Models of climate change predict close coupling between increases in aridity and conversion of Amazonian forests to savanna. Here we assess the vulnerability and resilience of Amazonian vegetation to climate change by analyzing observed climate-vegetation relationships using climate data, observed vegetation distributions, and evapotranspiration rates inferred from eddy flux data. We found that drought frequency is an excellent predictor of the forest-savanna boundary, indicating the key role of extreme climatic events for inducing vegetation change, and highlighting particularly vulnerable regions of Amazônia.

We assess errors in soil respiration fluxes of CO2 obtained using the closed dynamic chamber method. Particular attention is given to small pressure gradients between the chamber headspace and the external environment that may induce mass flow of soil air, leading to overestimation of soil respiration. These pressure gradients develop as air movement creates a Venturi effect at the vent that is designed to insure pressure equilibration, leading to aspiration of air from within the chamber. During field experiments at the Harvard Forest, the Venturi effect produced pressure gradients of approximately 1 Pa per 1 m s−1 for a chamber sealed to an impermeable plate, but no pressure gradient was observed in an identical system deployed on the forest soil. Mass flow of soil air compensated for the wind-driven pressure gradients, and increases in CO2 fluxes exceeding a factor of 2 were observed in response to wind events even under a dense forest canopy. The high porosity of forest soils allows pressure artifacts induced by winds or by sampling flows to perturb the diffusive flux from soils, potentially affecting virtually all chamber methods. Associated errors in soil respiration measurements must be addressed through chamber design and evaluation.

Most satellites provide, at best, a single daily snapshot of vegetation and, at worst, these snapshots may be separated by periods of many days when the ground was obscured by cloud cover. Since vegetation carbon exchange can be very dynamic on diurnal and day-to-day timescales, the limited temporal resolution of satellite data is a potential limitation in the use of these data to estimate integrated CO2 exchange between vegetation and the atmosphere. Our objective in this study was to determine whether consistent relationships exist between midday carbon flux on clear days and daily or 8-day mean values. CO2 flux data were obtained from eight sites, covering a wide range of vegetation types, which are part of the AmeriFlux system. Midday gross CO2 exchange was highly correlated with both daily and 8-day mean gross CO2 exchange and these relationships were consistent across all the vegetation types. In addition, it did not make any difference whether the midday data were derived from the AM or PM satellite overpass times, indicating that midday depression of photosynthesis was not a significant factor in these relationships. Inclusion of cloudy days in the 8-day means also did not affect the relationships relative to single clear days. Although there was a relationship between photosynthetic rates and photosynthetically active radiation (PAR) for half hour data, this relationship tended to saturate at PAR values less than half of full sun and for many of the sites the relationship between daily total photosynthesis and PAR was very weak. Consequently, cloudy conditions had less effect on daily gross CO2 exchange than would have been expected. Conversely, the saturation of photosynthesis at moderate PAR values resulted in considerable variation in light use efficiency (LUE). LUE was higher for daily and 8-day means than it was at midday on clear days and the correlation between midday and 8-day mean LUE was relatively weak. Although these results suggest that it may not be possible to estimate 8-day mean LUE reliably from satellite data, LUE models may still be useful for estimation of midday values of gross CO2 exchange which could then be related to longer term means of CO2 exchange.

The δ13C values of atmospheric carbon dioxide (CO2) can be used to partition global patterns of CO2 source/sink relationships among terrestrial and oceanic ecosystems using the inversion technique. This approach is very sensitive to estimates of photosynthetic 13C discrimination by terrestrial vegetation (ΔA), and depends on δ13C values of respired CO2 fluxes (δ13CR). Here we show that by combining two independent data streams – the stable isotope ratios of atmospheric CO2 and eddy-covariance CO2 flux measurements – canopy scale estimates of ΔA can be successfully derived in terrestrial ecosystems. We also present the first weekly dataset of seasonal variations in δ13CR from dominant forest ecosystems in the United States between 2001 and 2003. Our observations indicate considerable summer-time variation in the weekly value of δ13CR within coniferous forests (4.0‰ and 5.4‰ at Wind River Canopy Crane Research Facility and Howland Forest, respectively, between May and September). The monthly mean values of δ13CR showed a smaller range (2–3‰), which appeared to significantly correlate with soil water availability. Values of δ13CR were less variable during the growing season at the deciduous forest (Harvard Forest). We suggest that the negative correlation between δ13CR and soil moisture content observed in the two coniferous forests should represent a general ecosystem response to the changes in the distribution of water resources because of climate change. Shifts in δ13CR and ΔA could be of sufficient magnitude globally to impact partitioning calculations of CO2 sinks between oceanic and terrestrial compartments.

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 NPPIGPP 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 30m resolution), and process-based modeling. There was strong seasonality in the MODIS GPP at all sites, and mean NPP ranged from 80g Cm-2 yr-1 at an arctic tundra site to 550g Cm-2yr-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.

We tested the hypothesis that the date of the onset of net carbon uptake by temperate deciduous forest canopies corresponds with the time when the mean daily soil temperature equals the mean annual air temperature. The hypothesis was tested using over 30 site-years of data from 12 field sites where CO2 exchange is being measured continuously with the eddy covariance method. The sites spanned the geographic range of Europe, North America and Asia and spanned a climate space of 16°C in mean annual temperature. The tested phenology rule was robust and worked well over a 75 day range of the initiation of carbon uptake, starting as early as day 88 near Ione, California to as late as day 147 near Takayama, Japan. Overall, we observed that 64% of variance in the timing when net carbon uptake started was explained by the date when soil temperature matched the mean annual air temperature. We also observed a strong correlation between mean annual air temperature and the day that a deciduous forest starts to be a carbon sink. Consequently we are able to provide a simple phenological rule that can be implemented in regional carbon balance models and be assessed with soil and temperature outputs produced by climate and weather models.

Errors in atmospheric transport of tracers lead to errors in estimates of tracer fluxes based upon concentration observations. Typically, such “inverse” methods either neglect transport errors or only assess their effects roughly. We describe a method to quantitatively account for transport errors by incorporating uncertainties in winds into stochastic motions of air parcels. The magnitude of errors in wind fields, as well as their spatiotemporal covariances, are determined by direct comparison of assimilated winds to radiosonde observations. These statistics of transport errors are propagated through stochastic motions of air parcels in a Lagrangian model (STILT). We illustrate this method by conducting an inverse analysis using simulated CO2 observations over the continent and examine the effect of transport errors on estimates of regional terrestrial carbon fluxes. The inverse analysis demonstrates that transport errors can cause significantly biased estimates. We show that the proposed method properly accounts for these errors.

We recommend an automated statistical method (Moving Point Test, or MPT) to determine the friction velocity (u*) thresholds in nighttime eddy flux filtering. Our intention is to make the determination of the u* thresholds objective and reproducible and to keep flux treatment consistent over time and across sites. In developing the MPT method, we recognize that both ecosystem respiration and u* exhibit diurnal and seasonal cycles and there are potential correlative changes between them, which must be removed before u* can be used as a filter criterion. MPT uses an iterative approach to simultaneously determine a valid temperature response function, which is used to normalize nighttime flux measurements, and identify u* thresholds based on the normalized fluxes. Tests show that MPT works well for a variety of scenarios and vegetation types. We also recommend that in order to increase the reliability of nighttime flux filters, a detailed measurement of mean CO2 concentration profiles need to be employed to calculate canopy storage changes accurately. Preferably, multiple profiles at different locations within the nighttime flux footprint should be used so that volume-averaged storage changes can be made. In addition, efforts should be made to minimize measurement gaps in summer nights as much as possible because of the short-time duration and frequent calm conditions, which greatly limit the amount of reliable data. We emphasize that the MPT method is not meant to be a final solution to the nighttime flux issue. Continuous theoretical and experimental researches are still needed to overcome the challenges in measuring nighttime fluxes accurately. # 2004 Elsevier B.V. All rights reserved.

A CO2 eddy flux tower study has recently reported that an old-growth stand of seasonally moist tropical evergreen forest in Santarém, Brazil, maintained high gross primary production (GPP) during the dry seasons [Saleska, S. R., Miller, S. D., Matross, D. M., Goulden, M. L., Wofsy, S. C., da Rocha, H. R., de Camargo, P. B., Crill, P., Daube, B. C., de Freitas, H. C., Hutyra, L., Keller, M., Kirchhoff, V., Menton, M., Munger, J. W., Pyle, E. H., Rice, A. H., & Silva, H. (2003). Carbon in amazon forests: Unexpected seasonal fluxes and disturbance-induced losses. Science, 302, 1554–1557]. It was proposed that seasonally moist tropical evergreen forests have evolved two adaptive mechanisms in an environment with strong seasonal variations of light and water: deep roots system for access to water in deep soils and leaf phenology for access to light. Identifying tropical forests with these adaptive mechanisms could substantially improve our capacity of modeling the seasonal dynamics of carbon and water fluxes in the tropical zone. In this paper, we have analyzed multi-year satellite images from the VEGETATION (VGT) sensor onboard the SPOT-4 satellite (4/1998–12/2002) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite (2000–2003). We reported temporal analyses of vegetation indices and simulations of the satellite-based vegetation photosynthesis model (VPM). The Enhanced Vegetation Index (EVI) identified subtle changes in the seasonal dynamics of leaf phenology (leaf emergence, leaf aging and leaf fall) in the forest, as suggested by the leaf litterfall data. The land surface water index (LSWI) indicated that the forest experienced no water stress in the dry seasons of 1998–2002. The VPM model, which uses EVI, LSWI and site-specific climate data (air temperature and photosynthetically active radiation, PAR) for 2001–2002, predicted high GPP in the late dry seasons, consistent with observed high evapotranspiration and estimated GPP from the CO2 eddy flux tower.