Early spring onset increases carbon uptake more than late fall senescence: modeling future phenological change in a US northern deciduous forest.

In deciduous forests, spring leaf development and fall leaf senescence regulate the timing and duration of photosynthesis and transpiration. Being able to model these dates is therefore critical to accurately representing ecosystem processes in biogeochemical models. Despite this, there has been relatively little effort to improve internal phenology predictions in widely used biogeochemical models. Here, we optimized the phenology algorithms in a regionally developed biogeochemical model (PnET-CN) using phenology data from eight mid-latitude PhenoCam sites in eastern North America. We then performed a sensitivity analysis to determine how the optimization affected future predictions of carbon, water, and nitrogen cycling at Bartlett Experimental Forest, New Hampshire. Compared to the original PnET-CN phenology models, our new spring and fall models resulted in shorter season lengths and more abrupt transitions that were more representative of observations. The new phenology models affected daily estimates and interannual variability of modeled carbon exchange, but they did not have a large influence on the magnitude or long-term trends of annual totals. Under future climate projections, our new phenology models predict larger shifts in season length in the fall (1.1-3.2 days decade-1) compared to the spring (0.9-1.5 days decade-1). However, for every day the season was longer, spring had twice the effect on annual carbon and water exchange totals compared to the fall. These findings highlight the importance of accurately modeling season length for future projections of carbon and water cycling.

Analytical approaches for evaluating passive acoustic monitoring data: A case study of avian vocalizations.

The interface between field biology and technology is energizing the collection of vast quantities of environmental data. Passive acoustic monitoring, the use of unattended recording devices to capture environmental sound, is an example where technological advances have facilitated an influx of data that routinely exceeds the capacity for analysis. Computational advances, particularly the integration of machine learning approaches, will support data extraction efforts. However, the analysis and interpretation of these data will require parallel growth in conceptual and technical approaches for data analysis. Here, we use a large hand-annotated dataset to showcase analysis approaches that will become increasingly useful as datasets grow and data extraction can be partially automated.We propose and demonstrate seven technical approaches for analyzing bioacoustic data. These include the following: (1) generating species lists and descriptions of vocal variation, (2) assessing how abiotic factors (e.g., rain and wind) impact vocalization rates, (3) testing for differences in community vocalization activity across sites and habitat types, (4) quantifying the phenology of vocal activity, (5) testing for spatiotemporal correlations in vocalizations within species, (6) among species, and (7) using rarefaction analysis to quantify diversity and optimize bioacoustic sampling.To demonstrate these approaches, we sampled in 2016 and 2018 and used hand annotations of 129,866 bird vocalizations from two forests in New Hampshire, USA, including sites in the Hubbard Brook Experiment Forest where bioacoustic data could be integrated with more than 50 years of observer-based avian studies. Acoustic monitoring revealed differences in community patterns in vocalization activity between forests of different ages, as well as between nearby similar watersheds. Of numerous environmental variables that were evaluated, background noise was most clearly related to vocalization rates. The songbird community included one cluster of species where vocalization rates declined as ambient noise increased and another cluster where vocalization rates declined over the nesting season. In some common species, the number of vocalizations produced per day was correlated at scales of up to 15 km. Rarefaction analyses showed that adding sampling sites increased species detections more than adding sampling days.Although our analyses used hand-annotated data, the methods will extend readily to large-scale automated detection of vocalization events. Such data are likely to become increasingly available as autonomous recording units become more advanced, affordable, and power efficient. Passive acoustic monitoring with human or automated identification at the species level offers growing potential to complement observer-based studies of avian ecology.

Simulation of the effects of forest harvesting under changing climate to inform long-term sustainable forest management using a biogeochemical model.

Process ecosystem models are useful tools to provide insight on complex, dynamic ecological systems, and their response to disturbances. The biogeochemical model PnET-BGC was modified and tested using field observations from an experimentally whole-tree harvested northern hardwood watershed (W5) at the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA. In this study, the confirmed model was used as a heuristic tool to investigate long-term changes in hydrology, biomass accumulation, and soil solution and stream water chemistry for three different watershed cutting intensities (40%, 60%, 80%) and three rotation lengths (30, 60, 90 years) under both constant (current climate) and changing (MIROC5-RCP4.5) future climate scenarios and atmospheric CO2 through the year 2200. For the no future cutting scenario, total ecosystem stored carbon (i.e., sum of aboveground biomass, woody debris and soil) reached a maximum value of 207 t C ha-1 under constant climate but increased to 452 t C ha-1 under changing climate in 2200 due to a CO2 fertilization effect. Harvesting of trees decreased total ecosystem stored carbon between 7 and 36% for constant climate and 7-60% under changing climate, respectively, with greater reductions for shorter logging rotation lengths and greater watershed cutting intensities. Harvesting under climate change resulted in noticeable losses of soil organic matter (12-56%) coinciding with loss of soil nutrients primarily due to higher rates of soil mineralization associated with increases in temperature, compared with constant climate conditions (3-22%). Cumulative stream leaching of nitrate under climate change (181-513 kg N ha-1) exceeded constant climate values (139-391 kg N ha-1) for the various cutting regimes. Under both climate conditions the model projected greater sensitivity to varying the length of cutting period than cutting intensities. Hypothetical model simulations highlight future challenges in maintaining long-term productivity of managed forests under changing climate due to a potential for a deterioration of soil fertility.

Ambio's legacy on monitoring, impact, and management of acid rain : This article belongs to Ambio's 50th Anniversary Collection. Theme: Acidification.

Early studies published in Ambio showed large-scale acidification of lakes in southern Sweden and Norway from acid rain. These studies were important for delimiting various scientific issues and thus for eventually contributing to legislation, which reduced emissions of sulfur dioxide and nitrogen oxides and helped to mitigate this major environmental problem. Long-term studies and monitoring in Sweden and Norway and at Hubbard Brook Experimental Forest in New Hampshire helped guide this legislation in Europe and in the USA.

Nutrient retention and loss during ecosystem succession: revisiting a classic model.

In 1975, Vitousek and Reiners proposed a conceptual model relating the net retention of a limiting nutrient to the net biomass accumulation in terrestrial ecosystems, whereby terrestrial systems should be highly conservative of nutrients during ecosystem succession when plants are actively accumulating biomass, but should be relatively leakier in older stands, when net plant biomass accumulation nears zero. The model was based on measurements in the White Mountains of New Hampshire. However, recent data showing that nitrate output in streams is declining across this region even as forests are aging seem to be inconsistent with this theory. Because the more recent data do not match the predictions of the Vitousek and Reiners model, either new hypotheses, or modifications of the original hypothesis, need to be considered. I suggest that the original model can be amended by accounting for increased woody debris; an accumulation of both above and belowground high C:N coarse woody debris from tree mortality in these regenerating forests can lead to high microbial immobilization of N and can explain the recent patterns of declining stream nitrate. Few studies or models have attempted to calculate the impacts of coarse woody debris (CWD) decomposition products to the retention of C and N in forested ecosystems and their receiving streams, but evidence suggests that CWD can significantly affect stream N exports and should be considered in future models of ecosystem biogeochemical cycles.

Soil carbon losses due to higher pH offset vegetation gains due to calcium enrichment in an acid mitigation experiment.

Reductions in acid precipitation across North America and Europe have been linked to substantial declines of soil organic carbon (SOC) stocks in temperate forests, but the mechanisms underlying these declines remain poorly understood. As forests recover from acid precipitation, soil pH and calcium fertility are both expected to increase, and these changes in soil chemistry may drive altered SOC dynamics. Here, we performed a year-long pot experiment on acid-impacted soils to test the independent and interactive effects of increased soil pH and Ca fertility on SOC solubility, microbial activity and sugar maple (Acer saccharum) sapling growth. We found that microbial respiration and SOC solubility was strongly stimulated by increased soil pH, but only in the presence of plants. In planted pots, a soil pH increase of 0.76 units increased soil respiration by 19% in the organic soil horizon and 38% in the mineral soil horizon, whereas in unplanted pots, soil pH had no effect on microbial respiration. While increased soil pH enhanced plant-mediated heterotrophic respiration, it had no effect on plant growth. By contrast, soil Ca enrichment increased the relative growth rate of plants by 22%, but had no impact on microbial respiration. Our results suggest that, in terms of ecosystem carbon balance, losses of SOC due to increasing soil pH may offset potential gains in primary productivity due to enhanced Ca fertility as ecosystems recover from acid precipitation.

The application of an integrated biogeochemical model to simulate dynamics of vegetation, hydrology and nutrients in soil and streamwater following a whole-tree harvest of a northern hardwood forest.

Understanding the impacts of clear-cutting is critical to inform sustainable forest management associated with net primary productivity and nutrient availability over the long-term. Few studies have rigorously tested model simulations against field measurements which would provide more confidence in efforts to quantify logging impacts over the long-term. The biogeochemical model, PnET-BGC has been used to simulate forest production and stream chemistry at the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA. Previous versions of PnET-BGC could accurately simulate the longer-term biogeochemical response to harvesting, but were unable to reproduce the marked changes in stream NO3- immediately after clear-cutting which is an important impact of forest harvesting. Moreover, the dynamics of nutrients in major pools including mineralization and plant uptake were poorly predicted. In this study, the model was modified and parametrized allowing for a lower decomposition rate during the earlier years after the clear-cut and increased NH4+ plant uptake with the regrowth of new vegetation to adequately reproduce hydrology, aboveground forest biomass, and soil solution and stream water chemistry in response to a whole-tree harvest of a northern hardwood forest watershed (W5) at the HBEF. Modeled soil solution and stream water chemistry successfully captured the rapid recovery of leaching nutrients to pre-cut levels within four years after the treatment. The model simulated a substantial increase in aboveground net primary productivity (NPP) from around 36% to 97% of pre-cut aboveground values within years 2 to 4 of the cut, which closely reproduced the measured values. The projected accumulation of aboveground biomass 70 years following the harvest was almost 190 t ha-1, which is close to the pre-cut measured value. A first-order sensitivity analysis showed greater sensitivity of projections of the model outputs for the mature forest than the strongly aggrading forest.

Fifty years of continuous precipitation and stream chemistry data from the Hubbard Brook ecosystem study (1963-2013).

The Hubbard Brook Ecosystem Study officially began on 1 June 1963. This archive contains the results of 50 yr of collection and analysis of (at least) weekly stream water and precipitation samples obtained during the period 1963-2014 (from 1 June 1963 to 30 May 2013). Stream chemistry for the nine gauged watersheds and precipitation chemistry for precipitation gauges distributed throughout the Hubbard Brook Experimental Forest are reported as concentrations in (mg/L).

Reduced snow cover alters root-microbe interactions and decreases nitrification rates in a northern hardwood forest.

Snow cover is projected to decline during the next century in many ecosystems that currently experience a seasonal snowpack. Because snow insulates soils from frigid winter air temperatures, soils are expected to become colder and experience more winter soil freeze-thaw cycles as snow cover continues to decline. Tree roots are adversely affected by snowpack reduction, but whether loss of snow will affect root-microbe interactions remains largely unknown. The objective of this study was to distinguish and attribute direct (e.g., winter snow- and/or soil frost-mediated) vs. indirect (e.g., root-mediated) effects of winter climate change on microbial biomass, the potential activity of microbial exoenzymes, and net N mineralization and nitrification rates. Soil cores were incubated in situ in nylon mesh that either allowed roots to grow into the soil core (2 mm pore size) or excluded root ingrowth (50 µm pore size) for up to 29 months along a natural winter climate gradient at Hubbard Brook Experimental Forest, NH (USA). Microbial biomass did not differ among ingrowth or exclusion cores. Across sampling dates, the potential activities of cellobiohydrolase, phenol oxidase, and peroxidase, and net N mineralization rates were more strongly related to soil volumetric water content (P < 0.05; R2  = 0.25-0.46) than to root biomass, snow or soil frost, or winter soil temperature (R2  < 0.10). Root ingrowth was positively related to soil frost (P < 0.01; R2  = 0.28), suggesting that trees compensate for overwinter root mortality caused by soil freezing by re-allocating resources towards root production. At the sites with the deepest snow cover, root ingrowth reduced nitrification rates by 30% (P < 0.01), showing that tree roots exert significant influence over nitrification, which declines with reduced snow cover. If soil freezing intensifies over time, then greater compensatory root growth may reduce nitrification rates directly via plant-microbe N competition and indirectly through a negative feedback on soil moisture, resulting in lower N availability to trees in northern hardwood forests.

The effects of climate downscaling technique and observational data set on modeled ecological responses.

Assessments of future climate change impacts on ecosystems typically rely on multiple climate model projections, but often utilize only one downscaling approach trained on one set of observations. Here, we explore the extent to which modeled biogeochemical responses to changing climate are affected by the selection of the climate downscaling method and training observations used at the montane landscape of the Hubbard Brook Experimental Forest, New Hampshire, USA. We evaluated three downscaling methods: the delta method (or the change factor method), monthly quantile mapping (Bias Correction-Spatial Disaggregation, or BCSD), and daily quantile regression (Asynchronous Regional Regression Model, or ARRM). Additionally, we trained outputs from four atmosphere-ocean general circulation models (AOGCMs) (CCSM3, HadCM3, PCM, and GFDL-CM2.1) driven by higher (A1fi) and lower (B1) future emissions scenarios on two sets of observations (1/8º resolution grid vs. individual weather station) to generate the high-resolution climate input for the forest biogeochemical model PnET-BGC (eight ensembles of six runs).The choice of downscaling approach and spatial resolution of the observations used to train the downscaling model impacted modeled soil moisture and streamflow, which in turn affected forest growth, net N mineralization, net soil nitrification, and stream chemistry. All three downscaling methods were highly sensitive to the observations used, resulting in projections that were significantly different between station-based and grid-based observations. The choice of downscaling method also slightly affected the results, however not as much as the choice of observations. Using spatially smoothed gridded observations and/or methods that do not resolve sub-monthly shifts in the distribution of temperature and/or precipitation can produce biased results in model applications run at greater temporal and/or spatial resolutions. These results underscore the importance of carefully considering field observations used for training, as well as the downscaling method used to generate climate change projections, for smaller-scale modeling studies. Different sources of variability including selection of AOGCM, emissions scenario, downscaling technique, and data used for training downscaling models, result in a wide range of projected forest ecosystem responses to future climate change.

Simulating effects of changing climate and CO(2) emissions on soil carbon pools at the Hubbard Brook experimental forest.

Carbon (C) sequestration in forest biomass and soils may help decrease regional C footprints and mitigate future climate change. The efficacy of these practices must be verified by monitoring and by approved calculation methods (i.e., models) to be credible in C markets. Two widely used soil organic matter models - CENTURY and RothC - were used to project changes in SOC pools after clear-cutting disturbance, as well as under a range of future climate and atmospheric carbon dioxide (CO(2) ) scenarios. Data from the temperate, predominantly deciduous Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, were used to parameterize and validate the models. Clear-cutting simulations demonstrated that both models can effectively simulate soil C dynamics in the northern hardwood forest when adequately parameterized. The minimum postharvest SOC predicted by RothC occurred in postharvest year 14 and was within 1.5% of the observed minimum, which occurred in year 8. CENTURY predicted the postharvest minimum SOC to occur in year 45, at a value 6.9% greater than the observed minimum; the slow response of both models to disturbance suggests that they may overestimate the time required to reach new steady-state conditions. Four climate change scenarios were used to simulate future changes in SOC pools. Climate-change simulations predicted increases in SOC by as much as 7% at the end of this century, partially offsetting future CO(2) emissions. This sequestration was the product of enhanced forest productivity, and associated litter input to the soil, due to increased temperature, precipitation and CO(2) . The simulations also suggested that considerable losses of SOC (8-30%) could occur if forest vegetation at HBEF does not respond to changes in climate and CO(2) levels. Therefore, the source/sink behavior of temperate forest soils likely depends on the degree to which forest growth is stimulated by new climate and CO(2) conditions.

Determining the sources of calcium for migratory songbirds using stable strontium isotopes.

We investigated natural variations in the stable isotopic composition of strontium (a surrogate for calcium) in the bones of a single species of breeding migratory songbird, as well as in their eggshells, egg contents, and food sources. We use this information to determine the sources of calcium to these migratory songbirds and their offspring. Samples were collected from two locations in the northeastern USA (Hubbard Brook, NH, and Downer Forest, VT.) that differed in soil geochemistry. The mean 87Sr/86Sr ratios of food items (caterpillars and snails), eggshells, and egg contents were indistinguishable within each site, but significantly different between the two sites. Mean 87Sr/86Sr ratios for the bones of adult females were significantly different between the two sites, but values were significantly lower than those of food items and eggshells at each site. Two of four adult individuals studied at each site had 87Sr/86Sr ratios lower than the entire range of values for local food sources. Mixing calculations indicate that up to 60% of skeletal strontium and calcium was derived from foods consumed in the winter grounds where lower 87Sr/86Sr ratios predominate. At each study site, the 87Sr/86Sr ratio of eggshells differed significantly between clutches, but the mean clutch 87Sr/86Sr ratios were unrelated to the skeletal 87Sr/86Sr ratio of the laying adult. These findings suggest that strontium (and hence calcium) for eggshell production in this species is derived predominantly from local food sources in breeding areas. Thus, reductions in available calcium in northern temperate ecosystems due to the influences of acid deposition could be potentially harmful to this and other species of migratory bird.

Autumnal leaf conductance and apparent photosynthesis by saplings and sprouts in a recently disturbed northern hardwood forest.

Leaf surface conductance and apparent photosynthesis were measured during late summer and autumn on saplings and sprouts of pin cherry (Prunus pensylvanica), yellow birch (Betula alleghaniensis), American beech (Fagus grandifolia), and sugar maple (Acer saccharum) naturally revegetating a site in the northern hardwood forest 5 years following a commercial whole-tree harvest. Prior to the disturbance (i.e., the harvest) the site was codominated by American beech, sugar maple, and yellow birch, whereas after the disturbance pin cherry was the dominant species. Conductance and photosynthetic rate of pin cherry leaves were comparatively high while those of American beech and sugar maple were low. Pin cherry retained green, physiologically active leaves longer into autumn than American beech and sugar maple. The rates and seasonal duration of leaf gas exchange on the disturbed site were therefore greater than they would have been had the site not become dominated by pin cherry.