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LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems – Beef cattle) is a generic, mechanistic model designed to quantify potential and feed-limited growth, which provides insight in the biophysical scope to increase beef production (i.e. yield gap). Furthermore, it enables identification of the bio-physical factors that define and limit growth, which provides insight in management strategies to mitigate yield gaps. The aim of this paper, third in a series of three, is to evaluate the performance of LiGAPS-Beef with independent experimental data. After model calibration, independent data were used from six experiments in Australia, one in Uruguay and one in the Netherlands. Experiments represented three cattle breeds, and a wide range of climates, feeding strategies and cattle growth rates. The mean difference between simulated and measured average daily gains (ADGs) was 137 g/day across all experiments, which equals 20.1% of the measured ADGs. The root mean square error was 170 g/day, which equals 25.0% of the measured ADGs. LiGAPS-Beef successfully simulated the factors that defined and limited growth during the experiments on a daily basis (genotype, heat stress, digestion capacity, energy deficiency and protein deficiency). The simulated factors complied well to the reported occurrence of heat stress, energy deficiency and protein deficiency at specific periods during the experiments. We conclude that the level of accuracy of LiGAPS-Beef is acceptable, and provides a good basis for acquiring insight in the potential and feed-limited production of cattle in different beef production systems across the world. Furthermore, its capacity to identify factors that define or limit growth and production provides scope to use the model for yield gap analysis. [ABSTRACT FROM AUTHOR]

The model LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems – Beef cattle) has been developed to assess potential and feed-limited growth and production of beef cattle in different areas of the world and to identify the processes responsible for the yield gap. Sensitivity analysis and evaluation of model results with experimental data are important steps after model development. The first aim of this paper, therefore, is to identify which parameters affect the output of LiGAPS-Beef most by conducting sensitivity analyses. The second aim is to evaluate the accuracy of the thermoregulation sub-model and the feed intake and digestion sub-model with experimental data. Sensitivity analysis was conducted using a one-at-a-time approach. The upper critical temperature (UCT) simulated with the thermoregulation sub-model was most affected by the body core temperature and parameters affecting latent heat release from the skin. The lower critical temperature (LCT) and UCT were considerably affected by weather variables, especially ambient temperature and wind speed. Sensitivity analysis for the feed intake and digestion sub-model showed that the digested protein per kg feed intake was affected to a larger extent than the metabolisable energy (ME) content. Sensitivity analysis for LiGAPS-Beef was conducted for ¾ Brahman×¼ Shorthorn cattle in Australia and Hereford cattle in Uruguay. Body core temperature, conversion of digestible energy to ME, net energy requirements for maintenance, and several parameters associated with heat release affected feed efficiency at the herd level most. Sensitivity analyses have contributed, therefore, to insight which parameters are to be investigated in more detail when applying LiGAPS-Beef. Model evaluation was conducted by comparing model simulations with independent data from experiments. Measured heat production in experiments corresponded fairly well to the heat production simulated with the thermoregulation sub-model. Measured ME contents from two data sets corresponded well to the ME contents simulated with the feed intake and digestion sub-model. The relative mean absolute errors were 9.3% and 6.4% of the measured ME contents for the two data sets. In conclusion, model evaluation indicates the thermoregulation sub-model can deal with a wide range of weather conditions, and the feed intake and digestion sub-model with a variety of feeds, which corresponds to the aim of LiGAPS-Beef to simulate cattle in different beef production systems across the world. [ABSTRACT FROM AUTHOR]

The expected increase in the global demand for livestock products calls for insight in the scope to increase actual production levels across the world. This insight can be obtained by using theoretical concepts of production ecology. These concepts distinguish three production levels for livestock: potential (i.e. theoretical maximum) production, which is defined by genotype and climate only; feed-limited production, which is limited by feed quantity and quality; and actual production. The difference between the potential or limited production and the actual production is the yield gap. The objective of this paper, the first in a series of three, is to present a mechanistic, dynamic model simulating potential and feed-limited production for beef cattle, which can be used to assess yield gaps. A novelty of this model, named LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems – Beef cattle), is the identification of the defining factors (genotype and climate) and limiting factors (feed quality and available feed quantity) for cattle growth by integrating sub-models on thermoregulation, feed intake and digestion, and energy and protein utilisation. Growth of beef cattle is simulated at the animal and herd level. The model is designed to be applicable to different beef production systems across the world. Main model inputs are breed-specific parameters, daily weather data, information about housing, and data on feed quality and quantity. Main model outputs are live weight gain, feed intake and feed efficiency (FE) at the animal and herd level. Here, the model is presented, and its use is illustrated for Charolais and Brahman × Shorthorn cattle in France and Australia. Potential and feed-limited production were assessed successfully, and we show that FE of herds is highest for breeds most adapted to the local climate conditions. LiGAPS-Beef also identified the factors that define and limit growth and production of cattle. Hence, we argue the model has scope to be used as a tool for the assessment and analysis of yield gaps in beef production systems. [ABSTRACT FROM AUTHOR]

Mineral phosphorus (P) used to fertilise crops is derived from phosphate rock, which is a finite resource. Preventing and recycling mineral P waste in the food system, therefore, are essential to sustain future food security and long-term availability of mineral P. The aim of our modelling exercise was to assess the potential of preventing and recycling P waste in a food system, in order to reduce the dependency on phosphate rock. To this end, we modelled a hypothetical food system designed to produce sufficient food for a fixed population with a minimum input requirement of mineral P. This model included representative crop and animal production systems, and was parameterised using data from the Netherlands. We assumed no import or export of feed and food. We furthermore assumed small P soil losses and no net P accumulation in soils, which is typical for northwest European conditions. We first assessed the minimum P requirement in a baseline situation, that is 42% of crop waste is recycled, and humans derived 60% of their dietary protein from animals (PA). Results showed that about 60% of the P waste in this food system resulted from wasting P in human excreta. We subsequently evaluated P input for alternative situations to assess the (combined) effect of: (1) preventing waste of crop and animal products, (2) fully recycling waste of crop products, (3) fully recycling waste of animal products and (4) fully recycling human excreta and industrial processing water. Recycling of human excreta showed most potential to reduce P waste from the food system, followed by prevention and finally recycling of agricultural waste. Fully recycling P could reduce mineral P input by 90%. Finally, for each situation, we studied the impact of consumption of PA in the human diet from 0% to 80%. The optimal amount of animal protein in the diet depended on whether P waste from animal products was prevented or fully recycled: if it was, then a small amount of animal protein in the human diet resulted in the most sustainable use of P; but if it was not, then the most sustainable use of P would result from a complete absence of animal protein in the human diet. Our results apply to our hypothetical situation. The principles included in our model however, also hold for food systems with, for example, different climatic and soil conditions, farming practices, representative types of crops and animals and population densities. [ABSTRACT FROM AUTHOR]

Ethiopia is one of the countries most vulnerable to the impacts of climate variability and change on agriculture. The present study aims to understand and characterize agro-climatic variability and changes and associated risks with respect to implications for rainfed crop production in the Central Rift Valley (CRV). Temporal variability and extreme values of selected rainfall and temperature indices were analysed and trends were evaluated using Sen's slope estimator and Mann–Kendall trend test methods. Projected future changes in rainfall and temperature for the 2080s relative to the 1971–90 baseline period were determined based on four General Circulation Models (GCMs) and two emission scenarios (SRES, A2 and B1). The analysis for current climate showed that in the short rainy season (March–May), total mean rainfall varies spatially from 178 to 358 mm with a coefficient of variation (CV) of 32–50%. In the main (long) rainy season (June–September), total mean rainfall ranges between 420 and 680 mm with a CV of 15–40%. During the period 1977–2007, total rainfall decreased but not significantly. Also, there was a decrease in the number of rainy days associated with an increase (statistically not significant) in the intensity per rainfall event for the main rainy season, which can have implications for soil and nutrient losses through erosion and run-off. The reduced number of rainy days increased the length of intermediate dry spells by 0·8 days per decade, leading to crop moisture stress during the growing season. There was also a large inter-annual variability in the length of growing season, ranging from 76 to 239 days. The mean annual temperature exhibited a significant warming trend of 0·12–0·54 °C per decade. Projections from GCMs suggest that future annual rainfall will change by +10 to −40% by 2080. Rainfall will increase during November–December (outside the growing season), but will decline during the growing seasons. Also, the length of the growing season is expected to be reduced by 12–35%. The annual mean temperature is expected to increase in the range of 1·4–4·1 °C by 2080. The past and future climate trends, especially in terms of rainfall and its variability, pose major risks to rainfed agriculture. Specific adaptation strategies are needed for the CRV to cope with the risks, sustain farming and improve food security. [ABSTRACT FROM PUBLISHER]

Bangladesh faces huge challenges in achieving food security due to its high population, diet changes, and limited room for expanding cropland and cropping intensity. The objective of this study is to assess the degree to which Bangladesh can be self-sufficient in terms of domestic maize, rice and wheat production by the years 2030 and 2050 by closing the existing gap (Yg) between yield potential (Yp) and actual farm yield (Ya), accounting for possible changes in cropland area. Yield potential and yield gaps were calculated for the three crops using well-validated crop models and site-specific weather, management and soil data, and upscaled to the whole country. We assessed potential grain production in the years 2030 and 2050 for six land use change scenarios (general decrease in arable land; declining ground water tables in the north; cropping of fallow areas in the south; effect of sea level rise; increased cropping intensity; and larger share of cash crops) and three levels of Yg closure (1: no yield increase; 2: Yg closure at a level equivalent to 50% (50% Yg closure); 3: Yg closure to a level of 85% of Yp (irrigated crops) and 80% of water-limited yield potential or Yw (rainfed crops) (full Yg closure)). In addition, changes in demand with low and high population growth rates, and substitution of rice by maize in future diets were also examined. Total aggregated demand of the three cereals (in milled rice equivalents) in 2030 and 2050, based on the UN median population variant, is projected to be 21 and 24% higher than in 2010. Current Yg represent 50% (irrigated rice), 48-63% (rainfed rice), 49% (irrigated wheat), 40% (rainfed wheat), 46% (irrigated maize), and 44% (rainfed maize) of their Yp or Yw. With 50% Yg closure and for various land use changes, self-sufficiency ratio will be > 1 for rice in 2030 and about one in 2050 but well below one for maize and wheat in both 2030 and 2050. With full Yg closure, self-sufficiency ratios will be well above one for rice and all three cereals jointly but below one for maize and wheat for all scenarios, except for the scenario with drastic decrease in boro rice area to allow for area expansion for cash crops. Full Yg closure of all cereals is needed to compensate for area decreases and demand increases, and then even some maize and large amounts of wheat imports will be required to satisfy demand in future. The results of this analysis have important implications for Bangladesh and other countries with high population growth rate, shrinking arable land due to rapid urbanization, and highly vulnerable to climate change.

In the last decade the multifunctional agriculture (MFA) concept has emerged as a key notion in scientific and policy debates on the future of agriculture and rural development. Broadly speaking, MFA refers to the fact that agricultural activity beyond its role of producing food and fibre may also have several other functions such as renewable natural resources management, landscape and biodiversity conservation and contribution to the socio-economic viability of rural areas. The use of the concept can be traced to a number of wider societal and political transformation processes, which have influenced scientific and policy approaches in different ways amongst countries and disciplines. This paper critically discusses various existing research approaches to MFA, both from natural and social sciences. To this aim different strands of literature are classified according to their focus on specific governance mechanisms and levels of analysis into four main categories of research approaches (market regulation, land-use approaches, actor-oriented and public regulation approaches). For each category an overview of the state-of-the-art of research is given and an assessment is made of its strengths and weaknesses. The review demonstrates that the multifunctionality concept has attracted a wealth of scientific contributions, which have considerably improved our understanding of key aspects of MFA. At the same time approaches in the four categories have remained fragmented and each has limitations to understand MFA in all its complexity due to inherent constraints of applied conceptualizations and associated disciplinary backgrounds. To go beyond these limitations, we contend, new meta-level frameworks of analysis are to be developed that enable a more integrated approach. The paper concludes by presenting the main lines of an integrative, transitional framework for the study of MFA, which analyses multifunctional agriculture against the background of wider societal change processes towards sustainability and identifies a number of key elements and research challenges for this.

In different parts of the world, there is an urgent need for redesigning and innovating farming systems. Such a process may be supported by model-based explorations that enable ex-ante evaluation of a broad range of alternatives. Since a variety of viable patterns of farm development exists related to farm resource endowment and farmer's strategy, model-based explorations should be able to capture the existing variation in resource endowment and strategies in order to have impact on strategic farm management. In this paper, we present an overview of the model-based explorative method based on the MILP model Farm Images, applied to explore options for sustainable development of vegetable farms in Canelón Grande, Uruguay. The method is used to gain insight into the impact of current farm resource endowment on the possibilities for sustainable development and on the resource use efficiency at farm scale. We maximized farm income for 128 different farm types in an environment-oriented scenario and in an income-oriented scenario. Farm types were defined by combining 4 farm sizes, 2 labor endowments, 4 irrigation endowments, 2 soil quality combinations and 2 mechanization levels. The results demonstrate a strong impact of farm resource endowment on possibilities for sustainable development, as well as synergy between labor, land and irrigated area on resource-use efficiency at farm scale. Farms with 10ha of land or less, representing 47% of the farms in the Canelón Grande region, could only achieve a family income higher than the average income of Uruguayan families when the irrigated area was ca. 40% of the farm area. The achievement of environmental targets was less costly in terms of income on farms with a low rather than high labor availability per unit area and on farms with irrigation facilities.