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Informing models through empirical relationships between foliar phosphorus, nitrogen and photosynthesis across diverse woody species in tropical forests of Panama
Author(s) -
Norby Richard J.,
Gu Lianhong,
Haworth Ivan C.,
Jensen Anna M.,
Turner Benjamin L.,
Walker Anthony P.,
Warren Jeffrey M.,
Weston David J.,
Xu Chonggang,
Winter Klaus
Publication year - 2017
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.14319
Subject(s) - edaphic , panama , nutrient , photosynthesis , environmental science , phosphorus , canopy , agronomy , tropics , evergreen , ecology , biology , botany , soil water , chemistry , organic chemistry
Summary Our objective was to analyze and summarize data describing photosynthetic parameters and foliar nutrient concentrations from tropical forests in Panama to inform model representation of phosphorus (P) limitation of tropical forest productivity. Gas exchange and nutrient content data were collected from 144 observations of upper canopy leaves from at least 65 species at two forest sites in Panama, differing in species composition, rainfall and soil fertility. Photosynthetic parameters were derived from analysis of assimilation rate vs internal CO 2 concentration curves ( A / C i ), and relationships with foliar nitrogen (N) and P content were developed. The relationships between area‐based photosynthetic parameters and nutrients were of similar strength for N and P and robust across diverse species and site conditions. The strongest relationship expressed maximum electron transport rate ( J max ) as a multivariate function of both N and P, and this relationship was improved with the inclusion of independent data on wood density. Models that estimate photosynthesis from foliar N would be improved only modestly by including additional data on foliar P, but doing so may increase the capability of models to predict future conditions in P‐limited tropical forests, especially when combined with data on edaphic conditions and other environmental drivers.