Understanding farmers' willingness to participate in agricultural payment-for-environmental-services (PES) programmes is an essential precondition for designing effective and efficient programmes. Willingness to participate is typically examined via stated preference surveys using the standard hurdle model for whether and how much to participate. Among respondents who decline to participate, such analyses cannot distinguish between respondents who declined due to the payment level and those who were not interested at all. This paper applies a double hurdle model to incorporate a prior condition for whether a respondent is even willing to consider participating in the PES market. The model uses a unique stated preference survey permitting separation of the consideration and enrolment decisions of 1,700 farmers in Michigan, USA. The first hurdle probit model suggests that farmers' willingness to consider PES chiefly depends on farm and farmer characteristics, while the second hurdle tobit model shows that decisions on whether and how much to enrol depend more on the payment offer and marginal benefit-cost criteria. This study provides fresh insights on facilitating farmer participation in PES programmes using tiered strategies that differ in costs of programme payment and administration.

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Wildlife managers are tasked with identifying and managing stressors that threaten persistence of populations. We demonstrate an approach to land‐use planning that combines scenario modeling and ecological risk assessment to map and quantify risk to population persistence for three rare prairie species in Washington State, USA. Following corroboration of model output, we found that of the management scenarios considered, only a scenario with year‐round restrictions on use of off‐road vehicles, digging, and camping enforced in all potential habitat reduces risk to the species. Decreased risk is focused primarily in two patches of prairie habitat in our study area, indicating stringent restrictions need not be applied broadly. However, one area is not easily accessed by two of the three species considered, suggesting reintroductions to suitable but inaccessible habitat may play an important role in management of these species. Our analyses suggest changes in land use and management that might improve habitat for rare species, with options for minimizing monetary and social costs. Because the proposed approach relies on hypothetical management scenarios and uses a model flexible in data requirements to provide spatially explicit output, it can be used to inform adaptive management of rare species in diverse land‐planning processes and will be especially useful when management decisions must be made under time or cost constraints.

Public agencies worldwide are increasingly adopting an ecosystem service framework to manage lands serving multiple uses. Yet, reliable, practical, and well-tailored methods remain a major limitation in moving from conceptual to actionable approaches. Together with one of the largest federal land managing agencies, we co-develop and co-demonstrate an ecosystem services approach tailored to specific decisions, through a process with potentially widespread relevance. With the U.S. Department of Defense (DoD), we focus on balancing military training with biodiversity and resource conservation under both budgetary and land-use pressures at a representative installation. In an iterative process of co-design and application, we define, map, and quantify multiple ecosystem services under realistic management options. Resource management budget emerges as a major determinant of the degree to which managers can sustain both necessary training environments -a DoD-specific ecosystem service -and a prairie ecosystem with species of conservation concern. We also found clear tradeoffs between training intensity and forest-related services. Our co-developed approach brings otherwise hidden values and tradeoffs to the fore in a balanced way that can help public agencies safeguard priority services under potentially conflicting uses and budget limitations.