Research and Publications
Across the western US, severe wildfires fueled by tinder-dry vegetation have already burned more than 3.2 million hectares (8 million acres) — an area the size of Maryland — as of the end of October, 2020, and nearly six times that area burned this year in Australia. And even though neither country’s worst-ever fire year is not yet over, concerns are already mounting regarding the next hazard these regions will face: dangerous and destructive debris flows.
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Across the United States, millions of acres of land have been so disturbed by human activities or severe climate events that significant portions of their native plant communities have been lost and their ecosystems have been seriously compromised. Restoring impaired ecosystems requires a supply of diverse native plant seeds that are well suited to the climates, soils, and other living species of the system. Native seeds are also in demand for applications in urban land management, roadside maintenance, conservation agriculture, and other restorative activities that take into account the connection between native plant communities and the increasingly urgent need for resilient landscapes. Given the varied climatic and environmental niches of the more than 17,000 native plant species of the United States, supplying the desired seed types and species mixes for this wide range of activities is a challenge.
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This study showed that all models provided higher predictive accuracy than chance, with an average AUC across the 20 forage species of 0.84 for distal and proximal variables and 0.81 for proximal variables only. This indicated that the addition of distal variables improved model performance. We validated the models using two independent datasets from two regions of Idaho. We found that predicted forage species occurrence was on average within 10% of observed occurrence at both sites. However, predicted occurrences had much less variability between habitat patches than the validation data, implying that the models did not fully capture fine-scale heterogeneity. We suggest that future efforts will benefit from additional fine resolution (i.e., less than 30 m) environmental predictor variables and greater accounting of environmental disturbances (i.e., wildfire, grazing) in the training data. Our approach was novel both in methodology and spatial scale (i.e., resolution and extent). Our models can inform ungulate nutrition by predicting the occurrence of forage species and aide habitat management strategies to improve nutritional quality.
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This study developed a conceptual model that describes the possible uses of science in fire management (perception, planning, forecasting, implementation, assessment, communication, and policy), common barriers to science use (lack of science, uncertainty, funding/capacity, conflict), common facilitators to fire science use (collaboration, trust, boundary organizations, co-production), and factors that can act as facilitators or barriers to science use depending on their presence or absence (awareness, accessibility, relevance). In the context of our conceptual model, we reviewed 67 papers that examined fire science use between 1986 and 2019.
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Approximately 75% of models tested had acceptable, excellent, or outstanding predictive ability. The models that performed poorly were primarily models predicting stem mortality of angiosperms or tree mortality of thin-barked conifers. This suggests that different approaches—such as different model forms, better estimates of bark thickness, and additional predictors—may be warranted for these taxa. Future data collection and research should target the geographical and taxonomic data gaps and poorly performing models identified in this study. Our evaluation of post-fire tree mortality models is the most comprehensive effort to date and allows users to have a clear understanding of the expected accuracy in predicting tree death from fire for 44 species.
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This study’s objective was to determine whether remnant/unburned sagebrush patches contribute to sagebrush recovery in surrounding burned areas surrounding them.
Key Findings:
While conventional wisdom is that sagebrush seeds remain close to the mother plant, we found that a measurable percentage of seeds travel up to tens of meters. Remnant patches of sagebrush after fire could contribute to natural regeneration in surrounding landscapes. However, seed arrival was highly variable between sites and work remains to be done to predict where natural regeneration will be sufficient to rehabilitate sagebrush steppe after wildfire.
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This progress report highlights some of the many contributions and impacts of the JFSP over the past 2 years including:
- Continued scientific output from wildland fire research through manuscripts, management briefs, decision-support tools, and syntheses.
- Efficient delivery of wildland fire science to practitioners through the nationwide Fire Science Exchange Network.
- Incorporation of wildland fire science to improve policy, restoration success, public and firefighter health and safety, and fuels management, among others.
This study modelled 20 forage species that are suitable for mule deer and Rocky Mountain elk. Climatic, topographic, soil, vegetation, and disturbance variables were attributed to approximately 44.3 million habitat patches generated using multi-scale object-oriented image analysis. Lasso logistic regression was implemented to produce predictive SDMs. The study evaluated if the inclusion of distal environmental variables (i.e., indirect effects) improved model performance beyond the inclusion of proximal variables (i.e., direct physiological effect) only. Results showed that all models provided higher predictive accuracy than chance, with an average AUC across the 20 forage species of 0.84 for distal and proximal variables and 0.81 for proximal variables only. This indicated that the addition of distal variables improved model performance. The study validated the models using two independent datasets from two regions of Idaho and found that predicted forage species occurrence was on average within 10% of observed occurrence at both sites.
View our 10-year highlights in this Story Map.
For a decade, the Great Basin Fire Science Exchange (GBFSE) has supported fire, fuels, and restoration research and outreach in the region. We accelerate awareness, adoption, and implementation of fire science by providing a forum for managers, scientists, policy makers, and the public to interact and share. As one of 15 regional fire science exchanges sponsored by the Joint Fire Science Program, we organize and disseminate current research, make connections, and support long-term relationships between practitioners, managers, and researchers to improve the health of Great Basin ecosystems. From climate to communication, we’ve tackled the toughest issues facing managers and stakeholders in a stressed and changing environment. On our 10-year anniversary, we review our accomplishments and look to future challenges.
Weed-Suppressive Bacteria, or WSB, are bacteria strains of the soil bacterium Pseudomonas flourescens (D7, ACK55, and MB906) developed and marketed as a natural way to control exotic grasses, such as cheatgrass. In the late 1900s and early 2000s, scientists began experiments that looked for biological ways to selectively eliminate or inhibit growth of exotic annual grasses.