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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 SiO₂exports over nearly four decades, greatly exceeding the effects of direct CaSiO₃enrichment 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. 

Data collected from the Hubbard Brook Flux Tower starting in August 2016 that is also uploaded to the Ameriflux website under site name US-HBK. These data are from a suite of sensors installed on the 110 ft. tower and in the ground below the tower. Fast data is collected at 10Hz and is processed into 30min time steps using Licor’s Eddy Pro software. Slow data are averaged at 30 minute intervals and are included with this dataset. 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. 

Snowpacks are changing in northeastern North America as the regional climate warms, yet the relative influence of changes in precipitation compared to changes in ablation on snowpacks is poorly understood. We use 56 years of weekly snow water equivalent (SWE) measurements from three locations within a study site which vary in elevation and aspect, paired with adjacent daily climate measurements, to investigate relationships between climate and snowpack onset, maximum, and disappearance. Maximum snowpack size and snowpack duration are shrinking at all sites, at rates ranging from 4.3 days/decade at the coldest site to 9.6 days/decade at the warmest site. The shorter snowpack duration at all sites results from an earlier snowpack disappearance, stemming largely from reduced winter maximum snowpack sizes. Trends in snowpack establishment dates vary, with the south-facing site showing a trend toward later establishment but the two north-facing sites showing no change. The date of the maximum snowpack size varies by aspect and elevation but is not changing at any site. Using a 0° C threshold for frozen vs. liquid precipitation, we only observed a decrease in the proportion of precipitation falling in frozen form at the warmer, south-facing site in the winter period. In contrast, the total weekly snowpack ablation in the winter period has been increasing at least marginally at each site, even at sites which do not show increases in thawing conditions. Ablation increases range from 0.4 cm/decade at the warmest site, to 1.4 and 1.2 cm/decade at the north-facing sites. The south-facing site shows only marginally significant trends in total winter ablation, which we interpret as being limited by the smaller snowpack at this site. Overall, we conclude that rising air temperatures are leading to warmer, more sensitive snowpacks and this change becomes evident before those temperatures lead to changes in precipitation form. 

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. 

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. 

Data collected from the Hubbard Brook Flux Tower starting in August 2016 that is also uploaded to the Ameriflux website under site name US-HBK. These data are from a suite of sensors installed on the 110 ft. tower and in the soil adjacent to the tower. Flux data are collected at 10 Hz and are processed into 30-minute time steps using Licor’s Eddy Pro software. Supporting micro-meteorological data are averaged at 30 minute intervals and are included with this data set. 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. 

Statistical confidence in estimates of timber volume, carbon storage, and other forest attributes depends, in part, on the uncertainty in field measurements. Surprisingly, measurement uncertainty is rarely reported, even though national forest inventories routinely repeat field measurements for quality assurance. We compared measurements made by field crews and quality assurance crews in the Forest Inventory and Analysis program of the U.S. Forest Service, using data from 2790 plots and 51 740 trees and saplings across the 24 states of the Northern Region. We characterized uncertainty in 12 national core tree-level variables; seven tree crown variables used in forest health monitoring; three variables describing seedlings; and 11 variables describing the site, such as elevation, slope, and distance from a road. Discrepancies in measurement were generally small but were higher for some variables requiring judgment, such as tree class, decay class, and cause of mortality. When scaled up to states, forest types, or the region, uncertainties in basal area, timber volume, and aboveground biomass were negligible. Understanding all sources of uncertainty is important to designing forest monitoring systems, managing the conduct of the inventory, and assessing the uncertainty of forest attributes required for making regional and national forest policy decisions.