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Real-time monitoring usingin-situsensors is becoming a common approach for measuring water-quality within watersheds. High-frequency measurements produce big datasets that present opportunities to conduct new analyses for improved understanding of water-quality dynamics and more effective management of rivers and streams. Of primary importance is enhancing knowledge of the relationships between nitrate, one of the most reactive forms of inorganic nitrogen in the aquatic environment, and other water-quality variables. We analysed high-frequency water-quality data fromin-situsensors deployed in three sites from different watersheds and climate zones within the National Ecological Observatory Network, USA. We used generalised additive mixed models to explain the nonlinear relationships at each site between nitrate concentration and conductivity, turbidity, dissolved oxygen, water temperature, and elevation. Temporal auto-correlation was modelled with an auto-regressive–moving-average (ARIMA) model and we examined the relative importance of the explanatory variables. Total deviance explained by the models was high for all sites (99%). Although variable importance and the smooth regression parameters differed among sites, the models explaining the most variation in nitrate contained the same explanatory variables. This study demonstrates that building a model for nitrate using the same set of explanatory water-quality variables is achievable, even for sites with vastly different environmental and climatic characteristics. Applying such models will assist managers to select cost-effective water-quality variables to monitor when the goals are to gain a spatial and temporal in-depth understanding of nitrate dynamics and adapt management plans accordingly.

 

Autotrophic and heterotrophic microbes in stream biofilms dominate biogeochemical cycling and rely on nutrient and energy resources for growth and productivity. In the boreal forest, variation in these resources can originate from permafrost distribution and controls competition for nutrients between stream autotrophs and heterotrophs. We investigated which resources control nutrient uptake and metabolism in headwater stream biofilms of subarctic Alaska, USA, and how resource availability affects competition for inorganic nutrients. We hypothesized that the competitive outcome between autotrophs and heterotrophs for inorganic nutrients would be dependent on availability of organic C, or inorganic nutrients (N and P). To test our hypotheses, we measured resource limitation at the patch and reach scales along a permafrost gradient in interior Alaska. At the patch scale, nutrient diffusing substrata revealed that, secondary to light, N and P were colimiting to autotrophic growth, whereas C was primarily limiting to heterotrophic respiration. In the presence of labile C, heterotrophs exhibited a larger response to nutrient enrichment and outcompeted autotrophs for inorganic nutrients. At the reach scale, light availability had the largest influence on nutrient uptake, but inorganic nutrients were also important. The positive response to increased nutrient and C availability at the patch scale suggests that the predicted increase in exports into fluvial networks with permafrost degradation will alter biofilm structure and function. Ultimately, biofilm communities will shift to more heterotroph-dominated patches if heterotrophs outcompete autotrophs for inorganic nutrients. As permafrost thaws and nutrients and organic C mobilize into streams, nutrient uptake dynamics and competition within biofilms will be altered, affecting nutrient use and export. 

Key Points We compared tools for describing streamflow timeseries, including streamflow metrics, wavelet, and Fourier analysis Each method indicated streamflow data are structured: variability at short timescales is negatively correlated with long timescales Globally, dams were less correlated with streamflow regime than catchment size and climate were 

In situ sensors that collect high-frequency data are used increasingly to monitor aquatic environments. These sensors are prone to technical errors, resulting in unrecorded observations and/or anomalous values that are subsequently removed and create gaps in time series data. We present a framework based on generalized additive and auto-regressive models to recover these missing data. To mimic sporadically missing (i) single observations and (ii) periods of contiguous observations, we randomly removed (i) point data and (ii) day- and week-long sequences of data from a two-year time series of nitrate concentration data collected from Arikaree River, USA, where synoptically collected water temperature, turbidity, conductance, elevation, and dissolved oxygen data were available. In 72% of cases with missing point data, predicted values were within the sensor precision interval of the original value, although predictive ability declined when sequences of missing data occurred. Precision also depended on the availability of other water quality covariates. When covariates were available, even a sudden, event-based peak in nitrate concentration was reconstructed well. By providing a promising method for accurate prediction of missing data, the utility and confidence in summary statistics and statistical trends will increase, thereby assisting the effective monitoring and management of fresh waters and other at-risk ecosystems. 

Abstract Forest and freshwater ecosystems are tightly linked and together provide important ecosystem services, but climate change is affecting their species composition, structure, and function. Research at nine US Long Term Ecological Research sites reveals complex interactions and cascading effects of climate change, some of which feed back into the climate system. Air temperature has increased at all sites, and those in the Northeast have become wetter, whereas sites in the Northwest and Alaska have become slightly drier. These changes have altered streamflow and affected ecosystem processes, including primary production, carbon storage, water and nutrient cycling, and community dynamics. At some sites, the direct effects of climate change are the dominant driver altering ecosystems, whereas at other sites indirect effects or disturbances and stressors unrelated to climate change are more important. Long-term studies are critical for understanding the impacts of climate change on forest and freshwater ecosystems. 

Fluvial silicon (Si) plays a critical role in controlling primary production, water quality, and carbon sequestration through supporting freshwater and marine diatom communities. Geological, biogeochemical, and hydrological processes, as well as climate and land use, dictate the amount of Si exported by streams. Understanding Si regimes—the seasonal patterns of Si concentrations—can help identify processes driving Si export. We analyzed Si concentrations from over 200 stream sites across the Northern Hemisphere to establish distinct Si regimes and evaluated how often sites moved among regimes over their period of record. We observed five distinct regimes across diverse stream sites, with nearly 60% of sites exhibiting multiple regime types over time. Our results indicate greater spatial and interannual variability in Si seasonality than previously recognized and highlight the need to characterize the watershed and climate variables that affect Si cycling across diverse ecosystems.

 

Riverine exports of silicon (Si) influence global carbon cycling through the growth of marine diatoms, which account for ∼25% of global primary production. Climate change will likely alter river Si exports in biome‐specific ways due to interacting shifts in chemical weathering rates, hydrologic connectivity, and metabolic processes in aquatic and terrestrial systems. Nonetheless, factors driving long‐term changes in Si exports remain unexplored at local, regional, and global scales. We evaluated how concentrations and yields of dissolved Si (DSi) changed over the last several decades of rapid climate warming using long‐term data sets from 60 rivers and streams spanning the globe (e.g., Antarctic, tropical, temperate, boreal, alpine, Arctic systems). We show that widespread changes in river DSi concentration and yield have occurred, with the most substantial shifts occurring in alpine and polar regions. The magnitude and direction of trends varied within and among biomes, were most strongly associated with differences in land cover, and were often independent of changes in river discharge. These findings indicate that there are likely diverse mechanisms driving change in river Si biogeochemistry that span the land‐water interface, which may include glacial melt, changes in terrestrial vegetation, and river productivity. Finally, trends were often stronger in months outside of the growing season, particularly in temperate and boreal systems, demonstrating a potentially important role of shifting seasonality for the flux of Si from rivers. Our results have implications for the timing and magnitude of silica processing in rivers and its delivery to global oceans.

 

Retention of carbon (C), either by physical mechanisms or microbial uptake, is a key driver of the transformation and storage of C and nutrients within ecosystems. Both the molecular composition and nutrient content of organic matter influence the rate at which it is retained in streams, but the relative influence of these characteristics remains unclear. We estimated the effects of nutrient content and molecular composition of dissolved organic C (DOC) on uptake in boreal streams by measuring rates of C retention, in situ, following introduction of leachates derived from alder, poplar, and spruce trees subject to long-term fertilization with nitrogen (N) or phosphorus (P). Leachate C:N varied approximately twofold, and C:P varied nearly 20-fold across species and nutrient treatments. Uptake of DOC was greatest for leachates derived from trees that had been fertilized with P, a finding consistent with P-limitation of uptake and/or preferential sorption of P-containing molecules. Optical measures indicated that leachates derived from the three tree species varied in molecular composition, but uptake of DOC did not differ across species, suggesting weak constraints on retention imposed by molecular composition relative to nutrient limitation. Observed coupling between P and C cycles highlights the potential for increased P availability to enhance DOC retention in headwater streams.