Measurements Of Carbon Exchange Research Articles

Development and Optimization of a Chamber System Applied to Maize Net Ecosystem Carbon Exchange Measurements

Net ecosystem carbon exchange (NEE) in agricultural land represents a significant source of global greenhouse gas (GHG) emissions. While there are various tools for measuring NEE in agricultural fields, the chamber method remains the sole tool at the plot scale. In this research, we evaluated the NEE of maize plants at the nodulation stage using the flow-through chamber method. Many existing flow-through chamber systems directly introduce gases, leading to collisions with plants and subsequent turbulence inside the chamber. Turbulence can extend the time required to achieve a steady state. We modified the traditional flow-through chamber design to minimize turbulence in the measurement zone. Our modifications were validated by modeling the chamber and maize plants and by conducting fluid simulation experiments. In the analysis of our comparative field measurements between the two chamber designs, the use of the improved system notably shortened the time required to reach the steady state, increased the measurement frequency, and reduced the influence of changing environmental factors on the readings. Enhancing the measurement frequency is crucial for ensuring long-term accuracy. By reducing turbulence in the chamber, we anticipate improvements in the precision of NEE measurements in agricultural research, which could significantly contribute to an accurate assessment of the global carbon cycle.

Biocrust carbon exchange varies with crust type and time on Chihuahuan Desert gypsum soils.

In dryland systems, biological soil crusts (biocrusts) can occupy large areas of plant interspaces, where they fix carbon following rain. Although distinct biocrust types contain different dominant photoautotrophs, few studies to date have documented carbon exchange over time from various biocrust types. This is especially true for gypsum soils. Our objective was to assess the carbon exchange of biocrust types established at the world's largest gypsum dune field at White Sands National Park. We sampled five different biocrust types from a sand sheet location in three different years and seasons (summer 2020, fall 2021, and winter 2022) for carbon exchange measurements in controlled lab conditions. Biocrusts were rehydrated to full saturation and light incubated for 30 min, 2, 6, 12, 24, and 36 h. Samples were then subject to a 12-point light regime with a LI-6400XT photosynthesis system to determine carbon exchange. Biocrust carbon exchange values differed by biocrust type, by incubation time since wetting, and by date of field sampling. Lichens and mosses had higher gross and net carbon fixation rates than dark and light cyanobacterial crusts. High respiration rates were found after 0.5 h and 2 h incubation times as communities recovered from desiccation, leveling off after 6 h incubation. Net carbon fixation of all types increased with longer incubation time, primarily as a result of decreasing respiration, which suggests rapid recovery of biocrust photosynthesis across types. However, net carbon fixation rates varied from year to year, likely as a product of time since the last rain event and environmental conditions preceding collection, with moss crusts being most sensitive to environmental stress at our study sites. Given the complexity of patterns discovered in our study, it is especially important to consider a multitude of factors when comparing biocrust carbon exchange rates across studies. Understanding the dynamics of biocrust carbon fixation in distinct crust types will enable greater precision of carbon cycling models and improved forecasting of impacts of global climate change on dryland carbon cycling and ecosystem functioning.

Methane and Carbon Dioxide Fluxes in a Temperate Tidal Salt Marsh: Comparisons Between Plot and Ecosystem Measurements

AbstractTidal wetlands are comprised of complex interdependent pathways where measurements of carbon exchange are often scale dependent. Common data collection methods (i.e., chambers and eddy covariance) are inherently constrained to different spatial and temporal scales which could generate biased information for applications of carbon accounting, identifying functional relationships and predicting future responses to climate change. Consequently, it is needed to systematically evaluate measurements derived from multiple approaches to identify differences and how techniques complement each other to reconcile interpretations. To accomplish this, we tested ecosystem‐scale eddy covariance with plot‐scale chamber measurements within a temperate salt marsh. We found good agreement (R2 = 0.71–0.95) when comparing measurements of CH4 emissions and CO2 exchange but this agreement was dependent upon canopy phenology with discrepancies mainly arising during senescence and dormancy phenophases. The environmental drivers for CH4 and CO2 fluxes were mostly preserved across different measurement techniques, but the number of drivers increases while their individual strength decreases at the ecosystem scale. Empirical upscaling models parameterized with chamber measurements overestimated annual net ecosystem exchange (NEE; 108%) and gross primary production (GPP; 12%) while underestimating ecosystem respiration (Reco; 14%) and CH4 emissions (69%) compared to eddy covariance measurements. Our results suggest that the environmental complexity of CH4 and CO2 fluxes in salt marshes may be underestimated by chamber‐based measurements, and highlights how different techniques are complementary while considering limitations at each level of measurement.

Improving Estimation of Gross Primary Production in Dryland Ecosystems by a Model-Data Fusion Approach

Accurate and continuous monitoring of the production of arid ecosystems is of great importance for global and regional carbon cycle estimation. However, the magnitude of carbon sequestration in arid regions and its contribution to the global carbon cycle is poorly understood due to the worldwide paucity of measurements of carbon exchange in arid ecosystems. The Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity (GPP) product provides worldwide high-frequency monitoring of terrestrial GPP. While there have been a large number of studies to validate the MODIS GPP product with ground-based measurements over a range of biome types. Few studies have comprehensively validated the performance of MODIS estimates in arid and semi-arid ecosystems, especially for the newly released Collection 6 GPP products, whose resolution have been improved from 1000 m to 500 m. Thus, this study examined the performance of MODIS-derived GPP by compared with eddy covariance (EC)-observed GPP at different timescales for the main ecosystems in arid and semi-arid regions of China. Meanwhile, we also improved the estimation of MODIS GPP by using in situ meteorological forcing data and optimization of biome-specific parameters with the Bayesian approach. Our results revealed that the current MOD17A2H GPP algorithm could, on the whole, capture the broad trends of GPP at eight-day time scales for the most investigated sites. However, GPP was underestimated in some ecosystems in the arid region, especially for the irrigated cropland and forest ecosystems (with R2 = 0.80, RMSE = 2.66 gC/m2/day and R2 = 0.53, RMSE = 2.12 gC/m2/day, respectively). At the eight-day time scale, the slope of the original MOD17A2H GPP relative to the EC-based GPP was only 0.49, which showed significant underestimation compared with tower-based GPP. However, after using in situ meteorological data to optimize the biome-based parameters of MODIS GPP algorithm, the model could explain 91% of the EC-observed GPP of the sites. Our study revealed that the current MODIS GPP model works well after improving the maximum light-use efficiency (εmax or LUEmax), as well as the temperature and water-constrained parameters of the main ecosystems in the arid region. Nevertheless, there are still large uncertainties surrounding GPP modelling in dryland ecosystems, especially for desert ecosystems. Further improvements in GPP simulation in dryland ecosystems are needed in future studies, for example, improvements of remote sensing products and the GPP estimation algorithm, implementation of data-driven methods, or physiology models.

Observing carbon cycle–climate feedbacks from space

The impact of human emissions of carbon dioxide and methane on climate is an accepted central concern for current society. It is increasingly evident that atmospheric concentrations of carbon dioxide and methane are not simply a function of emissions but that there are myriad feedbacks forced by changes in climate that affect atmospheric concentrations. If these feedbacks change with changing climate, which is likely, then the effect of the human enterprise on climate will change. Quantifying, understanding, and articulating the feedbacks within the carbon–climate system at the process level are crucial if we are to employ Earth system models to inform effective mitigation regimes that would lead to a stable climate. Recent advances using space-based, more highly resolved measurements of carbon exchange and its component processes—photosynthesis, respiration, and biomass burning—suggest that remote sensing can add key spatial and process resolution to the existing in situ systems needed to provide enhanced understanding and advancements in Earth system models. Information about emissions and feedbacks from a long-term carbon–climate observing system is essential to better stewardship of the planet.

Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data

Abstract. Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm−3 in bare soil and lichen tundra and 89 g dm−3 in other LCTs. Total moss biomass varied from 0 to 820 g m−2, total vascular shoot mass from 7 to 112 g m−2 and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 ∘C in bare soil and lichen tundra, and varied from 5 to 9 ∘C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14–34 % of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6–15 % of variation. NDVI captured variation in vascular LAI better than in moss biomass, but while this difference was significant with late season NDVI, it was minimal with early season NDVI. For this reason, soil attributes associated with moss mass were better captured by early season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. The LCT map we produced had low to moderate uncertainty in predictions for plant and soil properties except for moss biomass and bare soil and lichen tundra LCTs. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM % and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance, topography or a LCT map. Despite the general accuracy of landscape level predictions in our LCT approach, this indicates challenges in the spatial extrapolation of some of those vegetation and soil attributes that are relevant for the regional ecosystem and global climate models.

Does day and night sampling reduce spurious correlation between canopy photosynthesis and ecosystem respiration?

It is necessary to partition eddy covariance measurements of carbon dioxide exchange into its offsetting gross fluxes, canopy photosynthesis, and ecosystem respiration, to understand the biophysical controls on the net fluxes. And independent estimates of canopy photosynthesis (G) and ecosystem respiration (R) are needed to validate and parametrize carbon cycle models that are coupled with climate and ecosystem dynamics models. Yet there is a concern that carbon flux partitioning methods may suffer from spurious correlation because derived values of canopy photosynthesis and ecosystem respiration both contain common information on net carbon fluxes at annual time scales.We hypothesized that spurious correlation among canopy photosynthesis and ecosystem respiration can be minimized using day–night conditional sampling of CO2 exchange; daytime fluxes are dominated by photosynthesis and nighttime fluxes are dominated by respiration. To test this hypothesis, we derived explicit equations that quantify the degree of spurious correlation between photosynthesis and respiration. Theoretically, day and night samples of net carbon exchange share a different common variable, daytime ecosystem respiration, and the degree of spurious correlation depends upon the variance of this shared variable.We then applied this theory to ideal measurements of carbon exchange of over a vigorous, irrigated, and frequently harvested alfalfa field in the sunny and windy region of California, the Sacramento-San Joaquin Delta, where soil CO2 efflux is strong. In this case, we found that the correlation coefficient between canopy photosynthesis and ecosystem respiration was −0.79. This relatively high correlation between canopy photosynthesis and respiration was mostly real as the degree of spurious correlation was only −0.32.We then expanded this analysis to the FLUXNET database that spans a spectrum of climate and plant functional types. We found, on average, that the correlation between gross photosynthesis and ecosystem respiration, using day–night sampling, was close to minus one (−0.828±0.130). For perspective, a large fraction of this correlation was real, as the degree of spurious correlation (Eq. (22)) was −0.526. We conclude that the potential for spurious correlation between canopy photosynthesis and ecosystem respiration across the FLUXNET database was moderate. Looking across the database, we found that the least negative spurious correlations coefficients (>−0.3) were associated with seasonal deciduous forests. The most negative spurious correlations coefficients (<−0.7) were associated with evergreen forests found in boreal climates.

Interpreting seasonal changes in the carbon balance of southern Amazonia using measurements of XCO2 and chlorophyll fluorescence from GOSAT

Amazon forests exert a major influence on the global carbon cycle, but quantifying the impact is complicated by diverse landscapes and sparse data. Here we examine seasonal carbon balance in southern Amazonia using new measurements of column‐averaged dry air mole fraction of CO2 (XCO2) and solar induced chlorophyll fluorescence (SIF) from the Greenhouse Gases Observing Satellite (GOSAT) from July 2009 to December 2010. SIF, which reflects gross primary production (GPP), is used to disentangle the photosynthetic component of land‐atmosphere carbon exchange. We find that tropical transitional forests in southern Amazonia exhibit a pattern of low XCO2 during the wet season and high XCO2 in the dry season that is robust to retrieval methodology and with seasonal amplitude double that of cerrado ecosystems to the east (4 ppm versus 2 ppm), including enhanced dilution of 2.5 ppm in the wet season. Concomitant measurements of SIF, which are inversely correlated with XCO2 in southern Amazonia (r = −0.53, p &lt; 0.001), indicate that the enhanced variability is driven by seasonal changes in GPP due to coupling of strong vertical mixing with seasonal changes in underlying carbon exchange. This finding is supported by forward simulations of the Goddard Chemistry Transport Model (GEOS‐Chem) which show that local carbon uptake in the wet season and loss in the dry season due to emissions by ecosystem respiration and biomass burning produces best agreement with observed XCO2. We conclude that GOSAT provides critical measurements of carbon exchange in southern Amazonia, but more samples are needed to examine moist Amazon forests farther north.

Evaluating responses of maize ( Zea mays L.) to soil physical conditions using a boundary line approach

The functional relation between the decline in the rate of a physiological process and the magnitude of a stress related to soil physical conditions is an important tool for uses as diverse as assessment of the stress-related sensitivity of different plant cultivars and characterization of soil structure. Two of the most pervasive sources of stress are soil resistance to root penetration (SR) and matric potential ( ψ). However, the assessment of these sources of stress on physiological processes in different soils can be complicated by other sources of stress and by the strong relation between SR and ψ in a soil. A multivariate boundary line approach was assessed as a means of reducing these complications. The effects of SR and ψ stress conditions on plant responses were examined under growth chamber conditions. Maize plants ( Zea mays L.) were grown in soils at different water contents and having different structures arising from variation in texture, organic carbon content and soil compaction. Measurements of carbon exchange (CE), leaf transpiration (LT), plant transpiration (PT), leaf area (LA), leaf + shoot dry weight (LSDW), root total length (RTL), root surface area (RSA) and root dry weight (RDW) were determined after plants reached the 12-leaf stage. The LT, PT and LA were described as a function of SR and ψ with a double S-shaped function using the multivariate boundary line approach. The CE and LSDW were described by the combination of an S-shaped function for SR and a linear function for ψ. The root parameters were described by a single S-shaped function for SR. The sensitivity to SR and ψ depended on the plant parameter. Values of PT, LA and LSDW were most sensitive to SR. Among those parameters exhibiting a significant response to ψ, PT was most sensitive. The boundary line approach was found to be a useful tool to describe the functional relation between the decline in the rate of a physiological process and the magnitude of a stress related to soil physical conditions.

Eddy covariance measurements of carbon exchange and latent and sensible heat fluxes over a boreal lake for a full open‐water period

Long‐term measurements of sensible and latent heat and carbon dioxide fluxes were performed over a boreal lake in southern Finland using the direct micrometeorological eddy covariance (EC) technique. The water column was sampled weekly for dissolved carbon dioxide, and the CO2 flux was estimated also applying the concentration gradient method. Temperature and oxygen profiles of the lake were measured twice a week. The measurements covered one full open‐water period from April to November 2003, and it is the longest continuous CO2 record ever measured over a lake by EC. The sensible heat flux H was positive, that is, from the lake to the atmosphere, except in May, when it was &gt;0 W/m2 at night and &lt;0 W/m2 in daytime. The latent heat flux dominated clearly over H in spring and summer; that is, the Bowen ratio was less than 1. Higher‐moment turbulence statistics proved to be efficient in detection of frequent nonstationary situations. Applying the statistical criteria for CO2 concentration and vertical wind speed, averaging over a 5‐min period and selecting only the wind direction with longest fetch, we could obtain lake‐representative CO2 fluxes. Footprint analysis based on a closure model revealed that the source areas were relatively short because of the presence of turbulence generated by the surrounding forest, compared to a larger lake with an extended smooth surface. We observed a net CO2 source of 0.2–0.4 μmol m−2 s−1 excluding July, when the flux was closer to zero. The results are consistent with the gradient method, based on more infrequent sampling, and both methods gave the same average flux, 0.2 μmol m−2 s−1, over the whole open‐water period.

Carbon mass fluxes of forests in Belgium determined with low resolution optical sensors

The primary objective of this paper is to describe the validation of a parametric model (C-Fix) designed to estimate the basic carbon mass fluxes of forests in Belgium. Most validation efforts in the literature are based on point measurements. Since landscapes in Belgium are quite heterogeneous, the spatial up-scaling of a point measurement to the level of a sensor pixel is a crucial issue. Process based models quite often have a large set of input variables, some of them hardly available or not measurable on a regional basis; on the other hand most of the process based models possess a prognostic capacity. The parametric C-Fix model estimates carbon mass fluxes from local, regional to continental scales. It ingests only a modest number of meteorological input variables, including satellite observations. Parametric models do not possess a prognostic capacity, but the spatial up-scaling by the use of remote sensing data is much more straightforward than with process models. In this paper, we describe the validation of C-Fix with eddy covariance NEP (net ecosystem production) measurements and further applied C-Fix for the mapping of the geographical distribution of carbon mass fluxes over the entire Belgian territory, using NOAA-AVHRR (1997) and SPOT4-VGT imagery (April 1998–March 1999). We combine a forest probability map, derived from NOAA data for 1997 with the mapped estimates of Belgian NEP to obtain forest NEP per image pixel. Forest NEP is validated regionally, with measurements of carbon exchange obtained at two Belgian Euroflux eddy covariance tower sites (the Brasschaat, ‘Inslag’ and Vielsalm, ‘Tinseubois' forest sites). A correlation analysis is performed for the estimated forest NEPs at both Euroflux sites and the NEP measured there, assumed to be primarily from forest. Finally, a correlation analysis with a process-based stand scale model (ASPECTS) is performed for the two forest sites, as a cross check on the validation results. Our results demonstrate that a parametric model, like C-Fix, provides a good basis to estimate the evolution and geographical distribution of the main constituents of the carbon budget of terrestrial ecosystems, in this study specifically forest ecosystems at the regional scale (Belgium).

Ecophysiological controls on the carbon balances of three southern boreal forests

Continuous measurements of carbon exchange using the eddy covariance (EC) technique were made at three boreal forest mature sites including Southern Old Aspen (SOA), Southern Old Black Spruce (SOBS) and Southern Old Jack Pine (SOJP) in 2000. Climatic conditions were slightly warmer than normal with precipitation exceeding evapotranspiration at each site. Annual ecosystem respiration ( R) derived from daytime analyses of EC data was 1141, 815 and 521 g C m −2 per year and was consistently lower than nighttime EC estimates of 1193, 897 and 578 g C m −2 per year for SOA, SOBS and SOJP, respectively. The differences, however, were not statistically significant given the large uncertainty associated with each analytical technique. The uncertainty in annual net ecosystem productivity (NEP) was assessed by randomly simulating missing data and gap filling using simple biophysical algorithms. The uncertainty analysis supports the finding that each site was a net sink, and that differences in NEP were only significant between SOA and SOBS. The annual NEP and uncertainty for SOA, SOBS and SOJP was 122 (64–142), 35 (18–53) and 78 (61–91) g C m −2 per year, respectively. These relatively old growth forests represent a weak to moderate carbon sink. Despite having the shortest growing period, carbon sequestration was greatest at SOA because of its relatively large photosynthetic capacity ( A max). At the evergreen sites, A max was marginally larger at SOBS; however, annual carbon sequestration was smaller as a result of greater R. The evergreen sites exhibited a pronounced mid-season reduction in NEP, which was attributed to a large increase in R while A max had not reached its full capacity. Non-growing season R resulted in a carbon loss of 285, 120 and 64 g C m −2 and accounted for 70, 80 and 46% of the summertime NEP at SOA, SOBS and SOJP, respectively. Six years of EC data at SOA indicate that carbon sequestration at boreal aspen sites may benefit from warmer climatic conditions because R is relatively conservative and photosynthesis increases in response to a longer growing period.

Photosynthetic Production of Ulva rotundata Bliding Estimated by Oxygen and Inorganic Carbon Exchange Measurements in the Field

The photosynthetic performance of an estuarine population of Ulva rotundata Bliding was determined under natural radiation during a daily cycle. The primary production was estimated following two methods, oxygen evolutionand dissolved inorganic carbon (DIC) uptake calculated from the pH change and alkalinity in the media after incubation in closed bottles. Maximum values of oxygen evolution (261 μmol O 2 m - 2 min - 1 ) were reached during midday. The daily course of the DIC uptake rates was different since the maximum rate (248′10 μmol C m - 2 min - 1 ) was obtained later in the afternoon. In any case, no photoinhibition was detected by either O 2 evolution or DIC uptake. Additionally, the parameters of photosynthesis vs. photon fluence density curves were similar in spite of the technique used. During the daily cycle, significant changes in CA activity and percentage of photosynthetic inhibition following the addition of an external CA inhibitor (acetazo-lamide) were produced. However, these changes appeared to have a limited effect on photosynthesis. On the other hand, chlorophyll a and b contents decreased drastically in the afternoon and there was not a good correlation between pigment content and photosynthesis rates. Taken into account the results obtained, the daily primary production of U. rotundata based on oxygen evolution was 20% higher than that based on DIC uptake (1.8 and 1.5 g C m - 2 day - 1 , respectively).

A first-order analysis of the potential role of CO2 fertilization to affect the global carbon budget: a comparison of four terrestrial biosphere models

We compared the simulated responses of net primary production, heterotrophic respiration, net ecosystem production and carbon storage in natural terrestrial ecosystems to historical (1765 to 1990) and projected (1990–2300) changes of atmospheric CO 2 concentration of four terrestrial biosphere models: the Bern model, the Frankfurt Biosphere Model (FBM), the High-Resolution Biosphere Model (HRBM) and the Terrestrial EcosystemModel (TEM). The results of the model intercomparison suggest that CO 2 fertilization of natural terrestrial vegetation has the potential to account for a large fraction of the so-called ‘‘missing carbon sink’′ of 2.0 Pg C in 1990. Estimates of this potential are reduced when the models incorporate the concept that CO 2 fertilization can be limited by nutrient availability. Although the model estimates differ on the potential size (126 to 461 Pg C) of the future terrestrial sink caused by CO 2 fertilization, the results of the four models suggest that natural terrestrial ecosystems will have a limited capacity to act as a sink of atmospheric CO 2 in the future as a result of physiological constraints and nutrient constraints on NPP. All the spatially explicit models estimate a carbon sink in both tropical and northern temperate regions, but the strength of these sinks varies over time. Differences in the simulated response of terrestrial ecosystems to CO 2 fertilization among the models in this intercomparison study reflect the fact that the models have highlighted different aspects of the effect of CO 2 fertilization on carbon dynamics of natural terrestrial ecosystems including feedback mechanisms. As interactions with nitrogen fertilization, climate change and forest regrowth may play an important role in simulating the response of terrestrial ecosystems to CO 2 fertilization, these factors should be included in future analyses. Improvements in spatially explicit data sets, whole-ecosystem experiments and the availability of net carbon exchange measurements across the globe will also help to improve future evaluations of the role of CO 2 fertilization on terrestrial carbon storage. DOI: 10.1034/j.1600-0889.1999.00017.x

A first-order analysis of the potential rôle of CO2 fertilization to affect the global carbon budget: a comparison of four terrestrial biosphere models

We compared the simulated responses of net primary production, heterotrophic respiration, net ecosystem production and carbon storage in natural terrestrial ecosystems to historical (1765 to 1990) and projected (1990–2300) changes of atmospheric CO2 concentration of four terrestrial biosphere models: the Bern model, the Frankfurt Biosphere Model (FBM), the High-Resolution Biosphere Model (HRBM) and the Terrestrial EcosystemModel (TEM). The results of the model intercomparison suggest that CO2 fertilization of natural terrestrial vegetation has the potential to account for a large fraction of the so-called “missing carbon sink” of 2.0 Pg C in 1990. Estimates of this potential are reduced when the models incorporate the concept that CO2 fertilization can be limited by nutrient availability. Although the model estimates differ on the potential size (126 to 461 Pg C) of the future terrestrial sink caused by CO2 fertilization, the results of the four models suggest that natural terrestrial ecosystems will have a limited capacity to act as a sink of atmospheric CO2 in the future as a result of physiological constraints and nutrient constraints on NPP. All the spatially explicit models estimate a carbon sink in both tropical and northern temperate regions, but the strength of these sinks varies over time. Differences in the simulated response of terrestrial ecosystems to CO2 fertilization among the models in this intercomparison study reflect the fact that the models have highlighted different aspects of the effect of CO2 fertilization on carbon dynamics of natural terrestrial ecosystems including feedback mechanisms. As interactions with nitrogen fertilization, climate change and forest regrowth may play an important role in simulating the response of terrestrial ecosystems to CO2 fertilization, these factors should be included in future analyses. Improvements in spatially explicit data sets, whole-ecosystem experiments and the availability of net carbon exchange measurements across the globe will also help to improve future evaluations of the role of CO2 fertilization on terrestrial carbon storage.

Land use change and carbon exchange in the tropics: III. Structure, basic equations, and sensitivity analysis of the model

The rationale, assumptions, structure and basic mathematical functions of the model used to produce the simulation results reported in the first two articles of this series are described in detail. Sensitivity analysis indicates that the most important parameters in the model, and, presumably, in the carbon exchange between tropical forests and the atmosphere, are: (a) the conversion rate of forests to permanent pasture and agriculture, (b) the changes that are occurring and have occurred in the shifting cultivation system, and (c) the fate of cleared vegetation. Although it is not possible to validate the model against direct measurements of carbon exchange, the model has been proven robust when subject to a series of explicit analyses and comparisons with other assessments.