Literature DB >> 27189787

Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests.

Xiangtao Xu1, David Medvigy1, Jennifer S Powers2, Justin M Becknell3, Kaiyu Guan4.   

Abstract

We assessed whether diversity in plant hydraulic traits can explain the observed diversity in plant responses to water stress in seasonally dry tropical forests (SDTFs). The Ecosystem Demography model 2 (ED2) was updated with a trait-driven mechanistic plant hydraulic module, as well as novel drought-phenology and plant water stress schemes. Four plant functional types were parameterized on the basis of meta-analysis of plant hydraulic traits. Simulations from both the original and the updated ED2 were evaluated against 5 yr of field data from a Costa Rican SDTF site and remote-sensing data over Central America. The updated model generated realistic plant hydraulic dynamics, such as leaf water potential and stem sap flow. Compared with the original ED2, predictions from our novel trait-driven model matched better with observed growth, phenology and their variations among functional groups. Most notably, the original ED2 produced unrealistically small leaf area index (LAI) and underestimated cumulative leaf litter. Both of these biases were corrected by the updated model. The updated model was also better able to simulate spatial patterns of LAI dynamics in Central America. Plant hydraulic traits are intercorrelated in SDTFs. Mechanistic incorporation of plant hydraulic traits is necessary for the simulation of spatiotemporal patterns of vegetation dynamics in SDTFs in vegetation models.
© 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Entities:  

Keywords:  Ecosystem Demography model 2 (ED2); diversity; plant functional trait; plant hydraulics; seasonally dry tropical forests; tropical phenology

Mesh:

Substances:

Year:  2016        PMID: 27189787     DOI: 10.1111/nph.14009

Source DB:  PubMed          Journal:  New Phytol        ISSN: 0028-646X            Impact factor:   10.151


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