cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15482/usda.adc/28256648
title: Groundwater Nitrogen and Phosphorus data

description: This data set contains NO3-N, NH4-N, PO4-P, and Total Nitrogen (TN) concentration (mg/L) measurements from shallow groundwater (GW) samples collected continuously over a three year period. Additional GW data collected included Ec, pH, depth to water table and GW resistance (Ohms). The GW analyzed in this dataset was collected in Beltsville, MD at the Central Maryland Research and Education Center (CMREC) (39°00'46.0"N 76°49'35.7"W). Maryland has a temperate climate with humid dry summers and wet cold winters. The groundwater collection was part of a greater experiment utilizing two different cover crop treatments (enhanced and standard) in two different cash crop residues (Corn and Soybean). The enhanced cover crop treatment utilized interseeding rye, radish and clover into standing cash crops in early fall and then late termination of the cover crop mixture after the cash crops had already been planted. Conversely, the standard cover crop treatment planted rye monoculture in late fall after cash crop harvest and terminated the cover crops in early spring prior to cash crop planting. The data in this data set was collected biweekly from July 2021 until May 2024 using an array of 14 hand dug groundwater wells. Four wells were installed in each cover crop treatment type, two were installed in a permanent grass control strip, and four wells were installed in the riparian forest patch adjacent to the study field. During each sampling event, depth to water table and GW resistivity were measured using a handheld Ohms meter. The wells were purged, allowed time to recharge, and then a 70mL sub-sample was taken back to the lab at the University of Maryland College Park. The Ec (uS/cm) and pH of each sub-sample were measured and then the sub-sample was filtered through a 0.45um filter paper. After filtration the inorganic N concentrations, NO3-N and NH4-N, were determined colorimetrically using the Salicylate Method and the Endol Blue Method respectively. The inorganic P concentration, PO4-P, was determined using the Molybdate colorimetric test. The filtrate was also analyzed for the TN concentration by mixing the filtrate with a strong alkaline persulfate solution and heating the mixture for 1hr at 120 deg C under 16kpa in an autoclave. Following this, the mixture was analyzed for NO3-N and using the respective NO3-N colorimetric methods, giving the total dissolved N concentration. All colorimetric analysis was performed using a DU 7000 Series Beckman Coulter Spectrophotometer and absorbance readings were converted into concentration (mg/L) using equations derived from the standard curves. <br>NO3-N (mg/L) = 135.5*absorbanceNH4-N (mg/L) = 55.7*absorbanceTN (mg/L) = 146.7*absorbance - 1.447PO4-P (mg/L) = 1.764*absorbance + 0.007
DOI: 10.15482/usda.adc/28256648.v1
title: Groundwater Nitrogen and Phosphorus data

description: This data set contains NO3-N, NH4-N, PO4-P, and Total Nitrogen (TN) concentration (mg/L) measurements from shallow groundwater (GW) samples collected continuously over a three year period. Additional GW data collected included Ec, pH, depth to water table and GW resistance (Ohms). The GW analyzed in this dataset was collected in Beltsville, MD at the Central Maryland Research and Education Center (CMREC) (39°00'46.0"N 76°49'35.7"W). Maryland has a temperate climate with humid dry summers and wet cold winters. The groundwater collection was part of a greater experiment utilizing two different cover crop treatments (enhanced and standard) in two different cash crop residues (Corn and Soybean). The enhanced cover crop treatment utilized interseeding rye, radish and clover into standing cash crops in early fall and then late termination of the cover crop mixture after the cash crops had already been planted. Conversely, the standard cover crop treatment planted rye monoculture in late fall after cash crop harvest and terminated the cover crops in early spring prior to cash crop planting. The data in this data set was collected biweekly from July 2021 until May 2024 using an array of 14 hand dug groundwater wells. Four wells were installed in each cover crop treatment type, two were installed in a permanent grass control strip, and four wells were installed in the riparian forest patch adjacent to the study field. During each sampling event, depth to water table and GW resistivity were measured using a handheld Ohms meter. The wells were purged, allowed time to recharge, and then a 70mL sub-sample was taken back to the lab at the University of Maryland College Park. The Ec (uS/cm) and pH of each sub-sample were measured and then the sub-sample was filtered through a 0.45um filter paper. After filtration the inorganic N concentrations, NO3-N and NH4-N, were determined colorimetrically using the Salicylate Method and the Endol Blue Method respectively. The inorganic P concentration, PO4-P, was determined using the Molybdate colorimetric test. The filtrate was also analyzed for the TN concentration by mixing the filtrate with a strong alkaline persulfate solution and heating the mixture for 1hr at 120 deg C under 16kpa in an autoclave. Following this, the mixture was analyzed for NO3-N and using the respective NO3-N colorimetric methods, giving the total dissolved N concentration. All colorimetric analysis was performed using a DU 7000 Series Beckman Coulter Spectrophotometer and absorbance readings were converted into concentration (mg/L) using equations derived from the standard curves. <br>NO3-N (mg/L) = 135.5*absorbanceNH4-N (mg/L) = 55.7*absorbanceTN (mg/L) = 146.7*absorbance - 1.447PO4-P (mg/L) = 1.764*absorbance + 0.007
DOI: 10.15482/usda.adc/28339583
title: Data from: Phenological variation associates with the stability of fruit quality traits in cultivated tetraploid blueberry

description: Data of twelve fruit quality traits and three phenology-related traits collected in 2020, 2021, 2022, and 2023 seasons from 187 genotypes of southern high bush blueberry established in Poplarville, MS, USA (30.8402°N, 89.5342°W) in a sandy loam soil. Fruit quality data include berry weight, berry size, firmness, pH, total polyphenol, citric acid, malic acid, total acids, D-glucose, D-fructose, total Glucose, and total sugar content. The phenology-related traits include flowering and ripening dates, and fruit development period.<br>
DOI: 10.15482/usda.adc/28339583.v1
title: Data from: Phenological variation associates with the stability of fruit quality traits in cultivated tetraploid blueberry

description: Data of twelve fruit quality traits and three phenology-related traits collected in 2020, 2021, 2022, and 2023 seasons from 187 genotypes of southern high bush blueberry established in Poplarville, MS, USA (30.8402°N, 89.5342°W) in a sandy loam soil. Fruit quality data include berry weight, berry size, firmness, pH, total polyphenol, citric acid, malic acid, total acids, D-glucose, D-fructose, total Glucose, and total sugar content. The phenology-related traits include flowering and ripening dates, and fruit development period.<br>
DOI: 10.15482/usda.adc/28235093
title: Data from: The Effect of the Frequency of Prescribed Burning on Annual Soil Carbon Balance in a Loblolly-Shortleaf Pine Forest in East Texas

description: This is the dataset for the manuscript "The Effect of the Frequency of Prescribed Burning on Annual Soil Carbon Balance in a Loblolly-Shortleaf Pine Forest in East Texas". This study reports the effect of prescribed burning frequency on net soil C balance in three loblolly-shortleaf pine stands with different burn frequencies over the past 20 years (with low-intensity ground fires applied (i) annually, (ii) intermittently (every 2-4 years), and (iii) not at all) in Cook's Branch Conservancy, Texas, USA (30.2919 N, 95.6989 W), located in a humid subtropical climate. The submitted data were collected monthly at study plots (each 730 m<sup>2</sup>) located in each stand (4 study plots per stand) between 2020 and 2021. Specifically, soil respiration were measured over five pairs of control and root exclusion collars per study plot. Litterfall production was sampled using litter traps with a surface area of 0.86 m<sup>2</sup> at a height of 0.5 m from three locations within each study plot. Soil samples were collected using a soil core (5.2 cm diameter with 33 cm length) from five locations within each study plot. Subsequently, fine root were extracted using a 1-mm sieve, and then then sorted based on diameter into fine roots (&lt; 2 mm diameter) and coarse roots (&gt; 2 mm diameter), and further categorized as dead and live roots based on color and texture.
DOI: 10.15482/usda.adc/28235093.v1
title: Data from: The Effect of the Frequency of Prescribed Burning on Annual Soil Carbon Balance in a Loblolly-Shortleaf Pine Forest in East Texas

description: This is the dataset for the manuscript "The Effect of the Frequency of Prescribed Burning on Annual Soil Carbon Balance in a Loblolly-Shortleaf Pine Forest in East Texas". This study reports the effect of prescribed burning frequency on net soil C balance in three loblolly-shortleaf pine stands with different burn frequencies over the past 20 years (with low-intensity ground fires applied (i) annually, (ii) intermittently (every 2-4 years), and (iii) not at all) in Cook's Branch Conservancy, Texas, USA (30.2919 N, 95.6989 W), located in a humid subtropical climate. The submitted data were collected monthly at study plots (each 730 m<sup>2</sup>) located in each stand (4 study plots per stand) between 2020 and 2021. Specifically, soil respiration were measured over five pairs of control and root exclusion collars per study plot. Litterfall production was sampled using litter traps with a surface area of 0.86 m<sup>2</sup> at a height of 0.5 m from three locations within each study plot. Soil samples were collected using a soil core (5.2 cm diameter with 33 cm length) from five locations within each study plot. Subsequently, fine root were extracted using a 1-mm sieve, and then then sorted based on diameter into fine roots (&lt; 2 mm diameter) and coarse roots (&gt; 2 mm diameter), and further categorized as dead and live roots based on color and texture.
DOI: 10.15482/usda.adc/28235093.v2
title: Data from: The Effect of the Frequency of Prescribed Burning on Annual Soil Carbon Balance in a Loblolly-Shortleaf Pine Forest in East Texas

description: This is the dataset for the manuscript "The Effect of the Frequency of Prescribed Burning on Annual Soil Carbon Balance in a Loblolly-Shortleaf Pine Forest in East Texas". This study reports the effect of prescribed burning frequency on net soil C balance in three loblolly-shortleaf pine stands with different burn frequencies over the past 20 years (with low-intensity ground fires applied (i) annually, (ii) intermittently (every 2-4 years), and (iii) not at all) in Cook's Branch Conservancy, Texas, USA (30.2919 N, 95.6989 W), located in a humid subtropical climate. The submitted data were collected monthly at study plots (each 730 m<sup>2</sup>) located in each stand (4 study plots per stand) between 2020 and 2021. Specifically, soil respiration were measured over five pairs of control and root exclusion collars per study plot. Litterfall production was sampled using litter traps with a surface area of 0.86 m<sup>2</sup> at a height of 0.5 m from three locations within each study plot. Soil samples were collected using a soil core (5.2 cm diameter with 33 cm length) from five locations within each study plot. Subsequently, fine root were extracted using a 1-mm sieve, and then then sorted based on diameter into fine roots (&lt; 2 mm diameter) and coarse roots (&gt; 2 mm diameter), and further categorized as dead and live roots based on color and texture.
DOI: 10.15482/usda.adc/28330952
title: Johnston Draw (Idaho) High Resolution Burn Severity Map 2023

description: Accurate mapping of rangeland burn severity is the first step towards managing and mitigating post-fire consequences, but the spatial resolution of freely available, remotely-sensed products is often too coarse to effectively represent the complexity of burned rangelands. We trained a support vector machine to classify burn severity over Johnston Draw (a 1.8 square kilometer prescribed fire study area in southwestern Idaho) at very high spatial resolution (0.5-meter) using post-fire pan-sharpened 8-band Worldview 3 imagery, co-registered with a complimentary pre-fire vegetation map. Burn severity map accuracy was quite high at 88.3% when validated at 1000 randomly distributed points within the study area. In 2023 alone the Bureau of Land Management treated fuels in over 1.2 million acres of rangeland, a quarter of which was treated with prescribed fire, and managing postfire consequences like soil erosion and vegetation recovery requires high-resolution burn severity mapping to inform mitigation on these vast acreages.
DOI: 10.15482/usda.adc/28330952.v1
title: Johnston Draw (Idaho) High Resolution Burn Severity Map 2023

description: Accurate mapping of rangeland burn severity is the first step towards managing and mitigating post-fire consequences, but the spatial resolution of freely available, remotely-sensed products is often too coarse to effectively represent the complexity of burned rangelands. We trained a support vector machine to classify burn severity over Johnston Draw (a 1.8 square kilometer prescribed fire study area in southwestern Idaho) at very high spatial resolution (0.5-meter) using post-fire pan-sharpened 8-band Worldview 3 imagery, co-registered with a complimentary pre-fire vegetation map. Burn severity map accuracy was quite high at 88.3% when validated at 1000 randomly distributed points within the study area. In 2023 alone the Bureau of Land Management treated fuels in over 1.2 million acres of rangeland, a quarter of which was treated with prescribed fire, and managing postfire consequences like soil erosion and vegetation recovery requires high-resolution burn severity mapping to inform mitigation on these vast acreages.
DOI: 10.15482/usda.adc/28304213
title: RapidFEM4D: aboveground biomass density maps for post-Hurricane Ian forest monitoring in Florida

description: This dataset provides spatially aboveground biomass density (AGBD) maps from 2022 to 2024, created to assess the impacts of Hurricane Ian on forest ecosystems in Florida. The Hurricane Ian made landfall in Florida on September 28, 2022, as a powerful Category 4 and was the second major storm of the 2022 Atlantic hurricane season.<br><br>Field data were collected in situ during the spring of 2023 and 2024 across 27 plots, each measuring 25 × 25 meters. These plots were strategically distributed to represent a full gradient of AGBD. Within each plot, tree species were identified, and diameter at breast height (DBH) and height measurements were recorded for all individuals with DBH greater than 10 cm. AGBD was estimated for each tree based on species-specific allometric equations, incorporating species identity, DBH, and tree height.<br><br>To generate the AGBD maps, we integrated multiple remote sensing datasets, including GEDI L4A AGBD estimates, Harmonized Landsat-Sentinel (HLS) optical imagery, and Sentinel-1C radar data, along with other ancillary layers, totaling 245 predictor variables. A random forest regression model was trained using field data and predictor layers to estimate AGBD, which was then upscaled to create a continuous AGBD map for the study area.<br>The final AGBD prediction for each year was obtained by averaging results from multiple bootstrap iterations.. Additionally, uncertainty maps were derived by calculating the standard deviation of predictions across these iterations, providing insight into spatial variability and model confidence.Resources in this dataset:AGBD predictions for consecutive years: RapidFEM4D_AGBD_prediction_2022.tif; RapidFEM4D_AGBD_prediction_2023.tif, and RapidFEM4D_AGBD_prediction_2024.tifMap uncertainties for the respective AGBD predictions: RapidFEM4D_AGBD_uncertainty_2022.tif; RapidFEM4D_AGBD_uncertainty_2023.tif, and RapidFEM4D_AGBD_uncertainty_2024.tifField data used for technical validation: RapidFEM4D_field_data.xlsx<br>
DOI: 10.15482/usda.adc/28304213.v1
title: RapidFEM4D: aboveground biomass density maps for post-Hurricane Ian forest monitoring in Florida

description: This dataset provides spatially aboveground biomass density (AGBD) maps from 2022 to 2024, created to assess the impacts of Hurricane Ian on forest ecosystems in Florida. The Hurricane Ian made landfall in Florida on September 28, 2022, as a powerful Category 4 and was the second major storm of the 2022 Atlantic hurricane season.<br><br>Field data were collected in situ during the spring of 2023 and 2024 across 27 plots, each measuring 25 × 25 meters. These plots were strategically distributed to represent a full gradient of AGBD. Within each plot, tree species were identified, and diameter at breast height (DBH) and height measurements were recorded for all individuals with DBH greater than 10 cm. AGBD was estimated for each tree based on species-specific allometric equations, incorporating species identity, DBH, and tree height.<br><br>To generate the AGBD maps, we integrated multiple remote sensing datasets, including GEDI L4A AGBD estimates, Harmonized Landsat-Sentinel (HLS) optical imagery, and Sentinel-1C radar data, along with other ancillary layers, totaling 245 predictor variables. A random forest regression model was trained using field data and predictor layers to estimate AGBD, which was then upscaled to create a continuous AGBD map for the study area.<br>The final AGBD prediction for each year was obtained by averaging results from multiple bootstrap iterations.. Additionally, uncertainty maps were derived by calculating the standard deviation of predictions across these iterations, providing insight into spatial variability and model confidence.Resources in this dataset:AGBD predictions for consecutive years: RapidFEM4D_AGBD_prediction_2022.tif; RapidFEM4D_AGBD_prediction_2023.tif, and RapidFEM4D_AGBD_prediction_2024.tifMap uncertainties for the respective AGBD predictions: RapidFEM4D_AGBD_uncertainty_2022.tif; RapidFEM4D_AGBD_uncertainty_2023.tif, and RapidFEM4D_AGBD_uncertainty_2024.tifField data used for technical validation: RapidFEM4D_field_data.xlsx<br>
DOI: 10.15482/usda.adc/28334207
title: A ‘Chambourcin’ x <i>Vitis vinifera</i> ‘Cabernet Sauvignon’ mapping population to genetically map powdery mildew resistance and other traits

description: This Vitis mapping population consisted of F1 hybrids derived from a cross between female parent ‘Chambourcin’ with a pollen donor ‘Cabernet Sauvignon’. These hybrids were planted at the Missouri State Fruit Experiment Station (MSFES), Mountain Grove, MO 65711 (latitude 37°09'14.8"N; longitude 92°14'46.8" W). An initial planting in 2014 contained 100 progeny, followed by 26 progeny in 2015 and 180 progeny in 2016. The data set includes microsatellite (SSR) and core genome rhAmpSeq haplotype marker data that was used to develop genetic map and phenotype data generated from Blackbird microscopy robot analysis of grapevine powdery mildew (<i>Erysiphe necator</i>) severity.
DOI: 10.15482/usda.adc/28334207.v1
title: A ‘Chambourcin’ x <i>Vitis vinifera</i> ‘Cabernet Sauvignon’ mapping population to genetically map powdery mildew resistance and other traits

description: This Vitis mapping population consisted of F1 hybrids derived from a cross between female parent ‘Chambourcin’ with a pollen donor ‘Cabernet Sauvignon’. These hybrids were planted at the Missouri State Fruit Experiment Station (MSFES), Mountain Grove, MO 65711 (latitude 37°09'14.8"N; longitude 92°14'46.8" W). An initial planting in 2014 contained 100 progeny, followed by 26 progeny in 2015 and 180 progeny in 2016. The data set includes microsatellite (SSR) and core genome rhAmpSeq haplotype marker data that was used to develop genetic map and phenotype data generated from Blackbird microscopy robot analysis of grapevine powdery mildew (<i>Erysiphe necator</i>) severity.
DOI: 10.15482/usda.adc/29460167
title: Data from: Soil health benefits of compost persist two decades after single application to winter wheat

description: Long-term published dataset containing observations on soil health and yield following a one-time compost application in a dryland wheat fallow system. The effectiveness of frequent compost application in improving soil health is well-documented. Less is known on the long-term effects of infrequent compost application to semiarid soils. Compost made of dairy manure and straw bedding was applied once in a dryland organic hard red winter wheat (Triticum aestivum L. emend. Thell.)–fallow system at 50 megagrams per hectare (Mg ha−1) dry weight in 1994 in a randomized complete block design with three replicates. Twenty-eight years later, yields in composted plots (1.4 Mg ha−1) remained higher (p &lt; 0.1) than in control plots (0.79 Mg ha−1). Plant-available phosphorous, acid phosphatase activity (ACP), and total nitrogen were higher in composted plots by 143%, 37%, and 29%. Soil organic carbon (SOC) and dehydrogenase enzyme activity were greater by 25% and 20% with compost compared to the control, as were aggregate stability determined using SLAKES method, autoclave-extractable protein, and carbon dioxide over 96 hours (CO2-96 h) by 143%, 22%, and 16%. Soil extractable K and Zn also increased with compost application. The interaction of ACP and estimated evapotranspiration (ET) emerged as a pivotal factor in explaining the variation in yield. These findings suggest that growers may see some yield improvements from periodic compost applications to dryland organic winter wheat–fallow systems. This strategy could help rebuild SOC and partially counter the challenges of low and variable precipitation.
DOI: 10.15482/usda.adc/29460167.v1
title: Data from: Soil health benefits of compost persist two decades after single application to winter wheat

description: Long-term published dataset containing observations on soil health and yield following a one-time compost application in a dryland wheat fallow system. The effectiveness of frequent compost application in improving soil health is well-documented. Less is known on the long-term effects of infrequent compost application to semiarid soils. Compost made of dairy manure and straw bedding was applied once in a dryland organic hard red winter wheat (Triticum aestivum L. emend. Thell.)–fallow system at 50 megagrams per hectare (Mg ha−1) dry weight in 1994 in a randomized complete block design with three replicates. Twenty-eight years later, yields in composted plots (1.4 Mg ha−1) remained higher (p &lt; 0.1) than in control plots (0.79 Mg ha−1). Plant-available phosphorous, acid phosphatase activity (ACP), and total nitrogen were higher in composted plots by 143%, 37%, and 29%. Soil organic carbon (SOC) and dehydrogenase enzyme activity were greater by 25% and 20% with compost compared to the control, as were aggregate stability determined using SLAKES method, autoclave-extractable protein, and carbon dioxide over 96 hours (CO2-96 h) by 143%, 22%, and 16%. Soil extractable K and Zn also increased with compost application. The interaction of ACP and estimated evapotranspiration (ET) emerged as a pivotal factor in explaining the variation in yield. These findings suggest that growers may see some yield improvements from periodic compost applications to dryland organic winter wheat–fallow systems. This strategy could help rebuild SOC and partially counter the challenges of low and variable precipitation.