Climate indices strongly influence old-growth forest carbon exchange. (13th April 2016)

• Record Type: Journal Article
• Authors: Wharton, Sonia; Falk, Matthias
• Is Part Of: Environmental research letters. Volume 11:Number 4(2016:Apr.)
• Publication Date: 2016-04-13
• Subjects: AmeriFlux -- old-growth forest -- eddy covariance -- net ecosystem exchange -- interannual variability -- Pacific teleconnections; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/11/4/044016
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: We present a decade and a half (1998–2013) of carbon dioxide fluxes from an old-growth stand in the American Pacific Northwest to identify ecosystem-level responses to Pacific teleconnection patterns, including the El Niño/Southern Oscillation (ENSO). This study provides the longest, continuous record of old-growth eddy flux data to date from one of the longest running Fluxnet stations in the world. From 1998 to 2013, average annual net ecosystem exchange ( F NEE ) at Wind River AmeriFlux was −32 ± 84 g C m −2 yr −1 indicating that the late seral forest is on average a small net sink of atmospheric carbon. However, interannual variability is high (>300 g C m −2 yr −1 ) and shows that the stand switches from net carbon sink to source in response to climate drivers associated with ENSO. The old-growth forest is a much stronger sink during La Niña years (mean F NEE = −90 g C m −2 yr −1 ) than during El Niño when the stand turns carbon neutral or into a small net carbon source (mean F NEE = +17 g C m −2 yr −1 ). Forest inventory data dating back to the 1930s show a similar correlation with the lower frequency Pacific North American (PNA) and Pacific Decadal Oscillation (PDO) whereby higher aboveground net primary productivity ( F ANPP ) is associated with cool phases of both the PNA and PDO. These measurements add evidence that carbon exchange in old-growth stands may be more sensitive to climate variability across shorter time scales than once thought.