Abstract
Shifts in the timing of phenological events in plants and animals are cited as one of the most robust bioindicators of climate change. Much effort has thus been placed on the collection of phenological datasets, the quantification of the rates of phenological shifts and the association of these shifts with recorded meteorological data. These outputs are of value both in tracking the severity of climate change and in facilitating more robust management approaches in forestry and agriculture to changing climatic conditions. However, such an approach requires meteorological and phenological records spanning multiple decades. For communities in the Delta State of Nigeria, small-scale farming communities do not have access to meteorological records, and the dissemination of government issued daily to seasonal forecasts has only taken place in recent years. Their ability to survive inter-annual to inter-decadal climatic variability and longer-term climatic change has thus relied on well-entrenched indigenous knowledge systems (IKS). An analysis of the environmental cues that are used to infer the timing and amount of rainfall by farmers from three communities in the Delta State reveals a reliance on phenological events, including the croaking of frogs, the appearance of red millipedes and the emergence of fresh rubber tree and cassava leaves. These represent the first recorded awareness of phenology within the Delta State of Nigeria, and a potentially valuable source of phenological data. However, the reliance of these indicators is of concern given the rapid phenological shifts occurring in response to climate change.
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Acknowledgements
The authors wish to acknowledge Prof D Simatele for his contribution in supervising EE during his PhD project from which these data were collected. EE was funded by the National Institute for the Humanities and Social Sciences-Council for the Development of Economic and Social Research in Africa (NIHSS-CODESRIA).
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Fitchett, J.M., Ebhuoma, E. Phenological cues intrinsic in indigenous knowledge systems for forecasting seasonal climate in the Delta State of Nigeria. Int J Biometeorol 62, 1115–1119 (2018). https://doi.org/10.1007/s00484-017-1495-x
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DOI: https://doi.org/10.1007/s00484-017-1495-x