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Thermal pace-of-life strategies improve phenological predictions in ectotherms.


ABSTRACT: Phenological variability among populations is widespread in nature. A few predictive phenological models integrate intrapopulational variability, but none has ever explored the individual strategies potentially occurring within a population. The "pace-of-life" syndrome accounts for such individual strategies, but has yet to be explored under a phenological context. Here we integrated, for the first time, the slow-fast thermal strategies stemming from the "pace-of-life" into a mechanistic predictive framework. We obtained 4619 phenological observations of an important crop pest in the Bolivian Andes by individually following 840 individuals under five rearing temperatures and across nine life stages. The model calibrated with the observed individual "pace-of-life" strategies showed a higher accuracy in phenological predictions than when accounting for intrapopulational variability alone. We further explored our framework with generated data and suggest that ectotherm species with a high number of life stages and with slow and/or fast individuals should exhibit a greater variance of populational phenology, resulting in a potentially longer time window of interaction with other species. We believe that the "pace-of-life" framework is a promising approach to improve phenological prediction across a wide array of species.

SUBMITTER: Struelens Q 

PROVIDER: S-EPMC6203799 | biostudies-other | 2018 Oct

REPOSITORIES: biostudies-other

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Thermal pace-of-life strategies improve phenological predictions in ectotherms.

Struelens Quentin Q   Rebaudo François F   Quispe Reinaldo R   Dangles Olivier O  

Scientific reports 20181026 1


Phenological variability among populations is widespread in nature. A few predictive phenological models integrate intrapopulational variability, but none has ever explored the individual strategies potentially occurring within a population. The "pace-of-life" syndrome accounts for such individual strategies, but has yet to be explored under a phenological context. Here we integrated, for the first time, the slow-fast thermal strategies stemming from the "pace-of-life" into a mechanistic predict  ...[more]

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