191 research outputs found
Observing and Simulating Temperate Grasslands in Central Europe
This presentation summarises recent activities to observe grassland features using remote sensing and uses this data to feed mechanistic simulation models for temperate grassland vegetation in Central Europe, in order to assess underlying processes that are difficult to observe. Public interest has recently focused on grassland ecosystem services, such as carbon stocks, nitrate retention and greenhouse gas emissions; variables that in principle can be simulated using models. However, current grassland models suffer from the fact that species dynamics in grasslands are very active, and may change in response to water supply and management. As different species come with different traits, a uniform representation of grassland in models is often not wise. This contribution highlights the potential of remote sensing in this problem space and gives an overview of where we stand now when aiming at predicting grass biomass yields and quality features in heterogeneous landscapes of temperate climate
The performance of the EU-Rotate_N model in predicting the growth and nitrogen uptake of rotations of field vegetable crops in a Mediterranean environment
The EU-Rotate_N model was developed as a tool to estimate the growth and nitrogen (N) uptake of vegetable crop rotations across a wide range of European climatic conditions and to assess the economic and environmental consequences of alternative management strategies. The model has been evaluated under field conditions in Germany and Norway and under greenhouse conditions in China. The present work evaluated the model using Italian data to evaluate its performance in a warm and dry environment. Data were collected from four 2-year field rotations, which included lettuce (Lactuca sativa L.), fennel (Foeniculum vulgare Mill.), spinach (Spinacia oleracea L.), broccoli (Brassica oleracea L. var. italica Plenck) and white cabbage (B. oleracea convar. capitata var. alba L.); each rotation used three different rates of N fertilizer (average recommended N1, assumed farmer's practice N2=N1+0·3ĂN1 and a zero control N0). Although the model was not calibrated prior to running the simulations, results for above-ground dry matter biomass, crop residue biomass, crop N concentration and crop N uptake were promising. However, soil mineral N predictions to 0·6 m depth were poor. The main problem with the prediction of the test variables was the poor ability to capture N mineralization in some autumn periods and an inappropriate parameterization of fennel. In conclusion, the model performed well, giving results comparable with other bio-physical process simulation models, but for more complex crop rotations. The model has the potential for application in Mediterranean environments for field vegetable production
A method to predict impacts of NVZ and Water Framework legislation on UK vegetable and arable farming.
EU-Rotate_N â a decision support system â to predict environmental and economic consequences of the management of nitrogen fertiliser in crop rotations
A model has been developed which assesses the economic and environmental performance of crop rotations, in both conventional and organic cropping, for over 70 arable and horticultural crops, and a wide range of growing conditions in Europe. The model, though originally based on the N_ABLE model, has been completely rewritten and contains new routines to simulate root development, the mineralisation and release of nitrogen (N) from soil organic matter and crop residues, and water dynamics in soil. New routines have been added to estimate the effects of sub-optimal rates of N and spacing on the marketable outputs and gross margins. The model provides a mechanism for generating scenarios to represent a range of differing crop and fertiliser management strategies which can be used to evaluate their effects on yield, gross margin and losses of nitrogen through leaching. Such testing has revealed that nitrogen management can be improved and that there is potential to increase gross margins whilst reducing nitrogen losses
Strategien fĂŒr die Landwirtschaft im Klimawandel: eine Modellstudie
Das dynamische, prozess-basierte Simulati-onsmodell MONICA wurde eingesetzt, um die Entwicklung des BewĂ€sserungs- und des Stickstoffbedarfs von Winterweizen, Wintergerste und Silomais in einem angenommenen Klimaszenario (A1B) zu berechnen. Der BewĂ€sserungsbedarf wurde mit einer automatischen BewĂ€sse-rungsfunktion in Simulationen auf einem Sandstandort (531 mm durchschnittlicher Jahresniederschlag 1951 â 2003), der Stickstoffbedarf zusĂ€tzlich auf einem Lössstandort ermittelt (876 mm). Es ergaben sich ein signifikant erhöhtes Ertragsniveau bei Mais und Weizen unter BewĂ€sserung im Zeitraum um das Jahr 2070 im Vergleich zur nicht bewĂ€sserten Kultur, jedoch eine kaum ertragssteigernde Wirkung bei Gerste. Der Stickstoffbedarf steigt in der Simulation um etwa 20 kg N haâ1 bei Weizen, bleibt bei Gerste und Mais jedoch auf heutigem Niveau
Agricultural land use changes â a scenario-based sustainability impact assessment for Brandenburg, Germany
AbstractDecisions for agricultural management are taken at farm scale. However, such decisions may well impact upon regional sustainability. Two of the likely agricultural management responses to future challenges are extended use of irrigation and increased production of energy crops. The drivers for these are high commodity prices and subsidy policies for renewable energy. However, the impacts of these responses upon regional sustainability are unknown. Thus, we conducted integrated impact assessments for agricultural intensification scenarios in the federal state of Brandenburg, Germany, for 2025. One Irrigation scenario and one Energy scenario were contrasted with the Business As Usual (BAU) scenario. We applied nine indicators to analyze the economic, social and environmental effects at the regional, in this case district scale, which is the smallest administrative unit in Brandenburg. Assessment results were discussed in a stakeholder workshop involving 16 experts from the state government.The simulated area shares of silage maize for fodder and energy were 29%, 37% and 49% for the BAU, Irrigation, and Energy scenarios, respectively. The Energy scenario increased bio-electricity production to 41% of the demand of Brandenburg, and it resulted in CO2 savings of up to 3.5milliontons. However, it resulted in loss of biodiversity, loss of landscape scenery, increased soil erosion risk, and increased area demand for water protection requirements. The Irrigation scenario led to yield increases of 7% (rapeseed), 18% (wheat, sugar beet), and 40% (maize) compared to the BAU scenario. It also reduced the year-to-year yield variability. Water demand for irrigation was found to be in conflict with other water uses for two of the 14 districts. Spatial differentiation of scenario impacts showed that districts with medium to low yield potentials were more affected by negative impacts than districts with high yield potentials.In this first comprehensive sustainability impact assessment of agricultural intensification scenarios at regional level, we showed that a considerable potential for agricultural intensification exists. The intensification is accompanied by adverse environmental and socio-economic impacts. The novelty lies in the multiscale integration of comprehensive, agricultural management simulations with regional level impact assessment, which was achieved with the adequate use of indicators. It provided relevant evidence for policy decision making. Stakeholders appreciated the integrative approach of the assessment, which substantiated ongoing discussions among the government bodies. The assessment approach and the Brandenburg case study may stay exemplary for other regions in the world where similar economic and policy driving forces are likely to lead to agricultural intensification
Converting simulated total dry matter to fresh marketable yield for field vegetables at a range of nitrogen supply levels
Simultaneous analysis of economic and environmental performance of horticultural crop production requires qualified assumptions on the effect of management options, and particularly of nitrogen (N) fertilisation, on the net returns of the farm. Dynamic soil-plant-environment simulation models for agro-ecosystems are frequently applied to predict crop yield, generally as dry matter per area, and the environmental impact of production. Economic analysis requires conversion of yields to fresh marketable weight, which is not easy to calculate for vegetables, since different species have different properties and special market requirements. Furthermore, the marketable part of many vegetables is dependent on N availability during growth, which may lead to complete crop failure under sub-optimal N supply in tightly calculated N fertiliser regimes or low-input systems. In this paper we present two methods for converting simulated total dry matter to marketable fresh matter yield for various vegetables and European growth conditions, taking into consideration the effect of N supply: (i) a regression based function for vegetables sold as bulk or bunching ware and (ii) a population approach for piecewise sold row crops. For both methods, to be used in the context of a dynamic simulation model, parameter values were compiled from a literature survey. Implemented in such a model, both algorithms were tested against experimental field data, yielding an Index of Agreement of 0.80 for the regression strategy and 0.90 for the population strategy. Furthermore, the population strategy was capable of reflecting rather well the effect of crop spacing on yield and the effect of N supply on product grading
Analysing urban heat island patterns and simulating potential future changes
Climate change is interpreted as one of the most serious environmental problems for the 21st century. Changes in climate are now generally accepted. However, the rate of change has spatial characteristics and is highly uncertain. The Himalaya is experiencing abrupt change; so vulnerability and adaptation studies have become crucial. This pilot study presents initial findings of the research project entitled âHuman Ecological Implications of Climate Change in the Himalaya.â A study of climate change perceptions, vulnerability, and adaptation strategies of farming communities of the cool-wet temperate (Lumle) and the hot-wet sub-tropical (Meghauli) villages in Central Nepal was conducted. The findings are derived from the analysis of temperature and precipitation data of last 40 years, and primary data collected in September 2012. Focus Group Discussions, Key Informant Interviews, and Historical Timeline Calender were applied. The changes perceived by the communities are fairly consistent with the meteorological observations and are challenging the sustainability of social-ecological systems and communitiesâ livelihoods. Farming communities have adopted some strategies to minimize the vulnerability. But the adopted strategies have produced both negative and positive results. Strategies like flood control, shifting crop calendars, occupational changes and labour migrations have produced positive results in livelihood security. Occupational changes and labour migration have negatively impacted local agro-ecology and agricultural economies. Early-harvesting strategies to reduce losses from hailstorm have reduced the food and fodder security. Lack of irrigation for rice-seedlings is severely affecting the efficacy of shifting the rice-transplantation calendar. Conclusions suggest that while farmers have practiced strategies to better management of farms, livelihood sustainabilities are reaching thresholds due to the changing conditions.Rishikesh Pandey, Douglas K Bardsle
Modelling different cropping systems
Grapevine is a worldwide valuable crop characterized by a high economic importance for the production of high quality wines. However, the impact of climate change on the narrow climate niches in which grapevine is currently cultivated constitute a great risk for future suitability of grapevine. In this context, grape simulation models are considered promising tools for their contribution to investigate plant behavior in different environments. In this study, six models developed for simulating grapevine growth and development were tested by focusing on their performances in simulating main grapevine processes under two calibration levels: minimum and full calibration. This would help to evaluate major limitations/strength points of these models, especially in the view of their application to climate change impact and adaptation assessments. Preliminary results from two models (GrapeModel and STICS) showed contrasting abilities in reproducing the observed data depending on the site, the year and the target variable considered. These results suggest that a limited dataset for model calibration would lead to poor simulation outputs. However, a more complete interpretation and detailed analysis of the results will be provided when considering the other models simulations
Climate-induced severe water scarcity events as harbinger of global grain price
The severe water scarcity (SWS) concept allows for consistent analysis of the supply and demand for water sourced grain production worldwide. Thus, the primary advantage of using SWS is its ability to simultaneously accommodate the spatial extent and temporal persistence of droughts using climatic data. The SWS concept was extended here to drivers of global grain prices using past SWS events and prices of three dominant grain crops: wheat, rice and maize. A significant relation between the SWS affected area and the prices of wheat was confirmed. The past priceâSWS association was then used to project future wheat prices considering likely climate change scenarios until 2050 and expected SWS extent. The projected wheat prices increase with increasing SWS area that is in turn a function of greenhouse gas emissions. The need to act to reduce greenhouse gas emissions is again reinforced assuming the SWS-price relation for wheat is unaltered
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