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Este artículo contiene 14 páginas, 5 figuras, 2 tablas. ; Wastewater treatment plant (WWTP) effluents alter water chemistry and in-stream nutrient uptake rates of receiving freshwaters, thus changing the magnitude and fate of the nutrients exported. In Mediterranean regions, the dilution capacity of receiving streams can vary strongly over time due to the seasonal occurrence of floods and droughts, causing temporal variability of nutrient uptake. We assessed the temporal patterns and the controlling factors of net nutrient uptake in an intermittent Mediterranean stream receiving WWTP effluent inputs. We compiled the longitudinal concentration profiles of ambient dissolved inorganic nitrogen (DIN) and soluble reactive phosphorus (SRP) along a 800 m reach on 47 sampling dates between 2001 and 2017, encompassing a wide range of hydrological conditions. We estimated net nutrient uptake in the receiving stream. In 72% of the dates, high rates of net ammonium uptake co-occurred with net releases of either nitrate or nitrite. This pattern suggests that the receiving stream has a high nitrification capacity. Conversely, 75% of the dates did not show any longitudinal pattern in SRP concentration, suggesting that uptake and release processes for this element were either counterbalanced or both occurred at very low rates. Finally, net ammonium uptake was low when the stream had a low dilution capacity (< 40%) and ammonium concentration was high. Overall, we demonstrate that consideration of the receiving stream's dilution capacity is imperative to the management of freshwaters to guarantee an adequate dilution of WWTP effluent inputs and avoid saturation of in-stream nutrient uptake capacity under low flow conditions in urban landscapes. ; Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This study was funded by the projects "EcoReactors" (PGC2018-101975-B C22), "CANTERA" (RTI2018- 094521-B-100) and "Fluvial P-removal" (PID2019-111803RB-I00) from I + D program of the Spanish Ministry of Science, Innovation, and Universities. AL was supported by the program Beatriu de Pinós (BP-2018–00082) from the Government of Catalonia and the European Commission. JLJL was supported by a Marie Skłodowska-Curie Individual Fellowship (H2020-MSCA-IF-2018, RIPARIONS ref: 834363). SB was supported by a Ramon y Cajal fellowship (RYC-2017–22643) from the Spanish Ministry of Science, Innovation, and Universities. ; Peer reviewed

Although most field and modeling studies of river corridor exchange have been conducted at scales ranging from tens to hundreds of meters, results of these studies are used to predict their ecological and hydrological influences at the scale of river networks. Further complicating prediction, exchanges are expected to vary with hydrologic forcing and the local geomorphic setting. While we desire predictive power, we lack a complete spatiotemporal relationship relating discharge to the variation in geologic setting and hydrologic forcing that is expected across a river basin. Indeed, the conceptual model of Wondzell (2011) predicts systematic variation in river corridor exchange as a function of (1) variation in baseflow over time at a fixed location, (2) variation in discharge with location in the river network, and (3) local geomorphic setting. To test this conceptual model we conducted more than 60 solute tracer studies including a synoptic campaign in the 5th-order river network of the H. J. Andrews Experimental Forest (Oregon, USA) and replicate-intime experiments in four watersheds. We interpret the data using a series of metrics describing river corridor exchange and solute transport, testing for consistent direction and magnitude of relationships relating these metrics to discharge and local geomorphic setting. We confirmed systematic decrease in river corridor exchange space through the river networks, from headwaters to the larger main stem. However, we did not find systematic variation with changes in discharge through time or with local geomorphic setting. While interpretation of our results is complicated by problems with the analytical methods, the results are sufficiently robust for us to conclude that space-for-time and time-for-space substitutions are not appropriate in our study system. Finally, we suggest two strategies that will improve the interpretability of tracer test results and help the hyporheic community develop robust datasets that will enable comparisons across multiple sites and/or discharge conditions. ; Leverhulme Trust (Where rivers, groundwater and disciplines meet: a hyporheic research network); UK Natural Environment Research CouncilNERC Natural Environment Research Council [NE/L003872/1]; European Commission, H2020 Marie Sklodowska-Curie Actions (HiFreq) [734317]; U.S. Department of Energy (Pacific Northwest National Lab); National Science FoundationNational Science Foundation (NSF) [DEB-1440409, EAR-1652293, EAR-1417603, EAR-1446328]; University of Birmingham (Institute of Advanced Studies); U.S. Department of EnergyUnited States Department of Energy (DOE) [DE-SC0019377] ; This research has been supported by the Leverhulme Trust (Where rivers, groundwater and disciplines meet: a hyporheic research network), the UK Natural Environment Research Council (grant no. NE/L003872/1), the European Commission, H2020 Marie Sklodowska-Curie Actions (HiFreq (grant no. 734317)), the U.S. Department of Energy (Pacific Northwest National Lab and DE-SC0019377), the National Science Foundation (grant nos. DEB-1440409, EAR-1652293, EAR-1417603, and EAR-1446328), and the University of Birmingham (Institute of Advanced Studies). ; Public domain authored by a U.S. government employee

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale.

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types.