Original articleDelta blue intensity vs. maximum density: A case study using Pinus uncinata in the Pyrenees
Introduction
Tree-rings are invaluable archives of past climate for the late Holocene due to their exact annually resolved dating control (Stokes and Smiley, 1968; Anchukaitis et al., 2012), the generally good understanding of the processes governing tree growth (Fritts, 1976; Körner, 2003; Vaganov et al., 2006, 2011; Rossi et al., 2013) and their ability to express a range of different climate variables (Schweingruber, 1988; Jones et al., 2009). Different parameters can be measured from the rings of trees including width, density, wood anatomical properties and stable isotopes (Speer, 2010; Björklund et al., 2019), the variability of which can represent varying climate signals which are often moderated by site ecology. For example, a rough rule of thumb is that the growth of trees growing at high elevation/latitude environments will be temperature limited (Fritts et al., 1965; Kienast et al., 1987; Briffa et al., 2002) while at low elevations/latitudes moisture availability becomes the primary driver of productivity (Fritts, 1976; Cook et al., 2004, 2015). More complex associations exist for stable isotopes (McCarroll and Loader, 2004).
For the reconstruction of Northern Hemispheric (NH) summer temperatures, tree-ring records hold particular prominence for the last 1000−2000 years (Masson-Delmotte et al., 2013; PAGES 2k Consortium, 2013; Esper et al., 2018). To date, large compilations of temperature sensitive tree-ring data have mostly focussed on both ring-width (RW) and ring-density parameters (Esper et al., 2002; D’Arrigo et al., 2006; Stoffel et al., 2015; Wilson et al., 2016; Anchukaitis et al., 2017) with notable exceptions using only maximum latewood density (MXD - Briffa et al., 2001; Schneider et al., 2015). RW data correlate moderately with summer temperatures (Briffa et al., 2002; Wilson et al., 2016) and generally express strong persistence (i.e. high 1st order autocorrelation) which may impart spectral biases in the resulting local and large-scale temperature estimates (Franke et al., 2013, Lücke et al., 2019). MXD, on the other hand, often matches better the autocorrelation structure of the target summer temperature data (Ljungqvist et al., 2020). In an ideal world, therefore, chronology development (new and updates) should focus on MXD, with RW being used cautiously so long as the spectral properties of the reconstruction matches the instrumental data target. The new generation of tree-ring only NH reconstructions (Schneider et al., 2015; Stoffel et al., 2015; Wilson et al., 2016) represent a substantial improvement on earlier attempts (Briffa et al., 2001; Esper et al., 2002; D’Arrigo et al., 2006). However, despite many studies over the last 20 years definitively detailing that MXD is the more robust parameter (Briffa et al., 2002; Wilson and Luckman, 2003; Esper et al., 2012; Büntgen et al., 2017; Ljungqvist et al., 2020), there has been no community wide strategic plan or investment to update datasets sampled in the 1980s/90s (Schweingruber and Briffa, 1996). Rather, those relatively few important millennial long MXD records that have been developed or updated, represent individual laboratory efforts to create improved regional records (Luckman and Wilson, 2005; Büntgen et al., 2006; Esper et al., 2012; McCarroll et al., 2013; Zhang et al., 2016; Büntgen et al., 2016, 2017; Esper et al., 2019). Presumably, this reflects the relatively small number of tree-ring laboratories with densitometric equipment (Wilson et al., 2014, 2017a) and for this situation to change, a more affordable method is needed that all laboratories can embrace and utilise.
Since the initial concept paper (McCarroll et al., 2002), measurement of the intensity of the reflectance of blue light from the latewood of conifer samples (often referred to as blue intensity (BI)) has shown great promise as a surrogate and cheaper replacement of MXD (Björklund et al., 2014, 2015; Rydval et al., 2014; Wilson et al., 2014). MXD and BI measure similar wood properties – the relative density of the latewood of conifers - and are well correlated with warm-season temperatures. Most studies that have compared MXD and BI directly show no significant difference between the two parameters (Wilson et al., 2014; Ljungqvist et al., 2020), although in one study BI was found to express temporal instabilities compared to MXD (Kaczka et al., 2018). Despite the ever-expanding number of papers using BI, it must still be seen as an experimental parameter as it has only been utilised on a relatively small number of conifer species (e.g. Pinus Sylvestris, Scotland, UK (Rydval et al., 2014), and Scandinavia (Campbell et al., 2007, 2011; Helama et al., 2013; Björklund et al., 2014, 2015; Fuentes et al., 2018); Picea engelmannii, the Canadian Rockies, British Columbia, Canada (Wilson et al., 2014); Picea abies, Europe (Österreicher et al., 2015; Buras et al., 2018; Kaczka et al., 2018; Rydval et al., 2018); Abies nordmanniana in the Northern Caucasus (Dolgova, 2016); Pinus ponderosa, American SW (Babst et al., 2016); Pinus cembra, Austria (Wilson et al., 2017a); Tsuga mertensiana (Bong. Carrière), Gulf of Alaska (Wilson et al., 2017b); Fokienia hodginsii, central Vietnam (Buckley et al., 2018); Larix decidua Mill, Europeanm Alps (Arbellay et al., 2018); Callitropsis nootkatensis (D. Don) Oerst. ex DP Little, Gulf of Alaska (Wiles et al., 2019); Picea glauca, the Yukon (Wilson et al., 2019)). There is no theoretical reason why BI should not produce similar results for any species from which MXD data have been measured (Björklund et al., 2019). However, the most significant limitation of BI is the fact that it is based on light reflectance. Any colour change on the surface of the wood samples that does not represent year-to-year climate driven latewood cell wall relative density changes (e.g. heartwood/sapwood colour change, or fungal-related discolouration) will impart a potential low frequency bias into the raw measurement data. A proposed method to correct for such biases subtracts the raw latewood minimum BI value from the maximum earlywood BI value (Björklund et al., 2014), producing the so-called Delta BI (DBI) parameter. Compared to standard latewood BI, DBI has only been tested on Pinus sylvestris (Björklund et al., 2014, 2015) and Tsuga mertensiana (Wilson et al., 2017b). Herein, we detail a small-scale study that tests DBI on Pinus uncinata samples from the Spanish Pyrenees by comparing the data with archived MXD chronologies from the surrounding region.
Section snippets
Data and methods
From previous experience working in Scotland, NW North America and the Carpathian Mountains (Rydval et al., 2014, 2018; Wilson et al., 2014, 2017a,b, 2019) a single well replicated tree-ring site should allow a robust test of the viability of BI as a climate proxy for any conifer species in a region. This is based on the consistent observation that BI expresses a “purer” summer temperature signal and is less impacted by site ecological (e.g. disturbance) effects than RW. Following this
Results and discussion
The between-chronology coherence is stronger for MXD/DBI than RW with a mean inter-series correlation of 0.78 compared to 0.57 (Fig. 2A and B). The Aranser RW chronology correlates with the other sites with a range of 0.48–0.70 (mean r = 0.61), while the DBI data express a range of 0.75 – 0.82 (mean r = 0.77) with the MXD data. This stronger common signal of the MXD/DBI data is further highlighted by the PCA with the MXD/DBI chronologies loading on PC1 (explaining 57.3% of the overall variance)
Concluding remarks
In this study, we have measured DBI data from a single well replicated P. uncinata site at upper treeline in the Spanish Pyrenees and compared the chronology properties with MXD data from similar sites within 120 kms. Despite heartwood/sapwood and fungal-related discolouration (Fig. 1), the DBI data appear to minimise the colour biases that would be expressed by the latewood BI data, and no significant trend differences are noted between the MXD and DBI chronologies (Fig. 2B). Principal
Acknowledgements
This paper is dedicated to Fritz Schweingruber who passed away while this manuscript was being finalised. He was an inspiration to all dendrochronologists and was integral in the exploration of conifer tree-ring density parameters for dendroclimatology in the 1970s. The development of blue intensity over the last decade benefitted greatly from Fritz’ experience and insight. He will be sorely missed. Many thanks to Cheryl Wood and Hannah Frith for measurement of much of the material utilised in
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2021, DendrochronologiaCitation Excerpt :This weaker climatic signal can be explained by a combination of a shorter correlation period, as well as temperature and precipitation data from different weather stations (data not accessible to us). MXD and MXBI are both estimates of cell wall thickness and lumen area in the latewood (Björklund et al., 2019; Reid and Wilson, 2020) and they are significantly positively correlated with each other in WICE (Table 2, Fig. 3C). The climatic signal of precipitation was similar (Figs. S5, 5 E; (Kaczka et al., 2018)), but was generally weaker for temperature in MXBI compared to MXD, which is in line with the results found in Reid and Wilson (2020).