Conserving large carnivores while keeping people safe depends on finding means for peaceful coexistence. Although large carnivore populations are generally declining globally, some populations are increasing, causing greater overlap with humans and increasing potential for conflict. One method of reducing conflict with large carnivores is to secure attractants like garbage and livestock. This method is effective when implemented; however, implementation requires a change in human behavior. Humanwildlife interaction is a public good collective action problem where solutions require contributions from many and individual actions have effects on others. We used the collective interest model to investigate how individual and collective factors work in concert to influence landowner attractant securing behavior in Montana, USA, in black (Ursus americanus) and grizzly bear (U. arctos) range. We used data from a mailback survey to develop logistic regression models testing the relative effects of collective and individual factors on landowners' attractant securing behaviors. The most important factor was whether individuals had spoken to a wildlife professional, a reflection of social coordination and pressure. Other collective factors (e.g., social norms [i.e., expectations and behaviors of peers] and the existence of discussion networks [i.e., how much social influence an individual has]) were equally important as individual factors (e.g., beliefs, age, gender) for influencing attractant securing behavior among Montana landowners. This research suggests pathways for wildlife managers and outreach coordinators to increase attractant securing behavior by emphasizing collective factors, such as social norms, rather than appealing exclusively to individual factors, such as risk perception of large carnivores. Furthermore, wildlife agencies would be justified in increasing their efforts to connect with landowners in person and to connect with members of the public who play an important role in discussion networks. This research demonstrates that, even on private lands, collective interests may be a missing and important piece of the puzzle for encouraging voluntary attractant securing behavior and improving wildlife-human coexistence.

The concept of adaptive capacity has received significant attention within social-ecological and environmental change research. Within both the resilience and vulnerability literatures specifically, adaptive capacity has emerged as a fundamental concept for assessing the ability of social-ecological systems to adapt to environmental change. Although methods and indicators used to evaluate adaptive capacity are broad, the focus of existing scholarship has predominately been at the individual- and household- levels. However, the capacities necessary for humans to adapt to global environmental change are often a function of individual and societal characteristics, as well as cumulative and emergent capacities across communities and jurisdictions. In this paper, we apply a systematic literature review and co-citation analysis to investigate empirical research on adaptive capacity that focus on societal levels beyond the household. Our review demonstrates that assessments of adaptive capacity at higher societal levels are increasing in frequency, yet vary widely in approach, framing, and results; analyses focus on adaptive capacity at many different levels (e.g., community, municipality, global region), geographic locations, and cover multiple types of disturbances and their impacts across sectors. We also found that there are considerable challenges with regard to the `fit' between data collected and analytical methods used in adequately capturing the cross-scale and cross-level determinants of adaptive capacity. Current approaches to assessing adaptive capacity at societal levels beyond the household tend to simply aggregate individual- or household-level data, which we argue oversimplifies and ignores the inherent interactions within and across societal levels of decision-making that shape the capacity of humans to adapt to environmental change across multiple scales. In order for future adaptive capacity research to be more practice-oriented and effectively guide policy, there is a need to develop indicators and assessments that are matched with the levels of potential policy applications.

Growing demand for water resources coupled with climate-driven water scarcity and variability present critical challenges to agriculture in the Western US. Despite extensive resources allocated to downscaling climate projections and advances in understanding past, current, and future climatic conditions, climate information is underutilized in decisions made by agricultural producers. Climate information providers need to understand why this information is underutilized and what would better meet the needs of producers. To better understand how agricultural producers perceive and utilize climate information, we conducted five focus groups with farmers and ranchers across Montana. Focus groups revealed that there are fundamental scalar issues (spatial and temporal) that make climate information challenging for producers to use. While climate information is typically produced at regional, national, or global spatial scales and at a seasonal and mid- to end-of-century temporal scales, producers indicated that decision-making takes place at multiple intermediate and small temporal and spatial scales. In addition, producers described other drivers of decision-making that have little to do with climate information itself, but rather aspects of source credibility, past experience, trust in information, and the politics of climate change. Through engaging directly with end-users, climate information providers can better understand the spatial and temporal scales that align with different types of agricultural producers and decisions, as well as the limitations of information provision given the complexity of the decision context. Increased engagement between climate information providers and end-users can also address the important tradeoffs that exist between scale and uncertainty.

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