Smallholder Knowledge of Local Climate Conditions Predicts Positive On-Farm Outcomes

  • Jonathan Salerno
  • , Karen Bailey
  • , Jeremy Diem
  • , Bronwen Konecky
  • , Ryan Bridges
  • , Shamilah Namusisi
  • , Robert Bitariho
  • , Michael Palace
  • , Joel Hartter

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

People’s observations of climate change and its impacts, mediated by cultures and capacities, shape adaptive responses. Adaptation is critical in regions of rainfed smallholder agriculture where changing rainfall patterns have disproportionate impacts on livelihoods, yet scientific climate data to inform responses are often sparse. Despite calls for better integration of local knowledge into adaptation frameworks, there is a lack of empirical evidence linking both small-holder climate observations and scientific data to on-farm outcomes. We combine smallholder observations of past seasonal rainfall timing with satellite-based rainfall estimates in Uganda to explore whether farmers’ ability to track climate patterns is associated with higher crop yields. We show that high-fidelity tracking, or alignment of farmer recall with recent rainfall patterns, predicts higher yields in the present year, suggesting that farmers may translate their cumulative record of environmental knowledge into productive on-farm decisions, such as crop selection and timing of planting. However, tracking of less-recent rainfall (i.e., 1–2 decades in the past) does not predict higher yields in the present, while climate data indicate significant trends over this period toward warmer and wetter seasons. Our findings demonstrate the value of small-holder knowledge systems in filling information gaps in climate science while suggesting ways to improve adaptive capacity to climate change.

Original languageEnglish
Pages (from-to)671-680
Number of pages10
JournalWeather, Climate, and Society
Volume14
Issue number3
DOIs
StatePublished - Jul 2022

Keywords

  • Adaptation
  • Africa
  • Agriculture
  • Bayesian methods
  • Climate services
  • Climate variability
  • Cloud tracking/cloud motion winds
  • Decision making
  • Indigenous knowledge
  • Interannual variability
  • Intraseasonal variability
  • Precipitation
  • Satellite observations
  • Seasonal forecasting

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