Records |
Author |
Özkan, Ş.; Vitali, A.; Lacetera, N.; Amon, B.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; de Haas, Y.; Dufrasne, I.; Elliott, J.; Eory, V.; Fox, N.J.; Garnsworthy, P.C.; Gengler, N.; Hammami, H.; Kyriazakis, I.; Leclère, D.; Lessire, F.; Macleod, M.; Robinson, T.P.; Ruete, A.; Sandars, D.L.; Shrestha, S.; Stott, A.W.; Twardy, S.; Vanrobays, M.L.; Ahmadi, B.V.; Weindl, I.; Wheelhouse, N.; Williams, A.G.; Williams, H.W.; Wilson, A.J.; Østergaard, S.; Kipling, R.P. |
Title |
Challenges and priorities for modelling livestock health and pathogens in the context of climate change |
Type |
Journal Article |
Year |
2016 |
Publication |
Environmental Research |
Abbreviated Journal |
Environ. Res. |
Volume |
151 |
Issue |
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Pages |
130-144 |
Keywords |
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Abstract |
Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire based exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change. |
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ISSN |
0013-9351 |
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LiveM |
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no |
Call Number |
MA @ admin @ |
Serial |
4766 |
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Author |
Kahiluoto, H.; Rötter, R.; Webber, H.; Ewert, F. |
Title |
The Role of Modelling in Adapting and Building the Climate Resilience of Cropping Systems |
Type |
Book Chapter |
Year |
2014 |
Publication |
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Abbreviated Journal |
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Volume |
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Issue |
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Pages |
204-215 |
Keywords |
CropM |
Abstract |
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Publisher |
CAB International |
Place of Publication |
Wallingford |
Editor |
Fuhrer, J.; Gregory, P.J. |
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Series Title |
Climate Change Impact and Adaptation in Agricultural Systems |
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no |
Call Number |
MA @ admin @ |
Serial |
2513 |
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Author |
Tao, F.; Zhang, Z.; Zhang, S.; Rötter, R.P. |
Title |
Variability in crop yields associated with climate anomalies in China over the past three decades |
Type |
Journal Article |
Year |
2016 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg Environ Change |
Volume |
16 |
Issue |
6 |
Pages |
1715-1723 |
Keywords |
Adaptation; Climate change; Climate extremes; Drought; Impacts and vulnerability |
Abstract |
We used simple and explicit methods, as well as improved datasets for climate, crop phenology and yields, to address the association between variability in crop yields and climate anomalies in China from 1980 to 2008. We identified the most favourable and unfavourable climate conditions and the optimum temperatures for crop productivity in different regions of China. We found that the simultaneous occurrence of high temperatures, low precipitation and high solar radiation was unfavourable for wheat, maize and soybean productivity in large portions of northern, northwestern and northeastern China; this was because of droughts induced by warming or an increase in solar radiation. These climate anomalies could cause yield losses of up to 50 % for wheat, maize and soybeans in the arid and semi-arid regions of China. High precipitation and low solar radiation were unfavourable for crop productivity throughout southeastern China and could cause yield losses of approximately 20 % for rice and 50 % for wheat and maize. High temperatures were unfavourable for rice productivity in southwestern China because they induced heat stress, which could cause rice yield losses of approximately 20 %. In contrast, high temperatures and low precipitation were favourable for rice productivity in northeastern and eastern China. We found that the optimum temperatures for high yields were crop specific and had an explicit spatial pattern. These findings improve our understanding of the impacts of extreme climate events on agricultural production in different regions of China. |
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2016-06-20 |
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English |
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1436-3798 1436-378x |
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Notes |
CropM, ft_macsur |
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no |
Call Number |
MA @ admin @ |
Serial |
4757 |
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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 |
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Edition |
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ISSN |
0936-577x |
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Notes |
CropM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4754 |
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Author |
Hoff, H.; Gerten, D.; Waha, K.; Warner, J.; Keulertz, M.; Sojamo, S. |
Title |
Green and Blue Water in Africa: How Foreign Direct Investment can Support Sustainable Intensification |
Type |
Book Chapter |
Year |
2013 |
Publication |
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Abbreviated Journal |
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Volume |
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Issue |
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Pages |
359-375 |
Keywords |
Xc |
Abstract |
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Thesis |
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Publisher |
Routledge |
Place of Publication |
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Editor |
Allan, T.; Keulertz, M.; Sojamo, S.A. |
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Series Title |
Handbook of Land and Water Grabs in Africa |
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no |
Call Number |
MA @ admin @ |
Serial |
2480 |
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