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Cognitive biases about climate variability in smallholder farming systems in Zambia

Cognitive biases about climate variability in smallholder farming systems in Zambia
Cognitive biases about climate variability in smallholder farming systems in Zambia

Given 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.

1948-8327
369-383
Waldman, Kurt B.
aba390f2-8b55-4ba3-af01-79f828061052
Vergopolan, Noemi
3c455209-3f04-4ef3-9687-d637239ec4b4
Attari, Shahzeen Z.
1114b66c-544f-42fd-9e6f-c0286b222a82
Sheffield, Justin
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Estes, Lyndon D.
6301c89d-4567-48ba-9808-8c9dae3fcc99
Caylor, Kelly K.
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Evans, Tom P.
a8c4d73b-075c-485a-bdec-4018b7315e06
Waldman, Kurt B.
aba390f2-8b55-4ba3-af01-79f828061052
Vergopolan, Noemi
3c455209-3f04-4ef3-9687-d637239ec4b4
Attari, Shahzeen Z.
1114b66c-544f-42fd-9e6f-c0286b222a82
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Estes, Lyndon D.
6301c89d-4567-48ba-9808-8c9dae3fcc99
Caylor, Kelly K.
9495817c-5392-47ed-a013-1d02f501aa28
Evans, Tom P.
a8c4d73b-075c-485a-bdec-4018b7315e06

Waldman, Kurt B., Vergopolan, Noemi, Attari, Shahzeen Z., Sheffield, Justin, Estes, Lyndon D., Caylor, Kelly K. and Evans, Tom P. (2019) Cognitive biases about climate variability in smallholder farming systems in Zambia. Weather, Climate and Society, 11 (2), 369-383. (doi:10.1175/WCAS-D-18-0050.1).

Record type: Article

Abstract

Given 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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WCAS-D-18-0050_R1-1_paper_only - Accepted Manuscript
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Accepted/In Press date: 22 January 2019
Published date: April 2019
Additional Information: Funding Information: Funding for this research came from National Science FoundationAwards SES-1360463, BCS-1115009, and BCS-1026776. Our deep gratitude to our colleagues from the Zambian Agricultural Research Institute (ZARI) who helped us with the logistics and data collection for this work. Funding Information: Acknowledgments. Funding for this research came from National Science Foundation Awards SES-1360463, BCS-1115009, and BCS-1026776. Our deep gratitude to our colleagues from the Zambian Agricultural Research Institute (ZARI) who helped us with the logistics and data collection for this work. Publisher Copyright: © 2019 American Meteorological Society. All rights reserved.

Identifiers

Local EPrints ID: 427774
URI: http://eprints.soton.ac.uk/id/eprint/427774
ISSN: 1948-8327
PURE UUID: 39c75ccd-d2d6-485d-b76e-084f8ed4e9bb
ORCID for Justin Sheffield: ORCID iD orcid.org/0000-0003-2400-0630

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Date deposited: 29 Jan 2019 17:30
Last modified: 18 Mar 2024 03:33

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Contributors

Author: Kurt B. Waldman
Author: Noemi Vergopolan
Author: Shahzeen Z. Attari
Author: Lyndon D. Estes
Author: Kelly K. Caylor
Author: Tom P. Evans

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