Context Urban-rural gradients are useful tools when examining the influence of human disturbances on ecological, social and coupled systems, yet the most commonly used gradient definitions are based on single broad measures such as housing density or percent forest cover that fail to capture landscape patterns important for conservation. Objectives We present an approach to defining urban–rural gradients that integrates multiple landscape pattern metrics related to ecosystem processes important for natural resources and wildlife sustainability. Methods We develop a set of land cover composition and configuration metrics and then use them as inputs to a cluster analysis process that, in addition to grouping towns with similar attributes, identifies exemplar towns for each group. We compare the outcome of the cluster-based urban-rural gradient typology to outcomes for four commonly-used rule-based typologies and discuss implications for resource management and conservation. Results The resulting cluster-based typology defines five town types (urban, suburban, exurban, rural, and agricultural) and notably identifies a bifurcation along the gradient distinguishing among rural forested and agricultural towns. Landscape patterns (e.g., core and islet forests) influence where individual towns fall along the gradient. Designations of town type differ substantially among the five different typologies, particularly along the middle of the gradient. Conclusions Understanding where a town occurs along the urban-rural gradient could aid local decision-makers in prioritizing and balancing between development and conservation scenarios. Variations in outcomes among the different urban-rural gradient typologies raise concerns that broad-measure classifications do not adequately account for important landscape patterns. We suggest future urban-rural gradient studies utilize more robust classification approaches.

We estimate a bivariate probit model using data from a survey of Maine and New Hampshire beachgoers to (i) assess the impact of exposure to and contact with beach waters on safety information-seeking behaviors, and (ii) compare information-seeking behaviors for surf conditions and water quality information. We find that individuals who engage in certain high-contact recreation activities (i.e., swimming, fishing, surfing) are more likely to seek out safety information and that some potential drivers of this behavior affect searches differently for surf conditions versus water quality information.Key Words: cost-effective risk communication, information-seeking behavior, risk, water qualityBeaches are important economic, social, and cultural assets. Coastal beaches host a range of recreation activities, from wading in calm shallows to surfing in rough waters. These areas attract large numbers of visitors nationally: an estimated 43 percent of the U.S. population visited a beach between (Cordell 2012. Those who recreate on beaches often travel great distances to visit, suggesting that they place a high economic value on these resources. Many studies estimate the value of a recreational day on beaches in diverse coastal systems across the nation. These estimates vary by region and study methods, and per-person-per-day values 1 range from $24.22 for beachgoers in San Diego County (Lew and Larson 2008), to $77.56 for

We investigate allocation of funds by citizens across management options addressing impairments to coastal water quality. We study systematic variation in citizen allocation of funds to adaptive versus preventative strategies including the impact of referundum choices and test whether allocations will be impacted by cuing in the design of the referendum. Two key policy insights from our results: citizens who vote no on a water quality referendum have different preferences over allocating funds and providing cues to voters influenced allocation behavior. These results can assist decision makers in thinking about language used to communicate coastal water quality issues, particularly budget referenda.

While research suggests that pollinator decline is linked with agricultural practices, it is unclear whether farmers share this view and adapt management to promote pollinators based on their understanding of these threats. To address these issues, we surveyed farmers of pollinator-dependent cucurbit crops across four states in the Midwest, USA. We grouped farmers by their perceptions of pollinator declines and routes of pesticide exposure and used statistical models to evaluate if farmers manage pests and pollinators based on these perceptions. Out of 93 completed surveys, 39% of farmers believed pollinators were in decline. When grouped, 17% of farmers were classified as proponents, ranking (on a 1–5 Likert scale) the factors mediating pesticide exposure and pollinator declines as important or highly important. For comparison, 44 and 39% of farmers were classified as neutral or skeptical, respectively, of these same factors. Compared to the neutral and skeptic groups, proponents were on average younger, had fewer years farming but more years in family farming, and were more dependent on income from outside the farming system. Proponents also on average reported smaller farms, higher pest richness, more land in cucurbit production, and greater richness of crops that are not pollinator dependent, when compared to the neutrals and skeptics. We did not find pest and pollinator management to be related to farmer perceptions of pollinator decline or routes of pesticide exposure, but farmers classified as pollinator “proponents” were more likely to indicate participation in future pollinator habitat restoration programs. Rather, management strategies were better explained by on-farm environmental conditions (e.g., pest richness, farm size, number of pollinator dependent crops) and economic factors (e.g., sources of income). Generally, our research shows that farmers who perceive pollinator threats may not be using pollinator supportive practices. Thus, while some farmers believe in pollinator declines, there remains a need to connect this knowledge with on-farm practices.