Filters: Types: OGC WMS Layer (X) > partyWithName: GS ScienceBase (X) > Categories: Publication (X)
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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....
Categories: Data,
Publication;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Hawaii,
biota,
gorse,
grass,
herbarium,
Habitat condition, both acres flooded and timing of inundation, were determined using remote sensing images from Landsat 5 and 8 for the Lower Klamath Basin, the representative basin for the southern Oregon and northeast California (SONEC) region. The dataset includes proportional water coverage (acres) for 8,825 distinct patches in Lower Klamath over 6 different time periods (1984-89; 1990-94; 1995-99; 2000-04; 2005-09; 2010-16), with a total of 368,301 acres of possibly foreageable land.
Categories: Data,
Publication;
Types: Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: California,
Klamath,
Lower Klamath,
Modoc,
Oregon,
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,
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