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Wildfire regimes are changing dramatically across North American deserts with the spread of invasive grasses. Invasive grass fire cycles in historically fire-resistant deserts are resulting in larger and more frequent wildfire. This study experimentally compared how single and repeat fires influence invasive grass-dominated plant fuels in the Great Basin, a semi-arid, cold desert, and the Mojave, a hyper-arid desert. Both study sites had identical study designs. In the summer of 2011, we experimentally burned half of each experimental block, the other half remaining as an unburned control. Half of the burned plots were reburned 5 years later to simulate increasing burn frequency. We estimated non-woody plant biomass, cover, and density in plots from 2017 to 2020.
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Pyrodiversity may affect biodiversity by diversifying available ecological niches, stabilizing community networks and/or supporting diverse species pools available for post-fire colonization. Further, pyrodiversity’s effects on biodiversity vary across different spatial, temporal and organismal scales depending on the mobility and other life history traits of the organisms in question and
may be mediated by regional eco-evolutionary factors such as historical fire regimes. Developing a generalizable understanding of pyrodiversity effects on biodiversity has been challenging, in part because pyrodiversity can be quantified in various ways.
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Mapped representations of species−habitat relationships often underlie approaches to prioritize area-based conservation strategies to meet conservation goals for biodiversity. Generally a single surrogate species is used to inform conservation design, with the assumption that conservation actions for an appropriately selected species will confer benefits to a broader community of organisms. Emerging conservation frameworks across western North America are now relying on derived measures of intactness from remotely sensed vegetation data, wholly independent from species data. Understanding the efficacy of species-agnostic planning approaches is a critical step to ensuring the robustness of emerging conservation designs. We developed an approach to quantify ‘strength of surrogacy’, by applying prioritization algorithms to previously developed species models, and measuring their coverage provided to a broader wildlife community. We used this inference to test the relative surrogacy among a suite of species models used for conservation targeting in the endangered grasslands of the Northern Sagebrush Steppe, where careful planning can help stem the loss of private grazing lands to cultivation. In this test, we also derived a simpler surrogate of intact rangelands without species data for conservation targeting, along with a measure of combined migration representative of key areas for connectivity. Our measure of intactness vastly outperformed any species model as a surrogate for conservation, followed by that of combined migration, highlighting the efficacy of strategies that target large and intact rangeland cores for wildlife conservation and restoration efforts.
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Adequate numbers of replicated, dispersed, and random samples are the basis for reliable sampling inference on resources of concern, particularly vegetation cover across large and heterogenous areas such as rangelands. Tools are needed to predict and assess data precision, specifically the sampling effort required to attain acceptable levels of precision, before and after sampling. We describe and evaluate a flexible and scalable process for assessing the sampling effort requirement for a common monitoring context (responses of rangeland vegetation cover to post-fire restoration treatments), using a custom R script called “SampleRange.” In SampleRange, vegetation cover is estimated from available digital-gridded or field data (e.g., using the satellite-derived cover from the Rangeland Assessment Platform). Next, the sampling effort required to estimate cover with 20% relative standard error (RSE) or to saturate sampling effort is determined using simulations across the environmental gradients in areas of interest to estimate the number of needed plots (“SampleRange quota”). Finally, the SampleRange quota are randomly identified for actual sampling. A 2022 full-cycle trial of SampleRange using the best available digital and prior field data for areas treated after a 2017 wildfire in sagebrush-steppe rangelands revealed that differences in the predicted compared with realized RSEs are inevitable. Future efforts to account for uncertainty in remotely sensed−based vegetative products will enhance tool utility.
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The sagebrush biome is a dryland region in the western United States experiencing rapid transformations to novel ecological states. Threat-based approaches for managing anthropogenic and ecosystem threats have recently become prominent, but successfully mitigating threats depends on the ecological resilience of ecosystems. We used a spatially explicit approach for prioritizing management actions that combined a threat-based model with models of resilience to disturbance and resistance to annual grass invasion. The threat-based model assessed geographic patterns in sagebrush ecological integrity (SEI) to identify core sagebrush, growth opportunity, and other rangeland areas. The resilience and resistance model identified ecologically relevant climate and soil water availability indicators from process-based ecohydrological models. The SEI areas and resilience and resistance indicators were consistent – the resilience and resistance indicators showed generally positive relationships with the SEI areas. They also were complementary – SEI areas provided information on intact sagebrush areas and threats, while resilience and resistance provided information on responses to disturbances and management actions. The SEI index and resilience and resistance indicators provide the basis for prioritizing conservation and restoration actions and determining appropriate strategies. The difficulty and time required to conserve or restore SEI areas increase as threats increases and resilience and resistance decrease.
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Using data on the patterns of participation of 10,199 individual stakeholders in 837 community wildfire protection plans (CWPPs) within the western U.S., we document the emergence of a locally clustered but spatially extensive wildfire risk governance network. Our evaluation of factors that contribute to connectivity within this network indicates that risk interdependence (e.g., joint exposure to the same fires) between planning jurisdictions increases the prospects for linkages between planning processes, and that connectivity is also more likely among planning processes that are more proximate and similar to one another. We discuss how our results advance understanding of how changing hazard conditions prompt risk mitigation policy networks to reorganize, which in turn affects risk outcomes at multiple spatial scales.
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The pathways tool provides a series of empirically informed processes, choices, and engagement tactics designed to foster shared agreement about the best practices for wildfire adaptation across site-specific local conditions. We outline how the tool can advance adaptation processes for a variety of users, including (1) a community oriented planning process that will help reinforce or catalyze collective action about fire management, (2) a systematic approach for monitoring differential progress toward development of fire-adapted communities, and (3) a potential feedback mechanism that informs programmatic foci or allocation of future resources across potential actions designed for diverse social conditions.
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This concept paper presents a Stages of Collaborative Readiness framework. Collaborative, multi-party entities provide fundamental roles and contributions to prepare landscapes and communities to receive and recover from wildfire (identifying, connecting, and aligning stakeholders; co-developing strategies at scale; synchronizing operations; and facilitating science informed, continuous learning). The framework applies insights from the collaborative development literature to the context of forest and wildland fire risk management. It embeds the fundamental roles and contributions within a four-stage framework, identifying stage appropriate benchmarks and outcomes to increase the ability of a collaborative over time to serve those important functions.
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In this article, we highlight strategies that Indigenous communities and scholars are employing to approach wildfire management. We start by introducing the reader to the colonial ecological violence that has resulted from the exclusion of fire and the ways that communities resist the settler colonial paradigm of fire suppression. We then analyze the role of militarism and incarceration within the “fire industrial complex.” Militarism and incarceration have been a part of settler colonial fire suppression in California since the beginning even as they emerge in novel forms in the twenty-first century, and they pose a challenge to regenerative and sovereign Indigenous fire futures. Next, we guide the reader through debates on Indigenous “traditional ecological knowledge” (TEK) and the ways that fire science variously erases, homogenizes, or romanticizes the epistemologically and politically complex practices of Indigenous burners. We advocate that scholars avoid participating in an extractive “TEK rush” and instead enter into direct relationships of accountability and collaboration with Indigenous fire practitioners. We conclude by discussing the ways Indigenous communities build anticolonial movements to assert sovereignty—fire and otherwise—based on reciprocal and relational systems for people and ecosystems. By reframing the current wildfire crisis through the lens of settler colonialism, we bypass unilateral, settler-driven solutions and emphasize that respect for Indigenous fire sovereignty—not only Indigenous fire knowledge—is essential for actualizing just fire futures in California and beyond.
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We present an easily replicable approach to calculate the economic cost from carbon released instantaneously from wildfires at state and county level (US). Our approach is straightforward and relies exclusively on publicly available data that can be easily obtained for locations throughout the USA. We also describe how to apply social cost of carbon estimates to the carbon loss estimates to find the economic value of carbon released from wildfires. We demonstrate our approach using a case study of the 2017 Eagle Creek Fire in Oregon. Our estimated value of carbon lost for this medium-sized (19,400 ha) fire is $187.2 million (2020 dollars), which highlights the significant role that wildfires can have in terms of carbon emissions and their associated cost. The emissions from this fire were equivalent to as much as 2.3% of non-fire emissions for the state of Oregon in 2020.