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Author Below, T.B.; Mutabazi, K.D.; Kirschke, D.; Franke, C.; Sieber, S.; Siebert, R.; Tscherning, K.
Title Can farmers’ adaptation to climate change be explained by socio-economic household-level variables Type Journal Article
Year 2012 Publication Global Environmental Change Abbreviated Journal Glob. Environ. Change
Volume 22 Issue 1 Pages 223-235
Keywords (up) Sub-Saharan Africa; Tanzania; Adaptive capacity; Index; Vulnerability; Adaptation; adaptive capacity; environmental-change; south-africa; vulnerability; variability; resilience; tanzania; framework; drought; policy
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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Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0959-3780 ISBN Medium Article
Area Expedition Conference
Notes TradeM Approved no
Call Number MA @ admin @ Serial 4467
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Author Montesino-San Martín, M.; Olesen, J.E.; Porter, J.R.
Title Can crop-climate models be accurate and precise? A case study for wheat production in Denmark Type Journal Article
Year 2015 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 202 Issue Pages 51-60
Keywords (up) Uncertainty; Model intercomparison; Bayesian approach; Climate change; Wheat; Denmark; uncertainty analysis; simulation-models; bayesian-approach; change; impact; yields; variability; projections; scale; calibration; framework
Abstract Crop models, used to make projections of climate change impacts, differ greatly in structural detail. Complexity of model structure has generic effects on uncertainty and error propagation in climate change impact assessments. We applied Bayesian calibration to three distinctly different empirical and mechanistic wheat models to assess how differences in the extent of process understanding in models affects uncertainties in projected impact. Predictive power of the models was tested via both accuracy (bias) and precision (or tightness of grouping) of yield projections for extrapolated weather conditions. Yields predicted by the mechanistic model were generally more accurate than the empirical models for extrapolated conditions. This trend does not hold for all extrapolations; mechanistic and empirical models responded differently due to their sensitivities to distinct weather features. However, higher accuracy comes at the cost of precision of the mechanistic model to embrace all observations within given boundaries. The approaches showed complementarity in sensitivity to weather variables and in accuracy for different extrapolation domains. Their differences in model precision and accuracy make them suitable for generic model ensembles for near-term agricultural impact assessments of climate change.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0168-1923 ISBN Medium Article
Area Expedition Conference
Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4572
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