Quaternaire
Revue de l'Association française pour l'étude du
Quaternaire
vol. 26/1 | 2015
Volume 26 - numéro 1
Using stable isotopes of oxygen from tree-rings to
study the origin of past flood events: first results
from the iberian peninsula
Utilisation des isotopes stables de l’oxygène des cernes d’arbres pour déterminer
l’origine des inondations passées : premiers résultats pour la péninsule ibérique
Juan Pedro Ferrio, Andrés Díez-Herrero, Daniel Tarrés, Juan Antonio
Ballesteros-Cánovas, Mònica Aguilera and José María Bodoque
Publisher
Association française pour l’étude du
quaternaire
Electronic version
URL: http://quaternaire.revues.org/7172
DOI: 10.4000/quaternaire.7172
ISSN: 1965-0795
Printed version
Date of publication: 1 March 2015
Number of pages: 67-80
ISSN: 1142-2904
Electronic reference
Juan Pedro Ferrio, Andrés Díez-Herrero, Daniel Tarrés, Juan Antonio Ballesteros-Cánovas, Mònica
Aguilera and José María Bodoque, « Using stable isotopes of oxygen from tree-rings to study the
origin of past flood events: first results from the iberian peninsula », Quaternaire [Online], vol.
26/1 | 2015, Online since 01 March 2017, connection on 27 February 2017. URL : http://
quaternaire.revues.org/7172 ; DOI : 10.4000/quaternaire.7172
© Tous droits réservés
Quaternaire, 26, (1), 2015, p. 67-80
USING STABLE ISOTOPES OF OXYGEN FROM TREE-RINGS
TO STUDY THE ORIGIN OF PAST FLOOD EVENTS:
FIRST RESULTS FROM THE IBERIAN PENINSULA
n
Juan Pedro FERRIO1, Andrés DÍEZ-HERRERO2, Daniel TARRÉS1,
Juan Antonio BALLESTEROS-CÁNOVAS3, Mònica AGUILERA1
& José María BODOQUE4
ABSTRACT
Tree-ring studies have been used for over fifty years to date and quantify past flood events. Stable C and O isotopes in
tree-rings have also been extensively applied to the reconstruction of past environmental conditions and their changes over time.
However, the two approaches have not previously been combined. In this study we explore whether the meteorological origin of
precipitation causing past flood events might be assessed by investigating oxygen stable isotopes in tree rings. It is well known that
floods may have different origins, e.g. heavy convective rainstorms, frontal precipitation, snow melting, etc.; each of these floodwater
sources bears a particular isotopic fingerprint.
This paper presents the first results of this methodology applied to a recent flash flood event occurring in Central Spain. For this
purpose, a well-known heavy-rain convective event was chosen from the recent flood record. In the forested area affected by this
event, six cores from each of four selected species (Pinus sylvestris L., Pinus pinaster Ait., Quercus pyrenaica Willd. and Alnus
glutinosa (L) Gaertn), were sampled using an incremental borer. After α-cellulose extraction, the oxygen-isotope composition (δ18O)
in tree-rings was analyzed and compared with climate data and δ18O values in precipitation. The isotope signal in tree-ring cellulose
was dominated by spring climatic conditions but, after removing this “spring signal”, a clear and site-specific signal in latewood
δ18O emerged, which was associated with the heavy-rain event. These preliminary results encourage more in-depth analyses aimed at
recognizing specific precipitation sources and separating different populations of past floods according to their cause.
Keywords: dendrogeomorphology, isotopes, past floods, meteorology
RÉSUMÉ
UTILISATION DES ISOTOPES STABLES DE L’OXYGÈNE DES CERNES D’ARBRES POUR DÉTERMINER L’ORIGINE
DES INONDATIONS PASSÉES : PREMIERS RÉSULTATS POUR LA PÉNINSULE IBÉRIQUE
Depuis un peu plus de cinquante ans, l’étude des cernes des troncs d’arbres a été utilisée pour dater et quantifier les inondations
passées. Les isotopes du carbone et de l’oxygène présents dans les cernes ont également été largement étudiés pour reconstituer les
conditions environnementales passées et leurs fluctuations au fil du temps. Jusqu’à présent, ces deux méthodes n’avaient pas été
associées. Cette étude vise à déterminer si l’origine météorologique des précipitations responsables des crues par le passé peut être
évaluée à travers l’étude des isotopes stables de l’oxygène présents dans les cernes. Il est bien connu que les crues peuvent avoir
différentes origines ou causes (orages, précipitations frontales, fonte des neiges, etc.). Chacune de ces causes se caractérise par une
empreinte isotopique particulière.
Cet article présente les premiers résultats de cette méthode appliquée à une crue-éclair récente qui s’est produite dans le centre de
l’Espagne à la suite d’un épisode de fortes pluies convectives. Dans la zone forestière touchée par cet événement, six échantillons
de chacune des quatre espèces sélectionnées (Pinus sylvestris L., Pinus pinaster Ait., Quercus pyrenaica Willd. et Alnus glutinosa
(L) Gaertn) ont été prélevés à l’aide d’une sonde Pressler. Après extraction de la cellulose, la composition de l’isotope oxygène des
cernes a été analysée et comparée avec les données climatiques et les valeurs de δ18O des précipitations. Le signal isotopique en
cellulose des cernes a été dominé par des conditions climatiques de printemps, mais, après la suppression de ce « signal de printemps », un signal clair et spécifique a été perçu dans le bois d’été δ18O. Ce signal a été associé à un événement de pluie intense. Ces
résultats préliminaires permettent d’envisager une meilleure reconnaissance de l’origine des précipitations et de classer les crues
passées selon leurs causes.
Mots-clés : dendrogéomorphologie, isotopes, anciennes crues, météorologie
Dep. Crop and Forest Sciences, AGROTECNIO CENTRE - University of Lleida, Avda. Rovira Roure 191, ES-25198 LLEIDA.
Emails: [email protected], [email protected], [email protected]
2
Geological Survey of Spain (IGME), Ríos Rosas 23, ES-28003 MADRID. Email: [email protected]
3
Dendrolab.ch, University of Bern, Baltzerstrasse 1+3, CH-3012 BERN. Email: [email protected]
4
Mining and Geological Engineering Department, University of Castilla-La Mancha, Campus Fábrica de Armas, Avda. Carlos III, Toledo,
ES-45071 TOLEDO. Email: [email protected]
1
Manuscrit reçu le 30/12/2013, accepté le 23/04/2014
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1 - INTRODUCTION
Floods are one of the most catastrophic natural hazards
in the world, causing thousands of casualties and great
economic loss (Pielke Jr. & Downton, 2000; Mitchell,
2003; Barredo, 2009). Integrated strategies for flood-risk
mitigation invariably include a detailed flood frequency
analysis (FFA) using a statistical approach (Gumbel,
1941; Kidson & Richards, 2005; Merz & Blöschl, 2008).
In the case of gauged basins, the FFA uses mathematical
models (a combination of a frequency-distribution function and a parameter fitting procedure) on the series of
river discharges (e.g. annual series of maximum daily
average stream flows), as a single population of data
(Bobée et al., 1993). Nevertheless, floods may have
different origins and causes, such as heavy convective rainstorms, persistent frontal precipitation, snow
melting, dam failure, etc., and thus cannot be considered
as repeated events (Merz & Blöschl, 2003; Díez-Herrero
et al., 2009). In several areas, flood events combine two
or more of these origins during each year or even during
the same season. In this regard, flood-frequency analysis
has often failed to take into account the division of
stream flows according to their origin (Botero & Francés,
2010). For recent flood events it is easy to use national
weather forecast services bulletins, which have been
available since the early-mid 20th century. However, for
flood events that took place prior to weather forecasts the
origin of flood-inducing precipitation events is unknown
and discharge events of different origins are mixed together within the series of extreme events. This contradicts
one of the main principles of statistics: the separation of
populations prior to analysis.
Tree-ring studies have been used for over fifty years to
analyze flood frequency and magnitude. This is termed
dendrogeomorphology or dendrohydrology, which
are two subdisciplines of dendrochronology. From the
pioneers (Sigafoos, 1964) to recent reviews of the state of
the art (St. George, 2010; Stoffel & Wilford, 2012; DíezHerrero et al., 2013a,b), dendrogeomorphological techniques have enabled us to date past flood events, estimate
discharge magnitude, calibrate roughness parameters (a
distributed calibration of Manning’s n values; Ballesteros
et al., 2011) and even compute the velocity and depth of
previous flooding from tilted trees (Díez-Herrero et al.,
2013a,b).
Stable and radiogenic isotopes in tree-rings have also
been used for several years to reconstruct past environmental conditions (i.e., temperature, precipitation
and water availability) and their pattern of change (see
e.g. McCarroll & Loader, 2004; Ferrio & Voltas, 2005;
Aguilera et al., 2011; Gessler et al., 2014). In particular,
the oxygen-isotope composition (δ18O) of plant tissues
reflects the variation in (1) δ18O in source water, (2)
evaporative enrichment of leaf water due to transpiration,
and (3) biochemical fractionation during the synthesis of
organic matter (Yakir, 1992; Farquhar & Lloyd, 1993).
Generally, the δ18O of source water is strongly dependent
on that of rain water (δ18OR). δ18OR is mainly determined by the temperature of droplet formation, which
1501-012-Mep1-2015.indd 68
is higher with higher temperatures (Dansgaard, 1964).
Other factors, such as altitude, precipitation intensity and
origin, also affect δ18OR; thus, particular rain events may
show a distinct isotopic signature (Poussart & Schrag,
2005; Díaz et al., 2007; Liu et al., 2008). Although the
isotopic signature of organic matter is also affected by
leaf-level processes (for further details, see Farquhar
& Lloyd, 1993), in the case of cellulose, about 50 % of
the leaf-level signal is further exchangeable with xylem
water (Sternberg et al., 2006). This exchange is the main
driver for the observed relationship between the δ18O of
tree-ring cellulose and δ18OR, as it enhances the original
source-water signal, softening the effect of leaf-level
enrichment (Saurer et al., 1997; Anderson et al., 1998;
Barbour et al., 2001; Offermann et al., 2011). Thus, treering δ18O has the potential to record the isotopic signature of precipitation events, and therefore to characterise
precipitation events from different origins.
However, to date the two approaches (dendrohydrology and stable isotopes) have not been combined. One
possible application of this integration might be to
improve flood-frequency analysis for hazard-and-risk
assessment. In this regard, we hypothesize that, in a
similar way to the dating of flood events using dendrogeomorphic techniques based on anatomic evidence, it
may be possible to associate past flood events with their
meteorological origin by means of tree-ring isotopes.
This paper proposes an innovative approach that could
improve flood-frequency analysis by incorporating stable
isotope data, using a case study to get a first insight into
its possibilities and limitations. This year-by-year or
even intraseasonal decoding of isotopic information may
represent a powerful tool both for the reconstruction of
past extreme flood events and in its application to the
assessment and prevention of natural risks, by means of
the incorporation of historical and palaeoflood data into
flood frequency analysis. Nevertheless, since the isotope
signal is derived from a complex combination of physiological and environmental signals, we also assume that
the extreme-event signal may be masked by long-term
responses, mainly associated with the prevailing meteorological conditions and the physiological attributes of
different species. Accordingly, we have also assessed the
responses of different functional types to average and
extreme events, in order to clarify which would be the
best candidate for our proposed approach.
2 - MATERIAL AND METHODS
2.1 - CONCEPTUAL FRAMEWORK
The theoretical framework for the proposed approach
is summarized in fig. 1. Given the existing variability in
isotopes from precipitation, floodwaters originating from
different sources are expected to have particular isotopic
fingerprints that can be used to identify the meteorological origin of the flood. Furthermore, distinct isotope
values in precipitation could be subsequently stored in
the isotope signature of tree-rings, given the ability of the
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DATA ANALYSIS
RESULTS
Fig. 1: Methodological scheme: from the data sources to the final results.
The general methodology includes two paths, one with the meteorological-hydrological data sources and isotopic analysis (grey), and the second corresponding with dendrochronological techniques and tree-ring isotopic analysis
(white). Both paths converge by means of the comparison in the final results.
Fig. 1 : Schéma présentant la méthode employée, depuis la collecte des données jusqu’auxrésultats finaux. La méthodologie généraleinclut deux démarches, l’une avec lessources de donnéesmétéorologiques-hydrologiquesetl’analyse isotopique(fond grisé), et l’autrecorrespondant à ladendrochronologieet àl’analyse isotopiquedes cernes(fond blanc). Les deux démarches se rejoignentlors decomparaison des résultats finaux.
DATA SOURCES
69
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70
latter to record a source-water signal. This classification
would allow us to separate different populations of flood
events and then apply individual frequency analysis to
each data sample, thereby improving estimation of return
period in comparison with conventional analyses of the
entire mixed dataset.
2.2 - STUDY AREAS
The two study areas are located in the central part of
the Iberian Peninsula, in the mountain chain called the
Central System, an alpine intraplate pop-up 500 km long,
extending from central Portugal to the eastern part of
Spain, in a WSW-ENE direction. The highest part of the
Spanish Central System is called “the Sierra de Gredos”;
its eastern area is formed by the Sierra de la Paramera
and the Sierra del Valle ranges, where both study areas
are located (fig. 2).
The first area of study was located in the headwaters
of the Gaznata River catchment (Tagus River Basin),
at the edge of the Gaznatilla gorge (fig. 2A). The substratum is formed by Variscan granites with thick colluvial and weathering mantles. These form fissured and
detrital surficial aquifers respectively. The tree vegetation
comprises a pine forest (Pinus sylvestris) planted in the
mid 20th century. The altitude ranges between 1,450 and
1,380 m asl; the average annual precipitation is around
630-700 mm; and the mean annual temperature is 9.6ºC.
On September 1st 1999, a convective storm caused heavy
rain in this area and a severe flood flash with three fatalities and significant economic losses downstream (DíezHerrero, 2003).
The second study area is located in the Venero Claro
catchment (also in the Tagus River Basin), at the drainage divide of many of its tributaries or on the riverbanks
(fig. 2B). The substratum is also formed by Variscan
granites with thick alluvial formations. These form a
fissured aquifer and several detrital surficial aquifers
respectively. Tree vegetation comprises a mixed forest
of pines (Pinus pinaster; Ballesteros et al., 2010a), oaks
(Quercus pyrenaica) and riverside species (Alnus glutinosa, Fraxinus angustifolia, Salix sp., Populus sp., etc.;
(Ballesteros et al., 2010b). The altitude ranges between
750 and 900 m asl; the average annual precipitation is
around 600-700 mm, and the mean annual temperature
is 12.6ºC.
2.3 - METEOROLOGICAL DATA AND ISOTOPES IN
PRECIPITATION
The methodological proposal is applied to a recent
flash flood event occurring in Central Spain. For this
purpose, a well-known heavy-rain convective event
(01-09-1999) was chosen from the recent flood record.
The meteorological data series were supplied by the
Spanish National Weather Service (AEMET). All the
available series of seven rain gauges around the study
areas have been analyzed (fig. 3). For the area of Gaznata,
we used precipitation and temperature data from the
station at Navas del Marqués, whereas for Venero Claro,
1501-012-Mep1-2015.indd 70
we used data from El Tiemblo and Ávila, for precipitation and temperature, respectively. In both cases, relative humidity was obtained from the automatic station in
Ávila. The isotopes in precipitation data were supplied
by the Spanish Network of Isotopes in Precipitation
(REVIP, Díaz-Teijeiro et al., 2009), using the data of the
three nearest stations (Madrid-Retiro, 1997-2006 period;
Ávila, 2002-2003 period; Valladolid, 2000-2006 period;
see fig. 3). In addition to the target event, we selected two
additional years combining markedly different isotopic
signatures in the REVIP stations with relatively strong
precipitation events in the study area (2003 and 2005).
2.4 - METHODS
2.4.1 - Tree sampling and sample preparation
In the two forested study areas, samples were taken
from at least six trees of each one of four species selected,
representative of distinct functional types [two conifer
species: the widespread temperate pine Pinus sylvestris
L. and the Mediterranean pine Pinus pinaster Aiton; and
two angiosperms: a sub-Mediterranean oak, Quercus
pyrenaica Willd., and a riparian species, Alnus glutinosa
(L.) Gaertn]. The sampling of individual trees started
with a rigorous, objective selection, based on their position in the divide to ensure that the roots were as far as
possible from the water table; to ensure that the water
supply was mainly derived from the unsaturated zone of
the soil (Mantese et al., 2012; Penna et al., 2013).
Each tree to be sampled was located (with a GPS
receiver) and tagged (with a univocal label), logging
the characteristics of the tree itself (species, subspecies,
dimensions, condition, etc.) and of its immediate environment (substratum, slope, slope orientation, distance
from other examples, etc.). Subsequently, two cylindrical
cores were extracted in the approximate direction of the
shaft radius, using a standard Pressler increment borer
(400 mm long x 5.5 mm interior diameter), which allows
a representative sample to be obtained of all tree-rings
formed between the bark and the interior of the trunk.
Normally the cores were extracted at 1.30 m above ground
level, except where this was not possible (particularly for
A. glutinosa) because of deformations and defects in the
trunk or the presence of low branches. In those cases the
cores were extracted lower down. All samples were ovendried at 60°C for 48 h and one core per tree was sanded
with sandpapers of progressively finer grain until tree
rings were clearly visible. The remaining core of every
tree was kept intact for isotope analysis.
2.4.2 - Tree-ring measurement and dating
The cores selected for dating were scanned and tree-ring
widths were measured using the software WinDendroTM
(Regent Instruments, Canada), assisted with visual crossdating under a binocular microscope. The COFECHA
program (Holmes, 1983) was used to evaluate the quality
of visual cross-dating. The quality of the average chronology for every site-species combination was examined
11/02/15 13:45
71
Fig. 2: Location of the study are and sampling sites.
A/ Gaznata, B/ Venero Claro. For each site, the specific location of the sampled species is indicated.
Fig. 2 : Localisation de la zone d’étude et des sites d’échantillonnage. A/ Gaznata, B/ Venero Claro. Pour chaque site, l’emplacement précis des espèces
échantillonnées est indiqué.
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72
Fig. 3: Location of meteorological stations and isotope records of precipitation.
A/ Location of the three stations from the Iberian Network of Isotope Surveilance (REVIP), which provide δ18O records of precipitation. B/ Location of
the six meteorological stations close to the study area.
Fig. 3 : Emplacement des stations météorologiques et des enregistrements isotopiques des précipitations. A/ Localisation des trois stations du Réseau
Ibérique de Isotope Surveilance (REVIP), qui ont fourni des enregistrements du δ 18O des précipitations. B/ Localisation des six stations météorologiques
proches de la zone d’étude.
by calculating the mean inter-series correlation (â) and
the Expressed Population Signal (EPS) statistics, as
described in Cook & Kairiukstis (1990):
EPS =
N*R
N * R + (1 – R)
where N is the number of individuals and R is the mean
inter-series correlation. Standard quality threshold is
EPS > 0.85.
Once the wood cores were dated, the tree-ring corresponding to the event year (1999), along with the preceding and subsequent rings (1998-2000), were identified
and isolated for isotope analysis. The same procedure
was applied to the outlier years recognised in the isotopic
record of precipitation (2003, 2005) and the adjacent
tree-rings (2002-2006). In all samples, earlywood and
latewood were analysed separately. Additionally, given
the larger size of tree-rings in oaks, latewood was divided
into two subsections, “early-” and “late-” latewood
(hereinafter, latewood-1 and latewood-2).
1501-012-Mep1-2015.indd 72
2.4.3 - Analysis of tree-ring isotopes
Each wood section was processed individually to
obtain the oxygen isotope composition (δ18O) of alphacellulose. For α-cellulose purification we followed the
method first described by (Brendel et al., 2000), as modified by Gaudinski et al. (2005). Briefly, the extraction
involves soaking the wood samples in a 10:1 mixture of
acetic (80 %) and nitric (69 %) acid at 120°C for 45 mn
in 1.5 ml polypropylene tubes, followed by a series of
rinses using ethanol, deionized water and acetone to
remove breakdown products and facilitate sample dehydration. A final purification step uses 17 % w/v NaOH
and subsequent rinsing steps with water, diluted acetic
acid and acetone to increase the purity of the extracted
cellulose. The samples are finally left to dry overnight in
a desiccator, then placed in an oven for 2 h at 50°C. For
oxygen isotope analysis, ca. 0.40 mg of dry α-cellulose
was weighed into silver foil capsules and combusted in
an elementar PyroCube (Elementar Analysensysteme
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73
GmbH, Hanau, Germany) interfaced to a PDZ Europa
20-20 isotope ratio mass spectrometer (Sercon Ltd.,
Cheshire, UK), at the Stable Isotope Facility of the
University of California-Davis (USA). Isotope ratios
were expressed as per mill deviations using the deltanotation (δ18O) relative to VSMOW standards. The
accuracy of the analyses (standard deviation of working
standards) was 0.25 ‰.
combination of species and tree-ring sections, resulting
from ANOVA, together with the growth index derived
from the standardised chronology.
3 - RESULTS
3.1 - QUALITY OF TREE-RING DATING
Series sensitivity was generally high in both pine species
and in oak, but very low in alder (tab. 1). For P. sylvestris,
after removing one outlier tree showing poor correlation
with the master series, inter-series correlation increased
from 0.59 to 0.62, while the expressed population signal
(EPS) remained almost the same (0.896 to 0.892), so the
latter chronology was selected for subsequent studies.
For P. pinaster, EPS was 0.821, very close to the quality
standard of EPS > 0.85, so this series was also included
in subsequent studies. In A. glutinosa, however, EPS
was extremely low, so the resulting chronology was not
reliable enough for dendrochronological studies.
2.4.4 - Statistical analyses
To obtain a first insight into the different variability
components in the stable isotopic signature of tree-rings,
data on δ18O were subjected to analysis of variance using
the SAS proc-mix procedure (SAS Institute, Cary, USA).
The analysis included species x tree and the residual
as covariance parameters, and species, year, section
(early- or latewood) and subsection (latewood-1 and
latewood-2, nested to section) as fixed factors, together
with the corresponding interactions. Product-moment
Pearson correlations between δ18O of tree-rings (early
and latewood) and environmental variables (maximum
and minimum temperature, total precipitation, δ18O in
precipitation) for the period 1998-2006 were calculated
to determine the variables determining the δ18O. In addition to total precipitation, we also assessed correlations
with monthly maximum precipitation in a single event,
as an indicator of the presence of strong rain events.
Finally, in order to determine the set of attributes that best
define the selected event year (1999), a series of Principal
Component Analyses (PCA) were performed. The candidate variables included the robust means of δ18O for each
3.2 - SOURCES OF VARIABILITY IN D18O OF TREERINGS
3.2.1 - Analysis of variance
The analysis of variance (tab. 2) showed significant
differences among species, together with a significant
year x species interaction, indicating that each species
shows a distinct response to environmental conditions, and must therefore be considered separately.
Site
Species
N
Mean
Interseries
correlation
Expressed
Population
Signal (EPS)
Tree age
(Mean
±Std. Dev.)
Gaznata
Pinus sylvestris
Venero Claro
Pinus pinaster
Quercus pyrenaica
Alnus glutinosa
6
5
6
6
6
0.591
0.622
0.434
0.563
0.134
0.896
0.892
0.821
0.885
0.480
41 ± 1.6
42 ± 1.7
58 ± 1.9
37 ± 2.6
37 ± 4.3
Tab. 1: Main descriptive parameters of the dendrochronological series.
Tab. 1 : Principaux paramètres descriptifs des séries dendrochronologiques.
Covariance Parameter Estimates
Parameter
Estimate Standard Error Z Value Pr. Z
Species*Tree
0.1859
0.07844
2.37 0.0089
Residual
0.7904
0.06318
12.51 <.0001
Type 1 Test of Fixed Effects
Effect
Num DF Den DF
Species
3
Year
7
Species*Year
21
Section
1
Section*Subsection
2
Year*Section
7
Species*Section
3
Species*Year*Section
21
20
314
314
314
314
314
314
314
F Value
82.8
20.34
5.59
103.21
43.21
10.94
34.24
4.04
Pr. > F
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
<.0001
Tab. 2: Summary results of the analysis of variance.
Tab. 2 : Sommaire des résultats de l’analyse de la variance.
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74
Both sections and subsections also showed significant
effects, indicating that the environmental signature
differs among early- and latewood, as well as between
latewood-1 and latewood-2 in oak. Consequently, all
subsequent analyses were performed separately for
each species and tree-ring section (see average values
in tab. 3).
3.2.2 - Correlations with isotope values in precipitation
Correlations with isotopes in precipitation were generally poor and inconsistent. We found a weak correlation
between latewood δ18O for the pines and inter-annual
variations in δ18OR for the station Madrid-Retiro (nearest
station with a long-term record). The strongest correlations were found with previous autumn δ18OR (Sept-Nov,
r = 0.73, P < 0.10) for P. sylvestris, and between current
spring δ18OR (March-June, r = 0.87, P < 0.10) and δ18O
of late wood for P. pinaster. In contrast, we did not find
any significant correlation between δ18O and δ18OR for the
second station with a long-term record (Valladolid). On a
monthly basis, the three REVIP stations were significantly
correlated (Madrid vs. Valladolid: r = 0.67, P < 0.001;
Madrid vs. Ávila: r = 0.65, P < 0.05; Valladolid vs. Ávila:
r = 0.82; P < 0.001); however, inter-annual correlations
between the long-term stations (Madrid and Valladolid)
were not significant, considering neither annual nor
seasonal means (r = [-0.35 + 0.44], period 2000-2006).
Due to the scarcity of data, it was not possible to assess
inter-annual correlations with the nearest station (Ávila),
but the trends for the two years recorded (2002-2003)
coincided with those observed in Madrid, and were the
opposite of those found in Valladolid.
3.2.3 - Correlations with climate variables
Correlations between δ18O in early wood and climate
variables mainly showed a spring signal, with precipitation, temperature and humidity in pines, but only
temperature and humidity in oaks (results summarised
in table 4 and figures 4a and b). In oaks, δ18O in the
Fig. 4: Most significant correlations with climate.
Correlation of early wood δ18O with spring (a) total precipitation (mm) and (b) mean maximum temperature (Tmax, ºC). Correlation of late wood δ18O
with autumn (c) total precipitation (mm) and (d) mean minimum temperature (Tmin, ºC). Values for correlations with p < 0.10 (+), p < 0.05 (*) and
p < 0.01 (**) are shown.
Fig. 4: Corrélations les plus significatives avec le climat.
Corrélation du δ 18O du bois de printemps avec (a) les précipitations totales du printemps (mm) et (b) la température maximale moyenne du printemps
(Tmax, ºC). Corrélation du δ 18O du bois d’été avec (c) les précipitations totales d’automne (mm) et (d) la température minimale moyenne d’automne
(Tmin, ºC). Les valeurs de corrélation avec p < 0.10 (+), p < 0.05 (*), and p < 0.01 (**) sont indiquées.
1501-012-Mep1-2015.indd 74
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P. pinaster
P. sylvestris
Year
18
30.61
32.09
31.35
34.72
30.56
34.47
-
-
32.10
33.08
31.79
34.00
34.45
34.22
36.25
35.49
34.41
33.24
1.27
1.17
0.72
0.71
0.74
0.55
0.75
1.04
0.98
18
18
34.27
34.59
32.98
34.77
33.71
35.48
Q. pyrenaica
A. glutinosa
δ OEW δ OLW RG δ OEW δ OLW RG δ OEW δ OLW1 δ OLW2 RG δ OEW δ18OLW
1998
1999
2000
2001
2002
2003
2004
2005
2006
18
-
-
35.00
34.92
33.70
35.79
37.85
33.72
34.95
34.03
34.58
35.50
0.98
0.73
0.99
1.26
0.66
0.60
0.84
0.65
1.01
18
18
18
29.40
30.26
30.16
32.14
32.36
32.73
32.74
32.48
31.52
33.14
33.55
31.51
31.89
32.38
32.63
33.27
32.08
32.83
32.80
30.67
30.92
29.93
30.58
31.34
18
1.07
1.08
1.01
0.87
0.90
0.93
1.22
0.76
0.93
30.34
30.62
30.81
30.34
30.20
30.51
31.19
31.68
30.01
30.06
30.74
30.60
30.52
31.00
30.89
30.53
Tab. 3: Average values of dendroecological variables.
δ18OEW, δ18OLW, δ18OLW1 and δ18OLW2 stand for the oxygen isotope composition (δ18O) in early wood, late wood, and in the two consecutive sections of late
wood, respectively; RG stands for the standardized chronology of radial growth.
Tab. 3 : Valeurs moyennes des variables dendroécologiques. δ 18OEW, δ 18OLW, δ 18OLW1 et δ 18OLW2 représentant la composition isotopique de l’oxygène
(δ 18O) dans le bois initial, le bois final, et dans les deux sections consécutives de bois final, respectivement; RG représente la chronologie standard de
la croissance radiale.
Species
P.sylvestris
δ18OEW
δ18OLW
RG
P. pinaster
δ18OEW
δ18OLW
RG
Q. pyrenaica
δ18OEW
δ18OLW1
δ18OLW1
RG
Species
P.sylvestris
Variable
δ18OEW
δ18OLW
RG
P. pinaster
δ18OEW
δ18OLW
RG
Q. pyrenaica
δ18OEW
δ18OLW1
δ18OLW1
RG
Species
P.sylvestris
Variable
δ18OEW
δ18OLW
RG
P. pinaster
δ18OEW
δ18OLW
RG
Q. pyrenaica
Total Precipitation (mm)
Maximum Precipitation event (mm)
Aut-1 Win
Spr
Sum
Aut
-0.22 0.02 -0.81 -0.40 0.51
0.71
0.61 -0.08 -0.52 0.35
-0.10 -0.44 0.26
0.41 -0.63
-0.33 -0.12 -0.81 -0.16 0.30
0.23 -0.12 0.29 -0.35 0.36
0.35
0.44
0.23
0.12 -0.37
-0.57 -0.21 -0.53 -0.45 0.80
-0.59 -0.38 -0.38 -0.23 0.48
-0.28 -0.01 -0.35 -0.54 0.76
0.34 -0.13 0.48
0.11 -0.15
Average Maximum Humidity (%)
Aut-1 Win
Spr
Sum
Aut
0.42
0.02 -0.79 -0.47 0.68
0.26
0.69
0.06 -0.41 0.29
0.23 -0.54 -0.14 0.56 -0.55
-0.63 0.53 -0.74 0.28
0.49
-0.32 -0.20 0.09 -0.31 -0.08
-0.48 -0.10 0.07
0.29 -0.34
-0.69 0.68 -0.88 0.21
0.32
-0.84 0.29 -0.74 0.09 -0.08
-0.49 0.48 -0.70 -0.21 0.22
0.66 -0.24 0.76
0.18
0.16
Average Minimum Humidity (%)
Aut-1 Win
Spr
Sum
Aut
-0.45 0.77 -0.84 -0.07 0.30
0.20 -0.28 0.33 -0.44 0.13
0.22 -0.24 0.21
0.03
0.02
-0.63 0.53 -0.74 0.28
0.49
-0.32 -0.20 0.09 -0.31 -0.08
-0.48 -0.10 0.07
0.29 -0.34
-0.69 0.68 -0.88 0.21
0.32
-0.84 0.29 -0.74 0.09 -0.08
-0.49 0.48 -0.70 -0.21 0.22
0.66 -0.24 0.76
0.18
0.16
Average Max. Temperature (%)
Aut-1 Win
Spr
Sum
Aut
0.14
0.45 -0.82 -0.41 0.23
0.83
0.16
0.49 -0.25 0.40
-0.49 -0.46 0.05
0.04 -0.79
-0.08 0.45 -0.76 -0.03 -0.15
0.17 -0.23 0.23 -0.58 -0.18
-0.02 0.12
0.06
0.14 -0.59
-0.03 0.53 -0.78 -0.14 0.43
-0.32 -0.08 -0.57 -0.31 -0.11
0.30
0.46 -0.51 -0.37 0.70
0.11 -0.11 0.57
0.29 -0.10
Average Min. Temperature (%)
Aut-1
-0.49
-0.52
0.72
0.08
-0.08
-0.29
-0.24
-0.29
-0.12
0.11
Aut-1
-0.22
0.54
0.20
-0.03
0.50
0.20
-0.20
-0.25
0.09
0.08
Variable
18
δ OEW
δ18OLW1
δ18OLW1
RG
Win
-0.89
-0.10
0.13
-0.54
0.02
0.47
-0.62
-0.35
-0.50
0.26
Spr
0.75
-0.31
-0.20
0.74
0.15
-0.31
0.87
0.62
0.79
-0.60
Sum
-0.04
-0.01
0.05
0.25
0.43
-0.39
0.16
0.04
0.32
0.03
Aut
-0.64
-0.28
0.68
0.66
0.38
0.03
0.47
0.46
0.23
-0.04
Win
-0.75
-0.04
0.23
-0.18
0.01
0.57
-0.31
-0.37
-0.23
0.09
Spr
0.69
-0.37
0.34
0.68
0.51
-0.25
0.80
0.70
0.80
-0.58
Sum
0.37
-0.28
0.53
0.47
0.18
-0.19
0.26
-0.03
0.19
0.14
Aut
0.53
-0.17
-0.09
0.49
0.14
-0.46
0.85
0.60
0.72
-0.22
3
Tab. 4: Correlation coefficients between dendroecological and meteorological variables.
δ18OEW, δ18OLW, δ18OLW1 and δ18OLW2 stand for oxygen isotope composition (δ18O) in early wood, late wood, and the two consecutive sections of late wood,
respectively; RG stands for the standardized chronology of radial growth. Significant correlations at p < 0.05 are shown in bold.
Tab. 4 : Coefficients de corrélation entre les variables dendroécologiques et météorologiques. δ 18OEW, δ 18OLW, δ 18OLW1 et δ 18OLW2, composition isotopique
de l’oxygène (δ 18O) dans le bois du printemps, le bois d’été, et dans les deux sections consécutives de bois d’été, respectivement; RG représent la chronologie standard de la croissance radiale. Les corrélations significatives à p < 0.05 sont marquées en gras.
1501-012-Mep1-2015.indd 75
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two latewood sections showed a consistent relationship
with spring conditions (mainly minimum temperature
and maximum humidity). We also found a positive relationship between oak δ18O (early- and late-wood) and
both precipitation and minimum temperature of currentyear autumn (tab. 4, fig. 4c and d). In P. sylvestris, δ18O
in latewood was positively correlated with mean precipitation in previous-year autumn (tab. 4), whereas for
Q. pyrenaica a negative relationship was found between
early and late wood δ18O and maximum relative humidity
in previous-year autumn (tab. 4).
3.2.4 - Principal Component Analysis
With the aim to disentangle the signal of the event
year (1999) from average meteorological responses, we
performed a series of Principal Component Analyses
(PCA). We discarded Alnus glutinosa from the analysis,
due to the lack of a reliable chronology for this species.
We also observed that including the standard tree-ring
chronology for each species as input variables did not
provide additional information, so we finally adopted a
PCA including only isotope data for the two pine species
and the oak (fig. 5). The model explained 83.1 % of
total variance with the first two components. The first
component (PC1) explained 44.8 % of total variance,
and was mainly explained by a positive weight for early
wood δ18O, particularly in pines. For the oaks, we also
found a positive weight for latewood-1 δ18O (QpL1 in
fig. 5). Maximum values for PC1 (i.e. high early wood
Fig. 5: Principal component analysis.
Vectors of variable weights for the two first principal components, PC1
and PC2, correspond to the dots. Sample loadings for each individual
year are indicated by the last two digits of the corresponding year. Ps,
Pp and Qp stand for P. sylvestris, P. pinaster and Q. pyrenaica, respectively. Subscripts: E/ early wood δ18O, L/ latewood δ18O, L1 and L2/ both
consecutive sections of latewood.
Fig. 5 : Analyse en composantes principales. Les points noirs représentent les vecteurs de pondération des variables PC1 et PC2 pour les
deux premières composantes principales. Les nombres correspondent
aux valeurs factorielles des échantillons pour l’année correspondante
(seuls les deux derniers chiffres sont indiqués). Ps, Pp et Qp représentent respectivement P. sylvestris, P. pinaster et Q. pyrenaica. Indices :
E/ δ 18O du bois de printemps, L/ δ 18O du bois d’été, L1 et L2/ les deux
sections consécutivesdu bois d’été.
1501-012-Mep1-2015.indd 76
δ18O) were found in 2006, whereas similar low values
were found in 1998, 2000 and 2004. The second component (PC2) explained 38.3 % of total variance, and was
mainly defined by a positive weight for latewood δ18O in
Pinus sylvestris (PsLW in fig. 5). A clear outlier year for
this component was 1999, showing the lowest values for
δ18O, whereas 2003 showed values slightly higher than
average.
4 - DISCUSSION
For all species, we found that the δ18O was mainly
explained by the environmental conditions during spring.
For the two pines, spring precipitation showed a strong
negative effect on earlywood δ18O, while temperature was
positively correlated. This suggests an effect of spring
water availability, on the one hand, and water demand,
on the other, thus mainly related to enrichment effects
at the leaf level (Farquhar & Lloyd, 1993), which in turn
are associated to the tight stomatal regulation of pines
(Barbour et al., 2001; Ferrio & Voltas, 2005; Barnard et
al., 2007). This appears to be a common feature among
pine species, particularly under Mediterranean conditions
(Ferrio & Voltas, 2005; Ferrio et al., 2005; Granados,
2011). However, this was not observed in latewood, which
under Mediterranean conditions would be expected to be
more strongly influenced by evaporative demand. The
reason for that might be that in the area of study interannual variability during summer was much smaller than
during spring (in all stations, inter-annual standard deviation in winter and spring was, respectively, ca. 4 and 2 fold
higher than in summer months). On the other hand, the
oaks also showed a negative correlation with spring precipitation, but were more closely correlated with temperature, which is consistent with their reliance on deep water
reservoirs, showing less dependence on growing-season
precipitation (Aguilera et al., 2011; Michelot et al., 2012;
del Castillo et al., 2013; Klein et al., 2013). Interestingly,
in oaks not only the earlywood but also the latewood
signal was mainly affected by spring conditions, although
monthly correlations showed peaks moving from April in
earlywood to June in the second half of latewood (data not
shown). This is in agreement with the stronger reliance
on stored carbohydrates of deciduous angiosperms,
as compared to the evergreen conifers, which imply a
carry-over signal from spring that can extend throughout the growing season (Damesin et al., 1998; Barbour
et al., 2002; Gessler et al., 2009; Michelot et al., 2011;
Offermann et al., 2011). On the other hand, previousyear signals and age effects might have partly masked the
response of δ18O in tree rings to current-season conditions
(see e.g. Labuhn et al., 2014). In this regard, although the
short series studied did not allow assessment of age effects
in δ18O, they are likely to be irrelevant for the pines, but
might have introduced an additional source of error in the
two species including younger individuals, Q. pyrenaica
and A. glutinosa (see tab. 1).
Interestingly, we also found some correlations between
current-year autumn maximum precipitation (as an
11/02/15 13:45
77
indicator of heavy rains) and the δ18O of spring wood
(see tab. 4). Although this relationship is not causal, it
may indicate an underlying connection between spring
isotopic signature in precipitation and the prevalence of
high-intensity rain events, which may deserve further
study as a potential predictive tool.
The PCA confirmed the results from correlation
analyses, showing that the main source of variability for
δ18O in tree-rings was related to spring conditions. Thus,
the first component was mainly correlated with the
early-wood δ18O in both pines and oaks (fig. 5, PsE, PpE
and QpE). For oaks, the first component was also correlated with δ18O in the first section of latewood (fig. 5,
QpL1), which was also responsive to spring conditions,
as shown in table 4. Considering the different location
of P. sylvestris (Gaznata) and the other two species
(Venero Claro), this agreement suggest a strong spatial
coherence for the spring signal, which further supports
a more significant role of temperature as compared
to precipitation, since the former shows better spatial
correlations than the latter (Ninyerola et al., 2000;
del Castillo et al., 2013). Interestingly, the only single
variable explaining the second principal component was
latewood δ18O in P. sylvestris, which in turn was mainly
influenced by the particularly low value of the event
year, 1999. These results are particularly encouraging,
since they suggest that the lack of clearer correlations
with autumn precipitation values was mainly due to the
restricted spatial coverage of the heavy rain event in
1999, which was only weakly reflected in meteorological records. In contrast, the isotope signal in tree-rings
showed a clear response of P. sylvestris growing in the
area affected by the extreme event (Gaznata), but left
unaffected the other two species, which were growing
in the Venero Claro area. Although this still requires
further assessment with a more extensive dataset, these
results confirm our working hypothesis that a clearer
signature of extreme events could appear once background trends in response to average climate variables
are removed.
Despite the clear signature of the 1999 event in treerings, we did not find clear relationships between δ18O
in tree-rings and in precipitation. However, this could
be explained by the erratic spatial distribution of precipitation events, which also explains the weak interannual correlations between δ18O of precipitation for the
different meteorological stations included in the study.
In particular, convective precipitation, such as the 1999
event studied, are developed in a very localized way,
covering only a few tens of kilometres (Díez-Herrero,
2003). Therefore, the isotopic response of these events
is restricted to the area where precipitation occurred, and
may not have been collected even by the nearest meteorological stations. In particular, within our area of study,
the Central System range constitutes a major barrier
for the distribution of convective storms, which follow
different pathways in the two areas (Ávila-Madrid and
Valladolid). Whereas convective nuclei in Madrid and
Ávila usually move along the Tajo and Jarama Valleys, in
Valladolid they move along the Duero Valley. In contrast,
1501-012-Mep1-2015.indd 77
precipitations associated with Atlantic fronts, such as
those occurring in winter and spring, are produced in
large regions, leaving their isotopic fingerprint over very
large areas. Although this could be considered a limitation of the isotopic approach, it also opens an alternative
line of study, taking advantage of the ability of tree rings
to record mainly precipitation events of frontal origin. In
particular, we hypothesize that strong but site-specific
signals in the tree-ring record might be associated with
local precipitation events of convective origin, whereas
very consistent signals across a wide range of sampling
sites would indicate a more generalized event, one likely
to be of frontal origin. However, this hypothesis can only
be tested by incorporating sampling sites in the vicinity
of those stations where an extensive record of isotopes in
precipitation is available. Following a similar reasoning,
it is likely that other kind of floods, e.g. those caused by
snow melt, could be also distinguished in the isotopic
record, given the particularly depleted isotope signature
of snow (Tang & Feng, 2001; Treydte et al., 2006). In this
case, we would expect this signal to appear in early wood,
and to be particularly strong in evergreen species with
early phenology (Treydte et al., 2006), but it might not
appear in deciduous species, which are not actively transpiring during snowmelt (see e.g. Treydte et al., 2014).
Another possible source of error that can mask the
results of the correlation is the influence of the amount
of precipitation on isotopic composition; this has been
discussed in several studies in recent decades (Poussart &
Schrag, 2005; Liu et al., 2008). Similarly, very short and
intense flood events are likely to have a greater run-off/
infiltration ratio (see e.g. Langhans et al., 2010), and thus
might not be able to modify the isotope signature of soil
water, and subsequently would not be stored in tree rings.
On top of that, the response of tree-ring isotopic composition to precipitation amount is not only due to the isotopic
signal of precipitation and soil water (Granados, 2011),
but has also a strong leaf-level signal that is carried over
from the leaf to xylem cellulose (Ferrio & Voltas 2005;
Gessler et al., 2009; Gessler et al., 2013). Briefly, higher
water availability or humidity would increase stomatal
conductance, reducing leaf-water isotopic enrichment
during evaporation, and this signal would be transferred
to exported sugars, thus potentially contributing to the
isotopic signature of wood (Offermann et al., 2011;
Gessler et al., 2013; Treydte et al., 2014). However, the
contribution of a leaf level signal can be variable with
species and even during the season (Offermann et al.,
2011; Gessler et al., 2013), and on the other hand leafwater signature is further complicated by the opposing
effects of transpiration flow and evaporative enrichment
(Farquhar & Lloyd 1993; Ferrio et al., 2012). In this
context, since the exchange of oxygen isotopes during
cellulose biosynthesis is variable at the intra-molecular
level, novel methods have emerged that will allow leaf
and source signals in tree-ring archives to be disentangled in the future (Ellsworth et al., 2013). Meanwhile, the
selection of tree species has also a significant influence
on the isotopic response, because the different climatic
sensitivity of the tree species, as is also demonstrated in
11/02/15 13:45
78
the results presented, is in line with previous research
(Saurer et al., 1997; Treydte et al., 2007; Battipaglia et
al., 2008; Daley et al., 2010).
Despite the aforementioned methodological limitations,
tree-ring oxygen stable-isotopes have a potential utility
in flood-hazard assessment. Specifically, this source of
data could be used in the improvement of the frequency
analysis and in the management and assessment of hazard.
In this respect, the most straightforward method for estimating flood frequency is to adjust a cumulative probability function to the recorded annual maximum flows.
However, this approach produces flood quantile estimators with a high degree of uncertainty (Botero & Francés,
2010). Oxygen stable isotope data, combined with nonsystematic data from the past (e.g. historical and paleoflood censored data), could increase the information
available and, therefore, reduce uncertainty in estimates.
The ability of stable isotopes to explore the meteorological origin of precipitation could also help to characterize hazard, which is a process that is highly dynamic due
to the seasonal climatic pattern and variability in vulnerability. So, seasonal effects may lead to significant differences between the flood hazard in summer and winter
and, at the same time, vulnerability to extreme events can
be also variable throughout the year (Merz et al., 2007).
5 - CONCLUSION
Although the results are preliminary and based on
a limited number of years, our study suggests that the
isotope signal in tree-ring cellulose for both pines and
oak is dominated by spring conditions, seemingly precluding its use as a proxy for precipitation events occurring
during late summer-autumn. However, after removing this
“spring signal”, we found a clear and site-specific signal
in latewood δ18O, associated with the heavy rain of autumn
1999. Thus, we cannot discard our working hypothesis
that a clearer signature of extreme events could appear
once background trends in response to average climate
variables are removed. Nevertheless, we did not find a
direct relationship between δ18O in precipitation and treerings, most likely due to the strong spatial heterogeneity
of precipitation. Therefore, we still lack a direct proof of
a causal association between an extreme-event isotopic
fingerprint and the observed site-specific signal in treering δ18O. In this regard, our results encourage further
research to test our initial hypothesis more thoroughly,
by considering a larger number of events, and using plant
material as close as possible to meteorological stations
where a record of isotopes in precipitation is available.
ACKNOWLEDGMENTS
This work was funded by the research projects
MAS Dendro-Avenidas (CGL2010-19274; www.
dendro-avenidas.es, Spanish Ministry of Economy
and Competitiveness), and IDEA-GesPPNN (OAPN
1501-012-Mep1-2015.indd 78
163/2010; Spanish Ministry of Agriculture, Food and
Environment). Meteorological data were freely provided
by the Spanish Weather Service (AEMET) thanks to a
collaboration agreement with the Spanish Geological
Survey (IGME; Jose María Pernía). Juan Vázquez
(UAM) facilitated contact between the two research
groups involved in this study. Jordi Voltas contributed to
the experimental design and assisted us in the statistical
analysis. We would also like to thank Javier Rodríguez
Arévalo and Marifé Díaz Teijeiro for providing isotope
data from the Red Española de Vigilancia de Isótopos
en la Precipitación (REVIP), which is run by CEDEX
in co-operation with AEMET. JPF was supported by the
Ramón y Cajal Programme (MEC, Spain). We thank
the comments and corrections from the guest editors
Stéphane Cordier, Gerardo Benito and David Bridgland,
and the reviewers Matthias Saurer and Alberto Viglione,
who improved the original manuscript significantly.
REFERENCES
AGUILERA M., FERRIO J.P., ARAUS J.L., TARRÚS J. & VOLTAS
J., 2011 - Climate at the onset of western Mediterranean agriculture
expansion: Evidence from stable isotopes of sub-fossil oak tree rings
in Spain. Palaeogeography, Palaeoclimatology, Palaeoecology, 299
(3-4), 541-551.
ANDERSON W.T., BERNASCONI S.M., MCKENZIE J.A. &
SAURER M., 1998 - Oxygen and carbon isotopic record of climatic
variability in tree ring cellulose (Picea abies): An example from
central Switzerland (1913-1995). Journal of Geophysical Research,
103 (D24), 31625-31636.
BALLESTEROS J.A., STOFFEL M., BODOQUE J.M.,
BOLLSCHWEILER M., HITZ O. & DÍEZ-HERRERO A.,
2010a - Changes in wood anatomy in tree rings of Pinus pinaster
Ait. following wounding by flash floods. Tree-Ring Research, 66 (2),
93-103.
BALLESTEROS J.A., STOFFEL M., BOLLSCHWEILER
M., BODOQUE J.M. & DÍEZ-HERRERO A., 2010b - Flashflood impacts cause changes in wood anatomy of Alnus glutinosa,
Fraxinus angustifolia and Quercus pyrenaica. Tree Physiology, 30
(6), 773-781.
BALLESTEROS J.A., BODOQUE J.M., DÍEZ-HERRERO A.,
SANCHEZ-SILVA M. & STOFFEL M., 2011 - Calibration of floodplain roughness and estimation of palaeoflood discharge based on
tree-ring evidence and hydraulic modelling. Journal of Hydrology,
403 (1-2), 103-115.
BARBOUR M.M., ANDREWS T.J. & FARQUHAR G.D.,
2001 - Correlations between oxygen isotope ratios of wood constituents of Quercus and Pinus samples from around the world.
Australian Journal of Plant Physiology, 28 (5), 335-348.
BARBOUR M.M., WALCROFT A.S. & FARQUHAR, G.D.,
2002 - Seasonal variation in δ13C and δ18O of cellulose from growth
rings of Pinus radiata. Plant, Cell and Environment, 25 (11), 14831499.
BARNARD R.L., SALMON Y., KODAMA N., SORGEL K.,
HOLST J., RENNENBERG H., GESSLER A. & BUCHMANN
N., 2007 - Evaporative enrichment and time lags between delta
O-18 of leaf water and organic pools in a pine stand. Plant Cell and
Environment, 30 (5), 539-550.
BARREDO J.-I., 2009 - Normalised flood losses in Europe: 19702006. Natural Hazards and Earth System Science, 9 (1), 97-104.
BATTIPAGLIA G., JÄGGI M., SAURER M., SIEGWOLF R.T.W.
& COTRUFO M.F., 2008 - Climatic sensitivity of δ18O in the
wood and cellulose of tree rings: Results from a mixed stand of
Acer pseudoplatanus L. and Fagus sylvatica L. Palaeogeography,
Palaeoclimatology, Palaeoecology, 261 (1-2), 193-202.
BOBÉE B., CAVADIAS G., ASHKAR F., BERNIER J. &
RASMUSSEN P., 1993 - Towards a systematic approach to comparing distributions used in flood frequency analysis. Journal of
Hydrology, 142 (1), 121-136.
BOTERO B. & FRANCÉS F., 2010 - Estimation of high return period
flood quantiles using additional non-systematic information with
11/02/15 13:45
79
upper bounded statistical models. Hydrology and Earth System
Sciences, 14 (12), 2617-2628.
BRENDEL O., IANNETTA P.P.M. & STEWART D., 2000 - A rapid
and simple method to isolate pure alpha-cellulose. Phytochemical
Analysis, 11 (1), 7-10.
COOK E.R. & KAIRIUKSTIS L.A., 1990 - Methods of dendrochronology: applications in the environmental science. Kluwer Academic
Publishers, Dordrecht, 394 p.
DALEY T.J., BARBER K.E., STREET-PERROTT F.A., LOADER
N.J., MARSHALL J.D., CROWLEY S.F. & FISHER E.H.,
2010 - Holocene climate variability revealed by oxygen isotope
analysis of Sphagnum cellulose from Walton Moss, northern
England. Quaternary Science Reviews, 29 (13), 1590-1601.
DAMESIN C., RAMBAL S. & JOFFRE R., 1998 - Seasonal and
annual changes in leaf delta C-13 in two co-occurring Mediterranean
oaks: relations to leaf growth and drought progression. Functional
Ecology, 12 (5), 778-785.
DANSGAARD W., 1964 - Stable isotopes in precipitation. Tellus.
Series B, Chemical and Physical Meteorology, 16 (4), 436-468.
DEL CASTILLO J., AGUILERA M., VOLTAS J. & FERRIO J.P.,
2013 - Isoscapes of tree-ring carbon-13 perform like meteorological
networks in predicting regional precipitation patterns. Journal of
Geophysical Research: Biogeosciences, 118 (1), 352-360.
DÍAZ M.F., RODRÍGUEZ J., PÉREZ E., CASTAÑO S. &
ARAGUÁS L., 2007 - Factors controlling the stable isotopic
composition of recent precipitation in Spain. In Proceedings of an
International Symposium on Advances in Isotope Hydrology and
its Role in Sustainable Water Resources Management (IHS-2007),
Vienna, 21-25 May 2007, Final Program. International Atomic
Energy Agency, Vienna, 239-249.
DÍAZ-TEIJEIRO M.F., RODRÍGUEZ-ARÉVALO J. &
CASTAÑO S., 2009 - La Red Española de Vigilancia de Isótopos
en la Precipitación (REVIP): distribución isotópica espacial y aportación al conocimiento del ciclo hidrológico [The Spanish Network
of Isotopes in Precipitation: spatial isotopic distribution and contribution to the knowledge of the hydrological cycle]. Ingeniería Civil,
104 (155), 87-97.
DÍEZ-HERRERO A., 2003 - Geomorfología e Hidrología fluvial del
río Alberche. Modelos y SIG para la gestión de riberas. Publicaciones
del Instituto Geológico y Minero de España (Ministerio de Ciencia y
Tecnología), Madrid, 587 p.
DÍEZ-HERRERO A., LAÍN-HUERTA L. & LLORENTE-ISIDRO
M., 2009 - A handbook on flood hazard mapping methodologies.
Series: Geological Hazards/Geotechnics, 2. Publications of the
Geological Survey of Spain (IGME), Madrid, 163 p.
DÍEZ-HERRERO
A.,
BALLESTEROS-CÁNOVAS
J.A.,
BODOQUE J.M. & RUIZ-VILLANUEVA V., 2013a - A new
methodological protocol for the use of dendrogeomorphological data
in flood risk analysis. Hydrology Research, 44 (2), 234-247.
DÍEZ-HERRERO A., FERRIO J.P., BALLESTEROS J.A., VOLTAS
J., BODOQUE J.M., AGUILERA M., RUIZ-VILLANUEVA V.
& TARRÉS D., 2013b - Using tree-ring oxygen stable isotopes for
studying the origin of past flood events: first results from the Iberian
Peninsula. In 8th International conference (AIG) on Geomorphology
Abstracts Volume : Paris – 2013, 27-31 August, “Geomorphology
and sustainability”. 376.
ELLSWORTH P.V., ANDERSON W.T., SONNINEN E., BARBOUR
M.M. & STERNBERG L.S.L., 2013 - Reconstruction of source
water using the δ18O of tree ring phenylglucosazone: A potential tool
in paleoclimate studies. Dendrochronologia, 31 (3), 153-158.
FARQUHAR G.D. & LLOYD J., 1993 - Carbon and oxygen isotope
effects in the exchange of carbon dioxide between terrestrial plants
and the atmosphere. In J.R. Ehleringer, A.E. Hall, & G.D. Farquhar
(eds.), Stable isotopes and plant carbon-water relations. Academic
Press, San Diego, 47-70.
FERRIO J.P., RESCO V., WILLIAMS D.G., SERRANO L. &
VOLTAS J., 2005 - Stable isotopes in arid and semi-arid forest systems.
Investigación Agraria, Sistemas y Recursos Forestales, 14, 371-382.
FERRIO J.P., POU A., FLOREZ-SARASA I., GESSLER A.,
KODAMA N., FLEXAS J. & RIBAS-CARBO M., 2012 - The
Péclet effect on leaf water enrichment correlates with leaf hydraulic
conductance and mesophyll conductance for CO2. Plant, Cell &
Environment 35 (3), 611-625.
FERRIO J.P. & VOLTAS J., 2005 - Carbon and oxygen isotope ratios
in wood constituents of Pinus halepensis as indicators of precipitation, temperature and vapour pressure deficit. Tellus. Series B,
Chemical and Physical Meteorology, 57 (2) 164-173.
GAUDINSKI J.B., DAWSON T.E., QUIDEAU S., SCHUUR E.A.G.,
RODEN J.S., TRUMBORE S.E., SANDQUIST D.R., OH S.W.
& WASYLISHEN R.E., 2005 - Comparative Analysis of Cellulose
Preparation Techniques for Use with 13C, 14C, and 18O Isotopic
Measurements. Analytical Chemistry, 77 (22), 7212-7224.
1501-012-Mep1-2015.indd 79
GESSLER A., BRANDES E., BUCHMANN N., HELLE G.,
RENNENBERG H. & BARNARD R.L., 2009 - Tracing carbon and
oxygen isotope signals from newly assimilated sugars in the leaves
to the tree-ring archive. Plant, Cell & Environment, 32 (7), 780-795.
GESSLER A., BRANDES E., KEITEL C., BODA S., KAYLER
Z. E., GRANIER A., BARBOUR M., FARQUHAR G. D. &
TREYDTE K., 2013 - The oxygen isotope enrichment of leafexported assimilates – does it always reflect lamina leaf water enrichment? New Phytologist, 200 (1), 144-157.
GESSLER A., FERRIO J.P, HOMMEL R., TREYDTE K.,
WERNER R.A. & MONSON R.K., 2014 - Stable isotopes in tree
rings: towards a mechanistic understanding of isotope fractionation
and mixing processes from the leaves to the wood. Tree Physiology,
34 (8), 796-818.
GRANADOS S., 2011 - Dendroclimatología isotópica en el sur de la
península Ibérica: implicaciones paleoclimáticas y paleohidrológicas. Tesis Doctoral, Universidad de Granada, Granada, 211 p.
GUMBEL E.J., 1941 - The return period of flood flows. The Annals of
Mathematical Statistics, 12 (2), 163-190.
HOLMES R.L., 1983 - Computer-assisted quality control in tree-ring
dating and measurement. Tree-Ring Bulletin, 43, 69-78.
KIDSON R. & RICHARDS K.S., 2005 - Flood frequency analysis:
assumptions and alternatives. Progress in Physical Geography, 29
(3), 392-410.
KLEIN T., SHPRINGER I., FIKLER B., ELBAZ G., COHEN S. &
YAKIR D., 2013 - Relationships between stomatal regulation, wateruse, and water-use efficiency of two coexisting key Mediterranean
tree species. Forest Ecology and Management, 302, 34-42.
LABUHN I., DAUX V., PIERRE M., STIEVENARD M.,
GIRARDCLOS O., FÉRON A., GENTY D., MASSONDELMOTTE V. & MESTRE O., 2014 - Tree age, site and climate
controls on tree ring cellulose 18O: A case study on oak trees from
south-western France. Dendrochronologia, 32 (1), 78-89.
LANGHANS C., GOVERS G., DIELS J., CLYMANS W. & VAN
DEN PUTTE A., 2010 - Dependence of effective hydraulic conductivity on rainfall intensity: loamy agricultural soils. Hydrological
Processes, 24 (16), 2257-2268.
LIU Y., CAI Q., LIU W., YANG Y., SUN J., SONG H. & LI X.,
2008 - Monsoon precipitation variation recorded by tree-ring δ18O
in arid Northwest China since AD 1878. Chemical Geology, 252 (1),
56-61.
MANTESE N., PENNA D., ZUECCO G., BORGA M.,
ANFODILLO T., CARRARO V. & DALLA FONTANA G.,
2012 - Analysis of runoff sources and water uptake by trees using
isotopic data in a small forested catchment. EGU General Assembly
2012, Geophysical Research Abstracts, 14, 5820.
MCCARROLL D. & LOADER N.J., 2004 - Stable isotopes in tree
rings. Quaternary Science Reviews, 23 (7-8), 771-801.
MERZ R. & BLÖSCHL G., 2003 - A process typology of regional floods.
Water Resources Research, 39 (12), doi:10.1029/2002WR001952.
MERZ R. & BLÖSCHL G., 2008 - Flood frequency hydrology: 1.
Temporal, spatial, and causal expansion of information. Water
Resources Research, 44 (8), doi:10.1029/2007WR006744.
MERZ B., THIEKEN A.H. & GOCHT M., 2007 - Flood risk mapping
at the local scale: concepts and challanges. In S. Begum, M.J.F. Stive
& J.W. Hall (eds.), Flood Risk Management in Europe - innovation in
policy and practice. Springer, Dordrecht, 231-251.
MICHELOT A., BRÉDA N., DAMESIN C. & DUFRÊNE E.,
2012 - Differing growth responses to climatic variations and soil
water deficits of Fagus sylvatica, Quercus petraea and Pinus sylvestris in a temperate forest. Forest Ecology and Management, 265,
161-171.
MICHELOT A., EGLIN T., DUFRÊNE E., LELARGETROUVERIE C. & DAMESIN C., 2011 - Comparison of seasonal
variations in water-use efficiency calculated from the carbon isotope
composition of tree rings and flux data in a temperate forest. Plant,
Cell and Environment, 34 (2), 230-244.
MITCHELL J.K., 2003 - European river floods in a changing world.
Risk Analysis, 23 (3), 567-574.
NINYEROLA M., PONS X. & ROURE J.M., 2000 - A methodological approach of climatological modelling of air temperature
and precipitation through GIS techniques. International Journal of
Climatology, 20 (14), 1823-1841.
OFFERMANN C., FERRIO J.P., HOLST J., GROTE R.,
SIEGWOLF R., KAYLER Z. & GESSLER A., 2011 - The long
way down–Are carbon and oxygen isotope signals in the tree ring
uncoupled from canopy physiological processes? Tree Physiology,
31 (10), 1088-1102.
PENNA D., OLIVIERO O., ASSENDELFT R., ZUECCO G., VAN
MEERVELD I.H.J., ANFODILLO T., CARRARO V., BORGA
M. & DALLA FONTANA G., 2013 - Tracing the water sources of
11/02/15 13:45
80
trees and streams: isotopic analysis in a small pre-alpine catchment.
Procedia Environmental Sciences, 19, 106-112.
PIELKE JR. R.A. & DOWNTON M.W., 2000 - Precipitation and
damaging floods: Trends in the United States, 1932-97. Journal of
Climate, 13 (20), 3625-3637.
POUSSART P.F. & SCHRAG D.P., 2005 - Seasonally resolved stable
isotope chronologies from northern Thailand deciduous trees. Earth
and Planetary Science Letters, 235 (3), 752-765.
SAURER M., AELLEN K. & SIEGWOLF R., 1997 - Correlating
δ13C and δ18O in cellulose of trees. Plant, Cell and Environment, 20
(12), 1543-1550.
SIGAFOOS R.S., 1964 - Botanical evidence of floods and floodplain deposition. Geological Survey Professional Paper, 485-A. US
Government Printing Office, Washington, 34 p.
ST. GEORGE S., 2010 - Tree rings as paleoflood and paleostage indicators. In M. Stoffel, M. Bollschweiler, D.R. Butler & B.H. Luckman
(eds.), Tree Rings and Natural Hazards. Advances in Global Change
Research, 41. Springer, Dordrecht, 233-239.
STERNBERG L.D.L., PINZON M.C., ANDERSON W.T. &
JAHREN A.H., 2006 - Variation in oxygen isotope fractionation
during cellulose synthesis: intramolecular and biosynthetic effects.
Plant, Cell & Environment, 29 (10), 1881-1889.
STOFFEL M. & WILFORD D.J., 2012 - Hydrogeomorphic processes
and vegetation: disturbance, process histories, dependencies and
interactions. Earth Surface Processes and Landforms, 37 (1), 9-22.
1501-012-Mep1-2015.indd 80
TANG K. & FENG X., 2001 - The effect of soil hydrology on the
oxygen and hydrogen isotopic compositions of plants’ source water.
Earth and Planetary Science Letters, 185 (3), 355-367.
TREYDTE K., SCHLESER G.H., HELLE G., FRANK D.C.,
WINIGER M., HAUG G.H. & ESPER J., 2006 - The twentieth
century was the wettest period in northern Pakistan over the past
millennium. Nature, 440 (7088), 1179-1182.
TREYDTE K., FRANK D., ESPER J., ANDREU L., BEDNARZ
Z., BERNINGER F., BOETTGER T., D’ALESSANDRO C.M.,
ETIEN N. & FILOT M., 2007 - Signal strength and climate calibration of a European tree-ring isotope network. Geophysical Research
Letters, 34 (6), L24302.
TREYDTE K., BODA S., GRAF PANNATIER E., FONTI P., FRANK
D., ULLRICH B., SAURER M., SIEGWOLF R., BATTIPAGLIA
G., WERNER W. & GESSLER A., 2014 - Seasonal transfer of
oxygen isotopes from precipitation and soil to the tree ring: source
water versus needle water enrichment. New Phytologist, 202 (3),
772-783.
YAKIR D., 1992 - Variations in the natural abundance of oxygen-18
and deuterium in plant carbohydrates. Plant, Cell and Environment,
15 (9), 1005-1020.
11/02/15 13:45