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Toscano, P., Genesio, L., Crisci, A., Vaccari, F. P., Ferrari, E., La Cava, P., et al. (2015). Empirical modelling of regional and national durum wheat quality. Agricultural and Forest Meteorology, 204, 67–78.
Abstract: The production of durum wheat in the Mediterranean basin is expected to experience increased variability in yield and quality as a consequence of climate change. To assess how environmental variables and agronomic practices affect grain protein content (GPC), a novel approach based on monthly gridded input data has been implemented to develop empirical model, and validated on historical time series to assess its capability to reproduce observed spatial and inter-annual GPC variability. The model was applied in four Italian regions and at the whole national scale and proved reliable and usable for operational purposes also in a forecast ‘real-time’ mode before harvesting. Precipitable water during autumn to winter and air temperature from anthesis to harvest were extremely important influences on GPC; these and additional variables, included in a linear model, were able to account for 95% of the variability in GPC that has occurred in the last 15 years in Italy. Our results are a unique example of the use of modelling as a predictive real-time platform and are a useful tool to understand better and forecast the impacts of future climate change projections on durum wheat production and quality.
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Waha, K., & Müller, C. (2013). The essential temperature routines in LPJmL for wheat simulations. In P. D. Alderman, E. Quilligan, S. Asseng, F. Ewert, & M. P. Reynolds (Eds.), (pp. 81–84). Proceedings of the Workshop ‘Modeling Wheat Response to High Temperature’ CIMMYT, El Batan, Texcoco, Mexico, June 19-21, 2013. |
Sándor, R., Barcza, Z., Hidy, D., Lellei-Kovács, E., Ma, S., & Bellocchi, G. (2016). Modelling of grassland fluxes in Europe: evaluation of two biogeochemical models. Agric. Ecosyst. Environ., 215, 1–19.
Abstract: Two independently developed simulation models – the grassland-specific PaSim and the biome-generic Biome-BGC MuSo (BBGC MuSo) – linking climate, soil, vegetation and management to ecosystem biogeochemical cycles were compared in a simulation of carbon (C) and water fluxes. The results were assessed against eddy-covariance flux data from five observational grassland sites representing a range of conditions in Europe: Grillenburg in Germany, Laqueuille in France with both extensive and intensive management, Monte Bondone in Italy and Oensingen in Switzerland. Model comparison (after calibration) gave substantial agreement, the performances being marginal to acceptable for weekly-aggregated gross primary production and ecosystem respiration (R-2 similar to 0.66 – 0.91), weekly evapotranspiration (R-2 similar to 0.78 – 0.94), soil water content in the topsoil (R-2 similar to 0.1 -0.7) and soil temperature (R-2 similar to 0.88 – 0.96). The bias was limited to the range -13 to 9 g C m(-2) week(-1) for C fluxes (-11 to 8 g C m(-2) week(-1) in case of BBGC MuSo, and -13 to 9 g C m(-2) week(-1) in case of PaSim) and -4 to 6 mm week for water fluxes (with BBGC MuSo providing somewhat higher estimates than PaSim), but some higher relative root mean square errors indicate low accuracy for prediction, especially for net ecosystem exchange The sensitivity of simulated outputs to changes in atmospheric carbon dioxide concentration ([CO2]), temperature and precipitation indicate, with certain agreement between the two models, that C outcomes are dominated by [CO2] and temperature gradients, and are less due to precipitation. ET rates decrease with increasing [CO2] in PaSim (consistent with experimental knowledge), while lack of appropriate stomatal response could be a limit in BBGC MuSo responsiveness. Results of the study indicate that some of the errors might be related to the improper representation of soil water content and soil temperature. Improvement is needed in the model representations of soil processes (especially soil water balance) that strongly influence the biogeochemical cycles of managed and unmanaged grasslands. (C) 2015 Elsevier B.V. All rights reserved.
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Sandhu, H., Wratten, S., Costanza, R., Pretty, J., Porter, J. R., & Reganold, J. (2015). Significance and value of non-traded ecosystem services on farmland. PeerJ, 3, e762.
Abstract: Background. Ecosystem services (ES) generated within agricultural landscapes, including field boundaries, are vital for the sustainable supply of food and fibre. However, the value of ES in agriculture has not been quantified experimentally and then extrapolated globally. Methods. We quantified the economic value of two key but contrasting ES (biological control of pests and nitrogen mineralisation) provided by non-traded non-crop species in ten organic and ten conventional arable fields in New Zealand using field experiments. The arable crops grown, same for each organic and conventional pair, were peas (Pisum sativum), beans (Phaseolus vulgaris), barley (Hordeum vulgare), and wheat (Triticum aestivum). Organic systems were chosen as comparators not because they are the only forms of sustainable agriculture, but because they are subject to easily understood standards. Results. We found that organic farming systems depended on fewer external inputs and produced outputs of energy and crop dry matter generally less than but sometimes similar to those of their conventional counterparts. The economic values of the two selected ES were greater for the organic systems in all four crops, ranging from US$ 68-200 ha(-1) yr(-1) for biological control of pests and from US$ 110-425 ha(-1)yr(-1) for N mineralisation in the organic systems versus US$ 0 ha(-1)yr(-1) for biological control of pests and from US$ 60-244 ha(-1)yr(-1) for N mineralisation in the conventional systems. The total economic value (including market and non-market components) was significantly greater in organic systems, ranging from US$ 1750-4536 ha(-1)yr(-1), with US$ 1585-2560 ha(-1)yr(-1) in the conventional systems. The non-market component of the economic value in organic fields was also significantly higher than those in conventional fields. Discussion. To illustrate the potential magnitude of these two ES to temperate farming systems and agricultural landscapes elsewhere, we then extrapolate these experimentally derived figures to the global temperate cropping area of the same arable crops. We found that the extrapolated net value of the these two services provided by non-traded species could exceed the combined current global costs of pesticide and fertiliser inputs, even if utilised on only 10% of the global arable area. This approach strengthens the case for ES-rich agricultural systems, provided by non-traded species to global agriculture.
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Schmitz, C., Kreidenweis, U., Lotze-Campen, H., Popp, A., Krause, M., Dietrich, J. P., et al. (2014). Agricultural trade and tropical deforestation: interactions and related policy options. Reg Environ Change, 15(8), 1757–1772.
Abstract: The extensive clearing of tropical forests throughout past decades has been partly assigned to increased trade in agricultural goods. Since further trade liberalisation can be expected, remaining rainforests are likely to face additional threats with negative implications for climate mitigation and the local environment. We apply a spatially explicit economic land-use model coupled to a biophysical vegetation model to examine linkages and associated policies between trade and tropical deforestation in the future. Results indicate that further trade liberalisation leads to an expansion of deforestation in Amazonia due to comparative advantages of agriculture in South America. Globally, between 30 and 60 million ha (5-10 %) of tropical rainforests would be cleared additionally, leading to 20-40 Gt additional emissions by 2050. By applying different forest protection policies, those values could be reduced substantially. Most effective would be the inclusion of avoided deforestation into a global emissions trading scheme. Carbon prices corresponding to the concentration target of 550 ppm would prevent deforestation after 2020. Investing in agricultural productivity reduces pressure on tropical forests without the necessity of direct protection. In general, additional trade-induced demand from developed and emerging countries should be compensated by international efforts to protect natural resources in tropical regions.
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