Using impact response surfaces to analyse the likelihood of impacts on crop yield under probabilistic climate change

Conventional methods of modelling impacts of future climate change on crop yields often rely on a limited selection of projections for representing uncertainties in future climate. However, large ensembles of climate projections offer an opportunity to estimate yield responses probabilistically. This study demonstrates an approach to probabilistic yield estimation using impact response surfaces (IRSs). These are constructed from a set of sensitivity simulations that explore yield responses to a wide range of changes in temperature and precipitation. Options for adaptation and different levels of future atmospheric carbon dioxide concentration [CO2] defined by representative concentration pathways (RCP4.5 and RCP8.5) were also considered. Model-based IRSs were combined with probabilistic climate projections to estimate impact likelihoods for yields of spring barley (Hordeum vulgare L.) in Finland during the 21st century. Probabilistic projections of climate for the same RCPs were overlaid on IRSs for corresponding [CO2] levels throughout the century and likelihoods of yield shortfall calculated with respect to a threshold mean yield for the baseline (1981–2010). Results suggest that cultivars combining short pre- and long post-anthesis phases together with earlier sowing dates produce the highest yields and smallest likelihoods of yield shortfall under future scenarios. Higher [CO2] levels generally compensate for yield losses due to warming under the RCPs. Yet, this does not happen fully under the more moderate warming of RCP4.5 with a weaker rise in [CO2], where there is a chance of yield shortfall throughout the century. Under the stronger warming but more rapid [CO2] increase of RCP8.5, the likelihood of yield shortfall drops to zero from mid-century onwards. Whilst the incremental IRS-based approach simplifies the temporal and cross-variable complexities of projected climate, it was found to offer a close approximation of evolving future likelihoods of yield impacts in comparison to a more conventional scenario-based approach. The IRS approach is scenario-neutral and existing plots can be used in combination with any new scenario that falls within the sensitivity range without the need to perform new runs with the impact model. A single crop model is used for demonstration, but an ensemble IRS approach could additionally capture impact model uncertainties.peerReviewe

What determines a productive winter bean-wheat genotype combination for intercropping in central Germany?

genotypes. Our study evaluates the performance of three winter wheat cultivars and eight winter faba bean genotypes (experimental inbred lines) sown as replacement row intercrops with sole cropping comparisons. Detailed agronomic, physiological and soil-based measurements were taken over three consecutive autumn-sown seasons at two sites (a marginal versus a fertile soil) in central Germany. This study aimed to contribute to our understanding of key traits required to achieve highly complementary and well-performing intercrops. Faba bean plus wheat intercrops yielded higher than sole crop equivalents at both sites, but more so at the marginal site (34 % > 12 %). High intercrop yields were associated with high wheat component yields. Such stands included faba bean genotypes that exhibited low leaf area index (LAI) values and low plant height. Tall and large faba beans i.e. with high vegetative biomass led to excessive lodging, both as a sole crop and when intercropped. To some extent, this concealed effects of faba bean genotype trait variation that would have otherwise been visible had lodging not occurred. The expression of these traits was heavily influenced by variation in environmental conditions. At the less fertile site, even tall intercropped faba beans showed relatively lower vegetative biomass, which promoted intercropped wheat and led to superior overyielding values and relative yield total. While site-specific differences are key, German winter faba beans need further genetic improvement to refrain from superfluous biomass growth when water resources are plentiful

Analysis of rainfall variability and trends for better climate risk management in the major agro-ecological zones in Tanzania

Managing climate risk in agriculture requires a proper understanding of climatic conditions, regional and global climatic drivers, as well as major agricultural activities at the particular location of interest. Critical analyses of variability and trends in the historical climatic conditions are crucial in designing and implementing action plans to improve resilience and reduce the risks of exposure to harsh climatic conditions. However, in Tanzania, less is known about the variability and trends in the recent climatological conditions. The current study examined variability and trends in rainfall of major agroecological zones in Tanzania (1o - 12oS, 21o - 41oE) using station data from seven locations i.e. Hombolo, Igeri, Ilonga, Naliendele, Mlingano, Tumbi, and Ukiliguru which had records from 1981 to 2020 and two locations i.e. Dodoma and Tanga having records from 1958 to 2020. The variability in annual rainfall was high in Hombolo and Tanga locations (CV ≥ 28%) and low in Igeri (CV = 16%). The OND season showed the highest variability in rainfall (34% to 61%) as compared to the MAM (26% to 36%) and DJFMA (20% to 31%) seasons. We found increasing and decreasing trends in the number of rainy days in Ukiliguru and Tanga respectively, and a decreasing trend in the MAM rainfall in Mlingano. The trends in other locations were statistically insignificant. We assessed the forecast skills of seasonal rainfall forecasts issued by the Tanzania Meteorological Authority (TMA) and IGAD (Intergovernmental Authority on Development) Climate Prediction and Application Center (ICPAC). We found TMA forecasts had higher skills compared to ICPAC forecasts, however, our assessment was limited to MAM and OND seasons due to the unavailability of seasonal forecasts of the DJFMA season issued by ICPAC. Moreover, we showed that Integration of SCF with SSTa increases the reliability of the SCF to 80% at many locations which present an opportunity for better utilization of the SCF in agricultural decision making and better management of climate risks

Assessment of the relations between crop yield variability and the onset and intensity of the West African Monsoon

Timely information on the onset of rain is essential for effectively adapting to climate variability and increasing the resilience of rain-fed systems. However, defining optimal sowing dates based on the onset of rain has been challenging. We compared and analyzed the West African Monsoon onset according to Raman’s, modified Sivakumar’s, Yamada’s, and Liebmann’s definitions using station data from 13 locations in Senegal from 1981 to 2020. Subsequently, we systematically analyzed the effect of the differently estimated monsoon onsets(WAM-OS) on maize development. To this end, we applied the set of the generated WAM-OS as sowing dates in simulations of maize growth and yields, applying the Agricultural Production Systems sIMulator(APSIM) at 13 locations representing different agroclimatic regions across Senegal. We examined the impact of the sowing dates under variable conditions of soil organic carbon(SOC) and plant available water capacity(PAWC). Our analysis showed statistically significant differences between the WAM-OS dates, rainfall characteristics computed for these, and maize yields simulated using different sowing dates according to the WAM-OS definitions. We found Liebmann’s onset dates were most suitable for both hydrological and agronomic applications since they were characterized by the lowest probabilities of prolonged dry spells after onset, the highest amount of rainfall in the mid-season, and the highest simulated maize yields compared to other onset definitions. Our results highlight the importance of sowing dates and their accurate prediction for improving crop productivity in the study area. We also found SOC and PAWC were important factors that improved maize yields. We recommend improved access to climate information services to help smallholder farmers get timely information that helps them in their sowing decisions and encourage agronomic interventions that improve the SOC level, soil pore volume to retain more water and other soil properties directly(e.g., tillage) and indirectly(suited cropping systems) that contribute to enhancing crop productivity

Analysing urban heat island patterns and simulating potential future changes

Climate change is interpreted as one of the most serious environmental problems for the 21st century. Changes in climate are now generally accepted. However, the rate of change has spatial characteristics and is highly uncertain. The Himalaya is experiencing abrupt change; so vulnerability and adaptation studies have become crucial. This pilot study presents initial findings of the research project entitled ‘Human Ecological Implications of Climate Change in the Himalaya.’ A study of climate change perceptions, vulnerability, and adaptation strategies of farming communities of the cool-wet temperate (Lumle) and the hot-wet sub-tropical (Meghauli) villages in Central Nepal was conducted. The findings are derived from the analysis of temperature and precipitation data of last 40 years, and primary data collected in September 2012. Focus Group Discussions, Key Informant Interviews, and Historical Timeline Calender were applied. The changes perceived by the communities are fairly consistent with the meteorological observations and are challenging the sustainability of social-ecological systems and communities’ livelihoods. Farming communities have adopted some strategies to minimize the vulnerability. But the adopted strategies have produced both negative and positive results. Strategies like flood control, shifting crop calendars, occupational changes and labour migrations have produced positive results in livelihood security. Occupational changes and labour migration have negatively impacted local agro-ecology and agricultural economies. Early-harvesting strategies to reduce losses from hailstorm have reduced the food and fodder security. Lack of irrigation for rice-seedlings is severely affecting the efficacy of shifting the rice-transplantation calendar. Conclusions suggest that while farmers have practiced strategies to better management of farms, livelihood sustainabilities are reaching thresholds due to the changing conditions.Rishikesh Pandey, Douglas K Bardsle

О перспективе извлечения йода из продукта утилизации окислителя ракетного топлива

Crop models are essential tools for assessing the threat of climate change to local and global food production. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degree C of further temperature increase and become more variable over space and time

An ensemble of projections of wheat adaptation to climate change in europe analyzed with impact response surfaces

IRS2 TEAM:Alfredo Rodríguez(1), Ignacio J. Lorite(3), Fulu Tao(4), Nina Pirttioja(5), Stefan Fronzek(5), Taru Palosuo(4), Timothy R. Carter(5), Marco Bindi(2), Jukka G Höhn(4), Kurt Christian Kersebaum(6), Miroslav Trnka(7,8),Holger Hoffmann(9), Piotr Baranowski(10), Samuel Buis(11), Davide Cammarano(12), Yi Chen(13,4), Paola Deligios(14), Petr Hlavinka(7,8), Frantisek Jurecka(7,8), Jaromir Krzyszczak(10), Marcos Lana(6), Julien Minet(15), Manuel Montesino(16), Claas Nendel(6), John Porter(16), Jaime Recio(1), Françoise Ruget(11), Alberto Sanz(1), Zacharias Steinmetz(17,18), Pierre Stratonovitch(19), Iwan Supit(20), Domenico Ventrella(21), Allard de Wit(20) and Reimund P. Rötter(4).An ensemble of projections of wheat adaptation to climate change in europe analyzed with impact response surfaces . International Crop Modelling Symposiu

Fertilization Strategies Based on Climate Information to Enhance Food Security Through Improved Dryland Cereals Production

Rainfall uncertainty and nutrient deficiency affect sorghum production in Sahel. This study aimed at (i) determining the responses (varieties*water*nitrogen) of various West-African sorghum (Sorghum bicolor L. Moench) varieties to the application of fertilizer (NPK and urea) at selected growing stages according to water regime (irrigated or not, different rainfall patterns) and (ii) simulating them to define alternative fertilization strategies. This chapter proposes alternative fertilization strategies in line with rainfall patterns. Split plot experiments with four replications were carried out in two locations (Senegal), with four improved sorghum varieties (Fadda, IS15401, Soumba and 621B). Treatments were T1, no fertilizer; T2 = 150 kg/ha of NPK (15-15-15) at emergence +50 kg/ha of urea (46%) at tillering +50 Kg/ha of urea at stem extension; T3 = half rate of T2 applied at the same stages; T4 = 150 kg/ha of NPK + 50 kg/ha of urea at stem extension +50 kg/ha of urea at heading, and T5 = half rate of T4 applied at the same stages. Plant height, leaf number, grain yield, and biomass were significantly affected by the timing and rate of fertilizers. Grain yield were affected by water*nitrogen and nitrogen*variety interactions. It varied from 2111 to 261 kg/ha at “Nioro du Rip” and from 1670 to 267 kg/ha at “Sinthiou Malème”. CERES-Sorghum model overestimated late fertilizer grain yields. To achieve acceptable grain yield, fertilizers application should be managed regarding weather