Notes: The net ecosystem exchange of CO2 between forests and the atmosphere, measured by eddy covariance, is the small difference between two large fluxes of photosynthesis and respiration. Chamber measurements of soil surface CO2 efflux (Fs), wood respiration (Fw) and foliage respiration (Ff) help identify the contributions of these individual components to net ecosystem exchange. Models developed from the chamber data also provide independent estimates of respiration costs. We measured CO2 efflux with chambers periodically in 1996–97 in a ponderosa pine forest in Oregon, scaled these measurements to the ecosystem, and computed annual totals for respiration by component. We also compared estimated half-hourly ecosystem respiration at night (Fnc) with eddy covariance measurements. Mean foliage respiration normalized to 10 °C was 0.20 μmol m–2 (hemi-leaf surface area) s–1, and reached a maximum of 0.24 μmol m–2 HSA s–1 between days 162 and 208. Mean wood respiration normalized to 10 °C was 5.9 μmol m–3 sapwood s–1, with slightly higher rates in mid-summer, when growth occurs. There was no significant difference (P 〉 0.10) between wood respiration of young (45 years) and old trees (250 years). Soil surface respiration normalized to 10 °C ranged from 0.7 to 3.0 μmol m–2 (ground) s–1 from days 23 to 329, with the lowest rates in winter and highest rates in late spring. Annual CO2 flux from soil surface, foliage and wood was 683, 157, and 54 g C m–2 y–1, with soil fluxes responsible for 76% of ecosystem respiration. The ratio of net primary production to gross primary production was 0.45, consistent with values for conifer sites in Oregon and Australia, but higher than values reported for boreal coniferous forests. Below-ground carbon allocation (root turnover and respiration, estimated as Fs– litterfall carbon) consumed 61% of GPP; high ratios such as this are typical of sites with more water and nutrient constraints. The chamber estimates were moderately correlated with change in CO2 storage in the canopy (Fstor) on calm nights (friction velocity u* 〈 0.25 m s–1; R2 = 0.60); Fstor was not significantly different from summed chamber estimates. On windy nights (u* 〉 0.25 m s–1), the sum of turbulent flux measured above the canopy by eddy covariance and Fstor was only weakly correlated with summed chamber estimates (R2 = 0.14); the eddy covariance estimates were lower than chamber estimates by 50%.

Notes: Operational monitoring of global terrestrial gross primary production (GPP) and net primary production (NPP) is now underway using imagery from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Evaluation of MODIS GPP and NPP products will require site-level studies across a range of biomes, with close attention to numerous scaling issues that must be addressed to link ground measurements to the satellite-based carbon flux estimates. Here, we report results of a study aimed at evaluating MODIS NPP/GPP products at six sites varying widely in climate, land use, and vegetation physiognomy. Comparisons were made for twenty-five 1 km2 cells at each site, with 8-day averages for GPP and an annual value for NPP. The validation data layers were made with a combination of ground measurements, relatively high resolution satellite data (Landsat Enhanced Thematic Mapper Plus at ∼30 m resolution), and process-based modeling. There was strong seasonality in the MODIS GPP at all sites, and mean NPP ranged from 80 g C m−2 yr−1 at an arctic tundra site to 550 g C m−2 yr−1 at a temperate deciduous forest site. There was not a consistent over- or underprediction of NPP across sites relative to the validation estimates. The closest agreements in NPP and GPP were at the temperate deciduous forest, arctic tundra, and boreal forest sites. There was moderate underestimation in the MODIS products at the agricultural field site, and strong overestimation at the desert grassland and at the dry coniferous forest sites. Analyses of specific inputs to the MODIS NPP/GPP algorithm – notably the fraction of photosynthetically active radiation absorbed by the vegetation canopy, the maximum light use efficiency (LUE), and the climate data – revealed the causes of the over- and underestimates. Suggestions for algorithm improvement include selectively altering values for maximum LUE (based on observations at eddy covariance flux towers) and parameters regulating autotrophic respiration.

Notes: There are two broad approaches to quantifying landscape C dynamics – by measuring changes in C stocks over time, or by measuring fluxes of C directly. However, these data may be patchy, and have gaps or biases. An alternative approach to generating C budgets has been to use process-based models, constructed to simulate the key processes involved in C exchange. However, the process of model building is arguably subjective, and parameters may be poorly defined. This paper demonstrates why data assimilation (DA) techniques – which combine stock and flux observations with a dynamic model – improve estimates of, and provide insights into, ecosystem carbon (C) exchanges. We use an ensemble Kalman filter (EnKF) to link a series of measurements with a simple box model of C transformations. Measurements were collected at a young ponderosa pine stand in central Oregon over a 3-year period, and include eddy flux and soil CO2 efflux data, litterfall collections, stem surveys, root and soil cores, and leaf area index data. The simple C model is a mass balance model with nine unknown parameters, tracking changes in C storage among five pools; foliar, wood and fine root pools in vegetation, and also fresh litter and soil organic matter (SOM) plus coarse woody debris pools. We nested the EnKF within an optimization routine to generate estimates from the data of the unknown parameters and the five initial conditions for the pools. The efficacy of the DA process can be judged by comparing the probability distributions of estimates produced with the EnKF analysis vs. those produced with reduced data or model alone. Using the model alone, estimated net ecosystem exchange of C (NEE)=−251±197 g C m−2 over the 3 years, compared with an estimate of −419±29 g C m−2 when all observations were assimilated into the model. The uncertainty on daily measurements of NEE via eddy fluxes was estimated at 0.5 g C m−2 day−1, but the uncertainty on assimilated estimates averaged 0.47 g C m−2 day−1, and only exceeded 0.5 g C m−2 day−1 on days where neither eddy flux nor soil efflux data were available. In generating C budgets, the assimilation process reduced the uncertainties associated with using data or model alone and the forecasts of NEE were statistically unbiased estimates. The results of the analysis emphasize the importance of time series as constraints. Occasional, rare measurements of stocks have limited use in constraining the estimates of other components of the C cycle. Long time series are particularly crucial for improving the analysis of pools with long time constants, such as SOM, woody biomass, and woody debris. Long-running forest stem surveys, and tree ring data, offer a rich resource that could be assimilated to provide an important constraint on C cycling of slow pools. For extending estimates of NEE across regions, DA can play a further important role, by assimilating remote-sensing data into the analysis of C cycles. We show, via sensitivity analysis, how assimilating an estimate of photosynthesis – which might be provided indirectly by remotely sensed data – improves the analysis of NEE.

Notes: We investigated variation in carbon stock in soils and detritus (forest floor and woody debris) in chronosequences that represent the range of forest types in the US Pacific Northwest. Stands range in age from 〈13 to 〉600 years. Soil carbon, to a depth of 100 cm, was highest in coastal Sitka spruce/western hemlock forests (36±10 kg C m−2) and lowest in semiarid ponderosa pine forests (7±10 kg C m−2). Forests distributed across the Cascade Mountains had intermediate values between 10 and 25 kg C m−2. Soil carbon stocks were best described as a linear function of net primary productivity (r2=0.52), annual precipitation (r2=0.51), and a power function of forest floor mean residence time (r2=0.67). The highest rates of soil and detritus carbon turnover were recorded on mesic sites of Douglas-fir/western hemlock forests in the Cascade Mountains with lower rates in wetter and drier habitats, similar to the pattern of site productivity. The relative contribution of soil and detritus carbon to total ecosystem carbon decreased as a negative exponential function of stand age to a value of ∼35% between 150 and 200 years across the forest types. These age-dependent trends in the portioning of carbon between biomass and necromass were not different among forest types. Model estimates of soil carbon storage based on decomposition of legacy carbon and carbon accumulation following stand-replacing disturbance showed that soil carbon storage reached an asymptote between 150 and 200 years, which has significant implications to modeling carbon dynamics of the temperate coniferous forests following a stand-replacing disturbance.

Notes: [Auszug] Temperate and boreal forests in the Northern Hemisphere cover an area of about 2 × 107 square kilometres and act as a substantial carbon sink (0.6–0.7 petagrams of carbon per year). Although forest expansion following agricultural abandonment is ...