Berrien Moore

Recent patterns and mechanisms of carbon exchange by terrestrial ecosystems

Knowledge of carbon exchange between the atmosphere, land and the oceans is important, given that the terrestrial and marine environments are currently absorbing about half of the carbon dioxide that is emitted by fossil-fuel combustion. This carbon uptake is therefore limiting the extent of atmospheric and climatic change, but its long-term nature remains uncertain. Here we provide an overview of the current state of knowledge of global and regional patterns of carbon exchange by terrestrial ecosystems. Atmospheric carbon dioxide and oxygen data confirm that the terrestrial biosphere was largely neutral with respect to net carbon exchange during the 1980s, but became a net carbon sink in the 1990s. This recent sink can be largely attributed to northern extratropical areas, and is roughly split between North America and Eurasia. Tropical land areas, however, were approximately in balance with respect to carbon exchange, implying a carbon sink that offset emissions due to tropical deforestation. The evolution of the terrestrial carbon sink is largely the result of changes in land use over time, such as regrowth on abandoned agricultural land and fire prevention, in addition to responses to environmental changes, such as longer growing seasons, and fertilization by carbon dioxide and nitrogen. Nevertheless, there remain considerable uncertainties as to the magnitude of the sink in different regions and the contribution of different processes.

Carbon balance of the terrestrial biosphere in the twentieth century: Analyses of CO2, climate and land use effects with four process-based ecosystem models

The concurrent effects of increasing atmospheric CO2 concentration, climate variability, and cropland establishment and abandonment on terrestrial carbon storage between 1920 and 1992 were assessed using a standard simulation protocol with four process-based terrestrial biosphere models. Over the long-term (1920-1992), the simulations yielded a time history of terrestrial uptake that is consistent (within the uncertainty) with a long-term analysis based on ice core and atmospheric CO2 data. Up to 1958, three of four analyses indicated a net release of carbon from terrestrial ecosystems to the atmosphere caused by cropland establishment. After 1958, all analyses indicate a net uptake of carbon by terrestrial ecosystems, primarily because of the physiological effects of rapidly rising atmospheric CO2. During the 1980s the simulations indicate that terrestrial ecosystems stored between 0.3 and 1.5 Pg C yr(-1), which is within the uncertainty of analysis based on CO2 and O-2 budgets. Three of the four models indicated tin accordance with O-2 evidence) that the tropics were approximately neutral while a net sink existed in ecosystems north of the tropics. Although all of the models agree that the long-term effect of climate on carbon storage has been small relative to the effects of increasing atmospheric CO2 and land use, the models disagree as to whether climate variability and change in the twentieth century has promoted carbon storage or release. Simulated interannual variability from 1958 generally reproduced the El Nino/Southern Oscillation (ENSO)-scale variability in the atmospheric CO2 increase, but there were substantial differences in the magnitude of interannual variability simulated by the models. The analysis of the ability of the models to simulate the changing amplitude of the seasonal cycle of atmospheric CO2 suggested that the observed trend may be a consequence of CO2 effects, climate variability, land use changes, or a combination of these effects. The next steps for improving the process-based simulation of historical terrestrial carbon include (1) the transfer of insight gained from stand-level process studies to improve the sensitivity of simulated carbon storage responses to changes in CO2 and climate, (2) improvements in the data sets used to drive the models so that they incorporate the timing, extent, and types of major disturbances, (3) the enhancement of the models so that they consider major crop types and management schemes, (4) development of data sets that identify the spatial extent of major crop types and management schemes through time, and (5) the consideration of the effects of anthropogenic nitrogen deposition. The evaluation of the performance of the models in the context of a more complete consideration of the factors influencing historical terrestrial carbon dynamics is important for reducing uncertainties in representing the role of terrestrial ecosystems in future projections of the Earth system.

Potential Net Primary Productivity in South America: Application of a Global Model

We use a mechanistically based ecosystem simulation model to describe and analyze the spatial and temporal patterns of terrestrial net primary productivity (NPP) in South America. The Terrestrial Ecosystem Model (TEM) is designed to predict major carbon and nitrogen fluxes and pool sizes in terrestrial ecosystems at continental to global scales. Information from intensively studies field sites is used in combination with continental-scale information on climate, soils, and vegetation to estimate NPP in each of 5888 non-wetland, 0.5° latitude °0.5° longitude grid cells in South America, at monthly time steps. Preliminary analyses are presented for the scenario of natural vegetation throughout the continent, as a prelude to evaluating human impacts on terrestrial NPP. The potential annual NPP of South America is estimated to be 12.5 Pg/yr of carbon (26.3 Pg/yr of organic matter) in a non-wetland area of 17.0 ° 106 km2 . More than 50% of this production occurs in the tropical and subtropical evergreen forest region. Six independent model runs, each based on an independently derived set of model parameters, generated mean annual NPP estimates for the tropical evergreen forest region ranging from 900 to 1510 g°m-2 °yr-1 of carbon, with an overall mean of 1170 g°m-2 °yr-1 . Coefficients of variation in estimated annual NPP averaged 20% for any specific location in the evergreen forests, which is probably within the confidence limits of extant NPP measurements. Predicted rates of mean annual NPP in other types of vegetation ranged from 95 g°m-2 °yr-1 in arid shrublands to 930 g°m@ ?yr-1 in savannas, and were within the ranges measured in empirical studies. The spatial distribution of predicted NPP was directly compared with estimates made using the Miami mode of Lieth (1975). Overall, TEM predictions were °10% lower than those of the Miami model, but the two models agreed closely on the spatial patterns of NPP in south America. Unlike previous models, however, TEM estimates NPP monthly, allowing for the evaluation of seasonal phenomena. This is an important step toward integration of ecosystem models with remotely sensed information, global climate models, and atmospheric transport models, all of which are evaluated at comparable spatial and temporal scales. Seasonal patterns of NPP in South America are correlated with moisture availability in most vegetation types, but are strongly influenced by seasonal differences in cloudiness in the tropical evergreen forests. On an annual basis, moisture availability was the factor that was correlated most strongly with annual NPP in South America, but differences were again observed among vegetation types. These results allow for the investigation and analysis of climatic controls over NPP at continental scales, within and among vegetation types, and within years. Further model validation is needed. Nevertheless, the ability to investigate NPP-environment interactions with a high spatial and temporal resolution at continental scales should prove useful if not essential for rigorous analysis of the potential effects of global climate changes on terrestrial ecosystems.

Effect of interannual climate variability on carbon storage in Amazonian ecosystems

The Amazon Basin contains almost one-half of the worlds undisturbed tropical evergreen forest as well as large areas of tropical savanna,. The forests account for about 10 per cent of the worlds terrestrial primary productivity and for a similar fraction of the carbon stored in land ecosystems,, and short-term field measurements suggest that these ecosystems are globally important carbon sinks. But tropical land ecosystems have experienced substantial interannual climate variability owing to frequent El Niño episodes in recent decades. Of particular importance to climate change policy is how such climate variations, coupled with increases in atmospheric CO2 concentration, affect terrestrial carbon storage. Previous model analyses have demonstrated the importance of temperature in controlling carbon storage,. Here we use a transient process-based biogeochemical model of terrestrial ecosystems, to investigate interannual variations of carbon storage in undisturbed Amazonian ecosystems in response to climate variability and increasing atmospheric CO2 concentration during the period 1980 to 1994. In El Niño years, which bring hot, dry weather to much of the Amazon region, the ecosystems act as a source of carbon to the atmosphere (up to 0.2 petagrams of carbon in 1987 and 1992). In other years, these ecosystems act as a carbon sink (up to 0.7 Pg C in 1981 and 1993). These fluxes are large; they compare to a 0.3 Pg C per year source to the atmosphere associated with deforestation inthe Amazon Basin in the early 1990s. Soil moisture, which is affected by both precipitation and temperature, and which affects both plant and soil processes, appears to be an important control on carbon storage.

Global deforestation: contribution to atmospheric carbon dioxide.

A study of effects of terrestrial biota on the amount of carbon dioxide in the atmosphere suggests that the global net release of carbon due to forest clearing between 1860 and 1980 was between 135 x 1015 and 228 x 1015 grams. Between 1.8 x 1015 and 4.7 x 1015 grams of carbon were released in 1980, of which nearly 80 percent was due to deforestation, principally in the tropics. The annual release of carbon from the biota and soils exceeded the release from fossil fuels until about 1960. Because the biotic release has been and remains much larger than is commonly assumed, the airborne fraction, usually considered to be about 50 percent of the release from fossil fuels, was probably between 22 and 43 percent of the total carbon released in 1980. The increase in carbon dioxide in the atmosphere is thought by some to be increasing the storage of carbon in the earths remaining forests sufficiently to offset the release from deforestation. The interpretation of the evidence presented here suggests no such effect; deforestation appears to be the dominant biotic effect on atmospheric carbon dioxide. If deforestation increases in proportion to population, the biotic release of carbon will reach 9 x 1015 grams per year before forests are exhausted early in the next century. The possibilities for limiting the accumulation of carbon dioxide in the atmosphere through reduction in use of fossil fuels and through management of forests may be greater than is commonly assumed.

Projecting the future of the U.S. carbon sink

Atmospheric and ground-based methods agree on the presence of a carbon sink in the coterminous United States (the United States minus Alaska and Hawaii), and the primary causes for the sink recently have been identified. Projecting the future behavior of the sink is necessary for projecting future net emissions. Here we use two models, the Ecosystem Demography model and a second simpler empirically based model (Miami Land Use History), to estimate the spatio-temporal patterns of ecosystem carbon stocks and fluxes resulting from land-use changes and fire suppression from 1700 to 2100. Our results are compared with other historical reconstructions of ecosystem carbon fluxes and to a detailed carbon budget for the 1980s. Our projections indicate that the ecosystem recovery processes that are primarily responsible for the contemporary U.S. carbon sink will slow over the next century, resulting in a significant reduction of the sink. The projected rate of decrease depends strongly on scenarios of future land use and the long-term effectiveness of fire suppression.

Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data

A unique physical feature of paddy rice fields is that rice is grown on flooded soil. During the period of flooding and rice transplanting, there is a large proportion of surface water in a land surface consisting of water, vegetation and soils. The VEGETATION (VGT) sensor has four spectral bands that are equivalent to spectral bands of Landsat TM, and its mid-infrared spectral band is very sensitive to soil moisture and plant canopy water content. In this study we evaluated a VGT-derived normalized difference water index (NDWI VGT =(B3-MIR)/ (B3+MIR)) for describing temporal and spatial dynamics of surface moisture. Twenty-seven 10-day composites (VGT- S10) from 1 March to 30 November 1999 were acquired and analysed for a study area (175 km by 165 km) in eastern Jiangsu Province, China, where a winter wheat and paddy rice double cropping system dominates the landscape. We compared the temporal dynamics and spatial patterns of normalized difference vegetation index (NDVI VGT ) and NDWI VGT . The NDWI VGT temporal dynamics were sensitive enough to capture the substantial increases of surface water due to flooding and rice transplanting at paddy rice fields. A land use thematic map for the timing and location of flooding and rice transplanting was generated for the study area. Our results indicate that NDWI and NDVI temporal anomalies may provide a simple and effective tool for detection of flooding and rice transplanting across the landscape.

Equilibrium responses of global net primary production and carbon storage to doubled atmospheric carbon dioxide: Sensitivity to changes in vegetation nitrogen concentration

We ran the terrestrial ecosystem model (TEM) for the globe at 0.5° resolution for atmospheric CO2 concentrations of 340 and 680 parts per million by volume (ppmv) to evaluate global and regional responses of net primary production (NPP) and carbon storage to elevated CO2 for their sensitivity to changes in vegetation nitrogen concentration. At 340 ppmv, TEM estimated global NPP of 49.0 1015 g (Pg) C yr−1 and global total carbon storage of 1701.8 Pg C; the estimate of total carbon storage does not include the carbon content of inert soil organic matter. For the reference simulation in which doubled atmospheric CO2 was accompanied with no change in vegetation nitrogen concentration, global NPP increased 4.1 Pg C yr−1 (8.3%), and global total carbon storage increased 114.2 Pg C. To examine sensitivity in the global responses of NPP and carbon storage to decreases in the nitrogen concentration of vegetation, we compared doubled CO2 responses of the reference TEM to simulations in which the vegetation nitrogen concentration was reduced without influencing decomposition dynamics (“lower N” simulations) and to simulations in which reductions in vegetation nitrogen concentration influence decomposition dynamics (“lower N+D” simulations). We conducted three lower N simulations and three lower N+D simulations in which we reduced the nitrogen concentration of vegetation by 7.5, 15.0, and 22.5%. In the lower N simulations, the response of global NPP to doubled atmospheric CO2 increased approximately 2 Pg C yr−1 for each incremental 7.5% reduction in vegetation nitrogen concentration, and vegetation carbon increased approximately an additional 40 Pg C, and soil carbon increased an additional 30 Pg C, for a total carbon storage increase of approximately 70 Pg C. In the lower N+D simulations, the responses of NPP and vegetation carbon storage were relatively insensitive to differences in the reduction of nitrogen concentration, but soil carbon storage showed a large change. The insensitivity of NPP in the N+D simulations occurred because potential enhancements in NPP associated with reduced vegetation nitrogen concentration were approximately offset by lower nitrogen availability associated with the decomposition dynamics of reduced litter nitrogen concentration. For each 7.5% reduction in vegetation nitrogen concentration, soil carbon increased approximately an additional 60 Pg C, while vegetation carbon storage increased by only approximately 5 Pg C. As the reduction in vegetation nitrogen concentration gets greater in the lower N+D simulations, more of the additional carbon storage tends to become concentrated in the north temperate-boreal region in comparison to the tropics. Other studies with TEM show that elevated CO2 more than offsets the effects of climate change to cause increased carbon storage. The results of this study indicate that carbon storage would be enhanced by the influence of changes in plant nitrogen concentration on carbon assimilation and decomposition rates. Thus changes in vegetation nitrogen concentration may have important implications for the ability of the terrestrial biosphere to mitigate increases in the atmospheric concentration of CO2 and climate changes associated with the increases.

MODELING GROSS PRIMARY PRODUCTION OF AN EVERGREEN NEEDLELEAF FOREST USING MODIS AND CLIMATE DATA

Forest canopies are composed of photosynthetically active vegetation (PAV, chloroplasts) and nonphotosynthetic vegetation (NPV, e.g., cell wall, vein, branch). The fraction of photosynthetically active radiation (PAR) absorbed by the canopy (FAPAR) should be partitioned into FAPARPAV and FAPARNPV. Gross primary production (GPP) of forests is affected by FAPARPAV. In this study we developed and validated a satellite-based vegetation photosynthesis model (VPM; GPP = eg X FAPAPPAV X PAR) that incorporates improved vegetation indices derived from the moderate resolution imaging spectroradimeter (MODIS) sensor. Site-specific data from the CO2 flux tower site (evergreen needleleaf forest) at Howland, Maine, USA, were used. The enhanced vegetation index (EVI) better correlated with the seasonal dynamics of GPP than did the normalized difference vegetation index (NDVI). Simulations of the VPM model were conducted, using both daily and eight-day composites of MODIS images (500-m spatial resolution) and climate data (air temperature and PAR), respectively. Predicted GPP values in 2001 agree reasonably well with estimated GPP from the CO2 flux tower site. There were no significant differences in VPM-predicted GPP (from eight-day MODIS composites) among one pixel (~500-m resolution), 3 X 3 pixel block (~ 1.5-km resolution), and 5 X 5 pixel block (~ 2.5-km resolution). The differences between VPM-predicted and observed GPP were smaller for simulations using eight-day MODIS composites than for simulations using daily MODIS images. The results of this study have shown the potential of MODIS data (both daily and eight-day composites) and the VPM model for quantifying seasonal and interannual variations of GPP of evergreen needleleaf forests.

A simulation model linking crop growth and soil biogeochemistry for sustainable agriculture

Abstract Predicting impacts of climate change or alternative management on both food production and environment safety in agroecosystems is drawing great attention in the scientific community. Most of the existing agroecosystem models emphasize either crop growth or soil processes. This paper reports the latest development of an agroecosystem model (Crop-DNDC) by integrating detailed crop growth algorithms with an existing soil biogeochemical model, DNDC (Li et al., J. Geophys. Res. (1992) 9759). In the Crop-DNDC model, crop growth is simulated not only by tracking crop physiological processes (phenology, leaf area index, photosynthesis, respiration, assimilate allocation, rooting processes and nitrogen uptake), but also by calculating water stress and nitrogen stress, which were closely related to soil biogeochemical processes and hydraulic dynamics. Crop-DNDC also quantifies crop residue incorporated in the soil at the end of each growing season. Thus the model has tightly coupled crop growth algorithms with soil biogeochemical components, and simulates carbon, nitrogen and water cycles in agroecosystems with a relatively complete scope. The model was validated against field measurements, including soil moisture, leaf area index, crop biomass and nitrogen content, and the modeled results were in agreement with observations on soil carbon dynamics and trace gas emissions as well. Sensitivity tests demonstrated that the modeled results in crop yield, soil carbon dynamics and trace gas emissions were sensitive to climate conditions, atmospheric CO 2 concentration and various farming practices. There are potentials of applying the model for simultaneously predicting effects of changes in climate or management on crop yield, soil carbon sequestration and trace gas emissions.