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At least 55 records · Page 3Linked to original sources
USGS2016

Spatio-temporal development of vegetation die-off in a submerging coastal marsh

In several places around the world, coastal marsh vegetation is converting to open water through the formation of pools. This is concerning, as vegetation die-off is expected to reduce the marshes' capacity to adapt to sea level rise by vegetation-induced sediment accretion. Quantitative analyses of the spatial and temporal development of marsh vegetation die-off are scarce, although these are needed to understand the bio-geomorphic feedback effects of vegetation die-off on flow, erosion, and sedimentation. In this study, we quantified the spatial and temporal development of marsh vegetation die-off with aerial images from 1938 to 2010 in a submerging coastal marsh along the Blackwater River (Maryland, U.S.A). Our results indicate that die-off begins with conversion of marsh vegetation into bare open water pools that are relatively far (> 75 m) from tidal channels. As vegetation die-off continues, pools expand, and new pools emerge at shorter and shorter distances from channels. Consequently larger pools are found at larger distances from the channels. Our results suggest that the size of the pools and possibly the connection of pools with the tidal channel system have important bio-geomorphic implications and aggravate marsh deterioration. Moreover, we found that the temporal development of vegetation die-off in moderately degraded marshes is similar as the spatial die-off development along a present-day gradient, which indicates that the contemporary die-off gradient might be considered a chronosequence that offers a unique opportunity to study vegetation die-off processes.

Limnology and Oceanography↗
USGS2017

Spectral wave dissipation by submerged aquatic vegetation in a back-barrier estuary

Submerged aquatic vegetation is generally thought to attenuate waves, but this interaction remains poorly characterized in shallow-water field settings with locally generated wind waves. Better quantification of wave–vegetation interaction can provide insight to morphodynamic changes in a variety of environments and also is relevant to the planning of nature-based coastal protection measures. Toward that end, an instrumented transect was deployed across a Zostera marina (common eelgrass) meadow in Chincoteague Bay, Maryland/Virginia, U.S.A., to characterize wind-wave transformation within the vegetated region. Field observations revealed wave-height reduction, wave-period transformation, and wave-energy dissipation with distance into the meadow, and the data informed and calibrated a spectral wave model of the study area. The field observations and model results agreed well when local wind forcing and vegetation-induced drag were included in the model, either explicitly as rigid vegetation elements or implicitly as large bed-roughness values. Mean modeled parameters were similar for both the explicit and implicit approaches, but the spectral performance of the explicit approach was poor compared to the implicit approach. The explicit approach over-predicted low-frequency energy within the meadow because the vegetation scheme determines dissipation using mean wavenumber and frequency, in contrast to the bed-friction formulations, which dissipate energy in a variable fashion across frequency bands. Regardless of the vegetation scheme used, vegetation was the most important component of wave dissipation within much of the study area. These results help to quantify the influence of submerged aquatic vegetation on wave dynamics in future model parameterizations, field efforts, and coastal-protection measures.

Limnology and Oceanography↗
USGS2016

Dissolved methane in the Beaufort Sea and the Arctic Ocean, 1992-2009; sources and atmospheric flux

Methane concentration and isotopic composition was measured in ice-covered and ice-free waters of the Arctic Ocean during eleven surveys spanning the years of 1992-1995 and 2009. During ice-free periods, methane flux from the Beaufort shelf varies from 0.14 to 0.43 mg CH4 m-2 day-1. Maximum fluxes from localized areas of high methane concentration are up to 1.52 mg CH4 m-2 day-1. Seasonal buildup of methane under ice can produce short-term fluxes of methane from the Beaufort shelf that varies from 0.28 to 1.01 to mg CH4 m-2 day-1. Scaled-up estimates of minimum methane flux from the Beaufort Sea and pan-Arctic shelf for both ice-free and ice-covered periods range from 0.02 Tg CH4 yr-1 and 0.30 Tg CH4 yr-1 respectively to maximum fluxes of 0.18 Tg CH4 yr-1 and 2.2 Tg CH4 yr-1 respectively. A methane flux of 0.36 Tg CH4 yr-1from the deep Arctic Ocean was estimated using data from 1993-94. The flux can be as much as 2.35 Tg CH4 yr-1 estimated from maximum methane concentrations and wind speeds of 12 m/s, representing only 0.42% of the annual atmospheric methane budget of ~560 Tg CH4 yr-1. There were no significant changes in methane fluxes during the time period of this study. Microbial methane sources predominate with minor influxes from thermogenic methane offshore Prudhoe Bay and the Mackenzie River delta and may include methane from gas hydrate. Methane oxidation is locally important on the shelf and is a methane sink in the deep Arctic Ocean.

Limnology and Oceanography↗
USGS2017

A river-scale Lagrangian experiment examining controls on phytoplankton dynamics in the presence and absence of treated wastewater effluent high in ammonium

Phytoplankton are critical component of the food web in most large rivers and estuaries, and thus identifying dominant controls on phytoplankton abundance and species composition is important to scientists, managers, and policymakers. Recent studies from a variety of systems indicate that ammonium ( NH + 4 ) in treated wastewater effluent decreases primary production and alters phytoplankton species composition. However, these findings are based mainly on laboratory and enclosure studies, which may not adequately represent natural systems. To test effects of effluent high in ammonium on phytoplankton at the ecosystem scale, we conducted whole-river–scale experiments by halting discharges to the Sacramento River from the regional wastewater treatment plant (WWTP), and used a Lagrangian approach to compare changes in phytoplankton abundance and species composition in the presence (+EFF) and absence (−EFF) of effluent. Over 5 d of downstream travel from 20 km above to 50 km below the WWTP, chlorophyll concentrations declined from 15–25 to ∼2.5 μg L −1 , irrespective of effluent addition. Benthic diatoms were dominant in most samples. We found no significant difference in phytoplankton abundance or species composition between +EFF and −EFF conditions. Moreover, greatest declines in chlorophyll occurred upstream of the WWTP where NH + 4 concentrations were low. Grazing by clams and zooplankton could not account for observed losses, suggesting other factors such as hydrodynamics and light limitation were responsible for phytoplankton declines. These results highlight the advantages of conducting ecosystem-scale, Lagrangian-based experiments to understand the dynamic and complex interplay between physical, chemical, and biological factors that control phytoplankton populations.

California↗
USGS2017

Ecosystem variability along the estuarine salinity gradient: Examples from long-term study of San Francisco Bay

The salinity gradient of estuaries plays a unique and fundamental role in structuring spatial patterns of physical properties, biota, and biogeochemical processes. We use variability along the salinity gradient of San Francisco Bay to illustrate some lessons about the diversity of spatial structures in estuaries and their variability over time. Spatial patterns of dissolved constituents (e.g., silicate) can be linear or nonlinear, depending on the relative importance of river-ocean mixing and internal sinks (diatom uptake). Particles have different spatial patterns because they accumulate in estuarine turbidity maxima formed by the combination of sinking and estuarine circulation. Some constituents have weak or no mean spatial structure along the salinity gradient, reflecting spatially distributed sources along the estuary (nitrate) or atmospheric exchanges that buffer spatial variability of ecosystem metabolism (dissolved oxygen). The density difference between freshwater and seawater establishes stratification in estuaries stronger than the thermal stratification of lakes and oceans. Stratification is strongest around the center of the salinity gradient and when river discharge is high. Spatial distributions of motile organisms are shaped by species-specific adaptations to different salinity ranges (shrimp) and by behavioral responses to environmental variability (northern anchovy). Estuarine spatial patterns change over time scales of events (intrusions of upwelled ocean water), seasons (river inflow), years (annual weather anomalies), and between eras separated by ecosystem disturbances (a species introduction). Each of these lessons is a piece in the puzzle of how estuarine ecosystems are structured and how they differ from the river and ocean ecosystems they bridge.

California↗
USGS2017

Seasonality of change: Summer warming rates do not fully represent effects of climate change on lake temperatures

Responses in lake temperatures to climate warming have primarily been characterized using seasonal metrics of surface-water temperatures such as summertime or stratified period average temperatures. However, climate warming may not affect water temperatures equally across seasons or depths. We analyzed a long-term dataset (1981–2015) of biweekly water temperature data in six temperate lakes in Wisconsin, U.S.A. to understand (1) variability in monthly rates of surface- and deep-water warming, (2) how those rates compared to summertime average trends, and (3) if monthly heterogeneity in water temperature trends can be predicted by heterogeneity in air temperature trends. Monthly surface-water temperature warming rates varied across the open-water season, ranging from 0.013 in August to 0.073°C yr −1 in September (standard deviation [SD]: 0.025°C yr −1 ). Deep-water trends during summer varied less among months (SD: 0.006°C yr −1 ), but varied broadly among lakes (–0.056°C yr −1 to 0.035°C yr −1 , SD: 0.034°C yr −1 ). Trends in monthly surface-water temperatures were well correlated with air temperature trends, suggesting monthly air temperature trends, for which data exist at broad scales, may be a proxy for seasonal patterns in surface-water temperature trends during the open water season in lakes similar to those studied here. Seasonally variable warming has broad implications for how ecological processes respond to climate change, because phenological events such as fish spawning and phytoplankton succession respond to specific, seasonal temperature cues.

Wisconsin↗
USGS2017

Historical patterns of acidification and increasing CO2 flux associated with Florida springs

Florida has one of the highest concentrations of springs in the world, with many discharging into rivers and predominantly into eastern Gulf of Mexico coast, and they likely influence the hydrochemistry of these adjacent waters; however, temporal and spatial trends have not been well studied. We present over 20 yr of hydrochemical, seasonally sampled data to identify temporal and spatial trends of pH, alkalinity, partial pressure of carbon dioxide (pCO 2 ), and CO 2 flux from five first-order-magnitude (springs that discharge greater than 2.83 m 3 s −1 ) coastal spring groups fed by the Floridan Aquifer System that ultimately discharge into the Gulf of Mexico. All spring groups had pCO 2 levels (averages 3174.3–6773.2 μatm) that were much higher than atmospheric levels of CO 2 and demonstrated statistically significant temporal decreases in pH and increases in CO 2 flux, pCO 2 , and alkalinity. Total carbon flux emissions increased from each of the spring groups by between 3.48 × 10 7 and 2.856 × 10 8 kg C yr −1 over the time period. By 2013 the Springs Groups in total emitted more than 1.1739 × 10 9 kg C yr −1 . Increases in alkalinity and pCO 2 varied from 90.9 to 347.6 μmol kg −1 and 1262.3 to 2666.7 μatm, respectively. Coastal data show higher CO 2 evasion than the open Gulf of Mexico, which suggests spring water influences nearshore waters. The results of this study have important implications for spring water quality, dissolution of the Florida carbonate platform, and identification of the effect and partitioning of carbon fluxes to and within coastal and marine ecosystems.

Florida↗
USGS2017

Disrupted carbon cycling in restored and unrestored urban streams: Critical timescales and controls

Carbon fixation and respiration in flowing waterways play significant roles in global and regional carbon budgets, yet how land use and watershed management interact with temporal disturbances (storms) to influence metabolism remains poorly understood. Here, we combine long-term with synoptic sampling of metabolism and its variable controls in neighboring watersheds of the Chesapeake Bay to resolve limiting factors and critical timescales associated with recovery from disturbance. We found that, relative to predictions of the river continuum concept, focal streams have “disrupted” carbon cycles, with carbon balances closer to zero, and, in some cases, tighter coupling between gross primary production (GPP) and ecosystem respiration (ER), attributable to carbon limitation. Carbon became limiting to ER where flashy storm hydrographs and simplified channel geomorphology inhibited accumulation of fine sediment. Shannon entropy analysis of timescales revealed that fine sediment served as a time-release capsule for nutrients and carbon over 4–6 months, fueling biogeochemical transformations. Loss of fines through hydraulic disturbance had up to 30-d impacts on GPP and 50-d impacts on ER in the stream with carbon limitation. In contrast, where GPP and ER were not tightly coupled, recovery occurred within 1 d. Results suggest that a complex interplay between nutrient and carbon limitation and mechanical and chemical disturbance governs patterns and consequences of disrupted carbon cycling in urban streams. Carbon limitation and tight GPP/ER coupling enhance the vulnerability of stream ecosystem functions, but best management practices that target stormflow reduction and channel geomorphic diversity can break that coupling and minimize carbon cycle disruptions.

Limnology and Oceanography↗
USGS2017

The land-sea interface: A source of high-quality phytoplankton to support secondary production

Coastal-estuarine systems are among the most productive marine ecosystems and their special role in producing harvestable fish and shellfish has been attributed to high primary production fueled by nutrient runoff from land and efficient trophic transfer. Here we ask if phytoplankton species composition and their food quality based on the percentage of long-chain essential fatty acids (LCEFA) is another factor contributing to high secondary production in these ecosystems. We used long-term measurements of major phytoplankton taxonomic groups and estimated their content of LCEFA along the salinity gradient in coastal-estuarine ecosystems, with emphasis on Chesapeake Bay and the Baltic Sea, and an oceanic transect. Our data show that cyanobacteria with low nutritional quality often dominate at low-salinity regions, while intermediate to higher salinity regions produce diatoms and dinoflagellates that have a higher content of LCEFA and are thus a higher-quality food resource for consumers. Higher salinity regions have less pronounced seasonal changes in the percentage of phytoplankton LCEFA compared to low salinity regions, providing a stable supply of nutritious phytoplankton to consumers. The phytoplankton LCEFA content is similarly high in coastal upwelling systems and it decreases further offshore in oligotrophic oceanic regions dominated by picophytoplankton. Our results from a broad range of coastal-ecosystem types show that ecosystems at the land-sea interface provide a valuable service by producing phytoplankton enriched in the biochemicals essential for consumers. High primary production, coupled with high quality of that production, explain why the production of fish and shellfish is high where land and sea meet.

Limnology and Oceanography↗
USGS2017

The metabolic regimes of flowing waters

The processes and biomass that characterize any ecosystem are fundamentally constrained by the total amount of energy that is either fixed within or delivered across its boundaries. Ultimately, ecosystems may be understood and classified by their rates of total and net productivity and by the seasonal patterns of photosynthesis and respiration. Such understanding is well developed for terrestrial and lentic ecosystems but our understanding of ecosystem phenology has lagged well behind for rivers. The proliferation of reliable and inexpensive sensors for monitoring dissolved oxygen and carbon dioxide is underpinning a revolution in our understanding of the ecosystem energetics of rivers. Here, we synthesize our current understanding of the drivers and constraints on river metabolism, and set out a research agenda aimed at characterizing, classifying and modeling the current and future metabolic regimes of flowing waters.

Limnology and Oceanography↗
USGS2017

Associations between cyanobacteria and indices of secondary production in the western basin of Lake Erie

Large lakes provide a variety of ecological services to surrounding cities and communities. Many of these services are supported by ecological processes that are threatened by the increasing prevalence of cyanobacterial blooms which occur as aquatic ecosystems experience cultural eutrophication. Over the past 10 yr, Lake Erie experienced cyanobacterial blooms of increasing severity and frequency, which have resulted in impaired drinking water for the surrounding communities. Cyanobacterial blooms may impact ecological processes that support other services, but many of these impacts have not been documented. Secondary production (production of primary consumers) is an important process that supports economically important higher trophic levels. Cyanobacterial blooms may influence secondary production because cyanobacteria are a poor‐quality food resource and cyanotoxins may be harmful to consumers. Over 3 yr at 34 sites across the western basin of Lake Erie, we measured three indices of secondary production that focus on the dominant bivalve taxa: (1) growth of a native unionid mussel, (2) the size of young‐of‐year dreissenid mussels, and (3) the mass of colonizing animals on a Hester‐Dendy sampler. Associations between these indices and cyanobacterial data were estimated to assess whether cyanobacteria are associated with variation in secondary production in the western basin of Lake Erie. The results suggest cyanobacterial abundance alone is only weakly associated with secondary production, but that cyanotoxins have a larger effect on secondary production. Given recurring late‐summer cyanobacterial blooms, this impact on secondary production has the potential to undermine Lake Erie's ability to sustain important ecosystem services.

Lake Erie↗
USGS2017

Evidence for regional nitrogen stress on chlorophyll a in lakes across large landscape and climate gradients

Nitrogen (N) and phosphorus (P) commonly stimulate phytoplankton production in lakes, but recent observations from lakes from an agricultural region suggest that nitrate may have a subsidy‐stress effect on chlorophyll a (Chl a ). It is unclear, however, how generalizable this effect might be. Here, we analyzed a large water quality dataset of 2385 lakes spanning 60 regions across 17 states in the Northeastern and Midwestern U.S. to determine if N subsidy‐stress effects on phytoplankton are common and to identify regional landscape characteristics promoting N stress effects in lakes. We used a Bayesian hierarchical modeling framework to test our hypothesis that Chl a –total N (TN) threshold relationships would be common across the central agricultural region of the U.S. (“the Corn Belt”), where lake N and P concentrations are high. Data aggregated across all regions indicated that high TN concentrations had a negative effect on Chl a in lakes with concurrent high total P. This large‐scale pattern was driven by relationships within only a subset of regions, however. Eight regions were identified as having Chl a –TN threshold relationships, but only two of these regions located within the Corn Belt clearly demonstrated this subsidy‐stress relationship. N stress effects were not consistent across other intense agricultural regions, as we hypothesized. These findings suggest that interactions among regional land use and land cover, climate, and hydrogeology may be important in determining the synergistic conditions leading to N subsidy‐stress effects on lake phytoplankton.

Limnology and Oceanography↗
USGS2017

Why large cells dominate estuarine phytoplankton

Surveys across the world oceans have shown that phytoplankton biomass and production are dominated by small cells (picoplankton) where nutrient concentrations are low, but large cells (microplankton) dominate when nutrient-rich deep water is mixed to the surface. I analyzed phytoplankton size structure in samples collected over 25 yr in San Francisco Bay, a nutrient-rich estuary. Biomass was dominated by large cells because their biomass selectively grew during blooms. Large-cell dominance appears to be a characteristic of ecosystems at the land–sea interface, and these places may therefore function as analogs to oceanic upwelling systems. Simulations with a size-structured NPZ model showed that runs of positive net growth rate persisted long enough for biomass of large, but not small, cells to accumulate. Model experiments showed that small cells would dominate in the absence of grazing, at lower nutrient concentrations, and at elevated (+5°C) temperatures. Underlying these results are two fundamental scaling laws: (1) large cells are grazed more slowly than small cells, and (2) grazing rate increases with temperature faster than growth rate. The model experiments suggest testable hypotheses about phytoplankton size structure at the land–sea interface: (1) anthropogenic nutrient enrichment increases cell size; (2) this response varies with temperature and only occurs at mid-high latitudes; (3) large-cell blooms can only develop when temperature is below a critical value, around 15°C; (4) cell size diminishes along temperature gradients from high to low latitudes; and (5) large-cell blooms will diminish or disappear where planetary warming increases temperature beyond their critical threshold.

Limnology and Oceanography↗
USGS2018

Combining nutrient, productivity, and landscape-based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales

Empirical nutrient models that describe lake nutrient, productivity, and water clarity relationships among lakes play a prominent role in limnology. Landscape-based regressions are also used to understand macroscale variability of lake nutrients, clarity, and productivity (hereafter referred to as nutrient-productivity). Predictions from both models are used to inform eutrophication management globally. To date, these two classes of models are generally conducted separately, which ignores the known dependencies among nutrient-productivity variables. We present a statistical model that integrates nutrient-productivity and landscape-based regressions—where lake nutrients, productivity, and clarity variables are modeled jointly. We fitted a joint nutrient-productivity model to over 7000 lakes with three nutrients (total phosphorus, total nitrogen, nitrate concentrations), chlorophyll a concentrations, and Secchi disk depth as response variables and landscape features as predictor variables. Because lakes in different regions respond to landscape features differently, we focused our analysis on two subregions with different dominant land uses, the agricultural Midwest and the forested Northeast U.S. Predictive performance was enhanced by modeling nutrient-productivity variables jointly. We also found strong evidence that nutrient-productivity variables were coupled, and that only nitrate may be decoupled from other nutrient-productivity variables in the forested region. We speculate that these regional differences may be related to differences in the strength of biogeochemical cycles and stoichiometric controls between these regions. Jointly modeling nutrient-productivity variables in lakes effectively integrates the two dominant approaches for studying lakes nutrient-productivity relationships and provides novel insight into macroscale patterns of the coupling of nutrients, chlorophyll, and water clarity in lakes.

Limnology and Oceanography↗
USGS2018

Changes in long-term water quality of Baltimore streams are associated with both gray and green infrastructure

The steadily rising global urban population has placed substantial strain on urban water quality, and this strain is projected to increase for the foreseeable future. Considerable attention has been given to the hydrological and physico-chemical effects of urbanization on stream ecosystems. However, due to the relative infancy of the field of urban ecology, long-term water quality analyses in urban streams are sparse. Using a 15-year stream chemistry monitoring record from Baltimore, MD, USA, we quantified long-term trends in nitrate, phosphate, total nitrogen, total phosphorus, chloride, and sulfate export at several sites along a rural-urban gradient. We found no significant change in solute export at most sites, although we did find specific patterns of interest for certain solutes. For example, nitrogen export declined at the most headwater urban site, while phosphorus export declined at the most downstream urban site. Coupling long-term monitoring with data on gray and green infrastructure management throughout the landscape, we established relationships between solute export at the most downstream urban monitoring site and sanitary sewer overflows (SSOs), best management practice (BMP) implementation, and road salt application rates. Phosphorus export was correlated with BMP implementation in the watershed, whereas nitrogen export was related to SSOs. Despite highly urbanized watersheds, water quality does not appear to be declining at most of these sites, suggesting that current management may have limited further impairment. Results of our study suggest that both gray and green infrastructure are key for maintaining and improving water quality in this highly urbanized watershed.

Maryland↗
USGS2018

Patterns, pace and processes of water-quality variability: Examples from a long-studied estuary

Environmental time series have rich information content that is invaluable for measuring and understanding changes over time and guiding policies to manage change. I extracted information from measurements of 10 water‐quality constituents in upper San Francisco Bay from 1975 to 2016, one of the longest observational records in a U.S. estuary. Changes were detected at every time scale captured by monthly sampling. Long‐term trends included increased ammonium (+53%), nitrate + nitrate (+50%), silicate (+14%), Secchi depth (+42%), and decreased chlorophyll a (Chl a ) (−74%) and suspended particulate matter (−45%). Changes at the decadal scale included abrupt shifts (Chl a , nitrate + nitrite) and oscillations between shorter trends of increase and decrease (Secchi depth, phosphate). Long‐term trends were not expressed equally across all seasons, and seasonal patterns of change varied across constituents. These examples illustrate key features of environmental variability at the land–sea interface: (1) water‐quality components change continually at time scales from months to decades; (2) patterns of seasonal, multiyear, and multidecadal change are complex and vary across constituents; (3) primary drivers of change are freshwater inflow, the master regulator of estuarine dynamics, and human activities such as river damming, water diversions, wastewater discharge, environmental policies, and species introductions; (4) extracting the full information content of time series requires multiple analyses, each revealing a different layer of insight into how changes develop over time; (5) water‐quality variability is nonstationary, so future changes cannot be forecast reliably; (6) repeated observation is an essential method of Earth system science with applications in the design and performance measures of environmental policies.

California↗
USGS2019

Estimating lake–climate responses from sparse data: An application to high elevation lakes

Although many studies demonstrate lake warming, few document trends from lakes with sparse data. Diel and seasonal variability of surface temperatures limit conventional trend analyses to datasets with frequent repeated observations. Thus, remote lakes, including many high elevation lakes, are underrepresented in trend analyses. We used a Bayesian technique to analyze sparse data that explicitly incorporated diel and seasonal variability. This approach allowed us to estimate lake warming in a region of limited knowledge: high elevation lakes (> 2100 m ASL) of the Southern Rocky Mountains, U.S.A. The analysis allowed for inclusion of lakes with few repeated measurements, and observations made before 1980 when more intensive lake monitoring began. We accumulated the largest dataset of high elevation lake temperatures analyzed to date. Data from 590 high elevation lakes in the Southern Rocky Mountains showed a 0.13°C decade −1 increase in surface temperatures and a 14% increase in seasonal degree days since 1955. This result is lower than other regional and global estimates of lake warming; however, it is similar to other high elevation lake studies. Our approach can be applied to other understudied regions, increasing our overall understanding of the effects of climate change on lakes and their temporal dynamics.

Colorado↗
USGS2019

Metabolic rhythms in flowing waters: An approach for classifying river productivity regimes

Although seasonal patterns of ecosystem productivity have been extensively described and analyzed with respect to their primary forcings in terrestrial and marine systems, comparatively little is known about these same processes in rivers. However, it is now possible to perform a large‐scale synthesis on the patterns and drivers of river productivity regimes because of the recent sensor advances allowing for near‐continuous estimates of river productivity. Here, we explore a dataset of 47 U.S. rivers to examine whether there are characteristic river productivity regimes. We use classification approaches to develop a typology of productivity regimes and then use these regimes to examine differences with respect to potential controls of productivity. We identified two distinct metabolic regimes, which we named Summer Peak and Spring Peak Rivers, within our dataset. These regimes meaningfully differed in both the timing and magnitude of productivity and were robust to different approaches to classification. We also found that several variables, including watershed area and characteristics of water temperature or discharge, were able to predict the class membership of these regimes with modest accuracy. Our results support the presence of characteristic metabolic regimes and suggests that these regimes may have common sets of environmental controls. We present classification as one approach to begin exploring the productivity regimes of rivers. The strength of our approach is that it fully leverages these newly available high‐frequency productivity estimates to create classes that can be used to draw inferences about how the controls of river productivity differ between or within systems.

Limnology and Oceanography↗