Search for: All records

Identifying which aspects of global environmental change are driving observed ecosystem process responses is a great challenge. Here, we address how long-term (10-25 year) alterations in soil moisture, and nitrogen (N) oligotrophication (i.e. decreases in soil N availability relative to plant demand), alter the production of plant-available N via net mineralization and nitrification in a northern hardwood forest. Our objectives were to determine whether soil moisture has changed over the past decade and whether N cycle processes have become less sensitive to soil moisture over time due to N oligotrophication. We used long-term data sets from several related studies to show: (i) increasing winter soil temperatures and declining summer soil moisture from late 2010 into 2024; (ii) reductions in sensitivity of N cycling rates to soil moisture, and (iii) declining moisture-adjusted N cycle processes (the ratio of rate of N process:soil moisture) over time in both summer and winter. These changes suggest continued reductions in N availability to plants in these forests, with potential effects on forest productivity and response to disturbance. 

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. 

Synoptic-scale weather patterns affect local meteorological variables, such as vapor pressure deficit (VPD), temperature, and insolation, that are known to influence evapotranspiration (ET) and net CO2 flux (FC). However, little research exists that links synoptic-scale patterns to ET and FC. In this study, we seek to understand how synoptic-scale patterns influence ET and FC for the temperate mixed-hardwood forest at Hubbard Brook Experimental Forest (HBEF) in New Hampshire, United States. We use self-organizing maps to identify the most common synoptic pattern types impacting HBEF during the 2016–21 growing seasons and determine how ET and FC vary with these synoptic pattern types. Our analysis reveals that high ET and most negative FC days occur for the weather pattern phases starting after the departure of a low pressure system and through the approach of a high pressure system. ET and the magnitude of FC remain high if the latitude of the high is south of HBEF but moderate (especially for ET) if the high is to the north and causes east winds to advect a humid maritime air mass over the region. ET is lowest when HBEF is located between high pressure to the east and low pressure to the west, which causes humid southerly flow to decrease VPD and insolation. Meanwhile, FC magnitude may remain high when this pattern occurs in June–July when photosynthetic capacity is at its highest. Our results suggest that future changes in the frequency of passing low pressure systems and pathways of high pressure systems could impact the fluxes of water and CO2 from this forest. Significance Statement: For decades, we have understood that local meteorological variables, such as insolation, temperature, and relative humidity, have a strong influence on a forest ecosystem’s use of water and carbon dioxide, two important greenhouse gases. We also understand that large-scale weather patterns and their interactions with forests shape these local meteorological conditions. This research advances knowledge of the relationship between various large-scale weather patterns and their impacts on forest’s use of water and carbon dioxide via local meteorological variables for a mixed-hardwood forest in the Northeastern United States. Connecting these results to the frequency of these various large-scale weather pattern types projected by global climate models will help us predict how forest ecosystems will influence water vapor and carbon dioxide concentrations and thus impact global climate. 

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. 

Soil carbon dioxide (CO2) flux, or soil respiration, is a critical control on net ecosystem carbon (C) balance. Using long-term (2002-2020) measurements at the Hubbard Brook Experimental Forest (New Hampshire, U.S.), we show that soil respiration rates have notably increased since ~2015. In 2020, cumulative summer respiration flux was approximately 90% higher than the average summer flux over the 2002–2015 period. The increase in soil respiration cannot be explained directly by temperature or pH change alone. We also found that heterotrophic microbial C mineralization and microbial biomass C have also increased rapidly since ~2015, pointing towards an increase in the bioavailability of organic C substrates. We suggest that these observations are consistent with a hypothetical increase in plant allocation of C belowground in response to changing climatic and soil conditions. Quantification of interactions among co-occurring global change factors (e.g., warming temperatures, increasing atmospheric CO2, and nutrient limitation) is needed to predict how the soil C reservoir will continue to respond to global environmental changes. 

The oxidation of organic matter from fuel combustion or vegetation emissions into organic acids is a major source of dissolved organic carbon (DOC) in precipitation. Long‐term measurements of DOC in precipitation are rare, but the existing records mostly show decreases due to reduction in fuel combustion. Here, we show a recent, sudden increase in precipitation DOC concentration in a 27‐year record from the Hubbard Brook Experimental Forest (HBEF) in northern New Hampshire, USA Starting in 2010, where mean annual DOC concentration increased from about 80 to 130 μmol L⁻¹in 2022. No other solutes in precipitation showed a similar sudden change. The weekly DOC concentration was not clearly related to the 72‐hr air mass trajectory characteristics or changes in trajectories. We assessed the feasibility of multiple possible causes for the DOC increase, including an increase in biogenic volatile organic compound (BVOC) emissions from the forest or from forest fires, changes in oxidation processes in the troposphere, and changes in gas‐phase solubility due to increasing pH in precipitation. Further study of sudden changes in BVOC emissions in the region, possible causes, and air quality effects are warranted. 

Soil temperature and soil moisture have been measured at multiple locations at the Hubbard Brook Experimental Forest (HBEF), as part of a study of the relationships between snow depth, soil freezing and nutrient cycling (http://www.ecostudies.org/people_sci_groffman_snow_summary.html). In October 2010, we established 6, 20 x 20-m plots (intensive plots) and 14 10 x 10-m plots (extensive plots) along an elevation gradient, with eight of the plots on north-facing slopes and twelve on south-facing slopes. Soil temperature and soil moisture were measured at hourly intervals on these plots beginning in November 2010. Six locations were discontinued in September 2012 (E04, E05, E06, E11-B, E13, and E14). Previous versions of this dataset included both temperature and moisture. These data are now available as moisture(this dataset) and temperature (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=315]. 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. 

Soil temperature and soil moisture have been measured at multiple locations at the Hubbard Brook Experimental Forest (HBEF), as part of a study of the relationships between snow depth, soil freezing and nutrient cycling (http://www.ecostudies.org/people_sci_groffman_snow_summary.html). In October 2010, we established 6, 20 x 20-m plots (intensive plots) and 14 10 x 10-m plots (extensive plots) along an elevation gradient, with eight of the plots on north-facing slopes and twelve on south-facing slopes. Soil temperature and soil moisture were measured at hourly intervals on these plots beginning in November 2010. Six locations were discontinued in September 2012 (E04, E05, E06, E11-B, E13, and E14). Previous versions of this dataset included both temperature and moisture. These data are now available as temperature (this dataset) and moisture (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=137). 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. 

This dataset consists of groundwater levels measured within wells distributed across Watershed 3 at Hubbard Brook Experimental Forest from 2007-2020. Water levels are expressed as a depth (cm) from the soil surface. This dataset is a part of a larger project aimed at explaining the spatial and temporal variation in stream water chemistry at the headwater catchment scale using a framework based on the combined study of hydrology and soil development – hydropedology. The project will demonstrate how hydrology strongly influences soil development and soil chemistry, and in turn, controls stream water quality in headwater catchments. Understanding the linkages between hydrology and soil development can provide valuable information for managing forests and stream water quality. Feedbacks between soils and hydrology that lead to predictable landscape patterns of soil chemistry have implications for understanding spatial gradients in site productivity and suitability for species with differing habitat requirements or chemical sensitivity. Tools are needed that identify and predict these gradients that can ultimately provide guidance for land management and silvicultural decision making. Better integration between soil science, hydrology, and biogeochemistry will provide the conceptual leap needed by the hydrologic community to be able to better predict and explain temporal and spatial variability of stream water quality and understand water sources contributing to streamflow. 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.