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Mayes, Melanie

Publications and source records attributed to Mayes, Melanie.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Meteorological Conditions and Atmospheric Components Concentration in Urban Sites in Knoxville, USA. 2024

This dataset, which contains five csv files, reports several meteorological conditions such as temperature, wind speed, solar radiation, and net radiation measured in Cumberland Estates Park (CEP) and Socially Equal Energy Efficient Development (SEEED) sites in Knoxville, Tennessee, USA. Also, hourly concentration of particulate matter (PM) with different aerodynamic diameter and inorganic gases such as ozone and nitrogen dioxide measured in the two are included in this dataset. The concentrations of PM and inorganic gases were monitored using the MODULAIR, a low-cost sensor equipped with a solar power module. The measurement of the concentration of biogenic and anthropogenic volatile organic compounds (VOCs) of the two sites was determined using a High-Resolution Proton Transfer Reaction Time of Flight Mass Spectrometer (PTR-ToF-MS). The VOCs were collected using miniature canister (400 mL) equipped with female RAVEqc valve to 1/4” male compression fitting and an integrated passive air sampling kit. This work is a part of a larger study which investigates the impact of soil moisture and plant evapotranspiration on ambient temperature and relative humidity in several city parks in Knoxville, Tennessee.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

NIST: Soil Respiration, Moisture, Temperature, Chemistry; and Fine Root Measurements from a Transect Through a Forest Edge, Gaithersburg, Maryland, 2017-2021

This dataset contains soil respiration, moisture, temperature, and chemistry, as well as fine root measurements from the National Institute of Standards and Technology (NIST) Forested Optical Reference for Evaluating Sensor Technology (FOREST) research facility at Gaithersburg, Maryland. Measurements were taken at an existing transect array that begins in a grassy meadow, crosses a sharp forest edge, then a small stream, and finally extends upwards in the interior of the forest at the top of a ridge. There are 6 different landscape positions replicated across three transects in the array. Soil respiration was measured during growing seasons in 2017-2019 (2017-06-02 to 2020-02-27). Pedons (1 m3) were isolated from surrounding tree roots using trenching and a fabric to inhibit root ingrowth. Flux measurements inside the pedons were thus assumed to represent heterotrophic only respiration in 2019, and these fluxes were paired with nearby fluxes assumed to represent total respiration. Deep vertical probes measured volumetric moisture content and temperature at the same points in the array every 10 cm in depth to either 90 cm or 120 cm total depth, at 15 minute intervals, from 2019-2021 (2019-07-09 to 2021-09-10). Soil core samples were collected from each of the array points for three different months in early- to mid-2019 (2019-03-19 to 2019-07-10), at three depths each. Soils were analyzed for gravimetric moisture content; pH; total carbon, nitrogen, and phosphorus; texture; microbial biomass carbon, nitrogen, and phosphorus; extractable dissolved organic carbon, nitrogen, and phosphorus; extractable nitrate and ammonia; and extracellular hydrolytic enzyme activities. The fine roots were separated from the cores and segregated by plant functional type (grass or tree species) and if they were dead or alive. Fine roots were then measured for length, surface area, diameter, and dry mass. This dataset contains four data files in comma separated (*.csv) format. These data serve to deepen our understanding of root and soil processes at forest edges and in transitional zones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Interrelationships among methods of estimating microbial biomass across multiple soil orders and biomes: Supporting data

This dataset contains environmental and soil measurements from 18 different locations across the globe including the SPRUCE experiment site and multiple sampling depths, with 17 of these locations having samples processed between 2012-2013 and one location (SPRUCE) collected in 2021 and processed in 2022. Environmental measurements include: mean annual temperature, mean annual precipitation, and 30-day presampling temperature. Soil physicochemical measurements include: particle size analysis (PSA), pH, gravimetric moisture content (GMC), bulk soil carbon (C) and nitrogen (N), total organic C and N, C:N ratio, and dissolved organic carbon (DOC). Soil biological measurements include: microbial biomass carbon (MBC) measured through chloroform fumigation extraction (CFE), gene copy numbers (GCN) of bacteria, fungi, and archaea measured through quantitative polymerase chain reaction (qPCR), DNA yield measured through Nanodrop spectrophotometry, and phospholipid fatty acids (PLFA) of bacteria and fungi measured through PLFA analysis. This data set contains one file in comma separate (*.csv) format.

archaea gene copy number↗
DOE OSTI2020

Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site-level Applications of the CLM-Microbe Model

Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for the realistic projections of soil carbon (C) and climate dynamics. The CLM-Microbe model builds upon the CLM4.5 and explicitly represents two major soil microbial groups, fungi and bacteria. Based on the compiled time-series data of fungal (FBC) and bacterial (BBC) biomass C from nine biomes, we parameterized and validated the CLM-Microbe model, and further conducted sensitivity analysis and uncertainty analysis for simulating C cycling. The model performance was evaluated with mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) for relative change in FBC and BBC. The CLM-Microbe model is able to reasonably capture the seasonal dynamics of FBC and BBC across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland, with MAE < 0.49 for FBC and <0.36 for BBC and RMSE <0.52 FBC and <0.39 for BBC, while R2 values are relatively smaller in some biomes (e.g., shrub) due to small sample sizes. We found good consistencies between simulated and observed FBC (R 2 =0.70, P<0.001) and BBC (R 2 =0.26, P<0.05) on average across biomes, but the model is not able to fully capture the large variation in observed FBC and BBC. Sensitivity analysis shows the most critical parameters are turnover rate, carbon-to-nitrogen ratio of fungi and bacteria, and microbial assimilation efficiency. This study confirms that the explicit representation of soil microbial mechanisms enhances model performance in simulating C variables such as heterotrophic respiration and soil organic C density. The further application of the CLM-Microbe model would deepen our understanding of microbial contributions to the global C cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Porewater data across a catena in the Luquillo Experimental Forest, Puerto Rico.

Landscape topography can influence biogeochemical processes in wet tropical forest soils. This dataset contains porewater concentrations of organic acid (acetate) from 2018 (February 22 to November 14) across a catena in the Luquillo Experimental Forest (LEF), Puerto Rico. The attached CSV file contains information on sampling date, location (El Verde field station) in LEF, topographic positions (ridge, slope, and valley, respectively), depth (unit: cm), and acetate concentration (unit: µM). Porewater concentrations of acetate were lower in the valley as compared to the ridge and slope topographic positions. This dataset can facilitate our understanding of the biogeochemical cycling of carbon and nutrient associated with complex topography in wet tropical forest soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Soil chemistry data across a catena in the Luquillo Experimental Forest, Puerto Rico

Landscape topography can influence biogeochemical processes across the wet tropical forest soils. This dataset contains soil chemistry data such as pH and dissolved organic carbon (DOC) from April 1, 2017 to May 1, 2018 across a catena in the Luquillo Experimental Forest, Puerto Rico. The attached CSV file contains information on sampling date, location (El Verde field station) in LEF, topographic positions (ridge, slope, and valley, respectively), field replicate number, laboratory replicate number, water extractable pH, CaCl2 extractable pH, and DOC (unit: mg/g). Overall, soil pH values were highest in the valley, followed by slope, and lowest in the ridge topographic positions. However, DOC values followed the opposite trend: ridge>slope>valley. This dataset can facilitate our understanding of the biogeochemical cycling of carbon and nutrient associated with complex topography in wet tropical forest soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Soil Chamber Fluxes (CO2 and CH4) across a catena in the Luquillo Experimental Forest, Puerto Rico

Wet tropical forest soils contribute significantly to global emissions of carbon dioxide (CO2) and methane (CH4). Landscape topography largely influences the rate of CO2 versus CH4 emissions from wet tropical forest soils. This dataset contains soil chamber fluxes of CO2 and CH4 from 2016 (April 5 through July 18) across a catena in the Luquillo Experimental Forest, Puerto Rico. Soil CO2 fluxes followed the trend of ridge>slope>valley. However, soil CH4 emissions followed the opposite trend, where valley soils served as the major source of CH4 emissions. This dataset can improve our understanding of greenhouse gas (CO2 and CH4) emissions associated with complex topography in wet tropical forest soils.

54 ENVIRONMENTAL SCIENCES↗