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Author's personal copy
Forest Ecology and Management 257 (2009) 773–781
Contents lists available at ScienceDirect
Forest Ecology and Management
journal homepage: www.elsevier.com/locate/foreco
The impact of sea erosion on coastal Pinus pinea stands:
A diachronic analysis combining tree-rings and ecological markers
Sabrina Raddi a,*, Paolo Cherubini b,1, Marco Lauteri c,2, Federico Magnani d,3
a
DISTAF, Università degli Studi di Firenze, Via San Bonaventura 13, 50145 Florence, Italy
WSL, Zuercherstrasse 111, CH-8903 Birmensdorf, Switzerland
c
CNR-IBAF, Viale Marconi 2, 05010 Porano, Italy
d
DCA, Università di Bologna, Via Fanin 46, 40127 Bologna, Italy
b
A R T I C L E I N F O
A B S T R A C T
Article history:
Received 22 March 2008
Received in revised form 7 September 2008
Accepted 11 September 2008
Coastal erosion is a widespread phenomenon on sandy coasts throughout the Mediterranean region;
along the Thyrrenian coast of Tuscany (Italy), stone pine (Pinus pinea L.) stands originally planted for the
protection of agricultural crops further inland are often damaged. In the present study, a pairwise
comparison of stands at different distance from the sea at eroded and control sites highlighted the effects
of coastal erosion alone on pine growth and function. Dendroecological analyses made it possible to
determine the temporal dynamics of the phenomenon since 1930 and the interactions with climate,
whilst additional structural (LAI, sapwood area) and functional (carbon isotope discrimination)
measurements were used to discriminate between stress mechanisms. Salty winds, exacerbated by the
removal of dunal vegetation, were found to be the most likely cause of the observed growth decline. The
presence and, in more recent times, the reduction of surfactants in sea water played an important
synergistic effect. The intrusion of salty water in the water table, on the contrary, played a marginal role at
the site. Finally, stressed trees were more sensitive to the inter-annual variability in precipitation; at all
sites, growth was stimulated by June, November and December precipitation in the current and two
preceding years.
ß 2008 Elsevier B.V. All rights reserved.
Keywords:
Dendrochronology
Coastal erosion
Pollution
Salt stress
1. Introduction
Coastal forests provide important functions by stabilizing sand
dunes and defending crops from salty winds and surfactants
damages. The spread of human settlements in coastal areas has
increased both environmental concerns and the recreational value
of coastal forests (Pezeshki et al., 1990; Williams et al., 1999; Pilker
and Cooper, 2004). Eustatic sea-level rise, in combination with a
reduced sediment input from fluvial discharge, has resulted over
the last decades in widespread coastal erosion for more than twothird of the global extension of sandy coastlines (Bird, 1985); in the
Mediterranean region, about 30% of the entire coastline is affected
by erosion (EEA, 2006). Despite large inter-annual fluctuations
(List et al., 1997), sea-level rise has been found to follow variations
* Corresponding author. Tel.: +39 055 3288653; fax: +39 055 319179.
E-mail addresses: sabrina.raddi@unifi.it (S. Raddi), [email protected]
(P. Cherubini), [email protected] (M. Lauteri), [email protected]
(F. Magnani).
1
Fax: +41 44 739 2 215.
2
Fax: +39 0763 374980.
3
Fax: +39 051 2096401.
0378-1127/$ – see front matter ß 2008 Elsevier B.V. All rights reserved.
doi:10.1016/j.foreco.2008.09.025
in global temperature with a considerable acceleration in recent
years (Holgate and Woodworth, 2004; Church and White, 2006).
According to commonly accepted models of coastal dynamics
(Bruun, 1988; Davidson-Arnott, 2005), an increase in coastal
erosion should be therefore expected for the future together with
an increase in the vulnerability of coastal ecosystems (IPCC, 2007).
Coastal erosion is thought to affect plant function and growth
mainly as a result of salty spraying and sea water intrusion in the
water table, both worsening vegetation water status (Kozlowski,
2000); plant vulnerability to water stress could be therefore
expected to increase in areas affected by shoreline regression, and
an understanding of past impacts by ecological and dendrochronological techniques could provide a hint of future patterns.
The reconstruction of past coastal erosion is also critical for
predictive purposes (Crowell and Leatherman, 1999). Even
considering the diversity of shoreline behaviour and the changing
dynamics of the processes involved, data obtained from long-term
(>100 years) shoreline mapping can be considered a reliable tool
for assessing shoreline recession rates and for predicting its future
position with reasonable confidence (Galgano and Douglas, 2000).
Maps and charts of sufficient accuracy have been available for parts
of Western Europe and North America for the past two centuries,
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S. Raddi et al. / Forest Ecology and Management 257 (2009) 773–781
but for much of the world’s coastline there is little information
preceding the advent of aerial photography in the last few decades
(Bird, 2000). The analysis of dendrochronological series may
therefore provide a useful dataset for the reconstruction of past
coastal dynamics, as well as of their effects on forest conditions.
Tree-rings have been widely used in the reconstruction of past
climate, i.e. precipitation in arid regions, and temperatures at highlatitude and -elevation sites (Hughes, 2002). However, they have
been used only occasionally to reconstruct sea-level rise (Robichaud and Bégin, 1997) or similar events such as shore erosion
(Bégin and Payette, 1991; Bégin et al., 1991), lake level fluctuations
(Bégin, 2000a), and lakeshore erosion (Bégin, 2000b), stream
erosion (Warren, 1961) and, recently, salinity of water table (Stahle
et al., 2001). Such studies were based on the evidence that plant
recruitment and tree growth are limited by sea vicinity, and treerings were used retrospectively for reconstructing past local
coastal erosion rates (Wiles et al., 1998).
In the present study, dendrochronological techniques have
been applied to estimate the effects of past coastal erosion on two
Italian stone pine (P. pinea L.) stands growing under contrasting
erosion regimes on the Mediterranean coast. Moreover, being
tree growth influenced by the interactions between erosion,
vicinity to the sea, climate and water table salinity, the impact of
sea erosion on the response of this species to precipitation has
also been evaluated. The specific hypothesis was tested that, by
worsening the water status of the plant, coastal erosion should
increase the sensitivity of pine growth to precipitation. Finally,
additional measurements were taken in order to elucidate the
functional basis for the observed response of pine growth to
coastal erosion.
Shoreline erosion estimates were derived from data reported in
Albani et al. (1940), from 1:5000 thematic regional maps reporting
shoreline position in years 1938, 1955, 1977 and 1984 (Bartolini
et al., 1989), from 1:5000 forest management maps for years 1942
and 1971 (Giordano, 1947; Baroni, 1976), from 1:2000 and
1:10,000 regional technical maps for year 1993 and from aerial
ortho-photographs taken in 1996.
2.2. Structural and functional measurements
For each sample plot, tree density (N, trees ha1), diameter at
breast height (DBH, cm) for all trees and height (H, m) of the three
trees nearest to the plot centre were measured. Tree volume was
derived from diameter and height using site-specific allometric
equations (Baroni, 1976) and summed up to obtain stand volume
(VOL, m3 ha1). Leaf area index (LAI, m2 m2) was estimated from
hemispherical photographs (Welles and Cohen, 1996) taken at the
centre of each plot, with a 16 mm Nikon fisheye lens attached to a
Nikon FM2 camera. Time exposure was determined with 18 spot
light meter (Sekonic Dual-Spot F L-778) pointed at the zenith
within a canopy gap. Negatives were scanned at 2800 dpi and
analysed by the Hemiview Canopy Analysis software (Delta-T
Devices, Cambridge, UK). At the end of April, pine needles (1-yearold or older) from the upper canopy were collected for each plot,
dried and analyzed for carbon isotope composition by a mass
spectrometer (Isochrom II; VG Isotech, Middlewich, UK) following
the methods described in detail by Lauteri et al. (2004). Carbon
isotope composition (d13C) and discrimination (D) were computed
as (Craig, 1957):
d13 C ¼ ðRsample =Rstandard Þ 1
(1)
D ¼ ðdair dneedle Þ=ð1 þ dneedle Þ
(2)
2. Materials and methods
2.1. Study site and sampling scheme
A 465 ha Pinus pinea plantation stretching for 15 km along the
Tyrrhenian Sea on both sides of the Cecina River estuary (438180 N,
108290 E, Italy) was selected as a test site. The pine forest is part of
the ‘‘Tomboli di Cecina’’ Natural Reserve; it was planted for the first
time in 1839 after a century of land reclamation efforts started in
1740 (Repetti, 1833; Gatteschi and Milanese, 1990). The forest is
homogenous for seed origin and management (Bassi, 1927;
Giordano, 1947; Baroni, 1973), but it faces coastal sectors with
different erosion regimes. The soil at the site is sandy (Typic
Xeropsamments according to local soil maps; USDA, 1999). The
area is characterized by a thermo-mediterranean sub-humid
climate (Blasi, 1996). Average annual precipitation in the area is
778 mm, with a minimum in July (21 mm) and a maximum in
October (114 mm). Average annual temperature is 15.3 8C (ranging
from 7.2 8C in January to 24.4 8C in August), average potential
evapotranspiration (Thornthwaite, 1948) is 951 mm, and from
Walter and Lieth thermo-pluviometrical diagram summer drought
lasts 2 months (July and August). Two areas with contrasting
coastal erosion regimes were selected 1 km North (ERD, eroded)
and 5.2 km South (CNT, control) of the Cecina River estuary. Twelve
transects were located in each area, perpendicular to the coastline
and spread over 1 km along the coast; in each transect a pairwise
sampling scheme was applied, comparing circular sample plots of
314 m2 located within the P. pinea stand at a distance of 30 and
105 m, respectively, from the seaward forest margin (hereafter
named sea and int, for interior). Four environmental conditions
were therefore compared (ERDsea, ERDint, CNTsea, CNTint),
corresponding to a 2 2 replicated experimental design. The four
plots were located at a distance from current seashore position of
80, 155, 245 and 320 m, respectively.
where R is the 13C/12C ratio in the sample and in the PDB standard,
and dair and dneedle are d13C for source atmospheric CO2 and needle,
respectively.
2.3. Dendroecological analyses
Two wood cores were extracted from each of the two trees
nearest to the plot centre with an increment borer at a height of
1.3 m from North and South direction. The transition to sapwood
was visually determined on each core; sapwood area was
extrapolated to the stand level using tree basal area as a scaling
factor. Cores were then mounted on channelled wood, carefully
dried and sanded for tree-ring analysis. The five outermost treerings were used to calculate tree current annual basal area
increment (BAI, cm2 ha1 year1). Ring-widths were measured to
the nearest 0.01 mm, using the Time Series Analysis Programme
(TSAP) measurement equipment (Lintab) and software package
(Frank Rinn, Heidelberg, Germany). Raw ring widths of the single
curves of each dated tree were plotted, visually and then
statistically crossdated by (a) the Gleichläufigkeit method, which
is the percent agreement in the signs of the 1st differences of two
time-series, and by (b) Student’s t-test, which determines the
degree of correlation between the curves.
Standard methods were used to build a mean series for each of
the four environmental conditions. Ring-width measurements for
a given calendar year from different trees were averaged into mean
series. A series of mean annual ring-width chronologies contains
different signals that can be described by the general model
proposed by Cook et al. (1990). Different signal types may be
detected over short time-scales (i.e. affecting inter-annual
variability or climate responses through time) or longer time-
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S. Raddi et al. / Forest Ecology and Management 257 (2009) 773–781
scales (as underlying trends). Standardization, which is the
removal of long-term variations from a time series of measured
ring widths by dividing the measurements by a standardizing
smoothing function, and their conversion to a time series of ringwidth indices (Fritts, 1976), is commonly used to remove agerelated sample bias. Standardisation, however, is sometimes
avoided since by removing the low-frequency variability attributable to stand dynamics it also removes other low-frequency
signals (Cook et al., 1990; Briffa et al., 1996). Different approaches
were used in the present study for the analysis (a) of the long-term
effects of coastal erosion on growth and (b) of pine sensitivity to
water availability under different erosion regimes. In the first
analysis, standardisation would have removed together with agerelated effects also the long-term dynamics which were the subject
of the study. Therefore no smoothing function was applied, but the
analysis was based on tree basal area increments, which are less
affected by tree age and dimensions than radial increments.
Because of a combination of tree allometry and applied thinning
regime, tree basal area is closely related to total stand volume in P.
pinea stands along the Tuscany coast (Castellani, 1982). Age effects
were removed, on the contrary, in the analysis of pine growth
sensitivity to annual and monthly precipitation, through the
application of a smoothing function following standard dendroecological procedures. In a first step, any ageing effects (long-term
trends included) were removed by modelling the ring-width series
(dependent data) as a Hugershoff function of cambial age
(independent data) and indexing procedure used (Fritts, 1976).
Afterwards, stepwise regressions and response functions were
performed with the ARSTAN and Precon51 software package (Cook
and Holmes, 1996). The analysis was based on monthly precipitation data for the period 1921–1995 recorded at a meteorological
station nearby (Cecina, station n. 2240; Annali idrologici Part I,
1921–2001); gaps in the dataset were filled with records from
other stations within 10 km and at similar altitude (Bolgheri, n.
2258; Vada, n. 2050), cross-calibrated with the main dataset.
2.4. Data analysis
A factorial ANOVA model with site (S) and distance from sea (D)
as sources of variation was applied at plot-level to main stand
parameters. The effect of coastal erosion on tree growth was
assessed quantitatively by a pairwise analysis, based on the
comparison of pairs of plots located in the same transect but at
variable distance from the sea, so as to minimize the effects of
between-site differences and extract only the effects of coastal
erosion on tree growth. Growth differences between stands will
result from a large number of site-specific factors (e.g., local
climate and fertility, age, management), the influence of the sea
and coastal erosion being only one among the others. The
assumption is made that, at any one site, all other environmental
factors can be considered constant and that differences within a
transect are the effect only of variable distance from the sea.
Growth is therefore represented as the product of two factors:
Isea ¼ Isite f sea
The fsea reduction factor was computed for each of the 12 transects
per site, and the statistical significance of the effects of erosion
(Derosion) then analyzed for each year by a two-tailed Student’s ttest (Sokal and Rohlf, 1981).
3. Results
3.1. Coastal erosion and pine growth
Since the middle of the 19th century, when the pine forest was
first established along the Cecina coast, shoreline position has
retreated at both sites (Fig. 1). Starting from the first decades of the
20th century, however, a much higher erosion rate has been
observed at the ERD (about 1.6 m year1 in the 1913–1985 period)
than at the CNT site (0.5 m year1 retreat in the 1913–1972
period). By 1985 much of the dunal vegetation in front of the pine
forest had disappeared at the ERD site, exposing pine trees directly
to the effects of marine aerosols. After 72 years of shoreline
regression, however, a reversal of the trend has been observed at
ERD since then, with an accretion of about 0.7 m year1. The more
moderate erosion at the CNT site also lasted a shorter period (59
years), with an accretion of 0.2 m year1 thereafter (Fig. 1).
Stand age, basal area and leaf-to-sapwood area did not differ
significantly as a result of site or distance from the sea (Table 1).
When comparing the two sites, pines at ERD were on average more
densely stocked and smaller in diameter than at CNT, irrespective
of distance from the sea. As for all other variables, ANOVA showed
that site did not consistently affect height, stand volume, leaf area
index and tree basal area increments. The results of the pairwise
analysis suggest that, despite potential problems related to their
location on opposite sides of the river mouth, the ERD and CNT
sites did not differ in background fertility, as height and stand
volume away from the sea differed by no more than 1.2 and 2.5%,
respectively. Considering the effects of distance from the sea,
significantly lower values of diameter, height, stand volume, tree
basal area increments and LAI were consistently observed in the
plots near the coast. The decrease in stand basal area and the
higher stand density near the sea, on the other hand, were not
statistically significant (Table 1). A significant interaction
between the two sources of variation (site and distance from the
sea) was observed for leaf area index (p = 0.004) and diameter
(p = 0.042; Table 1); in all cases, a higher reduction at ERDsea than
at CNTsea was observed, relative to the stands further inland
(Table 1).
The pairwise analysis of current forest characteristics further
illustrates the increasing detrimental effects of proximity to the
(3)
where maximum growth for the site (Isite), as realized far away
from the sea, is increasingly limited by the reducing factor fsea as
one approaches the shore. It is further assumed that, in the absence
of coastal erosion, vicinity to the sea has the same relative effect on
growth at all sites. Erosion will exacerbate the effects of vicinity to
the sea; its impact can be therefore quantified as the difference in
fsea between eroded and control sites, denoted as Derosion:
ERD
CNT
Derosion ¼ fsea
fsea
775
(4)
Fig. 1. Coastal line evolution since 1820 at the two test sites: eroded (black circle)
and control (gray circle) sites. Periods: 1820–1934 (Albani et al., 1940), 1938–1984
(Bartolini et al., 1989); years: 1946, 1979 (Baroni, 1973) and 1996 (Orthophoto
AIMA, 1996).
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S. Raddi et al. / Forest Ecology and Management 257 (2009) 773–781
Table 1
Pinus pinea pinewood traits tested by significance p-levels for analysis of variance (ANOVA) effects (S = site, D = distance from sea and S D = interaction) and by Tukey’s post
hoc comparison of the means at eroded (ERD) and control (CNT) sites for seawards (sea) and interior (int) plots.
Trait
ANOVA p-levela
S
D
SD
ERDsea
ERDint
CNTsea
CNTint
Age (year)
Tree diameter, DBH (cm)
Tree total height, H (m)
Stand density, N (tree ha1)
Stand basal area, BA (m2 ha1)
Stand volume, VOL (m3 ha1)
Tree basal area increment, BAI (cm2 tree1 year1)
Leaf area index, LAI (m2 m2)
Leaf-to-sapwood ratio, LA:SA (m2 cm2)
Foliage carbon isotope discrimination, D (0/00)
ns
ns
ns
**
**
*
ns
*
**
ns
ns
ns
ns
ns
ns
ns
63 1 a
31.3 0.4 a
15.5 0.3 ab
377 57 b
29.7 4.6 a
221.2 34.6 a
6.1 0.8 a
2.5 0.3 a
0.14 0.03 a
20.4 0.1 a
65 1 a
37.2 0.5 b
16.0 0.3 b
313 25 ab
34.7 2.1 a
283.7 17.8 a
9.7 0.9 b
4.5 0.3 b
0.19 0.01 a
20.4 0.3 a
63 1 a
39.3 0.7 c
14.8 0.3 a
236 20 a
29.4 1.2 a
251.1 11.4 a
8.0 0.8 ab
3.8 0.2 b
0.19 0.01 a
20.4 0.1 a
62 1 a
43.0 0.7 d
15.8 0.2 ab
220 18 a
32.6 1.9 a
291.1 18.4 b
9.6 0.7 b
4.2 0.2 b
0.20 0.02 a
20.4 0.1 a
a
b
*
**
ns
ns
ns
ns
ns
ns
*
**
Tukey–Kramer’s HSD testb
**
*
ns
ns
ns
ns
Plot-level analysis, df = 1, 44 for each ANOVA effects; ns = not significative.
Mean standard error. Means within row followed by the same letter were not significantly different (p 0.05).
p 0.05.
p 0.01.
sea under conditions of shoreline regression (Table 2). The fsea
factor, computed for each variable according to Eq. (3), quantifies
the relative effect of proximity to the sea at each site, so that the
difference between the two sites (Derosion; Eq. (4)) captures the net
effect of shoreline regression at ERD on forest growth next to the
coast. The greatest effects are observed for LAI (36%) and tree
basal area increments (29%), whilst smaller effects are observed
for other structural variables such as tree height and diameter and
stand basal area and volume, which integrate the effects of
proximity to the sea over the entire lifetime of the stand, including
the period before the onset of differences in shoreline regression. A
higher stand density, on the contrary, was observed as a result of
shoreline regression (Derosion = +20.2), but this was presumably
just the result of the reduced growth, which led to a delay in
imposed thinnings; at all sites, the Reineke’s relationship (Reineke,
1933) between stand density and average DBH closely adhered to
what prescribed by local growth and yield tables (Meschini, 1959;
Baroni, 1973; data not shown). However, a direct effect of erosion
on tree mortality at the ERD site was evidenced by the high
variability among transects in stand density close to the sea,
together with a lower variance in tree volume among plots in
comparison with the other treatments (Table 1).
Dendroecological techniques made it possible to extend back
into the past the same pairwise approach described above, so as to
investigate the time dynamics of the effects of erosion. The net
difference between the two sites oscillated around zero until 1975
(Fig. 2B), albeit with a period of statistically higher growth
(p < 0.05) at ERD relative to CNT between 1935 and 1972, and two
periods with lower growth at ERD in the years 1955–1958 and
1967–1971, with minima in 1955 and 1968 of 21 and 17%,
respectively. A much more pronounced absolute minimum was
then observed in the period 1977–1979, with a growth reduction
as a result of erosion of about 58%; but since 1984 a partial recovery
was observed, resulting in a new equilibrium status corresponding
to a growth reduction of about 20%. This pattern was not apparent
when considering the dynamics of the fsea reduction factor
computed at the ERD site alone (Fig. 2A), so demonstrating the
need for the pairwise approach adopted here: although a
worsening of the detrimental effects of the sea was observed at
the eroded site after 1970, the marked negative peak in the period
1977–1979 is only apparent from a comparison with the control
site.
Table 2
Pairwise analysis of current values of stand structure and growth. For each variable,
the fsea factor (Eq. (2)) represents the relative reduction induced by the proximity to
the sea; the Derosion (Eq. (3)) captures the increased impact of proximity to the sea at
the eroded (ERD) than at the control site (CNT).
Variable
DBH (cm)
H (m)
N (tree ha1)
BA (m2 ha1)
VOL (m3 ha1)
BAI (cm2 tree1 year1)
LAI (m2 m2)
LA:SA (m2 cm2)
a
b
fsea (%)a
Derosion (%)b
ERD
CNT
ERD-CNT
p-Value
16.2 2.3
2.4 3.0
31.4 25.4
8.8 17.7
17.1 16.2
29.3 9.3
35.6 10.3
18.0 19.8
7.2 3.3
4.4 2.2
11.2 8.8
4.3 9.6
7.2 11.0
10.9 10.7
5.7 6.2
7.3 8.3
8.9
2.0
20.2
4.5
9.8
18.4
29.9
25.3
0.032
0.588
0.442
0.817
0.606
0.190
0.017
0.228
Means standard errors over the 12 transects at each site.
Significant Derosion (in bold) are based on Student’s t-test.
Fig. 2. Long-term dynamics of coastal erosion and effects of proximity to the sea on
P. pinea growth. (A) Dynamics of the effects on growth of proximity to the sea, as
captured by the factor fsea (Eq. (2); mean S.E.), at the eroded (ERD) site. (B) Coastal
erosion trend at the control (CNT, gray circles) and eroded (ERD, black circle) sites and
time series of Derosion, the additional effect of coastal erosion at the eroded relative to
the control site (Eq. (3); mean S.E.).
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777
Fig. 5. Pearson correlation coefficient (r) between tree-ring growth index and total
rainfall in the whole year and in the single months of the current year (year 0) and of
the three preceding years (year-1, -2 and -3). Dotted lines indicate 1% and 5%
significance levels.
Fig. 3. Relationship between stand leaf area index (LAI, m2 m2) and sapwood area
(SA, m2 ha1) at the two study sites and at variable distance from the sea.
Mean S.E. (n = 12).
3.2. Ecological determinants of pine growth
The analysis of ancillary variables of ecological significance
provides additional information on the functional determinants of
the observed growth decline. At the tree level, sapwood area (Sa)
resulted a rather constant fraction of basal area (Ba; Sa:Ba = 0.697,
R2 = 0.802, p < 0.001, n = 192) for tree diameters over bark ranging
from 19 to 56 cm, making it possible to compute sapwood area at
the stand level (SA) and its relationship with leaf area. For all
treatments, except for ERDsea, leaf area index and sapwood area
were found to be linearly related (LAI, m2 m2 = 0.185 SA,
m2 mm2; R2 = 0.998, p < 0.001; Fig. 3); on the contrary, at ERDsea
a lower leaf area-to-sapwood area ratio was maintained. In
contrast with the observed differences in tree functional structure,
no reduction in carbon isotope discrimination (), an integrated
measure of water use efficiency, was observed for P. pinea at Cecina
as a result of erosion or distance from the sea (Table 1).
3.3. Climatic variables and pine growth
Age-detrended tree-ring widths were higher than average for
all treatments in the 1960–1969 period (Fig. 4), with a marked
peak in 1961; over this period, detrended ring widths were wider
at ERD than at CNT (+34%), and at the eroded site more near the sea
Fig. 4. Long-term dynamics of tree-ring width, detrended for the effects of age, at
the eroded site near the sea (ERDsea, black bold line) and interior (ERDint, black thin
line) in comparison with control site by the sea (CNTsea, gray bold line) and interior
(CNTint, gray thin line). Dotted lines represent the overall average and 99%
confidence intervals (mean + 3S.E.).
(+19%) than in the interior. The period was characterized by aboveaverage precipitation rates (data not shown). Over the entire
period investigated, tree-ring index averaged over the four
treatments was positively and significantly related to total annual
precipitation of the current year and of the year preceding radial
growth (Fig. 5); coming to consider the effects of monthly
precipitation, ring-width was significantly correlated to the
rainfall amount of June and November of the current year, and
June, November and December of the previous year (Fig. 5). Treering width was also positively correlated with spring (March–May;
r = 0.284*) and autumn (September–November; r = 0.271*) precipitation of the current year, but not with winter nor summer
rainfall of the current year (data not shown).
The positive effect on growth of the combination of intense
autumn and spring precipitation is even more evident when
looking at the correlation with rainfall cumulated across a number
of months of the current and the two preceding years. When
considering the 630 possible combinations of any 2 months in the
period, the best relationship with ring-width index (RWI, 105 m)
was observed for the cumulated precipitation (P, mm) in
November and December (r = +0.528, RWI = 1.78P + 661.28;
Fig. 6) and June and December of the year preceding growth
(r = +0.496, RWI = 2.22P + 727.12) or November of the current and
of the previous year (r = +0.486, RWI = 1.28P + 722.8). Even when
considering precipitation in any 3 months from current and the
two previous years, the highest regression coefficients were
obtained for precipitation in June, November and December in
the previous year (r = +0.625, RWI = 1.90P + 562.98). However,
growth appeared to be particularly stimulated by a sequence of
rainy periods over consecutive years. Three consecutive years of
high precipitation in June, November and December showed the
Fig. 6. Pearson correlation coefficient (r) between tree-ring growth index and the
sum of precipitation in the period November–December of the previous year and in
any two successive months of the current year (year 0) or of the previous year. The
dotted line indicates 1% significance level.
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S. Raddi et al. / Forest Ecology and Management 257 (2009) 773–781
Fig. 7. Tree-ring width index (105 m) at ERDsea (black dots) and CNTsea (circles) in
relation to cumulated rainfall over 3 years (current year and the previous 2 years)
for the months of June, November and December (r = 0.82***) and, in the inset for the
cumulated rainfall in the months of November and December alone (r = 0.75***).
Regression lines are drawn for ERDsea (
), ERDint (– –), CNTsea (—), CNTint (- ), and for the average of the four areas (— -).
highest Pearson correlation coefficient (r = +0.811), much higher
than if only the precipitation in the same period for the current
year or the current year and the year before were considered
(r = +0.460 and r = +0.736, respectively). This optimal combination
of periodic precipitation across years was therefore used for the
comparison of growth sensitivities among sites and with distance
from the sea. The relationship is shown in Fig. 7 for the individual
areas (ERDsea, ERDint, CNTsea and CNTint) as well as for their
average. The eroded site showed a greater sensitivity to climate
with higher slope and regression coefficient both near the sea
(ERDsea, r = +0.820, RWI = 2.08P 427.9) and in the interior
(ERDint, r = +0.794, RWI = 1.54P 60.97), relative to the control
site near the sea (CNTsea, r = +0.700, RWI = 1.01P + 309.69) and in
the interior (CNTint, r = +0.720, RWI = 1.09P + 251.10). The same
pattern was observed for the correlation with rainfall in November
and December cumulated over 3 years, albeit with lower r
coefficients (inset in Fig. 7).
4. Discussion
The most important environmental variables controlling the
Mediterranean distribution of P. pinea have been reported to be the
average temperature of the coldest month, determining plant
survival, and winter precipitation, being largely responsible for
growth rates (Thuiller et al., 2003a,b); the high sensitivity of
growth to precipitation has also been confirmed by Boreux et al.
(1988) and Raventós et al. (2001). This is particularly true for the
study site, where groundwater flow is reduced and water table
recharge is mainly related to local precipitation (Baldini et al.,
2004). The relationship between tree-ring index and monthly
rainfall, with a high sensitivity to rainfalls events in November and
December and in the period from March to July (Figs. 5 and 6),
largely reflects the seasonal course of environmental factors. P.
pinea has a drought-tolerant strategy with a strongly reduced
photosynthetic activity in presence of water stress and elevated
vapour pressure deficits (Awada et al., 2003), as commonly
observed in summer and early autumn (Teobaldelli et al., 2004).
Although a true winter dormancy has been observed in P. pinea in
response to low temperatures (Liphschitz et al., 1984), secondary
growth is still active in autumn, as a result of renewed water
availability and mild temperatures (Poupon, 1970; Castellani,
1979; Cherubini et al., 2003).
In the present study, growth was particularly stimulated when
favourable environmental conditions were repeated over successive years; moreover, growth appeared to be more affected by
above-average precipitation than by drought conditions: if we
consider only years with a cumulated rainfall in June, November
and December over 3 years of less than 700 mm (almost 60% of the
dataset), no relationship between tree growth index and precipitation is apparent (r = 0.066ns). The greater sensitivity at the
ERD site demonstrates the important interaction between climatic
conditions and shoreline regression.
The shoreline regression dynamics reported at the Cecina river
mouth during the past 150 years are rather common for rivers of
the Tyrrhenian coast of Tuscany, and are mainly related to reduced
sediment discharge. Over the preceding 2500 years, the estuary of
the main rivers in Tuscany had prograded of about 7 km, with
dynamics highly sensitive to changes in land use in the catchment
area: a rapid expansion of estuaries occurred between the XVI and
XVIII century because of the high sediment load carried by rivers,
following the expansion of farming and deforestation (Pranzini,
1995). As a reversal of this trend, the main causes of the recent
coastal erosion regime were recognized in mountain reforestation,
river damming, river bed quarrying and wetland reclamation
(Albani et al., 1940; Woodward, 1995; Pranzini, 2001). Coastal
erosion, even if evident at both sites, differed in intensity, with 125
and 75 m shoreline retreat for ERD and CNT, respectively, in the
140-year period between 1846 (when the pine forest was first
established) and 1985. In the period 1954–1985, in particular, a
total retreat of about 55 and 6 m was reported for ERD and CNT,
before the eventual stabilization of the beach in 1989–1991 by
means of groins and submerged breakwaters (Cipriani et al., 1993).
A comparison with the description of vegetation facies in the 1947
management plan (Giordano, 1947) exemplifies the evident
changes brought about by the contrasting erosion regimes. At
the control site no clear changes in vegetation zonation can be
observed from the situation described in 1947. At the eroded site,
on the contrary, shoreline regression has strongly altered the
vegetation pattern. Whilst in 1906 and still in 1926 a 40 m wide
zone of maquis vegetation was reported to protect a 90 m wide
Pinus pinaster stand in front of the P. pinea forest, in 1947 the
maquis area had been almost completely eroded and the P. pinaster
stand was beginning to decline. In 1996, the P. pinea stand stood
40–80 m from the shoreline, separated by a 20–30 m wide strip of
sclerophyllous maquis under sparse P. pinaster trees, the remnants
of the 90 m wide P. pinaster dense stand described by Giordano
(1947).
The combination of structural and dendroecological measurements has shown that a substantial growth reduction was
associated with shoreline regression in the P. pinea stand. The
retrospective analysis was based on a carefully cross-comparison
with a pairwise design, which made it possible to extract a
disturbance signal which otherwise would have been obscured by
other co-occurring long-term patterns. A strong decline was
observed at the eroded site in proximity to the sea in the period
1974–1984, with a maximum growth reduction in 1978 (73%); in
the following years, pines at ERDsea found a new equilibrium, with
growth rates around 25% lower than could be expected in the
absence of erosion. ANOVA and post hoc Tukey’s tests on present
structural variables confirmed the above results, as lower values of
tree basal area increments and LAI were found at ERDsea relative to
the other plots.
Ancillary ecological measurements also make it possible to
discriminate between alternative hypotheses about the functional
determinants of such a growth reduction. The progressive erosion
of the coast resulted in a strong variation in the growth
environment for P. pinea at the ERDsea site, with (i) a greater
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S. Raddi et al. / Forest Ecology and Management 257 (2009) 773–781
exposure of the crowns to salty winds and surfactants and (ii) an
increased salinity of the water table; both factors could have
contributed to the observed growth decline. P. pinea is highly
sensitive to exposure both to sea spray and to surfactants in marine
aerosols (Raventós et al., 2001; Rettori et al., 2005). Sea spray can
result in an increased chloride content in needles, damaging
almost completely the leaf for contents higher than 0.8% d.w.
(Lapucci et al., 1972; Lorenzini and Guidi, 2001). A synergistic
effect due to seawater contamination with anionic surfactants was
recognized to be the cause of forest decline in proximity of river
mouths, a problem particularly relevant until 1980, when sea
aerosols from the Northern Tyrrhenian Sea contained high levels of
surfactants (18–29 mg l1; Bussotti et al., 1983). More recently,
much lower values have been recorded (0.96–1.30 mg l1;
Nicolotti et al., 2001), due to the higher biodegradability of
detergents and the lower consumption of poorly biodegradable
organic ingredients (PBO), whose use was reduced in Italy by about
39% by 1996–2001 (EC Commission, 2004). Surfactants cause the
deterioration of epistomatal wax structure (Bussotti et al., 1997)
and reduce the surface tension of water, so favouring the needle
uptake of NaCl (Richard et al., 1996; Nicolotti et al., 2005). On the
Tyrrhenian coast, sea spray-exposed P. pinea needles showed 3–12
times higher chloride ion content compared to the opposite part of
the crown, as well as more negative midday water potentials
(Nicolotti et al., 2001, 2005), with higher water stress at increasing
doses of surfactant concentrations in sprayed water (Rettori et al.,
2005).
At our site, death of pines was reported since the end of the
1950s, becoming particularly relevant where erosion attacked the
dune profile (Lapucci et al., 1972; Paiero, 1971) and in proximity of
river mouths polluted with surfactants (Cantiani, 1971). The
protective effects of the coastal dune at the control site is
highlighted by the low surfactant concentration found in rainwater, which in the early 1980s typically contained 0.11 mg l1 at a
distance of 200 m from the sea, down from a maximum of
0.64 mg l1 (Bussotti and Grossoni, 1995).
The reduced distance between the pine stand and the shoreline
could also have influenced the NaCl content of the water available
to pines. Water table salinisation has been found to be a major
determinant of pine forest decline as a result of sea-level rise (Ross
et al., 1994), and salt intrusion into the water table has been
suspected to be the cause of the dieback of maritime pine stands in
the France coastal range (Guyon, 1991). NaCl toxicity reduces
shoot growth by suppressing leaf initiation and expansion, and by
accelerating leaf abscission (Kozlowski, 2000). As a result of water
stress and stomatal limitations, reduced photosynthetic rates were
also observed in pines in response to salinisation (Kozlowski,
1997); carbon isotope discrimination is therefore found to be
reduced in pine trees affected by severe salt stress (Ross et al.,
1994).
Drought-like effects associated with salinity have been
observed in several Mediterranean pines. In P. pinaster seedlings,
salinity reduced gas exchange and growth already at a NaCl
concentration of 50 mM (Loustau et al., 1995). In contrast, P. pinea
appears to be a relatively salt-tolerant species. Salt accumulation
was observed in P. pinea seedlings without any growth reduction
until the NaCl content of irrigation water reached 7 dS m1
(roughly corresponding to 70 mM NaCl), whereas needle chlorosis,
reduced needle expansion and accelerated shedding and finally
higher plant mortality rates were induced only by much higher
saline levels (11–22 dS m1; Barbolani et al., 1997). Similarly high
levels of water table salinity have indeed been found to induce a
marked reduction in summer sap flow (Teobaldelli et al., 2004),
needle length (Piussi and Torta, 1994) and diameter growth (Piussi,
2002) in a P. pinea plantation growing in central Italy under severe
779
saline conditions (16–19 dS m1, corresponding to a NaCl concentration of about 160–190 mM).
Salt concentration levels in the water table at the study site
appear to be well below these critical thresholds for P. pinea.
The water table at the study site is superficial and slightly
higher at CNT than at ERD (1.2 and 1.9 m, respectively, in
September 1971; Baroni, 1976). Even at the eroded site, however,
the water is only slightly saline: annual average values of chlorine
concentration of 11.0 mM have been recorded at the ERD site in
2001 (Provincia di Livorno, 2001), a figure very close to the value of
12.7 mM measured in 1971 by Baroni (1976). Even lower chlorine
concentrations were measured at the control site (6.2 mM Cl1 and
2.5 mM Cl1 in 2001 and in 1971, respectively); both sites showed
a similar intra-annual absolute variation of chlorine of about 2 mM
with a spring minimum (10.6 and 5.2 mM Cl1 at the ERD and CNT
sites, respectively) and a maximum in autumn (12.5 and 7.2 mM
Cl1). Water table salinisation is therefore unlikely to have
contributed to the observed growth decline at the site investigated
in the present study. The low NaCl concentrations reported in the
literature for the study sites are consistent with the evidence from
carbon isotope discrimination: crown needles did not show any
differences in D, indicating a similar level of water stress and water
use efficiency for the four treatments (Farquhar et al., 1989;
Warren et al., 2001). Rather, sea spray exposure appears to be the
main factor responsible for decreased growth, possibly as a result
of foliage death and the ensuing reduction in leaf area index and
light interception (Table 1); the observed decline in leaf area-tosapwood area ratio at the eroded site (Fig. 3) would be consistent
with this hypothesis, being the result of the extensive needle loss
and of the high longevity of sapwood in P. pinea (47.4 0.7 years).
The origin of the marked negative peak in Derosion (Fig. 2),
however, cannot be explained by coastal dynamics alone. The
dendroecological analysis demonstrates that such a transient is not
related to climatic effects, either. Although the analysis demonstrated a greater sensitivity to precipitation at the eroded site, and
in particular for the trees close to the sea, the years corresponding
to the observed transient did not present abnormal values of the
climatic variables which were found to be best correlated with pine
growth.
In conclusion, the observed negative peak in Derosion in the
period 1974–1984 does not appear to be the result of exceptional
climatic conditions; rather, above-average precipitation in the
period 1976–1981, together with a more pronounced response to
the increased water availability at the eroded site, could have
slightly reduced the magnitude of the effect. One possible
explanation for the observed transient could be related, on the
contrary, to the more strict legislation introduced in Italy at the
beginning of the 1980s, which effectively reduced the concentration of anionic surfactants in effluents and therefore in marine
aerosols (EC Commission, 2004). Although the removal of the
protective belt of halophyte and maquis vegetation in front of
the forest is still exacerbating the negative effects of proximity to
the sea, in the absence of a synergistic effect with surfactants and
following the stabilisation of the shoreline the impact of coastal
erosion on pine growth would appear to be far less extreme. These
complex dynamics could be documented through the pairwise
approach adopted in the present study, which could be usefully
applied to other dendroecological investigations of the long-term
effects of natural and anthropogenic disturbances.
Acknowledgements
The work was supported by the Italian Ministry of University
(Project IMPAFOR - Impact of climate change on forests and wood
production. Prot. 9807388499). We gratefully thank Dr. Paul Van
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Gardingen (University of Edinburgh, UK) for help with hemispherical photographs and to Dr. Otto U. Bräker (WSL, CH) for
advice in the dendrochronological analysis.
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