Manual century

The fraction of labile P that is available for plant uptake varies from 0. As more P is removed through plant and soil microbial uptake, larger amounts become immobilized in organic matter. The sorption affinity parameter controls the fraction of the labile plus sorbed pools which is in the labile pool at low levels of P in these pools.

The sorption maximum is the maximum amount of P which can be in the sorbed P pool. The sorption maximum controls the curvature of the relationship between labile P and the sum of the labile and sorbed P pools.

The rate of these P flows are all multiplied by the same moisture and temperature functions DEFAC that are used for organic matter decomposition. The organic part of the P submodel operates in the same way that the N submodel works; C:P ratios of organic fractions are fixed for the structural P pool and vary as a function of the labile P pool PLABIL for the active , slow , and passive SOM pools.

C:P ratios of newly formed surface microbes are functions of the P content of the material decomposing, and the C:P ratio of slow material formed from the surface microbes is a function of the C:P ratio of surface microbes. The flows for the organic P pools are calculated in exactly the same way as organic N flow. P additions come from P fertilizer and organic matter additions see parameters in the fert.

The structure of the sulfur submodel Figure is similar to the P submodel. The only major difference is that the S model does not include occluded or sorbed pools. The main source of S in most soils is the weathering of primary minerals. Secondary S is formed as a result of adsorption of S on clay minerals.

The organic component of the S model operates in the same way as the organic N and P submodels with the C:S ratio of the structural pool being fixed while the C:S ratios for the active , slow and passive pools vary as a function of the labile S pool MINERL 1,3.

The C:S ratios for the organic components are specified in the file fix. The model allows for S fertilization, addition of organic S material see parameters in the fert. The S submodel has not been as well tested as the N and P submodels. Parton et al. The S model could be set up to simulate K dynamics instead of S dynamics if K is a limiting factor in particular soils. Existing crop options may be altered to suit particular varieties or environments or new options created using the FILE program.

Harvest, grazing, fire and cultivation can all directly effect aboveground biomass, while grazing and fire may also impact root to shoot ratios and nutrient content.

The forest model simulates the growth of deciduous or evergreen forests in juvenile and mature phases. Fire, large scale disturbances e. Both plant production models assume that the monthly maximum plant production is controlled by moisture and temperature and that maximum plant production rates are decreased if there are insufficient nutrient supplies the most limiting nutrient constrains production.

The fraction of the mineralized pools that are available for plant growth is a function of the root biomass with the fraction of nutrients available for uptake increasing exponentially as live root biomass increases from 20 to gm The savanna model modifies maximum grass production by a shade modifier that is a function of tree leaf biomass and canopy cover.

Additional nutrient constraints on plant production due to nutrient allocation between trees and grasses decrease maximum production rates for the grasses. The model can simulate a wide variety of crops and grasslands by altering a number of crop specific parameters see Appendix 2 for the crop.

CENTURY is not designed to be a plant production model and some parameters may have to be calibrated for specific environments. The plant production model Figure has pools for live shoots and roots, and standing dead plant material. The maximum potential production of a crop, unlimited by temperature, moisture or nutrient stresses, is primarily determined by the level of photosynthetically active radiation, the maximum net assimilation rate of photosynthesis, the efficiency of conversion of carbohydrate into plant constituents, and the maintenance respiration rate van Heemst, Thus, the parameter for maximum potential production PRDX 1 has both genetic and environmental components.

However, in CENTURY, the seasonal distribution of production is primarily controlled by the temperature response function rather than the seasonal variation in photosynthetically active radiation, so the maximum potential production parameter should reflect aboveground crop production in optimal summer conditions. This parameter will frequently be used to calibrate the predicted crop production for different environments, species, and varieties. In the CENTURY model formulation the potential production is based on aboveground production, therefore root-shoot allocation must also be taken into account.

The value used should be set according to estimates of potential crop production. In general, C4 species have higher potential growth rates than C3 species because of higher maximum net assimilation rates van Heemst, The growth of most plant species exhibits a response curve to root temperature which is sigmoidal up to an optimum temperature, has a band of optimum temperatures over which there is relatively little effect on growth, and a rapid decline above the optimum Cooper, Plant growth rates will depend on the combined temperature response of photosynthesis and respiration.

For most temperate species the lower limit at which the rate of development is perceptible is between zero and 5 C. Development increases in rate up to an optimum of 20 to 25 C and then declines to an upper limiting temperature between 30 and 35 C. For tropical species the base, optimum and maximum temperatures are approximately 10 higher Monteith, The moisture status effect reduces growth when The slope of the linear relationship is dependent on the available soil water holding capacity, which varies with soil texture Figure This effect of soil texture has been observed in field data Sala et al.

The shading effect on potential growth rate is a response surface dependent on the amounts of live and dead vegetation. This function, which was originally developed for the tall grass prairie, was found to be too restrictive for no-till cropping systems. Therefore, the magnitude of the effect has been greatly reduced for crops by increasing the value of BIOK5 crop. Root growth is proportional to potential shoot growth, but the allocation of carbon to root growth can be made a function of time since planting FRTC The actual production is limited to that achievable with the currently available nutrient supply with plant nutrient concentrations constrained between upper and lower limits set separately for shoots and roots.

The limits of nutrient content for shoot growth are a function of plant biomass in order to reflect the changing nutrient content with plant age Figure This formulation does cause some anomalies when growth is limited by nutrients, as a nutrient limited crop can have a higher nutrient concentration than an unlimited crop of the same age with greater biomass.

It is assumed that plant available soil N will be preferentially used by the crop. All other potential limitations to growth, including P and S supply, are taken into account before calculating symbiotic N2 fixation. At harvest, grain is removed from the system and live shoots can either be removed or transferred to standing dead and surface residue.

Moisture stress is calculated as the ratio of actual to potential transpiration in these months. The crop harvest routine also allows for the harvest of roots, hay crops or straw removal after a grain crop see harv. The crop may be killed at harvest, as for cereal grain crops, or a fraction of roots and shoots may be unaffected by harvest operations and growth may continue. The crop model allows for the death of shoots and roots during the growing season.

Shoot and root death are functions of available soil water in the whole profile and the plant root zone respectively Figure Root death is only allowed to occur when roots are physiologically active, defined by soil temperature being greater than 2 C RTDTMP, crop.

They should reflect the lignin content of senescent plant material. The effects of grazing and fire on plant production are represented in the model by using data from Holland et al.

Grazing removes vegetation, returns nutrients to the soil, alters the root to shoot ratio, and increases the N content of live shoots and roots Holland et al.

The root:shoot ratio is constant for low to moderate grazing levels and decreases rapidly for heavy grazing levels.

The forest plant production model Figure divides the tree into leaves, fine roots, fine branches, large wood, and coarse roots with carbon and nutrients allocated to the different plant parts using a fixed allocation scheme. Maximum monthly gross production is calculated as the product of maximum gross production rate PRDX 2 , tree. The effect of moisture and temperature on potential productions are the same functions used for the monthly grassland model Figures and , while the effect of live leaf-area-index on production is shown in Figure Plant respiration is calculated as a function of wood N content and temperature using an equation developed by Ryan and subtracted from the gross production rate in order to get the net potential production rate.

The net potential production rate is not allowed to exceed the tree specific maximum net production rate PRDX 3 times the other limiting factors. The model assumes that only the sapwood part of the tree respires C and the sapwood fraction of aboveground large wood biomass is calculated using the relationship shown in Figure The same sapwood fraction is used for coarse woody roots Ryan, The leaf biomass is not allowed to exceed a maximum value that is a function of the live wood biomass Figure This function specifies the effect of tree allometry and structure on maximum leaf area and is potentially different for different species.

The model has two carbon allocation patterns for young and mature forests and can represent either deciduous forests or forests that grow continuously. With a continuous growth or evergreen forest the death of the live leaves is specified as a function of month LEAFDR , tree. For deciduous forest the leaf growth rate is also much higher during the first month of leaf growth. Dead leaves and fine roots are transferred to the surface and root residue pools and are then allocated into structural and metabolic pools.

Dead fine branch, large wood, and coarse root pools receive dead wood material from the live fine branch, large wood, and coarse root pools respectively. Each dead wood pool has a specific decay rate. The dead wood pools decay in the same way that the structural residue pool decomposes with lignin going to the slow SOM pool and the non-lignin fraction going to surface microbes or active SOM pool above- or belowground material.

The decay rates of the dead wood pools are also reduced by the temperature and moisture decomposition functions, and include CO2 losses. A forest removal event, which is defined in the trem. For each disturbance or harvest event, the fraction of each live plant part lost and the fraction of material that is returned to the soil system is specified see trem. Death of fine and coarse roots are also considered in the removal event along with the removal of dead wood.

Another feature is that the nutrient concentration of live leaves that go into surface residue can be elevated above the dead leaf nutrient concentration e. The fundamental difference in the savanna submodel is the manner in which total system production is obtained.

Total system production is the sum of forest and grass production. Potential maximum production of forest is computed in the manner described above. Increasing canopy cover and leaf biomass reduces the potential grass production.

In the present model, fire does not influence tree distribution and establishment. Nitrogen competition is the other major interaction between the forest and grass systems. The interaction is controlled by the amount of tree basal area, total nitrogen available, and site potential for plant production. The fraction of N available for tree uptake is calculated as a function of tree basal area m2 ha-1 and available mineral N using the function shown in Figure The fraction of N uptake by grass is one minus the forest fraction and if grass N uptake did not consume all of the N allocated to it, this amount is added to the pool of N which is available to the trees.

The automatic option can be set to maintain crop growth at a particular fraction of potential production with the minimum nutrient concentration 0. Organic matter additions are specified in omad. Automatic irrigations are scheduled if the available water stored in the plant root zone falls below a nominated fraction of the available water holding capacity FAWHC, irri.

The amount of water applied by the automatic option allows for the addition of a nominated amount of water IRRAUT, irri. Thus the model can simulate a variety of conventional cultivation methods, such as plowing or sweep tillage, thinning operations or herbicide application. The values for these parameters range from 1. As discussed above in Section 3. The effect of different intensities of fire in herbaceous vegetation can be parameterized by specifying the fractions of live shoots FLFREM, fire.

C labeling is specified in the. The c14data file contains a record of atmospheric 14C concentrations which are used by the model to label new plant material, which then flows through the other organic matter pools.

Simulations using the option for 13C give a constant label to plant material based on the value of DEL13C in the crop. This option will primarily be of use to follow the change in stable isotope signal when there has been a switch from C3 to C4 vegetation or vice-versa. Fractionation of the stable carbon isotopes is included in the model as discussed below. The magnitude and direction of the change in the ratio may vary with time and the prevailing environmental conditions Stout and Rafter, ; Stout et al.

Atmospheric CO2, plant material, and soil organic matter are depleted in 13C relative to the standard and therefore have negative delta 13C values. The more depleted in 13C a material is, the more negative the delta 13C value will be. Stout et al. The first takes place during photosynthesis with plant tissue being depleted in 13C relative to atmospheric CO2. Of considerable interest is the difference in delta 13C between plants with different photosynthesis pathways Bender, ; Smith and Epstein, This difference in stable carbon isotope signature can be used as a tracer for in situ labelling of soil organic matter when the dominant vegetation type has changed from C3 to C4 species or vice-versa Cerri et al.

The CENTURY model has been modified to partition carbon production by plants to the two isotope pools on the basis of a delta 13C value nominated in the crop.

The second major biological fractionation occurs in the synthesis of the major cell components Stout et al. The data of Benner et al. They observed a greater depletion of 13C in grass lignins than in wood lignins, which they attributed to different amino acid precursors. In the CENTURY model this fractionation in the partitioning of plant material shoots and roots from crops and grasses, and leaves and fine roots from trees to the structural and metabolic pools is accounted for as all of the plant lignin is assumed to enter the structural pool.

Because all dead wood and large tree roots enter dead wood pools, which are analogous to the structural pool, there was no need to account for 13C fractionation in wood lignin. The third major biological fractionation of carbon noted by Stout et al.

This is not accounted for this in the model because the important comparison for the CENTURY model is between delta 13C levels in feces and plant material.

The fourth major biological fractionation of carbon takes place during microbial metabolism Stout et al. Macko and Estep examined the isotopic composition of an aerobic, heterotrophic bacteria growing on a variety of amino acid substrates.

With most of substrates the bacterial cells were enriched in 13C relative to the amino acid. They suggested that the CO2 respired during the Krebs cycle would be isotopically depleted in 13C. However, in an anaerobic environment methane evolved is very depleted in 13C relative to the organic substrate, but the CO2 evolved is enriched Games and Hayes, The net effect on the residual organic matter would depend on the relative size of the fluxes. Environmental effects on fractionation are also reflected in different patterns of stable isotope distribution in soil profiles Stout and Rafter, In well-drained mineral soils delta 13C values increase slightly with depth and soil age, which is consistent with respired CO2 being slightly depleted in 13C.

In organic soils where decomposition is inhibited the delta 13C values decrease with depth. This could be due to the loss of readily decomposable plant fractions, such as sugars and proteins, with an accumulation of lignin, lipids and waxes in the residual plant material, resulting in depletion of 13C relative to the original plant material Stout et al.

In other soils, with intermediate levels of drainage and organic matter accumulation, there may be no change in delta 13C values with depth indicating a balance between fractionation due to respiration and accumulation of the depleted plant fractions.

The coefficient for isotope discrimination was calibrated to give a slight increase in the delta 13C value for the total soil organic matter relative to the vegetation.

The model was also enhanced to include the effects of documented changes in atmospheric CO2 and thus predict the effects on crop production. The direct effects of an increase in atmospheric CO2 concentration on soil processes will be insignificant because the CO2 concentration in the soil atmosphere is already greatly elevated.

However, the indirect effects on SOM mediated through effects on plant processes could be substantial and must be accounted for in simulations of the effect of global change on SOM Long, Net primary production, litter quality, and transpiration are all likely to be affected. Generally, the plant dry matter response to increasing rates of CO2 can be approximated with a logarithmic response function Gifford, ; Goudriaan, : where NPPE and NPP0 refer to net primary production in enriched and control CO2 environments respectively.

Beta is an empirical parameter which ranges between 0 and approximately 0. The response to CO2 is not simply due to the removal of a single limiting factor Sinclair, , but results from a hierarchy of effects Acock, First, increasing CO2 has a direct effect on C availability by stimulating photosynthesis and reducing photorespiration. There is a very important difference between C3 species, such as wheat, and C4 species, such as corn, in this response. With wheat, a growth response to elevated CO2 is almost invariably obtained Kimball, ; Cure and Acock, Corn sometimes shows no response to CO2 Hocking and Meyer, b.

The main reason for responses to CO2 in C4 species is due to improved water use efficiency as discussed below. The second effect of increased CO2 concentrations is a decrease in stomatal conductance Moss et al. Reduced transpiration will also increase the leaf temperature which can further increase photosynthesis Acock, The effect on stomatal conductance and transpiration is observed in both C3 and C4 species.

Both an increase in photosynthesis and a decrease in transpiration result in an increase in the plant's water use efficiency. Clearly with a fixed nutrient supply, an increase in C assimilation is likely to result in lower plant nutrient concentrations due to a dilution effect, but this is not the only effect.

However, CO2 had little effect on the relationship between relative yield and the external N concentration. A practical implication of this is that similar fertilizer application rates will still allow near maximum yields under a high CO2 environment, but that more fertilizer may be required to maintain similar grain protein concentrations Hocking and Meyer, b.

Physiologically, an increase in N use efficiency in C3 species with elevated CO2 has been related to decreased concentrations of the enzyme ribulose 1,5-bisphosphate carboxylase Schmitt and Edwards, which catalyses the initial carboxylation reaction in C3 species and accounts for a large proportion of the leaf protein. A fourth effect of increased CO2 on plant growth which affects SOM levels is an increase in root growth.

Most studies with elevated CO2 with grain crops in which root growth has been measured show very little or no effect on the root to shoot ratio Cure and Acock, The various effects of CO2 described above are controlled by functions of the CO2 concentration and crop or tree specific parameters in crop.

Parameter values are set using reference concentrations of and ppm CO2 for ambient and doubled CO2 respectively. See Figure A linear relationship of this effect with CO2 concentration is assumed. The model can be set up to simulate litter bag decomposition and soil incubations at constant temperature and soil moisture. The incubation option will simulate the dynamics of soil organic matter and surface or buried litter under constant soil temperature and soil water conditions.

Changes in carbon levels and nutrient mineralization can be simulated for laboratory incubations using this option. Incubation of the soil occurs in a similar manner by initializing all of the soil variables. Some of the options include fertilization, cultivations mixing of the soil and the addition of new labeled or unlabeled plant material during the incubations.

Plant growth does not occur during the incubation. Microcosm simulation is specified in the. For each block in the simulation, EVENT allows the user to choose between four options for weather data.

The first option uses the mean values for each month in every year of the block simulation. The second option uses the mean monthly temperature values in every year and stochastically generates precipitation from a skewed distribution Nicks, If skewness parameters are unavailable, a truncated normal distribution is used but this will increase the overall mean precipitation when the coefficient of variation for precipitation is high.

The third option reads the monthly values for precipitation, minimum and maximum air temperature from the start of a weather data file, while the fourth option will continue reading from the same file without rewinding. If a monthly value is missing from an actual weather file, it should be set equal to the value " Because CENTURY uses a monthly timestep and incorporates both continuous events such as crop growth and decomposition, and discrete events such as fertilizer addition, cultivation and harvest, it is necessary to set a priority order for calls to the model's subroutines Figure This is also necessary because the combined effect of subroutines on the changes in pool sizes can be large relative to the amount present and negative overflows would otherwise be a problem.

Furthermore, because of the importance of nutrient availability to immobilization in organic matter, and the limitation that immobilization can place on the rate of organic matter decomposition, the decomposition and soil nutrient routines have a timestep of one quarter of a month.

Most of the internal parameters in CENTURY were determined by fitting the model to long-term soil decomposition experiments 1 to 5 year where different types of plant material were added to soils with a number of soil textures Parton et al. Other more general databases Parton et al. Many of the parameters such as the plant nutrient content and lignin content were determined using a linear equation where the slope and intercept were the input parameters.

Work in the Great Plains suggested that lignin and N content changed as a linear function of annual precipitation. The model includes a method for estimating steady state soil C and N levels in grassland systems which was developed for the U. Great Plains. The soil P and S levels are quite different depending on soil parent material and need to be estimated with site-specific data. One of the most difficult parts of initializing the model is estimating the C, N, P, and S levels for the different soil fractions.

However, substantial progress has been made recently in estimating the size of the soil fractions. The active soil fraction includes the live soil microbes and microbial products. This fraction can be estimated by using the microbial fumigation technique Jenkinson and Powlson, ; Jenkinson et al. The slow SOM fraction is made up of lignin derived plant material and stabilized microbial products. Comparison of the size of the slow pool from C simulations with measurements of SOM indicate that the slow pool is approximately 1.

These approximations seem to work well for a large number of different soils. The C:P and C:S ratios are not as predictable and are functions of the initial soil parent material and degree of soil weathering. These values are appropriate for the relatively unweathered soils in the U. More weathered tropical soils have much higher C:P and C:S ratios that can be as high as To use the P and S submodels, determine the organic P and S levels and it would be preferable to run full P fractionation of the soil see citations in Hedley et al.

The model has been parameterized to simulate soil organic matter dynamics in the top 20 cm of the soil. The model does not simulate organic matter in the deeper soil layers and increasing the soil depth parameter EDEPTH, fix. To simulate a deeper soil depth i.

As a general rule deeper soil depths have older soil carbon dates Jenkinson et al. The major change for initializing the model for deep soil depths is adjusting the fraction of SOM in the different pools more C in passive SOM. Acock, B. Effects of carbon dioxide on photosynthesis, plant growth, and other processes.

In "Impact of carbon dioxide, trace gases, and climate changes on global agriculture. Kimball ed. Akita, S. Photosynthetic responses to CO2 and light by maize and wheat leaves adjusted for constant stomatal apertures. Crop Science Balesdent, J. Maize root-derived soil organic carbon estimated by natural 13C abundance. Soil Biology and Biochemistry Mariotti, B. Natural 13C abundance as a tracer for studies of soil organic matter dynamics.

Wagner, A. Soil organic matter turnover in long-term field experiments as revealed by carbon natural abundance. Soil Science Society of America Journal Bender, M. Phytochemistry Benner, R. Fogel, E. Sprague, R. Depletion of 13C in lignin and its implications for stable carbon isotope studies. Nature Burke, I. Yonker, W. Parton, C. Cole, K. Flach, D. Texture, climate, and cultivation effects on soil organic matter context in U. Soil Sci.

Cerri, C. Feller, J. Balesdent, R. Victoria, A. Application du tracage isotopique naturel en 13C, a l'etude de la dynamique de la matiere organique dans les sols. Comptes Rendus de l'Academie des Sciences de Paris, Cole, C. Innis, J. Simulation of phosphorus cycling in semiarid grasslands. Shielding gas covers arc and molten puddle. Century GL - V. Its simple operation allows practical repairs for many plastic parts potentially saving them from the scrap heap.

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