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Journal Article: Soil Temperature and Moisture Regimes across Sage-Grouse Range Emerging applications of ecosystem resilience and resistance concepts in sagebrush ecosystems allow managers to better predict and mitigate impacts of wildfire and invasive annual grasses. Soil temperature and moisture strongly influence the kind and amount of vegetation, and consequently, are closely tied to sagebrush ecosystem resilience and resistance (Chambers et al. 2014). Soil taxonomic temperature and moisture regimes can be used as indicators of resilience and resistance at landscape scales to depict environmental gradients in sagebrush ecosystems that range from cold/cool-moist sites to warm-dry sites. We aggregated soil survey spatial and tabular data to facilitate broad-scale analyses of resilience and... Categories: Data, Publication; Types: Citation, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: California, Colorado, EARTH SCIENCE > LAND SURFACE > LANDSCAPE, Greater sage-grouse, Greater sage-grouse, All tags... Idaho, Invasive, Invasive, LCC Network Science Catalog, Montana, Nevada, North Dakota, Oregon, Report, Sagebrush, Sagebrush, Sagebrush ecosystem, Sagebrush ecosystem, Soil, Soil, Soil Moisture, Soil Moisture, Soil Temperature and Moisture Regimes, Soil Temperature and Moisture Regimes, South Dakota, Temperature, Temperature, Utah, Washington, Washington, Wyoming, biota, cheatgrass, cheatgrass, completed, environment, geoscientificInformation, resilience, resilience, resistance, resistance, sagegrouse, sagegrouse, soil moisture, soil moisture, soil temperature, soil temperature, wildfire, wildfire, Fewer tags Report: Western Invasive Weed Summit Summary and Next Steps Wind erosion and aeolian transport processes are under studied compared to rainfall-induced erosion and sediment transport on burned landscapes. Post-fire wind erosion studies have predominantly focused on near-surface sediment transport and associated impacts such as on-site soil loss and site fertility. Downwind impacts, including air quality degradation and deposition of dust or contaminants, are also likely post-fire effects; however, quantitative field measurements of post-fire dust emissions are needed for assessment of these downwind risks. A wind erosion monitoring system was installed immediately following a desert sagebrush and grass wildfire in southeastern Idaho, USA to measure wind erosion from the burned... Categories: Data, Publication; Types: Citation; Tags: California, EARTH SCIENCE > LAND SURFACE > LANDSCAPE, Great Basin, Idaho, LCC Network Science Catalog, All tags... Nevada, Oregon, Report, Utah, biota, cheatgrass, completed, cooperative planning, coordination, invasive plants, management, wildfire, Fewer tags Selected Hawaiian Language Newspaper Articles Relating to Wildfires in 1877 and 1901 Wildfire is a dominant ridge to reef threat to human and natural communities in the Hawaiian Islands, with impacts to natural and cultural resources and ecoystem services. Fire regimes in Hawaii have shifted from very infrequent wildfire occurrence prior to human arrival to greatly increased frequency, intensity, and size over the past 100+ years, almost all of which is driven by anthropogenic ignitions and wildland fuels associated with invasive species, particularly grasses. Recent fire science has greatly increased understanding of contemporary drivers of fire in Hawaii; however, the social dimensions and historical perspectives from Hawaiian language primary sources have not been integrated into synthetic understanding... Categories: Data, Publication; Types: Citation; Tags: Hamakua, Hawaii, Hawaii, Kapaa, Kauai, All tags... Kealia, Newspaper, Wildfire, biota, Fewer tags Fire Risk Scores from Predictive Model Based on Flammability and Fire Ecology of Non-Native Hawaiian Plants from 2020-2021 We developed a screening system to identify introduced plant species that are likely to increase wildfire risk, using the Hawaiian Islands to test the system and illustrate how the system can be applied to inform management decisions. Expert-based fire risk scores derived from field experiences with 49 invasive species in Hawai′i were used to train a machine learning model that predicts expert fire risk scores from among 21 plant traits obtained from literature and databases. The model revealed that just four variables can identify species categorized as higher fire risk by experts with 90% accuracy, while low risk species were identified with 79% accuracy. We then used the predictive model to screen 365 naturalized... Categories: Data, Publication; Types: Citation, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Hawaii, farming, fire, fire risk, flammability, All tags... invasive plants, post-fire regeneration, species profile, weeds, wildfire, Fewer tags