| Literature DB >> 30692257 |
Claudie Giguère-Croteau1,2,3, Étienne Boucher4,5,6, Yves Bergeron1,3,7, Martin P Girardin8, Igor Drobyshev3,7, Lucas C R Silva9, Jean-François Hélie2,10, Michelle Garneau2,5,6.
Abstract
Due to anthropogenic emissions and changes in land use, trees are now exposed to atmospheric levels of [[Formula: see text]] that are unprecedented for 650,000 y [Lüthi et al. (2008) Nature 453:379-382] (thousands of tree generations). Trees are expected to acclimate by modulating leaf-gas exchanges and alter water use efficiency which may result in forest productivity changes. Here, we present evidence of one of the strongest, nonlinear, and unequivocal postindustrial increases in intrinsic water use efficiency ([Formula: see text]) ever documented (+59%). A dual-isotope tree-ring analysis ([Formula: see text] and [Formula: see text]) covering 715 y of growth of North America's oldest boreal trees (Thuja occidentalis L.) revealed an unprecedented increase in [Formula: see text] that was directly linked to elevated assimilation rates of [Formula: see text] (A). However, limited nutrient availability, changes in carbon allocation strategies, and changes in stomatal density may have offset stem growth benefits awarded by the increased [Formula: see text] Our results demonstrate that even in scenarios where a positive [Formula: see text] fertilization effect is observed, other mechanisms may prevent trees from assimilating and storing supplementary anthropogenic emissions as above-ground biomass. In such cases, the sink capacity of forests in response to changing atmospheric conditions might be overestimated.Entities:
Keywords: boreal forest; carbon dioxide; productivity; stable isotopes; water use efficiency
Mesh:
Substances:
Year: 2019 PMID: 30692257 PMCID: PMC6377478 DOI: 10.1073/pnas.1816686116
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205
Fig. 1.Evolution of , , RWI, and since 1300 CE for old-growth white cedars at lake Duparquet, Eastern Canada. Two distinct periods emerge which have been highlighted through different coloring and shading: P1 (1850–1965, red) and P2 (1965–2014, green). (A) is calculated from -derived physiological parameters shown in Fig. 2. The gray shading around the curve represents the intertree variability. The three theoretical scenarios presented in the Introduction (S1, constant ; S2, constant /; and S3, constant − ) are plotted as dotted lines. (B) Annually resolved RWI chronology, RCS standardized with bootstrap 95% CI (gray shading). (C) values.
Fig. 2.Tree-ring (corrected for Suess effect), derived physiological parameters (, , , , , plotted against . The scatter plot is divided into three periods: preindustrial (black, 1850), P1 (red, 1850–1965), and P2 (green, 1965–2014). Linear trends describing the evolution of physiological parameters as a function of are depicted for P1 and P2. Thick lines represent significant ( 0.05) increasing or decreasing trends.
Fig. 3.(A and B) Commonality analysis showing beta weights (A) and the proportion of variance (B) in explained by the pure effects of (gray) and growing-season (May–August) temperatures (T, blue), VPD (green), and SMI (red). Color bands represent the bootstrap 95% CIs for beta weights and proportion of variance explained in . (C) Pure and shared effects are detailed for two specific frequencies: = 0.013 (75 y) (C, 1) and = 0.125 (8 y) (C, 2).