Semiempirical modeling of abiotic and biotic factors controlling ecosystem respiration across eddy covariance sites

In this study we examined ecosystem respiration (R_ECO) data from 104 sites belonging to FLUXNET, the global network of eddy covariance flux measurements. The goal was to identify the main factors involved in the variability of R_ECO: temporally and between sites as affected by climate, vegetation structure and plant functional type (PFT) (evergreen needleleaf, grasslands, etc.). We demonstrated that a model using only climate drivers as predictors of R_ECO failed to describe part of the temporal variability in the data and that the dependency on gross primary production (GPP) needed to be included as an additional driver of R_ECO. The maximum seasonal leaf area index (LAI_MAX) had an additional effect that explained the spatial variability of reference respiration (the respiration at reference temperature T_ref=15 °C, without stimulation introduced by photosynthetic activity and without water limitations), with a statistically significant linear relationship (r²=0.52, P<0.001, n=104) even within each PFT. Besides LAI_MAX, we found that reference respiration may be explained partially by total soil carbon content (SoilC). For undisturbed temperate and boreal forests a negative control of total nitrogen deposition (N_depo) on reference respiration was also identified. We developed a new semiempirical model incorporating abiotic factors (climate), recent productivity (daily GPP), general site productivity and canopy structure (LAI_MAX) which performed well in predicting the spatio‐temporal variability of R_ECO, explaining >70% of the variance for most vegetation types. Exceptions include tropical and Mediterranean broadleaf forests and deciduous broadleaf forests. Part of the variability in respiration that could not be described by our model may be attributed to a series of factors, including phenology in deciduous broadleaf forests and management practices in grasslands and croplands.     

FLUXNET and modelling the global carbon cycle

Measurements of the net CO₂ flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO₂ source–sink patterns, CO₂ flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO₂ (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model‐data comparison. Flux measurements made over four vegetation types were used to calibrate the land‐surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land‐surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO₂ uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). This model is forced by satellite‐measured absorbed radiation and suggests that global net primary production (NPP) increased 6.2% over 1982–1999. Good agreement is found between global trends in NPP estimated by the PEM and a dynamic global vegetation model (DGVM), and between the DGVM and estimates of global NEE derived from a global inversion of atmospheric CO₂ measurements. Combining the PEM, DGVM, and inversion results suggests that CO₂ fertilization is playing a major role in current increases in NPP, with lesser impacts from increasing N deposition and growing season length. Both the PEM and the inversion identify the Amazon basin as a key region for the current net terrestrial CO₂ uptake (i.e. 33% of global NEE), as well as its interannual variability. The inversion's global NEE estimate of −1.2 Pg [C] yr⁻¹ for 1982–1995 is compatible with the PEM‐ and DGVM‐predicted trends in NPP. There is, thus, a convergence in understanding derived from process‐based models, remote‐sensing‐based observations, and inversion of atmospheric data. Future advances in field measurement techniques, including eddy covariance (particularly concerning the problem of night‐time fluxes in dense canopies and of advection or flow distortion over complex terrain), will result in improved constraints on land‐atmosphere CO₂ fluxes and the rigorous attribution of mechanisms to the current terrestrial net CO₂ uptake and its spatial and temporal heterogeneity. Global ecosystem models play a fundamental role in linking information derived from FLUXNET measurements to atmospheric CO₂ variability. A number of recommendations concerning FLUXNET data are made, including a request for more comprehensive site data (particularly historical information), more measurements in undisturbed ecosystems, and the systematic provision of error estimates. The greatest value of current FLUXNET data for global carbon cycle modelling is in evaluating process representations, rather than in providing an unbiased estimate of net CO₂ exchange.     

Microbial characteristics of soils on a latitudinal transect in Siberia

Soil microbial properties were studied from localities on a transect along the Yenisei River, Central Siberia. The 1000 km‐long transect, from 56°N to 68°N, passed through tundra, taiga and pine forest characteristic of Northern Russia. Soil microbial properties were characterized by dehydrogenase activity, microbial biomass, composition of microbial community (PLFAs), respiration rates, denitrification and N mineralization rates. Relationships between vegetation, latitude, soil quality (pH, texture), soil organic carbon (SOC) and the microbial properties were examined using multivariate analysis. In addition, the temperature responses of microbial growth (net growth rate) and activity (soil respiration rate) were tested by laboratory experiments. The major conclusions of the study are as follows: 1. Multivariate analysis of the data revealed significant differences in microbial activity. SOC clay content was positively related to clay content. Soil texture and SOC exhibited the dominant effect on soil microbial parameters, while the vegetation and climatic effects (expressed as a function of latitude) were weaker but still significant. The effect of vegetation cover is linked to SOC quality, which can control soil microbial activity. 2. When compared to fine‐textured soils, coarse‐textured soils have (i) proportionally more SOC bound in microbial biomass, which might result in higher susceptibility of SOC transformation to fluctuation of environmental factors, and (ii) low mineralization potential, but with a substantial part of the consumed C being transformed to microbial products. 3. The soil microbial community from the northernmost study region located within the permafrost zone appears to be adapted to cold conditions. As a result, microbial net growth rate became negative when temperature rose above 5 °C and C mineralization then exceeded C accumulation.     

Oxygen consumption of the aquatic leaf beetles Macroplea mutica and Macroplea appendiculata is low and not influenced by salinity

Leaf beetles of the genus Macroplea live permanently under water. Species‐specific preferences for either freshwater or brackish water are available in the literature. To detect potential physiological differences, the oxygen consumption of Macroplea mutica and Macroplea appendiculata from habitats with differing salinities is measured at two different salinities (0 and 10). The specific oxygen consumption does not depend on oxygen saturation of the water (values in the approximate range of 25–100% occur during the experiments). There is no difference between species or sampling locations. Similarly, the salinity during the measurements does not affect the oxygen consumption of the beetles, either when compared as salinity per se (0 versus 10), or when classified as home salinity or atypical salinity. Comparisons with other chrysomelid beetles and aquatic insects (using available published data) reveal that the two Macroplea species have relatively low metabolic rates. This finding is discussed in the light of activity patterns and morphology, especially the reduction of flight muscles, which comprise a highly metabolically active tissue.     

CO2 fertilization in temperate FACE experiments not representative of boreal and tropical forests

Results from free-air CO₂ enrichment (FACE) experiments in temperate climates indicate that the response of forest net primary productivity (NPP) to elevated CO₂ might be highly conserved across a broad range of productivities. In this study, we show that the LPJ-GUESS dynamic vegetation model reproduces the magnitude of the NPP enhancement at temperate forest FACE experiments. A global application of the model suggests that the response found in the experiments might also be representative of the average response of forests globally. However, the predicted NPP enhancement in tropical forests is more than twice as high as in boreal forests, suggesting that currently available FACE results are not applicable to these ecosystems. The modeled geographic pattern is to a large extent driven by the temperature dependence of the relative affinities of the primary assimilation enzyme (Rubisco) for CO₂ and O₂.     

Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation

The measured net ecosystem exchange (NEE) of CO₂ between the ecosystem and the atmosphere reflects the balance between gross CO₂ assimilation [gross primary production (GPP)] and ecosystem respiration (R_eco). For understanding the mechanistic responses of ecosystem processes to environmental change it is important to separate these two flux components. Two approaches are conventionally used: (1) respiration measurements made at night are extrapolated to the daytime or (2) light–response curves are fit to daytime NEE measurements and respiration is estimated from the intercept of the ordinate, which avoids the use of potentially problematic nighttime data. We demonstrate that this approach is subject to biases if the effect of vapor pressure deficit (VPD) modifying the light response is not included. We introduce an algorithm for NEE partitioning that uses a hyperbolic light response curve fit to daytime NEE, modified to account for the temperature sensitivity of respiration and the VPD limitation of photosynthesis. Including the VPD dependency strongly improved the model's ability to reproduce the asymmetric diurnal cycle during periods with high VPD, and enhances the reliability of R_eco estimates given that the reduction of GPP by VPD may be otherwise incorrectly attributed to higher R_eco. Results from this improved algorithm are compared against estimates based on the conventional nighttime approach. The comparison demonstrates that the uncertainty arising from systematic errors dominates the overall uncertainty of annual sums (median absolute deviation of GPP: 47 g C m^?2 yr^?1), while errors arising from the random error (median absolute deviation: ～2 g C m^?2 yr^?1) are negligible. Despite site‐specific differences between the methods, overall patterns remain robust, adding confidence to statistical studies based on the FLUXNET database. In particular, we show that the strong correlation between GPP and R_eco is not spurious but holds true when quasi‐independent, i.e. daytime and nighttime based estimates are compared.     

Assimilation exceeds respiration sensitivity to drought: A FLUXNET synthesis

The intensification of the hydrological cycle, with an observed and modeled increase in drought incidence and severity, underscores the need to quantify drought effects on carbon cycling and the terrestrial sink. FLUXNET, a global network of eddy covariance towers, provides dense data streams of meteorological data, and through flux partitioning and gap filling algorithms, estimates of net ecosystem productivity (F_NEP), gross ecosystem productivity (P), and ecosystem respiration (R). We analyzed the functional relationship of these three carbon fluxes relative to evaporative fraction (EF), an index of drought and site water status, using monthly data records from 238 micrometeorological tower sites distributed globally across 11 biomes. The analysis was based on relative anomalies of both EF and carbon fluxes and focused on drought episodes by biome and climatic season. Globally P was ≈50% more sensitive to a drought event than R. Network‐wide drought‐induced decreases in carbon flux averaged ?16.6 and ?9.3 g C m^?2 month^?1 for P and R, i.e., drought events induced a net decline in the terrestrial sink. However, in evergreen forests and wetlands drought was coincident with an increase in P or R during parts of the growing season. The most robust relationships between carbon flux and EF occurred during climatic spring for F_NEP and in climatic summer for P and R. Upscaling flux sensitivities to a global map showed that spatial patterns for all three carbon fluxes were linked to the distribution of croplands. Agricultural areas exhibited the highest sensitivity whereas the tropical region had minimal sensitivity to drought. Combining gridded flux sensitivities with their uncertainties and the spatial grid of FLUXNET revealed that a more robust quantification of carbon flux response to drought requires additional towers in all biomes of Africa and Asia as well as in the cropland, shrubland, savannah, and wetland biomes globally.