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Stream bryophytes (mosses and liverworts) are widely recognized as important macroinvertebrate habitats, but their overall role in the stream ecosystem, particularly in nutrient cycling, remains understudied. Hubbard Brook Experimental Forest in New Hampshire, USA, contains some of the most extensively researched streams in the world, yet few studies mention their bryophytes. Perhaps this is because early estimates place bryophyte coverage in these streams at an insignificant 2%. However, data from 2019 show that contemporary coverage ranges from 4 to 40% among streams. To investigate how stream bryophyte cover may be changing over time and influencing stream nutrient stocks, we conducted field surveys, measured the mass of organic and inorganic bryophyte contents, and quantified nutrient uptake with bottle incubations of bryophyte mats. This study marks a novel attempt to map stream bryophyte coverage with estimates of C, P, and N stocks and fluxes. From our 2022 field surveys, we found that median bryophyte coverage varied across streams in the same catchment (0–41.4%) and shifted from just 3 y prior. We estimate that these bryophyte mats stored between 14 and 414 g of organic matter per m2 of stream in the form of live biomass and captured particulates. Within 12 h of light incubation, 35 out of 36 bryophyte clump samples sorbed peak historical water-column concentrations of PO43– as measured in the Hubbard Brook stream chemistry record. In Bear Brook, our scaled estimate of bryophyte mat NO3– uptake (2.3 g N/y) constitutes a substantial portion of previously estimated whole-stream NO3– uptake (12 g N/y). Cumulatively, our data demonstrate that bryophytes and their associated mineral substrates and biota—known as the bryosphere—are crucial in facilitating headwater stream nutrient cycling. These bryospheres may contribute significantly to interannual variability in stream nutrient concentrations within nutrient-poor streams, especially in climate-sensitive regions. 

Abstract. Quantifying continuous discharge can be difficult, especially for nascent monitoring efforts, due to the challenges of establishing gauging locations, sensor protocols, and installations. Some continuous discharge series generated by the National Ecological Observatory Network (NEON) during its pre- and early-operational phases (2015–present) are marked by anomalies related to sensor drift, gauge movement, and incomplete rating curves. Here, we investigate the potential to estimate continuous discharge when discrete streamflow measurements are available at the site of interest. Using field-measured discharge as truth, we reconstructed continuous discharge for all 27 NEON stream gauges via linear regression on nearby donor gauges and/or prediction from neural networks trained on a large corpus of established gauge data. Reconstructions achieved median efficiencies of 0.83 (Nash–Sutcliffe, or NSE) and 0.81 (Kling–Gupta, or KGE) across all sites and improved KGE at 11 sites versus published data, with linear regression generally outperforming deep learning approaches due to the use of target site data for model fitting rather than evaluation only. Estimates from this analysis inform ∼199 site-months of missing data in the official record, and can be used jointly with NEON data to enhance the descriptive and predictive value of NEON's stream data products. We provide 5 min composite discharge series for each site that combine the best estimates across modeling approaches and NEON's published data. The success of this effort demonstrates the potential to establish “virtual gauges”, sites at which continuous streamflow can be accurately estimated from discrete measurements, by transferring information from nearby donor gauges and/or large collections of training data. 

This is the data and code associated with "Stream bryophytes promote 'cryptic' productivity in highly oligotrophic headwaters. Recent observations document increased abundance of algae in the headwater streams of Hubbard Brook Experimental Forest (HBEF). It is possible that this 'greening up' of HBEF streams may be due to climate change with rising temperatures, altered terrestrial phenology, and shifting hydrologic regimes. Alternatively, stream 'greening' could be due to the slow recovery of stream chemistry from decades of acid rain, which have led to rising stream water pH, declining concentrations of toxic Al3+, and extremely low solute concentrations. Three years of weekly algal measurements on contrasting substrates, 6 nutrient enrichment experiments reveal important new insights about the interactions between these two groups of autotrophs. We predicted that light availability, hydrologic disturbance and nutrient limitation were all important determinants of algal biomass in streams. To evaluate the relative strength and hierarchy of these limiting factors, we used nutrient diffusing substrates to investigate the role of nutrients for algae and compared algal accrual rate on artificial rock vs. moss substrates in stream channels vs. weir ponds to assess the role of hydrologic disturbance and scour. Our surveys and experiments spanned across seasons and local light regimes. Algal biomass was substantially higher in protected weir ponds than in stream channels, and in both habitats, algal biomass was substantially higher on artificial moss substrates than on tiles. Taken together, these results suggest that moss can provide physical protection from flood scour. Algal biomass instream on both substrate types was higher in high light seasons (pre-leaf out) and well-lit habitats indicating strong light limitation. Results from a series of 6 nutrient diffusing substrate experiments over the course of 2 years provided little evidence of nutrient limitation instream. The most striking finding of our investigation is the previously unsuspected role of stream bryophytes in providing critical refugia for algae in these steep, heavily shaded and oligotrophic headwaters. Shifts in stream productivity over time are likely to be closely tied to changes in bryophyte cover. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. 

Nitrogen (N) is a critical element in many ecological and biogeochemical processes in forest ecosystems. Cycling of N is sensitive to changes in climate, atmospheric carbon dioxide (CO2) concentrations, and air pollution. Streamwater nitrate draining a forested ecosystem can indicate how an ecosystem is responding to these changes. We observed a pulse in streamwater nitrate concentration and export at a long-term forest research site in eastern North America that resulted in a 10-fold increase in nitrate export compared to observations over the prior decade. The pulse in streamwater nitrate occurred in a reference catchment in the 2013 water year, but was not associated with a distinct disturbance event. We analyzed a suite of environmental variables to explore possible causes. The correlation between each environmental variable and streamwater nitrate concentration was consistently higher when we accounted for the antecedent conditions of the variable prior to a given streamwater observation. In most cases, the optimal antecedent period exceeded two years. We assessed the most important variables for predicting streamwater nitrate concentration by training a machine learning model to predict streamwater nitrate concentration in the years preceding and during the streamwater nitrate pulse. The results of the correlation and machine learning analyses suggest that the pulsed increase in streamwater nitrate resulted from both (1) decreased plant uptake due to lower terrestrial gross primary production, possibly due to increased soil frost or reduced solar radiation or both; and (2) increased net N mineralization and nitrification due to warm temperatures from 2010 to 2013. Additionally, variables associated with hydrological transport of nitrate, such as maximum stream discharge, emerged as important, suggesting that hydrology played a role in the pulse. Overall, our analyses indicate that the streamwater nitrate pulse was caused by a combination of factors that occurred in the years prior to the pulse, not a single disturbance event. 

Abstract Accurately estimating stream discharge is crucial for many ecological, biogeochemical, and hydrologic analyses. As of September 2022, The National Ecological Observatory Network (NEON) provided up to 5 years of continuous discharge estimates at 28 streams across the United States. NEON created rating curves at each site in a Bayesian framework, parameterized using hydraulic controls and manual measurements of discharge. Here we evaluate the reliability of these discharge estimates with three approaches. We (1) compared predicted to observed discharge, (2) compared predicted to observed stage, and (3) calculated the proportion of discharge estimates extrapolated beyond field measurements. We considered 1,523 site-months of continuous streamflow predictions published by NEON. Of these, 39% met our highest quality criteria, 11% fell into an intermediate classification, and 50% of site-months were classified as unreliable. We provided diagnostic metrics and categorical evaluations of continuous discharge and stage estimates by month for each site, enabling users to rapidly query for suitable NEON data.