| Records |
| Author |
Cassardo, C.; Andreoli, V. |
| Title |
On the Representativeness of UTOPIA Land Surface Model for Creating a Database of Surface Layer, Vegetation and Soil Variables in Piedmont Vineyards, Italy |
Type |
Journal Article |
| Year |
2019 |
Publication |
Applied Sciences-Basel |
Abbreviated Journal |
Applied Sciences-Basel |
| Volume |
9 |
Issue |
18 |
Pages |
3880 |
| Keywords |
land-surface; UTOPIA; NOAH; GLDAS; micrometeorology; exchanges; processes; vineyards; cabernet-sauvignon; climate-change; wine color; temperature; parameterization; simulations; circulation; balances; moisture; sunlight |
| Abstract |
The main aim of the paper is to show how, and how many, simulations carried out using the Land Surface Model UTOPIA (University of TOrino model of land Process Interaction with Atmosphere) are representative of the micro-meteorological conditions and exchange processes at the atmosphere/biosphere interface, with a particular focus on heat and hydrologic transfers, over an area of the Piemonte (Piedmont) region, NW Italy, which is characterized by the presence of many vineyards. Another equally important aim is to understand how much the quality of the simulation outputs was influenced by the input data, whose measurements are often unavailable for long periods over country areas at an hourly basis. Three types of forcing data were used: observations from an experimental campaign carried out during the 2008, 2009, and 2010 vegetative seasons in three vineyards, and values extracted from the freely available Global Land Data Assimilation System (GLDAS, versions 2.0 and 2.1). Since GLDAS also contains the outputs of the simulations performed using the Land Surface Model NOAH, an additional intercomparison between the two models, UTOPIA and NOAH, both driven by the same GLDAS datasets, was performed. The intercomparisons were performed on the following micro-meteorological variables: net radiation, sensible and latent turbulent heat fluxes, and temperature and humidity of soil. The results of this study indicate that the methodology of employing land surface models driven by a gridded database to evaluate variables of micro-meteorological and agronomic interest in the absence of observations is suitable and gives satisfactory results, with uncertainties comparable to measurement errors, thus, allowing us to also evaluate some time trends. The comparison between GLDAS2.0 and GLDAS2.1 indicates that the latter generally produces simulation outputs more similar to the observations than the former, using both UTOPIA and NOAH models. |
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2020-02-14 |
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English |
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CropM, ft_macsur |
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MA @ admin @ |
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5228 |
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Francioni, M.; D’Ottavio, P.; Lai, R.; Trozzo, L.; Budimir, K.; Foresi, L.; Kishimoto-Mo, A.W.; Baldoni, N.; Allegrezza, M.; Tesei, G.; Toderi, M. |
| Title |
Seasonal Soil Respiration Dynamics and Carbon-Stock Variations in Mountain Permanent Grasslands Compared to Arable Lands |
Type |
Journal Article |
| Year |
2019 |
Publication |
Agriculture-Basel |
Abbreviated Journal |
Agriculture-Basel |
| Volume |
9 |
Issue |
8 |
Pages |
165 |
| Keywords |
ecosystem services; C stock; CO2; GHG; land use change; Q(10); temperature; vegetation; patterns; emissions; climate |
| Abstract |
Permanent grasslands provide a wide array of ecosystem services. Despite this, few studies have investigated grassland carbon (C) dynamics, and especially those related to the effects of land-use changes. This study aimed to determine whether the land-use change from permanent grassland to arable lands resulted in variations in the soil C stock, and whether such variations were due to increased soil respiration or to management practices. To address this, seasonal variations of soil respiration, sensitivity of soil respiration to soil temperature (Q(10)), and soil C stock variations generated by land-use changes were analyzed in a temperate mountain area of central Italy. The comparisons were performed for a permanent grassland and two adjacent fields, one cultivated with lentil and the other with emmer, during the 2015 crop year. Soil respiration and its heterotrophic component showed different spatial and temporal dynamics. Annual cumulative soil respiration rates were 6.05, 5.05 and 3.99 t C ha(-1) year(-1) for grassland, lentil and emmer, respectively. Both soil respiration and heterotrophic soil respiration were positively correlated with soil temperature at 10 cm depth. Derived Q(10) values were from 2.23 to 6.05 for soil respiration, and from 1.82 to 4.06 for heterotrophic respiration. Soil C stock at over 0.2 m in depth was 93.56, 48.74 and 46.80 t C ha(-1) for grassland, lentil and emmer, respectively. The land-use changes from permanent grassland to arable land lead to depletion in terms of the soil C stock due to water soil erosion. A more general evaluation appears necessary to determine the multiple effects of this land-use change at the landscape scale. |
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2020-02-14 |
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LiveM, ft_macsur |
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MA @ admin @ |
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5229 |
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De Swaef, T.; Bellocchi, G.; Aper, J.; Lootens, P.; Roldan-Ruiz, I. |
| Title |
Use of identifiability analysis in designing phenotyping experiments for modelling forage production and quality |
Type |
Journal Article |
| Year |
2019 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
| Volume |
70 |
Issue |
9 |
Pages |
2587-2604 |
| Keywords |
Breeding; grassland modelling; identifiability analysis; perennial; ryegrass; phenotyping; sensitivity analysis; pasture simulation-model; practical identifiability; crop; water; parameters; systems; carbon; uncertainty; sensitivity; emissions |
| Abstract |
Agricultural systems models are complex and tend to be over-parameterized with respect to observational datasets. Practical identifiability analysis based on local sensitivity analysis has proved effective in investigating identifiable parameter sets in environmental models, but has not been applied to agricultural systems models. Here, we demonstrate that identifiability analysis improves experimental design to ensure independent parameter estimation for yield and quality outputs of a complex grassland model. The Pasture Simulation model (PaSim) was used to demonstrate the effectiveness of practical identifiability analysis in designing experiments and measurement protocols within phe-notyping experiments with perennial ryegrass. Virtual experiments were designed combining three factors: frequency of measurements, duration of the experiment. and location of trials. Our results demonstrate that (i) PaSim provides sufficient detail in terms of simulating biomass yield and quality of perennial ryegrass for use in breeding, (ii) typical breeding trials are insufficient to parameterize all influential parameters, (iii) the frequency of measurements is more important than the number of growing seasons to improve the identifiability of PaSim parameters, and (iv) identifiability analysis provides a sound approach for optimizing the design of multi-location trials. Practical identifiability analysis can play an important role in ensuring proper exploitation of phenotypic data and cost-effective multi-location experimental designs. Considering the growing importance of simulation models, this study supports the design of experiments and measurement protocols in the phenotyping networks that have recently been organized. |
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2020-02-14 |
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English |
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0022-0957 |
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LiveM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
5231 |
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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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1436-3798 |
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TradeM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
5220 |
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Schils, R.; Olesen, J.E.; Kersebaum, K.-C.; Rijk, B.; Oberforster, M.; Kalyada, V.; Khitrykau, M.; Gobin, A.; Kirchev, H.; Manolova, V.; Manolov, I.; Trnka, M.; Hlavinka, P.; Palosuo, T.; Peltonen-Sainio, P.; Jauhiainen, L.; Lorgeou, J.; Marrou, H.; Danalatos, N.; Archontoulis, S.; Fodor, N.; Spink, J.; Roggero, P.P.; Bassu, S.; Pulina, A.; Seehusen, T.; Uhlen, A.K.; Zylowska, K.; Nierobca, A.; Kozyra, J.; Silva, J.V.; Macas, B.M.; Coutinho, J.; Ion, V.; Takac, J.; Ines Minguez, M.; Eckersten, H.; Levy, L.; Herrera, J.M.; Hiltbrunner, J.; Kryvobok, O.; Kryvoshein, O.; Sylvester-Bradley, R.; Kindred, D.; Topp, C.F.E.; Boogaard, H.; de Groot, H.; Lesschen, J.P.; van Bussel, L.; Wolf, J.; Zijlstra, M.; van Loon, M.P.; van Ittersum, M.K. |
| Title |
Cereal yield gaps across Europe |
Type |
Journal Article |
| Year |
2018 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
Europ. J. Agron. |
| Volume |
101 |
Issue |
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Pages |
109-120 |
| Keywords |
Wheat, Barley, Grain maize, Crop modelling, Yield potential, Nitrogen; Nitrogen Use Efficiency; Sustainable Intensification; Climate-Change; Land-Use; Wheat; Soil; Agriculture; Impacts; Fertility; Emissions |
| Abstract |
Europe accounts for around 20% of the global cereal production and is a net exporter of ca. 15% of that production. Increasing global demand for cereals justifies questions as to where and by how much Europe’s production can be increased to meet future global market demands, and how much additional nitrogen (N) crops would require. The latter is important as environmental concern and legislation are equally important as production aims in Europe. Here, we used a country-by-country, bottom-up approach to establish statistical estimates of actual grain yield, and compare these to modelled estimates of potential yields for either irrigated or rainfed conditions. In this way, we identified the yield gaps and the opportunities for increased cereal production for wheat, barley and maize, which represent 90% of the cereals grown in Europe. The combined mean annual yield gap of wheat, barley, maize was 239 Mt, or 42% of the yield potential. The national yield gaps ranged between 10 and 70%, with small gaps in many north-western European countries, and large gaps in eastern and south-western Europe. Yield gaps for rainfed and irrigated maize were consistently lower than those of wheat and barley. If the yield gaps of maize, wheat and barley would be reduced from 42% to 20% of potential yields, this would increase annual cereal production by 128 Mt (39%). Potential for higher cereal production exists predominantly in Eastern Europe, and half of Europe’s potential increase is located in Ukraine, Romania and Poland. Unlocking the identified potential for production growth requires a substantial increase of the crop N uptake of 4.8 Mt. Across Europe, the average N uptake gaps, to achieve 80% of the yield potential, were 87, 77 and 43 kg N ha(-1) for wheat, barley and maize, respectively. Emphasis on increasing the N use efficiency is necessary to minimize the need for additional N inputs. Whether yield gap reduction is desirable and feasible is a matter of balancing Europe’s role in global food security, farm economic objectives and environmental targets. |
| Address |
2019-01-07 |
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English |
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Edition |
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1161-0301 |
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CropM, TradeM, ft_macsur |
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no |
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MA @ admin @ |
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5213 |
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