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This product provides a metric of percentage increase in the number of fires expected per year under various climate change scenarios in both the dry and wet season compared to a 1996-2016 baseline at a per-pixel basis for the main Hawaiian Islands (excluding Niʻihau) at 30 m x 30 m resolution. Future climate scenarios include statistically and dynamically downscaled RCP 8.5 in the year 2100 in addition to statistically downscaled RCP 8.5 in the year 2050. This is a modeled data product trained using historical fire perimeters, ignition density, mean annual temperature, mean annual soil moisture, historical rainfall data , and remotely sensed vegetation cover.
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Introduced (non-native) species that become established may eventually become invasive, so tracking all introduced species provides a baseline for effective modeling of species trends and interactions, geospatially and temporally. The United States Register of Introduced and Invasive Species (US-RIIS) (ver. 2.0, November 2022, https://doi.org/10.5066/P9KFFTOD), as of 2022-10-23, is comprised of three lists, for the localities of Alaska (AK, with 545 records), Hawaii (HI, with 5,628 records), and the conterminous (or lower 48) United States (L48, with 8,527 records). Each includes introduced (non-native), established (reproducing) taxa that: are, or may become, invasive (harmful) in the locality; are not known to...
Categories: Data;
Tags: Alaska, State of,
Aquatic Biology,
Botany,
Conterminous United States,
Contiguous United States, All tags...
Ecology,
Environmental Health,
Forestry,
Hawaii, State of,
Information Sciences,
USGS Science Data Catalog (SDC),
Wildlife Biology,
Wildlife Disease,
biocontrol,
degreeOfEstablishment,
establishmentMeans,
habitat,
intentional introduction,
introduced,
introduced species,
introduction date,
invasive,
invasive species,
taxonomy, Fewer tags
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This product used species distribution modeling (SDM) to model the geographic distribution fire promoting grasses across the islands of Hawaii under both current climate conditions and under future climate change scenarios (RCP 8.5 at year 2100). The RCP 8.5 scenario assumes unmitigated and continued release of greenhouse grasses and continued human population growth. Six species of well established and widely distributed grasses (Andropogon virginicus (broomsedge), Cenchrus ciliaris (buffelgrass), Cenchrus setaceus (fountain grass), Megathyrus maximus (guinea grass, Urochloa maxima, Pancicum maximum), Melinis minutiflora (mollasses grass), and Schizachyrium microstachyum (formerly referred to as S. condensatum...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Hawaii,
Species distribution modeling,
biota,
climate change,
fire, All tags...
flammable plants,
future climate,
grass, Fewer tags
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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, All tags...
vegetation,
vegetation plots, Fewer tags
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Globally, invasive plant-fueled wildfires have tremendous environmental, economical, and societal impacts, and the frequencies of wildfires and plant invasions are on an upward trend globally. Identifying which plant species tend to increase the frequency or severity of wildfire is important to help manage their impacts. 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...
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