Decreasing trend and fluctuations in the mean ring density of Norway spruce through the twentieth century

Abstract

Abstract• Studies on wood density variations are necessary for estimating the forest carbon pool. Further, they can help predict the technological properties of wooden end-products. While there have been frequent reports on the relationships between wood density, cambial age, and ring width, there is little information about the historical trend in wood density for the last century, particularly in the context of global climate change.• In this study, different sources of variations in mean ring density (site, tree, ring age, ring width, and calendar date) were studied using an original sampling design. A total of 105 Norway spruce (Picea abies Karst.) trees were sampled in north-eastern France, from thirteen sites with trees of different ages growing at the same site and in similar conditions. X-ray densitometry measurements were performed on samples taken at breast height. The chronology of the mean ring density over the 20th century was estimated by using a statistical modelling approach based on linear mixed-effects models after accounting for the effect on the mean ring density introduced by different ring widths, cambial ages, sites, and trees.• The mean ring density of Norway spruce was seen to decrease by about 18 kg m −3 relative to the year 1900. The chronology showed no evolution between 1900 and 1950, a steep decline from 1950 to 1980 (reaching a maximum decrease of 30 kg m −3 ), followed by an increase from 1980 to 2000.• The observed decrease was consistent with the results of previous works and supports the hypothesis that this could indicate a global trend and that this trend is independent of the wood structure. Moreover, high inter-annual density variations were found. In future studies, the influence of climate on the wood density and within-ring properties must be clarified to identify the anatomic causes for wood density variations.

Influence of wood density in tree-ring-based annual productivity assessments and its errors in Norway spruce

“…At an interannual scale, wood density variations can be substantial. There were several reports that (annual) ring density decreases with increasing ring width, for instance in Norway spruce (Bergqvist, 1998;Dutilleul et al, 1998;Lundgren, 2004;Bouriaud et al, 2005;Franceschini et al, 2010Franceschini et al, , 2013. Wood density was also proved to vary between trees (Wilhelmsson et al, 2002;Guilley et al, 2004), a fact which is never accounted for in studies using diameter surveys to produce biomass increment estimations.…”

“…Following recent publications on Norway spruce wood density (Franceschini et al, 2010(Franceschini et al, , 2013, the diameter and the ring cambial age (as counted from the pith) were used as independent variables. The selection of the model was based both on the AIC (Akaike information criterion) and the examination of the residual distribution.…”

“…Ring age is often considered in density models for representing the age trend or for the variations observed near the pith -the juvenile versus mature wood transition (e.g. Franceschini et al, 2010). WD in Norway spruce has been shown to present an age-dependent trend from pith to bark (Dutilleul et al, 1998;Hylen, 1999;Mäkinen et al, 2002), apart from the juvenile wood effect.…”

“…The relation between wood density, ring width, and cambial age were proven to fluctuate between trees sampled within a same stand for many species: oak (Guilley et al, 2004;Bergès et al, 2008), common beech (Bouriaud et al, 2004), Norway spruce (Mäkinen et al, 2002;Jaakola et al, 2005;Franceschini et al, 2010). For a given radial growth rate, the trees are building more or less biomass and so storing more or less carbon, according to the density of the wood.…”

Wavelet Analysis of X-ray Density Function of Tree Ring Structure

“…Franceschini et al (2010Franceschini et al ( , 2013 used the mean ring density profi le to study the radial pattern variations and their consistency with changes in temperature and climate. Mutz et al (2004), applied the nonlinear mixed-effects model to the average density profi le of Scots pine trees in order to statistically model the stem growth.…”