Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'

Worsham, H. Marshall; Wainwright, Haruko; Powell, Thomas; Falco, Nicola; Kueppers, Lara

doi:10.15485/2404585

Title: Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'

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Abstract

This package archives the core data used for analysis and inference in 'Abiotic influences on continuous conifer forest structure across a subalpine watershed' (Worsham et al., 2025). All data were collected in the East River, Washington Gulch, Slate River, and Coal Creek watersheds of Colorado. In the paper, we quantified the relative influence of climate, topographic, edaphic, and geologic factors on conifer stand structure and composition, and their functional relationships, at the watershed scale. We used waveform LiDAR data to derive spatially continuous stand structure metrics. We fused these with a species-level classification map to estimate tree species abundance. We applied generalized additive and generalized boosted models to evaluate the covariability of structural and compositional metrics with abiotic variables. The package contains the essential products required for reproducing our analysis and the tables and figures reported in the publication. The products comprise four classes: (1) geospatial data, (2) tabular data used for inferential analysis, (3) tabular data describing analytical results and performance statistics, and (4) a data user guide. (1) includes discretized waveform LiDAR data, locations and attributes of individual tree crowns, sampling locations and domain boundaries, a canopy height model, and raster files of estimated forest structural and compositionalmore »« less

Authors:

;

University of California Berkeley
Massachusetts Institute of Technology
The University of the South
Lawrence Berkeley National Laboratory

Publication Date:: Wed Jan 01 04:00:00 UTC 2025

DOE Contract Number:: AC02-05CH11231

Research Org.:: Integrating tree hydraulic trait, forest stand structure, and topographic controls on ecohydrologic function in a Rocky Mountain subalpine watershed

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES; Canopy_height: VARIABLE:CF; Climatic water deficit: VARIABLE:NONE; Discretized waveform LiDAR: VARIABLE:NONE; EARTH SCIENCE > AGRICULTURE > SOILS > HYDRAULIC CONDUCTIVITY: VARIABLE:GCMD; EARTH SCIENCE > AGRICULTURE > SOILS > SOIL MOISTURE/WATER CONTENT: VARIABLE:GCMD; EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WATER VAPOR > WATER VAPOR PROCESSES > EVAPOTRANSPIRATION: VARIABLE:GCMD; EARTH SCIENCE > BIOSPHERE > VEGETATION; EARTH SCIENCE > BIOSPHERE > VEGETATION > CANOPY CHARACTERISTICS: VARIABLE:GCMD; EARTH SCIENCE > BIOSPHERE > VEGETATION > CROWN: VARIABLE:GCMD; EARTH SCIENCE > BIOSPHERE > VEGETATION > FOREST COMPOSITION/VEGETATION STRUCTURE: VARIABLE:GCMD; EARTH SCIENCE > LAND SURFACE > SOILS > CATION EXCHANGE CAPACITY: VARIABLE:GCMD; EARTH SCIENCE > LAND SURFACE > SOILS > ORGANIC MATTER: VARIABLE:GCMD; EARTH SCIENCE > LAND SURFACE > SOILS > SOIL PH: VARIABLE:GCMD; EARTH SCIENCE > LAND SURFACE > SURFACE RADIATIVE PROPERTIES > REFLECTANCE: VARIABLE:GCMD; EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY; EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION > DIGITAL ELEVATION/TERRAIN MODEL (DEM): VARIABLE:GCMD; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SNOW/ICE > SNOW WATER EQUIVALENT: VARIABLE:GCMD; Forest composition; Forest structure; Generalized additive model performance: VARIABLE:NONE; Generalized boosted model performance: VARIABLE:NONE; Geologic substrate: VARIABLE:NONE; Individual tree crowns: VARIABLE:NONE; Individual tree detection algorithm performance: VARIABLE:NONE; LiDAR; NEON AOP; NEON Campaign 2018; Remote sensing; Sampling location identifiers: VARIABLE:NONE; Subalpine

OSTI Identifier:: 2404585

DOI:: https://doi.org/10.15485/2404585

Citation Formats


                    Worsham, H. Marshall, Wainwright, Haruko, Powell, Thomas, Falco, Nicola, and Kueppers, Lara. Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'.  United States: N. p., 2025. 
        Web.  doi:10.15485/2404585.

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                    Worsham, H. Marshall, Wainwright, Haruko, Powell, Thomas, Falco, Nicola, & Kueppers, Lara. Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'.  United States.  doi:https://doi.org/10.15485/2404585

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                    Worsham, H. Marshall, Wainwright, Haruko, Powell, Thomas, Falco, Nicola, and Kueppers, Lara. 2025.  
"Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'".  United States.  doi:https://doi.org/10.15485/2404585.  https://www.osti.gov/servlets/purl/2404585. Pub date:Wed Jan 01 04:00:00 UTC 2025

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@article{osti_2404585,

  title        = {Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'},

  author       = {Worsham, H. Marshall and Wainwright, Haruko and Powell, Thomas and Falco, Nicola and Kueppers, Lara},

  abstractNote = {This package archives the core data used for analysis and inference in 'Abiotic influences on continuous conifer forest structure across a subalpine watershed' (Worsham et al., 2025). All data were collected in the East River, Washington Gulch, Slate River, and Coal Creek watersheds of Colorado. In the paper, we quantified the relative influence of climate, topographic, edaphic, and geologic factors on conifer stand structure and composition, and their functional relationships, at the watershed scale. We used waveform LiDAR data to derive spatially continuous stand structure metrics. We fused these with a species-level classification map to estimate tree species abundance. We applied generalized additive and generalized boosted models to evaluate the covariability of structural and compositional metrics with abiotic variables. The package contains the essential products required for reproducing our analysis and the tables and figures reported in the publication. The products comprise four classes: (1) geospatial data, (2) tabular data used for inferential analysis, (3) tabular data describing analytical results and performance statistics, and (4) a data user guide. (1) includes discretized waveform LiDAR data, locations and attributes of individual tree crowns, sampling locations and domain boundaries, a canopy height model, and raster files of estimated forest structural and compositional metrics at 100 m grid scale. (2) includes all response and explanatory variable values applied in inferential models. Response variables include conifer forest stand density, basal area, 95th percentile height, quadratic mean diameter, and others. Explanatory variables include climatic water deficit, actual evapotranspiration, elevation, heat load, soil available water content, and others. (3) includes results of training and testing several individual tree detection (ITD) algorithms, as well as inferential modeling results. (4) is a PDF user guide for this data package, including detailed descriptions and data dictionaries for all files. The data package root contains 17 assets: 8 compressed tape archive (.tar.gz) files, 5 comma-separated values (.csv) files, 3 Geographic Tagged Image File Format (GeoTIFF) (.tif) files, and 1 Portable Document Format (.pdf) file. The compressed .tar.gz archives contain ESRI shapefiles (.shp) .tif, compressed LASer (.laz), and .csv files. The archives must first be decompressed using the widely distributed command-line software utility TAR. All other files, including constituent files within the .tar.gz archives, can be opened in the open-source R statistical computing environment. Alternatively, .csv files may also be read in any simple text editor software or Microsoft Excel. Geospatial files including .shp and .tif files can also be opened in GIS software, such as QGIS (open-source) or ESRI ArcGIS (proprietary). The .pdf Data User Guide can be read with Adobe Acrobat Reader or other compatible readers.},

  doi          = {10.15485/2404585},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Jan 01 04:00:00 UTC 2025},

  month        = {Wed Jan 01 04:00:00 UTC 2025}

}

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DOI: https://doi.org/10.15485/2404585

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