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Müller, C. (2013). African lessons on climate change risks for agriculture. Ann. Rev. Nutr., 33(1), 395–411.
Abstract: Climate change impact assessments on agriculture are subject to large uncertainties, as demonstrated in the present review of recent studies for Africa. There are multiple reasons for differences in projections, including uncertainties in greenhouse gas emissions and patterns of climate change; assumptions on future management, aggregation, and spatial extent; and methodological differences. Still, all projections agree that climate change poses a significant risk to African agriculture. Most projections also see the possibility of increasing agricultural production under climate change, especially if suitable adaptation measures are assumed. Climate change is not the only projected pressure on African agriculture, which struggles to meet demand today and may need to feed an additional one billion individuals by 2050. Development strategies are urgently needed, but they will need to consider future climate change and its inherent uncertainties. Science needs to show how existing synergies between climate change adaptation and development can be exploited.
Keywords: Africa/epidemiology; *Climate Change/economics; Crops, Agricultural/economics/*growth & development; Diet/adverse effects/economics; Forecasting; *Global Health/economics/trends; Humans; Malnutrition/economics/epidemiology/prevention & control; *Models, Theoretical; Risk; Soil/chemistry; Water Resources/economics
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Morales, I., Diaz, B. M., Hermoso De Mendoza, A., Nebreda, M., & Fereres, A. (2013). The Development of an Economic Threshold for Nasonovia ribisnigri (Hemiptera: Aphididae) on Lettuce in Central Spain. J. Econ. Entomol., 106(2), 891–898.
Abstract: This study reports economic thresholds for the lettuce aphid Nasonovia ribisnigri (Mosley), based exclusively on cosmetic damage, that is, presence or absence of aphids at harvest time. Field trials were conducted in La Poveda Experimental Farm, Madrid (Spain) during autumn (2004 and 2005) and spring (2005 and 2006). Plants were arranged in plots and just before the formation of lettuce hearts they were infested with different densities of N. ribisnigri. Two days later, half of each plot was treated with tau-fluvalinate (Klartan24AF) and the other half remained as an untreated control. Economic thresholds were obtained from nonlinear regressions calculated between the percentage of commercial plants at the end of the crop cycle for both, treated and untreated semiplots, and the different initial densities of N. ribisnigri per plant. Two criteria were used to consider a commercial lettuce plant: a conservative estimate (0 aphids/plant) and a lax one (< 5 aphids/plant). Thus, an economic threshold was established for each season and criterium. The economic thresholds that were obtained with the most and least conservative criteria were in spring 0.06 and 0.12 aphids per plant, and in autumn 0.07 and 0.13 aphids per plant, respectively. These results show that to avoid cosmetic damage, insecticide sprays are required when a very low aphid density is detected in lettuce seedlings soon after transplant.
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Mansouri, M., Dumont, B., & Destain, M. - F. (2013). Modeling and prediction of nonlinear environmental system using Bayesian methods. Computers and Electronics in Agriculture, 92, 16–31.
Abstract: An environmental dynamic system is usually modeled as a nonlinear system described by a set of nonlinear ODEs. A central challenge in computational modeling of environmental systems is the determination of the model parameters. In these cases, estimating these variables or parameters from other easily obtained measurements can be extremely useful. This work addresses the problem of monitoring and modeling a leaf area index and soil moisture model (LSM) using state estimation. The performances of various conventional and state-of-the-art state estimation techniques are compared when they are utilized to achieve this objective. These techniques include the extended Kalman filter (EKF), particle filter (PF), and the more recently developed technique variational filter (VF). Specifically, two comparative studies are performed. In the first comparative study, the state variables (the leaf-area index LAI, the volumetric water content of the soil layer 1, HUR1 and the volumetric water content of the soil layer 2, HUR2) are estimated from noisy measurements of these variables, and the various estimation techniques are compared by computing the estimation root mean square error (RMSE) with respect to the noise-free data. In the second comparative study, the state variables as well as the model parameters are simultaneously estimated. In this case, in addition to comparing the performances of the various state estimation techniques, the effect of number of estimated model parameters on the accuracy and convergence of these techniques are also assessed. The results of both comparative studies show that the PF provides a higher accuracy than the EKF, which is due to the limited ability of the EKF to handle highly nonlinear processes. The results also show that the VF provides a significant improvement over the PF because, unlike the PF which depends on the choice of sampling distribution used to estimate the posterior distribution, the VF yields an optimum choice of the sampling distribution, which also accounts for the observed data. The results of the second comparative study show that, for all techniques, estimating more model parameters affects the estimation accuracy as well as the convergence of the estimated states and parameters. However, the VF can still provide both convergence as well as accuracy related advantages over other estimation methods. (C) 2013 Elsevier B.V. All rights reserved.
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Lindeskog, M., Arneth, A., Bondeau, A., Waha, K., Seaquist, J., Olin, S., et al. (2013). Implications of accounting for land use in simulations of ecosystem carbon cycling in Africa. Earth System Dynamics, 4(2), 385–407.
Abstract: Dynamic global vegetation models (DGVMs) are important tools for modelling impacts of global change on ecosystem services. However, most models do not take full account of human land management and land use and land cover changes (LULCCs). We integrated croplands and pasture and their management and natural vegetation recovery and succession following cropland abandonment into the LPJ-GUESS DGVM. The revised model was applied to Africa as a case study to investigate the implications of accounting for land use on net ecosystem carbon balance (NECB) and the skill of the model in describing agricultural production and reproducing trends and patterns in vegetation structure and function. The seasonality of modelled monthly fraction of absorbed photosynthetically active radiation (FPAR) was shown to agree well with satellite-inferred normalised difference vegetation index (NDVI). In regions with a large proportion of cropland, the managed land addition improved the FPAR vs. NDVI fit significantly. Modelled 1991-1995 average yields for the seven most important African crops, representing potential optimal yields limited only by climate forcings, were generally higher than reported FAO yields by a factor of 2-6, similar to previous yield gap estimates. Modelled inter-annual yield variations during 1971-2005 generally agreed well with FAO statistics, especially in regions with pronounced climate seasonality. Modelled land-atmosphere carbon fluxes for Africa associated with land use change (0.07 PgC yr(-1) release to the atmosphere for the 1980s) agreed well with previous estimates. Cropland management options (residue removal, grass as cover crop) were shown to be important to the land-atmosphere carbon flux for the 20th century.
Keywords: global vegetation model; sub-saharan africa; climate-change; yield gaps; co2; balance; dynamics; atmosphere; cover; variability
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Jing, Q., Bélanger, G., Baron, V., Bonesmo, H., & Virkajärvi, P. (2013). Simulating the Nutritive Value of Timothy Summer Regrowth. Agronomy Journal, 105(3), 563.
Abstract: The process-based grass model, CATIMO, simulates the spring growth and nutritive value of timothy (Phleum pratense L.), a forage species widely grown in Scandinavia and Canada, but the nutritive value of the summer regrowth has never been simulated. Our objective was to improve CATIMO for simulating the N concentration, neutral detergent fiber (NDF), in vitro digestibility of NDF (dNDF), and in vitro true digestibility of dry matter (IVTD) of summer regrowth. Daily changes in summer regrowth nutritive value were simulated by modifying key crop parameters that differed from spring growth. More specifically, the partitioning fraction to leaf blades was increased to increase the leaf-to-weight ratio, and daily changes in NDF and dNDF of leaf blades and stems were reduced. The modified CATIMO model was evaluated with data from four independent experiments in eastern and western Canada and Finland. The model performed better for eastern Canada than for the other locations, but the nutritive value attributes of the summer regrowth across locations (range of normalized RMSE = 8-25%, slope < 0.17, R-2 < 0.10) were not simulated as well as those of the spring growth (range of normalized RMSE = 4-16%, 0.85 < slope < 1.07, R-2 > 0.61). These modeling results highlight knowledge gaps in timothy summer regrowth and prospective research directions: improved knowledge of factors controlling the nutritive value of the timothy summer regrowth and experimental measurements of leaf-to-weight ratio and of the nutritive value of leaves and stems.
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