David W. Kicklighter

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.

MEASURING NET PRIMARY PRODUCTION IN FORESTS: CONCEPTS AND FIELD METHODS

There are pressing reasons for developing a better understanding of net primary production (NPP) in the worlds forests. These ecosystems play a large role in the worlds carbon budget, and their dynamics, which are likely to be responding to global changes in climate and atmospheric composition, have major economic implications and impacts on global biodiversity. Although there is a long history of forest NPP studies in the ecological literature, current understanding of ecosystem-level production remains lim- ited. Forest NPP cannot be directly measured; it must be approached by indirect methods. To date, field measurements have been largely restricted to a few aspects of NPP; methods are still lacking for field assessment of others, and past studies have involved confusion about the types of measurements needed. As a result, existing field-based estimates of forest NPP are likely to be significant underestimates. In this paper we provide a conceptual framework to guide efforts toward improved estimates of forest NPP. We define the quantity NPP* as the summed classes of organic material that should be measured or estimated in field studies for an estimate of total NPP. We discuss the above- and belowground components of NPP* and the available methods for measuring them in the field. We then assess the implications of the limitations of past studies for current understanding of NPP in forest ecosystems, discuss how field NPP* measurements can be used to complement tower-based studies of forest carbon flux, and recommend design criteria for future field studies of forest NPP.

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.

Indirect Emissions from Biofuels: How Important?

Biofuel Backfire For compelling economical, geopolitical, and environmental reasons, biofuels are considered an attractive alternative to fossil fuels for meeting future global energy demands. Melillo et al. (p. 1397, published online 22 October), however, suggest that a few serious drawbacks related to land use need to be considered. Based on a combined biogeochemistry and economic model, indirect land use (for example, clearing forested land for food crops to compensate for increased biofuel crop production on current farmlands) is predicted to generate more soil carbon loss than directly harvesting biofuel crops. Furthermore, increased fertilizer use for biofuels will add large amounts of nitrous oxide—a more effective heat-trapping molecule than carbon dioxide—to the atmosphere. Policy decisions regarding land and crop management thus need to consider the long-term implications of increased biofuel production. Land-use changes associated with biofuel production are predicted to increase greenhouse gas emissions. A global biofuels program will lead to intense pressures on land supply and can increase greenhouse gas emissions from land-use changes. Using linked economic and terrestrial biogeochemistry models, we examined direct and indirect effects of possible land-use changes from an expanded global cellulosic bioenergy program on greenhouse gas emissions over the 21st century. Our model predicts that indirect land use will be responsible for substantially more carbon loss (up to twice as much) than direct land use; however, because of predicted increases in fertilizer use, nitrous oxide emissions will be more important than carbon losses themselves in terms of warming potential. A global greenhouse gas emissions policy that protects forests and encourages best practices for nitrogen fertilizer use can dramatically reduce emissions associated with biofuels production.

NET PRIMARY PRODUCTION IN TROPICAL FORESTS: AN EVALUATION AND SYNTHESIS OF EXISTING FIELD DATA

Information on net primary production in tropical forests is needed for the development of realistic global carbon budgets, for projecting how these ecosystems will be affected by climatic and atmospheric changes, and for evaluating eddy covariance mea- surements of tropical forest carbon flux. However, a review of the database commonly used to address these issues shows that it has serious flaws. In this paper we synthesize the data in the primary literature on NPP in old-growth tropical forests to produce a consistent data set on NPP for these forests. Studies in this biome have addressed only a few NPP com- ponents, all aboveground. Given the limited scope of the direct field measurements, we sought relationships in the existing data that allow estimation of unmeasured aspects of production from those that are more easily assessed. We found a predictive relationship between annual litterfall and aboveground biomass increment. For 39 diverse tropical forest sites, we then developed consistent, documented estimates of the upper and lower bounds around total NPP to serve as benchmarks for calibrating and validating biogeochemical models with respect to this biome. We developed these estimates based on existing field measurements, current understanding of aboveground consumption and biogenic volatile organic carbon emissions, and our judgment that belowground production is bounded by the range 0.2-1.2 3 ANPP (aboveground NPP). Across this broad spectrum of tropical forests (dry to wet, lowland to montane, nutrient-rich to nutrient-poor soils), our estimates of lower and upper bounds on total NPP range from 1.7 to 11.8 Mg C·ha 21 ·yr 21 (lower bounds) and from 3.1 to 21.7 Mg C·ha 21 ·yr 21 (upper bounds). We also showed that two relationships that have been used for estimating NPP (the Bray-Gorham relationship based on leaf litterfall and the Miami model based on temperature or precipitation) are not valid for the tropical forest biome.

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.

Belowground consequences of vegetation change and their treatment in models

The extent and consequences of global land-cover and land-use change are increasingly apparent. One consequence not so apparent is the altered structure of plants belowground. This paper examines such belowground changes, emphasizing the interaction of altered root distributions with other factors and their treatment in models. Shifts of woody and herbaceous vegetation with deforestation, afforestation, and woody plant en- croachment typically alter the depth and distribution of plant roots, influencing soil nutrients, the water balance, and net primary productivity (NPP). For example, our analysis of global soil data sets shows that the major plant nutrients C, N, P, and K are more shallowly distributed than are Ca, Mg, and Na, but patterns for each element vary with the dominant vegetation type. After controlling for climate, soil C and N are distributed more deeply in arid shrublands than in arid grasslands, and subhumid forests have shallower nutrient dis- tributions than do subhumid grasslands. Consequently, changes in vegetation may influence the distribution of soil carbon and nutrients over time (perhaps decades to centuries). Shifts in the water balance are typically much more rapid. Catchment studies indicate that the water yield decreases 25-40 mm for each 10% increase in tree cover, and increases in transpiration of water taken up by deep roots may account for as much as 50% of observed responses. Because models are increasingly important for predicting the consequences of vegetation change, we discuss the treatment of belowground processes and how different treatments affect model outputs. Whether models are parameterized by biome or plant life form (or neither), use single or multiple soil layers, or include N and water limitation will all affect predicted outcomes. Acknowledging and understanding such differences should help constrain predictions of vegetation change.

Methane fluxes between terrestrial ecosystems and the atmosphere at northern high latitudes during the past century : a retrospective analysis with a process-based biogeochemistry model

minus consumption) from these soils have increased by an average 0.08 Tg CH4 yr � 1 during the twentieth century. Our estimate of the annual net emission rate at the end of the century for the region is 51 Tg CH4 yr � 1 . Russia, Canada, and Alaska are the major CH4 regional sources to the atmosphere, responsible for 64%, 11%, and 7% of these net emissions, respectively. Our simulations indicate that large interannual variability in net CH4 emissions occurred over the last century. Our analyses of the responses of net CH4 emissions to the past climate change suggest that future global warming will increase net CH4 emissions from the Pan-Arctic region. The higher net CH4 emissions may increase atmospheric CH4 concentrations to provide a major positive feedback to the climate system. INDEX TERMS: 1610 Global Change: Atmosphere (0315, 0325); 1615 Global Change: Biogeochemical processes (4805); 1620 Global Change: Climate dynamics (3309); 1890 Hydrology: Wetlands; KEYWORDS: methane emissions, methane oxidation, permafrost

Multi-gas assessment of the Kyoto Protocol

The Kyoto Protocol allows reductions in emissions of several ‘greenhouse’ gases to be credited against a CO2-equivalent emissions limit, calculated using ‘global warming potential’ indices for each gas. Using an integrated global-systems model, it is shown that a multi-gas control strategy could greatly reduce the costs of fulfilling the Kyoto Protocol compared with a CO2-only strategy. Extending the Kyoto Protocol to 2100 without more severe emissions reductions shows little difference between the two strategies in climate and ecosystem effects. Under a more stringent emissions policy, the use of global warming potentials as applied in the Kyoto Protocol leads to considerably more mitigation of climate change for multi-gas strategies than for the—supposedly equivalent—CO2-only control, thus emphasizing the limits of global warming potentials as a tool for political decisions.

Probabilistic Forecast for Twenty-First-Century Climate Based on Uncertainties in Emissions (Without Policy) and Climate Parameters

Abstract The Massachusetts Institute of Technology (MIT) Integrated Global System Model is used to make probabilistic projections of climate change from 1861 to 2100. Since the model’s first projections were published in 2003, substantial improvements have been made to the model, and improved estimates of the probability distributions of uncertain input parameters have become available. The new projections are considerably warmer than the 2003 projections; for example, the median surface warming in 2091–2100 is 5.1°C compared to 2.4°C in the earlier study. Many changes contribute to the stronger warming; among the more important ones are taking into account the cooling in the second half of the twentieth century due to volcanic eruptions for input parameter estimation and a more sophisticated method for projecting gross domestic product (GDP) growth, which eliminated many low-emission scenarios. However, if recently published data, suggesting stronger twentieth-century ocean warming, are used to determine...