Raising surface water levels in peat areas with dairy farming: Upscaling hydrological, agronomical and economic effects from farm-scale to local scale

Raising surface water levels in peat areas is a measure to reduce soil subsidence, to prevent decay of wooden foundations and to stimulate wet nature restoration and reduce greenhouse gas emissions. However, in these areas dairy farms are present and farming at wetter soils is difficult due to lower bearing capacity of the soil for cattle and machines. Water boards are responsible for the water management of peat areas and thus have to evaluate the effects of water management strategies for the different land use functions. Therefore the hydrological, agronomical and economic effects of different surface water levels are calculated for dairy farms. The ‘Waterpas’ model is used to simulate hydrological effects, dairy farm management and economic results for different meteorological years. The raised surface water level causes a decrease in gross grass yield and a reduction in grass quality. This leads to higher costs and less farmers’ income relative to a reference situation with a freeboard of 60 cm. Raising the surface water increases the average costs for farmers with €89 ha⁻¹ year⁻¹ for a freeboard of 50 cm, €170 ha⁻¹ year⁻¹ for a freeboard of 40 cm and €239 ha⁻¹ year⁻¹ for a freeboard of 30 cm.However, water boards are not only interested in the effects for individual farms, but also for an entire region. A new spatial method was developed for upscaling from farm to polder level. For grassland fields in a typical Dutch peat area classes can be distinguished using GIS data on soil type, soil surface elevation, surface water levels, locations of farms and farm characteristics. The classification is based on 4 classes of freeboards of the grassland fields and 7 typical distributions of grassland fields within a dairy farm. The farm economics were simulated for these typical classes. An increase in costs was simulated for the whole polder Zegveld (1400 ha grassland) of €119,000 year⁻¹ at 10 cm surface water level rise; €133,000 year⁻¹ at 20 cm surface water level rise and €185,000 year⁻¹ at 30 cm surface water level rise.For an integral environmental evaluation of changing hydrological conditions it is advised to incorporate effects on nutrient emission to groundwater and surface water and emission of ammonia and greenhouse gases to the atmosphere.     

Bio-economic evaluation of dairy farm management scenarios using integrated simulation and multiple-criteria models

Appropriate selection of holistic management strategies for livestock farming systems requires: (1) understanding of the behaviour of, and interrelations between, the different parts of the system; (2) knowledge of the basic objectives of the decision maker managing such enterprise; and (3) understanding of the system as a whole in its agro-ecoregional context. A decision-support system based on simulation and mathematical programming techniques has been built to represent pastoral dairy production systems. The biological aspects (grass growth, grazing, digestion and metabolism, animal performance) are represented by simulation studies under a variety of management regimes. The outputs from the simulation runs (such as pasture utilisation, stocking rates, milk yields, fertilizer use, etc.) are used as data input to the multi-criteria decision-making models, and the latter have been used to select the management strategies which make the most efficient use of the farm's resources (i.e. land, animals, pastures). The paper discusses the effects and implications of different management scenarios and policies on the bio-economic performance of highland dairy farms in Costa Rica. Nevertheless, the model frameworks are generic and can be adapted to different farming systems or ruminant species. The effect of model formulation and sensitivity, different decision-maker objectives, and/or activity or constraint definitions on management strategy selection are also analysed.     

Use of animal density to estimate manure nutrient recycling ability of Wisconsin dairy farms

Animal density is increasingly being used as an indicator of agricultural nitrogen (N) and phosphorus (P) loss potential in Europe and the US. This study estimated animal-cropland ratios for over 800 Wisconsin dairy farms to: (1) illustrate the impact of alternative definitions of this ratio; (2) evaluate how the definition of ‘cropland’ would affect Wisconsin dairy farmers’ ability to comply to manure N and P land spreading standards and (3) investigate the potential of using an animal density standard for targeting manure management plan implementation on Wisconsin dairy farms. Animal density calculations based on total cropland area indicate that 95% of Wisconsin dairy farmers have sufficient cropland for recycling manure according to a N-based nutrient management standard. Calculating animal density based on tilled cropland area decreases this value to 79% of dairy farms. Implementation of a P-based standard increases the land requirement for manure application, and a large proportion of Wisconsin dairy farms (37% based on total cropland and 75% based on tilled cropland) would lack sufficient land area for recycling manure P. When the area of cropland on which manure is actually spread is used to calculate animal density, it is clear that the majority of farms do not currently meet either manure N- or P-based land application standards. Reasons for not utilizing the full cropland base for manure application are unclear, but regional differences suggest soil texture, land tenure, and development pressures may limit the proportion of cropland receiving manure. These results indicate the need to better understand factors influencing cropland management and manure spreading behavior on Wisconsin dairy farms.     

Modelling dairy cattle feeding in the South-East region of Brazil

Computer modelling techniques were applied to study the structure of traditional dairy farms in the South-East region of Brazil and to help define research priorities and policies. Animal feeding is considered the principal factor affecting dairy cattle performance in the study. Knowledge of animal nutrition and feed supply from Brazilian and other literature was synthesized in two mathematical models. One model deals with the optimization of resources used in supplementary feeding for dairy cows under grazing; the other predicts dairy cow performance under a range of feeding conditions imposed by changes in the level of supplementation, stocking rate and calving date. Both models are empirical in nature. The modelling approach shows itself to be a useful means of defining research priorities and making recommendations on practical aspects of dairy cow feeding and management.     

Exploring changes in world ruminant production systems

In the past 30 years world production of ruminant meat and milk has increased by about 40%, while the global area of grassland has increased by only 4%. This is because most of the increase in ruminant meat and milk production has been achieved by increasing the production in mixed and landless production systems and much less so in pastoral systems. Pastoral systems depend almost exclusively on grazing, while mixed and landless systems rely on a mix of concentrates (food crops) and roughage, consisting of grass, fodder crops, crop residues, and other sources of feedstuffs. A model was developed to describe these two aggregated production systems for different world regions, each having typical production characteristics, such as milk production per animal for dairy cattle, and off-take rates and carcass weights for non-dairy cattle, sheep and goats. The energy needed by the animals for the production of meat and milk is calculated on the basis of requirements for maintenance, grazing and labour, pregnancy, and lactation. We implemented the FAO Agriculture Towards 2030 projection for crop and livestock production and assumed that the past trend in the area of grassland will continue in the coming three decades. This assumption implies a rapid intensification of grassland management with a 33% increase in global grass consumption, which will only be possible with increasing fertilizer inputs, use of grass-clover mixtures and improved grassland management.     

DAIRYPRO—a knowledge-based decision support system for strategic planning on sub-tropical dairy farms. I. System description

DAIRYPRO is a combination decision support and expert system consisting of two modules. The system is designed to help dairy farmers in northern Australia make strategic decisions about their farm. It can be run by dairy extension officers as a consultation package for farmers. The system is based on a combination of statistical models developed from real farm survey data and opinions from experts in the field of dairy farming. The first module gathers together the data needed to run predictive models and the system of rules that enable the program to make estimates of regional average production (using predictive statistical models) and achievable production (using heuristics). These predictions can be compared to the farmer's actual production. Farmers are then encouraged to make hypothetical changes to the inputs on their farm, and `what-if' scenarios of increased or decreased milk production are displayed. The profit or loss associated with these changes is determined. The second module of DAIRYPRO uses the `rules of thumb' of an expert to determine how four pre-defined components of the dairy farm compare to optimum performance. These components are: the winter feeding program, summer feeding program, concentrate feeding program and capital and labour inputs. DAIRYPRO is a useful decision support package for dairy farmers, bank managers, loans officers and farm consultants. ©     

Climate change affects farm nitrogen loss – A Swiss case study with a dynamic farm model

The response of arable crops and grasslands to climatic changes and increasing CO₂ concentration has implications for the operation of farms, in particular for the management of resources such as nitrogen. A simple dynamic farm model (Stella^© model ‘CH-Farm’) was used to analyze the shift in the ratio of N lost via leaching, denitrification and volatilization to N exported with products from dairy or arable production (here defined as relative N loss). The model was run for two types of farms typical of Swiss conditions. Growth parameters for two sequentially grown crops (winter wheat and maize) and grass were determined with the process-oriented models Pasture Simulation Model (PaSim) and CropSyst, respectively. CH-Farm was forced with two assumptions about the transient change in temperature and precipitation, and with or without CO₂ effects. Relative N loss for the baseline was around 1.33 for the dairy-type farm and around 1.05 for the arable-type farm and increased progressively over the 100-year simulation period, with the largest shift in response to the dry/hot scenario. Soil N pools decreased with all scenarios, but at different rates. CO₂ fertilization alleviated the effect of climate change due to increased productivity and N fixation in plants. Adjustment of the growth parameters to progressively increasing temperatures reduced the difference between farm types and positively affected relative N losses mainly through increased productivity and reduced fallow periods between crops. The results suggest that the impact of climate change on relative farm-level N loss depends on physiological adjustments to climatic scenarios, whereas the distribution of land between dairy and arable crop production is less important, and that simple cultivar adjustments can help to mitigate negative effects of climate change on farm-level N use.     

Exploring options for sustainable beef cattle ranching in the humid tropics: a case study for the Atlantic Zone of Costa Rica

Options are explored for sustainable, i.e. non-soil-nitrogen (N) mining, beef production in the humid tropical Atlantic Zone of Costa Rica using a modelling approach. Tools used are linear programming and a technical coefficient generator called PASTOR. Due to the combination of high rainfall, highly permeable soils and high N turnover rates, N losses are high and current natural pastures are calculated to mine soil N reserves with 40–60 kg ha⁻¹ year⁻¹. With current financial returns, there is no economic incentive for farmers to convert soil mining natural pastures to sustainable alternatives, viz. grass–legume mixtures or fertilized improved grasslands. When degradation of natural pastures over time due to soil N mining is considered in the model, it becomes economically attractive to replace these pastures with grass–legume mixtures. Sustainable beef cattle ranching is best realized by integrated intensification that raises total economic returns, i.e. use of grass–legumes or fertilized pastures, high levels of feed supplements and improved herd management techniques.     

GAMEDE: A global activity model for evaluating the sustainability of dairy enterprises Part I – Whole-farm dynamic model

 Crop-livestock farms are complex systems. The interactions operating in such systems involve decisional, biophysical, structural, and environmental factors. Moreover, as farmers face a large range of management options, tools are needed to support their decision-making to enable them to reach production levels meeting their objectives and compatible with their human and physical resources, while controlling their effects on the environment. Gamede, a whole-dairy-farm model, has been developed to explore this complexity and to represent dynamically the effect of management decisions on biomass and nitrogen flows and on numerous sustainability indicators, such as milk and forage crop productivity, labour requirements, nitrogen balance, and nitrogen efficiency.This article describes the integration of six modules accounting for biophysical processes in a dairy farm (forage production; forage conditioning; herd demography; milk, excreta and animal biomass productions; grazing, quality of fertilisers; and nitrogen gaseous emissions) together with a decision system accounting for the farmer’s strategy and technical operations. Most of the six biophysical modules incorporate mathematical models from the literature, but the decision system stems from our own original work.Six commercial farms with different structures, agro-climatic conditions and management strategies were used for validation. The model can explain the differences found in their sustainability indicators at the year scale. The intra-year variability of the main biomass stocks and flows is also well explained. This quantitative validation was completed by a qualitative validation from researcher, adviser and farmer points of view, including simulations of prospective scenarios.     

Dairy farm nutrient management model. 1. Model description and validation

Intensive dairy farming results in significant phosphorus (P) emission to the environment. Field data indicates that farm-gate P surplus is highly positive in Finland and strategies to mitigate the surplus are needed. The objectives of this study were to build a P cycle model for dairy farms (1) and to validate the model with independent field data (2). The dairy farm nutrient management model (“Lypsikki”) described in this paper includes three sub-models: (1) soil and crop, (2) dairy herd and (3) manure management. The model is based on empirical regression equations allowing estimations of crop and milk yields in response to increased fertilisation and nutrient supply, respectively. In addition, the model includes a dynamic simulation model of the dairy herd structure and calculation of the farm-gate nutrient surplus. The model was validated with independent annual (average for 1-4 years) farm-gate P surplus data from 21 dairy farms. Model simulations were conducted using two levels of soil productivity, mean (M) and low (L). The model validation indicated a strong relationships between model-predicted and observed farm-gate P surplus: (M: R² = 0.77 and L: R² = 0.80). The line bias between the model-predicted and observed data was negligible and insignificant (P > 0.6) suggesting a robustness of the model. The mean biases were relatively high and significant (M: 4.7 and L: 1.8 kg/ha, P < 0.001), but evidently related to overestimation of crop yields that has to be taken into account when using the model on a single farm. The prediction error of the model (observed minus predicted P surplus) was significantly correlated to the difference between simulated and observed P import in feeds (M: R² = 0.55 and L: R² = 0.51). This suggests either that all the dairy farms did not fully exploit the possibilities in the crop production or that all the model assumptions are not correct. The effects of purchased feed and fertiliser P and exported milk P (per cow or cropping area) on farm-gate P surplus were of the same magnitude in both observed and simulated data. This implies that the model developed can be used as a management decision tool to find strategies to mitigate P surplus on dairy farms.     

Kleingrass growth and utilization by growing steers

A model of kleingrass (Panicum coloratum L.) growth and utilization by steers is presented. The model included stochastic inputs of climatological characteristics, water retention at different soil depths, rainfall runoff, potential evapotranspiration, forage growth, forage intake and steer performance. The model was used in a 2 × 3 × 4 factorial experiment where the factors were energy systems (ARC, 1965 versus NRC, 1976), stocking rates (2·47 head per hectare, 4·32 head per hectare and 6·18 head per hectare), and four management options. Individual steer weights by months were not significantly affected by the use of either energy system. Steer weights at the end of the grazing season were affected (F = 0·06) by energy system, the NRC system predicting 7·2 kg per head more liveweight gain than the ARC system. The light stocking rate had greater (P = 0·01?0·13) daily gains over months than the heavier stocking rates. The heavy stocking rate resulted, however, in greater (P < 0·05) production per hectare per year than the lighter stocking rates. Season-long production per hectare favored (P < 0·1) management options that removed steers immediately after forage was consumed rather than anticipating rainfall and new forage growth. The light stocking rate had the least mean seasonal production per hectare (P < 0.·05) but also had the least year-to-year variability. The heavy stocking rater yielded the greater (P < 0·05) mean seasonal production per hectare but the year-to-year variation was much greater. It was emphasized that the use of such probabilities of production could aid the grazier in making stocking rate and related decisions.     

Analysing farming practices to develop a numerical,operational model of farmers’ decision-making processes: An irrigated hay cropping system in France

Conventional water management in the Crau plain needs to be modified to ensure higher irrigation efficiency, better crop production and quality, and reduced environmental impacts. Because experimental approaches to test modifications of water management are difficult in relation to border irrigation, simulation may provide an alternative. We describe the development of a conceptual model of the decision-making process that determines the irrigation management of a cropping system, on which a simulation model is to be based. Interviews focused on water management were carried out, to understand how farmers manage their irrigation and how their decisions determine the technical system applied on the farm. These interviews were then analyzed using the “model for action” concept, to generate a conceptual model of the decision system, which is organized as a sequence of decision rules describing irrigation management. This model contains five elements: (1) spatial and temporal factors relevant to decision-making in terms of irrigation and hay cropping; (2) no interaction between the grassland cropping system and the sheep rearing system; (3) five rules to describe irrigation management in the cropping system; (4) major water distribution constraints; and (5) two inter-related operations, hay mowing and irrigation. The rules for irrigation decision-making are written as: “If <Indicator><Operator><Threshold> Then <Action1> Else <Action2>”. This conceptual model was used as the basis of a decision support system that includes models of grass growth and hydrology.     

Optimising land and fertiliser N usage in grassland systems where grazing and conservation areas are separate

In grassland systems where grazing and conservation areas are separate, the farmer must decide on the N rates to use in the two areas and on the proportion of the total area to devote to conservation. Quantified relationships between N supply and herbage yields, and estimates of DM requirements, were used to determine the optimum split of total area for cutting and grazing and the N rates to be used to maximise stocking rate for a fixed total fertiliser N usage, or to minimise N usage for a fixed stocking rate. Results indicated that the optimum split of area was around 70% grazed, 30% cut for conservation, with higher N rates on the cut area than on the grazed area. The method also allowed estimates to be made of the economic optimum fertiliser N usage and stocking rate.     

基于植被指数的锡林河流域生物量动态遥感估算

本研究以地面样方调查结合2000-2013年MODIS—NDVI数据,建立样方生物量和遥感数据的关系模型,反演锡林河流域产草量的时空分布。研究结果表明：建立的植被指数模型相关系数达到0.6以上,模型精度为80%,线性模型作为遥感估测应用可行;锡林河流域年平均产草量鲜重为1001kg/hm2,空间分布呈现东南高-西北低的空间分布规律;2000-2013年,产草量年际间变化大,变异系数为51.6%,产草量总体呈波动上升趋势。锡林河流域草原产草量的时空变化与主要气候因素（气温、降水）关系密切,特别是受降水量的时空变化影响更为显著。本研究结论可以为有效地保护和利用草地资源、合理配置载畜量和恢复草原生态环境提供有效的技术支持和保障。     

Assessment of the quality of farmers’ environmental management and its effects on resource use efficiency: a Dutch case study

Most research on efficiency of farm management focuses on the relationship between an array of individual management variables and technical performance. Few studies have analysed the relationship between the total complex of farm management and technical farm performance. The present study uses the concept of strategic management and applies it to nitrogen management on Dutch arable farms. Data Envelopment Analysis (DEA) was used to assess farm specific efficiency scores for fertiliser use. For a sub-sample of the farms used in the DEA analysis, the strategic management concept was addressed by means of a workshop. The management elements (objectives, internal analysis of weaknesses and strengths, external analysis of opportunities and threats, and synthesis) were made operational by relating them to the introduction of the Mineral Accounting System (MINAS) by 2001 for Dutch arable farms. The external analysis was evaluated by questions about the MINAS rules; the internal analysis was evaluated by questions on the expected consequences for the farmer's N management. An interactive simulation model evaluating whether farmers were able to choose the optimal fertilisation strategy in view of MINAS assessed the ‘quality of the synthesis’. A positive significant correlation was found between the ‘quality of the synthesis’ and N efficiency.     

基于Web的奶牛场管理信息系统

介绍基于JSP+SPrvlet+Javabean模式开发的、适合中型奶牛场使用的奶牛场管理信息系统,分为牛群管理、产乳管理、牛群繁殖、统计与分析、养牛场管理及系统管理功能6个方面,可以对奶牛及奶牛场各种技术数据进行分析与综合整理,是一种实用、经济和操作简便的奶牛场信息资料管理系统.     

Farmers' views of the prospects for agriculture in a metropolitan area

To determine how farmers view their future in agriculture under metropolitan development pressures, we interviewed 52 dairy and fruit/vegetable farmers in the suburbs of Worcester, Massachusetts, a metropolitan area in the heavily urbanized northeast region of the US. Three measures were used for whether the farmers are building up their farms or are anticipating having to leave agriculture: actions taken in the past five years, actions planned for the next five years and expectations of the future status of the land. The farmers were more positive and optimistic than would be expected from the ‘impermanence syndrome’ thought to cause the decline of agriculture near cities. Their answers varied more with personal and household characteristics than characteristics of the farm or of the surrounding area. This contradicts the belief that farmers' response to metropolitan pressures mainly is a consequence of land-use competition and the presence of a non-farming population.     

Differences in sheep production between sites within a heterogeneous area

Two stocking rate experiments were performed within an area of 160 ha with (a) weaners (randomised blocks) and (b) breeding ewes (completely randomised design). Using a quadratic economic objective function to combine outputs of wool, lambs, etc., the range of estimates of optimum stocking rates was, for weaners, from 9 to more than 25 per hectare and, for ewes 8 to 20 per hectare. Analyses of variance showed that residual errors were large compared with the effects of stocking rate, management and years. Where attributes of production were relatively accurately measured and sampled, the between site-within stocking rate variance accounted for approximately 75% of the total residual error.Differences in soil depth, aspect, slope, soil moisture and nutrient characteristics are suggested as the fundamental causes of these block differences. However, the few comparisons available did not permit further analysis. Possible benefits to both farm management and experimentation from predicting site potential from these parameters are discussed.     

The economic value of glyphosate-resistant canola in the management of two widespread crop weeds in a Western Australian farming system

Nitrogen fertilisation is a source of potential groundwater pollution and is a key issue in the current debate about the environmental impacts of agricultural production. It is also a key element in the management of cropping systems by farmers. Therefore, cropping system design entails the understanding and evaluation of farmers' fertilisation practices. Biophysical models describing the soil–plant system can serve this purpose. A comparison between model outputs and farmers' practices was made of a set of 128 apple (Malus domestica Borkh.) plots from 31 members of a farmers' co-operative in south-eastern France. Farmers' fertilisation practices were compared with theoretical practices generated by a series of soil–plant system models of increasing complexity, each model giving the amount of nitrogen that should be applied to the plot according to the knowledge included in the model. The model that reproduced farmers' fertilisation practices most closely was the most complex, taking all plant requirements, soil organic matter and residue mineralisation, denitrification and irrigation supply into account. A Monte Carlo method showed that the differences between farmers' practices and model outputs were not random. Spatial analysis showed a strong spatial organisation of these differences, mainly due to three farms. This congruence between farmers' practices and model outputs suggests the existence of some indicators that depict the N nutrition status of the orchard as a basis for rules indicating how much nitrogen should be applied. The spatial analysis suggests the existence of farmer and neighbourhood effects, which need to be explained. Models appear to be useful tools to study farmers' practices by removing biophysical effects (soil, variety, etc.). This raises new questions concerning agricultural research at the interface between the biophysical and social sciences.     

干草原禾草草场关键灌水期与缺水损失函数研究

本文在田间试验的基础上,研究了天然草场禾草十杂类草群落的水分敏感反应期,关键灌水期、缺水损失函数、亏水敏感指数,为提高灌溉草场的管理水平,水源工程的优化调度、灌溉草场的经济效益评价提供了依据。