Diverse climate sensitivity of Mediterranean tree-ring width and density
Understanding long-term environmental controls on the formation of tree-ring width (TRW) and maximum latewood density (MXD) is fundamental for evaluating parameter-specific growth characteristics and climate reconstruction skills. This is of particular interest for mid-latitudinal environments where future rates of climate change are expected to be most rapid. Here we present a network of 28 TRW and 21 MXD chronologies from living and relict conifers. Data cover an area from the Atlantic Ocean in the west to the Mediterranean Sea in the east and an altitudinal gradient from 1,000 to 2,500 m asl. Age trends, spatial autocorrelation functions, carry-over effects, variance changes, and climate responses were analyzed for the individual sites and two parameter-specific regional means. Variations in warm season (May–September) temperature mainly control MXD formation (r = 0.58 to 0.87 from inter-annual to decadal time-scales), whereas lower TRW sensitivity to temperature remains unstable over space and time.
KeywordsConifers Dendroclimatology Growth responses Climate reconstructions Summer temperature
Temperature sensitive tree growth in Europe is mainly restricted to the northern boreal forest and high-elevation sites in the Alps and Carpathian arc, limiting dendroclimatic evidence for the Mediterranean region, which has ironically been defined as a major climate change hotspot (Giorgi 2006), where future rates of temperature increase and precipitation decrease are expected to be most rapid (Gao and Giorgi 2008).
Temperature-controlled formation of tree-ring width (TRW) across Mediterranean environments, if at all existing, is limited to treeline ecotones in the Pyrenees (Schweingruber 1985). Previous studies of sub-alpine forest (Ruiz-Flaño 1988; Rolland and Schueller 1994; Camarero et al. 1998; Tardif et al. 2003; Andreu et al. 2007) and treeline responses to climate change (Camarero and Gutiérrez 2004; Camarero et al. 2005; Wiegand et al. 2006) focused on local scales and living trees, but were never extended to reconstruction purposes. In fact, larger compilations of maximum latewood density (MXD) measurements from relict wood and temporal calibration against different climatic variables are still missing for the Mediterranean region. When screening the International Tree-Ring Data Bank (ITRDB, http://www.ncdc.noaa.gov/paleo; 11.2008) for twentieth century (1901–2000) low- to mid-latitudinal data (45°N to 45°S), 99 TRW, but no MXD sites are found. These numbers change to 513 and 10 when reducing the period to 1901–1990, calling for a recent update of MXD sites.
Despite the large effort necessary to develop MXD chronologies (Schweingruber et al. 1978), this parameter is of relevance because of its pronounced climatic fingerprint and skill as an estimator of past climate variability (see references herein). The particular merit of temperature signals preserved in conifer MXD is related to known processes of intra-annual wood formation (Rossi et al. 2006a), and has been reported from numerous sites in the Northern US (e.g., Luckman and Wilson 2005; Szeicz and MacDonald 1995; Wang et al. 2001; Wilson et al. 2007), as well as along a European gradient from Northern Fennoscandia (Briffa et al. 2002), over the Tatra Mountains (Büntgen et al. 2007a), to the Central Alps (Frank and Esper 2005).
Here we present a compilation of existing and newly developed TRW and MXD data from the Pyrenees Mountains. This network covers an area from the Atlantic Ocean in the west to the Mediterranean Sea in the east and an altitudinal gradient from 1,000 to 2,500 m asl. Site chronologies, as well as parameter-specific regional means are compared with instrumental temperature, precipitation, and drought data. Relationships between climate forcing and tree growth are discussed with a focus on their relevance for ongoing endeavors in reconstructing Mediterranean temperature variability.
Materials and methods
Characteristics of the site chronologies, with MXD site numbers and mean density values indicated in bold
Elevation (m asl)
Start (≥5 series)
TRW samples were processed following standard techniques outlined in Stokes and Smiley (1968). MXD was measured via a WALESCH 2003 X-ray densitometer with a resolution of 0.01 mm, and brightness variations transferred into g/cm3 using a calibration wedge (Eschbach et al. 1995). Relationships between the absolute (volume and weight) and radiographic (X-ray) wood density (considering different species) were employed as correction factors.
To remove non-climatic age trends from the raw measurements, TRW and MXD series were detrended (standardized) using cubic smoothing splines with a 50% frequency-response cutoff equal to 300 years (Cook and Peters 1981). Indices were calculated as ratios (and as residuals after power transformation) from the estimated growth curves and averaged using a bi-weight robust mean (Cook and Peters 1997). Since such individual detrending eliminates wavelengths longer than the mean series length (Cook et al. 1995), the regional curve standardization method (RCS, Esper et al. 2003) was additionally applied (to the raw or power transformed values) to retain lower frequency information (using ratios or residuals). Series were first aligned by cambial age, a mean of these age-aligned series calculated, and this mean smoothed using a cubic spline of 10% the series length. The resulting time-series is termed regional curve (RC) and used for detrending, i.e., deviations of the individual measurements from the RC were calculated as ratios (and as residuals after power transformation). Dimensionless indices were then dated back to calendar years, and averaged to form a chronology. The variance in the mean chronology was stabilized using a time dependent ‘100-year moving window’ approach for adjusting temporal changes in both, sample replication and inter-series correlation (Frank et al. 2007b). Final chronologies were truncated at <5 series. Inter-series correlation (Rbar) and the expressed population signal (EPS) were calculated for 30-year windows lagged by 15 years along the time-series to assess their signal strength (Wigley et al. 1984). Mean EPS of the 28 TRW (21 MXD) chronologies is 0.85 (0.85) and ranges from 0.62 to 0.96 (0.68–0.96). Mean Rbar of the TRW (MXD) data is 0.30 (0.34).
Varimax rotated principal component analysis (PCA, Richman 1986) was performed to detect chronology subsets of ‘optimized’ signal coherency within and between the two tree-ring parameters. Correlations as a function of distance between sites revealed patterns of spatial autocorrelation.
Correlations between the MXD and TRW records computed over the maximum 1260–2005 and two split periods (1260–1632/1633–2005) depict stronger coherency over the post 1633 period. While the unfiltered chronologies correlate at 0.32 and 0.45 over the early and late period, respectively, correlations increase to 0.52–0.72 and 0.59–0.77 after 10–60 years low-pass filtering. Correlations obtained from the low-passed records computed over the full period range below those from the two split periods. After 10–60 year high-pass filtering of the chronologies, correlations decrease to 0.15–0.20 and 0.34–0.36 for the early and late period, respectively. Most significant correlation differences between the early/late split periods are revealed from the band-passed time-series. While correlation over the early period between the TRW and MXD records after 10–20 year band-pass filtering is zero, highest correlation of 0.79 is obtained after 40–60 year band-pass filtering and the late period. This harmonic mid-frequency variability is illustrated in Fig. 9b. In-phase swings of the two parameter-specific VARCS chronologies are most distinct between 1260–1360, ~1450, and from 1650 to present. Note that some recent divergence between decreasing TRW and increasing MXD data is most likely inflated by the smoothing applied. In contrast, more realistic offset is evident during the fifteenth to sixteenth century, when either differing variance (e.g., ~1400) or opposing trends (e.g., ~1540) occurred.
Age trends, wood formation, and growth characteristics
While age trends of the analyzed TRW series mainly depend on geometrical reasons (e.g., Fritts 1976), more subtle and less-well understood physiological processes appear to be responsible for the age trends in MXD (Schweingruber et al. 1978). Two possible hypothesis can be invoked: the observed age trend in MXD might be related to (i) a systematic decrease in the ratio between cell wall size and lumen area with increasing tree age, or alternatively (ii) that the annual lignin content decreases with age. The first hypothesis presupposes that the amount of annual lignin content remains stable over time, and seems to be supported by the lack of correlation between the lignin content of latewood cells and measured MXD values (Gindl et al. 2000).
In line with distinct carry-over effects on earlywood cell formation (e.g., Fritts 1976), the TRW time-series retain more low-frequency variability than the MXD data, which show more inter-annual variability. In other words, TRW integrates effects from previous year climatic and ecological conditions, which leads to different signal-to-noise ratios on inter-annual versus multi-decadal time-scales (e.g., Frank et al. 2007a). Such physiological induced autocorrelation reflects the utilization of abundant carbohydrates stored towards the end or even after the growing season (Kozlowski and Pallardy 1997). Carry-over processes can be obscured by longer-term gain (loss) in activating resources from root and needle growth following favorable (severe) conditions. Recent findings on carbon allocation of the evergreen conifer species Pinus uncinata suggest utilization of a considerable amount (42%) of carbohydrate storage from the previous year for new wood formation, i.e., shoot and twig growth, whereas current-year rates of photosynthesis are of minor importance (Felten von et al. 2007). Parameter-specific differences in carry-over effects are also reported from conifer networks across the high-northern latitudes (Briffa et al. 2002), the European Alps (Frank and Esper 2005), and western Carpathian arc (Büntgen et al. 2007a). Nevertheless, their causes are not fully understood and call for more efforts towards a better understanding of the timing of carbon allocation based on tracer studies (Kagawa et al. 2006). The coexistence of both TRW and MXD measurements may allows physiologically versus climate-induced persistence in cell development and enlargement to be separated Kirdyanov et al. 2007).
We found the relationship between TRW and summer temperatures to be weak and instable over time. A similar weak climatic signal is reported for high-elevation TRW by Tardif et al. (2003), who analyzed inter-annual relationships between radial growth variations and temperature fluctuations for several (near timberline) Pinus uncinata sites within the Central Spanish Pyrenees. The herein observed differences in the degree of parameter-specific carry-over effects additionally stress a decline in climate sensitivity of TRW after severe conditions. This is most evident when trees have not fully recovered from external impacts (e.g., climate, insect outbreaks) and utilize carbohydrate reserves for purposes other than radial expansion; cell wall thickening during the second half of the vegetation period, however, is less affected (Frank et al. 2007a). While such differences are most pronounced during and after decadal-scale depressions in warm season temperatures (such as the prominent cooling during the early 19th century, Büntgen et al. 2008a), general features of TRW sensitivity to climate variability are likely also applicable during less harsh episodes with additional effects on inter-annual time-scales.
Conversely, our analyses confirmed a strong relationship between MXD and May–September temperatures across the network. This climatic fingerprint is most likely related to the timing of secondary cell wall formation (Gindl et al. 2000). A significant correlation between tracheid wall thickness and the duration of tracheid maturation (lignification) indicates continuous and quasi steady-state rates of cell wall formation within growth and differentiation zones. An increase in radial growth yields larger lumen and thus a decline in measured density. During the first part of the growing season, climatic variations affect radial enlargement, whereas during the later part of the growing season, climatic variations only affect the cell wall thickening process. More detailed information on specific correlations with climate of numerous tree-ring parameters (i.e., early and latewood width, and density) from high-elevation conifers in the Pyrenees can be found in Büntgen et al. (2007b). Distinct characteristics of MXD data, such as strong correlations with temperature during the early and late vegetation period but weaker correlations in-between, are further reported from a high-elevation larch network in the Swiss Alps (Büntgen et al. 2006), from a multi-species network across the Alps (Frank and Esper 2005), and from hundreds of sites scattered along the northern latitudinal timberline (Briffa et al. 2002). A recent study along the northern timberline in Eurasia by Kirdyanov et al. (2007) highlighted offset in the timing of the initiation of cambial activity and of rapid cambial cell division at the beginning of the vegetation period, and the enlargement of latewood tracheids and the thickening of their walls towards the end of the vegetation period. More precise knowledge on the intra-annual timing of stem growth, i.e., the onset of cambial activity, the duration and ending of cell differentiation, radial enlargement (TRW), wall thickening, and lignification (MXD) can be derived from high-resolution dendrometer and punching approaches (Moser et al. in press). Detailed experiments showed that maximum tracheid production corresponded to maximum day length, thus allowing cell wall formation and lignification to be completed independently by the end of summer (Rossi et al. 2006b). Determination of the onset of cambial activity, the duration and ending of cell differentiation, radial enlargement, wall thickening, and lignification has been assessed for high-elevation conifers (Rossi et al. 2007), indicating that the formation of thicker cell walls (relative to lumen size) in latewood tracheids is related to duration length (Rossi et al. 2006a). Gricar et al. (2005) related high correlations between MXD and late summer temperature to the lignification process of latest formed tracheids extending long after cambial cell division has ceased.
Besides those differences in climate sensitivity of TRW and MXD that are mainly related to physiological processes, differences in the relationship with regional temperature variability might be caused by changing climate and/or environmental conditions (Carrer and Urbinati 2006; Andreu et al. 2007). While MXD time-series reveal stable correlations with warm season temperature over the twentieth century and western Mediterranean basin, our network suggests deviation of TRW from the principle of uniformitarianism (Fritts 1976). Interestingly, the relationship between TRW and May–September temperature variability vanished back in time, considering some bias possibly emerging from the extended seasonal window, which is optimized to match the climate sensitivity of MXD. This TRW related backward decline in sensitivity—the loss of temperature sensitivity is not compensated by increasing precipitation or drought response—contradicts the observed 20th century warming, and refutes underlying mechanisms of threshold-induced drought stress. Indication for a recent reduction in growth response to rising temperatures as reported from Alaska (Barber et al. 2000; Wilmking et al. 2004, 2005) is also not observed. Nevertheless, caution is advised, as the correlation between TRW and warm season temperature during the second part of the 20th century might be inflated by similar positive trends in both time-series (Büntgen et al. 2008b). Additional bias might emerge from a general underestimation of precipitation in higher elevation environments, and particularly the Mediterranean area where synoptic modes and topography complicate instrumental readings (Gao and Giorgi 2008). At this stage, we are unable to link the observed instability in climate sensitivity of TRW with plausible physiological and physical factors.
A network of 49 conifer TRW and MXD chronologies from the Pyrenees allowed parameter-specific climate sensitivity to be assessed over the 20th century. Correlations with summer temperatures indicated sensitivity for MXD, but less spatiotemporal stability for TRW. Other controls on the network’s growth/climate relationship that are possibly related to (i) climatic changes along the west-east gradient from the Atlantic Ocean to the Mediterranean Sea, (ii) differences in temperature means, precipitation totals and sunshine duration along the altitudinal gradient from the montane to sub-alpine forest zones, and (iii) physiological peculiarities of the three conifer species, have been shown to be insignificant for MXD. The formation of TRW, however, was found to be more responsive to a mixture of internal (biotic) and external (abiotic) factors besides summer temperature alone. Additional tree-ring parameters, such as isotopic composition might be helpful when estimating past Mediterranean climate variability.
R. Wilson, A. Verstege, and F. Anders assisted fieldwork. F. Schweingruber and other ITRDB contributors provided tree-ring data. The NP d’Aigüestortes I Estany de Sant Maurici (namely J. V. Canillas) kindly provided sampling permission. Spatial field correlations were generated using the KNMI Climate Explorer (http://climexp.knmi.nl). Supported by the SNF project NCCR-Climate (Extract) and the EU project MILLENNIUM (#017008).
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