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Cross-CZO -- Topographic Carbon Storage, GIS/Map Data, LiDAR, Land Cover -- Betasso -- (2010-2010)


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Abstract

The 'Stems' data are from an individual tree segmentation (Swetnam and Falk 2014) derived from the 2010 snow-off lidar and biomass-carbon allometric equations. The purpose of the dataset is to evaluate the distribution of aboveground carbon across an elevation gradient in temperature and precipitation.

The '10m Topo points' data are derived from a bare earth digital elevation model (DEM) generated from the 2010 snow-off lidar flight, these include the topographic metrics and the biomass-carbon for each pixel derived from the sum of STEMS. The purpose of the dataset is to evaluate the distribution of aboveground carbon across an elevation gradient in temperature and precipitation.

A total of three catchments in Boulder Creek were analyzed: Como Creek, Gordon Gulch, and Betasso Preserve.

Significance Statement:
Forest carbon reservoirs in complex terrain along an elevation-climate gradient spanning an 11 Celsius range in mean annual temperature (MAT) and a 50 cm yr-1 range in mean annual precipitation (MAP) did not exhibit the expected response of increasing in size with greater MAP and idealized MAT. Within catchments, the distribution of mean and peak carbon storage doubled in size for valleys versus ridges. These results suggest spatial variations in carbon storage relate more to topographically mediated water availability, as well as aspect (energy-balance) and topographic curvature (a proxy for soil depth and depth to ground water), than elevation-climate gradients. Consequently, lateral redistribution of precipitation across topographic position may either moderate or exacerbate regional climatic controls over ecosystem productivity and tree-level responses during drought.

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Resource Level Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Place/Area Name:
Betasso, Betasso
North Latitude
40.0157°
East Longitude
-105.3338°
South Latitude
40.0067°
West Longitude
-105.3437°

Temporal

Start Date:
End Date:

Content

ReadMe.md

Cross-CZO -- Topographic Carbon Storage, GIS/Map Data, LiDAR, Land Cover -- Betasso -- (2010)


OVERVIEW

Description/Abstract

The 'Stems' data are from an individual tree segmentation (Swetnam and Falk 2014) derived from the 2010 snow-off lidar and biomass-carbon allometric equations. The purpose of the dataset is to evaluate the distribution of aboveground carbon across an elevation gradient in temperature and precipitation.

The '10m Topo points' data are derived from a bare earth digital elevation model (DEM) generated from the 2010 snow-off lidar flight, these include the topographic metrics and the biomass-carbon for each pixel derived from the sum of STEMS. The purpose of the dataset is to evaluate the distribution of aboveground carbon across an elevation gradient in temperature and precipitation.

A total of three catchments in Boulder Creek were analyzed: Como Creek, Gordon Gulch, and Betasso Preserve.

Significance Statement:

Forest carbon reservoirs in complex terrain along an elevation-climate gradient spanning an 11 Celsius range in mean annual temperature (MAT) and a 50 cm yr-1 range in mean annual precipitation (MAP) did not exhibit the expected response of increasing in size with greater MAP and idealized MAT. Within catchments, the distribution of mean and peak carbon storage doubled in size for valleys versus ridges. These results suggest spatial variations in carbon storage relate more to topographically mediated water availability, as well as aspect (energy-balance) and topographic curvature (a proxy for soil depth and depth to ground water), than elevation-climate gradients. Consequently, lateral redistribution of precipitation across topographic position may either moderate or exacerbate regional climatic controls over ecosystem productivity and tree-level responses during drought.

Creator/Author

Tyson Lee Swetnam|Paul Brooks|Holly Barnard|Adrian Harpold|Erika Gallo

CZOs

Boulder|Catalina-Jemez

Contact

Tyson Lee Swetnam, University of Arizona, 1064 E Lowell St Tucson AZ 85721, tswetnam@email.arizona.edu

Subtitle

Topographic Carbon Storage




SUBJECTS

Disciplines

GIS / Remote Sensing|Biology / Ecology|Geomorphology|Hydrology

Topics

Topographic Carbon Storage|GIS/Map Data|LiDAR|Land Cover

Keywords

GIS|Topography|Morphometry|Carbon|Biomass

Variables

X|Y|ID|UTME|UTMN|HT|PRED|AREA|EQDIAM|MAJAX|MINAX|MAXHT|MINHT|MEANHT|EVT_Boulder|xmin|xmax|ymin|ymax|sten_num|agc_sum|nrmht|slope|aspect|cata|planc|twi|vllydpth|tpi|slpht|genc|midslp|dem|stdht|profc

Variables ODM2

Biomass, above-ground|Area|Aspect|Watershed deliniation|Digital elevation model|Tree crown measurement|Vegetation type|Lidar|Height|Recorder code|Slope|Curvature|Topographic Position Index (TPI)|Topographic wetness index (TWI)|Distance




TEMPORAL

Date Start

2010-05-01

Date End

2010-05-01




SPATIAL

Field Areas

Betasso

Location

Betasso

North latitude

40.01572

South latitude

40.006679999999996

West longitude

-105.34369646922146

East longitude

-105.33378




REFERENCE

Citation

Swetnam and Falk, Application of metabolic scaling theory to reduce error in local maxima tree segmentation from aerial LiDAR, 2014, Forest Ecology and Management, 323, 158-167.

Publications using this data

Swetnam T.L. and Falk D.A. (2014). Application of Metabolic Scaling Theory to reduce error in local maxima tree segmentation from aerial LiDAR. Forest Ecology and Management 323: 158–167 http://dx.doi.org/10.1016/j.foreco.2014.03.016

CZO ID

5131

Award Grant Numbers

Department of Energy - DE-SC0006968

National Science Foundation - NSF-1331408




COMMENTS

Comments

Description of the data production are given in the Supplemental Information in Swetnam et al. (in review) and are online at: href=https://pods.cyverse.org/wiki/display/~tyson_swetnam/Mapping+aboveground+biomass+from+individual+tree+segmentation+data> Mapping aboveground biomass from individual tree segmentation data

Additional Metadata

Name Value
czos Boulder, Catalina-Jemez
czo_id 5131
citation Swetnam and Falk, Application of metabolic scaling theory to reduce error in local maxima tree segmentation from aerial LiDAR, 2014, Forest Ecology and Management, 323, 158-167.
comments Description of the data production are given in the Supplemental Information in Swetnam et al. (in review) and are online at: href=https://pods.cyverse.org/wiki/display/~tyson_swetnam/Mapping+aboveground+biomass+from+individual+tree+segmentation+data> Mapping aboveground biomass from individual tree segmentation data
keywords GIS, Topography, Morphometry, Carbon, Biomass
subtitle Topographic Carbon Storage
variables X, Y, ID, UTME, UTMN, HT, PRED, AREA, EQDIAM, MAJAX, MINAX, MAXHT, MINHT, MEANHT, EVT_Boulder, xmin, xmax, ymin, ymax, sten_num, agc_sum, nrmht, slope, aspect, cata, planc, twi, vllydpth, tpi, slpht, genc, midslp, dem, stdht, profc
disciplines GIS / Remote Sensing, Biology / Ecology, Geomorphology, Hydrology

Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
Department of Energy DE-SC0006968
National Science Foundation NSF-1331408

How to Cite

Swetnam, T. L., P. Brooks, H. Barnard, A. Harpold, E. Gallo (2019). Cross-CZO -- Topographic Carbon Storage, GIS/Map Data, LiDAR, Land Cover -- Betasso -- (2010-2010), HydroShare, http://www.hydroshare.org/resource/21a405f32af346e19ddd1c2b1c694b2c

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
CC-BY

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