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We develop and evaluate a method to estimate O3 deposition and stomatal O3 uptake across networks of eddy covariance flux tower sites where O3 concentrations and O3 fluxes have not been measured. The method combines standard micrometeorological flux measurements, which constrain O3 deposition velocity and stomatal conductance, with a gridded dataset of observed surface O3 concentrations. Measurement errors are propagated through all calculations to quantify O3 flux uncertainties. We evaluate the method at three sites with O3 flux measurements: Harvard Forest, Blodgett Forest, and Hyytiälä Forest. The method reproduces 83% or more of the variability in daily stomatal uptake at these sites with modest mean bias (21% or less). At least 95% of daily average values agree with measurements within a factor of 2 and, according to the error analysis, the residual differences from measured O3 fluxes are consistent with the uncertainty in the underlying measurements. The product, called synthetic O3 flux or SynFlux, includes 43 FLUXNET sites in the United States and 60 sites in Europe, totaling 926 site years of data. This dataset, which is now public, dramatically expands the number and types of sites where O3 fluxes can be used for ecosystem impact studies and evaluation of air quality and climate models. Across these sites, the mean stomatal conductance and O3 deposition velocity is 0.03-1.0cms-1. The stomatal O3 flux during the growing season (typically April-September) is 0.5-11.0nmol O3m-2s-1 with a mean of 4.5nmol O3m-2s-1 and the largest fluxes generally occur where stomatal conductance is high, rather than where O3 concentrations are high. The conductance differences across sites can be explained by atmospheric humidity, soil moisture, vegetation type, irrigation, and land management. These stomatal fluxes suggest that ambient O3 degrades biomass production and CO2 sequestration by 20%-24% at crop sites, 6%-29% at deciduous broadleaf forests, and 4%-20% at evergreen needleleaf forests in the United States and Europe.

In Amazon forests, the relative contributions of climate, phenology, and disturbance to net ecosystem exchange of carbon (NEE) are not well understood. To partition influences across various timescales, we use a statistical model to represent eddy-covariance-derived NEE in an evergreen eastern Amazon forest as a constant response to changing meteorology and phenology throughout a decade. Our best fit model represented hourly NEE variations as changes due to sunlight, while seasonal variations arose from phenology influencing photosynthesis and from rainfall influencing ecosystem respiration, where phenology was asynchronous with dry-season onset. We compared annual model residuals with biometric forest surveys to estimate impacts of drought disturbance. We found that our simple model represented hourly and monthly variations in NEE well (R 2 Combining double low line 0.81 and 0.59, respectively). Modeled phenology explained 1 % of hourly and 26 % of monthly variations in observed NEE, whereas the remaining modeled variability was due to changes in meteorology. We did not find evidence to support the common assumption that the forest phenology was seasonally light- or water-triggered. Our model simulated annual NEE well, with the exception of 2002, the first year of our data record, which contained 1.2 MgC ha'1 of residual net emissions, because photosynthesis was anomalously low. Because a severe drought occurred in 1998, we hypothesized that this drought caused a persistent, multi-year depression of photosynthesis. Our results suggest drought can have lasting impacts on photosynthesis, possibly via partial damage to still-living trees.

Hourly measurements of O3, NO, NO2, PAN, HNO3 and NOy concentrations, and eddy-covariance fluxes of O3 and NOy over a temperate deciduous forest from June to November, 2000 were used to evaluate the dry deposition velocities (Vd) estimated by the WRF-Chem dry deposition module (WDDM), which adopted Wesely (1989) scheme for surface resistance (Rc), and the Noah land surface model coupled with a photosynthesis-based Gas-exchange Evapotranspiration Model (Noah-GEM). Noah-GEM produced better Vd(O3) variations due to its more realistically simulated stomatal resistance (Rs) than WDDM. Vd(O3) is very sensitive to the minimum canopy stomatal resistance (Ri) which is specified for each seasonal category assigned in WDDM. Treating Sep-Oct as autumn in WDDM for this deciduous forest site caused a large underprediction of Vd(O3) due to the leafless assumption in 'autumn' seasonal category for which an infinite Ri was assigned. Reducing Ri to a value of 70sm-1, the same as the default value for the summer season category, the modeled and measured Vd(O3) agreed reasonably well. HNO3 was found to dominate the NOy flux during the measurement period; thus the modeled Vd(NOy) was mainly controlled by the aerodynamic and quasi-laminar sublayer resistances (Ra and Rb), both being sensitive to the surface roughness length (z0). Using an appropriate value for z0 (10% of canopy height), WDDM and Noah-GEM agreed well with the observed daytime Vd(NOy). The differences in Vd(HNO3) between WDDM and Noah-GEM were small due to the small differences in the calculated Ra and Rb between the two models; however, the differences in Rc of NO2 and PAN between the two models reached a factor of 1.1-1.5, which in turn caused a factor of 1.1-1.3 differences for Vd. Combining the measured concentrations and modeled Vd, NOx, PAN and HNO3 accounted for 19%, 4%, and 70% of the measured NOy fluxes, respectively. © 2011 Elsevier Ltd.

Forest carbon sequestration offsets are methodologically uncertain, comprise a minor component of carbon markets and do not effectively slow deforestation. The objective of this study is to describe a commercial scale in situ measurement approach for determination of net forest carbon sequestration projects, the Direct Measurement Forest Carbon ProtocolTM, to address forest carbon market uncertainties. In contrast to protocols that rely on limited forest mensuration, growth simulation and exclusion of CO2 data, the Direct Measurement Forest Carbon ProtocolTM is based on standardized methods for direct determination of net ecosystem exchange (NEE) of CO2 employing eddy covariance, a meteorological approach integrating forest carbon fluxes. NEE is used here as the basis for quantifying the first of its kind carbon financial products. The DMFCP differentiates physical, project and financial carbon within a Systemof-SystemsTM (SoS) network architecture. SoS sensor nodes, the Global Monitoring PlatformTM (GMP), housing analyzers for CO2 isotopologues (e.g., 12CO2, 13CO2, 14CO2) and greenhouse gases are deployed across the project landscape. The SoS standardizes and automates GMP measurement, uncertainty and reporting functions creating diverse forest carbon portfolios while reducing cost and investment risk in alignment with modern portfolio theory. To illustrate SoS field deployment and operation, published annual NEE data for a tropical (Ankasa Park, Ghana, Africa) and a deciduous forest (Harvard Forest, Petersham, MA, USA) are used to forecast carbon revenue. Carbon pricing scenarios are combined with historical in situ NEE annual time-series to extrapolate pre-tax revenue for each project applied to 100,000 acres (40,469 hectares) of surrounding land. Based on carbon pricing of $5 to $36 per ton CO2 equivalent (tCO2eq) and observed NEE sequestration rates of 0.48 to 15.60 tCO2eq acre−1 yr−1, pre-tax cash flows ranging from $230,000 to $16,380,000 across project time-series are calculated, up to 5× revenue for contemporary voluntary offsets, demonstrating new economic incentives to reverse deforestation. The SoS concept of operation and architecture, with engineering development, can be extended to diverse gas species across terrestrial, aquatic and oceanic ecosystems, harmonizing voluntary and compliance market products worldwide to assist in the management of global warming. The Direct Measurement Forest Carbon Protocol reduces risk of invalidation intrinsic to estimation-based protocols such as the Climate Action Reserve and the Clean Development Mechanism that do not observe molecular CO2 to calibrate financial products. Multinational policy applications such as the Paris Agreement and the United Nations Reducing Emissions from Deforestation and Degradation, constrained by Kyoto Protocol era processes, will benefit from NEE measurement avoiding unsupported claims of emission reduction, fraud, and forest conservation policy failure. [ABSTRACT FROM AUTHOR]

Understanding the environmental and biotic drivers of respiration at the ecosystem level is a prerequisite to further improve scenarios of the global carbon cycle. In this study we investigated the relevance of physiological phenology, defined as seasonal changes in plant physiological properties, for explaining the temporal dynamics of ecosystem respiration ( RECO) in deciduous forests. Previous studies showed that empirical RECO models can be substantially improved by considering the biotic dependency of RECO on the short-term productivity (e.g., daily gross primary production, GPP) in addition to the well-known environmental controls of temperature and water availability. Here, we use a model-data integration approach to investigate the added value of physiological phenology, represented by the first temporal derivative of GPP, or alternatively of the fraction of absorbed photosynthetically active radiation, for modeling RECO at 19 deciduous broadleaved forests in the FLUXNET La Thuile database. The new data-oriented semiempirical model leads to an 8% decrease in root mean square error ( RMSE) and a 6% increase in the modeling efficiency ( EF) of modeled RECO when compared to a version of the model that does not consider the physiological phenology. The reduction of the model-observation bias occurred mainly at the monthly time scale, and in spring and summer, while a smaller reduction was observed at the annual time scale. The proposed approach did not improve the model performance at several sites, and we identified as potential causes the plant canopy heterogeneity and the use of air temperature as a driver of ecosystem respiration instead of soil temperature. However, in the majority of sites the model-error remained unchanged regardless of the driving temperature. Overall, our results point toward the potential for improving current approaches for modeling RECO in deciduous forests by including the phenological cycle of the canopy. [ABSTRACT FROM AUTHOR]

Over the last two and half decades, strong evidence showed that the terrestrial ecosystems are acting as a net sink for atmospheric carbon. However the spatial and temporal patterns of variation in the sink are not well known. In this study, we examined latitudinal patterns of interannual variability (IAV) in net ecosystem exchange (NEE) of CO2 based on 163 site-years of eddy covariance data, from 39 northern-hemisphere research sites located at latitudes ranging from ∼29°N to ∼64°N. We computed the standard deviation of annual NEE integrals at individual sites to represent absolute interannual variability (AIAV), and the corresponding coefficient of variation as a measure of relative interannual variability (RIAV). Our results showed decreased trends of annual NEE with increasing latitude for both deciduous broadleaf forests and evergreen needleleaf forests. Gross primary production (GPP) explained a significant proportion of the spatial variation of NEE across evergreen needleleaf forests, whereas, across deciduous broadleaf forests, it is ecosystem respiration (Re). In addition, AIAV in GPP and Re increased significantly with latitude in deciduous broadleaf forests, but AIAV in GPP decreased significantly with latitude in evergreen needleleaf forests. Furthermore, RIAV in NEE, GPP, and Re appeared to increase significantly with latitude in deciduous broadleaf forests, but not in evergreen needleleaf forests. Correlation analyses showed air temperature was the primary environmental factor that determined RIAV of NEE in deciduous broadleaf forest across the North American sites, and none of the chosen climatic factors could explain RIAV of NEE in evergreen needleleaf forests. Mean annual NEE significantly increased with latitude in grasslands. Precipitation was dominant environmental factor for the spatial variation of magnitude and IAV in GPP and Re in grasslands. [ABSTRACT FROM AUTHOR]