| Records |
| Author |
Ventrella, D.; Charfeddine, M.; Moriondo, M.; Rinaldi, M.; Bindi, M. |
| Title |
Agronomic adaptation strategies under climate change for winter durum wheat and tomato in southern Italy: irrigation and nitrogen fertilization |
Type |
Journal Article |
| Year |
2012 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg Environ Change |
| Volume |
12 |
Issue |
3 |
Pages |
407-419 |
| Keywords |
Modelling; Climate change; Agronomic adaptation strategies; Yield; Tomato; Winter durum wheat; air co2 enrichment; change scenarios; cropping systems; change impacts; simulation; agriculture; variability; increase; model; responses; Environmental Sciences & Ecology |
| Abstract |
Agricultural crops are affected by climate change due to the relationship between crop development, growth, yield, CO2 atmospheric concentration and climate conditions. In particular, the further reduction in existing limited water resources combined with an increase in temperature may result in higher impacts on agricultural crops in the Mediterranean area than in other regions. In this study, the cropping system models CERES-Wheat and CROPGRO-Tomato of the Decision Support System for Agrotechnology Transfer (DSSAT) were used to analyse the response of winter durum wheat (Triticum aestivum L.) and tomato (Lycopersicon esculentum Mill.) crops to climate change, irrigation and nitrogen fertilizer managements in one of most productive areas of Italy (i.e. Capitanata, Puglia). For this analysis, three climatic datasets were used: (1) a single dataset (50 km x 50 km) provided by the JRC European centre for the period 1975-2005; two datasets from HadCM3 for the IPCC A2 GHG scenario for time slices with +2A degrees C (centred over 2030-2060) and +5A degrees C (centred over 2070-2099), respectively. All three datasets were used to generate synthetic climate series using a weather simulator (model LARS-WG). Adaptation strategies, such as irrigation and N fertilizer managements, have been investigated to either avoid or at least reduce the negative impacts induced by climate change impacts for both crops. Warmer temperatures were primarily shown to accelerate wheat and tomato phenology, thereby resulting in decreased total dry matter accumulation for both tomato and wheat under the +5A degrees C future climate scenario. Under the +2A degrees C scenario, dry matter accumulation and resulting yield were also reduced for tomato, whereas no negative yield effects were observed for winter durum wheat. In general, limiting the global mean temperature change of 2A degrees C, the application of adaptation strategies (irrigation and nitrogen fertilization) showed a positive effect in minimizing the negative impacts of climate change on productivity of tomato cultivated in southern Italy. |
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1436-3798 1436-378x |
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CropM |
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no |
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MA @ admin @ |
Serial |
4480 |
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| Author |
Bodirsky, B.L.; Müller, C. |
| Title |
Robust relationship between yields and nitrogen inputs indicates three ways to reduce nitrogen pollution |
Type |
Journal Article |
| Year |
2014 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
| Volume |
9 |
Issue |
11 |
Pages |
111005 |
| Keywords |
nitrogen use efficiency; nitrogen; fertilizer; nitrogen pollution; agriculture; yields; mitigation; framework |
| Abstract |
Historic increases in agricultural production came at the expense of substantial environmental burden through nitrogen pollution. Lassaletta et al (2014 Environ. Res. Lett. 9 105011) examine the historic relationship of crop yields and nitrogen fertilizer inputs globally and find a simple and robust relationship of declining nitrogen use efficiency with increasing nitrogen inputs. This general relationship helps to understand the dilemma between increased agricultural production and nitrogen pollution and allows identifying pathways towards more sustainable agricultural production and necessary associated policies. |
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1748-9326 |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4514 |
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Waha, K.; Müller, C.; Rolinski, S. |
| Title |
Separate and combined effects of temperature and precipitation change on maize yields in sub-Saharan Africa for mid- to late-21st century |
Type |
Journal Article |
| Year |
2013 |
Publication |
Global and Planetary Change |
Abbreviated Journal |
Global and Planetary Change |
| Volume |
106 |
Issue |
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Pages |
1-12 |
| Keywords |
climate change; wet season; water stress; temperature stress; hierarchical cluster analysis; global vegetation model; climate-change; southern africa; east-africa; part i; food; heat; agriculture; variability; impacts |
| Abstract |
Maize (Zea mays L) is one of the most important food crops and very common in all parts of sub-Saharan Africa. In 2010 53 million tons of maize were produced in sub-Saharan Africa on about one third of the total harvested cropland area (similar to 33 million ha). Our aim is to identify the limiting agroclimatic variable for maize growth and development in sub-Saharan Africa by analyzing the separated and combined effects of temperature and precipitation. Under changing climate, both climate variables are projected to change severely, and their impacts on crop yields are frequently assessed using process-based crop models. However it is often unclear which agroclimatic variable will have the strongest influence on crop growth and development under climate change and previous studies disagree over this question. We create synthetic climate data in order to study the effect of large changes in the length of the wet season and the amount of precipitation during the wet season both separately and in combination with changes in temperature. The dynamic global vegetation model for managed land LPJmL is used to simulate maize yields under current and future climatic conditions for the two 10-year periods 2056-2065 and 2081-2090 for three climate scenarios for the A1b emission scenario but without considering the beneficial CO2 fertilization effect. The importance of temperature and precipitation effects on maize yields varies spatially and we identify four groups of crop yield changes: regions with strong negative effects resulting from climate change (<-33% yield change), regions with moderate (-33% to -10% yield change) or slight negative effects (-10% to +6% yield change), and regions with positive effects arising from climate change mainly in currently temperature-limited high altitudes (>+6% yield change). In the first three groups temperature increases lead to maize yield reductions of 3 to 20%, with the exception of mountainous and thus cooler regions in South and East Africa. A reduction of the wet season precipitation causes decreases in maize yield of at least 30% and prevails over the effect of increased temperatures in southern parts of Mozambique and Zambia, the Sahel and parts of eastern Africa in the two projection periods. This knowledge about the limiting abiotic stress factor in each region will help to prioritize future research needs in modeling of agricultural systems as well as in drought and heat stress breeding programs and to identify adaption options in agricultural development projects. On the other hand the study enhances the understanding of temperature and water stress effects on crop yields in a global vegetation model in order to identify future research and model development needs. (C) 2013 Elsevier B.V. All rights reserved. |
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0921-8181 |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
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MA @ admin @ |
Serial |
4508 |
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| Author |
Dietrich, J.P.; Popp, A.; Lotze-Campen, H. |
| Title |
Reducing the loss of information and gaining accuracy with clustering methods in a global land-use model |
Type |
Journal Article |
| Year |
2013 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
| Volume |
263 |
Issue |
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Pages |
233-243 |
| Keywords |
aggregation; downscaling; clustering; information conservation; land use model; scale; scales; agriculture; simulation; dynamics; pattern |
| Abstract |
Global land-use models have to deal with processes on several spatial scales, ranging from the global scale down to the farm level. The increasing complexity of modern land-use models combined with the problem of limited computational resources represents a challenge to modelers. One solution of this problem is to perform spatial aggregation based on a regular grid or administrative units such as countries. Unfortunately this type of aggregation flattens many regional differences and produces a homogenized map of the world. In this paper we present an alternative aggregation approach using clustering methods. Clustering reduces the loss of information due to aggregation by choosing an appropriate aggregation pattern. We investigate different clustering methods, examining their quality in terms of information conservation. Our results indicate that clustering is always a good choice and preferable compared to grid-based aggregation. Although all the clustering methods we tested delivered a higher degree of information conservation than grid-based aggregation, the choice of clustering method is not arbitrary. Comparing outputs of a model fed with original data and a model fed with aggregated data, bottom-up clustering delivered the best results for the whole range of numbers of clusters tested. (C) 2013 Elsevier B.V. All rights reserved. |
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0304-3800 |
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Article |
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| Notes |
TradeM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4488 |
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| Author |
Dono, G.; Cortignani, R.; Doro, L.; Giraldo, L.; Ledda, L.; Pasqui, M.; Roggero, P.P. |
| Title |
Adapting to uncertainty associated with short-term climate variability changes in irrigated Mediterranean farming systems |
Type |
Journal Article |
| Year |
2013 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
| Volume |
117 |
Issue |
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Pages |
1-12 |
| Keywords |
changed climate variability; dsp; epic; adaptation; water management; irrigation; simulating impacts; co2 concentration; crop production; productivity; maize; yield; growth; model; photosynthesis; agriculture |
| Abstract |
Short-term perspectives appear to be relevant in formulating adaptation measures to changed climate variability (CCV) as a part of the European Rural Development Policy (RDP). Indeed, short-run CCV is the variation that farmers would perceive to such an extent that a political demand would be generated for adapting support measures. This study evaluates some relevant agronomic and economic impacts of CCV as modelled in a near future time period at the catchment scale in a rural district in Sardinia (Italy). The effects of CCV are assessed in relation to the availability of irrigation water and the irrigation needs of maize. The Environmental Policy Integrated Climate (EPIC) model was used to simulate the impact of key climatic variables on the irrigation water requirements and yields of maize. A three-stage discrete stochastic programming model was then applied to simulate management and economic responses to those changes. The overall economic impact of a simulated CCV was found to be primarily caused by reduced stability in the future supply of irrigation water. Adaptations to this instability will most likely lead to a higher level of groundwater extraction and a reduction in the demand for labour. Changed climate variability will most likely reduce the income potential of small-scale farming. The most CCV-vulnerable farm typologies were identified, and the implications were discussed in relation to the development of adaptation measures within the context of the Common Agricultural Policy of European Union. (C) 2013 Elsevier Ltd. All rights reserved. |
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English |
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0308521x |
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CropM, ftnotmacsur |
Approved |
no |
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MA @ admin @ |
Serial |
4489 |
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