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The pace and trajectory of ecosystem development are governed by the availability and cycling of limiting nutrients, and anthropogenic disturbances such as acid rain and deforestation alter these trajectories by removing substantial quantities of nutrients via titration or harvest. Here, we use six decades of continuous chemical and hydrologic data from three adjacent headwater catchments in the Hubbard Brook Experimental Forest, New Hampshire—one deforested (W5), one CaSiO3-enriched (W1), and one reference (W6)—to quantify long-term nutrient and mineral fluxes. Acid deposition since 1900 drove pronounced depletion and export of base cations, particularly calcium, across all watersheds. Experimental deforestation of W5 intensified loss of biomass and nutrient cations and triggered sustained increases in streamwater pH, Ca2+, and SiO2 exports over nearly four decades, greatly exceeding the effects of direct CaSiO3 enrichment in both duration and magnitude. We detect no long-term changes in water yield or water flow paths in the experimental watersheds, and we attribute this multidecadal increase in weathering rates following deforestation to biological responses to severe nutrient limitation. Our evidence suggests that in the regrowing forest, plants are investing photosynthate into belowground processes that amplify mineral weathering to access phosphorus and micronutrients, consequently elevating the export of less limiting elements present in silicate parent material. Throughout decades of forest regrowth, enhanced biotic weathering has continued to deplete the acid buffering capacity of the terrestrial ecosystem while the export of weathering products has elevated the pH of the receiving stream. 

Machine‐learning models have been surprisingly successful at predicting stream solute concentrations, even for solutes without dedicated sensors. It would be extremely valuable if these models could predict solute concentrations in streams beyond the one in which they were trained. We assessed the generalizability of random forest models by training them in one or more streams and testing them in another. Models were made using grab sample and sensor data from 10 New Hampshire streams and rivers. As observed in previous studies, models trained in one stream were capable of accurately predicting solute concentrations in that stream. However, models trained on one stream produced inaccurate predictions of solute concentrations in other streams, with the exception of solutes measured by dedicated sensors (i.e., nitrate and dissolved organic carbon). Using data from multiple watersheds improved model results, but model performance was still worse than using the mean of the training dataset (Nash–Sutcliffe Efficiency < 0). Our results demonstrate that machine‐learning models thus far reliably predict solute concentrations only where trained, as differences in solute concentration patterns and sensor‐solute relationships limit their broader applicability. 

The Lamprey River watershed, located in southeastern New Hampshire (USA), drains 554 km² of low elevation land before discharging into the Great Bay Estuary (Wymore and others 2021). The watershed is classified as suburban with mixed land-use that includes forests (73%), wetlands (10%), development (7%), and agriculture (NOAA Coastal Change Analysis Program 2016). We selected four distinct sites within the watershed to capture the dynamics of both tributaries and the mainstem, while accounting for variations in land use, land cover, and nutrient availability. Wednesday Hill Brook (WHB) is a 1st-order stream that drains a residential landscape and has the highest NO3 concentrations among the sites due to a high density of septic systems (Flint and McDowell 2015). Dowst Cate Forest (DCF) is a 2nd-order stream draining a headwater wetland and forested landscape and is characterized by the highest concentrations of dissolved organic carbon (DOC). The two main stem Lamprey River sites, LMP72 and LMP73, exhibit moderate concentrations of both DOC and NO3 and are located approximately 1 km apart. LMP72 is located at a low-head run-of-river dam while LMP73 is free-flowing water downstream of the reservoir. Our dataset includes weekly water chemistry and dissolved gas data collected from April 2014 through May 2023, except for DCF where data collection ended in 2021, resulting in a total of 1,179 observations across the four different sites. 

Abstract Riverine silicon (Si) plays a vital role in governing primary production, water quality, and carbon cycling. Climate and land cover change have altered how dissolved Si (DSi) is processed on land, transported to rivers, and cycled through aquatic ecosystems. The Global Aggregation of Stream Silica (GlASS) database was constructed to assess changes in river Si concentrations and fluxes, their relationship to other nutrients (nitrogen (N) and phosphorus (P)), and to evaluate mechanisms driving the availability of Si. GlASS includes concentrations of DSi, dissolved inorganic N (NO₃, NO_x, and NH₄), and dissolved inorganic P (as soluble reactive P or PO₄-P) at daily to quarterly time steps from 1963 to 2024; daily discharge; and watershed characteristics for 421 rivers spanning eight climate zones. Original data sources are cited, data quality assurance workflows are public, and input files to a common load model are provided. GlASS offers critical data to address questions about patterns, controls, and trajectories of global river Si biogeochemistry and stoichiometry. 

ABSTRACT Nitrous oxide (N₂O) reductase, the sole natural microbial sink for N₂O, exists in two microbial clades:nosZI andnosZII. Although previous studies have explored inter‐clade ecological differentiation, the intra‐clade variations and their implications for N₂O dynamics remain understudied. This study investigated both inter‐ and intra‐clade ecological differentiation among N₂O reducers, the drivers influencing these patterns, and their effects on N₂O emissions across continental‐scale river systems. The results showed that bothnosZI andnosZII community turnovers were associated with similar key environmental factors, particularly total phosphorus (TP), but these variables explained a larger proportion of variation in thenosZI community. The influence of mean annual temperature (MAT) on community composition increased for more widespread N₂O‐reducing taxa. We identified distinct ecological clusters within each clade of N₂O reducers and observed identical ecological clustering patterns across both clades. These clusters were primarily characterized by distinct MAT regimes, coarse sediment texture as well as low TP levels, and high abundance of N₂O producers, with MAT‐related clusters constituting predominant proportions. Intra‐clade ecological differentiation was a crucial predictor of N₂O flux and reduction efficiency. Although different ecological clusters showed varying or even contrasting associations with N₂O dynamics, the shared ecological clusters across clades exhibited similar trends. Low‐MAT clusters in both thenosZI andnosZII communities were negatively correlated with denitrification‐normalized N₂O flux and the N₂O:(N₂O + N₂) ratio, whereas high‐MAT clusters showed positive correlations. This contrasting pattern likely stems from low‐MAT clusters being better adapted to eutrophic conditions and their more frequent co‐occurrence with N₂O‐producing genes. These findings advance our understanding of the distribution and ecological functions of N₂O reducers in natural ecosystems, suggesting that warming rivers may have decreased N₂O reduction efficiency and thereby amplify temperature‐driven emissions. 

Dissolved organic carbon (DOC) export from watersheds by streams is an important, changing component of the global carbon cycle. We examined the controls on DOC export by quantifying changes in the DOC concentration-discharge relationship from 1992 through 2022 for nine forested headwater catchments at the Hubbard Brook Experimental Forest in the northeastern United States. We observed a strong increase in the intercept of the log-log concentration-discharge relationship between 2005 and 2017 and a weak increase in the slope of that relationship between 2002 and 2021, along with seasonal and watershed-level differences. The intercept, which indicates the average stream DOC concentration at a given discharge, was strongly and inversely related to ionic strength of the soil solution as predicted by electrolyte solubility theory. This relationship varied among watersheds, perhaps because of soil pH. The intercept was not strongly related to annual precipitation or air temperature. DOC export ranged from 13 to 153 kg C ha-1 y-1 among study watersheds and years, and was correlated with annual precipitation and discharge. Historical data suggest that DOC export has probably increased over the past 50 years, likely due both to increases in precipitation and runoff and to increases in the intercept and slope of the concentration-discharge relationship. Our results suggest the potential for long-term legacy effects of acidification on DOC solubility and stream DOC concentrations in acid-sensitive watersheds, despite reductions in acid deposition, as mineral weathering slowly replenishes the ionic strength of soil solutions. 

Abstract Soils are a principal global reservoir of mercury (Hg), a neurotoxic pollutant that is accumulating through anthropogenic emissions to the atmosphere and subsequent deposition to terrestrial ecosystems. The fate of Hg in global soils remains uncertain, however, particularly to what degree Hg is re-emitted back to the atmosphere as gaseous elemental mercury (GEM). Here we use fallout radionuclide (FRN) chronometry to directly measure Hg accumulation rates in soils. By comparing these rates with measured atmospheric fluxes in a mass balance approach, we show that representative Arctic, boreal, temperate, and tropical soils are quantitatively efficient at retaining anthropogenic Hg. Potential for significant GEM re-emission appears limited to a minority of coniferous soils, calling into question global models that assume strong re-emission of legacy Hg from soils. FRN chronometry poses a powerful tool to reconstruct terrestrial Hg accumulation across larger spatial scales than previously possible, while offering insights into the susceptibility of Hg mobilization from different soil environments. 

Abstract Climate and atmospheric deposition interact with watershed properties to drive dissolved organic carbon (DOC) concentrations in lakes. Because drivers of DOC concentration are inter-related and interact, it is challenging to assign a single dominant driver to changes in lake DOC concentration across spatiotemporal scales. Leveraging forty years of data across sixteen lakes, we used structural equation modeling to show that the impact of climate, as moderated by watershed characteristics, has become more dominant in recent decades, superseding the influence of sulfate deposition that was observed in the 1980s. An increased percentage of winter precipitation falling as rain was associated with elevated spring DOC concentrations, suggesting a mechanistic coupling between climate and DOC increases that will persist in coming decades as northern latitudes continue to warm. Drainage lakes situated in watersheds with fine-textured, deep soils and larger watershed areas exhibit greater variability in lake DOC concentrations compared to both seepage and drainage lakes with coarser, shallower soils, and smaller watershed areas. Capturing the spatial variability in interactions between climatic impacts and localized watershed characteristics is crucial for forecasting lentic carbon and nutrient dynamics, with implications for lake ecology and drinking water quality.