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    Cognitive Biases about Climate Variability in Smallholder Farming Systems in Zambia

    Source: Weather, Climate, and Society:;2019:;volume 011:;issue 002::page 369
    Author:
    Waldman, Kurt B.
    ,
    Vergopolan, Noemi
    ,
    Attari, Shahzeen Z.
    ,
    Sheffield, Justin
    ,
    Estes, Lyndon D.
    ,
    Caylor, Kelly K.
    ,
    Evans, Tom P.
    DOI: 10.1175/WCAS-D-18-0050.1
    Publisher: American Meteorological Society
    Abstract: AbstractGiven the varying manifestations of climate change over time and the influence of climate perceptions on adaptation, it is important to understand whether farmer perceptions match patterns of environmental change from observational data. We use a combination of social and environmental data to understand farmer perceptions related to rainy season onset. Household surveys were conducted with 1171 farmers across Zambia at the end of the 2015/16 growing season eliciting their perceptions of historic changes in rainy season onset and their heuristics about when rain onset occurs. We compare farmers? perceptions with satellite-gauge-derived rainfall data from the Climate Hazards Group Infrared Precipitation with Station dataset and hyper-resolution soil moisture estimates from the HydroBlocks land surface model. We find evidence of a cognitive bias, where farmers perceive the rains to be arriving later, although the physical data do not wholly support this. We also find that farmers? heuristics about rainy season onset influence maize planting dates, a key determinant of maize yield and food security in sub-Saharan Africa. Our findings suggest that policy makers should focus more on current climate variability than future climate change.
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      Cognitive Biases about Climate Variability in Smallholder Farming Systems in Zambia

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4263240
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    • Weather, Climate, and Society

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    contributor authorWaldman, Kurt B.
    contributor authorVergopolan, Noemi
    contributor authorAttari, Shahzeen Z.
    contributor authorSheffield, Justin
    contributor authorEstes, Lyndon D.
    contributor authorCaylor, Kelly K.
    contributor authorEvans, Tom P.
    date accessioned2019-10-05T06:43:47Z
    date available2019-10-05T06:43:47Z
    date copyright1/29/2019 12:00:00 AM
    date issued2019
    identifier otherWCAS-D-18-0050.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4263240
    description abstractAbstractGiven the varying manifestations of climate change over time and the influence of climate perceptions on adaptation, it is important to understand whether farmer perceptions match patterns of environmental change from observational data. We use a combination of social and environmental data to understand farmer perceptions related to rainy season onset. Household surveys were conducted with 1171 farmers across Zambia at the end of the 2015/16 growing season eliciting their perceptions of historic changes in rainy season onset and their heuristics about when rain onset occurs. We compare farmers? perceptions with satellite-gauge-derived rainfall data from the Climate Hazards Group Infrared Precipitation with Station dataset and hyper-resolution soil moisture estimates from the HydroBlocks land surface model. We find evidence of a cognitive bias, where farmers perceive the rains to be arriving later, although the physical data do not wholly support this. We also find that farmers? heuristics about rainy season onset influence maize planting dates, a key determinant of maize yield and food security in sub-Saharan Africa. Our findings suggest that policy makers should focus more on current climate variability than future climate change.
    publisherAmerican Meteorological Society
    titleCognitive Biases about Climate Variability in Smallholder Farming Systems in Zambia
    typeJournal Paper
    journal volume11
    journal issue2
    journal titleWeather, Climate, and Society
    identifier doi10.1175/WCAS-D-18-0050.1
    journal fristpage369
    journal lastpage383
    treeWeather, Climate, and Society:;2019:;volume 011:;issue 002
    contenttypeFulltext
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