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Author |
Bellocchi, G.; Rivington, M.; Matthews, K.; Acutis, M. |
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Title |
Deliberative processes for comprehensive evaluation of agroecological models. A review |
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Journal Article |
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Year |
2015 |
Publication |
Agronomy for Sustainable Development |
Abbreviated Journal |
Agron. Sust. Developm. |
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Volume |
35 |
Issue |
2 |
Pages |
589-605 |
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Keywords |
component-oriented programing; deliberative approach; modeling; model evaluation; multiple metrics; stakeholders; decision-support-systems; environmental-models; performance evaluation; groundwater models; farming systems; climate-change; irene-dll; simulation; validation; integration |
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Abstract |
The use of biophysical models in agroecology has increased in the last few decades for two main reasons: the need to formalize empirical knowledge and the need to disseminate model-based decision support for decision makers (such as farmers, advisors, and policy makers). The first has encouraged the development and use of mathematical models to enhance the efficiency of field research through extrapolation beyond the limits of site, season, and management. The second reflects the increasing need (by scientists, managers, and the public) for simulation experimentation to explore options and consequences, for example, future resource use efficiency (i.e., management in sustainable intensification), impacts of and adaptation to climate change, understanding market and policy responses to shocks initiated at a biophysical level under increasing demand, and limited supply capacity. Production concerns thus dominate most model applications, but there is a notable growing emphasis on environmental, economic, and policy dimensions. Identifying effective methods of assessing model quality and performance has become a challenging but vital imperative, considering the variety of factors influencing model outputs. Understanding the requirements of stakeholders, in respect of model use, logically implies the need for their inclusion in model evaluation methods. We reviewed the use of metrics of model evaluation, with a particular emphasis on the involvement of stakeholders to expand horizons beyond conventional structured, numeric analyses. Two major topics are discussed: (1) the importance of deliberative processes for model evaluation, and (2) the role computer-aided techniques may play to integrate deliberative processes into the evaluation of agroecological models. We point out that (i) the evaluation of agroecological models can be improved through stakeholder follow-up, which is a key for the acceptability of model realizations in practice, (ii) model credibility depends not only on the outcomes of well-structured, numerically based evaluation, but also on less tangible factors that may need to be addressed using complementary deliberative processes, (iii) comprehensive evaluation of simulation models can be achieved by integrating the expectations of stakeholders via a weighting system of preferences and perception, (iv) questionnaire-based surveys can help understand the challenges posed by the deliberative process, and (v) a benefit can be obtained if model evaluation is conceived in a decisional perspective and evaluation techniques are developed at the same pace with which the models themselves are created and improved. Scientific knowledge hubs are also recognized as critical pillars to advance good modeling practice in relation to model evaluation (including access to dedicated software tools), an activity which is frequently neglected in the context of time-limited framework programs. |
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1774-0746 1773-0155 |
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Review |
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CropM, LiveM, ft_macsur |
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MA @ admin @ |
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4551 |
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Author |
Baranowski, P.; Jedryczka, M.; Mazurek, W.; Babula-Skowronska, D.; Siedliska, A.; Kaczmarek, J. |
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Title |
Hyperspectral and thermal imaging of oilseed rape (Brassica napus) response to fungal species of the genus Alternaria |
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Journal Article |
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Year |
2015 |
Publication |
PLoS One |
Abbreviated Journal |
PLoS One |
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Volume |
10 |
Issue |
3 |
Pages |
e0122913 |
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Keywords |
Algorithms; Alternaria/*pathogenicity; Brassica napus/microbiology/*physiology |
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Abstract |
In this paper, thermal (8-13 µm) and hyperspectral imaging in visible and near infrared (VNIR) and short wavelength infrared (SWIR) ranges were used to elaborate a method of early detection of biotic stresses caused by fungal species belonging to the genus Alternaria that were host (Alternaria alternata, Alternaria brassicae, and Alternaria brassicicola) and non-host (Alternaria dauci) pathogens to oilseed rape (Brassica napus L.). The measurements of disease severity for chosen dates after inoculation were compared to temperature distributions on infected leaves and to averaged reflectance characteristics. Statistical analysis revealed that leaf temperature distributions on particular days after inoculation and respective spectral characteristics, especially in the SWIR range (1000-2500 nm), significantly differed for the leaves inoculated with A. dauci from the other species of Alternaria as well as from leaves of non-treated plants. The significant differences in leaf temperature of the studied Alternaria species were observed in various stages of infection development. The classification experiments were performed on the hyperspectral data of the leaf surfaces to distinguish days after inoculation and Alternaria species. The second-derivative transformation of the spectral data together with back-propagation neural networks (BNNs) appeared to be the best combination for classification of days after inoculation (prediction accuracy 90.5%) and Alternaria species (prediction accuracy 80.5%). |
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1932-6203 |
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CropM, ft_macsur |
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MA @ admin @ |
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4549 |
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Baker, A.; Ceasar, S.A.; Palmer, A.J.; Paterson, J.B.; Qi, W.; Muench, S.P.; Baldwin, S.A. |
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Title |
Replace, reuse, recycle: improving the sustainable use of phosphorus by plants |
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Journal Article |
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Year |
2015 |
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Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
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66 |
Issue |
12 |
Pages |
3523-3540 |
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Keywords |
Conservation of Natural Resources; Crops, Agricultural/growth & development/metabolism; Gene Expression Regulation, Plant; Phosphorus/*metabolism; Plant Proteins/genetics/metabolism; Plants/genetics/*metabolism; Fertilizers; membrane transporters; nutrient recycling; phosphate; phosphate signalling; transcription factors |
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The ‘phosphorus problem’ has recently received strong interest with two distinct strands of importance. The first is that too much phosphorus (P) is entering into waste water, creating a significant economic and ecological problem. Secondly, while agricultural demand for phosphate fertilizer is increasing to maintain crop yields, rock phosphate reserves are rapidly declining. Unravelling the mechanisms by which plants sense, respond to, and acquire phosphate can address both problems, allowing the development of crop plants that are more efficient at acquiring and using limited amounts of phosphate while at the same time improving the potential of plants and other photosynthetic organisms for nutrient recapture and recycling from waste water. In this review, we attempt to synthesize these important but often disparate parts of the debate in a holistic fashion, since solutions to such a complex problem require integrated and multidisciplinary approaches that address both P supply and demand. Rapid progress has been made recently in our understanding of local and systemic signalling mechanisms for phosphate, and of expression and regulation of membrane proteins that take phosphate up from the environment and transport it within the plant. We discuss the current state of understanding of such mechanisms involved in sensing and responding to phosphate stress. We also discuss approaches to improve the P-use efficiency of crop plants and future direction for sustainable use of P, including use of photosynthetic organisms for recapture of P from waste waters. |
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0022-0957 1460-2431 |
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Review |
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CropM |
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MA @ admin @ |
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4548 |
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Watson, J.; Challinor, A.J.; Fricker, T.E.; Ferro, C.A.T. |
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Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model |
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Journal Article |
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Year |
2015 |
Publication |
Climatic Change |
Abbreviated Journal |
Clim. Change |
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132 |
Issue |
1 |
Pages |
93-109 |
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Keywords |
maize; yield; ensemble; impacts; design; heat |
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Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve. |
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0165-0009 1573-1480 |
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CropM, ft_macsur |
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MA @ admin @ |
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4546 |
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Shrestha, S.; Abdalla, M.; Hennessy, T.; Forristal, D.; Jones, M.B. |
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Title |
Irish farms under climate change – is there a regional variation on farm responses? |
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Journal Article |
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Year |
2015 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
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Volume |
153 |
Issue |
03 |
Pages |
385-398 |
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Keywords |
change impacts; elevated co2; potential impacts; maize production; united-states; winter-wheat; plant-growth; adaptation; ireland; yield |
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The current paper aims to determine regional impacts of climate change on Irish farms examining the variation in farm responses. A set of crop growth models were used to determine crop and grass yields under a baseline scenario and a future climate scenario. These crop and grass yields were used along with farm-level data taken from the Irish National Farm Survey in an optimizing farm-level (farm-level linear programming) model, which maximizes farm profits under limiting resources. A change in farm net margins under the climate change scenario compared to the baseline scenario was taken as a measure to determine the effect of climate change on farms. The growth models suggested a decrease in cereal crop yields (up to 9%) but substantial increase in yields of forage maize (up to 97%) and grass (up to 56%) in all regions. Farms in the border, midlands and south-east regions suffered, whereas farms in all other regions generally fared better under the climate change scenario used in the current study. The results suggest that there is a regional variability between farms in their responses to the climate change scenario. Although substituting concentrate feed with grass feeds is the main adaptation on all livestock farms, the extent of such substitution differs between farms in different regions. For example, large dairy farms in the south-east region adopted total substitution of concentrate feed while similar dairy farms in the south-west region opted to replace only 0.30 of concentrate feed. Farms in most of the regions benefitted from increasing stocking rate, except for sheep farms in the border and dairy farms in the south-east regions. The tillage farms in the mid-east region responded to the climate change scenario by shifting arable production to beef production on farms. |
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0021-8596 1469-5146 |
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CropM, TradeM |
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MA @ admin @ |
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4542 |
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