| Records |
| Author |
Kros, J.; Bakker, M.M.; Reidsma, P.; Kanellopoulos, A.; Jamal Alam, S.; de Vries, W. |
| Title |
Impacts of agricultural changes in response to climate and socioeconomic change on nitrogen deposition in nature reserves |
Type |
Journal Article |
| Year |
2015 |
Publication |
Landscape Ecology |
Abbreviated Journal |
Landscape Ecol. |
| Volume |
30 |
Issue |
5 |
Pages  |
871-885 |
| Keywords |
Agricultural adaptation; Climate change; Land use change; Environmental; impact; Farming system; Nitrogen losses; netherlands; diversity; scenario |
| Abstract |
This paper describes the environmental consequences of agricultural adaptation on eutrophication of the nearby ecological network for a study area in the Netherlands. More specifically, we explored (i) likely responses of farmers to changes in climate, technology, policy, and markets; (ii) subsequent changes in nitrogen (N) emissions in responses to farmer adaptations; and (iii) to what extent the emitted N was deposited in nearby nature reserves, in view of the potential impacts on plant species diversity and desired nature targets. For this purpose, a spatially-explicit study at landscape level was performed by integrating the environmental model INITIATOR, the farm model FSSIM, and the land-use model RULEX. We evaluated two alternative scenarios of change in climate, technology, policy, and markets for 2050: one in line with a ‘global economy’ (GE) storyline and the other in line with a ‘regional communities’ (RC) storyline. Results show that the GE storyline resulted in a relatively strong increase in agricultural production compared to the RC storyline. Despite the projected conversions of agricultural land to nature (as part of the implementation of the National Ecological Network), we project an increase in N losses and N deposition due to N emissions in the study area of about 20 %. Even in the RC storyline, with a relatively modest increase in agricultural production and a larger expansion of the nature reserve, the N losses and deposition remain at the current level, whereas a reduction is required. We conclude that more ambitious green policies are needed in view of nature protection. |
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English |
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| ISSN |
0921-2973 1572-9761 |
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Article |
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CropM |
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no |
| Call Number |
MA @ admin @ |
Serial |
4565 |
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| Author |
Özkan, Ş.; Hill, J.; Cullen, B. |
| Title |
Effect of climate variability on pasture-based dairy feeding systems in south-east Australia |
Type |
Journal Article |
| Year |
2014 |
Publication |
Animal Production Science |
Abbreviated Journal |
Animal Production Science |
| Volume |
55 |
Issue |
9 |
Pages |
1106-1116 |
| Keywords |
carry-forward surplus; conserved-hay; probability; winter deficit; grown forage consumption; new-zealand; nutritive characteristics; interannual variation; botanical composition; herbage accumulation; crop; systems; cows; management; profit |
| Abstract |
The Australian dairy industry relies primarily on pasture for its feed supply. However, the variability in climate affects plant growth, leading to uncertainty in dryland pasture supply. This paper models the impact of climate variability on pasture production and examines the potential of two pasture-based dairy feeding systems: (1) to experience winter deficits; (2) to carry forward the conserved pasture surpluses as silage for future use; and (3) to conserve pasture surpluses as hay. The two dairy feeding systems examined were a traditional perennial ryegrass-based feeding system (ryegrass max. – RM) and a system that incorporated double cropping into the perennial ryegrass pasture base (complementary forage – CF). The conditional probability of the RM and CF systems to generate pasture deficits in winter were 94% and 96%, respectively. Both systems could carry forward the surplus silage into the following lactation almost once in every 4-5 years with the RM system performing slightly better than the CF system. The proportions of the grain-based concentrates fed in the two systems were 25% and 27% for the RM and CF systems, respectively. This study suggests that double-cropping systems have the potential to provide high-quality feed to support the feed gaps when pasture is not available due to increased variability in climatic conditions. |
| Address |
2015-09-23 |
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English |
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| ISSN |
1836-5787 |
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Article |
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LiveM |
Approved |
no |
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MA @ admin @ |
Serial |
4689 |
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| Author |
Mansouri, M.; Destain, M.-F. |
| Title |
Predicting biomass and grain protein content using Bayesian methods |
Type |
Journal Article |
| Year |
2015 |
Publication |
Stochastic Environmental Research and Risk Assessment |
Abbreviated Journal |
Stoch. Environ. Res. Risk Assess. |
| Volume |
29 |
Issue |
4 |
Pages |
1167-1177 |
| Keywords |
crop model; particle filter; prediction; ensemble kalman filter; parameter-estimation; particle filters; decision-support; state estimation; model; nitrogen; navigation; tracking; systems |
| Abstract |
This paper deals with the problem of predicting biomass and grain protein content using improved particle filtering (IPF) based on minimizing the Kullback-Leibler divergence. The performances of IPF are compared with those of the conventional particle filtering (PF) in two comparative studies. In the first one, we apply IPF and PF at a simple dynamic crop model with the aim to predict a single state variable, namely the winter wheat biomass, and to estimate several model parameters. In the second study, the proposed IPF and the PF are applied to a complex crop model (AZODYN) to predict a winter-wheat quality criterion, namely the grain protein content. The results of both comparative studies reveal that the IPF method provides a better estimation accuracy than the PF method. The benefit of the IPF method lies in its ability to provide accuracy related advantages over the PF method since, unlike the PF which depends on the choice of the sampling distribution used to estimate the posterior distribution, the IPF yields an optimum choice of this sampling distribution, which also utilizes the observed data. The performance of the proposed method is evaluated in terms of estimation accuracy, root mean square error, mean absolute error and execution times. |
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English |
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1436-3240 1436-3259 |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4664 |
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| Author |
Salo, T.J.; Palosuo, T.; Kersebaum, K.C.; Nendel, C.; Angulo, C.; Ewert, F.; Bindi, M.; Calanca, P.; Klein, T.; Moriondo, M.; Ferrise, R.; Olesen, J.E.; Patil, R.H.; Ruget, F.; Takáč, J.; Hlavinka, P.; Trnka, M.; Rötter, R.P. |
| Title |
Comparing the performance of 11 crop simulation models in predicting yield response to nitrogen fertilization |
Type |
Journal Article |
| Year |
2016 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
| Volume |
154 |
Issue |
7 |
Pages |
1218-1240 |
| Keywords |
northern growing conditions; climate-change impacts; spring barley; systems simulation; farming systems; soil properties; winter-wheat; dynamics; growth; management |
| Abstract |
Eleven widely used crop simulation models (APSIM, CERES, CROPSYST, COUP, DAISY, EPIC, FASSET, HERMES, MONICA, STICS and WOFOST) were tested using spring barley (Hordeum vulgare L.) data set under varying nitrogen (N) fertilizer rates from three experimental years in the boreal climate of Jokioinen, Finland. This is the largest standardized crop model inter-comparison under different levels of N supply to date. The models were calibrated using data from 2002 and 2008, of which 2008 included six N rates ranging from 0 to 150 kg N/ha. Calibration data consisted of weather, soil, phenology, leaf area index (LAI) and yield observations. The models were then tested against new data for 2009 and their performance was assessed and compared with both the two calibration years and the test year. For the calibration period, root mean square error between measurements and simulated grain dry matter yields ranged from 170 to 870 kg/ha. During the test year 2009, most models failed to accurately reproduce the observed low yield without N fertilizer as well as the steep yield response to N applications. The multi-model predictions were closer to observations than most single-model predictions, but multi-model mean could not correct systematic errors in model simulations. Variation in soil N mineralization and LAI development due to differences in weather not captured by the models most likely was the main reason for their unsatisfactory performance. This suggests the need for model improvement in soil N mineralization as a function of soil temperature and moisture. Furthermore, specific weather event impacts such as low temperatures after emergence in 2009, tending to enhance tillering, and a high precipitation event just before harvest in 2008, causing possible yield penalties, were not captured by any of the models compared in the current study. |
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English |
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| ISSN |
0021-8596 1469-5146 |
ISBN |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4713 |
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| Author |
Mandryk, M.; Reidsma, P.; Kanellopoulos, A.; Groot, J.C.J.; van Ittersum, M.K. |
| Title |
The role of farmers’ objectives in current farm practices and adaptation preferences: a case study in Flevoland, the Netherlands |
Type |
Journal Article |
| Year |
2014 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg Environ Change |
| Volume |
14 |
Issue |
4 |
Pages |
1463-1478 |
| Keywords |
multi-criteria decision-making; multi-objective optimization; agriculture; arable farm; vegetable farms; climate-change; south uruguay; land-use; design; agriculture; model; management; options; systems |
| Abstract |
The diversity in farmers’ objectives and responses to external drivers is usually not considered in integrated assessment studies that investigate impacts and adaptation to climate and socio-economic change. Here, we present an approach to assess how farmers’ stated objectives relate to their currently implemented practices and to preferred adaptation options, and we discuss what this implies for assessments of future changes. We based our approach on a combination of multi-criteria decision-making methods. We consistently assessed the importance of farmers’ objectives and adaptation preferences from what farmers say (based on interviews), from what farmers actually do (by analysing current farm performance) and from what farmers want (through a selected alternative farm plan). Our study was performed for six arable farms in Flevoland, a province in the Netherlands. Based on interviews with farmers, we reduced the long list of possible objectives to the most important ones. The objectives we assessed included maximization of economic result and soil organic matter, and minimization of gross margin variance, working hours and nitrogen balance. In our sample, farmers’ stated preferences in objectives were often not fully reflected in realized farming practices. Adaptation preferences of farmers largely resembled their current performance, but generally involved a trend towards stated preferences. Our results suggest that in Flevoland, although farmers do have more objectives, in practical decision-making they focus on economic result maximization, while for strategic decision-making they account for objectives influencing long-term performance and indicators associated with sustainability, in this case soil organic matter. |
| Address |
2016-10-31 |
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English |
Summary Language |
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Series Issue |
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Edition |
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| ISSN |
1436-3798 1436-378x |
ISBN |
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Article |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4794 |
| Permanent link to this record |
