The eddy covariance technique ascertains the exchange rate of CO2 across the interface between the atmosphere and a plant canopy by measuring the covariance between fluctuations in vertical wind velocity and CO2 mixing ratio. Two decades ago, the method was employed to study CO2 exchange of agricultural crops under ideal conditions during short field campaigns. During the past decade the eddy covariance method has emerged as an important tool for evaluating fluxes of carbon dioxide between terrestrial ecosystems and the atmosphere over the course of a year, and more. At present, the method is being applied in a nearly continuous mode to study carbon dioxide and water vapor exchange at over a hundred and eighty field sites, worldwide. The objective of this review is to assess the eddy covariance method as it is being applied by the global change community on increasingly longer time scales and over less than ideal surfaces.

The eddy covariance method is most accurate when the atmospheric conditions (wind, temperature, humidity, CO2) are steady, the underlying vegetation is homogeneous and it is situated on flat terrain for an extended distance upwind. When the eddy covariance method is applied over natural and complex landscapes or during atmospheric conditions that vary with time, the quantification of CO2 exchange between the biosphere and atmosphere must include measurements of atmospheric storage, flux divergence and advection.

Averaging CO2 flux measurements over long periods (days to year) reduces random sampling error to relatively small values. Unfortunately, data gaps are inevitable when constructing long data records. Data gaps are generally filled with values produced from statistical and empirical models to produce daily and annual sums of CO2 exchange. Filling data gaps with empirical estimates do not introduce significant bias errors because the empirical algorithms are derived from large statistical populations. On the other hand, flux measurement errors can be biased at night when winds are light and intermittent. Nighttime bias errors tend to produce an underestimate in the measurement of ecosystem respiration.

Despite the sources of errors associated with long-term eddy flux measurements, many investigators are producing defensible estimates of annual carbon exchange. When measurements come from nearly ideal sites the error bound on the net annual exchange of CO2 is less than ±50 g C m−2 yr−1. Additional confidence in long-term measurements is growing because investigators are producing values of net ecosystem productivity that are converging with independent values produced by measuring changes in biomass and soil carbon, as long as the biomass inventory studies are conducted over multiple years.

/pdf/assessing-the-eddy-covariance-technique-for-evaluating-38dltwlqrv.pdf

Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: past, present and future

Improvements to a MODIS global terrestrial evapotranspiration algorithm

The Moderate Resolution Spectroradiometer (MODIS) sensor has provided near real-time estimates of gross primary production (GPP) since March 2000. We compare four years (2000 to 2003) of satellite-based calculations of GPP with tower eddy CO2 flux-based estimates across diverse land cover types and climate regimes. We examine the potential error contributions from meteorology, leaf area index (LAI)/fPAR, and land cover. The error between annual GPP computed from NASA's Data Assimilation Office's (DAO) and tower-based meteorology is 28%, indicating that NASA's DAO global meteorology plays an important role in the accuracy of the GPP algorithm. Approximately 62% of MOD15-based estimates of LAI were within the estimates based on field optical measurements, although remaining values overestimated site values. Land cover presented the fewest errors, with most errors within the forest classes, reducing potential error. Tower-based and MODIS estimates of annual GPP compare favorably for most biomes, although MODIS GPP overestimates tower-based calculations by 20%-30%. Seasonally, summer estimates of MODIS GPP are closest to tower data, and spring estimates are the worst, most likely the result of the relatively rapid onset of leaf-out. The results of this study indicate, however, that the current MODIS GPP algorithm shows reasonable spatial patterns and temporal variability across a diverse range of biomes and climate regimes. So, while continued efforts are needed to isolate particular problems in specific biomes, we are optimistic about the general quality of these data, and continuation of the MOD17 GPP product will likely provide a key component of global terrestrial ecosystem analysis, providing continuous weekly measurements of global vegetation production

/pdf/evaluation-of-remote-sensing-based-terrestrial-productivity-4cnz02vepn.pdf

Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations

https://www.fs.fed.us/pnw/pubs/journals/pnw_2006_turner002.pdf

Evaluation of MODIS NPP and GPP products across multiple biomes.

Forest development following stand-replacing disturbance influences a variety of ecosystem processes including carbon exchange with the atmosphere. On a series of ponderosa pine (Pinius ponderosa var. Laws.) stands ranging from 9 to> 300 years in central Oregon, USA, we used biological measurements to estimate carbon storage in vegetation and soil pools, net primary productivity (NPP) and net ecosystem productivity (NEP) to examine variation with stand age. Measurements were made on plots representing four age classes with three replications: initiation (I, 9–23 years), young (Y, 56–89 years), mature (M, 95–106 years), and old (O, 190–316 years) stands typical of the forest type in the region. Net ecosystem productivity was lowest in the I stands (−124 g C m−2 yr−1), moderate in Y stands (118 g C m−2 yr−1), highest in M stands (170 g C m−2 yr−1), and low in the O stands (35 g C m−2 yr−1). Net primary productivity followed similar trends, but did not decline as much in the O stands. The ratio of fine root to foliage carbon was highest in the I stands, which is likely necessary for establishment in the semiarid environment, where forests are subject to drought during the growing season (300–800 mm precipitation per year). Carbon storage in live mass was the highest in the O stands (mean 17.6 kg C m−2). Total ecosystem carbon storage and the fraction of ecosystem carbon in aboveground wood mass increased rapidly until 150–200 years, and did not decline in older stands. Forest inventory data on 950 ponderosa pine plots in Oregon show that the greatest proportion of plots exist in stands ∼ 100 years old, indicating that a majority of stands are approaching maximum carbon storage and net carbon uptake. Our data suggests that NEP averages ∼ 70 g C m−2 year−1 for ponderosa pine forests in Oregon. About 85% of the total carbon storage in biomass on the survey plots exists in stands greater than 100 years, which has implications for managing forests for carbon sequestration. To investigate variation in carbon storage and fluxes with disturbance, simulation with process models requires a dynamic parameterization for biomass allocation that depends on stand age, and should include a representation of competition between multiple plant functional types for space, water, and nutrients.

Changes in carbon storage and fluxes in a chronosequence of ponderosa pine

https://www7.nau.edu/mpcer/direnet/publications/publications_a/files/Anthoni_PM_Unsworth_MH_etal_Seasonal_differences.pdf

Darrin Moore

Papers

Seasonal differences in carbon and water vapor exchange in young and old-growth ponderosa pine ecosystems