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Climatic drivers of dipterocarp mass-flowering in South-East Asia

Published online by Cambridge University Press:  14 May 2019

Mariya Chechina  and
Andreas Hamann
Mariya Chechina*
Affiliation:
Department of Renewable Resources, University of Alberta, 751 General Services Building, Edmonton, AB, T6G 2H1, Canada
Andreas Hamann
Affiliation:
Department of Renewable Resources, University of Alberta, 751 General Services Building, Edmonton, AB, T6G 2H1, Canada
*
*Email: [email protected]
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Abstract

Dipterocarpaceae, a dominant family of trees in South-East Asian tropical forests, are remarkable in that they exhibit supra-annual mass-flowering events. The flowering patterns are related to the El Niño Southern Oscillation, but the mechanism that precipitates mass-flowering is still debated. Here, we test if a cumulative-trigger model that tracks resource availability, specifically light, may better explain dipterocarp phenology than a direct-environmental-trigger mechanism. Using 11 flowering time series with an average length of 29 y and variety of candidate predictor variables (precipitation, cloud cover, minimum temperature and El Niño indices) we could not find a plausible direct-environmental-trigger (median AUCs across regions from 0.53 to 0.57 indicating near random predictions). The cumulative-trigger model based on El Niño indices showed better predictive results (AUC 0.67), which could further be improved by resetting the resource at known flowering events (AUC 0.76). Additional support for a cumulative-trigger model comes from the observation that regional differences in the time of year of peak flowering correspond to where El Niño effects are strongest. We conclude that cumulative resource tracking is an evolutionary plausible trigger mechanism that has other primary evolutionary advantages, such as predator satiation.

Keywords

Dipterocarpaceaedipterocarpsgeneral floweringmass-floweringmastingphenologyresource tracking
Type
Research Article
Information
Journal of Tropical Ecology , Volume 35 , Issue 3 , May 2019 , pp. 108 - 117
Copyright
© Cambridge University Press 2019 

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