This the dataset shows the plot-level contributions to dC/dN from Figure 2 in the paper. The data is in file "SN_gs_dCdN01_state_means_expanded_limited_map_v1_plt_hist_2018MAR06_VIFN3_2021-10-06" and the metadata is in file "SN_gs_dCdN01_state_means_expanded_limited_map_v1_plt_hist_2018MAR06_VIFN3_2021-10-06_column key." The data show, for all the FIA plots used in the analysis, the net dC/dN (the net change in aboveground live tree carbon with change in N deposition) based on both growth and/or survival equations multiplied by the TPH (trees per hectare). Various other identifying pieces of information are also provided (e.g., State, Ecoregion, etc.).

This data is from Clark et al. (2023), "Future climate change effects on US forest composition may offset benefits of reduced atmospheric deposition of N and S." (https://onlinelibrary.wiley.com/doi/10.1111/gcb.16817). The dataset provides the decadal data (2010, 2020, etc., to 2100), for estimates of biomass and stem count, for each county (FIPS) in the lower 48 states, for the 94 tree species analyzed in Horn et al. (2018), separately for the 20 climate and atmospheric deposition scenarios examined in the Clark et al. manuscript. Summary tables and key supporting information are also provided. The data are too large to upload to Science Hub (>10 GB) and are instead available on the DataDryad here: https://datadryad.org/stash/dataset/doi:10.5061/dryad.tht76hf4f. This dataset is associated with the following publication: Clark, C., J. Phelan, J. Ash, J. Buckley, J. Cajka, K. Horn, R.Q. Thomas, and R.D. Sabo. Future climate change effects on U.S. forest composition may offset benefits of reduced atmospheric deposition of N and S. GLOBAL CHANGE BIOLOGY. Blackwell Publishing, Malden, MA, USA, 29(17): 4793-4810, (2023).

A tree database representing a single cohort of trees was assembled using data from U.S Forest Service monitoring plots. Applying existing species specific response relationships from Thomas et al. (2010), we simulated how forest stands in a 19-state study area would change (biomass and stem density) from 2005 to 2100 under 12 different future N deposition – climate scenarios based on historic levels, current policy and potential futures. This dataset is associated with the following publication: van Houtven, G., J. Phelan, C. Clark, R. Sabo, J. Buckley, R.Q. Thomas, K. Horn, and S. LeDuc. Nitrogen Deposition and Climate Change Effects on Tree Species Composition and Ecosystem Services: A Cohort Analysis. ECOLOGICAL MONOGRAPHS. Ecological Society of America, Ithaca, NY, USA, 75, (2018).

A tree database representing a single cohort of trees was assembled using data from U.S Forest Service monitoring plots. Applying existing species specific response relationships from Thomas et al. (2010), we simulated how forest stands in a 19-state study area would change (biomass and stem density) from 2005 to 2100 under 12 different future N deposition – climate scenarios based on historic levels, current policy and potential futures. This dataset is associated with the following publication: van Houtven, G., J. Phelan, C. Clark, R. Sabo, J. Buckley, R.Q. Thomas, K. Horn, and S. LeDuc. Nitrogen Deposition and Climate Change Effects on Tree Species Composition and Ecosystem Services: A Cohort Analysis. ECOLOGICAL MONOGRAPHS. Ecological Society of America, Ithaca, NY, USA, 75, (2018).

This document contains expanded tables from the report "Effects of Climate Change and Atmospheric Nitrogen Deposition on Forest Understory Vegetation Communities in Selected U.S. National Parks" by T.C. McDonnell, Brian Knees, Michael D. Bell, and Emmi Felker-Quinn that can be used to evaluate critical loads of individual map classes and herbaceous species found across parks.

This dataset, derived from the National Forest Carbon Monitoring System (NFCMS), provides estimates of forest carbon stocks and fluxes in the form of aboveground woody biomass (AGB), total live biomass, total ecosystem carbon, aboveground coarse woody debris (CWD), and net ecosystem productivity (NEP) as a function of the number of years since the most recent disturbance (i.e., stand age) for forests of the conterminous U.S. at a 30 m resolution for the benchmark years 1990, 2000, and 2010. The data were derived from an inventory-constrained version of the Carnegie-Ames-Stanford Approach (CASA) carbon cycle process model that accounts for disturbance processes for each combination of forest type, site productivity, and pre-disturbance biomass. Also provided are the core model data inputs including the year of the most recent disturbance according to the North American Forest Dynamics (NAFD) and the Monitoring Trends in Burn Severity (MTBS) data products; the type of disturbance; biomass estimates from the year 2000 according to the National Biomass and Carbon Dataset (NBCD); forest-type group; a site productivity classification; and the number of years since stand-replacing disturbance. The data are useful for a wide range of applications including monitoring and reporting recent dynamics of forest carbon across the conterminous U.S., assessment of recent trends with attribution to disturbance and regrowth drivers, conservation planning, and assessment of climate change mitigation opportunities within the forest sector.

Data files for Koplitz et al., "The contribution of wildland emissions to deposition in the U.S.: implications for tree growth and survival in the Northwest", Environmental Research Letters, in press, 2021, doi:10.1088/1748-9326/abd26e. This dataset is associated with the following publication: Koplitz, S., C. Nolte, R. Sabo, C. Clark, K. Horn, R.Q. Thomas, and T. Newcomer-Johnson. The contribution of wildland fire emissions to deposition in the U S: implications for tree growth and survival in the Northwest. Environmental Research Letters. IOP Publishing LIMITED, Bristol, UK, 16(2): 024028, (2021).

Data files for Koplitz et al., "The contribution of wildland emissions to deposition in the U.S.: implications for tree growth and survival in the Northwest", Environmental Research Letters, in press, 2021, doi:10.1088/1748-9326/abd26e. This dataset is associated with the following publication: Koplitz, S., C. Nolte, R. Sabo, C. Clark, K. Horn, R.Q. Thomas, and T. Newcomer-Johnson. The contribution of wildland fire emissions to deposition in the U S: implications for tree growth and survival in the Northwest. Environmental Research Letters. IOP Publishing LIMITED, Bristol, UK, 16(2): 024028, (2021).

This dataset has all the summary tables for the Figures and supplementary information in the Phelan et al. publication.

This dataset, derived from the National Forest Carbon Monitoring System (NFCMS), provides estimates of forest carbon stocks and fluxes in the form of aboveground woody biomass (AGB), total live biomass, total ecosystem carbon, aboveground coarse woody debris (CWD), and net ecosystem productivity (NEP) as a function of the number of years since the most recent disturbance (i.e., stand age) for forests of the conterminous U.S. at a 30 m resolution for the benchmark years 1990, 2000, and 2010. The data were derived from an inventory-constrained version of the Carnegie-Ames-Stanford Approach (CASA) carbon cycle process model that accounts for disturbance processes for each combination of forest type, site productivity, and pre-disturbance biomass. Also provided are the core model data inputs including the year of the most recent disturbance according to the North American Forest Dynamics (NAFD) and the Monitoring Trends in Burn Severity (MTBS) data products; the type of disturbance; biomass estimates from the year 2000 according to the National Biomass and Carbon Dataset (NBCD); forest-type group; a site productivity classification; and the number of years since stand-replacing disturbance. The data are useful for a wide range of applications including monitoring and reporting recent dynamics of forest carbon across the conterminous U.S., assessment of recent trends with attribution to disturbance and regrowth drivers, conservation planning, and assessment of climate change mitigation opportunities within the forest sector.