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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 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. 

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. 

We evaluated shoot nonstructural carbohydrate (NSC) concentrations, stem wound closure, and radial growth of sugar maple ( Acer saccharum Marsh.) and red maple ( Acer rubrum L.) trees in a novel ice storm experiment in which five storm treatments (0, 6.4, 12.7, and 19.1 mm of radial ice accretion in 1 year and 12.7 mm of ice in two consecutive years) were applied within a mature northern hardwood forest. We tested for changes in physiology at two levels: (1) associated with plot-level ice treatments and (2) with crown damage classes of individual trees. Few differences in NSC or wound closure associated with treatment were found. Growth decreased for red maple in the medium and high treatments and sugar maple in the high treatment but no other treatments. Changes in physiology were more evident when assessed using crown damage classes. Two NSC components were elevated in sugar and red maples with high (≥50%) crown damage. Wound closure was less for red maples with high damage, and separation among damage classes was even greater for sugar maple. Red maples with moderate (<50%) and high crown damage showed gradually declining growth, whereas sugar maples with high damage showed ∼80% reduction in growth the first year after injury. 

Flood peak magnitudes and frequency estimates are key components of any effective nationwide flood risk management and flood damage abatement program. In this study, we evaluated normalized peak design discharges (Qp) for 1,387 hydrologic unit code 16 to 20 (HUC16-20) watersheds in the White Mountain National Forest (WMNF), New Hampshire and in five Experimental Forest (EF) regions across the United States managed by USDA Forest Service (USDA-FS). Nonstationary regional frequency analysis (RFA) and single site frequency analysis (FA) with long-term high-resolution observed streamflow data along with the deterministic Rational Method (RM) and semi-empirical United States Geological Survey regional regression equation (USGS-RRE) were used. Additionally, a hydrologic vulnerability assessment was performed for 194 road culverts as a result of extreme precipitation-induced flooding on gauged and ungauged watersheds in the Hubbard Brook EF (HBR) within the WMNF. The RM outperformed the USGS-RRE in predicting Qp in the gauged and ungauged HUC16-20 watersheds of WMNF and in three other small, high-relief forest headwater watersheds—Coweeta Hydrologic Lab EF’s watershed-14, and watershed-27 in North Carolina and HJ Andrews EF’s watershed 8 in Oregon. However, the USGS-RRE performed better for larger watersheds, such as the Fraser EF’s St. Louis watershed in Colorado and the Santee EF’s watershed 80 in South Carolina. About 31 %, 26 %, and 56 % of the culverts at the HBR site could not accommodate the 100-yr Qp estimated by RFA, RM and USGS-RRE, respectively. Based on the chosen RIs and techniques, it is determined that except for one culvert with diameter = 0.91 m (36 in.), none of the culverts with diameter of 0.75 m (30 in.) or larger are hydrologically vulnerable. Our results suggest that the observation based RFA works best where multiple gauges are available to extrapolate information for ungauged watersheds, otherwise, RM is best-suited for smaller headwater watersheds and USGS-RRE for larger watersheds. Results from the hydrologic vulnerability analysis revealed that replacing undersized culverts with new culverts of diameter ≥ 0.75-m will improve flood resiliency, provided that the structure is geomorphologically safe (with minimal effects of debris flow, erosion, and sedimentation) and allows for both bank-full discharge and necessary fish passage within that design limit. This study has implications in managing road culverts and crossings at Forest Service and other forested lands for their resiliency to extreme precipitation and flooding hazards induced by climate change. 

Abstract Urgency of Precipitation Intensity-Duration-Frequency (IDF) estimation using the most recent data has grown significantly due to recent intense precipitation and cloud burst circumstances impacting infrastructure caused by climate change. Given the continually available digitized up-to-date, long-term, and fine resolution precipitation dataset from the United States Department of Agriculture Forest Service’s (USDAFS) Experimental Forests and Ranges (EF) rain gauge stations, it is both important and relevant to develop precipitation IDF from onsite dataset (Onsite-IDF) that incorporates the most recent time period, aiding in the design, and planning of forest road-stream crossing structures (RSCS) in headwaters to maintain resilient forest ecosystems. Here we developed Onsite-IDFs for hourly and sub-hourly duration, and 25-yr, 50-yr, and 100-yr design return intervals (RIs) from annual maxima series (AMS) of precipitation intensities (PIs) modeled by applying Generalized Extreme Value (GEV) analysis and L-moment based parameter estimation methodology at six USDAFS EFs and compared them with precipitation IDFs obtained from the National Oceanic and Atmospheric Administration Atlas 14 (NOAA-Atlas14). A regional frequency analysis (RFA) was performed for EFs where data from multiple precipitation gauges are available. NOAA’s station-based precipitation IDFs were estimated for comparison using RFA (NOAA-RFA) at one of the EFs where NOAA-Atlas14 precipitation IDFs are unavailable. Onsite-IDFs were then evaluated against the PIs from NOAA-Atlas14 and NOAA-RFA by comparing their relative differences and storm frequencies. Results show considerable relative differences between the Onsite- and NOAA-Atlas14 (or NOAA-RFA) IDFs at these EFs, some of which are strongly dependent on the storm durations and elevation of precipitation gauges, particularly in steep, forested sites of H. J. Andrews (HJA) and Coweeta Hydrological Laboratory (CHL) EFs. At the higher elevation gauge of HJA EF, NOAA-RFA based precipitation IDFs underestimate PI of 25-yr, 50-yr, and 100-yr RIs by considerable amounts for 12-h and 24-h duration storm events relative to the Onsite-IDFs. At the low-gradient Santee (SAN) EF, the PIs of 3- to 24-h storm events with 100-yr frequency (or RI) from NOAA-Atlas14 gauges are found to be equivalent to PIs of more frequent storm events (25–50-yr RI) as estimated from the onsite dataset. Our results recommend use of the Onsite-IDF estimates for the estimation of design storm peak discharge rates at the higher elevation catchments of HJA, CHL, and SAN EF locations, particularly for longer duration events, where NOAA-based precipitation IDFs underestimate the PIs relative to the Onsite-IDFs. This underscores the importance of long-term high resolution EF data for new applications including ecological restorations and indicates that planning and design teams should use as much local data as possible or account for potential PI inconsistencies or underestimations if local data are unavailable. 

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. 

This article describes the Research Apprenticeship Program (RAP), a mentored undergraduate research experience implemented in 2017 at a public land-grant institution located in the Appalachian region. The article focuses on RAP’s approach to recruiting, retaining, and supporting students in faculty-mentored research and creative inquiry. To assess the impact of RAP on undergraduate retention, institutional data were collected to identify RAP participants from the years 2017 to 2022 (n = 868) to compare next-year retention rates with institutional averages across similar demographic groups. The results showed that retention rates for RAP participants were significantly higher than institutional averages, and disaggregated data also showed higher retention rates for participants from historically marginalized populations. These This article describes the Research Apprenticeship Program (RAP), a mentored undergraduate research experience implemented in 2017 at a public land-grant institution located in the Appalachian region. The article focuses on RAP’s approach to recruiting, retaining, and supporting students in faculty-mentored research and creative inquiry. To assess the impact of RAP on undergraduate retention, institutional data were collected to identify RAP participants from the years 2017 to 2022 (n = 868) to compare next-year retention rates with institutional averages across similar demographic groups. The results showed that retention rates for RAP participants were significantly higher than institutional averages, and disaggregated data also showed higher retention rates for participants from historically marginalized populations. These results provide evidence of the program’s contribution to the educational development of the Appalachian region. 

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.