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Grassland management affects the carbon fluxes of one-third of the global land area and is thus an important factor for the global carbon budget. Nonetheless, this aspect has been largely neglected or underrepresented in global carbon cycle models. We investigate four harvesting schemes for the managed grassland implementation of the dynamic global vegetation model (DGVM) Lund-Potsdam-Jena managed Land (LPJmL) that facilitate a better representation of actual management systems globally. We describe the model implementation and analyze simulation results with respect to harvest, net primary productivity and soil carbon content and by evaluating them against reported grass yields in Europe.We demonstrate the importance of accounting for differences in grassland management by assessing potential livestock grazing densities as well as the impacts of grazing, grazing intensities and mowing systems on soil carbon stocks. Grazing leads to soil carbon losses in polar or arid regions even at moderate livestock densities ( < 0.4 livestock units per hectare-LSUha -1 ) but not in temperate regions even at much higher densities (0.4 to 1.2 LSUha -1 ). Applying LPJmL with the new grassland management options enables assessments of the global grassland production and its impact on the terrestrial biogeochemical cycles but requires a global data set on current grassland management.

Over 30 million people in East Africa depend on East African highland bananas for food and income. The bananas are grown with limited additions of nutrients and no irrigation, despite widespread poor soil fertility and regular dry seasons. This thesis describes the effect of increasing rainfall and application of potassium and nitrogen fertilizers on banana growth and yields. In areas that receive less than 1100 mm of rainfall per year, additional rainfall increases yields by 65%. Application of potassium increases yields by 88%, while nitrogen is not required. A framework for computing banana growth and yield in response to the amount of water stored in the soil is described. Where the soil water storage capacity is low, mulching increases yields by 10% but it has no effect in areas where the soil water storage is high. This framework is envisaged to guide improvements in banana management and productivity in East Africa.

In crop insurance, the accuracy with which the insurer quantifies the actual risk is highly dependent on the availability on actual yield data. Crop models might be valuable tools to generate data on expected yields for risk assessment when no historical records are available. However, selecting a crop model for a specific objective, location and implementation scale is a difficult task. A look inside the different crop and soil modules to understand how outputs are obtained might facilitate model choice. The objectives of this paper were (i) to assess the usefulness of crop models to be used within a crop insurance analysis and design and (ii) to select the most suitable crop model for drought risk assessment in semi-arid regions in Spain. For that purpose first, a pre-selection of crop models simulating wheat yield under rainfed growing conditions at the field scale was made, and second, four selected models (Aquacrop, CERES-Wheat, CropSyst and WOFOST) were compared in terms of modelling approaches, process descriptions and model outputs. Outputs of the four models for the simulation of winter wheat growth are comparable when water is not limiting, but differences are larger when simulating yields under rainfed conditions. These differences in rainfed yields are mainly related to the dissimilar simulated soil water availability and the assumed linkages with dry matter formation. We concluded that for the simulation of winter wheat growth at field scale in such semi-arid conditions, CERES-Wheat and CropSyst are preferred. WOFOST is a satisfactory compromise between data availability and complexity when detail data on soil is limited. Aquacrop integrates physiological processes in some representative parameters, thus diminishing the number of input parameters, what is seen as an advantage when observed data is scarce. However, the high sensitivity of this model to low water availability limits its use in the region considered. Contrary to the use of ensembles of cro

Key words: Sustainability, CATPCA, two-step cluster analysis, farm types, nutrient balances, West Africa, gross margin, NUTMON/MONQI. Urban and peri-urban agriculture (UPA) is defined as the cultivation of crops and keeping livestock within and around cities. In addition to providing the cities’ demand of fresh vegetables, crops and livestock products, it plays an important role in the livelihoods of the urban farmers. With the rapid urbanization in sub-Saharan Africa, UPA provides food and jobs for many urban dwellers. UPA makes use of a diverse range of urban resources such as labour, waste and wastewater to produce food and raise livestock, and it is characterized by large nutrient imports into farms or gardens, often accompanied by environmental and human health risks. In view of the complexity and diversity of the UPA systems, there is a need to understand the socio-economic characteristics of UPA as drivers to farm management practices. This research was conducted in three secondary West African cities with important UPA activities: Kano (Nigeria), Bobo Dioulasso (Burkina Faso) and Sikasso (Mali). From principal component analysis of categorical variables (CATPCA) and two-step cluster analysis, six major farm types were identified based on production systems and market orientation, of which three are common in the three cities and one farm type is unique to each city. The six farm types are commercial gardening plus field crop-livestock (cGCL); commercial gardening plus semi-commercial cropping (cGscC); commercial livestock plus subsistence field cropping (cLsC); commercial gardening plus semi-commercial livestock (cGscL); commercial cropping (cC); and commercial gardening (cG). The former three are common for the three cities, the latter three farm types are unique for one city, each. The diverse activities in these farm types contributed differently to household income. Nutrient balance studies are useful indicators to assess the sustainability of farming sy

Recently, the scale of interest for application of crop growth models has extended to the region or even globe with time frames of 50-100 years. The application at larger scales of a crop growth model originally developed for a small scale without any adaptation might lead to errors and inaccuracies. Moreover, application of crop growth models at large scales usually gives problems with respect to missing data. Knowledge about the required level of modelling detail to accurately represent crop growth processes in crop growth models to be applied at large scales is scarce. In this thesis we analysed simulated potential yields, which resulted from models which apply different levels of detail to represent important crop growth processes. Our results indicated that, after location-specific calibration, models in which the same processes were represented with different levels of detail may perform similarly. Model performance was in general best for models which represented leaf area dynamics with the lowest level of detail. Additionally, the results indicated that the use of a different description of light interception significantly changes model outcomes. Especially the representation of leaf senescence was found to be critical for model performance. Global crop growth models are often used with monthly weather data, while crop growth models were originally developed for daily weather data. We examined the effects of replacing daily weather data with monthly data. Results showed that using monthly weather data may result in higher simulated amounts of biomass. In addition, we found increasing detail in a modelling approach to give higher sensitivity to aggregation of input data. Next, we investigated the impact of the use of spatially aggregated sowing dates and temperatures on the simulated phenology of winter wheat in Germany. We found simulated winter wheat phenology in Germany to be rather similar using either non-aggregated input data or aggregated input data wi

Key words: Alternate wetting and drying, Climate change adaptation, Crop growth simulation models, Genotype × environment interaction, N use efficiency, Oryza sativa L., Phenology, Sahelian irrigation schemes, Sowing date, Spikelet sterility, Temperature increase, Water productivity, Weed control. In the vulnerable environment of the Sahel with its erratic rainfall pattern, irrigated rice production is of major importance. To aid Sahelian rice farmers to sustain irrigated rice production, this study explores management options. It includes field experiments performed at two typical Sahelian sites and simulation studies using crop growth simulation models. This thesis provides evidence that it is possible to use less irrigation water while maintaining rice production, thus increasing water productivity. The effects of a temperature increase on the growing cycle and spikelet sterility of new rice varieties in interaction with different sowing dates is quantified. The simulation results show that the sowing window will be restricted and that the cultivar choice may alter; together they will remain the most important determinants of rice production in the coming decades. In Chapter 2, field experiments involving three water saving regimes using combinations of alternate wetting and drying (AWD) and flooding and a fully flooded control show that between 480 and 1060 mm of irrigation water was used in the water saving treatments compared with 800 to 1490 mm in the flooded rice treatment. Water productivity of the water-saving treatments was higher than of the flooded control, and yields ranged between 141 and 56% of the control. When weeds were controlled, crop yields obtained with a combination of AWD and flooding were comparable with those obtained in fully flooded plots receiving the same weed management. In Ndiaye, agronomic N use efficiency was smaller in the AWD treatments compared with fully flooded conditions. An irrigation regime for rice that starts as conventio

Keywords: model structure, uncertainty, modularity, software design patterns, good modelling practices, crop growth and development. This thesis is an account of the development and use of a framework to introduce flexibility in crop modelling. The construction of such a framework is supported by two main beams: the implementation and the modelling beam. Since the beginning of the 1990s, the implementation beam has gained increasing attention in the crop modelling field, notably with the development of APSIM (Agricultural Production Systems sIMulator) in Australia, OMS (Object Modelling System) in the United States, and APES (Agricultural Production and Externalities Simulator) in Europe. The main focus of this thesis is on the modelling beam and how to combine it with the implementation beam. I first explain how flexibility is adopted in crop modelling and what is required for the implementation beam of the framework, namely libraries of modules representing the basic crop growth and development processes and of crop models (i.e. modelling solutions). Then, I define how to deal with this flexibility (i.e. modelling beam) and more specifically I describe systematic approaches to facilitate the selection of the appropriate model structure (i.e. a combination of modules) for a specific simulation objective. While developing the framework, I stress the need for better documentation of the underlying assumptions of the modules and of the criteria applied in the selection of these modules for a particular simulation objective. Such documentation should help to point out the sources of uncertainties associated with the development of crop models and to reinforce the role of the crop modeller as an intermediary between the software engineer, coding the modules, and the end users, using the model for a specific objective. Finally, I draw conclusions for the prospects of such a framework in the crop modelling field. I see its main contribution to (i) a better understanding i

Key words: leaf area; radiation interception; QUEFTS model; fertilizer recovery fractions; nutrient mass fractions; crop growth; calibration; validation; radiation use efficiency; sensitivity analysis East Africa Highland banana yields on smallholder farms in the Great Lakes region are small (11−26 Mg ha−1 cycle−1 in Uganda, 21−43 Mg ha−1 cycle−1 in Burundi and 25−53 Mg ha−1 cycle−1 in Rwanda). The major causes of poor yields are declining soil fertility and soil moisture stress. In order to improve production, knowledge on highland banana physiology, growth patterns and response to fertilization is important, to establish the potential yield of the crop, to quantify the yield gaps between potential and actual yield, and to explore options for closing the yield gaps. Measurements of plant morphological characteristics, radiation interception and biomass (by destructive harvesting) were taken in experimental fields in central and southwest Uganda. Results showed that total leaf area can be estimated by using height and girth (used to estimate middle leaf area) and number of functional leaves. The light extinction coefficient, k determined from photosynthetically active radiation (PAR) measurements over the entire day was 0.7. Banana plants partitioned more dry matter (DM) to the leaves during first phase of vegetative growth, with the pseudostem becoming the dominant sink later with 58% of total DM at flowering, and the bunch at harvest with 53% of the total DM. Changes in dry matter partitioning influenced the allometric relationships between above-ground biomass (AGB in kg DM) and girth (cm), the relationship following a power function during the vegetative phase (AGB = 0.0001 (girth)2.35), and exponential functions at flowering (AGB = 0.325 e0.036 (girth)) and at harvest (AGB = 0.069 e0.068 (girth)). This thesis shows that allometric relationships can be derived and used to estimate biomass and bunch weights. In fertilizer trials, yield increases above the control

The degradation of peatlands is a major and growing source of anthropogenic greenhouse gas (GHG) emissions, and small changes in the management of peatlands can lead to drastic changes in GHG emissions and changes in carbon storage and in the past have indeed done so. GHG emissions from peatlands and the subsidence of peat soils can both probably be decreased by rewetting peatland and by restoring peatland by reducing the intensity of agricultural land use on peat soils. It might even be possible for these agricultural peatlands to revert to being sinks of GHGs. To test whether agricultural peat areas can be turned into GHG sinks and carbon sinks if they are restored and whether GHG emissions can at least be reduced by reducing management intensity and rewetting, a landscape-scale experiment measuring GHG emissions and carbon releases was started in 2005.

Key words: biochemical model of leaf photosynthesis; carbon sink strength; chlorophyll fluorescence; harvest index; leaf protein; leaf senescence; legumes; photosynthetic nutrient use efficiency; Pi recycling; source-sink regulation; ureides One of the most fascinating processes in plant physiology and agronomy is the capability of legumes to associate symbiotically with rhizobial bacteria and arbuscular mycorrhizal (AM) fungi. The legumes supply photosynthates in exchange for nitrogen, derived from biological N2 fixation, and soil nutrients mainly phosphate, obtained from foraging of AM fungi from the soil. The rhizobial and arbuscular mycorrhizal symbioses each may use 4-16% of recently fixed photosynthates to maintain their activity, growth and reserves, but in turn, may supply 100% of the plant nutrient requirements. The C costs of the symbioses are often assumed to limit plant productivity due to photosynthate competition between the microsymbiont and the host. In addition, the C costs are often used as an entry point to understand the evolution of the symbioses. It is intriguing that despite of the symbiotic C costs, plants associated with rhizobia and/or AM fungi often produce more biomass and grains than fertilized plants. Increases in plant growth are traditionally attributed to improved plant nutrition and enhanced photosynthesis. This thesis gives evidence that plants – and particularly legumes – are able to overcome any putative C limitation associated with rhizobial and AM fungal symbioses by increasing the rates of photosynthesis due to sink stimulation, over and above the expected nutritional benefits from the symbioses. Sink stimulation of photosynthesis is a consequence of increased C demand from photosynthesis, which increases the export of triose-P from chloroplasts, recycling more inorganic phosphates and activating more photosynthetic enzymes. In the thesis, I report a literature study, which provides a framework for the quantification of sink s

Crop growth models developed at field level are increasingly used in larger scale studies often in combination with other models to explore management options at the whole-farm scale or for integrated assessment at regional level (e.g. Giller et al., 2006; van Ittersum et al., 2008). Unclear is whether the mechanistic detail of dynamic simulation crop models is required for such applications or whether summary models may be sufficient. To address this issue and to identify relationships that need specific attention in future research, we compared simulations of crop production by two models with a different degree of mechanistic detail.

Soil organic matter (SOM) is an essential component of any sustainable crop production system, both as a nutrient source for the crop and a physical conditioner for the soil. Land use systems based on (flooded) rice- aerobic upland crop rotations, with their annual cycles of wet and dry soil conditions, puddling and plowing, are unique in their influence on SOM dynamics. Recent reports have related yield 'stagnation' in rice-wheat systems in parts of the Indo-Gangetic Plains (IGP) to a decline in SOM quantity and quality. For exploration of the long-term effects of intensive cultivation on soil C and N dynamics, and the consequences for crop yields, a summary model has been developed, based on insights in the underlying processes, to investigate the role of soil organic matter in yield formation in rice-based cropping systems in the IGP and to identify possible reasons for declining yields in the region.Following a review of existing SOM models with emphasis on approaches and principles, to identify processes relevant for long-term dynamics of C and N in rice-based cropping systems, the different components of the systems (SOM and crop) were investigated. A simple analytical model (Yang's model) used to analyze soil carbon balances for different sites in the IGP, showed that carbon demand to maintain soil organic carbon (SOC) levels depends on their initial level, and SOC dynamics are governed by crop performance, determining the rate of carbon input into a soil, and the carbon input through organic amendments. A crop growth model (LINTUL3) was developed describing crop growth of rice for N-limited situations. Nitrogen stress in the model is quantified through the nitrogen nutrition index, a measure of relative crop (leaf and stem) nitrogen content. Subsequently, the knowledge was integrated into a summary model, comprising three modules: a soil organic matter (SOM) module, a soil (SOIL) module, and a crop growth (CROP) module. SOM in the model comprises three pools

Uitspoeling uit de bewortelde bovengrond en denitrificatie uit de bodem zijn verantwoordelijk voor een aanzienlijk deel van de N verliezen. Die verliezen zijn vooral problematisch op zandgrond met een diepe grondwaterspiegel, waar van nature weinig N denitrificeert. Veelvuldig wordt daar de maximumwaarde in Nederland overschreden. Een simulatiemodel is ontwikkeld dat de groei en N opname van vanggewassen (winterrogge en bladrammenas) en de dynamiek van water en stikstof in de bodem beschrijft

Keywords: optimization, multiple goal linear programming, technical coefficient generator, systems approach, peasant agriculture, trade-offsThe use of indicators for sustainability evaluation has been recognized as an important step towardsoperationalizationof the concepts of sustainability and sustainable development . In the context of Natural Resource Management Systems (NRMS), one of the main methodological challenges, whichisthe objective of this thesis, is the development of a methodological framework for sustainability evaluation via indicators at different scales of analysis (e.g. farm household and region).In this thesis, the methodological development and application of a framework for multi-scale sustainability evaluation of NRMS are presented.The frameworkoffers a structured and coherent set of guidelines, developed from an interdisciplinary and systemic perspective, to select, quantify, assess and integrate case-specific indicators derived from short and long term environmental, economic and social concerns (objectives, aspirations) of stakeholders.The analysis of key issues related to the sustainability of NRMS at different scales in the Cercle de Koutiala in the South of Maliillustrates theapplication of the framework for derivation and quantification of indicators for sustainability evaluation at farm household, Arrondissement and Cercle scale. By means of quantitative system analysis tools (e.g. simulation and linear programming models, technical coefficient generator), the framework provides insight in the potentials and limitations of alternatives for NRMS designed at different scales (e.g. policy measures or technological innovations) and the trade-offs between indicators relevant for different stakeholders. The framework explores biophysical opportunities and limitations, rather than predicting behaviour of actors.The multi-scale sustainability evaluation framework can reveal tensions between objectives across and within scales. Indicatorsretain

Keywords: improved fallows, biological N 2 -fixation, nitrogen cycling, nitrate leaching, oxide emissions, N mineralization -immobilization, granitic sandsThis thesis focuses on nitrogen: its acquisition in cropping systems through biological N 2 -fixation and subsoil capture, its release by legume prunings and litter, its use by maize and its loss through leaching and as nitrous oxide gas. The context of the study is improved fallows using leguminous trees/shrubs on a sandy clay loam soil under sub-humid conditions inZimbabwe.Two-year legume fallows of Sesbania Sesban, Acacia angustissima and Cajanuscajan were evaluated for their residual N effects on two subsequent maize crops under minimum and conventional tillage management. The proportion of N 2 -fixed in litter was 56, 55, 84 and 58 % for Acacia, Sesbania , Cajanus, and cowpea, respectively, resulting in inputs of biologically fixed N of 122, 84, 97 and 28 kg N ha -1 . Maize growth following the legumes for two subsequent cropping seasons was in most cases not directly related to the N inputs due to pest infestation and drought. On a sandy soil, these legumes adapted poorly and did not improve N cycling.Soil samples for mineral N determination in profiles were taken at fallow termination and every two weeks during maize cropping with an auger in 0.2 m sections to 1.2 m depth. Pre-season NH 4+ amounts were > 12 kg N ha -1 in the 0-0.2 m layer for treatments that had a large litter layer. There was a flush of NO 3- -N in the Sesbania and Acacia plots with the first rains. Topsoil NO 3- had increased to >29 kg N ha -1 by the time of establishing the maize crop. NO 3- -N amounts decreased rapidly within three weeks of maize planting to 9 and 11 kg N ha -1 for the Sesbania and Acacia plots, respectively. Total NO 3- -N leaching losses from the 0-0.4mlayer ranged from 29-40 kg ha -1 for Sesbania and Acacia plots within two weeks when 104 mm rainfall was received to an already fully recharged soil profile. NO 3- -N t