INCREASING ARIDITY IS ENHANCING SILVER FIR (ABIES ALBA MILL.) WATER STRESS IN ITS SOUTH-WESTERN DISTRIBUTION LIMIT
INCREASING ARIDITY IS ENHANCING SILVER FIR
(ABIES ALBA MILL.) WATER STRESS IN ITS SOUTH-WESTERN
MARC MACIAS1,2,3 , LAIA ANDREU2 , ORIOL BOSCH2 , J. JULIO CAMARERO4
and EMILIA GUTIERREZ2
Department of Geology, University of Helsinki, Gustaf H¨ llstr¨ minkatu 2 (P.O. Box 64). FI-00014
University of Helsinki, Finland
Departament d’Ecologia, Universitat de Barcelona, Avgda. Diagonal, 645. Barcelona 08028,
Finnish Forest Institute, Rovaniemi Research Station, Etel¨ ranta 55. 96300-Rovaniemi, Finland
Unidad de Recursos Forestales, Centro de Investigaci´ n Agroalimentaria, Gobierno de Arag´ n,
Apdo. 727, Zaragoza 50080, Arag´ n, Spain
Abstract. Tree populations located at the geographical distribution limit of the species may provide
valuable information about the response of tree growth to climate warming across climatic gradients.
Dendroclimatic information was extracted from a network of 10 silver-ﬁr (Abies alba) populations
in the south-western distribution limit of the species (Pyrenees, NE Iberian Peninsula). Ring-width
chronologies were built for ﬁve stands sampled in mesic sites from the Main Range in the Pyrenees, and
for ﬁve forests located in the southern Peripheral Ranges where summer drought is more pronounced.
The radial growth of silver-ﬁr in this region is constrained by water stress during the summer previous
to growth, as suggested by the negative relationship with previous September temperature and, to
a lesser degree, by a positive relationship with previous end of summer precipitation. Climatic data
showed a warming trend since the 1970s across the Pyrenees, with more severe summer droughts. The
recent warming changed the climate-growth relationships, causing higher growth synchrony among
sites, and a higher year-to-year growth variation, especially in the southernmost forests. Moving-
interval response functions suggested an increasing water-stress effect on radial growth during the
last half of the 20th century. The growth period under water stress has extended from summer up to
early autumn. Forests located in the southern Peripheral Ranges experienced a more intense water
stress, as seen in a shift of their response to precipitation and temperature. The Main-Range sites
mainly showed a response to warming. The intensiﬁcation of water-stress during the late 20th century
might affect the future growth performance of the highly-fragmented A. alba populations in the
southwestern distribution limit of the species.
Tree populations located at the limit of the species geographical distribution may be
responding more dramatically to climate change than those at the core of the range
(Brubaker, 1986; Gaston, 2003). Several authors have noted a greater sensitivity of
radial growth in response to climate variability in marginal populations than in those
found at the main range of species (Schulman, 1954; Fritts, 1976; Villalba et al.,
1997; Biondi, 2000). This spatial variability interacts with temporal variability
Climatic Change (2006) 79: 289–313
DOI: 10.1007/s10584-006-9071-0 c Springer 2006
290 M. MACIAS ET AL.
because climate-growth relationships are not stable through time (Guti´ rrez et al.,
1998; Tardif et al., 2003).
Several tree species, such as Abies alba Mill., Pinus sylvestris L., Pinus uncinata
Ram., Fagus sylvatica L., etc., meet in the Iberian Peninsula their southern latitudi-
nal limit of distribution. Silver ﬁr (A. alba) main distribution area is found in Central
Europe. Silver-ﬁr populations located in the south side of the main Pyrenean axis
(hereafter Main Range) and nearby, less elevated ranges further south from the
Main Range (hereafter Peripheral Ranges), constitute the south-western limit of
the species (Jalas et al., 1999; Figure 1). It is a highly-fragmented distribution area,
since most of these populations are very small (usually less than 50 ha) and far
from each other.
A. alba stands are usually found on the highest quality and productivity sites
in the Pyrenees, where they form dense monospeciﬁc stands or coexist with F.
sylvatica in the westernmost locations (Vigo and Ninot, 1987; Blanco et al., 1997).
These zones may experience summer drought but receive abundant precipitation
during spring and autumn (Aussenac, 2002). In the study area, A. alba grows in
humid sites on north-facing, shady slopes with relatively deep soils, although often
very stony, where the risk of severe water stress in summer is lower than in the
surrounding areas often dominated by P. sylvestris forests. A. alba populations may
also appear in valley bottoms, but always at elevations above 1200 m.a.s.l.
Silver ﬁr has been historically subjected to regular logging in the Pyrenees,
in some cases up to the late 1970s, when it was no longer used as a source of
timber (Kirby and Watkins, 1998; Cabrera, 2001). Managed forests pose a set of
problems in the standardization process of ring-width series, which is a critical
step in dendroclimatology and dendroecology (Fritts, 1976; Cook et al., 1990).
However, dendroecological studies from these marginal stands are valuable tools
to assess the growth-climate relationships at the limit of the species distribution
area, where recent decline episodes have been described (Camarero, 2001). To
extract the climatic signal contained in tree-ring series from stands disturbed by
local disturbances such as logging, new methodological approaches must be used.
In addition, many trees should be sampled across a large geographical area to obtain
a reliable growth pattern related to the regional climatic signal.
Orography and atmospheric circulation patterns create a rain shadow in the
Southern Pyrenees. Most of the rain carried by low pressure systems coming from
North Atlantic falls north of the Continental Divide (Plana, 1985). The rain shadow
especially affects Peripheral Southern Ranges, which receive less precipitation
than Pyrenean Main Range (Allu´ , 1990). As a whole, climate in the area has a
strong Mediterranean inﬂuence and summer drought is not uncommon (Figure 1).
This inﬂuence decreases westward. Easternmost Ranges get extra precipitation
because cyclone formation is enhanced in the NW Mediterranean region due to
the combined effects of the Pyrenees and the Southern Alps to the westerly ﬂow
(Barry, 1992; Cuadrat, 2000). Also in this region, Mediterranean moisture enhances
the growth of summer thunderstorms which soften summer drought. Overall, the
SPATIOTEMPORAL VARIABILITY IN RADIAL GROWTH
Figure 1. Map of the Pyrenees showing the distribution of Abies alba (stained, Blanco et al., 1997). Note the scarce and scattered presence of silver ﬁr
in Spanish Territory (S of the dotted line). Numbers are locations of the sites, displayed as in table I. Letters are meteorological stations used to build the
sub-regional series of temperature and precipitation (circles). Jacetania/G´ llego: (a). Candanch´ , (b). Canfranc, (c). Sallent de G´ llego; Jacetania/Hoya:
a u a
n´ n `
(d). Jaca, (e). Sabi˜ anigo, (f). Bolta˜ a, (g). Nocito; Pallars: (h). Estany Gento, (i). Cabdella, (j). Estany de Sant Maurici, (k). Espot, (l). Esterri d’Aneu, (m).
Tavascan; Alt Urgell: (n). Oliana, (o). Organy` , (p). Adrall; Cerdanya: (q). Port´ , (r). Puigcerd` , (s). La Molina; Ripoll` s: (t). N´ ria, (u). Ribes de Freser,
a e a e u
(v). Ripoll, (x). Vallter; Montseny: (y). Tur´ de l’Home, (z). Cardedeu and aa. Girona. Square: Pic du Midi station. Climatic diagrams are shown next to
each sub-regional series of temperature and precipitation.
292 M. MACIAS ET AL.
N-S precipitation gradient in the Pyrenees (rain shadow) is stronger than the W-E
Atlantic-Mediterranean gradient, as evidenced by climatic and ﬂoristic data (L´ pez
The climatic trends in the Mediterranean Basin during the last 50 years were
characterized by a rise of mean temperature (2–4 ◦ C), and an increase in both the fre-
quency and intensity of severe droughts (IPCC, 2001). Piervitali et al. (1997) noted a
20% decrease in total precipitation between 1951 and 1995 in the Western Mediter-
ranean Basin. In the Iberian Peninsula, the 1980–1995 period was characterized
by intense droughts, which caused the decline of several woody species (Pe˜ uelas
et al., 2001). In the Central Pyrenees, mean annual temperature has increased by
0.83 ◦ C at the Pic du Midi meteorological station (2862 m.a.s.l). between 1882 and
1970 (B¨ cher and Dessens, 1991; Dessens and B¨ cher, 1995). For Western-Europe
mountains, Diaz and Bradley (1997) reported a similar strong warming trend since
the 1940s, resulting in the latest decades being much warmer than any other period
of the instrumental records. In conclusion, climate in the Iberian Peninsula during
the 20th century has been characterized by exceptionally high temperatures with a
great interannual variability within the context of the last 500 years (Manrique and
Fern´ ndez-Cancio, 2000; Camarero and Guti´ rrez, 2004).
The strong climate warming detected in the Pyrenees during the 20th century
involves increasing aridity and should be detected among species sensitive to water
stress such as A. alba. Speciﬁcally, we hypothesize that silver-ﬁr forests located
in the southern Peripheral Ranges have experienced a more intense water stress in
response to warming than stands located in the Main Range, where precipitation
is higher than in the former sites. The climate-growth relationship might indicate
when and where water stress is increasing. The objectives of this study were:
(i) to assess the sensitivity of silver-ﬁr populations located in contrasting sites
(Peripheral vs. Main Ranges) in response to the regional climate warming observed
in the Pyrenees, and (ii) to analyse the spatio-temporal variability of radial growth
in these two contrasting groups of sites. To achieve this aim we have established
the ﬁrst dendrochronological network of A. alba in the south-western limit of the
species distribution (NE Iberian Peninsula).
2. Material and Methods
Ten silver-ﬁr chronologies were produced for the present work (Table I, Figure 1).
We sought for a homogeneous spatial distribution along the E-W axis of the Pyre-
nees when selecting those sites where old trees could be found. In each stand,
10–17 trees were selected and cored. At least two cores per tree were extracted
at 1.3 m using an increment borer (28–40 cores per site). The cores were visually
cross-dated following Yamaguchi (1991). Then, ring widths were measured to the
nearest 0.01mm using a semiautomatic ANIOL measuring device (Aniol, 1983)
and the resulting series were checked statistically using the program COFECHA
Characteristics of the A. alba sampled sites
Site Location Latitude(N) Longitude Span Elevation(m) Aspect
1 Aztparreta MAIN RANGE 42◦ 90 0◦ 78 W 1749–1999 1400 NE
2 Pe˜ a Oroel
n PERIPHERAL S RANGES 42◦ 55 0◦ 53 W 1889–2000 1650 NNW
3 Guara PERIPHERAL S RANGES 42◦ 30 0◦ 20 W 1893–1999 1500 NNE
4 Conangles MAIN RANGE 42◦ 63 0◦ 78 E 1578–1999 1800 N
5 La Mata de Val` ncia
e MAIN RANGE 42◦ 63 1◦ 06 E 1767–1999 1750 N
6 Boavi MAIN RANGE 42◦ 68 1◦ 32 E 1878–1999 1470 N
7 Boumort PERIPHERAL S RANGES 42◦ 20 1◦ 20 E 1804–1999 1583 N
8 Moixer´o PERIPHERAL S RANGES 42◦ 31 1◦ 81 E 1852–1999 1680 NW
9 Setcases MAIN RANGE 42◦ 39 2◦ 27 E 1777–1999 1750 NE
10 Montseny PERIPHERAL S RANGERS 41◦ 77 2◦ 43 E 1587–1999 1550 N
SPATIOTEMPORAL VARIABILITY IN RADIAL GROWTH
294 M. MACIAS ET AL.
2.1. RADIAL GROWTH CHANGES, STANDARDIZATION AND CHRONOLOGY BUILDING
In order to reconstruct and infer the logging history of the studied sites, we calculated
the percentage growth change for each individual tree-ring series in all the study
sites. To identify growth releases we used the formula proposed by Nowacki and
Abrams (1997): GC = 100 * [(M2–M1) / M1] × 100, where GC is the percentage
growth change between preceding and subsequent 10-yr ring-width means, and M1
and M2 are the preceding and subsequent 10-year means, respectively. A release
or abrupt growth recovery along an individual tree-ring series was deﬁned as any
GC > 75 %. We calculated the yearly relative frequency of releases per year for the
Main-Range and Peripheral-Range groups of sites.
In the case of mesic sites with a long history of logging, the only reliable
method able to produce complete chronologies without release signals was to ﬁt
a very ﬂexible smoothing spline (Cook and Peters, 1981), although it removed
a considerable amount of long– and mid-term climatic signal from the resulting
site chronologies. Splitting the series at the release years, as Blasing et al. (1983)
suggested, would create a missing period of several years in each series, which
would leave little chances for an inter-chronology comparison and climate response
Residual chronologies were used in the study since our purpose was mainly
dendroclimatic (Cook et al., 1990). Desplanque et al. (1998) showed that this stan-
dardization method extracted relevant climatic information from A. alba ring-width
series in Alps forests similar to ours. A spline length was needed which would be
ﬂexible enough to ﬁlter the series growth releases but still able to produce residual
series with climatic information. To solve this problem, we took the maximum
signal-to-noise ratio (SNR) criterion to the chronology level. SNR is a measure of
the common variance in a chronology scaled by a measure of the total variance
of the chronology (Wigley et al., 1984; Cook et al., 1990). We compared our 10
chronologies and quantiﬁed their common signal by means of the inter-chronology
SNR for spline lengths ranging from 5 to 50 years (Figure 2, left). The maximum
SNR for the residual chronologies was obtained for spline lengths of 15 years
(Figure 2). However, declines in the spline stiffness lead to a decrease in the 1st
order autocorrelation coefﬁcient of the resulting standard series (Figure 2, right).
SNR between residual chronologies started to decrease for splines shorter than 15
yrs. In the case of the trees and conditions we are dealing with, residual chronolo-
gies resulting from 15-yr spline standardizations constituted a trade-off between
an efﬁcient removal of the disturbance signal and problems related with adjusting
too ﬂexible curves to the growth-series (i.e. artiﬁcially creating negatively auto-
correlated series (blue noise) by removing low frequencies). Thus, all subsequent
analyses were performed using the 15-yr spline residual chronologies, and all the
results presented were derived from them. We assume that such a spline ﬁt may
remove much long- and mid-term variation from the series, so it must be noted
that our results are only referred to the short-term variation patterns of tree growth.
SPATIOTEMPORAL VARIABILITY IN RADIAL GROWTH 295
Inter-chronology S N R
4 -0.2 0 5 10 15 20 25 30 35 40 45 50 55
0 10 20 30 40 50 60 -0.8
Spline lenght (yr) L: Spline lenght(yr)
Figure 2. Left: Mean inter-chronology Signal-to-noise-ratio (SNR) vs. spline length in years (com-
parisons between residual (squares) & standard chronologies (triangles)). Right: ﬁrst-order autocor-
relation coefﬁcients (AC) versus spline length (the thick line is the mean of the 10 chronologies).
Despite SNR between standard chronologies increased at lower values of spline
stiffness (as low as 5 years) (Figure 2), such ﬂexible splines would imply a clear
loss of climatic signal. This was evidenced by an accelerated variance decrease in
all chronologies for spline lengths shorter than 10 years.
Descriptive statistics were calculated for each chronology to allow comparisons
among sites and with other dendroclimatic data sets (Fritts, 1976; Briffa and Jones,
1990). These statistics were: ﬁrst order autocorrelation (r1), the percentage of vari-
ation explained by the ﬁrst principal component (VARpc1), signal-to-noise ratio
(SNR), as well as standard deviation (SD) and mean sensitivity (MS). A time series
of year-to-year sensitivity indexes (St ) was also calculated for each chronology,
based on the formula St = | (It+1 − It ) * 2 / (It+1 + It ) |, for It = residual index
value for the year t (Fritts, 1976), to analyse the variation of each chronology. We
used the Expressed Population Signal (EPS) to establish a criterion to select a com-
mon period where all chronologies would be reliable enough (Wigley et al., 1984).
The common period 1902–1999 was selected based on a minimum EPS value of
0.85, which is a widely used threshold in dendroclimatic studies.
2.2. SPATIO-TEMPORAL VARIABILITY IN RADIAL GROWTH
Shared growth variability can be interpreted as a common response to regional
climatic signals (Tardif et al., 2003; Macias et al., 2004), and its changes along
the 20th century as a signal of climatic changes which have affected the growth of
silver ﬁr. Moreover, the spatial distribution of these relationships and their temporal
changes can also give information about homogeneous climatic areas or about where
climatic gradients are more important for tree growth (Villalba et al., 1997).
First, we performed a Principal Component Analyses (PCA) based on the cor-
relation matrix for the common period 1902–1999 to evaluate the shared variance
among residual chronologies. Pearson correlation and PCA were also computed for
296 M. MACIAS ET AL.
successive 20-yr periods with a 5-yr lag in order to evaluate the temporal changes
of this shared variability. We also assessed the spatial variability of radial growth
through the relationship between distance and correlation for pairs of chronologies
for the study period, as well as its changes along the 20th century. This is a good
way to analyze spatiotemporal relationships within a network of chronologies and
the existence (or not) of spatial gradients in Abies alba radial growth (Fritts, 1991).
2.3. RADIAL GROWTH RESPONSE TO CLIMATE
In mountainous regions such as the study area, temperature series have shown
stronger inter-site relationships between distant sites than precipitation data, which
are more variable locally (Agust´-Panareda et al., 2000). Seven sub-regional
monthly average temperature and precipitation data series were obtained from 27
meteorological stations in the area (Figure 1, Table II). Meteorological stations
were grouped according to their homogeneity based on the Mann-Kendall test us-
ing HOM routine from the Dendrochronology Program Library (DPL; Holmes,
1996). Sub-regional datasets were then produced using the MET routine from the
same software. These calculations are based on the average and standard deviation
of each month for each station. In addition, Main Range and Peripheral Ranges se-
ries of temperature and precipitation were constructed by combining the different
sub-regional data sets.
Five sub-regional datasets allowed a response function analysis for the period
1941–1994. Two of them, Montseny and Ripoll` s, started in 1951. Correlation and
response function analyses were performed for such periods using the program Den-
droclim2002 (Biondi and Waikul, 2003) to quantify the climate-growth relation-
ships between the different sets of regional climate series (monthly mean temper-
ature, monthly total precipitation) and the residual radial-growth chronologies. In
order to avoid the problem of multi-collinearity, commonly found in multi-variable
sets of meteorological data, Fritts (1976) introduced a stepwise multiple regression
on principal components to assess climate-growth relationships (response func-
tion). The signiﬁcance and stability of the calculated regression coefﬁcients were
estimated based on 1000 bootstrap estimates obtained by random extraction with
replacement from the initial data set (Guiot, 1991). Climate-growth relationships
were analyzed from the previous August up to September of the growth year. In
these analyses, we used the sub-regional dataset corresponding to the area where
each chronology was located.
We used evolutionary response functions to analyse how the growth-climate rela-
tionships changed through time and to detect these changes in the climatic response
of Abies alba. First, a regional chronology was created by performing Principal
Component Analyses on the chronology network. Two sub-regional chronologies
were also built with the same procedure: one for the Main Range group (sites 1,
4, 5 and 6 as in Figure 1) and one for the Peripheral Ranges group (sites 2, 3, 7, 8
Sub-regional temperature (T) and precipitation (P) studied datasets.
Sub Regional Temperature Precipitation
Climate Mean C Annual sum (mm) m
Series Total period 1941–1994 Total period 1941–1994 Station Latitude Longitude a.s.I. First Last First Last
Candanch´ u 42 47 19 − 00 32 14 1613 1951 1975 1951 1975
SPATIOTEMPORAL VARIABILITY IN RADIAL GROWTH
Jacetania/ 1910–1999 7.4 1910–1999 1655 Canfranc 42◦ 44 03 − 00◦ 31 24 1075 1910 1999 1910 1999
a Sallent de G´ llego
a 42◦ 46 26 − 00◦ 19 49 1285 1953 1994 1960 1999
Jaca 42◦ 34 05 − 00◦ 34 05 800 1943 1985 1930 1972
Jacetania/ 1941–1999 10.3 1941–1999 873 Sabi˜ anigo
n´ 42◦ 31 08 − 00◦ 21 38 790 1941 1995 1941 1999
Hoya Nocito 42◦ 19 24 − 00◦ 15 21 931 1973 2000 – –
n 42◦ 26 45 + 00◦ 04 00 643 – – 1951 1999
Cabdella 42◦ 27 55 + 00◦ 59 28 1270 1954 1992 1954 1994
Estany Gento 42◦ 30 28 + 01◦ 00 03 2120 1930 1985 1925 1985
Pallars 1940–1994 6.9 1926–1999 984 Estany de St. Maurici 42◦ 34 50 + 01◦ 00 17 1920 1953 2000 – –
Espot 42◦ 34 28 + 01◦ 05 21 1310 1953 1991 1953 1991
Esterri d’ Aneu 42◦ 37 27 + 01◦ 07 31 940 – – 1955 2000
Tavascan 42◦ 38 15 + 01◦ 15 07 1100 1967 1994 – –
Oliana 42◦ 05 00 + 01◦ 18 10 480 1931 1997 – –
Alt Urgell 1940–2000 11.5 1940–1996 660 Organy`a 42◦ 12 43 + 01◦ 19 46 540 1972 1999 1915 1999
Adrall 42◦ 19 25 + 01◦ 23 39 642 1940 1996 1933 1996
e 42◦ 33 + 01◦ 50 1600 – – 1966 1987
Cerdanya 1944–1996 7.9 1940–1994 902 La Molina 42◦ 20 02 + 01◦ 56 15 1704 1929 1998 1927 1998
a 42◦ 26 07 + 01◦ 56 16 1145 1911 2000 1912 1974
Mean values are shown for the common period used in the study (1941–1994). Positive longitude: Eastern Hemisphere; negative longitude: Western
Hemisphere. (Continued on next page)
Sub Regional Temperature Precipitation
Climate Mean C Annual sum (mm) m
Series Total period 1941–1994 Total period 1941–1994 Station Latitude Longitude a.s.I. First Last First Last
u 42 23 38 + 02◦ 09 20 1967 1950 1996 1934 1996
e 1951–1996 9.1 1951–1994 983 Ribes de Freser 42◦ 17 60 + 02◦ 10 00 912 1930 1994 1942 1988
Ripoll 42◦ 12 01 + 02◦ 11 23 690 1975 2000 – –
Vallter-2000 42◦ 26 06 + 02◦ 15 58 2180 – – 1961 1995
M. MACIAS ET AL.
Cardedeu 41◦ 38 11 + 02◦ 21 35 195 – – 1951 1997
Montseny 1911–1996 11.8 1951–1996 894 Tur´ de I’Home
o 41◦ 46 33 + 02◦ 26 03 1708 1961 1997 1932 1997
Girona 2 41◦ 58 20 + 02◦ 48 20 90 1975 1994 – –
Girona 1 41◦ 58 36 + 02◦ 49 30 94 1911 1977 – –
SPATIOTEMPORAL VARIABILITY IN RADIAL GROWTH 299
and 10 as in Figure 1). Second, we built a long climatic series (1910–1999) using
monthly meteorological data from Pic du Midi (B¨ cher and Dessens, 1991), and
Canfranc stations (see Figure 1 for location), which characterize well the climatic
variability in the Central Pyrenees during the 20th century (Tardif et al., 2003).
We performed evolutionary response functions based on the three different modes
available in Dendroclim 2002 (Biondi, 1997, 2000): (1) moving response intervals,
considering a 60-year ﬁxed interval, and increasing the initial and ﬁnal years of
the analyses by one for each iteration; (2) forward evolutionary intervals, using the
same initial year of the interval but increasing by one for each iteration the ﬁnal year
so that the intervals go progressively forward in time; (3) backward evolutionary
intervals, using a ﬁxed ﬁnal year of the interval, and decreasing by one for each
iteration the initial year, so that the intervals go progressively backward in time.
3.1. CHRONOLOGY STATISTICS
Statistical characteristics of the chronologies are shown in Table III. For the study
period 1902–1999, EPS values were > 0.85 in all chronologies but in three: Pe˜ a n
Oroel, Guara and Boavi showed values > 0.80 for this period. Their quality is still
very good and they were kept. First-order autocorrelation was very close to zero for
most of the standard chronologies due to the very ﬂexible spline (15 years) used in
the standardization (Figure 2). Mean sensitivity (MS) values were generally higher
for chronologies located in the Peripheral Ranges (e.g., 0.18 for Moixer´ , 0.15 for
Oroel, 0.14 for Guara) and lower for chronologies located in the Main Range (e.g.,
0.08 for Conangles, 0.11 for Boavi). Although this trend was observed, it was not
possible to separate two groups according to their MS values. However, time series
of Sensitivity (St ) gave more information (discussed later).
3.2. SPATIAL VARIABILITY IN RADIAL GROWTH
The average Pearson correlation coefﬁcient for the network of chronologies and
for the period 1902–1999 was 0.44 ± 0.09 (mean ± SD). All correlation pairs
were positive and highly signiﬁcant ( p < 0.01). The lowest correlation values were
found when comparing sites located in the Main Range against sites located in the
Peripheral Southern Ranges (sites 5 vs. 10 = 0.20; 4 vs. 8 = 0.28; 1 vs. 2 = 0.35;
see Figure 1 for name and location). Low correlation coefﬁcients were also found
between sites located at the western Peripheral Southern Ranges (wPSR) and sites
located at the eastern Peripheral Southern Ranges (ePSR) (sites 2 vs. 10 = 0.32; 2
vs. 8 = 0.31; 3 vs. 8 = 0.35). Highest values were achieved for pairs of chronologies
within the wPSR (sites 2 vs. 3 = 0.61) or within ePSR (sites 7 vs. 8 = 0.61), as
Chronology characteristics: expressed population signal (EPS), n◦ of cores, mean radial growth, mean sensitivity (MS), standard deviation (SD),
ﬁrst-order autocorrelation (r1), signal-to-noise ratio (SNR) and variance explained by the ﬁrst principal component (VARpc1). The common period
was set as 1902–1991
Radial Common interval:
growth Standard chronology Residual chronology 1902–1999 detrended series
EPS > 0.85 N◦ of mean (SD)
Study site since cores (mm) MS SD r1 MS SD SNR VARpc1
1 Aztaparreta 1844 28 1.83(0.17) 0.13 0.11 −0.01 0.13 0.11 8.53 42.51%
2 Pe˜ a Oroel
n 1905∗ 28 2.67(1.13) 0.14 0.13 −0.04 0.15 0.13 3.10 64.60%
3 Guara 1905∗ 30 2.99(1.20) 0.16 0.13 −0.13 0.13 0.12 5.95 77.68%
4 Conangles 1828 30 0.92(0.44) 0.11 0.09 0.07 0.09 0.08 7.00 45.87%
M. MACIAS ET AL.
5 La Mata de Val` ncia
e 1790 35 0.89(0.43) 0.13 0.11 −0.20 0.12 0.10 17.74 60.40%
6 Boavi 1903∗ 30 2.99(1.22) 0.11 0.09 0.02 0.11 0.09 5.68 52.02%
7 Boumort 1892 40 1.58(0.82) 0.14 0.14 0.08 0.14 0.13 6.55 40.08%
8 Moixer´o 1869 31 1.85(1.13) 0.16 0.14 −0.03 0.17 0.14 12.84 51.46%
9 Setcases 1886 31 2.05(1.14) 0.14 0.14 0.13 0.14 0.14 5.59 35.88%
10 Montseny 1871 30 1.23(0.68) 0.18 0.19 0.24 0.15 0.13 8.23 49.31%
EPS > 0.8 since: Pe˜ a Oroel, 1902; Guara, 1900 and Boavi, 1897.
SPATIOTEMPORAL VARIABILITY IN RADIAL GROWTH 301
well as for a pair within the Main Range (sites 1 vs. 9 = 0.63). Despite the spatial
coherence of these extreme values, a look at the bulk of correlation pairs did not
show a clear zonation.
The variance explained by the ﬁrst principal component (PC) of the PCA for
all residual chronologies was 49.43 %. The ﬁrst PC had positive loadings for all
chronologies, and it was interpreted as the common variability of the network of
chronologies, that is, as a macroclimatic signal. Thus, the time series of the ﬁrst
PC was used as a regional chronology. The second, third and fourth PCs explained
a cumulative variance of 25.2% and represented sub-regional to local sources of
3.3. TEMPORAL VARIABILITY IN RADIAL GROWTH
As a result of the management history of the studied stands, we found a high
frequency of releases when looking at the non-standardized raw growth data, most
probably due to logging, in the 1910s, 1920s and 1930s, which was higher in the
Peripheral-Ranges than in the Main-Range groups of chronologies (Figure 3). A
Frequency of growth-changes > 0.75 (%)
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990
Figure 3. Inferred logging history in the studied sites based on the yearly relative frequency of radial-
growth changes greater than 75%. Results are presented separately for the Peripheral-Ranges and
302 M. MACIAS ET AL.
P e ars o n C o rrelation C o efficient
y = 0.0132x + 0.3323
30 2 0.3
R = 0.6812
y = 1.1224x + 41.429
20 Fmodel=32.0477, p<0.0001 0.2
R2 = 0.6648
Slope: t=5.66, p<0.0001
Figure 4. Pearson correlation coefﬁcients for the A. alba chronology network (20-yr periods with
a 5-yr lag, squares) and percentage of variance expressed by the 1st component of the PCA (20-yr
periods with a 5-yr lag, triangles). Linear regressions were applied in both cases. Continuous line box
contains statistics from the linear regression for the % of Variance of the 1st PC. Dashed line box
contains statistics from the linear regression for the Pearson Coefﬁcients. Both cases showed highly
signiﬁcant ( p < 0.0001) models (F test) and slopes (t test).
high frequency of positive growth changes greater than 75% was also observed
in the 1950s, this time being higher in the Main-Range sites. Since the 1960s the
frequency of releases has greatly decreased, except for a slight increase in the late
Both average Pearson correlation and variance explained by the ﬁrst PC of the
ten residual chronologies showed a signiﬁcant increase in the common variability
of chronologies along the 20th century (Figure 4). Correlation values and variance
explained by the ﬁrst PC rose from r = 0.31 and 38.8 % in the beginning of the 20th
century to r = 0.58 and 62.6 % in the end of the analyzed period. The cumulative
variance of the second, third and fourth PCs showed a steady and signiﬁcant decline
during the 20th century from 38.7% to 26.3%, which implied a decrease in sub-
regional to local variability (not shown). Both the linear regressions and their slopes
were highly signiﬁcant ( p < 0.0001). Thus, the common macroclimatic signal
(common variability) has been increasing markedly during all the studied period.
The relationships between inter-site correlation and distance have also steadily
increased during the 20th century (Figure 5). During the ﬁrst half of the 20th century
(1902–1950), correlation between pairs of chronologies decreased signiﬁcantly ( p
< 0.05) with increasing distance between sites, i.e., there was a spatial gradient in
the growth of A. alba in the Pyrenees. However, the gradient disappeared during the
second half of the century (1951–1999), when distant chronologies showed more
similar growth patterns than before. Thus, for the ﬁrst half of the 20th century, local
or at least sub-regional features had a stronger effect on silver ﬁr growth in the Pyre-
nees than for the second half, when the signal of regional factors became dominant.
SPATIOTEMPORAL VARIABILITY IN RADIAL GROWTH 303
0.8 y = 3E-05x + 0.4996
R2 = 0.0003
0.7 Fmodel=0.0128, p>0.1
Slope: t=0.11, p>0.1
0.2 y = -0.0005x + 0.4373
R2 = 0.106
0.1 Fmodel=5.0969, p<0.05
Slope: t=-2.26, p<0.05
0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0
Figure 5. Correlation coefﬁcients vs distance between chronologies. The relationship was negative
and signiﬁcant for the period 1902–1950 (squares), while it disappeared for the period 1951–1999
(triangles). Note also the higher correlation values for the second half 20th century.
Some series of year-to-year sensitivity (St ) showed great variability, whereas
others were more regular throughout the 20th century (Figure 6). Two groups were
formed according to the variances of St of each chronology (t-test, p < 0.005),
which were different by one order of magnitude: a high variance of St Group:
sites 2, 3, 7, 8, 9 and 10 (see Figure 1 and Table I for names and location), and
a low variance of St Group: sites 1, 4, 5 and 6. Note that all chronologies of the
low variance group are located in the Main Range, whereas all chronologies of the
high variance group but one (Setcases, site 9) are located in the Peripheral Ranges.
Although being located in the Main Range, Setcases has the particularity of being
the closest site to the Mediterranean Sea, only ca. 65 km from it, and so a higher
Mediterranean inﬂuence in terms of precipitation regime is expected for this site
than for the other Main Range sites.
We found peaks in St around 1930s, 1960s and 1980s, which reached much
higher values in the high-variance than in the low-variance group. Sensitivity
increased during the 20th century ( p < 0.05), but the increase was stronger in the
high-variance group (Figure 6). During the second half of the 20th century, there
was a strong and highly signiﬁcant ( p < 0.0001) increase in St in the high-variance
group, whereas no signiﬁcant increase could be detected in the low-variance one.
3.4. RADIAL GROWTH-CLIMATE RELATIONSHIPS
All sub-regional datasets showed a Mediterranean inﬂuence characterized by pre-
cipitation maxima in spring and autumn, and a relative minimum in summer
(Figure 1). Annual precipitation was highest in the westernmost site (Jacetania-
304 M. MACIAS ET AL.
High Variance Group
y = 0.0004x - 0.6775 y = 0.0021x - 3.995
R = 0.0808 R2 = 0.3725
. , Fmodel=26.114, p<0.0001
Slope t=2.76, p=0.007
t= , Slope: t=5.11, p<0.0001
e: 0. 1
Year-to-year sensitivity( St)
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Low V a riance G r oup
y = 0.0002x - 0.3729 y = 0.0005x - 0.8849
0.5 R = 0.0807 R 2 = 0.
odel=7.635, Fmodel=2.628, p>0.1
0.4 Slope: t=2.76, p=0.007
e: Slope: t=1.62, p>0.1
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Figure 6. Year-to-year sensitivity time series (St ) for the two groups of chronologies: high variance
of St (up), low variance of St (down). The thick line is a 10-yr centred running mean. The dashed
straight line is a linear regression for the period 1902–1999, whereas the continuous straight line
is a linear regression for the sub-period 1950–1999. Note that the maximum values observed in the
high-variance group were much higher than those reached by the low-variance group.
G´ llego: Table II, Figure 1), where climate is under greater oceanic inﬂuence, and
lowest in the stations far from the sea (Alt Urgell). We noted a general process of
aridiﬁcation in all datasets during the 20th century. Taking the period 1941–1994
as the study period, annual mean temperature has been rising, especially since the
1970s (Figure 7.A, B). The temperature increase was observed both in winter (De-
cember to March) and summer (July, August) months. The temperature increase in
winter was more pronounced in the Western and Central Main-Range sub-regions,
SPATIOTEMPORAL VARIABILITY IN RADIAL GROWTH 305
Figure 7. (A). Recent trends (slope of the linear regression; b in y = a + bx) of monthly mean
temperature and monthly total precipitation for the seven sub-regional datasets and Pic du Midi
climate data (abbreviations follow Figure 1). Squares correspond to p < 0.05. The period analysed is
1941–1994, except for Montseny and Ripoll` s (1952–1994) (B). Two examples of the recent climatic
trends starting in the 1980s (aridiﬁcation) corresponding to the average departures for the seven sub-
regional datasets (see Figure 1) in mean July temperature and total August precipitation from the
whereas the summer warming was more intense in the Central Pyrenees sub-regions.
In some cases, precipitation sums have also been declining, especially in summer
(July, August) and March. Positive trends in precipitation were observed in October
everywhere and their value decreased eastwards. The two easternmost sub-regions
(Ripoll` s and Montseny) did not show these trends, but a process of temperature
increase was evident since the 1970s. Generally, the temperature rise and the precip-
itation decrease in February, March, July and August have been more pronounced
since the 1980s (Figure 7.B)..
306 M. MACIAS ET AL.
Table IV summarizes the general climate response for all sites based on the
relationships between A. alba regional chronology (the ﬁrst Principal Component
of the chronology network) and the regional climatic series for all the study area, and
also separately for the Main Range and the Peripheral Ranges. Variance explained
by the ﬁrst PC was 58.6% and 52.8%, for the Main-Range and Peripheral-Ranges
groups, respectively. As mentioned in methods, these PCs were used as the Main-
Range and Peripheral-Ranges sub-regional chronologies.
All chronologies showed signiﬁcant responses to the climate conditions of the
late summer prior to the growth year, especially a negative and generalized re-
sponse to September temperature (Table IV). During the year previous to tree-ring
formation, tree-growth showed signiﬁcant (p < 0.05) positive relationships with
August precipitation for the Main Range chronology, and, to a lesser degree, with
September precipitation for the Peripheral Ranges chronology. During the growth
year, radial growth was positively related to February temperature and to July pre-
cipitation (restricted to the Peripheral Ranges Chronologies). Response functions
performed for each individual site with the climatic data of the closest sub-region
climate series showed similar results, with the only difference being a more ex-
tended negative response to previous late summer temperature by the Main Range
Chronologies (August to October) (not shown).
3.5. TEMPORAL INSTABILITY OF GROWTH-CLIMATE RELATIONSHIPS
We analysed the moving-interval response functions based on 60-yr intervals for the
regional chronology, and for the Main-Range and Peripheral-Ranges sub-regional
chronologies (Figure 8). The negative response to previous August temperature has
extended until October, and a positive response to previous August precipitation has
shown to be important, extending into September during the 1980s. Both changes
suggest a longer water-stress season during the year prior to growth at the end
of the 20th century than at the beginning of the past century. When performing
the sub-regional analyses, we found slightly different results for the Main Range
and the Peripheral Ranges chronologies. From 1986 to 1999, negative responses
to previous October temperature appeared in the Main Range, whereas positive
responses to previous August precipitation became stronger at the end of the 20th
century. Positive responses to previous summer precipitation extended from August
to September in the Peripheral Ranges from 1986 to 1993; for the same period,
negative responses to previous September temperatures were also found in the
Peripheral Ranges. During the year of tree-ring formation, the negative effect of
August precipitation in the Main Range was not signiﬁcant since 1982. The positive
effect of current July precipitation in the Peripheral Ranges weakened and June
precipitation became more important for tree growth at the end of the 20th century.
The analyses based on forward and backward evolutionary intervals conﬁrmed
these ﬁndings (results not presented).
Correlation (C) and response (R) functions based on bootstrap correlation and orthogonal regression on residual chronologies
and monthly climate data from previous September to current August (months abbreviated by capital letters correspond to the
year of growth). Results correspond to the regional (up), the Main-Range (middle) and the Peripheral-Ranges chronologies
(down). Only signiﬁcant values are presented ( p < 0.05)
Year t − 1 Year t
SPATIOTEMPORAL VARIABILITY IN RADIAL GROWTH
Chronology Variable Analysis a s o n d J F M A J J A S
Regional T C −0.52 0.37
P C 0.31 0.29 0.21
Main range T C −0.35 −0.49 0.35
P C 0.31 0.29
Peripheral range C −049 0.34
C 0.28 0.31
The analyses are based on regional climatic series (T, mean monthly temperature; P, total monthly precipitation) for all the
study area, the Main Range and the Preipheral Ranges covering the 1941–1994 period. The window starts with August of
previous year (t − 1) and ends with September of the year of growth (year t, months abbreviated by capital letters). Only
bootstrap correlation (C) and response (R) signiﬁcant values are displayed ( p < 0.05).
308 M. MACIAS ET AL.
1970 1975 1980 1985 1990 1995 1970 1975 1980 1985 1990 1995 2000
Time (60-year intervals)
Main Range Peripheral Ranges
T P T P
197019751980198519901995 197019751980198519901995 197019751980198519901995 1970197519801985199019952000
Time (60-year intervals)
Figure 8. Moving-interval response functions showing the signiﬁcant coefﬁcients ( p < 0.05) based
on the relationships between mean monthly temperature (T) or total monthly precipitation (P) and the
Regional (up), Main-Range (down and left) and Peripheral-Ranges (down and right) chronologies.
Months abbreviated by capital letters correspond to the year t of growth, and the rest of months
correspond to the previous year t − 1. The displayed years in the abscissa axis correspond to the last
year of 60-yr moving intervals. The symbol type indicates the type of relationship: circles, negative
coefﬁcients; squares, positive coefﬁcients. The symbol colour indicates the strength of the relationship:
grey symbols, coefﬁcient = 0.1–0.2; black symbols, coefﬁcient = 0.2–0.3.
SPATIOTEMPORAL VARIABILITY IN RADIAL GROWTH 309
Standardizing the series with a ﬂexible spline produced reliable chronologies since
A. alba climatic signal was successfully extracted, as seen in the response functions,
which show similar patterns and magnitudes to those found in the Alps for the same
species (Rolland, 1993; Desplanque et al., 1998; Rolland et al., 1999). The spatial
synchrony between sites was low in 1902–1950 (r < 0.4 at distances > 100 km)
but high in 1951–1999 (r > 0.5 at distances > 200 km), which partially agrees
with results presented by Rolland (2002). These ﬁndings emphasize the greater
local variability in radial growth of low-elevation species from mesic sites such
as A. alba, which caused the low spatial synchrony between sites in the ﬁrst half
of the 20th century. However, during the second half of the last century, A. alba
showed a greater similarity in radial growth at long distances, which suggests that
a regional climatic factor was modulating radial growth (Tardif et al., 2003). This
last behaviour was similar to that usually observed for conifers from high-elevation
and harsh sites such as P. uncinata, which usually show greater inter-site similarity
in radial growth at long distances (>500 km). Spatial synchrony between distant
chronologies is a valuable property for dendroclimatic reconstructions, but our
study has demonstrated that it may not be ascribed only to species from harsh sites.
The studied area has shown a trend towards an aridiﬁcation during the 20th
century, especially since the 1970s and 1980s (Figure 7). In NE Iberian Peninsula,
a greater drought stress might have been induced by the recent warming detected
in the Pyrenees starting in the 1980s, which caused severe summer droughts in
the 1980s and 1990s (B¨ cher and Dessens, 1991; Tardif et al., 2003; Brunet et al.,
2005). Southern-Pyrenean areas close to the Mediterranean Sea did not show a
decrease in precipitation (Pi˜ ol et al., 1998).
Silver ﬁr response to summer drought seems to be general as inferred from
the presented response functions (Table IV). Drought during the summer prior
to growth was the most limiting factor for radial growth, which agrees with the
“drought-avoidance” strategy of the species (Rolland et al., 1999; Aussenac, 2002).
A. alba has lower water-use efﬁciency than other ﬁr species from more xeric areas
(Guehl and Aussenac, 1987; Guehl et al., 1991). Thus, it is expected that A. alba
would be a species highly sensitive to drought.
Increasing water stress during the second half of the 20th century might be the
cause of the higher synchrony in tree growth (Figure 4) and the increase in year-to-
year sensitivity (Figure 6). An elongation of the period of water stress might explain
why silver-ﬁr growth shifted in the mid 1980s from being sensitive to August
temperature to being sensitive up to September and even October temperature
(Figure 8). Other authors noted similar growth responses in the Pyrenees in other
subalpine conifers (P. uncinata) during this decade (Guti´ rrez et al., 1998; Tardif
et al., 2003).
The stands in the Peripheral Ranges have experienced these changes with special
intensity, as seen in the higher increase of sensitivity when compared with the
310 M. MACIAS ET AL.
Main Range chronologies, which showed an increase in the length of previous
late summer temperature response. Peripheral chronologies showed this response
and also a shift in the response to precipitation from previous August to previous
September in the second half of the 20th century (Figure 8). Besides, they showed
positive relationships with current early summer precipitation, which changed from
July at the beginning of the study period to June at its end, also suggesting an
elongation of the water stress period (Figure 8). These results are logical since these
peripheral forests grow under the most stressful conditions (drier climatology).
Main Range sites are usually located at the bottom of upper valleys or on N-
NW slopes, at the base of high mountains (2500 to 3000 m). Snowmelt during
late spring and summer could guarantee water supply in the soils of these sites, as
they do not show any positive response to current late spring-summer precipitation.
However, Peripheral Ranges are lower (usually less than 2000 m) and dryer, with
silver ﬁr forests located in northern slopes not far away from the summit. In this
case, there is probably not much water supply coming from snowmelt and Peripheral
Chronologies show a current late spring-summer positive response to precipitation.
The positive inﬂuence of February temperature on growth (Table IV) is probably
comparable to the positive response to current March temperature in the French Alps
for the same species (Rolland et al., 1999). Warmer Februaries might accelerate
snowmelt (or at least stop snow accumulation), favouring soil warming and thus
enhancing an earlier start of the growing season. However, the effect of cold winters
on A. alba growth over the area might not be strong and general given the fact that
such relationship did not show to be signiﬁcant when performing the bootstrap
response functions and only showed signiﬁcance in the less restrictive correlation
Silver-ﬁr populations have been receding in the Iberian Peninsula after their
post-glacial expansion (Huntley and Birks, 1983) due to climate, but also because
of competition with Fagus sylvatica in the last four millennia (Blanco et al., 1997)
and intense logging in the last centuries (Jalut, 1988). Nowadays, A. alba reaches its
SW distribution limit in the Pyrenees, where previous summer drought is a major
limiting factor for silver ﬁr growth. Due to the ecological requirements of silver ﬁr,
most of the Iberian Peninsula under Mediterranean inﬂuence constitutes a ‘desert’
to the species, which only ﬁnds ‘oasis’ in very special places such as northward
slopes and valley bottoms where slope aspect, moist climate and deep soils allow
it to strive. These places are mainly located in the Main Range, where most of A.
alba forests are found. The scattered small stands in the southern Peripheral Ranges
form relict populations of former glacial refuges whose future growth performance
is uncertain under current warming trends in the light of our results. The presented
climatic signal extracted from Abies alba growth series makes this species a reliable
monitor of the effects of climate change on forests in the Pyrenees. More efforts
should be put to improve the present network of chronologies, especially in the
central Pyrenees, and to relate their growth patterns to current climatic patterns
including synoptic situations, with the aim of assessing their potential association
SPATIOTEMPORAL VARIABILITY IN RADIAL GROWTH 311
with different phases of the North Atlantic Oscillation and other regional to global
climate patterns relevant in the area.
This study was funded by EU project For MAT (Sensitivity of tree-growth to climate
change and growth modelling from past to future), contract ENV4-CT97-0641, as
well as by a CICyT (AMB95-0160) project. Marc Macias Fauria acknowledges
the support of a CIMO – Centre for International Mobility – fellowship, code
TM-03-1535, given by the Finnish Ministry of Education, as well as the good
advices of Samuli Helama at the Department of Geology of the University of
Helsinki, and Aslak Grinsted and John Moore at the Arctic Centre in Rovaniemi.
J. J. Camarero acknowledges the support of an INIA-Gob.Arag´ n post-doctoral
contract. We also thank Montse Ribas and Elena Munt´ n for their help in core sam-
pling and cross-dating, as well as for their contribution in the climatic dataset. We
thank S.H. Schneider, two anonymous referees and F. Biondi for their constructive
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(Received 26 October 2004; in revised form 16 December 2005)