Prescribed fire provides a valuable tool for habitat management and restoration. Practitioner networks in Oklahoma and North Carolina are compared using government and nonprofit organizational actors as the units of analysis. Measures of individual and network social capital are used to compare actor importance and collaboration with other actor types as well as network centralization and density. The results indicate that the two networks are similar in structure, but that there are differences which include the composition of core and peripheral actor groups as well as prominence of certain actor types. The data reported here suggest a common structural composition of prescribed fire networks. This information may prove useful in adapting similar state networks or determining how to improve the performance of existing networks. Increasing the social capital is a pathway to improve prescribed burning and integrate long-term ecological strategies and funding sources with short-term goals and labor capabilities.

Observed increases in wildfire activity across the contiguous United States (U.S.), together with continued warming and expanding development in fire-prone landscapes, highlight the need to anticipate near-term changes in fire regimes. We apply a Bayesian statistical model that integrates projected population density (SSP2) and downscaled climate simulations under a moderate emissions scenario (RCP 4.5) to estimate future wildfire occurrence, maximum fire size (using the 90th percentile of fire size distribution), and total area burned for large fires (>1000 acres) across all EPA Level III ecoregions for 2020–2060. Relative to 1984–2019, we project nationwide increases of 56% in fire occurrence and 59% in area burned, with larger increases in maximum fire size (63%) in 2020–2060. Spatial patterns vary substantially: fire occurrence increases most strongly in the eastern U.S., including regions where large fires have historically been rare, while western ecoregions experience the largest absolute increases in burned area and extreme fire size. The disproportionate growth in maximum fire size suggests that changes in fire weather will amplify extreme events beyond increases in ignition frequency alone. These projections indicate expanding wildfire risk across diverse U.S. landscapes and underscore the need for regionally tailored fire management and preparedness strategies.

This dataset is a "catalog of literature" produced in support of a review paper titled: "What Goes with the Flow: A Review of Linkages among Climate Change, Low-Flows, Water Quality, and Instream Flow Management Response across the United States". The dataset consists of six tabular sheets, each of them containing information critical to the review paper: a summary of search terms used to collect literature pertinent to this review; terminology encountered that were used to define "low-flows"; detailed summaries of all literature that were collected using these search terms and definitions; quoted examples of ecological impacts of low-flows on river water quality; quoted examples of the management implications for low-flows and river water quality.

Historical and projected suitable habitat of 33 tree and shrub species a under CCSM4 GCMs from 1980 to 2099 was predicted to assess projected climate change impacts in forest communities of North Central U.S. We obtained presence/absence record of each species from Forest Inventory and Analysis (FIA) data. required ata. Historical tme period ranges from 1980 to 2005, and projected time period ranges from 2071 to 2099. Random Forest was used to project historical and future suitable habitat of all species across north central U.S. using the Biomod2 software programmed in R environment. We adopted a climate change scenarios generated from the experiments conducted under fifth assessment of Coupled Model Intercomparison Project (CMIP5) for the Intergovernmental Panel on Climate Change. Selected climate change scenarios include high representative concentrative pathway (RCP8.5).

The PROSPER output rasters represent the estimates of probability of annual streamflow permanence produced by the PRObability of Streamflow PERmanence (PROSPER) model, for years 1989 through 2021, in the upper Missouri River basin and parts of the Great Basin, Upper Colorado River basin, and Pacific Northwest hydrographic regions of the United States. The PROSPER model is a raster-based empirical model with outputs representing probabilistic predictions of an unregulated and minimally impaired stream channel in the study area having year-round flow. This region includes 4-digit Hydrologic Unit Code boundaries 1002-1013, 1015, 1018, 1019, 1404, 1405, 1601, and 1704,. The model provides predictions at a 10-m spatial resolution based on monthly or annually updated values of basin climatic conditions and static physiographic variables upstream from a pixel cell along a stream network. Predictions are assigned to pixel cells on the channel network consistent with the high-resolution National Hydrography Dataset channel network stream grid. Revision History First release: November 5, 2022 Revision ver. 2.0:  July 26, 2024

We used a Bayesian statistical model that includes projections of where people will be located on the landscape and future atmospheric conditions from downscaled climate model simulations using a moderate warming trajectory (RCP 4.5), to make predictions regarding the number, size of the 90% largest fires, and area burned by wildfires in each Environmental Protection Agency (EPA) level-3 ecoregion across the U.S. from 2020-2060