Bart Kruijt

Carbon dioxide transfer over a Central Amazonian rain forest

Tropical rain forests are among the most important and least monitored of terrestrial ecosystems. In recent years, their influence on atmospheric concentrations of carbon dioxide and water vapor has become the subject of much speculation. Here we present results from a yearlong study of CO2 fluxes at a tropical forest in central Amazonia, using the micrometeorological technique of eddy covariance. The diurnal cycle of CO2 flux was consistent with previous short-term studies in tropical rain forests, implying that the Amazonian rain forest shows a fair degree of spatial uniformity in bulk ecophysiological characteristics. Typical peak daytime photosynthesis rates were 24–28 μmol CO2 m−2 s−1, and respiration rates were 6–8 μmol CO2 m−2 s−1. There was significant seasonality in peak photosynthesis over the year, which appeared strongly correlated with soil moisture content. On the other hand, there was no evidence of strong seasonality in soil respiration. Central Amazonia has only a short, 3-month dry season, not atypical of tropical rain forest, and it is therefore likely that large areas of Amazonia exhibit significant seasonality in photosynthetic capacity. The gross primary production was calculated to be 30 t C ha−1 yr−1. An analysis of data quality is included in the appendix.

Respiration from a tropical forest ecosystem: partitioning of sources and low carbon use efficiency

Understanding how tropical forest carbon balance will respond to global change requires knowledge of individual heterotrophic and autotrophic respiratory sources, together with factors that control respiratory variability. We measured leaf, live wood, and soil respiration, along with additional environmental factors over a 1-yr period in a Central Amazon terra firme forest. Scaling these fluxes to the ecosystem, and combining our data with results from other studies, we estimated an average total ecosystem respiration (Reco) of 7.8 μmol·m−2·s−1. Average estimates (per unit ground area) for leaf, wood, soil, total heterotrophic, and total autotrophic respiration were 2.6, 1.1, 3.2, 5.6, and 2.2 μmol·m−2·s−1, respectively. Comparing autotrophic respiration with net primary production (NPP) estimates indicated that only ∼30% of carbon assimilated in photosynthesis was used to construct new tissues, with the remaining 70% being respired back to the atmosphere as autotrophic respiration. This low ecosystem carbon use efficiency (CUE) differs considerably from the relatively constant CUE of ∼0.5 found for temperate forests. Our Reco estimate was comparable to the above-canopy flux (Fac) from eddy covariance during defined sustained high turbulence conditions (when presumably Fac = Reco) of 8.4 (95% ci = 7.5– 9.4). Multiple regression analysis demonstrated that ∼50% of the nighttime variability in Fac was accounted for by friction velocity (u*, a measure of turbulence) variables. After accounting for u* variability, mean Fac varied significantly with seasonal and daily changes in precipitation. A seasonal increase in precipitation resulted in a decrease in Fac, similar to our soil respiration response to moisture. The effect of daily changes in precipitation was complex: precipitation after a dry period resulted in a large increase in Fac, whereas additional precipitation after a rainy period had little effect. This response was similar to that of surface litter (coarse and fine), where respiration is greatly reduced when moisture is limiting, but increases markedly and quickly saturates with an increase in moisture.

Patterns of water and heat flux across a biome gradient from tropical forest to savanna in Brazil

[1] We investigated the seasonal patterns of water vapor and sensible heat flux along a tropical biome gradient from forest to savanna. We analyzed data from a network of flux towers in Brazil that were operated within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). These tower sites included tropical humid and semideciduous forest, transitional forest, floodplain (with physiognomies of cerrado), and cerrado sensu stricto. The mean annual sensible heat flux at all sites ranged from 20 to 38 Wm 2 , and was generally reduced in the wet season and increased in the late dry season, coincident with seasonal variations of net radiation and soil moisture. The sites were easily divisible into two functional groups based on the seasonality of evaporation: tropical forest and savanna. At sites with an annual precipitation above 1900 mm and a dry season length less than 4 months (Manaus, Santarem and Rondonia), evaporation rates increased in the dry season, coincident with increased radiation. Evaporation rates were as high as 4.0 mm d 1 in these evergreen or semidecidous forests. In contrast, ecosystems with precipitation less than 1700 mm and a longer dry season (Mato Grosso, Tocantins

ECOLOGICAL RESEARCH IN THE LARGE-SCALE BIOSPHERE– ATMOSPHERE EXPERIMENT IN AMAZONIA: EARLY RESULTS

The Large-scale Biosphere-Atmosphere Experiment in Amazonia (LBA) is a multinational, interdisciplinary research program led by Brazil. Ecological studies in LBA focus on how tropical forest conversion, regrowth, and selective logging influence carbon storage, nutrient dynamics, trace gas fluxes, and the prospect for sustainable land use in the Amazon region. Early results from ecological studies within LBA emphasize the var- iability within the vast Amazon region and the profound effects that land-use and land- cover changes are having on that landscape. The predominant land cover of the Amazon region is evergreen forest; nonetheless, LBA studies have observed strong seasonal patterns in gross primary production, ecosystem respiration, and net ecosystem exchange, as well as phenology and tree growth. The seasonal patterns vary spatially and interannually and evidence suggests that these patterns are driven not only by variations in weather but also by innate biological rhythms of the forest species. Rapid rates of deforestation have marked the forests of the Amazon region over the past three decades. Evidence from ground-based surveys and remote sensing show that substantial areas of forest are being degraded by logging activities and through the collapse of forest edges. Because forest edges and logged forests are susceptible to fire, positive feedback cycles of forest degradation may be initiated by land-use-change events. LBA studies indicate that cleared lands in the Amazon, once released from cultivation or pasture usage, regenerate biomass rapidly. However, the pace of biomass accumulation is dependent upon past land use and the depletion of nutrients by unsustainable land-management practices. The challenge for ongoing research within LBA is to integrate the recognition of diverse patterns and processes into general models for prediction of regional ecosystem function.

THE ROBUSTNESS OF EDDY CORRELATION FLUXES FOR AMAZON RAIN FOREST CONDITIONS

We analyzed errors and uncertainties in time-integrated eddy correlation data for sites in the Amazon. A well-known source of potential error in eddy correlation is through possible advective losses of CO2 emissions during calm nights. There are also questions related to the treatment of low frequencies, non-horizontal flow, and uncertainties in, e.g., corrections for tube delay and frequency loss, as well as the effect of missing data. In this study, we systematically explore these issues for the specific situation of flux mea- surements at two Amazon forest sites. Results indicate that, for this specific environment with tall forest and tall towers, errors and uncertainties caused by data spikes, delay cor- rections, and high-frequency loss are small (,3% on an annual basis). However, sensitivities to the treatment of low frequencies and non-horizontal flow can be large, especially if the landscape is not homogeneous. Given that there is no consensus on methodology here, this represents an uncertainty of 10-25% on annual total carbon uptake. The other large un- certainty is clearly in the nighttime fluxes. Two different ways to evaluate the validity of these fluxes resulted in at least a 100% difference of annual totals. Finally, we show that uncertainty (standard errors) associated with data gaps can be reduced to ,0.5 Mg·ha 21 ·yr 21 if data are covering at least half of the time, with random spread. Overall uncertainty, on annual CO2 fluxes, excluding the nighttime dilemma, is estimated at 612% (central Amazon site) to 632% (southwest Amazon site). Additionally, the nighttime uncertainty is of similar magnitude as the time-integrated fluxes themselves.

NOCTURNAL ACCUMULATION OF CO2 UNDERNEATH A TROPICAL FOREST CANOPY ALONG A TOPOGRAPHICAL GRADIENT

Flux measurements of carbon dioxide and water vapor above tropical rain forests are often difficult to interpret because the terrain is usually complex. This complexity induces heterogeneity in the surface but also affects lateral movement of carbon dioxide (CO2) not readily detected by the eddy covariance systems. This study describes such variability using measurements of CO2 along vertical profiles and along a toposequence in a tropical rain forest near Manaus, Brazil. Seasonal and diurnal variation was recorded, with atmospheric CO2 concentration maxima around dawn, generally higher CO2 build-up in the dry season and stronger daytime CO2 drawdown in the wet season. This variation was reflected all along the toposequence, but the slope and valley bottom accumulated clearly more CO2 than the plateaus, depending on atmospheric stability. Particularly during stable nights, accumulation was along lines of equal altitude, suggesting that large amounts of CO2 are stored in the valleys of the landscape. Flushing of this store only occurs during mid-morning, when stored CO2 may well be partly transported back to the plateaus. It is clear that, for proper interpretation of tower fluxes in such complex and actively respiring terrain, the horizontal variability of storage needs to be taken into account not only during the night but also during the mornings.

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Abstract Understanding the processes that determine above‐ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin‐wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs.

After more than a decade of soil moisture deficit, tropical rainforest trees maintain photosynthetic capacity, despite increased leaf respiration.

Abstract Determining climate change feedbacks from tropical rainforests requires an understanding of how carbon gain through photosynthesis and loss through respiration will be altered. One of the key changes that tropical rainforests may experience under future climate change scenarios is reduced soil moisture availability. In this study we examine if and how both leaf photosynthesis and leaf dark respiration acclimate following more than 12 years of experimental soil moisture deficit, via a through‐fall exclusion experiment (TFE) in an eastern Amazonian rainforest. We find that experimentally drought‐stressed trees and taxa maintain the same maximum leaf photosynthetic capacity as trees in corresponding control forest, independent of their susceptibility to drought‐induced mortality. We hypothesize that photosynthetic capacity is maintained across all treatments and taxa to take advantage of short‐lived periods of high moisture availability, when stomatal conductance (g s) and photosynthesis can increase rapidly, potentially compensating for reduced assimilate supply at other times. Average leaf dark respiration (R d) was elevated in the TFE‐treated forest trees relative to the control by 28.2 ± 2.8% (mean ± one standard error). This mean R d value was dominated by a 48.5 ± 3.6% increase in the R d of drought‐sensitive taxa, and likely reflects the need for additional metabolic support required for stress‐related repair, and hydraulic or osmotic maintenance processes. Following soil moisture deficit that is maintained for several years, our data suggest that changes in respiration drive greater shifts in the canopy carbon balance, than changes in photosynthetic capacity.

Forest edges and the soil-vegetation-atmosphere interaction at the landscape scale: The state of affairs

Although the soil-vegetation-atmosphere exchange of momentum and heat is fairly well understood for many types of homogeneous surfaces, the disturbances created by tran sitions of one surface type to another remain to be analysed more fully. This is especially true for the impact which a large transition such as the forest edge has on the average fluxes in a small-scale heterogeneous landscape with forest. Recently acquired experimental evidence appears to some extent contradictory and at variance with conventional concepts.

Ecosystem Carbon Fluxes and Amazonian Forest Metabolism

Long-term measurements of ecosystem-atmosphere exchanges of carbon, water, and energy, via eddy flux towers, give insight into three key questions about Amazonian forest function. First, what is the carbon balance of Amazon forests? Some towers give accurate site-specific carbon balances, as validated by independent methods, but decisive resolution of the large-scale question will also require integration of remote sensing techniques (to detect and encompass the distribution of naturally induced disturbance states across the landscape of old growth forests) with eddy flux process studies (to characterize the association between carbon balance and forest disturbance states). Second, what is the seasonality of ecosystem metabolism in Amazonian forests? Models have historically simulated dry season declines in photosynthetic metabolism, a consequence of modeled water limitation. Tower sites in equatorial Amazonian forests, however, show that photosynthetic metabolism increases during dry seasons (“green up”), perhaps because deep roots buffer trees from dry season water stress, while phenological rhythms trigger leaf flush, associated with increased solar irradiance. Third, how does ecosystem metabolism vary across biome types and land use patterns? As dry season length increases from equatorial forest, to drier southern forests, to savanna, fluxes show seasonal patterns consistent with increasing water stress, including a switch from dry season green up to “brown down.” Land use change in forest ecosystems removes deep roots, artificially inducing the same trend toward brown down. In the final part, this review suggests that eddy tower network and satellitebased insights into seasonal responses provide a model for detecting responses to extreme interannual climate variations that can test whether forests are vulnerable to model-simulated Amazonian forest collapse under climate change.