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Are lianas more drought tolerant than trees? A test for the role of hydraulic architecture and other leaf and stem traits

Journal Article

Van der Sande M; Poorter L; Schnitzer SA; Schnitzer SA

Markesteijn L

2013

Oecologia

172

961-973

Lianas are an important component of Neotropical forests where evidence suggests that they are increasing in abundance and biomass. Lianas are especially abundant in seasonally dry tropical forests and as such it has been hypothesized that they are better adapted to drought or that they are at an advantage under the higher light conditions in these forests. However the physiological and morphological characteristics that allow lianas to capitalize more on seasonal forest conditions compared to trees are poorly understood. Here we evaluate how saplings of 21 tree and liana species from a seasonal tropical forest in Panama differ in cavitation resistance (P (50)) and maximum hydraulic conductivity (K (h)) and how saplings of 24 tree and liana species differ in four photosynthetic leaf traits (e.g. maximum assimilation and stomatal conductance) and six morphological leaf and stem traits (e.g. wood density maximum vessel length and specific leaf area). At the sapling stage lianas had a lower cavitation resistance than trees implying lower drought tolerance and they tended to have a higher potential hydraulic conductivity. In contrast to studies focusing on adult trees and lianas we found no clear differences in morphological and photosynthetic traits between the life forms. Possibly lianas and trees are functionally different at later ontogenetic stages with lianas having deeper root systems than trees or experience their main growth advantage during wet periods when they are less vulnerable to cavitation and can achieve high conductivity. This study shows however that the hydraulic characteristics and functional traits that we examined do not explain differences in liana and tree distributions in seasonal forests.

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Support

The Liana Ecology Project is supported by Marquette University and funded in part by the National Science Foundation.