caused increases in decomposition and long-term emission of CO 2 from grassland soils. Nutrient release associated with the loss of soil organic matter caused.
GRASSLAND
BIOGEOCHEMISTRY:
ATMOSPHERIC
L I N K S TO
PROCESSES
D. S. S C H I M E L 1
NASA Ames Research Center, SLE 239-12, Moffett Field, CA 94035, U.S.A. W. J. P A R T O N
Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, U.S.A. T. G. F. K I T T E L
Natural Resource Ecology Laboratory and Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80523, U.S.A. D. S. O J I M A 2
Natural Resoume Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, U.S.A. and C. V. C O L E
U.S. Department of Agriculture, Agriculture Research Service and Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, US.A.
Abstract. Regional modeling is an essential step in scaling plot measurements of
biogeochemical cycling to global scales for use in coupled atmosphere-biosphere studies. We present a model of carbon and nitrogen biogeochemistry for the U.S. Central Grasslands region based on laboratory, field, and modeling studies. Model simulations of the geography of C and N biogeochemistry adequately fit observed data. Model results show geographic patterns of cycling rates and element storage to be a complex function of the interaction of climatic and soil properties. The model also includes regional trace gas simulation, providing a link between studies of atmospheric geochemistry and ecosystem function. The model simulates nitrogenous trace gas emission rates as a function of N turnover and indicates that they are variable across the grasslands. We studied effects of changing climate using information from a global climate model. Simulations showed that increases in temperature and associated changes in precipitation caused increases in decomposition and long-term emission of CO 2 from grassland soils. Nutrient release associated with the loss of soil organic matter caused increases in net primary production, demonstrating that nutrient interactions are a major control over vegetation response to climate change.
1. Introduction
A central concern of scientists in the area of global biogeochemistry is the integration of field measurements to spatial scales relevant to global issues (Bolin and Cook, 1983). Measurements of rates of biogeochemical processes are typically made from small areas and must be extrapolated to large regions and over long Current address: Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, U.S.A. 2 Current address: IGBP Secretariat, The Royal Swedish Academy, Box 50005, S 10405 Stockholm, Sweden.
Climatic Change 17:13-25, 1990. 9 1990 Kluwer Academic Publishers. Printed in the Netherlands.
14
D.S. Schimel et al. PLANT RESIDUE
C02
/
LN
IVE/~
(~-=y)
A~nual Roinfoll
I \
r~1 DEC
,~q~TEX
~ _ /1 PASSIVE/NI ORGANIC/ /
~
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Fig. 1. Structure of the CENTURY model. Carbon to nitrogen ratios of the soil pools are fixed. Pools which contain both elements are partitioned by a diagonal line. Mineralization occurs when N fluxes into a pool are in excess of the amount required to maintain those ratios and also as a consequence of respiratory losses of carbon during turnover. Turnover times for soil pools are indicated in parentheses. Each carbon transfer occurs at a given efficiency, with a percentage of carbon lost as CO2. These efficiencies are controlled by various environmental factors (e.g., climate, soil texture) and by lignin to N ratio. Temperature and water and nutrient availability control primary production. Controls over rates and efficiencies are noted adjacent to the valve symbols.
time periods for global studies. Regional extrapolation of biogeochemical measurements is especially important for processes controlled by atmosphere-biosphere interactions, since changes in the atmosphere occur at scales inherently larger than ecological plot measurements. Modeling is an essential tool in such endeavors since exhaustive measurement is impractical and direct remote sensing of many ecosystem properties unlikely (Waring et al., 1986). Additionally, predictive models of biogeochemical cycles are required for studies of global ecosystem change, in the same way that general atmospheric circulation models (GCMs) provide an essential tool in studies of future climate change. Such models may be driven by GCM output to evaluate effects of climate change on ecosystem function. We have developed a regional scale model (CENTURY) of the biogeochemical cycling of carbon and nitrogen (Figure 1) for the U.S. Central Grasslands region (Parton et al., 1987). The model builds on the ideas and early data of Hans Jenny Climatic Change August 1990
Grassland Biogeochernistry
15
(1941). CENTURY has also been employed to simulate phosphorus and sulfur cycling (Parton et al., 1988a). While the model is simple enough to predict regional trends in these key ecosystem processes, it is mechanistic enough to explore regional response to climate change. The rationale and validation of the model have been presented elsewhere in detail (Parton et al., 1987, 1988a). In short, model development was supported by a series of process studies (Schimel et al., 1985; Parton et al., 1988b; Schimei et al., 1986; Holland and Coleman, 1987; Schimel, 1986; Pinck et al., 1950), a Soil Conservation Service data base of rangeland productivity and soil organic matter (USDA-SCS, unpublished data), and nitrogen input data from the National Atmospheric Deposition Program (NADP) (NADP/NTN, 1987). Most model parameters were estimated directly from the experimental studies. The climatic dependence of soil organic matter formation parameters was tuned from original 14C estimates by fitting the model to observed data from a climatic transect. The model was then validated at 24 sites. Separate sites were used for estimation and validation. Here we present new model applications examining ecosystem interactions with the atmospheric system via trace gas production and climate change. We also discuss general methodology for development of regional-scale biogeochemical models and their integration with satellite and other geographic data sources. 1.1. Regional Modeling of Grassland Biogeochemistry Soil organic matter is the primary reservoir in grasslands of organic C, N, and, in many cases, P and serves as the source for most plant available macronutrients (Paul and Van Veen, 1978; Stevenson, 1986). A key feature of the CENTURY model is the separation of soil organic matter into three fractions based on their turnover time. These include active, slow, and passive organic matter pools with turnover times of 1-2, 20-50, and 800-1500 years, respectively. The concept of active and slow pools comes from isotope dilution studies (Jansson, 1958; Schimel, 1986), while the existence of a passive fraction is deduced from carbon dating studies (Martel and Paul, 1974). An objective of our research program was to develop a model which would require as few site-specific parameters as possible. As a result, the model only requires information on air temperature, precipitation, soil texture, grazing intensity, and atmospheric nitrogen input. Temperature and precipitation data are extracted from National Weather Service records, soil texture from site-specific data bases or Soil Conservation Service surveys (USDA-SCS, unpublished data), and nitrogen input from the NADP data base (NADP/NTN, 1987). Parameters controlling the simulated rates of C and N flux, including primary production, are calculated from the above data. The model estimates potential primary productivity as a function of rainfall with a monthly time step. Actual productivity is reduced from this level if nutrients are limiting. Nutrient limitation Climatic Change August 1990
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D.S. Schimel et al.
occurs when insufficient N is available to achieve maximal plant C:N ratios. In such cases, net primary production (NPP) is calculated as available N multiplied by the maximum C :N ratio allowed (typically 80-100). Texture exerts control over the stabilization of plant residue carbon into soil organic matter (SOM) (Schimel et al., 1985; Parton et al., 1988b; Schimel, 1986; Pinck et al., 1950) (Figure 1). A higher proportion of plant material is stabilized into SOM in fine-textured soils than in coarse soils. Passive SOM is assumed to be stabilized from slow SOM. This is equivalent to the assumption that rates of old organic matter formation are influenced by both organo-mineral and organic reactions (Stevenson, 1986). As organic matter containing C and N is decomposed, nitrogen is mineralized into an inorganic N compartment and becomes available for plant uptake. Most of this pool is released from active and intermediate SOM pools. In the model, N mineralization occurs simultaneously with microbial uptake (N immobilization). Immobilization is greater during decomposition of organic matter with a high C: N ratio. Rates of microbial activity are driven by temperature and moisture. Plant lignin content is also a major control over decomposition rate, such that increases in lignin content significantly decrease the release of inorganic N. Available data from the Grassland Biome International Biological Program show that while shoot lignin content increases from east to west with increasing aridity, root lignin content decreases. This effect of climate on lignin is incorporated into the model. Herbivores affect N cycling in the model directly by releasing some N directly to the atmosphere as NH 3 and by removing plant N which would have otherwise been immobilized. The significance of grazing was unexpected and was included after initial failure to validate the model. 2. Results
2.1. Simulated Element Storage and Turnover Output from the model includes turnover rates for the state variables shown in Figure 1 and rates of nitrogen gas production, above- and below-ground primary production, and decomposition. Simulated grassland biogeochemical processes showed complex response to dlimatic gradients (Figures 2 and 3). Note that temperature and precipitation trends in the Central Grassland region are roughly orthogonal to each other, with temperature increasing from north to south and precipitation increasing from west to east (Figures 2a, b). Above and belowground production (Figures 3a, b) increased from west to east following the precipitation trend. Maps of decomposition rates show diagonal isograms, increasing towards the southeast (Figures 3c, d). Decomposition rates were influenced by both temperature and moisture and responded to the regional lignin gradient. Soil organic carbon levels reflected contrasting regional patterns of C input (production) and output (decomposition) and thus increased from southwest to Climatic Change August 1990
Grassland Biogeochemistry
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80
~o
IOO
12
3
8O
Fig. 2. Climateof the Central Grasslands.(a) Mean annual precipitation (cm). (b) Mean annualtemperature (~ The maps are based on monthlydata fromsix hundredand fortystations.
northeast (Figure 3e). Soil organic carbon and nitrogen levels varied with texture; C and N values for fine textured soils are shown in Figures 3e and f, respectively. Coarse textured soils showed the same regional pattern but had lower values. The spatial patterns of soil organic carbon and nitrogen for the 0 to 20 cm layer (Figures 3e, f) were highly correlated with one another, and, in fact, soil C :N ratios vary only slightly about a mean of 11 throughout the region (Parton et al., 1987). Soil organic nitrogen storage is also a function of inputs and losses: N inputs were highly correlated with precipitation, increasing from west to east, while losses were related to trace gas emission. 2.2. Regional Trace Gas Emission Nitrogenous trace gas (N20 , NH3, NO) production is simulated in CENTURY because it is significant in the long term to ecosystem nitrogen balance. In addition, trace gases are significant modifiers of the global atmospheric energy balance (Ramanathan et al., 1987; Bowden, 1986; Dickinson and Cicerone, 1986). Oxidized N and N 2 emission is modeled as a by-product of inorganic N turnover and, in the Central Grasslands, appears to be primarily a product of nitrification (Parton et al., 1988b; Robertson and Tiedje, 1987). The model lumps N20 , N2, and, potentially, NO together. Current data indicate that N20 production is greater than N 2 production in the semiarid grasslands (Parton et al., 1988b). Simulated N losses from nitrification and denitrification varied geographically with N turnover rate, increasing from west to east (Figure 3g). Because very few annual budgets exist for N effiux in grasslands, these trace gas emission rates are difficult to validate and may be somewhat high. Herbivores are assumed in the model to consume about 40% of aboveground biomass N on an annual basis, of which 20% is lost to the atmosphere as NH 3 (Schimel et al., 1986). Consumption and loss are calculated monthly. Plant N content also influences the rate of herbivore mediated N loss. Simulated NH 3 fluxes ClimaticChangeAugust 1990
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D.S. Schimel et al.
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Climatic Change'August 1990
6 .8
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Grassland Biogeochemistry
19
(Figure 3h) increased from west to east reflecting a general increase in plant biomass and N content from west to east. N loss increased eastward because of higher aboveground N amounts consumed by herbivores. No data exist to validate these results. 2.3. Effects of Climate Change We simulated effects on grassland biogeochemistry of changing climate over 50 years (transient case) and of a new equilibrium climate for 500 years using output from the Goddard Institute for Space Studies G C M for a CO2-doubling climate experiment (Rind and Lebedeff, 1984; Hansen et al., 1984). For the transient case, we simulated two locations in adjacent GCM grid squares centered on 4 3 ~ 100 ~W and 35.2 ~ N 100 ~ W, respectively. Temperature and precipitation changes between i x CO 2 and 2 x CO2 equilibrium simulations were applied to contemporary climate data from stations located near grid centers. Both grid cells had annual temperature increases on the order of 4 ~ Changes in temperature were not applied uniformly throughout the year, but were rather varied monthly based on seasonal results from the GCM. Precipitation changes were based on seasonal results presented in Rind and Lebedeff (1984). Annual precipitation increased in the northern grid cell by 7.7% relative to current levels and decreased in the southern by 3.5%. We formed a transient climate change time series by applying the GISS-predicted change incrementally to the current climate field using a linear ramp over 50 years. Grazing was assumed to consume a constant fraction of aboveground NPE No direc{ effects of CO 2 on plant growth were simulated. These were omitted because insufficient data exist to quantify plant response over the study region. However, changes in ratios of carbon fixed to water and nitrogen used in response to increasing atmospheric CO2 concentration could produce vegetation with reduced litter quality (i.e., wider C :N ratios). This would cause plant available N to decline in response to increased uptake by microorganisms decomposing plant litter and would act as a negative feedback to NPR We plan sensitivity analyses of potential effects of increasing [CO2] via changes in water and N use efficiencies. Note that the region of the simulation is dominated by C 4 species. Since C 4 and C 3 species
Fig. 3. Simulated geography of ecosystem processes for the Central Grasslands. Estimates and pool sizes are for grazed grassland vegetation (potential vegetation) and do n o t represent the conditions that would apply in cultivated areas within the region. Simulation of cultivated conditions is in progress. (a) Regional patterns of aimual a b o v e g r o u n d plant production. Units are g biomass 9 m -2 9 yr -1. ( b ) A n n u a l belowground (root) production. Units are g biomass 9 m -z 9 yr -1. (c) A n n u a l d e c o m p o s i t i o n rate for aboveground plant residue. Units are fraction lost per year. (d) A n n u a l root d e c o m p o s i t i o n rate. U n i t s are fraction lost p e r year. (e) Soil organic c a r b o n storage for fine textured soils. U n i t s are kg C 9 m - 2 to 20 c m depth. (f) Soil nitrogen storage in fine textured soils. Units are kg N 9 m - 2 to 20 cm depth. (g) A n n u a l losses of trace gases ( N 2 0 , N 2 and possibly NO). Units are g N 9 m -2 9 yr -a. (h) A n n u a l N H 3 losses from herbivore excreta. Units are g N 9 m -2 9 yr-1. Climatic C h a n g e A u g u s t 1990
20
D.S. Schimel
et
al.
have differing water and N use efficiencies, changes in grassland species composition could modify the conclusions we reached in the current exercise. Aboveground NPP increased in both grid cells during transient climate change (Figure 4A). This increase was greater in the northern cell. Increasing temperatures resulted in higher rates of soil organic matter (SOM) decomposition, with accompanying increases in N availability (by 10 and 20% in the north and south, respectively) for plant growth. The increase in NPP in the southern cell was due to this increase in N availability, while the larger increase in the north reflected both N and rainfall effects. Soil organic carbon storage decreased in both sites (Figure 4B) producing a net release of CO 2 to the atmosphere. We also conducted 500-year simulations to examine long-term effects of altered climate. These long-term simulations are of particular interest given the slow turnover of organic matter in grasslands. We simulated 2 ~ and 4 ~ increases using a A I10
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Fig. 4. (A) Annual aboveground net primary productivity (g C 9 m -2 9 y r - 1 ) and (B) soil organic carbon storage to 20 cm depth (g C 9 m 2) during simulated transient climate change. Two grassland sites were simulated, northern (N) and southern (S), in adjacent-7.8~ x 10 ~ (latitude x longitude) G C M grid cells. Mean annual temperatures were linearly increased over 50 years by 4 ~ Annual precipitation was similarly increased over the period by 7.7% for the northern site and decreased by 3.5% for the southern site. These climatic changes were applied on a monthly basis according to the predicted seasonal distribution of temperature and precipitation changes (see text). Note the break in the ordinate in (B) to allow both sites to be plotted in the same figure. Climatic Change August 1990
21
Grassland Biogeochemistry 72
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50-year linear ramp to constant climate and then held climate constant. Precipitation was left unchanged. NPP increased initially (Figure 5A), but declined as soon as climatic forcing stabilized. The larger increase in NPP in the +4 ~ scenario was due to the larger amount of N released as the result of higher decomposition rates under higher temperatures. After climate stabilized, nutrient availability declined as nutrient loss and sequestration in organic matter became dominant over mineralization. Soil organic carbon (Figure 5B) declined by about 10% but did not reach steady state by the end of the simulation. Simulated SOM levels were not expected to reach steady state in 50i? years, given that the passive fraction (Figure 1) turns over in 800 to 1500 years. We also estimated the effect of temperature on steady state SOM from the regional maps (Figures 2b and 3e). Changes in steady state soil organic carbon corresponding to +4 ~ changes in mean annual temperature were as high as 20%. While climate change produced a transient increase in NPR a decrease in carbon storage resulted in negative net ecosystem production-(NEP) in all simulations. The geographic correlation between SOM levels and climate supports the prediction that SOM levels will adjust in the long term as climate changes. However, the exisClimatic Change August 1 9 9 0
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D.S. Schimelet al.
tence of soil organic matter compartments with 100-1000 year lifetimes (Parton et al., 1987; Balesdent and Mariotti, 1987) implies non-steady state ecosystem responses during and following climatic transients. Simulation results illustrate how climate change effects on NPP and carbon storage can depend upon interactions with decomposition and nutrient cycling. 3. Dicussion
The CENTURY model predicts reasonable patterns of biogeochemical cycling across the Central Grassland region. Where data exist to validate these regional patterns (e.g., for primary productivity and soil organic carbon and nitrogen), the model performs well (Parton et al., 1987). Though developed for North American grasslands, this model should be widely applicable to grasslands and agroecosystems worldwide. The model is composed of several submodels, each of which constitutes a statement of a hypothesis concerning the regulation of the biogeochemical cycling of C and N. The model can be used to test these hypotheses regarding the geography of organic matter dynamics and trace gas production from grasslands. The development of ecosystem models for regional extrapolation requires several steps. First, driving variables need to be identified for the processes of interest. Second, relationships between driving variables and rates of processes must be quantified. Third, the geography of the driving variables must be determined. In the future, we see remote sensing and other advanced measurement technologies playing an increasingly important role at this step. Finally, a regional simulation model can be developed. If environmental gradients in variables that have large effects on processes have been identified, much of the spatial variability in rates of processes can be simulated. This approach provides a mechanism for extrapolating from process measurements typically conducted in the laboratory or using small field experiments to regions thousands or millions of hectares in area. Forest and watershed modelers have used similar approaches (Pastor and Post, 1986; Aber e t al., 1982). The approach is robust regionally because it links key processes to independent variables with strong spatial gradients, minimizing spatial error. However, application of this approach is often limited by the lack of data on the geography and spatial variance structure of driving variables. In addition, regional models are not readily falsifiable with current technology. Lack of techniques for measurement of soil and nutrient parameters over large spatial scales may impose the most severe restriction to rapid progress. Forcing the model with climatic data yielded two significant results. First, effects of climate on heterotrophic processes influencing decomposition and nutrient cycling will mediate plant response to changing climate. Despite increased NPP during the transient phase of such response, simulated climate change resulted in net carbon loss and hence net release of CO 2 to the atmosphere. Second, simulated Climatic ChangeAugust 1990
Grassland Biogeochemistry
23
production of trace gases across the Central Plains region indicates that production rates may vary geographically by more than a factor of two within this biome. Variations were most closely related to precipitation patterns and were less correlated with temperature. Most current models of land surface interactions with the atmosphere assume that vegetation is controlled by biophysical response to light, water, and temperature (Sellers et al., 1986; Dickinson, 1984; Wilson et al., 1987). We suggest that nutrient availability is an additional control, especially during periods of rapid climate change. Spatial variability in nutrient cycling as a result of soil texture and other factors will introduce complexity in land surface processes at GCM grid and sub-grid scales which could influence atmospheric dynamics (Avissar and Pielke, 1989; Segal et aL, 1988). This study suggests that simulation modeling can be successfully undertaken at the regional scale. Models that are mechanistic enough to simulate effects of changing climate or atmospheric chemistry form a second generation of large-scale biogeochemical models following static budget models (Gildea et al., 1986; Vorosmarty et al., 1986; Houghton et al., 1983; Detwiler, 1986). This type of model will be an essential tool in the study of global change. Preliminary results indicate a complex response of the plant-soil-microorganism system to climate change.
Acknowledgements We acknowledge the scientific and editorial assistance of Klaus Flach, Caroline Yonker, John Stewart, William Lanenroth, Ingrid Burke, Frank Davis, and Carol Taylor. Steven Holzhey of the U.S. Soil Conservation Service provided access to the soils data base. David Rind of the Goddard Institute for Space Studies made their GCM results available to us. This research has been supported by NASA (FIFE) and NSF grants and the U.S. Soil Conservation Service and Agricultural Research Service.
References Aber, J. D., Melillo, J. M. and Federer, C. A.: 1982, 'Predicting the Effects of Rotation Length, Harvest Intensity and Fertilization on Fiber Yields from Northern Hardwood Forests in New England', Forest ScL 28, 31-45. Avissar, R. and Pielke, R. A.: 1989, 'A Parameterization of Heterogeneous Land Surfaces for Atmospheric Numerical Models and Its Impact on Regional Meteorology', Mon. Wea~Rev. 117, 21132136. Balesdent, J. and Mariotti, A.: 1987, 'Natural ~3C Abundances as a Tracer for Studies of Soil Organic Matter Dynamics', SoilBio. Biochem. 19, 25-30. Bolin, B. and Cook, R.B. (eds.): 1983, The Major Biogeochemical Cycles and Their Interactions. SCOPE 21, Edited by R G. Risser, John Wiley and Sons, New York; ICSU Press, Paris, France. Bowden, W.B.: 1986, 'Gaseous Nitrogen Emissions from Undisturbed Terrestrial Ecosystems: An Assessment of Their Impacts on Local and Global Nitrogen Budgets', Biogeochernistry 2, 249-280.
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Detwiler, R. E: 1986, 'Land Use Changes and the Global Carbon Cycle: The Role of Tropical Soils', Biogeochemistry 2, 67-94. Dickinson, R.E.: 1984, 'Modelling Evapotranspiration for Three-Dimensional Global Climate Models', in J. E. Hansen and T. Takahashi (eds.), Climate Processes and Climate Sensitivity. Geophysical Monograph 29, American Geophysical Union, Washington D.C., pp. 58-72. Dickinson, R. E. and Cicerone, R. J.: 1986, 'Future Global Warming from Atmospheric Trace Gases', Nature 319, 109-115. Gildea, M. E, Moore, B., and Vorosmarty, C. J.: 1986, ~ Global Model of Nutrient Cycling: I. Introduction, Model Structure and Terrestrial Mobilization of Nutrients', in D. L. Correll (ed.), Watershed Research Perspectives. Smithsonian Institution Press, Washington, D.C., pp. 1-31. Hansen, J., Lacis, A., Rind, D., Russell, G., Stone, E, Fung, I., Ruedy, R., and Lerner, J.: 1984, 'Climate Sensitivity: Analysis of Feedback Mechanisms', in J. E. Hansen and T. Takahashi (eds.), Climate Processes and Climate Sensitivity. American Geophysical Union, Washington, D.C., pp. 130-163. Holland, E. A. and Coleman, D. C.: 1987, 'Litter Placement Effects on Microbial and Organic Matter Dynamics in an Agroecosystem', Ecology 68, 425-433. Houghton, R. A., Hobbie, J. E., Melillo, J. M., Moore, B., Peterson, B. J., Shaver, G. R., and Woodwell, G.M.: 1983, 'Changes in the Carbon Content of Terrestrial Biota and Soils Between 1860 and 1980: A Net Release of CO 2 to the Atmosphere', EcoL Monogr. 53,235-262. Jansson, S. L.: 1958, 'Tracer Studies on Nitrogen Transformations in Soil with Special Attention to Mineralization-ImmobilizationRelationships', Lantsbrukshogs-Kolans Annaler 24, 101-361, Ann. Roy. Agr. Coll. Sweden. Jenny, H.: 1941, 'Factors of Soil Formation', McGraw-Hill, New York, N.Y. Martel, Y. A. and Paul, E. A.: 1974, 'Effects of Cultivation on Organic Matter of Grassland Soils as Determined by Fractionation and Radio-Carbon Dating', Can. J. Soil Sci. 54,419-426. National Atmospheric Deposition Program/National Trends Network: 1987, Precipitation Weighted Average Report: Fall 1978-Spring 1986, National Atmospheric Deposition Program, 15 pp. Parton, W. J., Schimel, D. S., Cole, C. V., and Ojima, D. S.: 1987, ~nalysis of Factors Controlling Soil Organic Matter Levels in Great Plains Grasslands', Soil Sci. Soc. Amen J. 51 (5), 1173-1179. Patton, W. J., Stewart, J. W. B., and Cole, C. V.: 1988a, 'Dynamics of C, N, P and S in Grassland Soils: A Model', Biogeochemistry 5, 109-131. Parton, W. J., Mosier, A. R., and Schimel, D. S.: 1988b, 'Rates and Pathways of Nitrous Oxide Production in a Shortgrass Steppe', Biogeochemistry 6, 45-58. Pastor, J. and Post, W. M.: 1986, 'Influence of Climate, Soil Moisture and Succession on Forest Carbon and Nitrogen Cycles', Biogeochemistry 2, 3-27. Paul, E. A. and Van Veen, J.: 1978, 'The Use of Tracers to Determine the Dynamic Nature of Organic Matter', Trans. ll th Int. Congr. Soil Science 3, 61-102. Pinck, L. A., Allison, E E., and Sherman, M. S.: 1950, 'Maintenance of Soil Organic Matter: II. Losses of Carbon and Nitrogen from Young and Mature Plant Material During Decomposition in Soil', Soil Science 69, 391-401. Ramanathan, V., Callis, L., Cess, R., Hansen, J., lsaksen, I., Kuhn, W., Lacis, A., Luther, E, Mahlman, J., Reck, R., and Schlesinger, M.: 1987, 'Climate-Chemical Interactions and Effects of Changing Atmospheric Trace Gases', Rev. Geophys. 25, 1441-1482. Rind, D. and Lebedeff, S.: 1984, Potential Climatic Impacts of Increasing Atmospheric C02 with Emphasis on Water Availability and Hydrology in the United States. EPA Report, NASA Goddard Space Flight Center, Institute for Space Studies, New York, NY, 96 pp. Robertson, G.P. and Tiedje, J.M.: 1987, 'Nitrous Oxide Sources in Aerobic Soils: Nitrification, Denitrification, and Other Biological Processes', Soil Biol. Biochem. 19, 187-194. Schimel, D.S.: 1986, 'Carbon and Nitrogen Turnover in Adjacent Grassland and Cropland Ecosystems', Biogeochemistry 2, 345-357. Schimel, D. S., Coleman, D. C., and Horton, K. A.: 1985, 'Soil Organic Matter Dynamics in Paired Rangeland and Cropland Toposequences in North Dakota', Geoderma 36,201-214. Schimel, D. S., Parton, W. J., Adamsen, E J., Woodmansee, R. G., Senft, R. L., and Stillwell, M. A.: 1986, 'The Role of Cattle in the Volatile Loss of Nitrogen from a Shortgrass Steppe', Biogeochemistry 2, 39-52. Segal, M., Avissar, R., McCumber, M. C., and Pielke, R. A.: 1988, 'Evaluation of Vegetation Effects on the Generation and Modification of Mesoscale Circulations" J. Atmos. Sci. 45, 2268-2392. Climatic Change August 1990
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Sellers, E J., Mintz, Y., Sud, Y. C., and Dalcher, A.: 1986, ~k Simple Biosphere (SiB) Model for Use Within General Circulation Models; J. Atmos. ScL 43, 505-531. Stevenson, E J.: 1986, Cycles of Soil Carbon, Nitrogen, Phosphorus, Sulfur, and Micronutrients. John Wiley and Sons, New York. USDA-Soil Conservation Service. National Soil Survey Laboratory, Midwest National Technical Center, Lincoln, Nebraska, unpublished data. Vorosmarty, C. J., Gildea, M. E, and Moore, B.: 1986, 7k Global Model of Nutrient Cycling: II. Aquatic Processing, Retention and Distribution of Nutrients in Large Drainage Basins', in D. L. Correll (ed.), Watershed Research Perspectives. Smithsonian Institution Press, Washington, D.C., pp. 32-56. Waring, R. H., Aber, J. D., Melillo, J. M., and Moore, lII, B.: 1986, 'Precursors of Change in Terrestrial Ecosystems', Bioscience 36,433-438. Wilson, M. E, Henderson-Sellers, A., Dickinson, R. E., and Kennedy, R J.: 1987, 'Sensitivity of the Biosphere/Atmosphere Transfer Scheme (BATS) to the Inclusion of Variable Soil Characteristics; J. Climate Appl. Meteor. 26, 341-362. (Received 18 July, 1988; in revised form 8 September, 1989)
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