Filters: partyWithName: U.S. Geological Survey - ScienceBase (X) > partyWithName: Benjamin M Sleeter (X)
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This dataset contains a projection of land use and land cover for the conterminous United States for the period 2001 - 2061. This projection used the USGS's LUCAS (Land Use and Carbon Scenario Simulator) model to project a business as usual scenario of land cover and land use change. By running the LUCAS model on the USGS's YETI high performance computer and parallelizing the computation, we ran 100 Monte Carlo simulations based on empirically observed rates of change at a relatively fine scale (270m). We sampled from multiple observed rates of change at the county level to introduce heterogeneity into the Monte Carlo simulations. Using this approach allowed the model to project different outcomes that were summarized...
The USGS’s FORE-SCE model was used to produce land-use and land-cover (LULC) projections for the conterminous United States. The projections were originally created as part of the "LandCarbon" project, an effort to understand biological carbon sequestration potential in the United States. However, the projections are being used for a wide variety of purposes, including analyses of the effects of landscape change on biodiversity, water quality, and regional weather and climate. The year 1992 served as the baseline for the landscape modeling. The 1992 to 2005 period was considered the historical baseline, with datasets such as the National Land Cover Database (NLCD), USGS Land Cover Trends, and US Department of Agriculture's...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: CONUS,
CONUS,
Conterminous,
Conterminous United States,
FORE-SCE,
This dataset includes ten years of emissions and sequestration estimates (2005-2014) in two separate tables, 1) the combustion and extraction of fossil fuels on Federal lands and 2) processes from the ecosystems on those Federal lands. The fossil fuel related estimates include the greenhouse gases carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), and the ecosystems estimates include only CO2. The results are presented by State and year, including the Pacific and Gulf offshore areas in the fossil fuel associated estimates. In addition to total emissions, the estimates are broken into categories by the sector of the economy where the combustion or extraction related emissions occurred or the biologic process...
Categories: Data;
Tags: Climatology,
Energy Resources,
Environmental Health,
USGS Science Data Catalog (SDC),
United States of America,
Scenario-based simulation model projections of land use change, ecosystem carbon stocks, and ecosystem carbon fluxes for the State of California from 2001-2101 using the SyncroSim software framework, see http://doc.syncrosim.com/index.php?title=Reference_Guide for software documentation. We explored four land-use scenarios and two radiative forcing scenarios (e.g. Representative Concentration Pathways; RCPs) as simulated by four earth system models (i.e. climate models). Results can be used to understand the drivers of change in ecosystem carbon storage over short, medium, and long (e.g. 100 year) time intervals. See Sleeter et al. (2019) Global Change Biology (doi: 10.1111/gcb.14677) for detailed descriptions of...
This data series provides tabular output from a series of modeling simulations for the State of California. The methods and results of this research are described in detail in Sleeter et al. (2019). We used the LUCAS model to project changes in ecosystem carbon balance resulting from land use and land use change, climate change, and ecosystem disturbances such as wildfire and drought. The model was run at a 1-km spatial resolution on an annual timestep. We simulated 32 unique scenarios, consisting of 4 land-use scenarios and 2 radiative forcing scenarios as simulated by 4 global climate models. For each scenario, we ran 100 Monte Carlo realizations of the model. Additional details describing the modeling effort...
This dataset consists of modeled projections of land use and land cover for the State of California for the period 2001-2101. The Land Use and Carbon Scenario Simulator (LUCAS) model was initialized in 2001 and run forward on an annual time step to 2100. In total 9 simulations were run with 10 Monte Carlo replications of each simulation. Two base scenarios were selected from Sleeter et al., 2017 (http://onlinelibrary.wiley.com/doi/10.1002/2017EF000560/full) for analysis, including a "business-as-usual" (BAU) land use scenario and a scenario based on "medium" population projections. For each base scenario we ran three alternative conservation scenarios where we simulated conversion of lands into conservation easements....
We summarized annual remote sensing land cover classifications from the U.S. Geological Survey Land Cover Monitoring, Assessment, and Projection (LCMAP) annual time series to characterize forest change across the conterminous United States (CONUS) for the years 1985-2020. The raster output includes a map where each pixel is given an integer value based on the number of years in which it was classified as forest across the annual LCMAP time series. Values of 36 indicate the pixel was classified as forest across all years while a value of 0 indicates forests (tree cover) was never detected during the time series.
This data series provides annual maps of carbon stocks for conterminous U.S. forests. Annual raster maps are provided at 1-km resolution for the period 2001-2020. Carbon stock estimates were derived by linking the Land Use and Carbon Scenario Simulator (LUCAS) model and the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) as described in the accompanying publication. The model was run on an annual timestep for the period 2001-2020. Four scenario simulations were conducted including 1) the combined effects of land use and land cover change (LULC) and climate, 2) only LULC effects, 3) only climate effects, and 4) no effects from either LULC or climate.
This dataset consists of modeled projections of land use and land cover and population for the State of California for the period 1970-2101. For the 1970-2001 period, we used the USGS's LUCAS model to "backcast" LULC, beginning with the 2001 initial conditions and ending with 1970. For future projections, the model was initialized in 2001 and run forward on an annual time step to 2100. In total 5 simulations were run with 10 Monte Carlo replications of each simulation. The simulations include: 1) Historical backcast from 2001-1970, 2) Business-as-usual (BAU) projection from 2001-2101, and 3) three modified BAU projections based on California Department of Finance population projections based on high, medium, and...
Categories: Data;
Tags: California,
California,
LUCAS model,
Land Use Change,
USGS Science Data Catalog (SDC),
Tabular data output from a series of modeling simulations for forest ecoystems of the continental United States (CONUS). We linked the LUCAS model of land-use and land-cover change with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to project changes in forest ecosystem carbon balance resulting from land use, land use change, climate change, and disturbance from wildfire and insect mortality. The model was run at a 1-km spatial resolution on an annual timestep for the years 2001 to 2020. We simulated four unique scenarios, consisting of a climate change only scenario, a land-use change only scenario, a combined climate and land-use change scenario, and a no change scenario. Results presented here...
This simulated ecosystem carbon dataset is used to report terrestrial carbon budget of the conterminous U.S. in the Golobal Change Biology paper "Critical land change information enhances understanding of carbon balance in the U.S." The data is derived from simulations of the parallel Integrated Biosphere simulator (pIBIS). Annual carbon variables cover 1971-2015 at 1-km (960m) spatial resolution with 3052 rows and 4823 columns. Carbon stock and flux units are in kgC/m2 and kgC/m2/yr, respectively. Data are in NetCDF format and Albers equal area projection. Overall data creation steps: 1. The pIBIS model was used to run simulations using climate, vegetation, soil and disturbance input data; 2. Model outputs were...
We summarized annual remote sensing land cover classifications from the U.S. Geological Survey Land Cover Monitoring, Assessment, and Projection (LCMAP) annual time series to characterize the frequency of forest change across the conterminous United States (CONUS) between 1985-2020. Data include a raster map of CONUS with pixel values representing the number of years in which it was classified as forest across the annual LCMAP time series (0-36), as well as tabular data summarizing forest change by area and proportion for each of the 48 conterminous U.S. states and the District of Columbia. Tabular output includes information on 1) the area classified as forest in each State by year, 2) the forest area in each frequency...
This simulated ecosystem carbon dataset is derived from simulations of the parallel Integrated Biosphere simulator (pIBIS). Annual carbon variables cover 1971-2015 at 1-km (960m) spatial resolution with 3052 rows and 4823 columns. Carbon stock and flux units are in kgC/m2 and kgC/m2/yr, respectively. Data are in NetCDF format and Albers equal area projection. Overall data creation steps: 1. The pIBIS model was used to run simulations using climate, vegetation, soil and disturbance input data; 2. Model outputs were converted to NetCDF format; 3. 1971-2015 subsets were clipped from original 1901-2015 simulation outputs. Variable List: aynbp – annual net biome productivity ayneetot – net ecosystem productivity aynpptot...
Spatially explicit maps of annual forest carbon stocks and tabular estimates of land use/land cover change, LULC transitions, carbon stocks and carbon fluxes for selected regions and geographies. Estimates span the period from 2001-2020. Scenarios included are defined with a unique numerical identifier. scn160 = Full Simulation (Land use and Climate Effects) scn155 = Climate Effects only scn156 = No Effects included scn161 = Land Use Effects only Raster output is organized into three categories: CBM pools: Include 14 unique carbon pools used in the model, including 5 biomass pools and 9 dead organic matter (DOM) pools. IPCC pools: Include aggregations of CBM pool types corresponding to IPCC guidelines, including...
Nature-based solutions is a leading policy option for mitigating climate change. We mapped areas of potential restoration and conservation opportunities in the conterminous U.S. (CONUS). The potential for five scenarios were examined: increasing forest cover in urban centers, restoring historically forested areas that have been converted to grasslands, conserving pristine grasslands, rewetting peatlands, and conserving vulnerable tidal wetlands.
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