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A dataset cataloging product-specific human appropriation of net primary production (HANPP) in US counties

Suman PaudelDepartment of Environment and Society, Quinney College of Natural Resources, Utah State University, 5215 Old Main Hill, Logan, UT 84322-5215, USAKaeli MuellerDepartment of Environment and Society, Quinney College of Natural Resources, Utah State University, 5215 Old Main Hill, Logan, UT 84322-5215, USAGustavo A. Ovando-MontejoUtah State University-Blanding 576 West 200 South, Blanding, UT, USALauren TangoDepartment of Environment and Society, Quinney College of Natural Resources, Utah State University, 5215 Old Main Hill, Logan, UT 84322-5215, USARichard RushforthSchool of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011, USAChristopher L. LantDepartment of Environment and Society, Quinney College of Natural Resources, Utah State University, 5215 Old Main Hill, Logan, UT 84322-5215, USA
Data in Briefjournal2023en
ABI

Аннотация

This paper describes the dataset associated with the paper "Product-Specific Human Appropriation of Net Primary Production (HANPP) in US Counties" (Paudel et al., 2023). This dataset comprises human appropriation of net primary production (HANPP) values for 3101 counties in the conterminous US for the years 1997, 2002, 2007, and 2012. For this dataset, HANPP is the carbon content of specific crop, timber, and livestock grazing products appropriated by humans in a county in a year. To calculate HANPP, raw agricultural data were downloaded from public databases such as USDA-National Agricultural Statistics Service Quick Stats and Cropland Data Layer, US Forest Service Timber Product Output, and NPP data from MODIS. These data were processed in Microsoft Excel using stoichiometry derived from established scientific literature. HANPP was partitioned by year, county, product, used and unused and above- and below-ground. This complete dataset is published in Mendeley Data and the methods used to compile them are included to make our research well documented, reproducible, and useful for future studies.

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