Academic literature on the topic 'Agricultural adaptation, climate change, Sahel, climate/crop-growth modelling'

Climate change is a challenging fact influencing diverse sectors in society including the agricultural one, which is heavily dependent on natural resources and climate. In the Mediterranean region, climate change-related increases in air temperature, and in the frequency and intensity of extreme weather events, such as droughts, boost the pressure on the agricultural systems and affect crop yield potential. The growth of the world population implies that production needs to increase in a sustainable manner. Therefore, this study focuses on the maize crop due to its importance for food security and because it is a crop with significant water consumption that occupies a large worldwide area. In order to study climate change impacts on crop production, plant water requirements, and provide farmers guidelines helping them to adapt, it is necessary to simultaneously evaluate a large number of factors. For this reason, modelling tools are normally used to measure the future impact of climate change on crop yield by using historical and future climate data. This review focuses on climate change impacts on maize crop irrigation requirements and compares—by means of critical analysis—existing approaches that allow for the building a set of mitigation and adaptation measures throughout the study of climate.

A comprehensive assessment of the impacts of climate change on agro-ecosystems over this century is developed, up to 2080 and at a global level, albeit with significant regional detail. To this end an integrated ecological–economic modelling framework is employed, encompassing climate scenarios, agro-ecological zoning information, socio-economic drivers, as well as world food trade dynamics. Specifically, global simulations are performed using the FAO/IIASA agro-ecological zone model, in conjunction with IIASAs global food system model, using climate variables from five different general circulation models, under four different socio-economic scenarios from the intergovernmental panel on climate change. First, impacts of different scenarios of climate change on bio-physical soil and crop growth determinants of yield are evaluated on a 5′×5′ latitude/longitude global grid; second, the extent of potential agricultural land and related potential crop production is computed. The detailed bio-physical results are then fed into an economic analysis, to assess how climate impacts may interact with alternative development pathways, and key trends expected over this century for food demand and production, and trade, as well as key composite indices such as risk of hunger and malnutrition, are computed. This modelling approach connects the relevant bio-physical and socio-economic variables within a unified and coherent framework to produce a global assessment of food production and security under climate change. The results from the study suggest that critical impact asymmetries due to both climate and socio-economic structures may deepen current production and consumption gaps between developed and developing world; it is suggested that adaptation of agricultural techniques will be central to limit potential damages under climate change.

AbstractThe impact of climate change on agricultural productivity is difficult to assess. However, determining the possible effects of climate change is an absolute necessity for planning by decision-makers. The aim of the study was the evaluation of the CSM-CROPGRO-Sunflower model of DSSAT4.7 and the assessment of impact of climate change on sunflower yield under future climate projections. For this purpose, a 2-year sunflower field experiment was conducted under semi-arid conditions in the Konya province of Turkey. Rainfed and irrigated treatments were used for model analysis. For the assessment of impact of climate change, three global climate models and two representative concentration pathways, i.e. 4.5 and 8.5 were selected. The evaluation of the model showed that the model was able to simulate yield reasonably well, with normalized root mean square error of 1.3% for the irrigated treatment and 17.7% for the rainfed treatment, a d-index of 0.98 and a modelling efficiency of 0.93 for the overall model performance. For the climate change scenarios, the model predicted that yield will decrease in a range of 2.9–39.6% under rainfed conditions and will increase in a range of 7.4–38.5% under irrigated conditions. Results suggest that temperature increases due to climate change will cause a shortening of plant growth cycles. Projection results also confirmed that increasing temperatures due to climate change will cause an increase in sunflower water requirements in the future. Thus, the results reveal the necessity to apply adequate water management strategies for adaptation to climate change for sunflower production.

This article presents selected flow modeling indices of the Bystra River catchment area (east Poland) obtained using the SWAT model simulations for three regional climate models driven by the EC-EARTH global climate model for 2021–2050 and both RCP4.5 and RCP 8.5 scenarios. The research area was selected due to the large relief of the terrain, the predominance of soils made of loess and the agricultural nature of the Bystra River catchment area, which is very sensitive to climate change, has very valuable soils, and can be used as a test area for modeling land use-based adaptation measures to climate change. The calibration and validation using the SUFI-2 algorithm in the SWAT CUP program was carried out in order to determine the water balance. After obtaining satisfactory results, the SWAT-CUP program simulated the best parameter values for climate change projections. In analyzed climate projections, the monthly mean sums of actual evapotranspiration and potential evapotranspiration will be higher compared to the simulation period of the 2010–2017 model. The exception is the month of June, where actual evapotranspiration in most climate projections is lower compared to the years 2010–2017. The average monthly total runoff for the Bystra River basin will be lower in most of the 2021–2030 climate change projections for most months compared to the reference period. Also, in the 2031–2040 and 2041–2050 periods, the average monthly total runoff will be lower for the RCP 4.5 scenarios (except for one RCP 4.5 scenario in 2031–2040). Additionally, in the case of the RCP 8.5 for the two scenarios in 2041–2050, the average monthly total runoff will be higher compared to the reference years. We determine that the analysis impact of climate change will result in 31 recognized and different small sub-catchments of the Bystra River, which result from higher precipitation and less evapotranspiration for RCP 8.5 in 2041–2050. All of the above changes in the individual components of the water balance may have a negative impact on the vegetation in the coming decades. The temperature increase and the variable amount of precipitation in individual months may lead to an increased number of extreme phenomena. Increased mean monthly sum of actual and potential evapotranspiration, as well as changes in monthly sums of total runoff, may disturb the vegetation in the studied area at every stage of growth. The above components may also influence changes in the amount of water in the soil (especially during the growing season). Counteracting the effects of future climate change requires various adaptation measures.

Eutrophication manifested by massive algal blooms is the most acute problem in many coastal waters and lakes around the world. The main source of phosphorus and nitrogen transport in the region studied, the Baltic Sea basin, is agriculture. Several studies have predicted adverse climate change impact on eutrophication problems. Here we show that in regions with a climate characterized by pronounced winter seasons and snow-melt flow peaks, this may not be the case. Regional Climate Model results were used to drive hydrological and nutrient modelling. Substantial reductions of phosphorus losses and small reductions for nitrogen were predicted. The main factors behind these results were fewer and less pronounced snow-melt occasions, elevated plant uptake of nutrients and increased growth and crop yield. Based on IPCC scenarios, one ‘market driven’ (A2) and one ‘Local Sustainability’ (B2), the impact on nutrient loss of societal development and future policy lines were assessed. Agricultural adaptation to a future climate, market demand and remedial action policies, e.g. more autumn crops and bio-fuel production, gave further reductions in nutrient loss. The results should not be taken as a motive to reduce efforts to minimize eutrophication in these areas, since severe eutrophication may cause irreversible effects in the decades to come.

In the context of climate change, the sowing date and cultivar choice can influence the productivity of sorghum, especially where production is constrained by low soil fertility and early terminal drought across the challenging agro-ecologies of north-eastern Nigeria. Planting within an optimal sowing window to fit the cultivar’s maturity length is critical for maximizing/increasing the crop yield following the appropriate climate-smart management practices. In this study, the APSIM crop model was calibrated and validated to simulate the growth and yield of sorghum cultivars with differing maturing periods sown within varying planting time windows under improved agricultural practices. The model was run to simulate long-term crop performance from 1985 to 2010 to determine the optimal planting windows (PWs) and most suitable cultivars across different agro-ecological zones (AEZs). The performance of the model, validated with the observed farm-level grain yield, was satisfactory across all planting dates and cropping systems. The model predicted a lower mean bias error (MBE), either positive or negative, under the sole cropping system in the July sowing month compared to in the June and August sowing months. The seasonal climate simulations across sites and AEZs suggested increased yields when using adapted sorghum cultivars based on the average grain yield threshold of ≥1500 kgha−1 against the national average of 1160 kgha−1. In the Sudan Savanna (SS), the predicted optimum PWs ranged from 25 May to 30 June for CSR01 and Samsorg-44, while the PWs could be extended to 10 July for ICSV400 and Improved Deko. In the Northern Guinea Savanna (NGS) and Southern Guinea Savanna (SGS), the optimal PWs ranged from 25 May to 10 July for all cultivars except for SK5912, for which predicted optimal PWs ranged from 25 May to 30 June. In the NGS zone, all cultivars were found to be suitable for cultivation with exception of SK5912. Meanwhile, in the SGS zone, the simulated yield below the threshold (1500 kgha−1) could be explained by the sandy soil and the very low soil fertility observed there. It was concluded that farm decisions to plant within the predicted optimal PWs alongside the use of adapted sorghum cultivars would serve as key adaptation strategies for increasing the sorghum productivity in the three AEZs.

AbstractFood security under climate change, several sustainability problems, and ambitious climate targets are considered challenges for agriculture and food sectors in many countries. Since agricultural production and its land use produce appr. 20% of greenhouse gas (GHG) emissions of Finland, reducing agricultural GHG emissions is important for meeting national target of climate neutrality by 2035. Healthier food diets, maintenance of biodiversity, and reduced nutrient leaching from agriculture are also required for a more sustainable food economy. This paper aims to show how agriculture in Finland, traditionally dominated by livestock production, could decrease GHG emissions significantly and simultaneously respond to other sustainability concerns. Our results, based on economic modelling of the agricultural sector, suggest that moderate changes in food diets and land use can reduce GHG emissions of agriculture by more than 40% by 2050 if productivity growth and policy changes support the overall change in the agriculture and food sector. Adaptation to climate change, e.g. more higher crop yields efficient input use, is necessary for productivity growth. Decreased demand for meat and decreased cultivation of feed crops would decrease GHG emissions and free up land for carbon sequestration through afforestation. Whilst healthier food diets imply less livestock and increased imports of protein crops for food, a reasonable volume of livestock production is useful for maintaining food security, grasslands, crop rotations, soil carbon, and biodiversity. We conclude that transition to low carbon and more sustainable agriculture is possible without risking food security at northern latitudes.

Global demand for agricultural products continues to grow. However, efforts to boost productivity exacerbate existing pressures on nature, both on farms and in the wider landscape. There is widespread appreciation of the critical need to achieve balance between biodiversity and human well-being in rural tropical crop production landscapes, that are essential for livelihoods and food security. There is limited empirical evidence of the interrelationships between natural capital, the benefits and costs of nature and its management, and food security in agricultural landscapes. Agroforestry practices are frequently framed as win-win solutions to reconcile the provision of ecosystem services important to farmers (i.e., maintaining soil quality, supporting pollinator, and pest control species) with nature conservation. Yet, underlying trade-offs (including ecosystem disservices linked to pest species or human-wildlife conflicts) and synergies (e.g., impact of ecosystem service provision on human well-being) are seldom analysed together at the landscape scale. Here, we propose a systems model framework to analyse the complex pathways, with which natural capital on and around farms interacts with human well-being, in a spatially explicit manner. To illustrate the potential application of the framework, we apply it to a biodiversity and well-being priority landscape in the Southern Agricultural Growth Corridor of Tanzania, a public-private partnership for increasing production of cash and food crops. Our framework integrates three main dimensions: biodiversity (using tree cover and wildlife as key indicators), food security through crop yield and crop health, and climate change adaptation through microclimate buffering of trees. The system model can be applied to analyse forest-agricultural landscapes as socio-ecological systems that retain the capacity to adapt in the face of change in ways that continue to support human well-being. It is based on metrics and pathways that can be quantified and parameterised, providing a tool for monitoring multiple outcomes from management of forest-agricultural landscapes. This bottom-up approach shifts emphasis from global prioritisation and optimisation modelling frameworks, based on biophysical properties, to local socio-economic contexts relevant in biodiversity-food production interactions across large parts of the rural tropics.

Since the industrial revolution, there has been a continuous increase in atmospheric carbon dioxide (CO2) concentrations to the highest levels in the last 800,000 years, over 400 ppm. This underscores human-induced climate change, and CO2-projections are not promising (Representative Concentration Pathway (RCP) 4.5: 550 ppm of CO2; RCP 8.5: 1000 ppm of CO2 by 2100). Scientists foresee a point of no return in the climate system, where humankind and ecosystems are expected to face unprecedented changes in climate. Populations living in less developed countries are likely to suffer the most severe impacts of climate change (heatwaves, droughts, flooding…). With uncontrollable population growth, high-reliance on climate-sensitive sectors (agriculture), lack of governance, poor educational and health systems, and conflict, a sophisticated time-bomb is developing. The time-bomb will be in the form of populations facing starvation, causing conflict and displacing, even more, the population within and from the Sahel. The Sahel is often portrayed as one of the world’s most vulnerable regions to climate change impacts, which are expected to severely affect Sub-Saharan agriculture and consequently human livelihoods. Many of the crops (maize, sorghum, millet, sugarcane, fonio and tef) grown at lower latitudes, have a C4 photosynthetic pathways which are more efficient in environments with higher solar radiation when compared to C3 crops. Nevertheless, C3 crops have a photosynthetic pathway that benefit more from increasing CO2 concentrations in the atmosphere. This is because the optimal CO2 atmospheric concentrations for enhancing the photosynthetic rate of C3 crops has not yet been reached. Modelling of C4 crops under changing climatic conditions has shown considerable yield losses of main crops (maize, millet and sorghum) within the region and for the coming decades. Trait improvement of C4 crops is time consuming with limited time for action, therefore alternative strategies to adapt to future climate are now imperative. Different agricultural adaptive strategies may be available for the Sahel to face the detrimental impacts of climate change. Hence this research proposes a novel approach: to introduce a resistant to abiotic-stresses-C3-crop in a country suffering from high undernourishment rates, Burkina Faso. Field experimentation with Chenopodium quinoa Willd. has shown that quinoa is a very resilient plant, that can cope with drought-stress conditions (200-400 mm) and withstand the effect of heat-stress (38 °C), besides having low nitrogen nutrient requirements (25 kg N ha-1). Multimodel simulations under different climate scenarios (RCP 4.5 and RCP 8.5), predicting temperature increases of 2 °C to 5 °C, have shown that quinoa is capable of adjusting, with even yield enhancements, to the projected temperatures and CO2 concentrations. Although crop substitution may face social and research challenges, it is a more rapid solution for building climate-resilient communities than crop improvement.