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Directly observing autotrophic biomass at ecologically relevant frequencies is difficult in many ecosystems, hampering our ability to predict productivity through time. Since disturbances can impart distinct reductions in river productivity through time by modifying underlying standing stocks of biomass, mechanistic models fit to productivity time series can infer underlying biomass dynamics. We incorporated biomass dynamics into a river ecosystem productivity model for six rivers to identify disturbance flow thresholds and understand the resilience of primary producers. The magnitude of flood necessary to disturb biomass and thereby reduce ecosystem productivity was consistently lower than the more commonly used disturbance flow threshold of the flood magnitude necessary to mobilize river bed sediment. The estimated daily maximum percent increase in biomass (a proxy for resilience) ranged from 5% to 42% across rivers. Our latent biomass model improves understanding of disturbance thresholds and recovery patterns of autotrophic biomass within river ecosystems.

 

Processes that drive variability in catchment solute sourcing, transformation, and transport can be investigated using concentration–discharge (C–Q) relationships. These relationships reflect catchment and in‐stream processes operating across nested temporal scales, incorporating both short and long‐term patterns. Scientists can therefore leverage catchment‐scale C–Q datasets to identify and distinguish among the underlying meteorological, biological, and geological processes that drive solute export patterns from catchments and influence the shape of their respective C–Q relationships. We have synthesized current knowledge regarding the influence of biological, geological, and meteorological processes on C–Q patterns for various solute types across diel to decadal time scales. We identify cross‐scale linkages and tools researchers can use to explore these interactions across time scales. Finally, we identify knowledge gaps in our understanding of C–Q temporal dynamics as reflections of catchment and in‐stream processes. We also lay the foundation for developing an integrated approach to investigate cross‐scale linkages in the temporal dynamics of C–Q relationships, reflecting catchment biogeochemical processes and the effects of environmental change on water quality.

This article is categorized under:

Science of Water > Hydrological Processes

Science of Water > Water Quality

Science of Water > Water and Environmental Change

 

Mean annual temperature and mean annual precipitation drive much of the variation in productivity across Earth's terrestrial ecosystems but do not explain variation in gross primary productivity (GPP) or ecosystem respiration (ER) in flowing waters. We document substantial variation in the magnitude and seasonality of GPP and ER across 222 US rivers. In contrast to their terrestrial counterparts, most river ecosystems respire far more carbon than they fix and have less pronounced and consistent seasonality in their metabolic rates. We find that variation in annual solar energy inputs and stability of flows are the primary drivers of GPP and ER across rivers. A classification schema based on these drivers advances river science and informs management. 

Freshwater salinization of rivers is occurring across the globe because of nonpoint source loading of salts from anthropogenic activities such as agriculture, urbanization, and resource extraction that accelerate weathering and release salts. Multidecadal trends in river salinity are well characterized, yet our understanding of annual regimes of salinity in rivers draining diverse central and western U.S. landscapes and their associated catchment attributes is limited. We classified annual salinity regimes in 242 stream locations through dynamic time warping and fuzzy c‐medoids clustering of salinity time series. We found two dominant regimes in salinity characterized by an annualsummer–fall peakorspring decline. Using random forest regression, we found that precipitation amount, stream slope, and soil salinity were the most important predictors of salinity regime classification. Advancing our understanding of salinity regimes in rivers will improve our ability to predict and mitigate the effects of salinization in freshwater ecosystems through management interventions.

 

Abstract Non-perennial streams are widespread, critical to ecosystems and society, and the subject of ongoing policy debate. Prior large-scale research on stream intermittency has been based on long-term averages, generally using annually aggregated data to characterize a highly variable process. As a result, it is not well understood if, how, or why the hydrology of non-perennial streams is changing. Here, we investigate trends and drivers of three intermittency signatures that describe the duration, timing, and dry-down period of stream intermittency across the continental United States (CONUS). Half of gages exhibited a significant trend through time in at least one of the three intermittency signatures, and changes in no-flow duration were most pervasive (41% of gages). Changes in intermittency were substantial for many streams, and 7% of gages exhibited changes in annual no-flow duration exceeding 100 days during the study period. Distinct regional patterns of change were evident, with widespread drying in southern CONUS and wetting in northern CONUS. These patterns are correlated with changes in aridity, though drivers of spatiotemporal variability were diverse across the three intermittency signatures. While the no-flow timing and duration were strongly related to climate, dry-down period was most strongly related to watershed land use and physiography. Our results indicate that non-perennial conditions are increasing in prevalence over much of CONUS and binary classifications of ‘perennial’ and ‘non-perennial’ are not an accurate reflection of this change. Water management and policy should reflect the changing nature and diverse drivers of changing intermittency both today and in the future. 

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 rivers in 93 countries and territories across the globe. The dataset also includes site characteristics derived from StreamCat, the National Hydrography and HydroAtlas datasets and proximal land cover derived from MODIS-based IGBP land cover types compiled using Google Earth Engine (GEE). 

Deoxygenation of aquatic ecosystems is a key feature of the Anthropocene. Studies are increasingly reporting low oxygen conditions in rivers and headwater streams even in the absence of high nutrient loads. We examined the frequency of river hypoxia (dissolved oxygen [DO] < 50% saturated in O₂) in the North Carolina Piedmont by examining monitoring records collected since the 1960s, and by collecting high‐resolution measurements of DO saturation along a 20 km segment of New Hope Creek. State records reported nearly 11,000 incidences of hypoxia from a total of ~ 140,000 measurements (7.8% over 55 yr). In contrast, our measurements in New Hope Creek suggest that assessing river hypoxia from point measurements is highly problematic. We propose new approaches for evaluating and comparing river oxygen regimes. In a detailed longitudinal survey of DO in May 2018, 31% of measurements over 20 km were hypoxic. Over a 3‐week period, 11 of our 12 sites throughout this segment experienced hypoxia 5%–96% of the time. Interannual comparisons for several long‐term monitoring sites document significant potential for hypoxia even in well‐aerated reaches during particularly warm, low flow periods. Oxygen regimes within this river vary between near continuous hypoxia to near continuous saturation and call into question the binary distinction between lotic and lentic oxygen dynamics with which we tend to categorize and model freshwater ecosystems.

 

Nonpoint source urban nutrient loading into streams and receiving water bodies is widely recognized as a major environmental management challenge. A dominant research and management paradigm assumes that loading primarily derives from elevated stormwater. However, baseflow can account for a large portion of total loading, especially for low development intensity watersheds which comprise the largest urban areas. We investigated the sources and drivers of nonpoint source baseflow nitrogen loading across 27 headwater catchments in the urbanized Piedmont region of North Carolina, USA. Nitrate isotopes, predictors of concentration‐discharge (CQ) slopes, and predictors of mean annual total dissolved nitrogen (TDN) loading suggest that wastewater was a major baseflow nonpoint source of nitrogen across developed catchments likely contributing 61% of nitrate loading from septic served catchments and 49% from sewer served catchments. Our findings suggest that subsurface TDN was abundant, loading was largely transport limited, and the hydrogeomorphic position of sanitary infrastructure strongly influences transport. We developed an empirical model showing catchment loading increased with the topographic wetness index of sanitary sewer location, convergent sloping land area, parcel density, and residual agricultural landcover (R² = 0.78). We extended this model to the study region's 1,436 developed small (0.3–20.8 sq km) catchments. We estimated up to 92.7% of nonpoint source baseflow TDN loading comes from low and medium development intensity catchments, and sanitary infrastructure in wet areas of the landscape accounts for 39% of regional baseflow loading. Our research indicates that managing baseflow loading will require addressing lower development intensity catchments and sanitary infrastructure.

 

Recent advances in high‐frequency environmental sensing and statistical approaches have greatly expanded the breadth of knowledge regarding aquatic ecosystem metabolism—the measurement and interpretation of gross primary productivity (GPP) and ecosystem respiration (ER). Aquatic scientists are poised to take advantage of widely available datasets and freely‐available modeling tools to apply functional information gained through ecosystem metabolism to help inform environmental management. Historically, several logistical and conceptual factors have limited the widespread application of metabolism in management settings. Benefitting from new instrumental and modeling tools, it is now relatively straightforward to extend routine monitoring of dissolved oxygen (DO) to dynamic measures of aquatic ecosystem function (GPP and ER) and key physical processes such as gas exchange with the atmosphere (G). We review the current approaches for using DO data in environmental management with a focus on the United States, but briefly describe management frameworks in Europe and Canada. We highlight new applications of diel DO data and metabolism in regulatory settings and explore how they can be applied to managing and monitoring ecosystems. We then review existing data types and provide a short guide for implementing field measurements and modeling of ecosystem metabolic processes using currently available tools. Finally, we discuss research needed to overcome current conceptual limitations of applying metabolism in management settings. Despite challenges associated with modeling metabolism in rivers and lakes, rapid developments in this field have moved us closer to utilizing real‐time estimates of GPP, ER, and G to improve the assessment and management of environmental change.

This article is categorized under:

Water and Life > Nature of Freshwater Ecosystems

Water and Life > Conservation, Management, and Awareness

 

Hypoxia in coastal waters and lakes is widely recognized as a detrimental environmental issue, yet we lack a comparable understanding of hypoxia in rivers. We investigated controls on hypoxia using 118 million paired observations of dissolved oxygen (DO) concentration and water temperature in over 125,000 locations in rivers from 93 countries. We found hypoxia (DO < 2 mg L⁻¹) in 12.6% of all river sites across 53 countries, but no consistent trend in prevalence since 1950. High‐frequency data reveal a 3‐h median duration of hypoxic events which are most likely to initiate at night. River attributes were better predictors of riverine hypoxia occurrence than watershed land cover, topography, and climate characteristics. Hypoxia was more likely to occur in warmer, smaller, and lower‐gradient rivers, particularly those draining urban or wetland land cover. Our findings suggest that riverine hypoxia and the resulting impacts on ecosystems may be more pervasive than previously assumed.