Hierarchical levels in agro-ecosystems : selective case studies on water and nitrogen

The subject of this thesisToday, agronomic research faces the triple challenge to develop knowledge and insight to manage agro-ecosystems which are inherently sustainable, to diminish the undesirable side effects and to meet the increasing demand of food of a still growing world population, without claiming all the available land. Sound management of agro-ecosystems is not solely a matter of the individual farmer, nor of only field and farm level. Local, national and international policy levels demand guidance from the agricultural research community in management of the natural resources. Thus, agronomic processes, so far studied at the level of plots, have to be studied and applied at higher hierarchical levels, i.e. larger entities such as toposequences, watersheds, river systems, continents and even the entire globe, and over longer time periods. Furthermore, agronomic research must switch from a reductionistic to a more holistic approach. Agro-ecosystem analysis at multiple hierarchical levels, the subject of this thesis, is such an approach.In the first chapter, several issues related to this subject are introduced: agro- ecosystem analysis, hierarchical levels, scales, scaling and spatial up-scaling in agronomy. In the subsequent chapters examples are presented, that deal with agro- ecosystem analysis at hierarchical levels varying from plant to watershed. In addition, they touch upon issues of agro-ecosystem analysis at multiple hierarchical levels.Agro-ecosystem analysis at multiple hierarchical levelsAt the hierarchical level of the plant (and crop), the reproductive effort of annual species in Mediterranean pastures is analyzed (Chapter 2). The reproductive effort is defined as the reproductive ratio (proportion of biomass invested in the reproductive organs in relation to the total biomass produced) and as harvest index (proportion of harvestable seed in relation to the total biomass produced). It appears that the proportion of the total production invested in reproductive tissue may be as high as that of cultivated species. The variation within a species of both ratios is high, owing to environmental conditions. A model is introduced which describes the relation between the harvest index and the nutrient (mainly nitrogen) transfer from vegetative organs to the reproductive organs in the period between flowering and maturity. This model explains to a large extent the possible variation within a species.The Chapters 3 and 4 are examples of agro-ecosystem analysis at the hierarchical level of cropping and livestock systems. Traditional livestock systems and ranching in Botswana are compared in Chapter 3. These systems differ in production objectives. Ranching is solely oriented to meat production in particular for export, while traditional systems have multiple objectives i.e. meat and milk production for self-sufficiency, and provision of animal traction. The systems are compared considering one output (meat) and considering multiple outputs (meat, milk and animal traction), both on a productivity per animal and per hectare basis. It depends on the way that systems are compared, which system is more productive. Ranching is more productive if compared on a per animal basis and only meat is considered as an output. Traditional systems are more productive if compared on a per hectare basis and multiple outputs are considered.In Chapter 4, the role of organic matter in intensified arable farming systems in the semi-arid tropical zones of West Africa is discussed. Different aspects are treated: its function as a source of nutrients, its effects on soil physical and on soil chemical properties. It is concluded that often the major effect is through increased nutrient supply, but that in combination with chemical fertilizers particularly nitrogen - organic matter serves to counteract the negative effects of these fertilizers, such as acidification and the increased removal of nutrients other than the one applied in the chemical fertilizers. Insufficient organic material appears to be available to realize the required production increase and to prevent the negative effects of nitrogen fertilizers. However, application of chemical fertilizer alone can lead to sustainable production systems, provided export and losses of all nutrient elements are sufficiently compensated and acidification is avoided by using the correct type of nitrogen fertilizer, possibly in combination with liming.Next, two examples are given to transfer information of lower to higher hierarchical levels. Chapter 5 describes the development of transfer functions, which are developed at the hierarchical level of crop/vegetation and applied at the hierarchical level of physiographic units. Transfer functions use easily measurable indicators, such as texture of the soil, as independent variables in regression analysis. In order to construct transfer functions many data have to be obtained to carry out the regression analysis. These data are normally obtained in the field, but in this case have been generated with a process-simulation model, which has been fully validated. The transfer functions presented can be used to calculate maximum depth of soil wetting and water losses from the rooting zone or shallow soils, using water content at pF2.5 and average annual infiltration as dependent variables. In comparison to simple rainfall-biomass relations, the application of transfer functions allow more accuracy in estimating biomass production of physio-graphic units.In Chapter 6 information on evapotranspiration, obtained at the lower hierarchical level (leaf/plant), is extrapolated to higher levels (canopies), showing emerging properties. When moving to this higher hierarchical level the time and spatial scales increase from day to year and leaf to canopy, respectively. Direct comparison of literature data on evapotranspiration of different crops is hardly possible, since differences in soils and climate make data incomparable. Literature data are presented on crop parameters and environmental conditions, that determine transpiration for four crops (oil palm, cocoa, maize and rice), and on evaporation.Transpiration at leaf scale and soil evaporation as well as evaporation of intercepted rainfall have been computed using these data and scaled up to canopy level. Thus, daily and annual evapotranspiration of the four crops are quantified under identical environmental conditions. Variation among crops in transpiration at the spatial scale of leaves is levelled out in scaling up to the canopy scale. Differences in annual evapotranspiration between perennial and annual crops are mainly due to the fact that perennial crops transpire during the dry season, although at low rates, but still considerably higher than evaporation rates of bare and dry soils. Apparently, the degree of soil cover with Vegetation in space and in time is of major importance to evaluate differences in annual evapotranspiration of canopies.The following two chapters cover the hierarchical level of watersheds. They show the effects on system behaviour if the spatial processes of water and nitrogen flows are explicitly taken into account. Chapter 7 considers the possible effect of up-scaling in space of the process of infiltration and run-off to the level of a watershed. A conceptual water balance model is presented, mimicking the scale dependency of the run-off coefficient of watersheds by the introduction of a scale dependent variable (REDF). By using the transfer functions developed in Chapter 5, the water balance is kept simple. Notwithstanding the inherent impossibility to validate this conceptual model, the same kind of scale dependency in run-off coefficients is found as in those obtained from lymnographic data of watersheds in West Africa. The scale dependent variable REDF has to be established in field experiments, where run-off is measured at two or three spatial scales in relation to soil type, vegetation and agronomic practices.Chapter 8 elaborates on consequences of the scale dependency of run-off if land use changes. An equation to calculate the annual nitrogen balance is included in the water balance model of Chapter 7. This equation uses the calculated infiltration from the water balance as input variable and differentiates between nitrogen uptake efficiency of annual and perennial vegetation. The run-off coefficients and the annual nitrogen balances of a representative watershed in West Africa are calculated for different land use scenario's, replacing perennial by annual vegetation and varying the spatial pattern of these vegetation types. The model runs simulating these different scenario's illustrate that the effects of changes in land use on water and nitrogen flows are not additive. The relationships between the run-off coefficient and the annual nitrogen balance of the watershed on the one hand and the proportion of the two types of land use on the other, cannot be described by a single line. A solution domain exists with each value in this domain representing a specific combination of the proportion of the two types of land use and its spatial pattern in the watershed.Issues of agro-ecosystem analysisIn Chapter 9, several issues of agro-ecosystems analysis, emerged in the Chapters 2-8, are discussed. These issues are: (1) the interdependence between objectives of study and agro-ecosystem boundaries, (2) sustainability in relation to hierarchical levels, and (3) up-scaling. The latter is discussed in relation to: (i) transfer functions to transfer information to higher hierarchical levels, (ii) emerging properties, (iii) spatial up- scaling of the water balance and (iv) integrated upscaling of soil and crop processes.The issue of interdependence between objectives of study and agro-ecosystem boundaries is touched upon in the Chapters 2, 3 and 4. In Chapter 2, three objectives of study are considered resulting in three ways of delimitating the system. The first objective is to study the reproductive effort in relation to survival of annual species. Then, the reproductive ratio in relation to the harvest index is used. The second objective relates to the agricultural efficiency to produce seed, with the harvest index as the appropriate measure. Both approaches implicitly take the genetic variation as the main determinant factor to explain variation between species, and are as such examples of the Population-Community approach. The third objective aims at explaining the variability in reproductive effort within a species. Then, environmental conditions are included in the system analysis, by introducing the relation between these conditions and the transfer of nutrients from vegetative organs to reproductive organs during the period between flowering and maturation. The latter is an example of the ProcessFunctional approach.In Chapter 3, the two livestock systems are compared in several ways. These ways indicate different delimitations of the systems. A comparison is made including only one output (meat) and two components (cows and calves). The objective of study is to compare productivity for export. In a second comparison more outputs are considered (meat, milk and draught power) and more components (all the classes in a herd). In that case, the objective is to compare productivity for selfsufficiency of the rural population. Finally, the two ways to compare the systems are applied on a per animal and a per hectare basis.Comparison on a per animal basis is appropriate if land is abundantly available, whereas comparison on a per hectare basis is appropriate if land is scarce.In Chapter 4, the viability of an arable farming system in West Africa, based on manure to sustain soil fertility is tested. This farming system seems to be viable if it is regarded in isolation. This is one way to delimitate the system. However, if potential manure production is considered in relation to livestock and rangelands needed to produce that manure, i.e. another way to delimitate the system, the conclusion about viability alters.All these examples show, that system delimitation changes with the objectives of the study and that the objectives of study determine the approach to follow, whether it be a Process-Functional or Population-Community approach. Each way of delimitating the system is legitimate if in accordance with the objectives of study. However, additional insight is gained by looking at agro-ecosystems from different points of view.The issue of sustainability in relation to multiple hierarchical levels is touched upon in the Chapters 4, 7 and 8.Chapter 4 illustrates that, to assess the ecological sustainability of an agro-ecosystem (the arable farming system in isolation), the embedding of this system in the organizational structure at higher hierarchical levels (combination of arable systems and livestock systems) must be considered.On a completely different subject, the same view is illustrated in the Chapters 7 and 8. The runs with a conceptual model describing water and nitrogen balances, show that the run-off and nitrogen losses at a low hierarchical level (plots of 1 M 2) are higher than at higher hierarchical levels (slopes and entire watersheds). If run-off is considered as the driving force for erosion, sustainability at the plot level may be less than at higher hierarchical levels.The spatial pattern of isolated units (rangeland and arable land in Chapter 4 and perennial and annual vegetation in Chapter 8) is important as well in judging the sustainability of agro-ecosystems.The examples in the Chapters 4, 7 and 8 illustrate that the assessment of the sustainability of agro-ecosystems is not possible, without considering multiple hierarchical levels. We constantly have to move between agro-ecosystems at different hierarchical levels. At the same time, we explicitly have to take into account the spatial scale and spatial patterns.Different aspects of up-scaling are touched upon in the Chapters 5, 6, 7 and 8. The method to develop transfer functions with the use of a simulation model (Chapter 5) shows, that detailed information at the hierarchical level of vegetation can be summarized to obtain a better description of system behaviour at higher hierarchical levels. The process of spatial and temporal up-scaling of evapotranspiration described in Chapter 6 shows, that other properties become determinant at higher hierarchical levels. Thus, to analyze an agro-ecosystem at higher hierarchical levels involves the search for those properties which emerge at these higher levels. The conceptual model presented in Chapter 7 shows, that applying a summation, averaging and aggregation strategy in up-scaling can lead to inaccurate conclusions at higher hierarchical levels if variables and processes, such as run-off, are non-linear. Finally, it is shown that it is not necessary to transfer all details of both plant and soil processes, which are obtained at lower hierarchical levels, to study higher hierarchical levels (Chapter 8). Transfer functions and/or equations can be used to integrate the processes in a simple form, which can be applied at higher hierarchical levels. Then, crop and soil processes can be integrated in up-scaling.Concluding remarksIt is concluded that at each hierarchical level the objectives of study determine the definition of the agro-ecosystem. Therefore several choices can be made resulting in different agro-ecosystem studies. Each of these agro-ecosystem studies are legitimate and valuable. However, additional insight is obtained by playing with the objectives and the system boundaries. Secondly, it is concluded that we must move constantly between agro-ecosystems at different hierarchical levels to assess sustainability of agro-ecosystems. At the same time, we must take into account explicitly the spatial scale and spatial patterns. Thirdly, in the transfer of information from lower to higher hierarchical levels the level of detail can be reduced through the use of transfer functions, which are developed with simulation models. Such functions, in combination with other functions that summarize information, can assist in integrated up-scaling of crop and soil processes. Finally, searching for emerging properties at higher hierarchical levels can facilitate the analysis of agro- ecosystems at these higher hierarchical levels.