| Records |
| Author |
Nguyen, T.P.L.; Seddaiu, G.; Virdis, S.G.P.; Tidore, C.; Pasqui, M.; Roggero, P.P. |
| Title |
Perceiving to learn or learning to perceive? Understanding farmers’ perceptions and adaptation to climate uncertainties |
Type |
Journal Article |
| Year |
2016 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
Volume  |
143 |
Issue |
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Pages |
205-216 |
| Keywords |
climate variability; socio-cognitive learning process; adaptation strategies; mediterranean agricultural systems; agricultural land-use; adaptive capacity; farming systems; variability; knowledge; risk; drought; africa; future; rain |
| Abstract |
Perception not only shapes knowledge but knowledge also shapes perception. Humans adapt to the natural world through a process of learning in which they interpret their sensory impressions in order to give meaning to their environment and act accordingly. In this research, we examined how farmers’ decision making is shaped in the context of changing climate. Using empirical data (face-to-face semi-structured interviews and questionnaires) on four Mediterranean farming systems from a case study located in Oristano (Sardinia, Italy) we sought to understand farmers’ perception of climate change and their behaviors in adjustment of farming practices. We found different perceptions among farmer groups were mainly associated with the different socio-cultural and institutional settings and perceived relationships between climate factors and impacts on each farming systems. The research findings on different perceptions among farmer groups can help to understand farmers’ current choices and attitudes of adaptation for supporting the development of appropriate adaptation strategies. In addition, the knowledge of socio-cultural and economic factors that lead to biases in climate perceptions can help to integrate climate communication into adaptation research for making sense of climate impacts and responses at farm level. |
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0308-521x |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4707 |
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| Author |
Liu, X.; Lehtonen, H.; Purola, T.; Pavlova, Y.; Rötter, R.; Palosuo, T. |
| Title |
Dynamic economic modelling of crop rotations with farm management practices under future pest pressure |
Type |
Journal Article |
| Year |
2016 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
| Volume |
144 |
Issue |
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Pages |
65-76 |
| Keywords |
Farm management; Dynamic optimization; Crop rotation; Risk aversion; Climate change; Prices; climate-change; sequester carbon; changing climate; food security; challenge; Finland; ensembles; systems; europe; tool |
| Abstract |
Agricultural practice is facing multiple challenges under volatile commodity markets, inevitable climate change, mounting pest pressure and various other environment-related constraints. The objective of this research is to present a dynamic optimization model of crop rotations and farm management and show its suitability for economic analysis over a 30 year time period. In this model, we include management practices such as fertilization, fungicide treatment and liming, and apply it in a region in Southwestern Finland. Results show that (i) growing pest pressure favours the cultivation of wheat-oats and wheat-oilseeds combinations, while (ii) market prices largely determine the crops in the rotation plan and the specific management practices adopted. The flexibility of our model can also be utilized in evaluating the value of other management options such as new cultivars under different projections of future climate and market conditions. |
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0308521x |
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CropM, TradeM, ftnotmacsur |
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no |
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MA @ admin @ |
Serial |
4719 |
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Schönhart, M.; Schauppenlehner, T.; Kuttner, M.; Kirchner, M.; Schmid, E. |
| Title |
Climate change impacts on farm production, landscape appearance, and the environment: Policy scenario results from an integrated field-farm-landscape model in Austria |
Type |
Journal Article |
| Year |
2016 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
| Volume |
145 |
Issue |
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Pages |
39-50 |
| Keywords |
Integrated land use modeling; Climate change impacts; Mitigation; Adaptation; Field-farm-landscape; Environment; agricultural landscapes; land-use; netherlands; adaptation; indicators; management; responses |
| Abstract |
Climate change is among the major drivers of agricultural land use change and demands autonomous farm adaptation as well as public mitigation and adaptation policies. In this article, we present an integrated land use model (ILM) mainly combining a bio-physical model and a bio-economic farm model at field, farm and landscape levels. The ILM is applied to a cropland dominated landscape in Austria to analyze impacts of climate change and mitigation and adaptation policy scenarios on farm production as well as on the abiotic environment and biotic environment. Changes in aggregated total farm gross margins from three climate change scenarios for 2040 range between + 1% and + 5% without policy intervention” and compared to a reference situation under the current climate. Changes in aggregated gross margins are even higher if adaptation policies are in place. However, increasing productivity from climate change leads to deteriorating environmental conditions such as declining plant species richness and landscape appearance. It has to be balanced by mitigation and adaptation policies taking into account effects from the considerable spatial heterogeneity such as revealed by the ILM. (C) 2016 Elsevier Ltd. All rights reserved. |
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0308-521x |
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CropM, TradeM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4767 |
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Nendel, C.; Wieland, R.; Mirschel, W.; Specka, X.; Guddat, C.; Kersebaum, K.C. |
| Title |
Simulating regional winter wheat yields using input data of different spatial resolution |
Type |
Journal Article |
| Year |
2013 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
| Volume |
145 |
Issue |
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Pages |
67-77 |
| Keywords |
monica; agro-ecosystem model; dynamic modelling; scaling; input data; climate-change; crop yield; nitrogen dynamics; food security; mineral nitrogen; soil-moisture; scaling-up; model; maize; water |
| Abstract |
The success of using agro-ecosystem models for the high-resolution simulation of agricultural yields for larger areas is often hampered by a lack of input data. We investigated the effect of different spatially resolved soil and weather data used as input for the MONICA model on its ability to reproduce winter wheat yields in the Federal State of Thuringia, Germany (16,172 km(2)). The combination of one representative soil and one weather station was insufficient to reproduce the observed mean yield of 6.66 +/- 0.87 t ha(-1) for the federal state. Use of a 100 m x 100 m grid of soil and relief information combined with just one representative weather station yielded a good estimator (7.01 +/- 1.47 t ha(-1)). The soil and relief data grid used in combination with weather information from 14 weather stations in a nearest neighbour approach produced even better results (6.60 +/- 1.37 t ha(-1)); the same grid used with 39 additional rain gauges and an interpolation algorithm that included an altitude correction of temperature data slightly overpredicted the observed mean (7.36 +/- 1.17 t ha(-1)). It was concluded that the apparent success of the first two high-resolution approaches over the latter was based on two effects that cancelled each other out: the calibration of MONICA to match high-yield experimental data and the growth-defining and -limiting effect of weather data that is not representative for large parts of the region. At the county and farm level the MONICA model failed to reproduce the 1992-2010 time series of yields, which is partly explained by the fact that many growth-reducing factors were not considered in the model. (C) 2013 Elsevier B.V. All rights reserved. |
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0378-4290 |
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CropM, ftnotmacsur |
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no |
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MA @ admin @ |
Serial |
4498 |
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| Author |
Hakala, K.; Jauhiainen, L.; Himanen, S.J.; RÖTter, R.; Salo, T.; Kahiluoto, H. |
| Title |
Sensitivity of barley varieties to weather in Finland |
Type |
Journal Article |
| Year |
2012 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
| Volume |
150 |
Issue |
02 |
Pages |
145-160 |
| Keywords |
climate-change; winter-wheat; spring wheat; reproductive growth; high-temperatures; changing climate; crop production; increased CO2; yield; tolerance |
| Abstract |
Global climate change is predicted to shift seasonal temperature and precipitation patterns. An increasing frequency of extreme weather events such as heat waves and prolonged droughts is predicted, but there are high levels of uncertainty about the nature of local changes. Crop adaptation will be important in reducing potential damage to agriculture. Crop diversity may enhance resilience to climate variability and changes that are difficult to predict. Therefore, there has to be sufficient diversity within the set of available cultivars in response to weather parameters critical for yield formation. To determine the scale of such ‘weather response diversity’ within barley (Hordeum vulgare L.), an important crop in northern conditions, the yield responses of a wide range of modern and historical varieties were analysed according to a well-defined set of critical agro-meteorological variables. The Finnish long-term dataset of MTT Official Variety Trials was used together with historical weather records of the Finnish Meteorological Institute. The foci of the analysis were firstly to describe the general response of barley to different weather conditions and secondly to reveal the diversity among varieties in the sensitivity to each weather variable. It was established that barley yields were frequently reduced by drought or excessive rain early in the season, by high temperatures at around heading, and by accelerated temperature sum accumulation rates during periods 2 weeks before heading and between heading and yellow ripeness. Low temperatures early in the season increased yields, but frost during the first 4 weeks after sowing had no effect. After canopy establishment, higher precipitation on average resulted in higher yields. In a cultivar-specific analysis, it was found that there were differences in responses to all but three of the studied climatic variables: waterlogging and drought early in the season and temperature sum accumulation rate before heading. The results suggest that low temperatures early in the season, delayed sowing, rain 3-7 weeks after sowing, a temperature change 3-4 weeks after sowing, a high temperature sum accumulation rate from heading to yellow ripeness and high temperatures (25 degrees C) at around heading could mostly be addressed by exploiting the traits found in the range of varieties included in the present study. However, new technology and novel genetic material are needed to enable crops to withstand periods of excessive rain or drought early in the season and to enhance performance under increased temperature sum accumulation rates prior to heading. |
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0021-8596 1469-5146 |
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CropM |
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MA @ admin @ |
Serial |
4586 |
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