| Records |
| Author |
Dono, G.; Raffaele, C.; Luca, G.; Roggero, P.P. |
| Title |
Income Impacts of Climate Change: Irrigated Farming in the Mediterranean and Expected Changes in Probability of Favorable and Adverse Weather Conditions |
Type |
Journal Article |
| Year |
2014 |
Publication |
German Journal of Agricultural Economics |
Abbreviated Journal |
German Journal of Agricultural Economics |
| Volume |
63 |
Issue  |
3 |
Pages |
177-186 |
| Keywords |
discrete stochastic programming; rdp measures to adapt to climate change; economic impact of climate change; irrigated agriculture and climate change; insurance tools for adaptation to climate change; water markets; risk; variability; management; systems |
| Abstract |
EU rural development policy (RDP) regulation 1305/2013 aims to protect farmers’ incomes from ongoing change of climate variability (CCV), and the increase in frequency of adverse climatic events. An income stabilization tool (IST) is provided to compensate drastic drops in income, including those caused by climatic events. The present study examines some aspect of its application focussing on Mediterranean irrigation area where frequent water shortages may generate significant income reductions in the current climate conditions, and may be further exacerbated by climate change. This enhanced loss of income in the future would occur due to a change in climate variability. This change would appreciably reduce the probability of weather conditions that are favourable for irrigation, but would not significantly increase either the probability of unfavourable weather conditions or the magnitude of their impact. As the IST and other insurance tools that protect against adversity and catastrophic events are only activated under extreme conditions, farmers may not consider them to be suitable in dealing with the new climate regime. This would leave a portion of the financial resources allocated by the RDP unused, resulting in less support for climate change adaptation. |
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English |
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| ISSN |
0002-1121 |
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| Notes |
CropM, TradeM, ft_macsur |
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no |
| Call Number |
MA @ admin @ |
Serial |
4669 |
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| Author |
Schönhart, M.; Mitter, H.; Schmid, E.; Heinrich, G.; Gobiet, A. |
| Title |
Integrated analysis of climate change impacts and adaptation measures in Austrian agriculture |
Type |
Journal Article |
| Year |
2014 |
Publication |
German Journal of Agricultural Economics |
Abbreviated Journal |
German Journal of Agricultural Economics |
| Volume |
63 |
Issue |
3 |
Pages |
156-176 |
| Keywords |
land use; modelling; climate change impact; adaptation; integrated analysis; epic; pasma; crop production; land-use; management-practices; model projections; central-europe; soil-erosion; water; variability; strategies; region |
| Abstract |
An integrated modelling framework (IMF) has been developed and applied to analyse climate change impacts and the effectiveness of adaptation measures in Austrian agriculture. The IMF couples the crop rotation model CropRota, the bio-physical process model EPIC and the bottom-up economic land use model PASMA at regional level (NUTS-3) considering agri-environmental indicators. Four contrasting regional climate model (RCM) simulations represent climate change until 2050. The RCM simulations are applied to a baseline and three adaptation and policy scenarios. Climate change increases crop productivity on national average in the IMF. Changes in average gross margins at national level range from 0% to + 5% between the baseline and the three adaptation and policy scenarios. The impacts at NUTS-3 level range from -5% to + 7% between the baseline and the three adaptation and policy scenarios. Adaptation measures such as planting of winter cover crops, reduced tillage and irrigation are effective in reducing yield losses, increasing revenues, or in improving environmental states under climate change. Future research should account for extreme weather events in order to analyse whether average productivity gains at the aggregated level suffice to cover costs from expected higher climate variability. |
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English |
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0002-1121 |
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| Notes |
TradeM, ft_macsur |
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no |
| Call Number |
MA @ admin @ |
Serial |
4652 |
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| Author |
Legarrea, S.; Velázquez, E.; Aguado, P.; Fereres, A.; Morales, I.; Rodríguez, D.; Del Estal, P.; Viñuela, E. |
| Title |
Effects of a photoselective greenhouse cover on the performance and host finding ability of Aphidius ervi in a lettuce crop |
Type |
Journal Article |
| Year |
2014 |
Publication |
BioControl |
Abbreviated Journal |
BioControl |
| Volume |
59 |
Issue |
3 |
Pages |
265-278 |
| Keywords |
aphidius ervi; macrosiphum euphorbiae; uv-absorbing net; parasitoid; sadie; spatial distribution; integrated pest-management; natural enemies; plastic films; mosaic-virus; insect pests; count data; pea aphid; uv; parasitoids; hymenoptera |
| Abstract |
In the search for a durable pest control management, biological control agents and photoselective covers are suitable candidates to be implemented in greenhouse crops. In this work, we studied the effects of a 50 mesh photoselective cover compared to a standard with similar characteristics but without UV-absorbing additives on the performance of Aphidius ervi Haliday (Hymenoptera: Braconidae), a widely used parasitoid to control aphids in vegetable crops. Four field experiments were conducted in La Poveda Experimental Farm (Central Spain) where a lettuce crop was grown during the years 2008-2010. Lettuce plants were infested by Macrosiphum euphorbiae (Thomas) (Hemiptera: Aphididae) and the parasitoid A. ervi was released and monitored throughout the crop cycle to evaluate any constraint in its performance produced by UV-absorbing nets. The ability of A. ervi to find and parasitize the host was not modified by the photoselective cover during the four seasons studied. Thus, we suggest that both strategies could be combined in the context of IPM in vegetable crops where this natural enemy is released. |
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1386-6141, 1573-8248 |
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Article |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4509 |
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| Author |
Holman, I.P.; Brown, C.; Carter, T.R.; Harrison, P.A.; Rounsevell, M. |
| Title |
Improving the representation of adaptation in climate change impact models |
Type |
Journal Article |
| Year |
2019 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg. Environ. Change |
| Volume |
19 |
Issue |
3 |
Pages |
711-721 |
| Keywords |
Adaptive capacity; Limits; Water; Land; Decision making; Integrated assessment; Land-Cover Change; Global Change; River-Basin; Integrated Assessment; Adaptive Capacity; Vulnerability; Variability; Precautionary; Agriculture; Management |
| Abstract |
Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate. |
| Address |
2019-04-27 |
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English |
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| ISSN |
1436-3798 |
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Article |
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| Notes |
TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5220 |
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| Author |
Mansouri, M.; Dumont, B.; Leemans, V.; Destain, M.-F. |
| Title |
Bayesian methods for predicting LAI and soil water content |
Type |
Journal Article |
| Year |
2014 |
Publication |
Precision Agriculture |
Abbreviated Journal |
Precision Agric. |
| Volume |
15 |
Issue |
2 |
Pages |
184-201 |
| Keywords |
crop model; bayes; data assimilation; extended kalman filtering; particle filtering; variational filtering; leaf-area index; parameter-estimation; crop models; moisture; instruments; management; sensors; state |
| Abstract |
LAI of winter wheat (Triticum aestivum L.) and soil water content of the topsoil (200 mm) and of the subsoil (500 mm) were considered as state variables of a dynamic soil-crop system. This system was assumed to progress according to a Bayesian probabilistic state space model, in which real values of LAI and soil water content were daily introduced in order to correct the model trajectory and reach better future evolution. The chosen crop model was mini STICS which can reduce the computing and execution times while ensuring the robustness of data processing and estimation. To predict simultaneously state variables and model parameters in this non-linear environment, three techniques were used: extended Kalman filtering (EKF), particle filtering (PF), and variational filtering (VF). The significantly improved performance of the VF method when compared to EKF and PF is demonstrated. The variational filter has a low computational complexity and the convergence speed of states and parameters estimation can be adjusted independently. Detailed case studies demonstrated that the root mean square error of the three estimated states (LAI and soil water content of two soil layers) was smaller and that the convergence of all considered parameters was ensured when using VF. Assimilating measurements in a crop model allows accurate prediction of LAI and soil water content at a local scale. As these biophysical properties are key parameters in the crop-plant system characterization, the system has the potential to be used in precision farming to aid farmers and decision makers in developing strategies for site-specific management of inputs, such as fertilizers and water irrigation. |
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English |
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Edition |
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| ISSN |
1385-2256 |
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| Notes |
CropM, ftnotmacsur |
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no |
| Call Number |
MA @ admin @ |
Serial |
4629 |
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