Harvard Forest Research Articles

Measuring effective leaf area index, foliage profile, and stand height in New England forest stands using a full-waveform ground-based lidar

Effective leaf area index (LAI) retrievals from a scanning, ground-based, near-infrared (1064 nm) lidar that digitizes the full return waveform, the Echidna Validation Instrument (EVI), are in good agreement with those obtained from both hemispherical photography and the Li-Cor LAI-2000 Plant Canopy Analyzer. We conducted trials at 28 plots within six stands of hardwoods and conifers of varying height and stocking densities at Harvard Forest, Massachusetts, Bartlett Experimental Forest, New Hampshire, and Howland Experimental Forest, Maine, in July 2007. Effective LAI values retrieved by four methods, which ranged from 3.42 to 5.25 depending on the site and method, were not significantly different (β < 0.1 among four methods). The LAI values also matched published values well. Foliage profiles (leaf area with height) retrieved from the lidar scans, although not independently validated, were consistent with stand structure as observed and as measured by conventional methods. Canopy mean top height, as determined from the foliage profiles, deviated from mean RH100 values obtained from the Lidar Vegetation Imaging Sensor (LVIS) airborne large-footprint lidar system at 27 plots by − 0.91 m with RMSE = 2.04 m, documenting the ability of the EVI to retrieve stand height. The Echidna Validation Instrument is the first realization of the Echidna® lidar concept, devised by Australia's Commonwealth Scientific and Industrial Research Organization (CSIRO), for measuring forest structure using full-waveform, ground-based, scanning lidar.

A new model of net ecosystem carbon exchange for the deciduous-dominated forest by integrating MODIS and flux data

The eddy covariance technique provides continuous measurements of plot-level net ecosystem carbon exchange (NEE) across a wide range of vegetation types. However, these NEE estimates only represent fluxes at the tower footprint scale. To quantify the NEE over regions or continents, flux tower measurements need to be up-scaled to large areas. In the present study, we propose a new NEE model solely based on Moderate Resolution Imaging Spectroradiometer data, including enhanced vegetation index (EVI), land surface water index (LWSI), land surface temperature (LST), and Terra nighttime LST′. Site-specific data from the deciduous-dominated Harvard Forest flux site were used. Analysis covered six years (2001–2006) of CO 2 flux data. The data of the first four years were used for model building and the rest as validation set. Compared with the model based solely on EVI, we also introduced LST and LSWI into the new model. The results showed that this method could further improve the precision ( R 2 and RMSE reached 0.857 and 1.273, respectively) and generally capture the expected seasonal patterns of NEE.

Diagnosing errors in a land surface model (CABLE) in the time and frequency domains

[1] We present an approach for diagnosing errors in land surface models in the time and frequency domains. The approach is applied to the Community Atmosphere-Biosphere-Land Exchange (CABLE). We compare modeled and observed fluxes of net ecosystem carbon exchange (NEE), latent heat (LE) and sensible heat (H) at two different forested flux station sites. Using wavelet analysis, we identify the frequencies where model errors are relatively large, and then analyze the sensitivities of model errors at those frequencies to selected model parameters, yielding significant improvements in several measures of model performance. At Harvard Forest, the predictions by CABLE using the modified parameter values reduce model errors at daily to yearly timescales for all three fluxes, but not at interannual timescales for NEE. At the Tumbarumba site, predictions by CABLE with modified parameter values reduce the variance of model errors of all three fluxes from daily to interannual timescales, but do not improve the agreement with the observed mean diurnal or daily time series for H. We conclude that analyzing both mean and variance of model errors at a range of time/frequency scales is useful for identifying and reducing errors of a land surface model.

Heating up the forest: open‐top chamber warming manipulation of arthropod communities at Harvard and Duke Forests

Summary1. Recent observations indicate that climatic change is altering biodiversity, and models suggest that the consequences of climate change will differ across latitude. However, long‐term experimental field manipulations that directly test the predictions about organisms’ responses to climate change across latitude are lacking. Such experiments could provide a more mechanistic understanding of the consequences of climate change on ecological communities and subsequent changes in ecosystem processes, facilitating better predictions of the effects of future climate change.2. This field experiment uses octagonal, 5‐m‐diameter (c. 22 m3) open‐top chambers to simulate warming at northern (Harvard Forest, Massachusetts) and southern (Duke Forest, North Carolina) hardwood forest sites to determine the effects of warming on ant and other arthropod populations and communities near the edges of their ranges. Each site has 12 plots containing open‐top chambers that manipulate air temperature incrementally from ambient to 6 °C above ambient. Because the focus of this study is on mobile, litter‐ and soil‐dwelling arthropods, standard methods for warming chambers (e.g. soil‐warming cables or infrared heaters applied to relatively small areas) were inappropriate and new technological approaches using hydronic heating and forced air movement were developed.3. We monitor population dynamics, species composition, phenology and behaviour of ants and other arthropods occupying these experimental chambers. Microclimatic measurements in each chamber include the following: air temperature (three), soil temperatures (two each in organic and mineral soil), photosynthetically active radiation (PAR), relative humidity and soil moisture (one each). In two chambers, we are also measuring soil heat flux, associated soil temperatures at 2 and 6 cm and volumetric water content. To assess the composition, phenology and abundance of arthropod communities within the experiment, we use monthly pitfall trapping and annual Winkler sampling. We also census artificial and natural ant nests to monitor changes in ant colony size and productivity across the temperature treatments.4. This experiment is a long‐term ecological study that provides opportunities for collaborations across a broad spectrum of ecologists, including those studying biogeochemical, microbial and plant responses to warming. Future studies also may include implementation of multifactorial climate manipulations, examination of interactions across trophic levels and quantification of changes in ecosystem processes.

Retrieval of canopy height using moderate-resolution imaging spectroradiometer (MODIS) data

In this study we use the 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) product to develop multivariate linear regression models that estimate canopy heights over study sites at Howland Forest, Maine, Harvard Forest, Massachusetts and La Selva Forest, Costa Rica using (1) directional escape probabilities that are spectrally independent and (2) the directional spectral reflectances used to derive the directional escape probabilities. These measures of canopy architecture are compared with canopy height information retrieved from the airborne Laser Vegetation Imaging Sensor (LVIS). Both the escape probability and the directional reflectance approaches achieve good results, with correlation coefficients in the range 0.54–0.82, although escape probability results are usually slightly better. This suggests that MODIS 500 m BRDF data can be used to extrapolate canopy heights observed by widely-spaced satellite LIDAR swaths to larger areas, thus providing wide-area coverage of canopy height.

Seasonal dynamics of soil respiration and N mineralization in chronically warmed and fertilized soils

Although numerous studies have examined the individual effects of increased temperatures and N deposition on soil biogeochemical cycling, few have considered how these disturbances interact to impact soil C and N dynamics. Likewise, many have not assessed season-specific responses to warming and N inputs despite seasonal variability in soil processes. We studied interactions among season, warming, and N additions on soil respiration and N mineralization at the Soil Warming × Nitrogen Addition Study at the Harvard Forest. Of particular interest were wintertime fluxes of C and N typically excluded from investigations of soils and global change. Soils were warmed to 5°C above ambient, and N was applied at a rate of 5 g m−2 y−1. Soil respiration and N mineralization were sampled over two years between 2007 and 2009 and showed strong seasonal patterns that mirrored changes in soil temperature. Winter fluxes of C and N contributed between 2 and 17% to the total annual flux. Net N mineralization increased in response to the experimental manipulations across all seasons, and was 8% higher in fertilized plots and 83% higher in warmed plots over the duration of the study. Soil respiration showed a more season-specific response. Nitrogen additions enhanced soil respiration by 14%, but this increase was significant only in summer and fall. Likewise, warming increased soil respiration by 44% over the whole study period, but the effect of warming was most pronounced in spring and fall. The only interaction between warming × N additions took place in autumn, when N availability likely diminished the positive effect of warming on soil respiration. Our results suggest that winter measurements of C and N are necessary to accurately describe winter biogeochemical processes. In addition, season-specific responses to the experimental treatments suggest that some components of the belowground community may be more susceptible to warming and N additions than others. Seasonal changes in the abiotic environment may have also interacted with the experimental manipulations to evoke biogeochemical responses at certain times of year.

Effects of the Hemlock Woolly Adelgid on Nitrogen Losses from Urban and Rural Northern Forest Ecosystems

The objectives of this study were to quantify rates of nitrogen inputs to the forest floor, determine rates of nitrogen losses via leaching and to partition the sources of NO3 − from healthy, declining, and salvage or preemptively cut eastern hemlock (Tsuga canadensis) stands in both an urban forest at the Arnold Arboretum in Boston, MA and a rural forest at Harvard Forest in Petersham, MA. Rates of nitrogen inputs (NH4 + and NO3 −) to the forest floor were 4–5 times greater, and rates of nitrogen losses via leachate were more than ten times greater, at the Arnold Arboretum compared to Harvard Forest. Nitrate that was lost via leachate at Harvard Forest came predominantly from atmospheric deposition inputs, whereas NO3 − losses at the Arnold Arboretum came predominantly from nitrification. Although our study was limited to one urban and one rural site, our results suggest that current management regimes used to control the hemlock woolly adelgid (Adelges tsugae), such as salvage cutting, may be reducing nitrogen losses in urban areas due to rapid regrowth of vegetation and uptake of nitrogen by those plants. In contrast, preemptive cutting of trees in rural areas may be leading to proportionately greater losses of nitrogen in those sites, though the total magnitude of nitrogen lost is still smaller than in urban sites. Results of our study suggest that the combination of the hemlock woolly adelgid, nitrogen inputs, and management practices lead to changes in the movement and source of NO3 − losses from eastern hemlock forest ecosystems.

A geostatistical synthesis study of factors affecting gross primary productivity in various ecosystems of North America

Abstract. A coupled Bayesian model selection and geostatistical regression modeling approach is adopted for empirical analysis of gross primary productivity (GPP) at six AmeriFlux sites, including the Kennedy Space Center Scrub Oak, Vaira Ranch, Tonzi Ranch, Blodgett Forest, Morgan Monroe State Forest, and Harvard Forest sites. The analysis is performed at a continuum of temporal scales ranging from daily to monthly, for a period of seven years. A total of 10 covariates representing environmental stimuli and indices of plant physiology are considered in explaining variations in GPP. Similarly to other statistical methods, the presented approach estimates regression coefficients and uncertainties associated with the covariates in a selected regression model. Unlike traditional regression methods, however, the approach also estimates the uncertainty associated with the selection of a single "best" model of GPP. In addition, the approach provides an enhanced understanding of how the importance of specific covariates changes with the examined timescale (i.e. temporal resolution). An examination of changes in the importance of specific covariates across timescales reveals thresholds above or below which covariates become important in explaining GPP. Results indicate that most sites (especially those with a stronger seasonal cycle) exhibit at least one prominent scaling threshold between the daily and 20-day temporal scales. This demonstrates that environmental variables that explain GPP at synoptic scales are different from those that capture its seasonality. At shorter time scales, radiation, temperature, and vapor pressure deficit exert the most significant influence on GPP at most examined sites. At coarser time scales, however, the importance of these covariates in explaining GPP declines. Overall, unique best models are identified at most sites at the daily scale, whereas multiple competing models are identified at longer time scales.

Short-term effects of rain on soil respiration in two New England forests

To gain new insights into the underlying mechanisms responsible for wetting-induced soil respiration, rain simulation field experiments were carried out in two temperate mixed-hardwood forests in New England (Great Mountain Forest and Harvard Forest). The rain-induced CO2 pulses were observed in both xeric and mesic soils. The pulse intensity was negatively correlated with the site moisture level and the pre-rain soil CO2 flux. At both forests, plots without O horizon responded to wetting with limited or even negative enhancement, confirming previous finding that the rain pulse was likely due to enhanced microbial consumption on substrates mainly of microbial origin. Our results show that the flux rain pulse was a reproducible phenomenon not limited to dry soils.

Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest

Gross primary production (GPP) defined as the overall rate of fixation of carbon through the process of vegetation photosynthesis is important for carbon cycle and climate change research. Three models, the Vegetation Photosynthesis Model (VPM), the Temperature and Greenness (TG) model and the Vegetation Index (VI) model have been compared for the estimation of GPP in Harvard Forest from 2003 to 2006 using climate variables acquired by eddy covariance (EC) measurements and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. All these models provide more reliable estimates of GPP than that of MODIS GPP product. High Pearsons correlation coefficients r equal to 0.94, 0.92 and 0.90 are observed for the VPM, the TG and the VI model, respectively. Relationships between GPP and land surface temperature (LST, R 2 = 0.72), and vapor pressure deficit (VPD, R 2 = 0.45) indicate that climate variables are important for GPP estimation. Due to proper characterization of temperature, water stress and leaf age by three scalars, VPM best follows the seasonal variations of GPP. By incorporation of the MODIS surface reflectance and LST product, the TG model is the most suitable choice for areas without prior knowledge as it is based entirely on remote sensing observations. Results from the VI model demonstrate the possibility of using a single vegetation index for light use efficiency (LUE) estimation in deciduous forest that is of high spatial heterogeneity. The validation and comparison of models will be helpful in development of future GPP models using combinations of climate variables and/or remote sensing observations.

Interannual, seasonal, and diel variation in soil respiration relative to ecosystem respiration at a wetland to upland slope at Harvard Forest

Soil carbon dioxide efflux (soil respiration, SR) was measured with eight autochambers at two locations along a wetland to upland slope at Harvard Forest over a 4 year period, 2003–2007. SR was consistently higher in the upland plots than at the wetland margin during the late summer/early fall. Seasonal and diel hystereses with respect to soil temperatures were of sufficient magnitude to prevent quantification of the influence of soil moisture, although apparent short‐term responses of SR to precipitation occurred. Calculations of annual cumulative SR illustrated a decreasing trend in SR over the 5 year period, which were correlated with decreasing springtime mean soil temperatures. Spring soil temperatures decreased despite rising air temperatures over the same period, possibly as an effect of earlier leaf expansion and shading. The synchronous decrease in spring soil temperatures and SR during regional warming of air temperatures may represent a negative feedback on a warming climate by reducing CO2 production from soils. SR reached a maximum later in the year than total ecosystem respiration (ER) measured at a nearby eddy covariance flux tower, and the seasonality of their temperature response patterns were roughly opposite. SR, particularly in the upland, exceeded ER in the late summer/early fall in each year, suggesting that areas of lower efflux such as the wetland may be significant in the flux tower footprint or that long‐term bias in either estimate may create a mismatch. Annual estimates of ER decreased over the same period and were highly correlated with SR.

Experimentally testing the role of foundation species in forests: the Harvard Forest Hemlock Removal Experiment

Summary 1. Problem statement– Foundation species define and structure ecological systems. In forests around the world, foundation tree species are declining due to overexploitation, pests and pathogens. Eastern hemlock (Tsuga canadensis), a foundation tree species in eastern North America, is threatened by an exotic insect, the hemlock woolly adelgid (Adelges tsugae). The loss of hemlock is hypothesized to result in dramatic changes in assemblages of associated species with cascading impacts on food webs and fluxes of energy and nutrients. We describe the setting, design and analytical framework of the Harvard Forest Hemlock Removal Experiment (HF‐HeRE), a multi‐hectare, long‐term experiment that overcomes many of the major logistical and analytical challenges of studying system‐wide consequences of foundation species loss. 2. Study design– HF‐HeRE is a replicated and blocked Before‐After‐Control‐Impact experiment that includes two hemlock removal treatments: girdling all hemlocks to simulate death by adelgid and logging all hemlocks &gt;20 cm diameter and other merchantable trees to simulate pre‐emptive salvage operations. These treatments are paired with two control treatments: hemlock controls that are beginning to be infested in 2010 by the adelgid and hardwood controls that represent future conditions of most hemlock stands in eastern North America. 3. Ongoing measurements and monitoring– Ongoing long‐term measurements to quantify the magnitude and direction of forest ecosystem change as hemlock declines include: air and soil temperature, light availability, leaf area and canopy closure; changes in species composition and abundance of the soil seed‐bank, understorey vegetation, and soil‐dwelling invertebrates; dynamics of coarse woody debris; soil nitrogen availability and net nitrogen mineralization; and soil carbon flux. Short‐term or one‐time‐only measurements include initial tree ages, hemlock‐decomposing fungi, wood‐boring beetles and throughfall chemistry. Additional within‐plot, replicated experiments include effects of ants and litter‐dwelling microarthoropods on ecosystem functioning, and responses of salamanders to canopy change. 4. Future directions and collaborations– HF‐HeRE is part of an evolving network of retrospective studies, natural experiments, large manipulations and modelling efforts focused on identifying and understanding the role of single foundation species on ecological processes and dynamics. We invite colleagues from around the world who are interested in exploring complementary questions to take advantage of the HF‐HeRE research infrastructure.

Responses of terrestrial ecosystems and carbon budgets to current and future environmental variability

We assess the significance of high-frequency variability of environmental parameters (sunlight, precipitation, temperature) for the structure and function of terrestrial ecosystems under current and future climate. We examine the influence of hourly, daily, and monthly variance using the Ecosystem Demography model version 2 in conjunction with the long-term record of carbon fluxes measured at Harvard Forest. We find that fluctuations of sunlight and precipitation are strongly and nonlinearly coupled to ecosystem function, with effects that accumulate through annual and decadal timescales. Increasing variability in sunlight and precipitation leads to lower rates of carbon sequestration and favors broad-leaved deciduous trees over conifers. Temperature variability has only minor impacts by comparison. We also find that projected changes in sunlight and precipitation variability have important implications for carbon storage and ecosystem structure and composition. Based on Intergovernmental Panel on Climate Change model estimates for changes in high-frequency meteorological variability over the next 100 years, we expect that terrestrial ecosystems will be affected by changes in variability almost as much as by changes in mean climate. We conclude that terrestrial ecosystems are highly sensitive to high-frequency meteorological variability, and that accurate knowledge of the statistics of this variability is essential for realistic predictions of ecosystem structure and functioning.

A clumped-foliage canopy radiative transfer model for a Global Dynamic Terrestrial Ecosystem Model II: Comparison to measurements

In a previous paper, we developed an analytical clumped two-stream model (ACTS) of canopy radiative transfer from an analytical geometric-optical and radiative transfer (GORT) scheme ( Ni-Meister et al., 2010). The ACTS model accounts for clumping of foliage and the influence of trunks in vegetation canopies for modeling of photosynthesis, radiative fluxes and surface albedo in dynamic global vegetation models (DGVMs), and particularly for the Ent Dynamic Global Terrestrial Ecosystem Model (DGTEM). This study evaluates the gap probability and transmittance estimates from the ACTS model by comparing the modeled results with ground-based data, as well as with the original full GORT model and a layered Beer's law scheme. The ground data used in this study include vertical profile measurements of incident photosynthetically active radiation (PAR) in (1) mixed deciduous forests in Morgan-Monroe State Forest, IN, USA, (2) coniferous forests in central Canada, (3) mixed deciduous forests in Harvard Forest, MA, and (4) ground lidar measurements of the canopy gap fraction in woodland in Australia. The model comparisons with these measurements demonstrate that the ACTS model achieves better or similar performance compared to the full GORT and the layered Beer's law schemes with regard to agreements with field measurements and computational cost. The ACTS model has excellent accuracy and flexibility to model the canopy gap probability and transmittance for various forest scenarios. Also, it has advantages relative to the currently widely used two-stream scheme through better radiation estimation for photosynthesis by accounting for the impact of both vertical and horizontal structure heterogeneity of complex vegetation on radiative transfer. Currently the ACTS is being implemented in Ent and will be further tested for how it improves surface energy balance and carbon flux estimates.

Seasonality, the latitudinal gradient of diversity, and Eocene insects

In the modern world, biotic diversity is typically higher in low-latitude tropical regions where there is abundant insolation (light and heat) and low thermal seasonality. Because these factors broadly covary with latitude, separating their possible effects on species diversity is difficult. The Eocene was a much more equable world, however, with low temperature seasonality extending into lower-insolation higher, cooler latitudes, allowing us to test these factors by comparing insect species diversity in (1) modern, temperate, low-insolation, highly seasonal Harvard Forest, Massachusetts, U.S.A., 42°29'N; (2) modern, tropical, high-insolation, low-seasonality La Selva, Costa Rica, 10°26'N, and; (3) Eocene, temperate, low-insolation, yet low-seasonality McAbee, British Columbia, Canada, above 50°N paleolatitude. We found insect diversity at McAbee to be more similar to La Selva than to Harvard Forest, with high species richness of most groups and decreased diversity of ichneumon wasps, indicating that seasonality is key to the latitudinal diversity gradient. Further, midlatitude Eocene woody dicot diversities at McAbee, Republic (Washington, U.S.A.), and Laguna del Hunco (Argentina) are also high, similar to modern tropical samples, higher than at the modern midlatitude Harvard Forest. Modern correlations between latitude, species diversity, and seasonal climates were established some time after the Eocene.

Special Volume devoted to the 15th International Frankia and Actinorhizal Plant Meeting

The 15th International Frankia and Actinorhizal Plant Meeting was held from October 19th to 23rd, 2008, in Bariloche, Argentina. Frankia is an actinomycete that nodulates roots of a group of angiospermous plants. Frankia fixes atmospheric nitrogen symbiotically with its specific host plants in 24 genera within eight families. This was the first of the biennial meetings to be held in South America and only the second, after New Zealand, to be held outside of North America and Europe. Thirty four scientists and students from nine different countries in South America, North America, Europe and Asia attended. The site of the meeting, Bariloche, is in the Patagonian region of the southern Andean Mountains, where a distinct group of actinorhizal plants and their Frankia symbionts occur. These plants are in the tribe Colletiae (family Rhamnaceae) and the meeting participants had the opportunity to explore their natural environs from steppe to humid forest in the Nahuel Huapi National Park near Bariloche and to hear reports of the most recent research on this actinorhizal group. Much research progress has been made on Frankia and on actinorhizal plants since the first meeting was held at Harvard Forest in Petersham, Massachusetts in 1978. At that meeting, hosted by Dr. John Torrey, an icon in the field of Frankia research, the common interests of a small group of researchers had evolved from developments in three areas. The first area of advancement was the effort, sponsored by the International Biological Program, to establish a worldwide accounting for actinorhizal plants, then known to be comprised of 15 genera in seven “diverse” families. These morphologically “diverse” groups are now known to cluster together with other plant taxa, including legumes, in the subclade rosidae, apparently a taxonomic unit with plants predisposed to diazotrophic symbioses. The second impetus came from the increased recognition by foresters and other natural resource managers that actinorhizal plants possessed nitrogen fixation capacities equal to those of legumes and that actinorhizal plants conferred the dual benefits of superior host-plant productivity on poor soils and enhancement of soil nitrogen fertility. The third development was the first successful isolation of a Frankia strain (CpI1 from Comptonia peregrina) in pure culture and reinfection of a host plant by this isolate. This feat opened the door to a detailed understanding of this nitrogen-fixing actinomycete, its symbiosis with angiospermous host plants, and its potential for genetic improvement through biotechnology. Since the first conference, and even the most recent one held at the University of Umea in Sweden in 2006, substantial changes in emphasis and developments have occurred and were featured at this 15th meeting in Argentina. These included (1) notable advancements in E. Chaia (*) Universidad Nacional del Comahue, Centro Regional Universitario Bariloche, Quintral 1250, Bariloche 8400, Argentina e-mail: echaia@crub.uncoma.edu.ar

Modeling gross primary production of deciduous forest using remotely sensed radiation and ecosystem variables

We explored the potential application of two remotely sensed (RS) variables, the Global Vegetation Moisture Index (GVMI) and the near‐infrared albedo (AlbedoNIR), in modeling the gross primary production (GPP) of three deciduous forests. For the Harvard Forest (deciduous) of Massachusetts, it was found that GPP is strongly correlated with GVMI (coefficient of determination, R2 = 0.60) during the growing season, and with AlbedoNIR (R2 = 0.82) throughout the year. Subsequently, a statistical model called the Remotely Sensed GPP (R‐GPP) model was developed to estimate GPP using remotely sensed radiation (land surface temperature (LST), AlbedoNIR) and ecosystem variables (enhanced vegetation index (EVI) and GVMI). The R‐GPP model, calibrated and validated against the GPP estimates derived from the eddy covariance flux tower of the Harvard Forest, could explain 95% and 92% of the observed GPP variability for the study site during the calibration (2000–2003) and the validation (2004–2005) periods, respectively. It outperformed the primary RS‐based GPP algorithm of Moderate Resolution Imaging Spectroradiometer (MODIS), which explained 80% and 77% of the GPP variability during 2000–2003 and 2004–2005, respectively. The calibrated R‐GPP model also explained 93% and 94% of the observed GPP variation for two other independent validation sites, the Morgan Monroe State Forest and the University of Michigan Biological Station, respectively, which demonstrates its transferability to other deciduous ecoregions of northeastern United States.

Evaluating the effect of drier and warmer conditions on water use by Quercus pyrenaica

Under climate change, severe and recurrent droughts can reduce forest production and cause widespread tree dieback. The response of different vegetation types to climate change can vary greatly and, therefore, must be individually assessed. This study was carried out in a Mediterranean oak forest ( Quercus pyrenaica) subject to seasonal summer drought. To examine the response of the forest to the climate conditions predicted under climate change, a Soil–Vegetation–Atmosphere Transfer model [SPA, Williams, M., Rastetter, E.B., Fernandes, D.N., Goulden, M.L., Wofsy, S.C., Shaver, G.R., Melillo, J.M., Munger, J.W., Fan, S.M., Nadelhoffer, K.J. 1996. Modelling the soil-plant-atmosphere continuum in a Quercus– Acer stand at Harvard Forest: the regulation of stomatal conductance by light, nitrogen and soil/plant hydraulic properties. Plant, Cell, Environment 19, 911–927] was used. The model was parameterized using mostly local measurements (independent of the verification data) and tested against in situ sap flow measurements obtained during year 2007. The predictions of the model were broadly consistent with the observed dynamics of sap flow (the model explained 71% of the variance in daily transpiration and 75% of half-hourly sap flow), leaf water potentials and soil water content. Once the model had been validated, simulations were carried out under warmer and dryer conditions. Predicted warmer conditions (4 °C) caused a moderate increase in total simulated transpiration. Less frequent precipitation (40% longer dry periods between rainfall events) had very little effect on transpiration. In contrast, transpiration was reduced by 17% when the soil water reserves at the beginning of the summer were lower than in 2007, corresponding to those measured in a very dry year (2005). The reduction was exacerbated when changes in temperature and rainfall were also considered (up to 28% decline in transpiration). The higher atmospheric CO 2 concentrations (712 ppm) simulated together with climate change, did not prevent the decline in tree water use or soil water storage at the end of the summer. All scenarios caused the soil water storage to reach extremely low values at the end of the dry season (a minimum of 25 mm). It is concluded that climate change is likely to have a negative impact on tree water use and soil water resources in the study area, increasing the water deficit by as much as 30%.

Three scales of temporal resolution from automated soil respiration measurements

Soil respiration ( R s) is a combination of autotrophic and heterotrophic respiration, but it is often modeled as a single efflux process, influenced by environmental variables similarly across all time scales. Continued progress in understanding sources of variation in soil CO 2 efflux will require development of R s models that incorporate environmental influences at multiple time scales. Coherence analysis, which requires high temporal frequency data on R s and related environmental variables, permits examination of covariation between R s and the factors that influence it at varying temporal frequencies, thus isolating the factors important at each time scale. Automated R s measurements, along with air, soil temperature and moisture were collected at half hour intervals at a temperate forest at Harvard Forest, MA in 2003 and a boreal transition forest at the Howland Forest, ME in 2005. As in other temperate and boreal forests, seasonal variation in R s was strongly correlated with soil temperature. The organic and mineral layer water contents were significantly related to R s at synoptic time scales of 2–3 days to weeks, representing the wetting and drying of the soils as weather patterns move across the region. Post-wetting pulses of R s were correlated with the amount of precipitation and the magnitude of the change from pre-wet-up moisture content to peak moisture content of the organic horizon during the precipitation events. Although soil temperature at 8–10 cm depth and R s showed strong coherence at a 24-h interval, calculated diel Q 10 values for R s were unreasonably high (6–74) during all months for the evergreen forest and during the growing season for the deciduous forest, suggesting that other factors that covary with soil temperature, such as canopy assimilatory processes, may also influence the diel amplitude of R s. Lower diel Q 10 values were obtained based on soil temperature measured at shallower depths or with air temperature, but the fit was poorer and a lag was needed to improve the fit (peak R s followed peak air temperature by several hours), suggesting a role for delayed substrate supply from aboveground processes to affect diel patterns of R s. High frequency automated R s datasets afford the opportunity to disentangle the temporal scales at which environmental factors, such as seasonal temperature and phenology, synoptic weather events and soil moisture, and diel variation in temperature and photosynthesis, affect soil respiration processes.

Estimation of evapotranspiration in a mid-latitude forest using the Microwave Emissivity Difference Vegetation Index (EDVI)

We developed an algorithm to estimate evapotranspiration (ET) from dense vegetation covered area from the first principle of surface energy balance model by using satellite retrieved Microwave Emissivity Difference Vegetation Index (EDVI). This algorithm can be used under both clear sky and cloudy sky conditions. Long term seasonal trend of EDVI is linked to variance of canopy resistance due to the interrelationship among leaf development, environmental condition and microwave radiation. Short term changes of EDVI caused by synoptic scale weather variations is used to parameterize the responds of vegetation resistance to the quick changes of environmental factors including water vapor deficit, water potential and others. The performance of this algorithm was test at the Harvard forest site by using satellite measurements from the SSM/I F13 and F14 sensors. Validation at the site with 169 samples shows that the correlation coefficient ( R 2) between estimated and observed ETs is 0.83 with a mean bias of 3.31 Wm − 2 and a standard deviation of 79.63 Wm − 2 . The overall uncertainty of our ET retrieval is ~30%, which is within the uncertainty of current ground based ET measurements. Furthermore, the estimated ET in different local times (up to 4 times per day) successfully captured the diurnal cycle of ET. It is the first time that the diurnal variations of vegetation–atmosphere interactions were directly monitored from space. This study demonstrates that the technique reported here extends the current satellite capability of vegetation property and ET flux remote sensing from daytime, clear-sky conditions to day and night times and from intermediate leaf area index (LAI) to all range of vegetation states.