Seasonal changes of trace elements, nutrients, dissolved organic matter, and coastal acidification over the largest oyster reef in the Western Mississippi Sound, USA.

Seasonal changes of trace elements, nutrients, dissolved organic matter (DOM), and carbonate system parameters were evaluated over the largest deteriorating oyster reef in the Western Mississippi Sound using data collected during spring, summer, and winter of 2018, and summer of 2019. Higher concentrations of Pb (224%), Cu (211%), Zn (2400%), and Ca (240%) were observed during winter of 2018 compared to summer 2019. Phosphate and ammonia concentrations were higher (> 800%) during both summers of 2018 and 2019 than winter of 2018. Among the three distinct DOM components identified, two terrestrial humic-like components were more abundant during both spring (12% and 36%) and summer (11% and 33%) of 2018 than winter of 2018, implying a relatively lesser supply of humic-like components from terrestrial sources during winter. On the other hand, the protein-like component was more abundant during summer of 2019 compared to rest of the study period, suggesting a higher rate of autochthonous production during summer 2019. In addition, to their significant depth-wise variation, ocean acidification parameters including pH, pCO2, CO32-, and carbonate saturation states were all higher during both summers of 2018 and 2019. The measured variables such as trace elements, organic carbon, suspended particulates, and acidification parameters exhibited conservative mixing behavior against salinity. These observations have strong implications for the health of the oyster reefs, which provides ecologically important habitats and supports the economy of the Gulf Coast.

Using hyperspectral leaf reflectance to estimate photosynthetic capacity and nitrogen content across eastern cottonwood and hybrid poplar taxa.

Eastern cottonwood (Populus deltoides W. Bartram ex Marshall) and hybrid poplars are well-known bioenergy crops. With advances in tree breeding, it is increasingly necessary to find economical ways to identify high-performing Populus genotypes that can be planted under different environmental conditions. Photosynthesis and leaf nitrogen content are critical parameters for plant growth, however, measuring them is an expensive and time-consuming process. Instead, these parameters can be quickly estimated from hyperspectral leaf reflectance if robust statistical models can be developed. To this end, we measured photosynthetic capacity parameters (Rubisco-limited carboxylation rate (Vcmax), electron transport-limited carboxylation rate (Jmax), and triose phosphate utilization-limited carboxylation rate (TPU)), nitrogen per unit leaf area (Narea), and leaf reflectance of seven taxa and 62 genotypes of Populus from two study plantations in Mississippi. For statistical modeling, we used least absolute shrinkage and selection operator (LASSO) and principal component analysis (PCA). Our results showed that the predictive ability of LASSO and PCA models was comparable, except for Narea in which LASSO was superior. In terms of model interpretability, LASSO outperformed PCA because the LASSO models needed 2 to 4 spectral reflectance wavelengths to estimate parameters. The LASSO models used reflectance values at 758 and 935 nm for estimating Vcmax (R2 = 0.51 and RMSPE = 31%) and Jmax (R2 = 0.54 and RMSPE = 32%); 687, 746, and 757 nm for estimating TPU (R2 = 0.56 and RMSPE = 31%); and 304, 712, 921, and 1021 nm for estimating Narea (R2 = 0.29 and RMSPE = 21%). The PCA model also identified 935 nm as a significant wavelength for estimating Vcmax and Jmax. Therefore, our results suggest that hyperspectral leaf reflectance modeling can be used as a cost-effective means for field phenotyping and rapid screening of Populus genotypes because of its capacity to estimate these physicochemical parameters.

Evaluating hydrogeochemical characteristics of groundwater and surface water in the Upper Pearl River Watershed, USA.

The groundwater quality of the Upper Pearl River Watershed (UPRW) and surface water quality of the basin's outlet, Ross Barnett Reservoir (RBR), are critically important because of growing demands for drinking, agriculture, and industrial use in the region. To identify factors affecting water quality and characterize the surface water outlet and the watershed's groundwater, geochemical and statistical analyses were performed using results from various hydrogeochemical parameters. Based on surface geology, groundwater samples analyzed (n = 51) within the watershed were partitioned into three recharge zones: North, Mid, and South. Precipitation and rock-water interactions were identified to dominantly influence the groundwater chemistry in the region. The chemistry of the surface water samples (n = 9), on the other hand, was influenced more by precipitation with minor contribution from the proximal aquifer system. Principal component analysis (PCA) revealed that two groundwater recharge zones and RBR samples exhibited significant clustering. The groundwater had a complex array of parameters influencing its chemistry owing to diverse properties, including Na, Ca, Mg, alkalinity, and conductivity. Comparing land use at the sub-watershed level with the water quality parameters showed that agriculture and development could have contributed nitrate, especially to the groundwater in the south zone. However, a general lack of distinct relationship between land use and water quality, along with detection of excess nitrate in select wells suggested that the water in the region was likely affected by point sources, such as poultry farms. The research recommends evaluating point sources of pollution to cater to future water management in the region.

Pollution assessment and land use land cover influence on trace metal distribution in sediments from five aquatic systems in southern USA.

Trace elements and heavy metals concentrate in aquatic sediments, potentially endangering benthic organisms. Comparing the concentration of metals in different aquatic bodies will help evaluate their accumulation and distribution characteristics within these systems. Metal pollution and enrichment indices in sediments from diverse aquatic systems in Southern USA, including agricultural ponds, man-made reservoir, river, swamp, and coastal environment were investigated. Following total digestion of the sediments, the concentrations of chromium (Cr), cobalt (Co), copper (Cu), zinc (Zn), arsenic (As), selenium (Se), cadmium (Cd), antimony (Sb), lead (Pb), and uranium (U) were measured using inductively coupled plasma-mass spectrometry (ICP-MS). Pb was found to be highly enriched in the sediment samples from all five environments. The samples from coastal and agricultural ponds showed highest degree of anthropogenic modification (enrichment factor >10), especially with Se, U, and Pb. Agricultural ponds, previously unknown as a metal hotspot, had the most deteriorated sediment quality as determined by high pollution load index (>1) and contamination factor (>6) for Cd and U. Principal component analysis comparing land use land cover distribution surrounding the aquatic systems to metal concentrations confirmed that agriculture-related land activities correlated well with majority of the metals. Overall, compared to agricultural ponds and coastal regions, sediments in river, swamp and man-made reservoir systems contained relatively fewer metal pollutants, the former two serving as collection points for metal-laden fertilizers and chemicals. The research provides key insights into simultaneously comparing metal accumulation in multiple water bodies and is useful to test and develop effective sediment quality guidelines.

Hurricane pulses: Small watershed exports of dissolved nutrients and organic matter during large storms in the Southeastern USA.

Extreme weather events, such as hurricanes, can cause ecological disturbances that alter energy and nutrients across terrestrial-aquatic boundaries. Yet, relatively few studies have considered the impacts of extreme weather events on biogeochemical dynamics in watersheds at larger spatial scales. Here, we assessed the effects of Hurricanes Harvey and Irma on the export of dissolved organic matter (DOM) and nutrients in ten watersheds from five southeastern states of the United States. We quantified the magnitude of dissolved organic carbon (DOC) and nutrients exported during the storms and assessed the changes in DOM sources and bioreactivity after storms. Our results show that the storm-mobilized DOC and nutrients fluxes were primarily driven by water discharge. The proportions of terrestrial, humic-like DOM compounds increased, and percent autochthonous, protein-like DOM decreased during high flows. Percent bioreactive DOC decreased with increasing discharge. Bioreactivity increased with increasing nitrate concentration, but decreased as percent terrestrial humic-like DOM, aromaticity, and molecular weight increased. These observations suggest that storms may have shifted flow paths to shallower depths that promoted the addition of biorefractory organic matter from topsoils into the water column. Notably, the total flux of bioreactive DOC was at least nearly twice as high at peak discharge, indicating materials transported by large storm flows could strongly enhance microbial activity in streams, although the position of storm-mediated microbial hotspots would depend on the flow rate and other instream parameters. Additionally, compared to forest-dominated watersheds, urban watersheds exported high loads of nutrients and bioreactive DOC, and a wetland-dominated watershed had a prolonged, but relatively subdued export of DOC and nutrients. Together, our findings highlight the ecological significance of extreme weather and climate events in leading to rapid, large-magnitude changes in energy and nutrient availability within drainage networks, and the potential interactions between land use and climate change on watershed biogeochemistry.

Effect of photo-biodegradation and biodegradation on the biogeochemical cycling of dissolved organic matter across diverse surface water bodies.

The objective of this research was to quantify the temporal variation of dissolved organic matter (DOM) in five distinct waterbodies in watersheds with diverse types of land use and land cover in the presence and absence of sunlight. The water bodies were an agricultural pond, a lake in a forested watershed, a man-made reservoir, an estuary, and a bay. Two sets of samples were prepared by dispensing unfiltered samples into filtered samples in 1:10 ratio (V/V). The first set was exposed to sunlight (10 hr per day for 30 days) for examining the combined effect of photo-biodegradation, while the second set was stored in dark for examining biodegradation alone. Spectroscopic measurements in tandem with multivariate statistics were used to interpret DOM lability and composition. The results suggest that the agricultural pond behaved differently compared to other study locations during degradation experiments due to the presence of higher amount of microbial humic-like and protein-like components derived from microbial/anthropogenic sources. For all samples, a larger decrease in dissolved organic carbon (DOC) concentration (10.12% ±â€¯9.81% for photo-biodegradation and 6.65% ±â€¯2.83% for biodegradation) and rapid transformation of DOM components (i.e., terrestrial humic-like components into microbial humic and protein-like components) were observed during photo-biodegradation experiments. Results suggest that sunlight facilitated DOM biodegradation, resulting in simpler recalcitrant molecules regardless of original composition. Overall, it was found that combined effects of light and bacteria are more efficient than bacterial effects alone in remineralizing and altering DOM, which highlights the crucial importance of sunlight in transforming aquatic DOM.

Application of Climate Assessment Tool (CAT) to Estimate Climate Variability Impacts on Nutrient Loading from Local Watersheds.

A vast amount of future climate scenario datasets, created by climate models such as general circulation models (GCMs), have been used in conjunction with watershed models to project future climate variability impact on hydrological processes and water quality. However, these low spatial-temporal resolution datasets are often difficult to downscale spatially and disaggregate temporarily, and they may not be accurate for local watersheds (i.e., state level or smaller watersheds). This study applied the US-EPA (Environmental Protection Agency)'s Climate Assessment Tool (CAT) to create future climate variability scenarios based on historical measured data for local watersheds. As a case demonstration, CAT was employed in conjunction with HSPF (Hydrological Simulation Program-FORTRAN) model to assess the impacts of the potential future extreme rainfall events and air temperature increases upon nitrate-nitrogen (NO3-N) and orthophosphate (PO4) loads in the Lower Yazoo River Watershed (LYRW), a local watershed in Mississippi, USA. Results showed that the 10 and 20% increases in rainfall rate, respectively, increased NO3-N load by 9.1 and 18% and PO4 load by 12 and 24% over a 10-year simulation period. In contrast, simultaneous increases in air temperature by 1.0 oC and rainfall rate by 10% as well as air temperature by 2.0 oC and rainfall rate by 20% increased NO3-N load by 12% and 20%%, and PO4 load by 14 and 26 %, respectively. A summer extreme rainfall scenario was created if a 10% increase in rainfall rate increased the total volume of rainwater for that summer by 10% or more. When this event occurred, it could increase the monthly loads of NO3-N and PO4, by 31 and 41%, respectively, for that summer. Therefore, the extreme rainfall events had tremendous impacts on the NO3-N and PO4 loads. It is apparent that CAT is a flexible and useful tool to modify historical rainfall and air temperature data to predict climate variability impacts on water quality for local watersheds.

Influence of land use and land cover on the spatial variability of dissolved organic matter in multiple aquatic environments.

Water quality of lakes, estuaries, and coastal areas serves as an indicator of the overall health of aquatic ecosystems as well as the health of the terrestrial ecosystem that drains to the water body. Land use and land cover plays not only a significant role in controlling the quantity of the exported dissolved organic matter (DOM) but also influences the quality of DOM via various biogeochemical and biodegradation processes. We examined the characteristics and spatial distribution of DOM in five major lakes, in an estuary, and in the coastal waters of the Mississippi, USA, and investigated the influence of the land use and land cover of their watersheds on the DOM composition. We employed absorption and fluorescence spectroscopy including excitation-emission matrix (EEM) combined with parallel factor (PARAFAC) analysis modeling techniques to determine optical properties of DOM and its characteristics in this study. We developed a site-specific PARAFAC model to evaluate DOM characteristics resulting in five diverse DOM compositions that included two terrestrial humic-like (C1 and C3), two microbial humic-like (C2 and C5), and one protein-like (C4) DOM. Our results showed elevated fluorescence levels of microbial humic-like or protein-like DOM in the lakes and coastal waters, while the estuarine waters showed relatively high fluorescence levels of terrestrial humic-like DOM. The results also showed that percent forest and wetland coverage explained 68 and 82% variability, respectively, in terrestrial humic-like DOM exports, while 87% variability in microbially derived humiclike DOM was explained by percent agricultural lands. Strong correlations between microbial humic-like DOM and fluorescence-derived DOM indices such as biological index (BIX) and fluorescence index (FI) indicated autochthonous characteristics in the lakes, while the estuary showed largely allochthonous DOM of terrestrial origin. We also observed higher concentrations of total dissolved phosphorous (TDP) and ammonium nitrogen (NH4-N) in coastal waters potentially due to photodegradation of refractory DOM derived from the sediment-bound organic matter in the coastal wetlands. This study highlights the relationships between the DOM compositions in the water and the land use and land cover in the watershed. The spatial variability of DOM in three different types of aquatic environments enhances the understanding of the role of land use and land cover in carbon cycling through export of organic matter to the aquatic ecosystems..