Publication
 

Liana abundance and diversity increase with rainfall seasonality along a precipitation gradient in Panama

In tropical regions, rainfall gradients often explain the abundance and distribution of plant species. For example, many tree and liana species adapted to seasonal drought are more abundant and diverse in seasonally‐dry forests, characterized by long periods of seasonal water deficit. Mean annual precipitation (MAP) is commonly used to explain plant distributions across climate gradients. However, the relationship between MAP and plant distribution is often weak, raising the question of whether other seasonal precipitation patterns better explain plant distributions in seasonally‐dry forests. In this study, we examine the relationship between liana abundance and multiple metrics of seasonal and annual rainfall distribution to test the hypothesis that liana density and diversity increase with increasing seasonal drought along a rainfall gradient across the isthmus of Panama. We found that a normalized seasonality index, which combines MAP and the variability of monthly rainfall throughout the year, was a significant predictor of both liana density and species richness, whereas MAP, rainfall seasonality and the mean dry season precipitation (MDP) were far weaker predictors. The strong response of lianas to the normalized seasonality index indicates that, in addition to the total annual amount of rainfall, how rainfall is distributed throughout the year is an important determinant of the hydrological conditions that favor liana proliferation. Our findings imply that changes in annual rainfall and rainfall seasonality will determine the future distribution and abundance of lianas. Models that aim to predict future plant diversity, distribution, and abundance may need to move beyond MAP to a more detailed understanding of rainfall variability at sub‐annual timescales.

Authors: 
Anthony J. Parolari, Kassandra Paul, Aaron Griffing, Richard Condit, Rolando Pérez, Salomón Aguilar, & Stefan A. Schnitzer
Journal: 
Ecography
Year: 
2019
Pages: 
1-9
DOI: 
10.1111/ecog.04678