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Scale dependence of canopy trait distributions along a tropical forest elevation gradient
Author(s) -
Asner Gregory P.,
Martin Roberta E.,
Anderson Christopher B.,
Kryston Katherine,
Vaughn Nicholas,
Knapp David E.,
Bentley Lisa Patrick,
Shenkin Alexander,
Salinas Norma,
Sinca Felipe,
Tupayachi Raul,
Quispe Huaypar Katherine,
Montoya Pillco Milenka,
Ccori Álvarez Flor Delis,
Díaz Sandra,
Enquist Brian J.,
Malhi Yadvinder
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.14068
Subject(s) - elevation (ballistics) , trait , environmental science , canopy , ecology , physical geography , atmospheric sciences , biology , geography , mathematics , geology , geometry , computer science , programming language
Summary Average responses of forest foliar traits to elevation are well understood, but far less is known about trait distributional responses to elevation at multiple ecological scales. This limits our understanding of the ecological scales at which trait variation occurs in response to environmental drivers and change. We analyzed and compared multiple canopy foliar trait distributions using field sampling and airborne imaging spectroscopy along an Andes‐to‐Amazon elevation gradient. Field‐estimated traits were generated from three community‐weighting methods, and remotely sensed estimates of traits were made at three scales defined by sampling grain size and ecological extent. Field and remote sensing approaches revealed increases in average leaf mass per unit area ( LMA ), water, nonstructural carbohydrates ( NSC s) and polyphenols with increasing elevation. Foliar nutrients and photosynthetic pigments displayed little to no elevation trend. Sample weighting approaches had little impact on field‐estimated trait responses to elevation. Plot representativeness of trait distributions at landscape scales decreased with increasing elevation. Remote sensing indicated elevation‐dependent increases in trait variance and distributional skew. Multiscale invariance of LMA , leaf water and NSC mark these traits as candidates for tracking forest responses to changing climate. Trait‐based ecological studies can be greatly enhanced with multiscale studies made possible by imaging spectroscopy.