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Dryad

A catastrophic tropical drought kills hydraulically vulnerable tree species

Cite this dataset

Powers, Jennifer et al. (2020). A catastrophic tropical drought kills hydraulically vulnerable tree species [Dataset]. Dryad. https://doi.org/10.5061/dryad.2rbnzs7jp

Abstract

Drought-related tree mortality is now a widespread phenomenon predicted to increase in magnitude with climate change. However, the patterns of which species and trees are most vulnerable to drought, and the underlying mechanisms have remained elusive, in part due to the lack of relevant data and difficulty of predicting the location of catastrophic drought years in advance. We used long‐term demographic records and extensive databases of functional traits and distribution patterns to understand the responses of 20 to 53 species to an extreme drought in a seasonally dry tropical forest in Costa Rica, which occurred during the 2015 El Niño Southern Oscillation event. Overall, species-specific mortality rates during the drought ranged from 0% to 34%, and varied little as a function of tree size. By contrast, hydraulic safety margins correlated well with probability of mortality among species, while morphological or leaf economics spectrum traits did not. This firmly suggests hydraulic traits as targets for future research.

Methods

The dataset contains annual observations of tree mortality in different 18 plots, expanded sampling for mortality during 2015, and datasets of plant functional and hydraulic traits.  Please refer to the publication for exact methods.  All data come from Guanacaste, Costa Rica.

Usage notes

All data and associated R scripts are contained in the files. The R scripts refer to the three main questions asked in the associated publication.

Funding

National Science Foundation, Award: CAREER grant DEB 1053237

National Science Foundation, Award: PRFB 1711366

National Science Foundation, Award: CRN3025

Instituto Tecnológico de Costa Rica

Australian Research Council, Award: DP170100761

Consejo Nacional de Humanidades, Ciencias y Tecnologías

United States Department of Energy, Award: DESC0014363