Hotspots of wetland loss to impervious surfaces in the conterminous United States.

In this study, a first wall-to-wall comparison between the National Wetlands Inventory (NWI) and the National Land Cover Database (NLCD) was conducted across the entire conterminous United States (CONUS) to evaluate U.S. wetland loss conditions. Annually, around 26 km2 of wetlands are lost to impervious surfaces across the CONUS. Spatially, wetland loss is not evenly distributed, with 90 % of losses occurring in only 9 % of the land area, forming hotspots around expanding urban regions such as Houston, Jacksonville, and Naples. Over the past few decades, Florida experienced the highest wetland loss (5.73 km2/year) among all states, while Houston had the most wetland loss (2.54 km2/year) among all metropolitan regions. Stepwise multiple regression models identified population growth and its associated demand for new housing as the major drivers for wetland loss. Wetland loss per population increase is the highest (>15 m2/person) in most metropolitan regions around the East Coast and Gulf of Mexico. Unfortunately, current wetland loss hotspots will likely suffer further losses in future decades due to projected population growth, with Houston, Cape Coral, and Miami metropolitan regions having the greatest projected wetland loss of 89.15 km2, 34.35 km2, and 28.20 km2, respectively. This study has identified wetland loss hotspots and their drivers across the U.S. that were not possible in previous sample-based studies. The findings are critical in wetland management and protection across the U.S.

Intercomparison of Same-Day Remote Sensing Data for Measuring Winter Cover Crop Biophysical Traits.

Winter cover crops are planted during the fall to reduce nitrogen losses and soil erosion and improve soil health. Accurate estimations of winter cover crop performance and biophysical traits including biomass and fractional vegetative groundcover support accurate assessment of environmental benefits. We examined the comparability of measurements between ground-based and spaceborne sensors as well as between processing levels (e.g., surface vs. top-of-atmosphere reflectance) in estimating cover crop biophysical traits. This research examined the relationships between SPOT 5, Landsat 7, and WorldView-2 same-day paired satellite imagery and handheld multispectral proximal sensors on two days during the 2012-2013 winter cover crop season. We compared two processing levels from three satellites with spatially aggregated proximal data for red and green spectral bands as well as the normalized difference vegetation index (NDVI). We then compared NDVI estimated fractional green cover to in-situ photographs, and we derived cover crop biomass estimates from NDVI using existing calibration equations. We used slope and intercept contrasts to test whether estimates of biomass and fractional green cover differed statistically between sensors and processing levels. Compared to top-of-atmosphere imagery, surface reflectance imagery were more closely correlated with proximal sensors, with intercepts closer to zero, regression slopes nearer to the 1:1 line, and less variance between measured values. Additionally, surface reflectance NDVI derived from satellites showed strong agreement with passive handheld multispectral proximal sensor-sensor estimated fractional green cover and biomass (adj. R2 = 0.96 and 0.95; RMSE = 4.76% and 259 kg ha-1, respectively). Although active handheld multispectral proximal sensor-sensor derived fractional green cover and biomass estimates showed high accuracies (R2 = 0.96 and 0.96, respectively), they also demonstrated large intercept offsets (-25.5 and 4.51, respectively). Our results suggest that many passive multispectral remote sensing platforms may be used interchangeably to assess cover crop biophysical traits whereas SPOT 5 required an adjustment in NDVI intercept. Active sensors may require separate calibrations or intercept correction prior to combination with passive sensor data. Although surface reflectance products were highly correlated with proximal sensors, the standardized cloud mask failed to completely capture cloud shadows in Landsat 7, which dampened the signal of NIR and red bands in shadowed pixels.

Evaluation of [225Ac]Ac-DOTA-anti-VLA-4 for targeted alpha therapy of metastatic melanoma.

Very late antigen 4 (VLA-4; also called integrin α4ß1) is overexpressed in melanoma tumor cells with an active role in tumor growth, angiogenesis, and metastasis, making VLA-4 a potential target for targeted alpha therapy (TAT). METHODS: An anti-VLA-4 antibody was conjugated to DOTA for [225Ac]Ac-labeling and DTPA for [111In]In-labeling. The resulting agents, [225Ac]Ac- or [111In]In-labeled anti-VLA-4 were evaluated in vitro, including binding affinity, internalization, and colony formation assays as well as in vivo biodistribution studies. In addition, the therapeutic efficacy of [225Ac]Ac-DOTA-anti-VLA-4 was evaluated in a disseminated disease mouse model of melanoma. RESULTS: [111In]In-DTPA-anti-VLA-4 demonstrated high affinity for VLA-4 (Kd = 5.2 ± 1.6 nM). [225Ac]Ac-DOTA-anti-VLA-4 was labeled with an apparent molar activity of 3.5 MBq/nmol and > 95% radiochemical purity. Colony formation assays demonstrated a decrease in the surviving fraction of B16F10 cells treated with [225Ac]Ac-DOTA-anti-VLA-4 compared to control. Biodistribution studies demonstrated accumulation in the VLA-4-positive tumor and VLA-4 rich organs. Therapeutic efficacy studies demonstrated a significant increase in survival in mice treated with [225Ac]Ac-DOTA-anti-VLA-4 as compared to controls. CONCLUSION: The work presented here demonstrated that [225Ac]Ac-DOTA-anti-VLA-4 was effective as a treatment in mice with disseminated disease, but potentially has dose limiting hematopoietic toxicity. Preliminary studies presented here also supported the potential to overcome this limitation by exploring a pre-loading or blocking dose strategy, to optimize the targeting vector to help minimize the absorbed dose to VLA-4 rich organs while maximizing the dose delivered to VLA-4-positive melanoma tumor cells.

Nitrogen release and leachable organic matter decomposition of anaerobically digested biosolids with variable pre-treatments.

Thermal hydrolysis pretreatments (THP) coupled to anaerobic digestion (AD) are implemented to treat municipal solids, but limited study indicates whether THP-AD materials merit different land application rates than AD biosolids without THP. Three AD biosolids types with either no pretreatment, THP, or two-hour fermentation were evaluated for differences in leachable dissolved organic matter (DOM), DOM decomposition, and nitrogen (N) releases in biosolids incubated in sandy loam soil. DOM characterizations of size exclusion chromatography, FTIR, and fluorescence maxima > Ex: 400 nm indicated similarities in among AD-DOM that contrasted waste activated sludge Milorganite and Suwannee River Organic Matter (SRNOM). Fluorescence peak picking was a more adaptable analysis for shifted leachate spectra than fluorescence regional integration (FRI). Peak ratio analysis is recommended over FRI for biosolids-DOM. The 3-month net inorganic N produced in biosolids-soil incubations was 155 ± 12.1, 149 ± 18.2, 140 ± 17.4, and 354 ± 15.1 mg N/kg for AD biosolids with no pretreatment, fermentation-AD, THP-AD, and Milorganite respectively. Overall, there was limited evidence of differences in leachable organic matter quality or net mineral N release after 105 days for AD solids with or without THP. Red-shifted fluorescence of leachates decayed by day 45 in aerobic biosolids-soil incubations, suggesting that larger, complex carbon sources liberated during solids stabilization may decompose readily in soils. Overall, other variables (source material, AD operation) may have a greater influence on final nutrient releases and organic matter quality than full-scale pretreatments to AD alone. Critical and targeted application of DOM spectroscopy specific to biosolid-leachates will improve use in advanced stabilization studies.

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon.

Landscape topography is a critical factor affecting soil formation and plays an important role in determining soil properties on the earth surface, as it regulates the gravity-driven soil movement induced by runoff and tillage activities. The recent application of Light Detection and Ranging (LiDAR) data holds promise for generating high spatial resolution topographic metrics that can be used to investigate soil property variability. In this study, fifteen topographic metrics derived from LiDAR data were used to investigate topographic impacts on redistribution of soil and spatial distribution of soil organic carbon (SOC). Specifically, we explored the use of topographic principal components (TPCs) for characterizing topography metrics and stepwise principal component regression (SPCR) to develop topography-based soil erosion and SOC models at site and watershed scales. Performance of SPCR models was evaluated against stepwise ordinary least square regression (SOLSR) models. Results showed that SPCR models outperformed SOLSR models in predicting soil redistribution rates and SOC density at different spatial scales. Use of TPCs removes potential collinearity between individual input variables, and dimensionality reduction by principal component analysis (PCA) diminishes the risk of overfitting the prediction models. This study proposes a new approach for modeling soil redistribution across various spatial scales. For one application, access to private lands is often limited, and the need to extrapolate findings from representative study sites to larger settings that include private lands can be important.

Estimating restorable wetland water storage at landscape scales.

Globally, hydrologic modifications such as ditching and subsurface drainage have significantly reduced wetland water storage capacity (i.e., volume of surface water a wetland can retain) and consequent wetland functions. While wetland area has been well documented across many landscapes and used to guide restoration efforts, few studies have directly quantified the associated wetland storage capacity. Here, we present a novel raster-based approach to quantify both contemporary and potential (i.e., restorable) storage capacities of individual depressional basins across landscapes. We demonstrate the utility of this method by applying it to the Delmarva Peninsula, a region punctuated by both depressional wetlands and drainage ditches. Across the entire peninsula, we estimated that restoration (i.e., plugging ditches) could increase storage capacity by 80%. Focusing on an individual watershed, we found that over 59% of restorable storage capacity occurs within 20 m of the drainage network, and that 93% occurs within 1 m elevation of the drainage network. Our demonstration highlights widespread ditching in this landscape, spatial patterns of both contemporary and potential storage capacities, and clear opportunities for hydrologic restoration. In Delmarva and more broadly, our novel approach can inform targeted landscape-scale conservation and restoration efforts to optimize hydrologically mediated wetland functions.

Primary cilia are sensors of electrical field stimulation to induce osteogenesis of human adipose-derived stem cells.

In this study, we report for the first time that the primary cilium acts as a crucial sensor for electrical field stimulation (EFS)-enhanced osteogenic response in osteoprogenitor cells. In addition, primary cilia seem to functionally modulate effects of EFS-induced cellular calcium oscillations. Primary cilia are organelles that have recently been implicated to play a crucial sensor role for many mechanical and chemical stimuli on stem cells. Here, we investigate the role of primary cilia in EFS-enhanced osteogenic response of human adipose-derived stem cells (hASCs) by knocking down 2 primary cilia structural proteins, polycystin-1 and intraflagellar protein-88. Our results indicate that structurally integrated primary cilia are required for detection of electrical field signals in hASCs. Furthermore, by measuring changes of cytoplasmic calcium concentration in hASCs during EFS, our findings also suggest that primary cilia may potentially function as a crucial calcium-signaling nexus in hASCs during EFS.-Cai, S., Bodle, J. C., Mathieu, P. S., Amos, A., Hamouda, M., Bernacki, S., McCarty, G., Loboa, E. G. Primary cilia are sensors of electrical field stimulation to induce osteogenesis of human adipose-derived stem cells.

Biological aspects of metal waste reclamation with biosolids.

Smelter waste deposits pose an environmental threat worldwide. Biosolids are potentialy useful in reclamation of such sites. Biological aspects of revegetation of Zn and Pb smelter wastelands using biosolids are discussed in this report. The goal of the studies was to assess to what extent biosolid treatment would support ecosystem functioning as measured by biological indicators such as enzyme activities of revegetated metal waste or plant growth. Another crucial aspect was related to the assessment of metal transfer to the ecosystem which could affect the health of local fauna and also create a food chain risk. A field experiment was conducted on a smelter waste deposit in Piekary Slaskie, Silesia, Poland, with two separate fields - established on wastes from the Welz and Doerschel smelting processes. The tested methods allowed revegetation of the fields - application of municipal biosolid at the rate 300 dry t ha(-1) combined with the incorporation of commercial lime in a mixed oxide and carbonate form at the rate of 1.5 and 30 t for Welz waste or use of a 30 cm by-product lime cap followed by incorporation of biosolid at a rate of 300 t ha(-1) for the more acidic Doerschel waste. Studies on biological activities demonstrated that the reclamation methods used are an effective way to establish new, fully-functioning ecosystems that support plant growth. They also provided strong evidence that forage crops grown on Zn, Cd and Pb contaminated sites reclaimed using lime and biosolids do not pose identified risk for wildlife and food safety.