Modelling tree ring cellulose <i>δ</i><sup>18</sup>O variations in two temperature-sensitive tree species from North and South America

Abstract

Abstract. Oxygen isotopes in tree rings (δ 18 O TR ) are widely used to reconstruct past climates. However, the complexity of climatic and biological processes controlling isotopic fractionation is not yet fully understood. Here, we use the MAIDENiso model to decipher the variability in δ 18 O TR of two temperature-sensitive species of relevant palaeoclimatological interest (Picea mariana and Nothofagus pumilio) and growing at cold high latitudes in North and South America. In this first modelling study on δ 18 O TR values in both northeastern Canada (53.86 • N) and western Argentina (41.10 • S), we specifically aim at (1) evaluating the predictive skill of MAIDENiso to simulate δ 18 O TR values, (2) identifying the physical processes controlling δ 18 O TR by mechanistic modelling and (3) defining the origin of the temperature signal recorded in the two species. Although the linear regression models used here to predict daily δ 18 O of precipitation (δ 18 O P ) may need to be improved in the future, the resulting daily δ 18 O P values adequately reproduce observed (from weather stations) and simulated (by global circulation model) δ 18 O P series. The δ 18 O TR values of the two species are correctly simulated using the δ 18 O P estimation as MAIDENiso input, although some offset in mean δ 18 O TR levels is observed for the South American site. For both species, the variability in δ 18 O TR series is primarily linked to the effect of temperature on isotopic enrichment of the leaf water. We show that MAIDENiso is a powerful tool for investigating isotopic fractionation processes but that the lack of a denser isotope-enabled monitoring network recording oxygen fractionation in the soil-vegetation-atmosphere compartments limits our capacity to decipher the processes at play. This study proves that the eco-physiological modelling of δ 18 O TR values is necessary to interpret the recorded climate signal more reliably.

Absence of Age‐Related Trends in Stable Oxygen Isotope Ratios From Oak Tree Rings

“…A cost-effective solution is to pool the wood from several trees prior to the chemistry and mass spectrometry (Borella et al, 1998;Dorada-Liñan, 2011;Lavergne et al, 2017;Leavitt, 2008;Liu et al, 2015;Szymczak et al, 2012). A cost-effective solution is to pool the wood from several trees prior to the chemistry and mass spectrometry (Borella et al, 1998;Dorada-Liñan, 2011;Lavergne et al, 2017;Leavitt, 2008;Liu et al, 2015;Szymczak et al, 2012).…”

“…Although there is clear potential for constructing long, well-replicated isotope chronologies using oak, this work can be constrained by the high cost of separating the alpha cellulose from individual latewood samples and measuring the samples individually by mass spectrometry. A cost-effective solution is to pool the wood from several trees prior to the chemistry and mass spectrometry (Borella et al, 1998;Dorada-Liñan, 2011;Lavergne et al, 2017;Leavitt, 2008;Liu et al, 2015;Szymczak et al, 2012). However, doubts have been raised about the wisdom of such an approach, as it has been argued that the isotope ratios from the rings of individual trees are influenced by tree age as well as by climate, and therefore require statistical detrending to remove these nonclimatic trends (Esper et al, 2010;Helama et al, 2015).…”

An Overview on Isotopic Divergences – Causes for instability of Tree-Ring Isotopes and Climate Correlations

“…Most models make forward predictions and allow verifying that the measured tree-ring isotopic trends compare well with the isotopic outputs modelled with the meteorological and non-meteorological inputs. So far, only MAIDENiso has been used in inverse mode for reconstructing climate (Danis et al, 2012;Boucher et al, 2014;Lavergne et al, 2017). The limitations when using processbased models come from the fact that all the required daily input data are in cases not measured over long periods, or in other cases, just derived, inducing uncertainties.…”

“…Depending on the sophistication of the mechanistic or proxy-system approaches, modeling may even compensate for divergences due to climate change. The tree-ring isotopic outputs from process-based models are sensitive to changes in key input parameters, such as  18 O values in rain, vapour and soil water (Lavergne et al, 2017).…”

“…Importantly, not all mechanistic models have the same readiness for climatic inversion. MAIDENiso is the only model that was successfully inversed for reconstructing climate using several proxies including tree-ring isotopes, in three regions of the world (France, Québec and southern Argentina; Danis et al, 2012;Boucher et al, 2014;Lavergne et al, 2017). Moreover, ecophysiological models and experts with the required coding knowledge for improving the existing executable formats are rare.…”