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Folders: ROOT > ScienceBase Catalog > National and Regional Climate Adaptation Science Centers > Pacific Islands CASC ( Show direct descendants )

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Previous research identified species of invasive plants in Hawai'i which are highly flammable and act as fuels in wildfires across Hawai'i. This work aimed to map the distribution of these species (largely grasses) around the islands of Hawai'i with the goal of using the locations for species distribution modeling. All data represents presence data, no absence data were recorded. Data are largely from within the past 20 years, but some georeferenced herbarium specimens go as far back as 1905. Data were obtained from georeferenced herbarium specimens, vegetation plot data, citizen science data (iNaturalist) reviewed by the authors, and data from roadside surveys conducted as part of this research to map these species....
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This dataset provides seasonal means of 7 WRF variables for the Hawaiian Islands region including: rainfall (PR), 2m temperatures (TAS), 90th percentile daily rainfall extremes (PR90), 99th percentile daily rainfall extremes (PR99), 90th percentile daily temperature extremes (TAS90), 99th percentile daily temperature extremes (TAS99), and the vertically integrated moisture flux convergence (VIMFC) The files are organized and labeled by simulation period (present-day:1996-2005 and future: 2026-2035), season (wet or dry), and PDO phase (positive or negative). For a full description of the WRF model and simulations, please refer to related publication. ​Data are also available from a federal repository upon request....
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This dataset provides daily WRF output for the Hawaiian Islands region for the following variables: daily rainfall (RAINNC), daily 2m temperature (TMEAN), max 2m temperature (TMAX), and min 2m temperature (TMIN) These quantities are provided for 20 WRF simulations over the time periods (1996-2005) and (2026-2035). Files are labeled based on the WRF simulation and year. (WRF 1-5 and 11-15: negative PDO phase, WRF 6-10 and 16-20: positive PDO phase). ​Data are also available from a federal repository upon request. Contact: casc@usgs.gov.
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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...
    map background search result map search result map Seasonal WRF Output (PI-CASC) Fire Risk Scores from Predictive Model Based on Flammability and Fire Ecology of Non-Native Hawaiian Plants from 2020-2021 Locations of Fire Promoting Alien Plants Across the Islands of Hawaii Based on Field Surveys and Museum Collections from 1903-2023 Daily WRF output (PI-CASC) Seasonal WRF Output (PI-CASC) Fire Risk Scores from Predictive Model Based on Flammability and Fire Ecology of Non-Native Hawaiian Plants from 2020-2021 Locations of Fire Promoting Alien Plants Across the Islands of Hawaii Based on Field Surveys and Museum Collections from 1903-2023 Daily WRF output (PI-CASC)