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Defining a spectrum of integrative trait‐based vegetation canopy structural types
Author(s) -
Fahey Robert T.,
Atkins Jeff W.,
Gough Christopher M.,
Hardiman Brady S.,
Nave Lucas E.,
Tallant Jason M.,
Nadehoffer Knute J.,
Vogel Christoph,
Scheuermann Cynthia M.,
StuartHaëntjens Ellen,
Haber Lisa T.,
Fotis Alexander T.,
Ricart Raleigh,
Curtis Peter S.
Publication year - 2019
Publication title -
ecology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.852
H-Index - 265
eISSN - 1461-0248
pISSN - 1461-023X
DOI - 10.1111/ele.13388
Subject(s) - canopy , vegetation (pathology) , ecosystem , ecology , forest ecology , trait , structural complexity , environmental science , terrestrial ecosystem , temperate forest , ecosystem ecology , physical geography , atmospheric sciences , geography , biology , geology , computer science , medicine , pathology , programming language
Vegetation canopy structure is a fundamental characteristic of terrestrial ecosystems that defines vegetation types and drives ecosystem functioning. We use the multivariate structural trait composition of vegetation canopies to classify ecosystems within a global canopy structure spectrum. Across the temperate forest sub‐set of this spectrum, we assess gradients in canopy structural traits, characterise canopy structural types (CST) and evaluate drivers and functional consequences of canopy structural variation. We derive CSTs from multivariate canopy structure data, illustrating variation along three primary structural axes and resolution into six largely distinct and functionally relevant CSTs. Our results illustrate that within‐ecosystem successional processes and disturbance legacies can produce variation in canopy structure similar to that associated with sub‐continental variation in forest types and eco‐climatic zones. The potential to classify ecosystems into CSTs based on suites of structural traits represents an important advance in understanding and modelling structure–function relationships in vegetated ecosystems.