Below, T. B., Mutabazi, K. D., Kirschke, D., Franke, C., Sieber, S., Siebert, R., et al. (2012). Can farmers’ adaptation to climate change be explained by socio-economic household-level variables. Glob. Environ. Change, 22(1), 223–235.
Abstract: A better understanding of processes that shape farmers’ adaptation to climate change is critical to identify vulnerable entities and to develop well-targeted adaptation policies. However, it is currently poorly understood what determines farmers’ adaptation and how to measure it. In this study, we develop an activity-based adaptation index (AAI) and explore the relationship between socioeconomic variables and farmers’ adaptation behavior by means of an explanatory factor analysis and a multiple linear regression model using latent variables. The model was tested in six villages situated in two administrative wards in the Morogoro region of Tanzania. The Mlali ward represents a system of relatively high agricultural potential, whereas the Gairo ward represents a system of low agricultural potential. A household survey, a rapid rural appraisal and, a stakeholder workshop were used for data collection. The data were analyzed using factor analysis, multiple linear regression, descriptive statistical methods and qualitative content analysis. The empirical results are discussed in the context of theoretical concepts of adaptation and the sustainable livelihood approach. We found that public investment in rural infrastructure, in the availability and technically efficient use of inputs, in a good education system that provides equal chances for women, and in the strengthening of social capital, agricultural extension and, microcredit services are the best means of improving the adaptation of the farmers from the six villages in Gairo and Mlali. We conclude that the newly developed AAI is a simple but promising way to capture the complexity of adaptation processes that addresses a number of shortcomings of previous index studies.
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Rusu, T., Coste, C. L., Moraru, P. I., Szajdak, L. W., Pop, A. I., & Duda, B. M. (2017). Impact of climate change on agro-climatic indicators and agricultural lands in the Transylvanian Plain between 2008-2014. Carpathian Journal of Earth and Environmental Sciences, 12(1), 23–34.
Abstract: Integrated conservation and management of agricultural areas affected by the current global warming represents a priority at international level following the implementation of the principles of sustainable agriculture and adaptation measures. Transylvanian Plain (TP), with an area of 395,616 ha is of great agricultural importance for Romania, but with an afforestation degree of only 6.8% and numerous degradation phenomena of farmland, it has the lowest degree of sustainability to climate change. Monitoring of agro-climatic indicators and their evolution in between 2008-2014 and the analysis of the obtained data underlie the technological development of recommendations tailored to current favorable conditions for the main crops. Results obtained show that: the thermal regime of the soils in TP is of mesic type and the hydric regime is ustic; multiannual average of temperature in soil at 10 cm depth is 11.40ºC, respectively at 50 cm depth is 10.24ºC; the average yearly air temperature is 11.17ºC; multiannual average of soil moisture is 0.227 m3/m3; Multiannual average value of precipitation is 466.52 mm. During the studied period, compared with data series available (1961-1990; 1901-2000), clear decrease of the average quantities of rainfall especially during critical periods for crops, and increases in average temperatures for the entire year can be noticed. Between June and August the highest temperature difference were recorded, differences of +3.09°C to +3.65°C. There is an increase phenomenon of drought and heat; determined indicators show that most values, 61.11%, are commensurate with a semiarid climate. Aggression peaks are in February-April, July, and October-November, and for the whole period, in 19.43% of the cases are favorable and very favorable conditions for triggering erosion. Recommended agro-technical measures to limit and counteract the effects of drought, as a climatic phenomenon with major risk to agriculture in TP, refer to: i) use of a biological material resistant to water stress and heat; ii) use of management practices favorable for accumulation of, conservation and the efficient use of water from rainfall; iii) operating a system of conservation agriculture based on soil protection and desertification avoidance.
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Foyer, C. H., Siddique, K. H. M., Tai, A. P. K., Anders, S., Fodor, N., Wong, F. - L., et al. (2019). Modelling predicts that soybean is poised to dominate crop production across Africa. Plant Cell Environ., 42(1), 373–385.
Abstract: The superior agronomic and human nutritional properties of grain legumes (pulses) make them an ideal foundation for future sustainable agriculture. Legume-based farming is particularly important in Africa, where small-scale agricultural systems dominate the food production landscape. Legumes provide an inexpensive source of protein and nutrients to African households as well as natural fertilization for the soil. Although the consumption of traditionally grown legumes has started to decline, the production of soybeans (Glycine max Merr.) is spreading fast, especially across southern Africa. Predictions of future land-use allocation and production show that the soybean is poised to dominate future production across Africa. Land use models project an expansion of harvest area, whereas crop models project possible yield increases. Moreover, a seed change in farming strategy is underway. This is being driven largely by the combined cash crop value of products such as oils and the high nutritional benefits of soybean as an animal feed. Intensification of soybean production has the potential to reduce the dependence of Africa on soybean imports. However, a successful “soybean bonanza” across Africa necessitates an intensive research, development, extension, and policy agenda to ensure that soybean genetic improvements and production technology meet future demands for sustainable production.
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Refsgaard, J. C., Madsen, H., Andréassian, V., Arnbjerg-Nielsen, K., Davidson, T. A., Drews, M., et al. (2014). A framework for testing the ability of models to project climate change and its impacts. Clim. Change, 122(1-2), 271–282.
Abstract: Models used for climate change impact projections are typically not tested for simulation beyond current climate conditions. Since we have no data truly reflecting future conditions, a key challenge in this respect is to rigorously test models using proxies of future conditions. This paper presents a validation framework and guiding principles applicable across earth science disciplines for testing the capability of models to project future climate change and its impacts. Model test schemes comprising split-sample tests, differential split-sample tests and proxy site tests are discussed in relation to their application for projections by use of single models, ensemble modelling and space-time-substitution and in relation to use of different data from historical time series, paleo data and controlled experiments. We recommend that differential-split sample tests should be performed with best available proxy data in order to build further confidence in model projections.
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Dono, G., Cortignani, R., Doro, L., Giraldo, L., Ledda, L., Pasqui, M., et al. (2013). An integrated assessment of the impacts of changing climate variability on agricultural productivity and profitability in an irrigated Mediterranean catchment. Water Resource Manage., 27(10), 3607–3622.
Abstract: Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ETN), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ETN may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy.
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