may abandon species with little hope of long-term recovery [for example, ( 4 )], even when science suggests that the former strategy may miss opportunities to prevent species from ever experiencing the risk of imminent extinction ( 2 ). We suggest that framing recovery prioritization as a resource allocation problem provides a structure to facilitate constructive debate about such important questions. We discuss here the merits of an explicit resource allocation framework and introduce a prototype decision tool [( 5 ); see supplementary materials for details] that we developed with the U.S. Fish and Wildlife Service (USFWS) to facilitate transparent and efficient recovery allocation decisions.

Science↗

A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers’ actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.

Conservation Biology↗