| Records |
| Author |
Reidsma, P.; Bakker, M.M.; Kanellopoulos, A.; Alam, S.J.; Paas, W.; Kros, J.; de Vries, W. |
| Title |
Sustainable agricultural development in a rural area in the Netherlands? Assessing impacts of climate and socio-economic change at farm and landscape level |
Type |
Journal Article |
| Year |
2015 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
| Volume |
141 |
Issue |
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Pages  |
160-173 |
| Keywords |
Integrated assessment; Global change; Sustainability; Agriculture; Farm; structural change; Spatially explicit; Climate smart agriculture; affecting land-use; integrated assessment; multiobjective optimization; analytical framework; trade-offs; systems; uncertainties; policies; future; adaptation |
| Abstract |
Changes in climate, technology, policy and prices affect agricultural and rural development. To evaluate whether this development is sustainable, impacts of these multiple drivers need to be assessed for multiple indicators. In a case study area in the Netherlands, a bio-economic farm model, an agent-based land-use change model, and a regional emission model have been used to simulate rural development under two plausible global change scenarios at both farm and landscape level. Results show that in this area, climate change will have mainly negative economic impacts (dairy gross margin, arable gross margin, economic efficiency, milk production) in the warmer and drier W+ scenario, while impacts are slightly positive in the G scenario with moderate climate change. Dairy farmers are worse off than arable farmers in both scenarios. Conversely, when the W+ scenario is embedded in the socio-economic Global Economy (GE) scenario, changes in technology, prices, and policy are projected to have a positive economic impact, more than offsetting the negative climate impacts. Important is, however, that environmental impacts (global warming, terrestrial and aquatic eutrophication) are largely negative and social impacts (farm size, number of farms, nature area, odour) are mixed. In the G scenario combined with the socio-economic Regional Communities (RC) scenario the average dairy gross margin in particular is negatively affected. Social impacts are similarly mixed as in the GE scenario, while environmental impacts are less severe. Our results suggest that integrated assessments at farm and landscape level can be used to guide decision-makers in spatial planning policies and climate change adaptation. As there will always be trade-offs between economic, social, and environmental impacts stakeholders need to interact and decide upon most important directions for policies. This implies a choice between production and income on the one hand and social and environmental services on the other hand |
| Address |
2016-06-01 |
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| Language |
English |
Summary Language |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0308-521x |
ISBN |
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Article |
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Expedition |
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Conference |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4742 |
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| Author |
Gabaldón-Leal, C.; Lorite, I.J.; Mínguez, M.I.; Lizaso, J.I.; Dosio, A.; Sanchez, E.; Ruiz-Ramos, M. |
| Title |
Strategies for adapting maize to climate change and extreme temperatures in Andalusia, Spain |
Type |
Journal Article |
| Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
| Volume |
65 |
Issue |
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Pages |
159-173 |
| Keywords |
climate change; impact; adaptation; maize; crop model; regional climate model; extreme temperature; elevated carbon-dioxide; iberian peninsula; future climate; mediterranean environment; crop productivity; model simulations; pollen viability; european climate; bias correction; change impacts |
| Abstract |
Climate projections indicate that rising temperatures will affect summer crops in the southern Iberian Peninsula. The aim of this study was to obtain projections of the impacts of rising temperatures, and of higher frequency of extreme events on irrigated maize, and to evaluate some adaptation strategies. The study was conducted at several locations in Andalusia using the CERES-Maize crop model, previously calibrated/validated with local experimental datasets. The simulated climate consisted of projections from regional climate models from the ENSEMBLES project; these were corrected for daily temperature and precipitation with regard to the E-OBS observational dataset. These bias-corrected projections were used with the CERES-Maize model to generate future impacts. Crop model results showed a decrease in maize yield by the end of the 21st century from 6 to 20%, a decrease of up to 25% in irrigation water requirements, and an increase in irrigation water productivity of up to 22%, due to earlier maturity dates and stomatal closure caused by CO2 increase. When adaptation strategies combining earlier sowing dates and cultivar changes were considered, impacts were compensated, and maize yield increased up to 14%, compared with the baseline period (1981-2010), with similar reductions in crop irrigation water requirements. Effects of extreme maximum temperatures rose to 40% at the end of the 21st century, compared with the baseline. Adaptation resulted in an overall reduction in extreme T-max damages in all locations, with the exception of Granada, where losses were limited to 8%. |
| Address |
2016-06-01 |
| Corporate Author |
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Place of Publication |
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| Language |
English |
Summary Language |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
0936-577x 1616-1572 |
ISBN |
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Medium |
Article |
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Expedition |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4738 |
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| Author |
Zhao, G.; Siebert, S.; Enders, A.; Rezaei, E.E.; Yan, C.; Ewert, F. |
| Title |
Demand for multi-scale weather data for regional crop modeling |
Type |
Journal Article |
| Year |
2015 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
| Volume |
200 |
Issue |
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Pages |
156-171 |
| Keywords |
multi-scale; spatial heterogeneity; spatial resolution; crop model; climate variability; climate-change scenarios; integrated assessment; large-scale; phenological development; agricultural systems; spatial-resolution; data aggregation; european-union; winter-wheat; input data |
| Abstract |
A spatial resolution needs to be determined prior to using models to simulate crop yields at a regional scale, but a dilemma exists in compromising between different demands. A fine spatial resolution demands extensive computation load for input data assembly, model runs, and output analysis. A coarse spatial resolution could result in loss of spatial detail in variability. This paper studied the impact of spatial resolution, data aggregation and spatial heterogeneity of weather data on simulations of crop yields, thus providing guidelines for choosing a proper spatial resolution for simulations of crop yields at regional scale. Using a process-based crop model SIMPLACE (LINTUL2) and daily weather data at 1 km resolution we simulated a continuous rainfed winter wheat cropping system at the national scale of Germany. Then we aggregated the weather data to four resolutions from 10 to 100 km, repeated the simulation, compared them with the 1 km results, and correlated the difference with the intra-pixel heterogeneity quantified by an ensemble of four semivariogram models. Aggregation of weather data had small effects over regions with a flat terrain located in northern Germany, but large effects over southern regions with a complex topography. The spatial distribution of yield bias at different spatial resolutions was consistent with the intra-pixel spatial heterogeneity of the terrain and a log-log linear relationship between them was established. By using this relationship we demonstrated the way to optimize the model resolution to minimize both the number of simulation runs and the expected loss of spatial detail in variability due to aggregation effects. We concluded that a high spatial resolution is desired for regions with high spatial environmental heterogeneity, and vice versa. This calls for the development of multi-scale approaches in regional and global crop modeling. The obtained results require substantiation for other production situations, crops, output variables and for different crop models. (C) 2014 Elsevier B.V. All rights reserved. |
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English |
Summary Language |
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Series Issue |
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Edition |
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| ISSN |
0168-1923 |
ISBN |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4753 |
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| Author |
Zhao, G.; Hoffmann, H.; van Bussel, L.G.J.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.L.; Constantin, J.; Raynal, H.; Teixeira, E.; Grosz, B.; Doro, L.; Zhao, Z.G.; Nendel, C.; Kiese, R.; Eckersten, H.; Haas, E.; Vanuytrecht, E.; Wang, E.; Kuhnert, M.; Trombi, G.; Moriondo, M.; Bindi, M.; Lewan, E.; Bach, M.; Kersebaum, K.C.; Rotter, R.; Roggero, P.P.; Wallach, D.; Cammarano, D.; Asseng, S.; Krauss, G.; Siebert, S.; Gaiser, T.; Ewert, F. |
| Title |
Effect of weather data aggregation on regional crop simulation for different crops, production conditions, and response variables |
Type |
Journal Article |
| Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
| Volume |
65 |
Issue |
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Pages |
141-157 |
| Keywords |
crop model; model comparison; spatial resolution; data aggregation; spatial heterogeneity; scaling; climate-change scenarios; sub-saharan africa; winter-wheat; spatial-resolution; yield response; input data; systems simulation; large-scale; soil data; part i |
| Abstract |
We assessed the weather data aggregation effect (DAE) on the simulation of cropping systems for different crops, response variables, and production conditions. Using 13 process-based crop models and the ensemble mean, we simulated 30 yr continuous cropping systems for 2 crops (winter wheat and silage maize) under 3 production conditions for the state of North Rhine-Westphalia, Germany. The DAE was evaluated for 5 weather data resolutions (i.e. 1, 10, 25, 50, and 100 km) for 3 response variables including yield, growing season evapotranspiration, and water use efficiency. Five metrics, viz. the spatial bias (Delta), average absolute deviation (AAD), relative AAD, root mean squared error (RMSE), and relative RMSE, were used to evaluate the DAE on both the input weather data and simulated results. For weather data, we found that data aggregation narrowed the spatial variability but widened the., especially across mountainous areas. The DAE on loss of spatial heterogeneity and hotspots was stronger than on the average changes over the region. The DAE increased when coarsening the spatial resolution of the input weather data. The DAE varied considerably across different models, but changed only slightly for different production conditions and crops. We conclude that if spatially detailed information is essential for local management decision, higher resolution is desirable to adequately capture the spatial variability for heterogeneous regions. The required resolution depends on the choice of the model as well as the environmental condition of the study area. |
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English |
Summary Language |
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Series Issue |
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Edition |
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| ISSN |
0936-577x |
ISBN |
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Article |
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Expedition |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4754 |
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| Author |
De Pascale, S.; Maggio, A.; Orsini, F.; Stanghellini, C.; Heuvelink, E. |
| Title |
Growth response and radiation use efficiency in tomato exposed to short-term and long-term salinized soils |
Type |
Journal Article |
| Year |
2015 |
Publication |
Scientia Horticulturae |
Abbreviated Journal |
Scientia Horticulturae |
| Volume |
189 |
Issue |
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Pages |
139-149 |
| Keywords |
Leaf osmotic adjustment; Stomatal resistance; Leaf water potential; Light; Salt stress; RUE; physiological-response; salt tolerance; drought stress; water-use; yield; nitrogen; interception; productivity; leaf; photosynthesis |
| Abstract |
Farmlands are increasingly exposed to degradation phenomena associated to climate change and agricultural practices, including irrigation. It is estimated that about 20% of the world’s irrigated land is salt affected. In this paper we aimed at evaluating the effect of seasonal and multiannual soil satinization on growth, yield, and radiation use efficiency of tomato in open field. Two field experiments were carried out at the Experimental Station of the University of Naples Federico II (latitude 40 degrees 31’N longitude 14 degrees 58’E) (Italy) on tomato during 2004 and 2005 to study the effect of five levels of water salinity: NSC (EC = 0.5 dS m(-1)), SW1 (EC= 2.3 dS m(-1)), SW2 (EC= 4.4 dS m(-1)), SW3 (EC= 8.5 dS m(-1)) and SW4 (EC= 15.7 dS m(-1)) in a soil exposed to one-season salinization (ST = short-term) and an adjacent soil exposed to >20 years salinization (LT = long-term). Plant growth, yield and fruit quality (pH, EC, total soluble solids and the concentration of reducing sugars and of titratable acids), and plant water relations were measured and radiation use efficiency (RUE) was calculated. Increasing water salinity negatively affected the leaf area index (LAI), radiation use efficiency (RUE) and above-ground dry weight (DW) accumulation resulting in lower total and marketable yield. Maximum total and marketable yield obtained with the NSC treatment were respectively 117.9 and 111.0 Mg ha(-1) in 2004 and 113.1 and 107.9 Mg ha(-1) in 2005. Although the smaller leaf area of salinized plants was largely responsible for reduced RUE, we found approximately 50% of this reduction to be accounted for by processes other than changed crop architecture. These may include an increased stomatal resistance, increased mesophyll resistance and other impaired metabolic functions that may occur at high salinity. Remarkably, we found that LT salinized plants had a slightly better efficiency of use of intercepted radiation (RUEIR) at a given EC of soil extract than ST salinized plants indicating that LT salinization, and consequent permanent modifications of the soil physical properties, may trigger additional physiological mechanisms of adaptation compared to ST salinized plants. These differences are relevant in light of the evolution of salinized areas, also in response to climate change. |
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English |
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Edition |
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| ISSN |
0304-4238 |
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Article |
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| Notes |
CropM, ftnotmacsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4557 |
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