Climate controls over ecosystem metabolism: insights from a fifteen-year inductive artificial neural network synthesis for a subalpine forest

Oecologia

Volumn 184, Issue 1, 2017, Pages 25-41

  Albert, Loren P ^a   Keenan, Trevor F ^b   Burns, Sean P ^c,d   Huxman, Travis E ^e   Monson, Russell K ^a,f  

^a University of Arizona   (United States)

^b LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

^c UNIVERSITY OF COLORADO   (United States)

^d NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

^e UNIVERSITY OF CALIFORNIA   (United States)

^f UNIVERSITY OF ARIZONA   (United States)

Author keywords

Coniferous; Eddy covariance; Fluxnet; Model data assimilation; Photosynthesis

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CLIMATE EFFECT; CONIFEROUS FOREST; DATA ASSIMILATION; DATA SET; ECOSYSTEM MODELING; EDDY COVARIANCE; EVAPOTRANSPIRATION; LONG-TERM CHANGE; NET ECOSYSTEM PRODUCTION; PHOTOSYNTHESIS; SEASONAL VARIATION; SUBALPINE ENVIRONMENT;

CARBON DIOXIDE;

CLIMATE; ECOSYSTEM; FOREST; METABOLISM; SEASON; TREE;

CARBON DIOXIDE; CLIMATE; ECOSYSTEM; FORESTS; SEASONS; TREES;

EID: 85016054995     PISSN: 00298549     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00442-017-3853-0     Document Type: Review

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