PhenoCam images from ARSLTARMDCR site, Caroline County, Maryland, USA since 2017
This data set consists of repeat digital imagery from a tower-mounted digital camera (hereafter, PhenoCam) maintained by the USDA-ARS Hydrology Remote Sensing Laboratory (HRSL) in the Lower Chesapeake Bay (LCB) watershed. HRSL is a member of the PhenoCam network, which has as its mission to serve as a long-term, continental-scale, phenological observatory. Imagery is uploaded to the PhenoCam server every 30 minutes.
PhenoCam images from ARSOPE3LTAR site, Beltsville Agricultural Research Center, Maryland, USA since 2017
This data set consists of repeat digital imagery from a tower-mounted digital camera (hereafter, PhenoCam) maintained by the USDA-ARS Hydrology Remote Sensing Laboratory (HRSL) in the Lower Chesapeake Bay (LCB) watershed. HRSL is a member of the PhenoCam network, which has as its mission to serve as a long-term, continental-scale, phenological observatory. Imagery is uploaded to the PhenoCam server every 30 minutes.
Comparison of methods to detect low levels of Salmonella enterica in surface waters to support antimicrobial resistance surveillance efforts performed in multiple laboratories
Identifying and developing effective and sensitive detection methods for antimicrobial resistant Salmonella enterica from surface water is a goal of the U.S. National Antimicrobial Resistance Monitoring System (NARMS). No specific microbiological methods used in surveillance efforts for Salmonella enterica or antimicrobial resistant S. enterica in water have been standardized or reported in the U.S. Here we describe a multi-laboratory evaluation of four methods, bulk water enrichment (BW), vertical Modified Moore Swab (VMMS), modified Standard Method 9260.B3 (SM), and dead-end ultrafiltration (DEUF), to recover S. enterica from surface water.
- 6x xlsx
Data and code from: Synergistic soil, land use, and climate influences on wind erosion on the Colorado Plateau: Implications for management - v2
This dataset includes code and data to recreate analysis from the manuscript "Nauman, T. W., Munson, S. M., Dhital, S., Webb, N. P., & Duniway, M. C. (2023). Synergistic soil, land use, and climate influences on wind erosion on the Colorado Plateau: Implications for management. Science of The Total Environment (p. 164605). https://doi.org/10.1016/j.scitotenv.2023.164605". This includes R statistical code, aeolian monitoring data and associated soil, land use, and climate explanatory data for each site, and a raster map showing areas modeled to have more sediment transport.
- 2x zip
Data and models from: A novel design method for customized visual delimiting surveys for plant pests based on transects and scouting
Models were used in the manuscript "A novel design method for customized visual delimiting surveys for plant pests based on transects and scouting," by Barney P. Caton, Godshen R. Pallipparambil, and Hui Fang. This paper describes a novel approach for designing custom visual delimitation surveys, called ‘Delimitation via Transect Data and Scouting,’ or DTDS.