Carbon and nitrogen dynamics of northeastern United States forests in response to environmental stress: Measurements and models at local to regional scales

This thesis stems from several ongoing efforts to characterize patterns of productivity and nitrogen cycling in northeastern US forests and to address the effects of nitrogen deposition, tropospheric ozone and rising atmospheric CO2. The work reported on involves two related projects; (1) an ecosystem model analysis that integrates physiological and biogeochemical processes with important environmental variables across the northeast region and (2) a field and remote sensing analysis that examines landscape-level patterns of forest biogeochemistry in the White Mountains of New Hampshire. Chapter 1 presents a regional analysis of forest productivity using the PnET forest ecosystem model and discusses the relative importance of water, temperature and nitrogen on predicted spatial patterns. Chapter 2 integrates ozone effects on leaf-level carbon gain and describes interactions with canopy and stand-level processes. Using ambient ozone data from across the northeast region, the model predicted declines in annual forest production of between 3% and 16% and demonstrated an interaction with water availability whereby ozone damage declined during periods of drought. In chapter 3, a physiological response to CO2 is added to the model and applied with historical changes in N deposition and ozone. This analysis suggested that increased CO2 and N deposition have stimulated forest carbon uptake, but to different degrees following agriculture and timber harvesting. Further, the concurrent increases in ozone offset a large fraction of the predicted growth enhancement. This result is particularly relevant given the related spatial distributions of ozone and N deposition. The final chapter presents a field study in the White Mountain National Forest that examines relationships between nitrogen cycling and foliar chemistry among forests of diverse history and composition. Across a wide range of conditions, foliar lignin:N ratios were correlated with soil C:N ratios, providing a means of assessing soil N status using hyperspectral remote sensing. Relationships between foliar chemistry and soil N transformations (mineralization and nitrification) were also observed, but these trends differed between historically disturbed versus undisturbed stands. Disturbed stands had significantly lower rates of mineralization and nitrification and higher soil C:N ratios than undisturbed stands, but these trends were not clearly reflected in stand-level foliar chemistry

Generalization and evaluation of the process-based forest ecosystem model PnET-CN for other biomes

Terrestrial ecosystems play an important role in carbon, water, and nitrogen cycling. Process-based ecosystem models, including PnET-CN, have been widely used to simulate ecosystem processes during the last two decades. PnET-CN is a forest ecosystem model, originally designed to predict ecosystem carbon, water, and nitrogen dynamics of temperate forests under a variety of circumstances. Among terrestrial ecosystem models, PnET-CN offers unique benefits, including simplicity and transparency of its structure, reliance on data-driven parameterization rather than calibration, and use of generalizeable relationships that provide explicit linkages among carbon, water and nitrogen cycles. The objective of our study was to apply PnET-CN to non-forest biomes: grasslands, shrublands, and savannas. We determined parameter values for grasslands and shrublands using the literature and ecophysiological databases. To assess the usefulness of PnET-CN in these ecosystems, we simulated carbon and water fluxes for six AmeriFlux sites: two grassland sites (Konza Prairie and Fermi Prairie), two open shrubland sites (Heritage Land Conservancy Pinyon Juniper Woodland and Sevilleta Desert Shrubland), and two woody savanna sites (Freeman Ranch and Tonzi Ranch). Grasslands and shrublands were simulated using the biome-specific parameters, and savannas were simulated as mixtures of grasslands and forests. For each site, we used flux observations to evaluate modeled carbon and water fluxes: gross primary productivity (GPP), ecosystem respiration (ER), net ecosystem productivity (NEP), evapotranspiration (ET), and water yield. We also evaluated simulated water use efficiency (WUE). PnET-CN generally captured the magnitude, seasonality, and interannual variability of carbon and water fluxes as well as WUE for grasslands, shrublands, and savannas. Overall, our results show that PnET-CN is a promising tool for modeling ecosystem carbon and water fluxes for non-forest biomes (grasslands, shrublands, and savannas), and especially for modeling GPP in mature biomes. Limitations in model performance included an overestimation of seasonal variability in GPP and ET for the two shrubland sites and overestimation of early season ER for the two shrubland sites and Freeman Ranch. Future modifications of PnET-CN for non-forest biomes should focus on belowground processes, including water storage in dry shrubland soils, root growth and respiration in grasslands, and soil carbon fluxes for all biomes

SIMULATING OZONE EFFECTS ON FOREST PRODUCTIVITY: INTERACTIONS AMONG LEAF‐, CANOPY‐, AND STAND‐LEVEL PROCESSES

Ozone pollution in the lower atmosphere is known to have adverse effects on forest vegetation, but the degree to which mature forests are impacted has been very difficult to assess directly. In this study, we combined leaf‐level ozone response data from independent ozone fumigation studies with a forest ecosystem model in order simulate the effects of ambient ozone on mature hardwood forests. Reductions in leaf carbon gain were determined as a linear function of ozone flux to the leaf interior, calculated as the product of ozone concentration and leaf stomatal conductance. This relationship was applied to individual canopy layers within the model in order to allow interaction with stand‐ and canopy‐level factors such as light attenuation, leaf morphology, soil water limitations, and vertical ozone gradients. The resulting model was applied to 64 locations across the northeastern United States using ambient ozone data from 1987 to 1992. Predicted declines in annual net primary production ranged from 3 to 16% with greatest reductions in southern portions of the region where ozone levels were highest, and on soils with high water‐holding capacity where drought stress was absent. Reductions in predicted wood growth were slightly greater (3–22%) because wood is a lower carbon allocation priority in the model than leaf and root growth. Interannual variation in predicted ozone effects was small due to concurrent fluctuations in ozone and climate. Periods of high ozone often coincided with hot, dry weather conditions, causing reduced stomatal conductance and ozone uptake. Within‐canopy ozone concentration gradients had little effect on predicted growth reductions because concentrations remained high through upper canopy layers where net carbon assimilation and ozone uptake were greatest. Sensitivity analyses indicate a trade‐off between model sensitivity to available soil water and foliar nitrogen and demonstrate uncertainties regarding several assumptions used in the model. Uncertainties surrounding ozone effects on stomatal function and plant water use efficiency were found to have important implications on current predictions. Field measurements of ozone effects on mature forests will be needed before the accuracy of model predictions can be fully assessed

Quantifying the effects of harvesting on carbon fluxes and stocks in northern temperate forests

Harvest disturbance has substantial impacts on forest carbon (C) fluxes and stocks. The quantification of these effects is essential for the better understanding of forest C dynamics and informing forest management in the context of global change. We used a process-based forest ecosystem model, PnET-CN, to evaluate how, and by what mechanisms, clear-cuts alter ecosystem C fluxes, aboveground C stocks (AGC), and leaf area index (LAI) in northern temperate forests. We compared C fluxes and stocks predicted by the model and observed at two chronosequences of eddy covariance flux sites for deciduous broadleaf forests (DBF) and evergreen needleleaf forests (ENF) in the Upper Midwest region of northern Wisconsin and Michigan, USA. The average normalized root mean square error (NRMSE) and the Willmott index of agreement (d) for carbon fluxes, LAI, and AGC in the two chronosequences were 20% and 0.90, respectively. Simulated gross primary productivity (GPP) increased with stand age, reaching a maximum (1200–1500 g C m−2 yr−1) at 11–30 years of age, and leveled off thereafter (900–1000 g C m−2 yr−1). Simulated ecosystem respiration (ER) for both plant functional types (PFTs) was initially as high as 700–1000 g C m−2 yr−1 in the first or second year after harvesting, decreased with age (400–800 g C m−2 yr−1) before canopy closure at 10–25 years of age, and increased to 800–900 g C m−2 yr−1 with stand development after canopy recovery. Simulated net ecosystem productivity (NEP) for both PFTs was initially negative, with net C losses of 400–700 g C m−2 yr−1 for 6–17 years after clear-cuts, reaching peak values of 400–600 g C m−2 yr−1 at 14–29 years of age, and eventually stabilizing in mature forests (\u3e 60 years old), with a weak C sink (100–200 g C m−2 yr−1). The decline of NEP with age was caused by the relative flattening of GPP and gradual increase of ER. ENF recovered more slowly from a net C source to a net sink, and lost more C than DBF. This suggests that in general ENF may be slower to recover to full C assimilation capacity after stand-replacing harvests, arising from the slower development of photosynthesis with stand age. Our model results indicated that increased harvesting intensity would delay the recovery of NEP after clear-cuts, but this had little effect on C dynamics during late succession. Future modeling studies of disturbance effects will benefit from the incorporation of forest population dynamics (e.g., regeneration and mortality) and relationships between age-related model parameters and state variables (e.g., LAI) into the model

Near-surface remote sensing of spatial and temporal variation in canopy phenology

There is a need to document how plant phenology is responding to global change factors, particularly warming trends. “Near-surface” remote sensing, using radiometric instruments or imaging sensors, has great potential to improve phenological monitoring because automated observations can be made at high temporal frequency. Here we build on previous work and show how inexpensive, networked digital cameras (“webcams”) can be used to document spatial and temporal variation in the spring and autumn phenology of forest canopies. We use two years of imagery from a deciduous, northern hardwood site, and one year of imagery from a coniferous, boreal transition site. A quantitative signal is obtained by splitting images into separate red, green, and blue color channels and calculating the relative brightness of each channel for “regions of interest” within each image. We put the observed phenological signal in context by relating it to seasonal patterns of gross primary productivity, inferred from eddy covariance measurements of surface–atmosphere CO2 exchange. We show that spring increases, and autumn decreases, in canopy greenness can be detected in both deciduous and coniferous stands. In deciduous stands, an autumn red peak is also observed. The timing and rate of spring development and autumn senescence varies across the canopy, with greater variability in autumn than spring. Interannual variation in phenology can be detected both visually and quantitatively; delayed spring onset in 2007 compared to 2006 is related to a prolonged cold spell from day 85 to day 110. This work lays the foundation for regional- to continental-scale camera-based monitoring of phenology at network observatory sites, e.g., National Ecological Observatory Network (NEON) or AmeriFlux

Modeling physical and chemical climate of the northeastern United States for a geographic information system

A model of physical and chemical climate was developed for New York and New England that can be used in a GIs for integration with ecosystem models. The variables included are monthly average maximum and minimum daily temperatures, precipitation, humidity, and solar radiation, as well as annual atmospheric deposition of sulfur and nitrogen. Equations generated from regional data bases were combined with a digital elevation model of the region to generate digital coverages of each variable

Nitrogen cycling, forest canopy reflectance, and emergent properties of ecosystems

In Ollinger et al. (1), we reported that mass-based concentrations of nitrogen in forest canopies (%N) are positively associated with whole-canopy photosynthetic capacity and canopy shortwave albedo in temperate and boreal forests, the latter result stemming from a positive correlation between %N and canopy near infrared (NIR) reflectance. This finding is intriguing because a functional link between %N and NIR reflectance could indicate an influence of nitrogen cycling on surface energy exchange, and could provide a means for estimating %N using broad-band satellite sensors

DIRECT ESTIMATION OF ABOVEGROUND FOREST PRODUCTIVITY THROUGH HYPERSPECTRAL REMOTE SENSING OF CANOPY NITROGEN

The concentration of nitrogen in foliage has been related to rates of net photosynthesis across a wide range of plant species and functional groups and thus represents a simple and biologically meaningful link between terrestrial cycles of carbon and nitrogen. Although foliar N is used by ecosystem models to predict rates of leaf‐level photosynthesis, it has rarely been examined as a direct scalar to stand‐level carbon gain. Establishment of such relationships would greatly simplify the nature of forest C and N linkages, enhancing our ability to derive estimates of forest productivity at landscape to regional scales. Here, we report on a highly predictive relationship between whole‐canopy nitrogen concentration and aboveground forest productivity in diverse forested stands of varying age and species composition across the 360 000‐ha White Mountain National Forest, New Hampshire, USA. We also demonstrate that hyperspectral remote sensing can be used to estimate foliar N concentration, and hence forest production across a large number of contiguous images. Together these data suggest that canopy‐level N concentration is an important correlate of productivity in these forested systems, and that imaging spectrometry of canopy N can provide direct estimates of forest productivity across large landscapes

Development of scenarios for land cover, population density, impervious cover, and conservation in New Hampshire, 2010–2100

Future changes in ecosystem services will depend heavily on changes in land cover and land use, which, in turn, are shaped by human activities. Given the challenges of predicting long-term changes in human behaviors and activities, scenarios provide a framework for simulating the long-term consequences of land-cover change on ecosystem function. As input for process-based models of terrestrial and aquatic ecosystem function, we developed scenarios for land cover, population density, and impervious cover for the state of New Hampshire for 2020–2100. Key drivers of change were identified through information gathered from six sources: historical trends, existing plans relating to New Hampshire’s land-cover future, surveys, existing population scenarios, key informant interviews with diverse stakeholders, and input from subject-matter experts. Scenarios were developed in parallel with information gathering, with details added iteratively as new questions emerged. The final scenarios span a continuum from spatially dispersed development with a low value placed on ecosystem services (Backyard Amenities) to concentrated development with a high value placed on ecosystem services (the Community Amenities family). The Community family includes two population scenarios (Large Community and Small Community), to be combined with two scenarios for land cover (Protection of Wildlands and Promotion of Local Food), producing combinations that bring the total number of scenarios to six. Between Backyard Amenities and Community Amenities is a scenario based on linear extrapolations of current trends (Linear Trends). Custom models were used to simulate decadal change in land cover, population density, and impervious cover. We present raster maps and proportion of impervious cover for HUC10 watersheds under each scenario and discuss the trade-offs of our translation and modeling approach within the context of contemporary scenario projects

Simulating ozone effects on forest productivity: Interactions among leaf-, canopy-, and stand-level processes

Ozone pollution in the lower atmosphere is known to have adverse effects on forest vegetation, but the degree to which mature forests are impacted has been very difficult to assess directly. In this study, we combined leaf-level ozone response data from independent ozone fumigation studies with a forest ecosystem model in order simulate the effects of ambient ozone on mature hardwood forests. Reductions in leaf carbon gain were determined as a linear function of ozone flux to the leaf interior, calculated as the product of ozone concentration and leaf stomatal conductance. This relationship was applied to individual canopy layers within the model in order to allow interaction with stand- and canopy-level factors such as light attenuation, leaf morphology, soil water limitations, and vertical ozone gradients. The resulting model was applied to 64 locations across the northeastern United States using ambient ozone data from 1987 to 1992. Predicted declines in annual net primary production ranged from 3 to 16% with greatest reductions in southern portions of the region where ozone levels were highest, and on soils with high water-holding capacity where drought stress was absent. Reductions in predicted wood growth were slightly greater (3–22%) because wood is a lower carbon allocation priority in the model than leaf and root growth. Interannual variation in predicted ozone effects was small due to concurrent fluctuations in ozone and climate. Periods of high ozone often coincided with hot, dry weather conditions, causing reduced stomatal conductance and ozone uptake. Within-canopy ozone concentration gradients had little effect on predicted growth reductions because concentrations remained high through upper canopy layers where net carbon assimilation and ozone uptake were greatest. Sensitivity analyses indicate a trade-off between model sensitivity to available soil water and foliar nitrogen and demonstrate uncertainties regarding several assumptions used in the model. Uncertainties surrounding ozone effects on stomatal function and plant water use efficiency were found to have important implications on current predictions. Field measurements of ozone effects on mature forests will be needed before the accuracy of model predictions can be fully assessed