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Lai, R.; Arca, P.; Lagomarsino, A.; Cappai, C.; Seddaiu, G.; Demurtas, C.E.; Roggero, P.P. |
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Title |
Manure fertilization increases soil respiration and creates a negative carbon budget in a Mediterranean maize (Zea mays L.)-based cropping system |
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Journal Article |
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Year |
2017 |
Publication |
Catena |
Abbreviated Journal  |
Catena |
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Volume |
151 |
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Pages |
202-212 |
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Keywords |
Biomass; C turnover; GHG emission; Microbial activity; Soil moisture; Organic-Matter Dynamics; Co2 Efflux; N Fertilization; Forage Systems; Winter-Wheat; Nitrogen; Temperature; Forest; Water; Root |
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Abstract |
Agronomic research is important to identify suitable options for improving soil carbon (C) sequestration and reducing soil CO2 emissions. Therefore, the objectives of this study were i) to analyse the on-farm effects of different nitrogen fertilization sources on soil respiration, ii) to explore the effect of fertilization on soil respiration sensitivity to soil temperature (T) and iii) to assess the effect of the different fertilization regimes on the soil C balance. We hypothesized that i) the soil CO2 emission dynamics in Mediterranean irrigated cropping systems were mainly affected by fertilization management and T and ii) fertilization affected the soil C budget via different C inputs and CO2 efflux. Four fertilization systems (farmyard manure, cattle slurry, cattle slurry + mineral, and mineral) were compared in a double-crop rotation based on silage maize (Zea mays L) and a mixture of Italian ryegrass (Lolium multiflorum Lam.) and oats (Avena sativa L). The research was performed in the dairy district of Arborea, in the coastal zone of Sardinia (Italy), from May 2011 to May 2012. The soil was a Psammentic Palexeralfs with a sandy texture (940 g sand kg(-1)). The soil total respiration (SR), heterotrophic respiration (Rh), T and soil water content (SWC) were simultaneously measured in situ. The soil C balance was computed considering the Rh C losses and the soil C inputs from fertilizer and crop residues. The results showed that the maximum soil CO2 emission rates soon after the application of organic fertilizer reached values up to 121,1111 1 111(-2) s(-1). On average, the manure fertilizer showed significantly higher CO2 emissions, which resulted in a negative annual C balance (-2.9 t ha(-1)). T also affected the soil respiration temporal dynamics during the summer, consistently with results obtained in other temperate climatic regions that are characterized by wet summers and contrary to results from rainfed Mediterranean systems where the summer SR and Rh are constrained by the low SWC. The sensitivity of soil respiration to temperature significantly increased with C input from fertilizer. In conclusion, this research supported the hypotheses tested. Furthermore, the results indicated that i) soil CO2 efflux was significantly affected by fertilization management and T, and ii) fertilization with manure increased the soil respiration and resulted in a significantly negative soil C budget. This latter finding could be primarily explained by a reduction in productivity and, consequently, in crop residue with organic fertilization alone as compared to mineral, by the favourable SWC and T for mineralization, and by the sandy soil texture, which hindered the formation of macroaggregates and hence soil C stabilization, making fertilizer organic inputs highly susceptible to mineralization. (C) 2016 Elsevier B.V. All rights reserved. |
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2017-03-16 |
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0341-8162 |
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CropM, ft_MACSUR |
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MA @ admin @ |
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4939 |
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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. |
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Title |
Effect of weather data aggregation on regional crop simulation for different crops, production conditions, and response variables |
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Journal Article |
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Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
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Volume |
65 |
Issue |
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Pages |
141-157 |
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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 |
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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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0936-577x |
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CropM, ft_macsur |
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MA @ admin @ |
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4754 |
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Hoffmann, H.; Zhao, G.; van Bussel, L.G.J.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.; Constantin, J.; Raynal, H.; Teixeira, E.; Grosz, B.; Doro, L.; Zhao, Z.; Wang, E.; Nendel, C.; Kersebaum, K.C.; Haas, E.; Kiese, R.; Klatt, S.; Eckersten, H.; Vanuytrecht, E.; Kuhnert, M.; Lewan, E.; Rötter, R.; Roggero, P.P.; Wallach, D.; Cammarano, D.; Asseng, S.; Krauss, G.; Siebert, S.; Gaiser, T.; Ewert, F. |
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Title |
Variability of effects of spatial climate data aggregation on regional yield simulation by crop models |
Type |
Journal Article |
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Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
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Volume |
65 |
Issue |
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Pages |
53-69 |
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Keywords |
spatial aggregation effects; crop simulation model; input data; scaling; variability; yield simulation; model comparison; input data aggregation; systems simulation; nitrogen dynamics; data resolution; n2o emissions; winter-wheat; scale; water; impact; apsim |
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Field-scale crop models are often applied at spatial resolutions coarser than that of the arable field. However, little is known about the response of the models to spatially aggregated climate input data and why these responses can differ across models. Depending on the model, regional yield estimates from large-scale simulations may be biased, compared to simulations with high-resolution input data. We evaluated this so-called aggregation effect for 13 crop models for the region of North Rhine-Westphalia in Germany. The models were supplied with climate data of 1 km resolution and spatial aggregates of up to 100 km resolution raster. The models were used with 2 crops (winter wheat and silage maize) and 3 production situations (potential, water-limited and nitrogen-water-limited growth) to improve the understanding of errors in model simulations related to data aggregation and possible interactions with the model structure. The most important climate variables identified in determining the model-specific input data aggregation on simulated yields were mainly related to changes in radiation (wheat) and temperature (maize). Additionally, aggregation effects were systematic, regardless of the extent of the effect. Climate input data aggregation changed the mean simulated regional yield by up to 0.2 t ha(-1), whereas simulated yields from single years and models differed considerably, depending on the data aggregation. This implies that large-scale crop yield simulations are robust against climate data aggregation. However, large-scale simulations can be systematically biased when being evaluated at higher temporal or spatial resolution depending on the model and its parameterization. |
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0936-577x 1616-1572 |
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CropM, ft_macsur |
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MA @ admin @ |
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4694 |
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Author |
Persson, T.; Kværnø, S.; Höglind, M. |
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Title |
Impact of soil type extrapolation on timothy grass yield under baseline and future climate conditions in southeastern Norway |
Type |
Journal Article |
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Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
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Volume |
65 |
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71-86 |
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Keywords |
climate change scenarios; crop modelling; forage grass; lingra; soil properties; spatial variability; phleum pretense; poaceae; simulation-model; nutritive-value; systems simulation; catimo model; crop models; growth; nitrogen; scale; productivity; regrowth |
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Interactions between soil properties and climate affect forage grass productivity. Dynamic models, simulating crop performance as a function of environmental conditions, are valid for a specific location with given soil and weather conditions. Extrapolations of local soil properties to larger regions can help assess the requirement for soil input in regional yield estimations. Using the LINGRA model, we simulated the regional yield level and variability of timothy, a forage grass, in Akershus and Ostfold counties, Norway. Soils were grouped according to physical similarities according to 4 sets of criteria. This resulted in 66, 15, 5 and 1 groups of soils. The properties of the soil with the largest area was extrapolated to the other soils within each group and input to the simulations. All analyses were conducted for 100 yr of generated weather representing the period 1961-1990, and climate projections for the period 2046-2065, the Intergovernmental Panel on Climate Change greenhouse gas emission scenario A1B, and 4 global climate models. The simulated regional seasonal timothy yields were 5-13% lower on average and had higher inter-annual variability for the least detailed soil extrapolation than for the other soil extrapolations, across climates. There were up to 20% spatial intra-regional differences in simulated yield between soil extrapolations. The results indicate that, for conditions similar to these studied here, a few representative profiles are sufficient for simulations of average regional seasonal timothy yield. More spatially detailed yield analyses would benefit from more detailed soil input. |
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0936-577x 1616-1572 |
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CropM, ft_macsur |
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MA @ admin @ |
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4674 |
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Fan, F.; Henriksen, C.B.; Porter, J. |
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Title |
Relationship between stoichiometry and ecosystem services: A case study of it organic farming systems |
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Journal Article |
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Year |
2018 |
Publication |
Ecological Indicators |
Abbreviated Journal |
Ecological Indicators |
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85 |
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400-408 |
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Keywords |
Ecosystem services; Organic farming; Stoichiometry; Field practices; Soil Carbon Storage; Ecological Stoichiometry; Agricultural Management; Earthworm Populations; Nitrogen-Fixation; Cropping Systems; New-Zealand; Quantification; Valuation; Matter |
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Over the past five decades, the delivery of global Ecosystem Services (ES) has diminished and this has been driven partly by anthropogenic activities. Agro-ecosystems cover almost 40% of the terrestrial surface on Earth, and have been considered as one of the most significant ecological experiments with a potential to both contribute to and mitigate global ES loss. In the present study, six different ES (food and fodder production, carbon sequestration, biological pest control, soil water storage, nitrogen regulation and soil formation) were quantified in various organic farming systems and the hypothesis that there is a link between these ES and C:N, C:O and H:O stoichiometric ratios in farming systems was experimentally tested. The results show that different ES are correlated with the stoichiometric ratios to different extents. There are significant positive linear correlations between C:N stoichiometric ratios and all measured ES in the investigated organic farming systems, while not all the ES are correlated with the C:O and H:O ratios. This study has expanded the horizons of stoichiometry by linking a fundamental chemical property of molecules with an emergent property of organic farming systems, namely their ecosystem service provision. |
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2018-06-07 |
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1470-160x |
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CropM, ft_macsur |
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MA @ admin @ |
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5201 |
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