CHAPTER 5 Utilization of Biological Interactions and Matter Cycling in Agriculture Masae Shiyomi CONTENTS Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 From Agriculture Based on Fossil Energy to Agriculture Based on the Use of Complex Biological Interactions . . . . . . . . . . . . . . . . . . . . . . . . 97 Plant-Grasshopper-Mantis-Bird Model. . . . . . . . . . . . . . . . . . . . . . . . . 98 Grasshopper-Mantis Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 The Importance of Matter Cycling in the New Agriculture. . . . . . . . . . . . . 101 Grassland Ecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Upland Crop Field Ecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Paddy Field Ecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 INTRODUCTION For the 50 years following the Second World War, agricultural produc- tion markedly increased. Examples are shown in Figure 5.1 for corn in the U.S. and rice in Japan (Uchijima, 1990). In the U.S., the use of F 1 hybrid corn in the 1960s led to a rapid increase in production per hectare. Although the production of rice in Japan has not made such rapid strides as that of corn in the U.S., the production per unit area has gradually increased from 1900 to the very high present level, especially in the last 50 years. Modern agriculture, which depends on the consumption of large quanti- ties of fossil fuel, is now being forced to change to an alternative system in 95 0-8493-0904-2/01/$0.00+$.50 © 2001 by CRC Press LLC 920103_CRC20_0904_CH05 1/13/01 10:48 AM Page 95 96 STRUCTURE AND FUNCTION IN AGROECOSYSTEMS DESIGN AND MANAGEMENT Corn, United States Rice, Japan Yield t ha -1 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 7 6 5 4 3 2 5 4 3 2 Figure 5.1 Corn and rice yields in the U.S. and Japan in the last 100 years (Uchijima, 1990). which the interactions between organisms and environment and matter cycling in agricultural ecosystems are properly utilized (Edwards et al., 1990; Shiyomi, 1993). First we discuss the problems everyone is presently facing. There are three reasons for making such a change. One reason is the depletion of readily available fossil fuel resources. According to the Tokyo newspaper Asahi-shinbun (December 25, 1994), Energy problem is serious. The Central Institute of Electric Power Industry, Japan, predicts that the annual energy demand in the world in 2050 will reach an equivalent of 13 to 24 billion tons of petroleum. If the present rate of consumption of fossil fuel continues, all presently known oil deposits will have been mined by 2040, and all deposits to be found in the future will be mined by 2080, too. Natural gas will be exhausted by 2080. An American entomologist, D. Pimentel, stated (Pimentel 1992), “Unfortunately throughout the world more fossil energy is being used in order to increase food production for the ever expanding world population. While the world population grows, the known supplies of fossil energy are being rapidly drawn down. For example, most world oil and natural gas reserves will be consumed during the next 35 years.” Although the time 920103_CRC20_0904_CH05 1/13/01 10:48 AM Page 96 UTILIZATION OF BIOLOGICAL INTERACTIONS AND MATTER CYCLING IN AGRICULTURE 97 when the fossil deposits would have been exhausted differs among the reports, someday they will disappear. A second reason for change is that as the amount of fertilizers and agro- chemicals used increases, increase in the growth and yield of crops decreases exponentially, and eventually the growth and yield level off. Furthermore, to these reduced marginal rates of return from input use, it is unlikely that new strains or varieties can be developed that will respond more effectively to an increase in input. Another reason for change is that the consumption of fossil fuel energy has led to the degradation of the environment. According to Pimentel (1992), “In addition, the heavy use of pesticides, especially in developed countries, is having widespread impact on aquatic and terrestrial ecosystems. Worldwide an estimated 2.5 billion kg of pesticide is applied to agriculture. Yet, less than 0.1% of this pesticide reaches the target pests, with the remain- der negatively affecting humans, livestock, and natural biota. Just in the U.S., it is estimated that pesticides cause $8 billion in damage to the environment and public health each year. Million of wild birds, mammals, fishes, and ben- eficial natural enemies are destroyed each year because of the recommended use of pesticides in the U.S.” It is clear that modern agricultural practices, which depend on inputs of fossil energy, have exerted a variety of harmful effects on both the local ecosystems and the global biosphere. This chapter discusses two topics. The first concerns the importance of the use of complex biological interactions as an alternative to the heavy use of fossil energy in modern agriculture. The second discusses the impor- tance of matter cycling in agricultural ecosystems and uses examples of car- bon and nitrogen budgets in ecosystems of grassland, upland field and paddy field. FROM AGRICULTURE BASED ON FOSSIL ENERGY TO AGRICULTURE BASED ON THE USE OF COMPLEX BIOLOGICAL INTERACTIONS As mentioned above, the increases in agricultural production in advanced countries from the 1950s to the 1970s were largely due to large increases in the use of fossil fuel energy. Specifically, the increases have been due to the increased use of fertilizers, agricultural chemicals, and big machines that are produced and operated with fossil energy sources, and to the breeding of new varieties of crops that are responsive to and compatible with such chemical inputs and cultural practices (Pimentel et al., 1973). Researchers have also promoted this agricultural system by focusing on research on improving crop yield through the direct use of these fertilizers, agrochemical inputs, and machinery. Indeed, these research programs have been very efficient and have led to the increase of both crop and livestock production. The use of intra- and interspecific interactions and interactions 920103_CRC20_0904_CH05 1/13/01 10:48 AM Page 97 98 STRUCTURE AND FUNCTION IN AGROECOSYSTEMS DESIGN AND MANAGEMENT between organisms and the environment, such as climatic factors and soils, have no particular place in the current agricultural system. In modern agri- culture, these interactions are viewed as production constraints that must be overcome to make high production possible. Since the direct effects of the use of fossil fuel energy and products on agricultural production have been so powerful, reliable, and dramatic, little attention has been paid to the complex networks of interactions operating in agricultural ecosystems. For example, competition between phytophagous insects, the effects of insect pathogens and other natural enemies on these phytophagous species, and antagonisms between them have intentionally been ignored. Because of the clear, direct effectiveness of agrochemicals, it seemed that insect pests, plant pathogens, and weeds could be controlled at sufficiently low levels without considering the biological functions and interactions in agricultural ecosystems. And because of the clear, direct effectiveness of fertilizers, it seemed that high crop yields could be guaranteed without the help of the subtle actions of soil- borne microorganisms. Complex intercroppings have been excluded so that machinery can be operated more efficiently. However, this modern agricul- ture has led to the three problems stated above. In the alternative type of agri- culture, instead of modern agriculture, analyses of indirect effects operating among the complex networks of biological interactions and between organ- isms and the environments in place of the direct effects must be considered. Plant-Grasshopper-Mantis-Bird Model Because of the complexity of biological interactions, such interactions are most effectively understood by the use of system analysis (Edwards, 1990). To demonstrate this concept, I will use a 4-component system composed of pasture plants, grasshoppers, mantes and birds (Figure 5.2) (Levins and Vandermeer, 1990). Grasshoppers eat plants, mantes eat grasshoppers, and birds eat both grasshoppers and mantes. The first system (Figure 5.2a) is composed of only the three components, in which the population of grasshoppers increases as the biomass of pasture plants increases. If the pop- ulation of grasshoppers increases, the population of mantes increases, and the biomass of plants decreases. Then, when the biomass of plants increases, the populations of grasshoppers and mantes increase. When the population of mantes increases, the population of grasshoppers decreases, and then the plant biomass increases. If we add birds as the fourth component in the system (Figure 5.2b), the interactions operating among these components become much more compli- cated because the birds kill both grasshoppers and mantes. As can be seen in Figure 5.2c, the bird population increases as the grasshopper population increases. In Figure 5.2d, I is an agrochemical. Farmers do not ordinarily use agrochemicals if many mantes, which can kill most of the grasshoppers, live there. It becomes increasingly difficult to understand intuitively the interac- tions operating in such systems even in such a 4-component system like this 920103_CRC20_0904_CH05 1/13/01 10:48 AM Page 98 UTILIZATION OF BIOLOGICAL INTERACTIONS AND MATTER CYCLING IN AGRICULTURE 99 P P H I I I C C P H H C P H C a b c d Figure 5.2 Plant-grasshopper-mantis-bird model. P, H, C and I indicate the numbers of plants, grasshoppers, mantes and birds, respectively. In (d) I stands for pesticide. Arrows and circles indicate positive and negative feedbacks, respectively. (From Levins and Vandermeer, 1990.) example. Indeed, even such a simple system may be too complicated for the human brain to understand. Grasshopper-Mantis Model As another example for conceptualizing such simple systems, a 3-com- ponent system, is shown in Figure 5.3. In this system, there are two kinds of grasshoppers and one kind of mantis, where mantes eat both kinds of grasshoppers. The two kinds of grasshoppers compete with each other for resources. The time-dependent changes in these three components are expressed by the following equations (Levins and Vandermeer, 1990): dH 1 /dt ϭ H 1 (r 1 Ϫ a 11 H 1 Ϫ a 12 H 2 Ϫ a 13 C) (5.1) dH 2 /dt ϭ H 2 (r 2 Ϫ a 22 H 2 Ϫ a 21 H 1 Ϫ a 23 C) (5.2) dC/dt ϭ C(r 3 ϩ a 32 H 2 ϩ a 31 H 1 ). (5.3) 920103_CRC20_0904_CH05 1/13/01 10:48 AM Page 99 100 STRUCTURE AND FUNCTION IN AGROECOSYSTEMS DESIGN AND MANAGEMENT Grasshoppers 1Grasshoppers 2Mantes 600 400 200 1000 500 0 200 100 100 200 200 300 400 400 500 600 800 800 600 400 200 0 1000 0 0 0 0 100 200 300 400 500 100 200 300 400 500 0 0 Time Time (b) (a) A B a 13 a 23 a 32 a 31 a 21 a 12 a 11 a 22 H1 H2 C Figure 5.3 Grasshopper-mantis model (Levins and Vandermeer, 1990). There are two kinds of competitive grasshoppers and one kind of mantis. H 1 , H 2 , and C indicate the numbers of the two kinds of grasshoppers and mantes, respectively. The simulated results on the left and right sides depict the cases for r 3 ϭϪ1.25 and Ϫ1.0, respectively. A large negative r 3 indicates large cannibalism by mantes. 920103_CRC20_0904_CH05 1/13/01 10:48 AM Page 100 UTILIZATION OF BIOLOGICAL INTERACTIONS AND MATTER CYCLING IN AGRICULTURE 101 Here, H 1 , H 2 , and C denote the densities of the two kinds of grasshoppers and mantes, respectively, and a and r are positive constants, except for r 3 which denotes cannibalism by the mantes and has a negative value. Time is expressed by t. Equation 5.1 indicates that the population growth rate of grasshopper 1 is proportional to the quantity indicated in parentheses, where r 1 is a growth coefficient assuming the absence of interspecific competition and predation. The negative terms are corrections to r 1 due to interactions with each of the three organisms. Equation 5.2 for grasshopper 2 is very sim- ilar to the first equation. Equation 5.3 applies to the mantis, whose popula- tion increases in proportion to the quantities of the two kinds of grasshoppers, and decreases with their own cannibalism. In the first simulation, r 3 was set at Ϫ1.25. The results are shown on the left side of Figure 5.3. What changes will occur if r 3 increases to Ϫ1 (i.e., can- nibalism decreases)? Intuitively, one would expect an increase in the popula- tion of mantes and a decrease in the population of grasshoppers due to increased predation. However, as shown in Figure 5.3 (right panel), the pop- ulation of mantes did not increase, and the population dynamics of grasshop- pers were very different from our expectation. This phenomenon is known as an example of a chaotic event. The above two examples, the 4-component and 3-component systems, indicate that even in such simple systems it is not easy to predict how the individual components interact with each other. Predicting the behavior of and properly managing an actual agricultural ecosystem may be too difficult without appropriate methods such as system simulations (Edwards, 1990). THE IMPORTANCE OF MATTER CYCLING IN THE NEW AGRICULTURE To grow crops with reduced amounts of fertilizers in agricultural ecosys- tems in the next generation, it is important to develop methods to accelerate nutrient cycling, and there are two approaches: activation of inactive ele- ments that are stored in the ecosystem, such as inactive nitrogen and phos- phorus in the soil; and acceleration of the turnover rate. Examples of the former are utilization of phosphorus by plants after solubilization by phos- phate-solubilizing soil microorganisms (Kimura et al., 1991) and utilization of mineralized nitrogen from microbial biomass and organic matter by dry- ing and heating of soil (Okano, 1990), although they have not been developed as a technology yet. Iwama et al. (1992) reported an example of improvement of nutrient turnover rate through the introduction of intermittent grazing. At the National Grassland Research Institute, Nagano, Japan, a pasture was seeded in 1966 with tall fescue, orchard grass, timothy, red clover, and white clover. The grass was then cut three times a year. Starting in 1973, grazing was allowed in one part of the pasture after the second cutting each year. Dry 920103_CRC20_0904_CH05 1/13/01 10:48 AM Page 101 102 STRUCTURE AND FUNCTION IN AGROECOSYSTEMS DESIGN AND MANAGEMENT matter plant yield was found to be dramatically higher in the grazed pasture than in the ungrazed pasture. Although no direct, numerical data were provided, the nutrient turnover rate in the pasture where grazing was intro- duced was clearly accelerated through the animal-excreta-soil microbial- plant interactions. In this section, we present examples of carbon and nitrogen flow in agroecosystems. Grassland Ecosystems Energy flow and nutrient cycling have been analyzed in various ecosys- tems for the past twenty years. These analyses are essential to obtain a more detailed description of a system’s productivity and nutrient cycling. In agri- cultural ecosystems, solar energy is converted into chemical energy by pho- tosynthesis in crops. Some of the energy is used by the plant for respiration, and the remainder is fixed as net primary production. The energy of net pri- mary production is passed on to the other compartments, and finally it flows out from the system to the inorganic environment in various ways. Understanding the balance between the energy or carbon inflow and outflow and also the transfer functions is essential for the study of the dynamic behavior of an ecosystem. The energy or carbon budget in an agricultural ecosystem indicates the degree of stability of the soil fertility or the sustain- ability of the agricultural ecosystem. To explore these ideas, we discuss the carbon and nitrogen budgets in grasslands and then compare them with the corresponding budgets in upland and paddy fields. Surveys of energy and matter budgets in a grassland have been carried out at the National Grassland Research Institute, located in central Japan, a region where the livestock industry has predominated on the main island of Japan, since 1974. These budgets have been measured at the plant, animal, and ecosystem levels on a yearly basis (Akiyama et al., 1984; Koyama et al., 1986; Takahashi et al., 1989). Based on these measurements, an energy, or car- bon, and nitrogen flow model was constructed (Shiyomi et al., 1988; Shiyomi et al., 2000). The outline of the model is as follows: we assume that the amounts of energy and nitrogen and their time-dependent variations in each compartment are determined by their fluxes into and out of each of these compartments. Thus, the time-dependent variation in the amounts of energy and nitrogen at time t, x(t)’s, can be described by dx(t)/dt’s although the equations are omitted here. The concept of the model is illustrated in Figures 5.4a and 5.4b. Key parameters in the model are as follow: 1. Global solar radiation, Q, which changes over the course of a year according to a sine curve (kJ m Ϫ2 day Ϫ1 ). 2. Conversion efficiency of global solar radiation to photosynthesis f ϭ [1 Ϫ (2.4L ϩ 1) Ϫ 1]a(aQ ϩ 1) Ϫ1 , where L is the leaf area index and a is a constant. 920103_CRC20_0904_CH05 1/13/01 10:48 AM Page 102 UTILIZATION OF BIOLOGICAL INTERACTIONS AND MATTER CYCLING IN AGRICULTURE 103 A Light intensity Leaf area index Sun Grazing intensity Digestibility Amount of standing dead material Amount of available herbage Amount of unavailable herbage Amount of herbage intake by cattle Body weight of cattle Air temperature Amount of feces Respiration Amount of belowground portions Soil organisms Soil organic matter Tu r nover rate of soil organisms Water content Amount of litter Figure 5.4a Energy flow compartment model for grazing grassland (Shiyomi et al., 1988). “A” indicates the link between energy and nitrogen models. 3. Respiration-loss energy by plants is expressed by a linear relation of daily air temperature, and heat-loss energy from cattle is a func- tion of body weight, digestibility, etc. (kJ m Ϫ2 day Ϫ1 ). 4. The herd ingests each day an amount of herbage (dry weight) equivalent to 2.5% of live cattle body weight (kJ m Ϫ2 day Ϫ1 ). 5. Theenergy accumulation ina cattlebody is given by (herbage intake, kgDM) ϫ (digestibility) ϫ 0.414, where 41.4% of digested energy is accumulated in the cattle body. Digestibility is given by the equa- tion 619.6/(herbage biomass, kJ m Ϫ2 ) ϩ 0.398 (Koyama et al., 1986). 6. The total amount of nitrogen lost from the soil, which includes the amounts absorbed by plants and runoff/leaching, is expressed by linear functions of the number of days counted from March 1. 7. A 100 kg heifer excretes 58.0 gN as dung and 26.8 gN as urine each day. 920103_CRC20_0904_CH05 1/13/01 10:48 AM Page 103 104 STRUCTURE AND FUNCTION IN AGROECOSYSTEMS DESIGN AND MANAGEMENT Mortality rate Amount in above- ground portion A Ingestion rate Amount ingested by cattle Cattle body Amount in standing dead material T/R balance Amount in litter Decomposition rate Soil organic matter Soil organisms Rate from standing dead material to litter Amount in below- ground portion Amount in soil Turnover rate Fixation Legume biomass Volatilization, leaching etc. Application Amount in excreta Volatilization rate etc. Crop growth rate Figure 5.4b Nitrogen flow compartment model for grazing grassland (Shiyomi et al., 1988). “A” indicates the link between energy and nitrogen models. 8. Legumes fix 0.011 to 0.012 gN m Ϫ2 day Ϫ1 . 9. The nitrogen concentration in plant leaves affects the leaf area index, which is expressed by a logistic function of nitrogen concen- tration. An annual gain of 1 ton cattle body weight ha Ϫ1 was attained in an inten- sively managed pasture (IMP) at the National Grassland Research Institute, Tochigi, in 1986 (Kobayashi et al., 1989). The carbon and nitrogen budgets estimated using the systems model for the ecosystem in this pasture were compared with those estimated in an extensively managed pasture (EMP). In a computer simulation of the IMP, seven young Holstein oxen were grazed on a 1-ha orchard grass-white clover pasture, where 160 kgN ha Ϫ1 yr Ϫ1 was applied, for a period of 200 days from April onward. Likewise, in a com- puter simulation of the EMP, three young Holstein oxen were grazed on a 1- ha orchard grass-tall fescue-red top-white clover pasture, where 50 kgN ha Ϫ1 yr Ϫ1 was applied, for the same grazing period. The results are shown in Table 5.1. If we suppose that the amounts of carbon in plant bodies in both the EMP and IMP do not change between the successive two years in the simulations, 920103_CRC20_0904_CH05 1/13/01 10:48 AM Page 104 [...]... 920103_CRC20_0904_CH 05 106 1/13/01 10:48 AM Page 106 STRUCTURE AND FUNCTION IN AGROECOSYSTEMS DESIGN AND MANAGEMENT (about 80 kgN ha yr Ϫ1 in our case), we found in the simulations that these two grassland ecosystems could keep a balance between the inflow and outflow of nitrogen Upland Crop Field Ecosystems The investigations of carbon dynamics were carried out from June 19 85 to May 1988, in upland fields in the... dynamics in the paddy field ecosystem with respect to the inflow of car- 920103_CRC20_0904_CH 05 108 1/13/01 10:48 AM Page 108 STRUCTURE AND FUNCTION IN AGROECOSYSTEMS DESIGN AND MANAGEMENT bon through irrigation to the paddy field, the outflow through runoff of above- and underground water from the paddy field, and fixation of carbon by rice plants and algae growing in the paddy field (see Figure 10.2 in Chapter. .. Each Component in Three Double-cropping Ecosystems Item/System Rice-Barley Peanut-Wheat Corn-Italian Ryegrass Carbon in crops Gross production Net production Removal by harvest Residual in/ on soil Removal by predation Respiration by crops 1070 6 15 278 338 nil 454 13 15 626 244 382 nil 689 2910 1 357 1084 274 nil 155 3 18 950 0 382 798 Ϫ4 15 10480 146 274 1 050 Ϫ630 Carbon in soil Storage in the upper 70... ecosystems in Japan are sustainable An outline of the simulation model is shown in Figure 5. 5 Nitrogen in the paddy soil is categorized into the following five classes: (1) effective nitrogen, (2) nitrogen contained in easily decomposable organic matter such as protein, (3) nitrogen contained in hardly decomposable organic matter such as cellulose and lignin, (4) nitrogen contained in live soil organisms, and. .. complex biological interactions and matter cycling because such types of agriculture have not been developed during the 50 years after the war Thus, it is important to elucidate the structure and function and to use complex biological interactions and matter cycling in agricultural ecosystems (Shiyomi, 1993) The world population was 2.8 billion in 19 45, and it doubled in the following 50 years It is predicted... AGRICULTURE 109 920103_CRC20_0904_CH 05 110 1/13/01 10:48 AM Page 110 STRUCTURE AND FUNCTION IN AGROECOSYSTEMS DESIGN AND MANAGEMENT (N.Kg/ ha) 150 0 3 3 3 3 3 3 3 11 25 1: 2: 3: 4: 750 Effective N NEDOM NHDOM NLSO 1 1 3 75 24 2 4 1 1 1 1 1 2 4 2 4 2 4 2 4 2 4 0 0 5 10 15 20 Time (year) Figure 5. 6 Simulated nitrogen dynamics in a paddy field (Torigoe et al., 1991) The unit is expressed in kgN haϪ1 EN: effective nitrogen;... Grassland Res Inst (Japan) 33: 17 –26 (Japanese, English summary) Levins, R and J.H Vandermeer 1990 The agroecosystem embedded in a complex ecological community In: C.R Carroll, J.H Vandermeer and P.M Rosset, Eds Agroecology, McGraw-Hill Publishing Company, New York 341 –362 Okano, S 1990 Availability of mineralized nitrogen from microbial biomass and organic matter after drying and heating of grassland... Potential effect of no-till management on carbon in the agricultural soils of the former Soviet Union Agric Ecosystems & Environ 45: 2 95 –309 Iwama, H., H Murakami, N Kitahara, and K Okamoto 1991 Increase in rate of nutrient cycling in meadow in introduction of seasonal grazing Bulletin of National Grassland Research Institute (Japan) 46: 61–71 (Japanese, English summary) Kimura, R., M Nishio, and K Katoh 1992... Harashima, K Sato, and M Nashiki 1989 New grazing animal production system in Japan Proc 16th Int Grassland Cong The French Grassland Society Versailles 1139–1140 Koizumi, H., Y Usami, and M Satoh 1993 Carbon dynamics and budgets in three double-cropping agro-ecosystems in Japan Agric Ecosystems & Environ 43: 2 35 244 Koyama, N., M Shiyomi and M Tsuiki 1986 Energy flow on grazing pasture 2 Energy and nitrogen...920103_CRC20_0904_CH 05 1/13/01 10:48 AM Page 1 05 UTILIZATION OF BIOLOGICAL INTERACTIONS AND MATTER CYCLING IN AGRICULTURE 1 05 Table 5. 1 Carbon and Nitrogen Budgets at the Ecosystem Level in a Grazing Pasture in the Kanto District, Japan Input Item Carried-forward from previous year by plant bodies by organic C in soil Net primary production Supplement (hay supply) Rain Total Output Item Cutting Heat production . 109 UTILIZATION OF BIOLOGICAL INTERACTIONS AND MATTER CYCLING IN AGRICULTURE 109 110 STRUCTURE AND FUNCTION IN AGROECOSYSTEMS DESIGN AND MANAGEMENT 150 0 11 25 750 3 75 0 05 10 15 20 ( y e a r ) ( N . K g / h. Nat’l. Grassland Res. Inst., (Japan) 39:24–39. 920103_CRC20_0904_CH 05 1/13/01 10:48 AM Page 1 05 106 STRUCTURE AND FUNCTION IN AGROECOSYSTEMS DESIGN AND MANAGEMENT (about 80 kgN ha yr Ϫ1 in our case),. each day. 920103_CRC20_0904_CH 05 1/13/01 10:48 AM Page 103 104 STRUCTURE AND FUNCTION IN AGROECOSYSTEMS DESIGN AND MANAGEMENT Mortality rate Amount in above- ground portion A Ingestion rate Amount ingested by cattle Cattle body Amount