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Title: Distribution, frequency, and global extent of hypoxia in rivers
To assess the distribution, frequency, and global extent of riverine hypoxia, we compiled 118 million paired dissolved oxygen (DO) and water temperature measurements from 125,158 unique locations in riversMore>>
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U.S. Geological Survey
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National Science Foundation
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  1. Abstract. Methane (CH4) emissions from the boreal and arcticregion are globally significant and highly sensitive to climate change.There is currently a wide range in estimates of high-latitude annualCH4 fluxes, where estimates based on land cover inventories andempirical CH4 flux data or process models (bottom-up approaches)generally are greater than atmospheric inversions (top-down approaches). Alimitation of bottom-up approaches has been the lack of harmonizationbetween inventories of site-level CH4 flux data and the land coverclasses present in high-latitude spatial datasets. Here we present acomprehensive dataset of small-scale, surface CH4 flux data from 540terrestrial sites (wetland and non-wetland) and 1247 aquatic sites (lakesand ponds), compiled from 189 studies. The Boreal–Arctic Wetland and LakeMethane Dataset (BAWLD-CH4) was constructed in parallel with acompatible land cover dataset, sharing the same land cover classes to enablerefined bottom-up assessments. BAWLD-CH4 includes information onsite-level CH4 fluxes but also on study design (measurement method,timing, and frequency) and site characteristics (vegetation, climate,hydrology, soil, and sediment types, permafrost conditions, lake size anddepth, and our determination of land cover class). The different land coverclasses had distinct CH4 fluxes, resulting from definitions that wereeither based on or co-varied with key environmental controls. Fluxes ofCH4 from terrestrial ecosystems were primarily influenced by watertable position, soil temperature,more »and vegetation composition, while CH4fluxes from aquatic ecosystems were primarily influenced by watertemperature, lake size, and lake genesis. Models could explain more of thebetween-site variability in CH4 fluxes for terrestrial than aquaticecosystems, likely due to both less precise assessments of lake CH4fluxes and fewer consistently reported lake site characteristics. Analysisof BAWLD-CH4 identified both land cover classes and regions within theboreal and arctic domain, where future studies should be focused, alongsidemethodological approaches. Overall, BAWLD-CH4 provides a comprehensivedataset of CH4 emissions from high-latitude ecosystems that are usefulfor identifying research opportunities, for comparison against new fielddata, and model parameterization or validation. BAWLD-CH4 can bedownloaded from (Kuhn et al., 2021).« less
  2. Abstract
    The National Land Cover Dataset was compiled from Landsat satellite TM imagery (circa 1992) with a spatial resolution of 30 meters and supplemented by various ancillary data (where available). The analysis and interpretation of the satellite imagery was conducted using very large, sometimes multi-state image mosaics (i.e. up to 18 Landsat scenes). Using a relatively small number of aerial photographs for 'ground truth', the thematic interpretations were necessarily conducted from a spatially-broad perspective. Furthermore, the accuracy assessments (see below) correspond to 'federal regions' which are groupings of contiguous states. Thus, the reliability of the data is greatest at the state or multi-State level. The statistical accuracy of the data is known only for the region. Important Caution Advisory With this in mind, users are cautioned to carefully scrutinize the data to see if they are of sufficient reliability before attempting to use the dataset for larger-scale or local analyses. This evaluation must be made remembering that the NLCD represents conditions in the early 1990s. The New Hampshire portion of the NLCD was created as part of land cover mapping activities for Federal Region I that includes the States of Connecticut, Maine, Vermont, Rhode Island, New Hampshire, and Massachusetts. TheMore>>
  3. Abstract Aim

    Vegetation is sensitive to mean annual precipitation (MAP), but the sensitivity of vegetation to precipitation variability (PV) is less clear. Tropical ecosystems are likely to experience increased PV in the future. Here we assessed the importance, magnitude and mechanism of PV effects on tree cover in the context of covarying environmental drivers such as fire, temperature and soil properties.


    Tropical land.

    Time period


    Major taxa studied



    We compiled climate, soil and remotely‐sensed tree cover data over tropical land. We then comprehensively assessed the contribution of PV at different time‐scales to tropical tree cover variations and estimated the sensitivity of tree cover to PV changes by conducting rolling‐window regression and variance decomposition analyses. We further adopted a mechanistic modelling approach to test whether water competition between trees and grasses can explain the observed effect of PV.


    We find that PV contributes 33–56% to the total explained spatial variation (65–79%) in tree cover. The contribution of PV depends on MAP and is highest under intermediate MAP (500–1,500 mm). Tree cover generally increases with rainy day frequency and wet season length but shows mixed responses to inter‐annual PV. Based on the estimated sensitivity, tropical tree cover can decrease by 3–5% overall andmore »by up to 20% in Amazonia under a 20% decrease in rainy days. Mechanistic modelling analysis reproduced the continental differences in tree cover along an MAP gradient.

    Main conclusions

    Under intermediate rainfall regimes (500–1,500 mm), PV can be a more important determinant of tropical tree cover than conventionally proposed drivers such as MAP and fire. The effect of PV likely results from the sensitivity of tree–grass competition to the temporal distribution of water resources. These results show that climate variability can strongly shape the biosphere.

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  4. Abstract Aim

    Anthropogenic warming of marine systems has caused biological and physiological responses that are fundamentally altering ecosystem structure. Because estuaries exist at the land‐ocean interface, they are particularly vulnerable to the effects of ocean warming as they can undergo rapid biogeochemical and hydrological shifts due to climate and land‐use change. We explored how multiple components of estuarine fish diversity—turnover, richness, and abundance—have changed in the North Atlantic and Gulf of Mexico estuaries across space and time and the drivers of change.


    North Atlantic and Gulf of Mexico.




    We compiled long‐term (>30 years), continent‐wide fisheries independent trawl surveys conducted in estuaries—from the Gulf of Maine to the Gulf of Mexico (U.S. waters)—and combined these with climate and land‐use‐land‐cover data to examine trends and ecological drivers of fish richness, abundance and turnover using mixed‐effect models.


    Species richness, abundance and turnover have increased in North Atlantic and Gulf of Mexico estuaries in the last 30 years. These changes were mediated largely by sea‐surface temperature anomalies, especially in more northern estuaries where warming has been relatively pronounced.

    Main Conclusion

    The increasing trajectory of turnover in many estuaries suggests that fish communities have changed fundamentally from the baselines. A fundamental change in community composition can lead tomore »an irreversible trophic imbalance or alternative stable states among other outcomes. Thus, predicting how shifting community structures might influence food webs, ecosystem stability, and human resource use remain a pertinent task.

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  5. Abstract

    Understanding relationships between stream chemistry and watershed factors: land use/land cover, climate, and lithology are crucial to improving our knowledge of critical zone processes that influence water quality. We compiled major ion data from >100 monitoring stations collected over 60 years (1958–2018) across the Colorado River Watershed in Texas (103,000 km2). We paired this river chemistry data with complementary lithology, land use, climate, and stream discharge information. Machine learning techniques were used to produce new insights on controls of stream water chemical behavior, which were validated using traditional multivariate analyses. Studies on stream flow and chemistry in the American west and globally have shown strong relationships between major ion chemical composition, climate, and lithology which hold true for the Colorado River basin in this study. Reactive minerals, including carbonates and evaporites, dominate major ion chemistry across the upper, low‐precipitation regions of the watershed. Upstream and middle reaches of the Colorado River showed shifts from Na‐Cl‐SO4dominated water from multiple sources including dissolution of gypsum and halite in shallow groundwater, and agricultural activities, to Ca‐HCO3water types controlled by carbonate dissolution. In the lower portion of the watershed multiple analyses demonstrate that stream chemistry is more influenced by greater precipitation and the presence ofmore »silicate minerals than the middle and upstream reaches. This study demonstrates the power of applying machine learning approaches to publicly available long term water chemistry data sets to improve the understanding of watershed interactions with surficial lithology, salinity sources, and anthropogenic influences of water quality.

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