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Among emerging contaminants, microplastics (MPs) are of particular concern due to their ubiquity across environments and the unique challenges posed by attempted removal. In-line washing machine filters are one potential tool for preemptively preventing a category of MPs from entering waterways. A sample of registered voters and environmental interest groups in Oregon were asked about their general knowledge and concerns surrounding microplastics, as well as their willingness to pay for high-efficiency washing machine filters. Findings show that less than a quarter of all respondents would be willing to pay full price for a high-efficiency filter, indicating a limited-scale early adopter program may be a more feasible implementation option. Up to 20% more people may support if part of the cost were to be covered by a government subsidy. Understanding consumer knowledge, characteristics, and willingness to pay (WTP) for filters across demographics can be particularly beneficial to researchers and policymakers looking to engage early adopters for this potential solution to the ongoing issue of MPs. 

Abstract Theory predicts that effective environmental governance requires that the scales of management account for the scales of environmental processes. A good example is community wildfire protection planning. Plan boundaries that are too narrowly defined may miss sources of wildfire risk originating at larger geographic scales whereas boundaries that are too broadly defined dilute resources. Although the concept of scale (mis)matches is widely discussed in literature on risk mitigation as well as environmental governance more generally, rarely has the concept been rigorously quantified. We introduce methods to address this limitation, and we apply our approach to assess scale matching among Community Wildfire Protection Plans (CWPPs) in the western US. Our approach compares two metrics: (1) the proportion of risk sources encompassed by planning jurisdictions (sensitivity) and (2) the proportion of area in planning jurisdictions in which risk can originate (precision). Using data from 852 CWPPs and a published library of 54 million simulated wildfires, we demonstrate a trade-off between sensitivity and precision. Our analysis reveals that spatial scale match—the product of sensitivity and precision—has an n-shaped relationship with jurisdiction size and is maximal at approximately 500 km². Bayesian multilevel models further suggest that functional scale match—via neighboring, nested, and overlapping planning jurisdictions—may compensate for low sensitivity. This study provides a rare instance of a quantitative framework to measure scale match in environmental planning and has broad implications for risk mitigation as well as in other environmental governance settings. 

We integrated a mechanistic wildfire simulation system with an agent-based landscape change model to investigate the feedbacks among climate change, population growth, development, landowner decision-making, vegetative succession, and wildfire. Our goal was to develop an adaptable simulation platform for anticipating risk-mitigation tradeoffs in a fire-prone wildland–urban interface (WUI) facing conditions outside the bounds of experience. We describe how five social and ecological system (SES) submodels interact over time and space to generate highly variable alternative futures even within the same scenario as stochastic elements in simulated wildfire, succession, and landowner decisions create large sets of unique, path-dependent futures for analysis. We applied the modeling system to an 815 km2 study area in western Oregon at a sub-taxlot parcel grain and annual timestep, generating hundreds of alternative futures for 2007–2056 (50 years) to explore how WUI communities facing compound risks from increasing wildfire and expanding periurban development can situate and assess alternative risk management approaches in their localized SES context. The ability to link trends and uncertainties across many futures to processes and events that unfold in individual futures is central to the modeling system. By contrasting selected alternative futures, we illustrate how assessing simulated feedbacks between wildfire and other SES processes can identify tradeoffs and leverage points in fire-prone WUI landscapes. Assessments include a detailed “post-mortem” of a rare, extreme wildfire event, and uncovered, unexpected stabilizing feedbacks from treatment costs that reduced the effectiveness of agent responses to signs of increasing risk. 

Private landowners in the southern Willamette Valley of Oregon, USA were surveyed. The survey queried probabilities of implementing specific fuels reduction projects in extensive areas of specific forest types on their property. The projects were described in relation to the beginning and target forest types, the actions required, costs, and long-term maintenance. Forest types were first rated for scenic beauty and informed levels of wildfire risk reduction, scarce habitat production, and associated property rights risks. Propensities to perform each fuels reduction project were then obtained. These were adversely affected by disbelief in heightened wildfire risks or climate change, higher project costs, feelings of hopeless vulnerability to wildfire, and low aesthetic affections for target forests. Propensities were enhanced by aesthetic affection for target forests, belief in the efficaciousness of fuels reduction, previous experience with wildfire evacuation, and higher incomes. All landowners favored thinning of young conifer forests, but some were averse to thinning of mature conifer forests. Anthropocentric landowners, mainly farmers, foresters, and some small holders, tended to favor conventional thinnings toward commercially valuable conifer forests and avoided long-term habitat maintenance. Nature-centric landowners, mainly some rural residents and wealthy estate owners, leaned more toward long term habitat goals and oak forests. 

Nearly 0.8 million hectares of land were burned in the North American Pacific Northwest (PNW) over two weeks under record-breaking fuel aridity and winds during the extraordinary 2020 fire season, representing a rare example of megafires in forests west of the Cascade Mountains. We quantified the relative influence of weather, vegetation, and topography on patterns of high burn severity (>75% tree mortality) among five synchronous megafires in the western Cascade Mountains. Despite the conventional wisdom in climate-limited fire regimes that regional drivers (e.g., extreme aridity, and synoptic winds) overwhelm local controls on vegetation mortality patterns (e.g., vegetation structure and topography), we hypothesized that local controls remain important influences on burn severity patterns in these rugged forested landscapes. To study these influences, we developed remotely sensed fire extent and burn severity maps for two distinct weather periods, thereby isolating the effect of extreme east winds on drivers of burn severity. Our results confirm that wind was the major driver of the 2020 megafires, but also that both vegetation structure and topography significantly affect burn severity patterns even under extreme fuel aridity and winds. Early-seral forests primarily concentrated on private lands, burned more severely than their older and taller counterparts, over the entire megafire event regardless of topography. Meanwhile, mature stands burned severely only under extreme winds and especially on steeper slopes. Although climate change and land-use legacies may prime temperate rainforests to burn more frequently and at higher severities than has been historically observed, our work suggests that future high-severity megafires are only likely to occur during coinciding periods of heat, fuel aridity, and extreme winds. 

Characterizing wildfire regimes where wildfires are uncommon is challenged by a lack of empirical information. Moreover, climate change is projected to lead to increasingly frequent wildfires and additional annual area burned in forests historically characterized by long fire return intervals. Western Oregon and Washington, USA (westside) have experienced few large wildfires (fires greater than 100 hectares) the past century and are characterized to infrequent large fires with return intervals greater than 500 years. We evaluated impacts of climate change on wildfire hazard in a major urban watershed outside Portland, OR, USA. We simulated wildfire occurrence and fire regime characteristics under contemporary conditions (1992–2015) and four mid-century (2040–2069) scenarios using Representative Concentration Pathway (RCP) 8.5. Simulated mid-century fire seasons expanded in most scenarios, in some cases by nearly two months. In all scenarios, average fire size and frequency projections increased significantly. Fire regime characteristics under the hottest and driest mid-century scenarios illustrate novel disturbance regimes which could result in permanent changes to forest structure and composition and the provision of ecosystem services. Managers and planners can use the range of modeled outputs and simulation results to inform robust strategies for climate adaptation and risk mitigation.