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    Time-varying impact of climate on maize and wheat yields in France since 1900
    (Bristol : IOP Publ., 2020) Ceglar, Andrej; Zampieri, Matteo; Gonzalez-Reviriego, Nube; Ciais, Philippe; Schauberger, Bernhard; Van der Velde, Marijn
    Climate services that can anticipate crop yields can potentially increase the resilience of food security in the face of climate change. These services are based on our understanding of how crop yield anomalies are related to climate anomalies, yet the share of global crop yield variability explained directly by climate factors is largely variable between regions. In Europe, France has been a major crop producer since the beginning of the 20th Century. Process based and statistical approaches to model crop yields driven by observed climate have proven highly challenging in France. This is especially due to a high regional diversity in climate but also due to environmental and agro-management factors. An additional level of uncertainty is introduced if these models are driven by seasonal-to-decadal surface climate predictions due to their low performances before the harvesting months of both wheat and maize in western Europe. On the other hand, large scale circulation patterns can possibly be better predicted than the regional surface climate, which offers the opportunity to rely on large scale circulation patterns as an alternative to local climate variables. This method assumes a certain degree of stationarity in the relationships between large scale patterns, surface climate variables, and crop yield anomalies. However, such an assumption was never tested, because of the lack of suitable long-term data. This study uses a unique dataset of subnational crop yields in France covering more than a century. By calibrating and comparing statistical models linking large scale circulation patterns and observed surface climate variables to crop yield anomalies, we can demonstrate that the relationship between large scale patterns and surface variables relevant for crop yields is not stationary. Therefore, large scale circulation pattern based crop yield forecasting methods can be adopted for seasonal predictions provided that regression parameters are constantly updated. However, the statistical crop yield models based on large-scale circulation patterns are not suitable for decadal predictions or climate change impact assessments at even longer time-scales.
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    Energy balance, greenhouse gas emissions, and profitability of thermobarical pretreatment of cattle waste in anaerobic digestion
    (Amsterdam : Elsevier, 2015) Budde, Jörn; Prochnow, Annette; Plöchl, Matthias; Suárez Quiñones, Teresa; Heiermann, Monika
    In this study modeled full scale application of thermobarical hydrolysis of less degradable feedstock for biomethanation was assessed in terms of energy balance, greenhouse gas emissions, and economy. Data were provided whether the substitution of maize silage as feedstock for biogas production by pretreated cattle wastes is beneficial in full-scale application or not. A model device for thermobarical treatment has been suggested for and theoretically integrated in a biogas plant. The assessment considered the replacement of maize silage as feedstock with liquid and/or solid cattle waste (feces, litter, and feed residues from animal husbandry of high-performance dairy cattle, dry cows, and heifers). The integration of thermobarical pretreatment is beneficial for raw material with high contents of organic dry matter and ligno-cellulose: Solid cattle waste revealed very short payback times, e.g. 9 months for energy, 3 months for greenhouse gases, and 3 years 3 months for economic amortization, whereas, in contrast, liquid cattle waste did not perform positive replacement effects in this analysis.
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    Can Tanzania’s adaptation measures prevent future maize yield decline? A simulation study from Singida region
    (Berlin ; Heidelberg ; New York : Springer, 2021) Volk, Johanna; Gornott, Christoph; Sieber, Stefan; Lana, Marcos Alberto
    Cereal crop production in sub-Saharan Africa has not achieved the much-needed increase in yields to foster economic development and food security. Maize yields in the region’s semi-arid agroecosystems are constrained by highly variable rainfall, which may be worsened by climate change. Thus, the Tanzanian government has prioritized agriculture as an adaptation sector in its intended nationally determined contribution, and crop management adjustments as a key investment area in its Agricultural Sector Development Programme. In this study, we investigated how future changes in maize yields under different climate scenarios can be countered by regional adjusted crop management and cultivar adaptation strategies. A crop model was used to simulate maize yields in the Singida region of Tanzania for the baseline period 1980–2012 and under three future climate projections for 2020–2060 and 2061–2099. Adaptation strategies to improve yields were full irrigation, deficit irrigation, mulch and nitrogen addition and another cultivar. According to our model results, increase in temperature is the main driver of future maize yield decline. Increased respiration and phenological development were associated with lower maize yields of 16% in 2020–2060 and 20% in 2061–2099 compared to the 1980–2012 baseline. Surprisingly, none of the management strategies significantly improved yields; however, a different maize variety that was tested as an alternative coping strategy performed better. This study suggests that investment in accessibility of improved varieties and investigation of maize traits that have the potential to perform well in a warmer future are better suited for sustaining maize production in the semi-arid region than adjustments in crop management.