Spruce tree-ring proxy signals during cold and warm periods

Abstract

Abstract:The strength and temporal rigidity of climate signals are important characteristics of proxy data used to reconstruct climate variability over pre-instrumental periods. Here, we assess the performance of different tree-ring proxies, including ring width, maximum latewood density, δ 13 C, and δ 18 O, during exceptional cold (1800-1850) and warm periods . The analysis was conducted at a spruce (Picea abies) timberline site in the Swiss Alps in proximity to long homogenized instrumental records to support calibration tests against early temperature and precipitation data. In this cold environment, tree-ring width, maximum latewood density, and δ 18O are mainly controlled by temperature variations. δ 13 C is influenced by various factors including temperature, precipitation, sunshine, and relative humidity. When comparing the response patterns during cold and warm periods, ring width and maximum latewood density revealed temporally stable temperature signals. In contrast, the association between the stable isotopes and climate changed considerably between the early 19th and late 20th centuries. The temperature signal in δ 18O was stronger during the recent warm period, whereas the opposite is true for δ 13 C. In δ 13 C, the temperature signal weakened from the early 19th to the late 20th centuries, but an (inverse) precipitation signal evolved indicating that soil moisture conditions additionally limited recent carbon isotope ratios. An attempt to combine the tree-ring proxies in a multiple regression model did not substantially improve the strength of the dominating temperature signal retained in the latewood density data as this proxy already explained a significant fraction of summer temperature variability. Our findings underscore the importance of split calibration/verification approaches including cold and warm periods, and challenge transfer models based on only late 20th century observational data.

Evaluation of Different Pooling Methods to Establish a Multi-Century δ18O Chronology for Paleoclimate Reconstruction

“…This study explored the effect of various pooling methods on the statistical characteristics and climate responses of a site-specific δ 18 O-chronology, and the possibility of using pooled isotope chronologies for paleoclimate reconstruction in Northern Iran. Comparable to the results of other studies that used different pooling methods, such as inter-tree pooling [27][28][29] and shifted serial pooling [14,19], our pooled chronologies contained a significant climate signal. However, the linkage between δ 18 O TRC and climate variables during the current year has been masked in the shifted 5-year block series, since conditions during preceding years have a strong influence on the isotope signal of these chronologies.…”

“…Furthermore, pooling enables the establishment and the extension of isotope chronologies further back in time at lower cost. Hence, the pooling technique has been widely used for valuable paleoclimate reconstructions [21,[27][28][29][30][31][32][33][34][35][36][37][38][39]. Various techniques exist for pooling tree rings prior to stable isotope analysis such as (i) inter-tree pooling, which combines calendar synchronous tree rings from individual trees [15,22,40,41]; and (ii) serial pooling, which combines the use of pentad or temporally lower resolved blocks within the individual trees, with the risk of losing high-frequency climate signals [14].…”

Global assessment of relationships between climate and tree growth

“…This might potentially lead to biased estimates of past climate variability, past and future forest growth and tree‐species performance, and carbon and water dynamics of forest ecosystems. To overcome these challenges, careful selection of tree‐ring chronologies based on adequate stationarity tests over the full range of climate target variability should be mandatory (Buras et al, 2017; Esper et al, 2017). Our data also indicate a need to re‐evaluate the a priori stationarity assumption that often underpins tree‐ring studies.…”

“…First, indications are increasing that the stationarity assumption does not accurately reflect complex tree–environment relationships (Babst et al, 2019; Briffa et al, 1998; Carrer, 2011; Carrer & Urbinati, 2006; D'Arrigo et al, 2008; Esper et al, 2017; Harvey et al, 2020; Hofgaard et al, 2019; Leonelli et al, 2011; Lloyd, Duffy, & Mann, 2013; Smith, 2008; Stine & Huybers, 2017; Trouillier et al, 2019; Visser et al, 2010; Wilmking et al, 2005; Wilmking, Juday, Barber, & Zald, 2004; Zhang, Wilmking, & Gou, 2009). Trees are sessile organisms and undergo ontogeny in a constantly changing world (Smith, 2008), influenced by a multitude of factors of varying importance through time (Carrer & Urbinati, 2006; Stine & Huybers, 2017; Trouillier et al, 2019).…”

An 1800-year stable carbon isotope chronology based on sub-fossil wood from Lake Schwarzensee, Austria

“…A similar unstable relationship with climate parameters was previously described for the carbon isotope measurements carried out for Norway spruce trees from the Swiss Alps. The temperature signal obtained for this area was substantially enhanced during the cooler and wetter summers of the first half of the 19th century, whereas in the warmer late 20th century, precipitation became more influential (Esper et al, 2017). Presumably, the photosynthetic rate (forced by temperature and irradiance) controlled the fractionation during the less favourable thermal conditions of the early 19th century, while stomatal conductivity (forced by soil moisture and air humidity) governed the discrimination against 13 C during the calibration period of the late 20th century (Esper et al, 2017).…”