Volume 43, Issue 15 pp. 2983-2997
Research Article
Full Access

Quantification of cliff retreat in coastal Quaternary sediments using anatomical changes in exposed tree roots

Jérôme Lopez-Saez

Corresponding Author

Jérôme Lopez-Saez

Institute for Environmental Sciences, Climate Change Impacts and Risks in the Anthropocene (C-CIA), University of Geneva, Geneva, Switzerland

Correspondence to: Jérôme Lopez-Saez, Institute for Environmental Sciences, Climate Change Impacts and Risks in the Anthropocene (C-CIA), University of Geneva, 66 Boulevard Carl-Vogt, CH-1205 Geneva, Switzerland. E-mail: [email protected]Search for more papers by this author
Christophe Corona

Christophe Corona

Centre National de la Recherche Scientifique (CNRS), UMR 6042, GEOLAB, Clermont-Ferrand, Cedex, France

Search for more papers by this author
Pauline Morel

Pauline Morel

Irstea, UR LESSEM, Université Grenoble Alpes, St-Martin-d'Hères, France

Search for more papers by this author
Georges Rovéra

Georges Rovéra

CNRS, UMR 5194 PACTE Territoires, Grenoble, France

Search for more papers by this author
Thomas J.B. Dewez

Thomas J.B. Dewez

Risk and Prevention Direction BRGM, Orléans 45060 and PACA Territorial Direction, Marseille, France

Search for more papers by this author
Markus Stoffel

Markus Stoffel

Institute for Environmental Sciences, Climate Change Impacts and Risks in the Anthropocene (C-CIA), University of Geneva, Geneva, Switzerland

Search for more papers by this author
Frédéric Berger

Frédéric Berger

Irstea, UR LESSEM, Université Grenoble Alpes, St-Martin-d'Hères, France

Search for more papers by this author
First published: 28 June 2018
Citations: 7

Abstract

Sea cliffs represent 80% of the world's coasts and can be found virtually in all types of morphogenetic environments. Most studies on rocky environments focused on the impacts of modern sea level rise on cliff stability derived from sequential surveys, direct measurements or erosional features in anthropogenic structures. In this study, we explore the potential of dendrogeomorphic techniques to quantify multidecadal changes in coastal environments on Porquerolles Island (France). We sampled a total of 56 cross-sections from 16 Pinus halepensis Mill. roots growing on former alluvial deposits and on sandy-gravelly cliffs to quantify mean annual cliff retreat rates as well as changes in cliff geometry. Anatomical changes in roots have been used successfully in the past to quantify continuous denudation rates on slopes, channel incision and gullying processes but the approach has not been used so far in a coastal cliff context. At Porquerolles Island, reconstructed rates of cliff retreat cover 30–40 years and show average erosion rates between 0.6 and 3.9 cm yr−1 (average: 2.1 cm yr−1). Highest rates are observed at Pointe de la Tufière (2.6–3.9 cm yr−1), a small rock promontory that is more exposed to wave and storm surges than the remainder of the study area. By contrast, lower erosion rates are recorded at cliffs protected by the La Courtade pocket beach (0.6–1.9 cm yr−1). This contribution demonstrates that dendrogeomorphic analyses of roots clearly have a significant potential and that they are a powerful tool for the quantification of multidecadal rates of cliff retreat in areas where measurements of past erosion are lacking. More specifically, the approach also has clear advantages over the shorter time series obtained with repeat monitoring (e.g. terrestrial laser scanning, sensors, erosion pins) or over longer, but more coarsely resolved records obtained from aerial photographs or radio-nuclides. © 2018 John Wiley & Sons, Ltd.

Introduction

Sea cliffs comprise 80% of the world's coasts (Granja, 2009), along which almost one-fourth of the global population resides (Small and Nicholls, 2003; Young et al., 2009a). Coastal changes and erosion therefore can induce a threat for human activity and safety. Indeed, seacliff erosion not only threatens coastal structures, but may also negatively affect public property, recreational resources, public safety, and major transportation corridors. As a result of the predicted acceleration of coastal erosion due to climatic changes and the related sea-level rise (Zhang et al., 2004; Hurst et al., 2016, Naylor et al., 2017), cliff retreat has been the subject of a wealth of studies which mostly aimed at the quantification of erosional phenomena and their timescales (Katz and Mushkin, 2013; Trenhaile, 2014; see Table 1 for a recent review). Conventional techniques used to quantify cliff retreat include erosion pins installed at the base of rock masses, repeat aerial photography, comparison of different generations of topographic maps, or in situ surveys (Lim et al., 2005; Brooks and Spencer, 2010; Dornbusch et al., 2008). More recently, cosmogenic radionuclides as well as LiDAR (light detection and ranging) and stereophotogrammetric surveys have been used (i) to date and/or quantify changes in the coastal zone and (ii) to demonstrate their huge potential to monitor and model cliff erosion (e.g. Young et al., 2009a; Lim et al., 2010; Regard et al., 2012; Earlie et al., 2015a, 2015b; Hurst et al., 2016). As a result of the great monitoring efforts required, observational time series of long-term erosion cliff retreat remain exceptional, and thereby prevent the creation of reliable data on average cliff retreat at larger (decadal to centennial) temporal scales. Other indirect methods might thus be needed to assess longer term process activity and the correlation and interdependence of the latter with environmental changes. In this paper the dendrogeomorphic analysis (Alestalo, 1971; Stoffel and Bollschweiler, 2008; Stoffel et al., 2010) of exposed tree roots and the interpretation of anomalies registered in their growth rings are used as an alternative to the methods traditionally used to quantify cliff recession.

Table 1. Overview of work published on coastal cliff retreat. Identifiers are the same as in Figure 7
Index Author(s), Year Journals Country Latitude (deg) Longitude (deg) Location Lithology Erosion rate (m yr-1) Methods Period
1 Agar, 1960 Proceedings UK 54.6 −1.06 North Yorkshire Mudstone, sandstone 0.03 Photogrammetry 1892–1960
2 Andriani and Walsh, 2007 Geomorphology Italy 41 17.2 Apullia Biocalcarenites 0.2 Photogrammetry 1930–2003
3 Borges, 2003 PhD Thesis Portugal 37.8 −25.5 Azore archipelago Rocky coast 0.05 NA NA
4 Brooks and Spencer, 2010 Geomorphology UK 52.37 1.7 Suffolk Softrock 0.9–3.5 Historic maps 1983–2003
5 Brooks et al., 2012 Geomorphology UK 52.3 1.68 Suffolk Softrock 3.5 Photogrammetry 1883–2010
6 Brooks et al., 2016 Earth Surface Processes and Landforms UK 52.95 0.81 Norfolk mud- and sand-flats 1.15 Aerial photograph 1891–2013
7 Lopez-Saez et al., this study Earth Surface Processes and Landforms France 43.01 6.3 Porquerolles Sandstone 0.021 Exposed roots 1976–2011
8 Costa et al., 2004 Engineering Geology France 50.1 1.45 Normandy Chalk 0.3 NA 1966–1995
9 Dornbusch et al., 2008 Marine Geology UK 50.76 0.11 Sussex Chalk 0.35 Photogrammetry 1873–2001
10 Earlie et al., 2015a Journal of Coastal Conservation UK 50.15 5.03 Cornwall Softrock <0.1–0.5 LiDAR 2007–2011
11 Earlie et al., 2015b Geophysical Research Letter UK 50.05 5.18 Cornwall Softrock 0.09 LiDAR 2007–2011
12 Greenwood and Orford, 2007 Geomorphology UK 54.48 −5.58 Strangford Lough Glacigenic sediments 0.08 Erosion pines 1994–1997
13 Hall et al., 2002 Coastal Engineering UK 50.88 0.68 Sussex Softrock 0.47 Historic maps 1907–1991
14 Hapke and Green, 2004 USGS USA 37 −122 California Various 0.12–0.25 Various Various
15 Harper, 1978 Arctic USA 71.3 −156.8 Alaska Silts and sands 0.3 Photogrammetry 1949–1976
16 Henaff et al., 2002 Géomorphologie France 49.7 0.2 Pays de Caux Chalk 0.06 Photogrammetry 1824–1986
17 Kumar et al., 2009 Environmental Geology India 10.76 75.91 Kerala Sandstone, clay and silt 0.5 GPS survey 2004–2006
18 Lee, 2008 Geomorphology UK 52.93 1.3 Norfolk Sand and clay 1.05 GPS survey 1992–2003
19 Lim et al., 2009 Journal of Coastal Research South Korea 35.5 126.25 Hampyung Bay Soft soil 1.4 Aerial photograph 1976–1990
20 Marques, 2003 Proceedings Morocco 35.2 −6.15 Larache Sandstone 0.08 Photogrammetry 1961–1997
21 Marques, 1997 PhD Thesis Portugal 37.01 −8.01 Algarve Sandstone 0.019 Photogrammetry 1947–1991
23 Moon and Healy, 1994 Journal of Coastal Research New Zealand −36.8 174.75 Auckland Sandstone and silstone 0.04 Dated structures NA
24 Moore and Griggs, 2002 Marine Geology USA 36.97 −122.03 California Sandstone and silstone 0.15 Photogrammetry 1953–1994
25 Orviku et al., 2013 Journal of Coastal Research Estonia 59.45 24.53 Kakumae Sandstone 0.6 Field survey 1996–2006
26 Pierre, 2006 Geomorphology France 50.8 1.58 Boulonnais Clay and sandstone 0.08 Photogrammetry 1939–2003
27 Poulton et al., 2006 Bulletin of the Geological Society of Norfolk UK 52.49 1.31 Norfolk Softrock 8.75 Various 1992–2004
29 Rudberg, 1967 Geografiska annaler Sweden 57.4 18.8 Gotland Limestone and marl 0.05 Photogrammetry 1899–1955
30 Stephensen et al., 2012 Marine Geology Australia −38.32 143.58 Victoria Sandstone and mudstone 0.00031 Field survey 1979–2011
32 Wangensteen et al., 2007 Polar Research Norway 78.26 21.95 Svalbard Dolomit limestone 0.003 Photogrammetry 2002–2004
33 Xeidakis et al., 2007 Environmental Geology Greece 40.84 25.87 Alexandroupolis Sandy-silty sediments 0.5 Photogrammetry NA
34 Young and Ahsford, 2006 Journal of Coastal Research USA 33.12 −117.19 California Mudstone and sandstone 0.08 LiDAR 1998–2004
35 Young et al., 2009a Geomorphology USA 36.96 −121.98 California Sand and clay 0.3 LiDAR 2002–2006
36 Zviely and Klein, 2004 Earth Surface Processes and Landforms Israel 32.38 34.86 Beit–Yannay Quartzose 0.2 Photogrammetry 1918–2000

Dendrogeomorphology is typically used at locations where geomorphic process activity interferes in space and time with vegetation (Stoffel and Bollschweiler, 2008; Stoffel et al., 2010). The approach, first elucidated by Alestalo (1971), takes advantage of the fact that trees growing in temperate climates do not only form yearly increment rings but that they will also record the occurrence of external disturbances in their growth-ring record, thus allowing accurate dating and reconstruction of past process histories (Stoffel and Corona, 2014). Previous dendrogeomorphic work focused primarily on tree stem and only to a lesser extent on tree roots. In addition, research on roots was mostly centered on the sprouting of adventitious roots to infer sediment deposition during floods (Martens, 1993; Nakamura et al., 1995) or debris flows (Strunk, 1989, 1991, 1997). Another focus was on the determination of aerial erosion rates over timescales of hundreds to thousands of years, based on the ratio between the minimum depth of erosion – obtained from the reconstructed root diameter at the moment of denudation – and the time (i.e. number of growth rings) passed since root exposure (Eardley and Viavant, 1967; LaMarche, 1968; Gärtner, 2001; McAuliffe et al., 2006). More recently, microscopic approaches have been used to determine the year of exposure. These approaches focus on changes in the anatomical structure of tracheids in conifer roots (Corona et al., 2011b; see Stoffel et al., 2013, for a detailed review). The approach has been used in various environments, but mostly in relation with gullying processes (Vandekerckhove, 2001; Malik, 2008; Ballesteros-Cánovas et al., 2017), aerial (or sheet) (Bodoque et al., 2005; Lopez Saez et al., 2011; Lucía et al., 2011), river bank (Malik, 2006; Hitz et al., 2008a; Stoffel et al., 2012), or lake shore (Fantucci, 2007) erosion (see Table 2 for an overview).

Table 2. Overview of published reconstructions of erosion using dendrogeomorphic techniques
Process Environment Location Latitude Longitude Rates (mm yr−1) Number of roots Number of samples References
Bank erosion Riverbank Patagonia 40°56′ S 71°24′ W 31 64 Stoffel et al., 2012
Bank erosion Riverbank Czech Republic 50°15′ N 15°05′ E 23 60 Malik and Matyja, 2008
Bank erosion Riverbank Switzerland & Germany 46°17′ N 7°32′ E 18 38 Gärtner et al., 2001
Gully retreat Gullies Czech Republic 49°22′ N 18°7′ E 150–3000 21 21 Silhan, 2012
Gully retreat Gullies Poland 50°21′ N 17°51′ E 0.63 28 53 Malik, 2008
Sheet erosion Gullies Spain 41°10′ N 3°48′ W 6.2 21 21 Bodoque et al., 2015
Sheet erosion Hillslopes China 36°69′ N 102°71′ E 3.3–13.5 23 40 Zhou et al., 2013
Sheet erosion Hillslopes Iran 0.54 42 42 Bahrami et al., 2011
Sheet erosion Badlands Spain 41°10′ N 3°48′ W 6.2–8.8 29 29 Bodoque et al., 2011
Sheet erosion Gullies France 44°08′ N 6°20′ E 5.9–6.2 17 39 Corona et al., 2011a
Sheet erosion Gullies France 44°08′ N 6°20′ E 5.9 27 48 Lopez-Saez et al., 2011
Sheet erosion Hiking trails Spain 40°59′ N 4°05′ E 18 18 Rubiales et al., 2008
Sheet erosion Forest Spain 40°12′ N 3°34′ W 3.5–8.8 49 49 Pérez-Rodriguez et al., 2007
Sheet erosion Hillslopes USA 36°09′ N 109°33′ W 2.0–3.0 Wawrzyniec et al., 2007
Sheet erosion Hillslopes USA 36°09′ N 109°33′ W 1.9 49 49 Scuderi et al., 2008
Sheet erosion Hiking trails Spain 40°52′ N 4°01′ W 1.6–2.6 86 86 Bodoque et al., 2005
Sheet erosion Various USA 39°20′ N 106°52′ W 1.18 20 83 Carrara and Carroll, 1979
Shore erosion Lakes USA 32°23′ N 110°42′ W 1 Danzer, 1996
Soil erosion Badlands France 44°08′ N 6°20′ E 0.5 23 123 Corona et al., 2011b
Soil erosion Karst area China 14°26′ N 105°42′ E 24 24 Luo et al., 2011
Soil erosion Rangelands Patagonia 42°58′ S 64°20′ W 2.4–3.2 15 15 Chartier et al., 2009
Soil erosion Gullies Poland 50°04′ N 14°24′ E 28 53 Malik, 2006
Soil erosion Hiking trails Italy 46°24′ N 10°31′ E 2.7 72 72 Pelfini and Santilli, 2006
Soil erosion Roadcut USA 10.0–11.0 41 41 Megahan et al., 1983
Soil erosion Rangelands Kenya 1°26′ S 36°57′ E 5.5 14 14 Dunne et al., 1978
Bank erosion Riverbank USA 78°51′ N 38°7′ W 3.85 73 73 Stotts et al., 2014
Sheet erosion Gullies Spain 41°9′ N 3°48′ W 4.4–8.8 46 46 Ballesteros-Cánovas et al., 2015
Soil erosion Karst area China 11 22 Mei et al., 2015
Soil erosion Methodological contribution NA Ballesteros-Cánovas et al., 2013
Soil erosion NA China 25°41′ N 101°49′ E 1.04–3.61 25 136 Sun et al., 2014
Bank erosion Riverbank USA 1–259 46 78 Dick et al., 2013
Soil erosion Rills and gullies Argentina 31°34′ S 64°50′ W 14 14 Chartier et al., 2016
Coastal erosion See shore France 43°00′ N 6°21′ E 21 17 56 Present study

In this contribution, we aim at testing the potential of wood-anatomical signatures in tree roots to quantify spatial and temporal changes in cliff retreat in a marine context and at vertical sites for which roots have not been employed in the past. We document erosion signals and rates of erosion for 56 cross-sections selected from Pinus halepensis Mill. roots from sandy-gravelly cliffs and compare results with rates found in the literature and for sites located next to our study region on Porquerolles Island.

Study Site

Porquerolles Island (Var, France) is located in the Mediterranean Sea, east-southeast (E-SE) of Toulon; the island belongs to the Hyères Islands, which are partially closing the natural Hyères harbor (Figure 1A). Porquerolles Island is 7.5 km long, 1.7 km wide, reaches 142 m above sea level (a.s.l.), and has a surface of 12.54 km2. The south (S) and southwest (SW) coasts of Porquerolles are lined with cliffs, whereas the north (N) and northwest (NW) coasts exhibit an alternation of small capes (Pointe de Lequin, Pointe Bon-Renaud) and beaches, with the latter being located predominantly at the mouth of floodplains (Notre-Dame, La Courtade, Plage d'Argent).

Details are in the caption following the image
(A) Location of the study site; (B) compass showing the main wind directions over Porquerolles; (C) simplified geological map of Porquerolles Island adapted from Bellot (2004): 1. Fluvial deposit, 2. Succesion of sandstone/schist, 3. Sandstone, 4. Schist, 5. Succesion of finely conglomeratic sandstone/banded schist interleaved with limestone 6. Finequartzite, 7. Yellow quartzitesfrom Cap des Mèdes, 8. Schists/micaschists, 9. Black- green-schists, quartzites, sandstone, 10. Monotonous green schists, 11. Schist interleaved with metabasit and calcschist, 12. Ductile srtike-slip fault (potential and observed); (D) the northern part of La Courtade beach is characterized by an alternation of rocky headlands (phyllite) as well as (E) by pocket beaches dominated by sandy-gravelly cliffs affected by erosion. [Colour figure can be viewed at wileyonlinelibrary.com]

Some parts of the coastline display small cliffs (up to 5 m in height) composed of sands and gravels, laid behind beaches and next to capes. In this study we focused on such cliffs located in the area of La Courtade (43°003 N; 6°213 E; Figure 1C). The island has a geological structure very similar to that of the Maures massif (Bordet et al., 1976); it consists predominantly of phyllitic rocks (Figure 1C) which alternate with quartzite veins. The most important units form a large N–S ridge and extend from Cape des Medes to Mont-Sarranier (126 m). The cliffs investigated here are dark and light ocher in color and consist of a consolidated sandy-gravelly matrix of paleo-alluvial origin (Würmian age, Bordet et al., 1976). The base of the cliffs (Figures 2A and 2B) consists of compact sands (stratum 1) covered with torrential strata revealing angular, decimetric (stratum 2) to centimetric (stratum 3) phyllite and quartzite debris of periglacial origin. The uppermost layer of the cliff is formed by sand and gravel horizons (stratum 4). The deposits under investigation have been affected by sea erosion throughout the Holocene to form receding cliffs located behind pocket beaches (Figures 1D and 1E). As described by Lee (2008), cliff recession is characterized by the balance between the strength of cliff materials and the stresses imposed on the cliff by gravity and the kinetic energy of waves at the cliff foot. Albeit slope processes dominate recession rates in sheltered inlets and bays (e.g. Greenwood and Orford, 2007), most of the time geological materials and wave attack are the dominant factors leading to open-coast recessions processes (Sunamura, 1992; Costa et al., 2004; Lee, 2008). Present-day erosion processes are driven by ongoing sea-level rise and themechanical erosion of the cliffs (e.g. swell in particular) as well as by subaerial processes. Observations also point to the importance of Mistral winds (blowing from NW, after the passage of low-pressure systems in the Gulf of Genoa) on wave action and thus on erosion processes (Gervais, 2012) (Figure 1B). This wind system also leads to storm surges and the hydration of cliffs. The short foreshore (5–10 m) and the small difference in height between the average level of the water and the bottom of the cliffs (0.5–1 m) allow waves and swells to directly impact the foot of the cliffs. Some notches are thus carved up to 1 m in height and at depths of several decimeters (Figures 1D and 1E.). These sporadic episodes of storm-related erosion are complemented by surficial and quasi-continuous rill erosion, with the latter being driven by seasonal variations in weather and the rhythmicity of splash, desiccation–hydration alternations, or salt weathering.

Details are in the caption following the image
(A) Segment of a sandy-gravelly cliff close to the Pointe de la Tufière. (B) The base of the landform corresponds to (1) a compact sandy stratum and a torrential deposit revealing decimetric (2) to centimetric (3) angular phyllite and quartzite debris. The upper part is made of (4) sand and gravel horizons, sometimes individual, sometimes overlapping. Cliff retreat is revealed by the exposure of a Pinus halepensis Mill. root. [Colour figure can be viewed at wileyonlinelibrary.com]

Material and Methods

Methods of cliff retreat reconstruction

For a precise quantification of the cliff retreat based on root exposure, two parameters are needed: the number of annual rings since exposure (NRex) and the thickness of the eroded soil layer (Er). When a root loses its soil cover, a series of anatomical changes (cell size, tangential growth, compression wood) will occur in terms of ring growth, firstly because of the effect of the exposure itself (e.g. variations in edaphic temperature and humidity, reduction in soil cover pressure), but also because of mechanical stress (e.g. abrasion) that a root will undergo when exposed. As proposed by Corona et al. (2011b), a reduction of cell lumen area in earlywood tracheids by about 50% can be used as a distinct sign of exposure in conifer roots (Figure 3). To calculate the annual erosion rate Era, Er is divided by the number of rings formed since the year of exposure (NRex):
urn:x-wiley:01979337:media:esp4462:esp4462-math-0001(1)
Details are in the caption following the image
Micro-sections of roots R17.1 and R17.2 with exposure signals in 1997 and 2000, respectively. Determination of exposure years was based on the sharp decrease of cell lumen area of earlywood tracheids. [Colour figure can be viewed at wileyonlinelibrary.com]

Sampling strategy and root-ring analysis

At the study site, 56 root cross-sections (six from buried and 50 from exposed roots) were sampled from 16 different roots of 16 P. halepensis Mill. trees, and at a minimum distance of 50 cm from the stem basis. This distance has been chosen as (i) stem movement induced by ongoing growth tends to pull roots upwards (Stokes and Berthier, 2000), and as (ii) roots close to the stem basis and growing near the soil surface often experience bending stress resulting from stem displacement (Watson, 2000), and therefore exhibit asymmetric growth structures in cross-sections. The position of exposed roots with respect to the present cliff surface was documented in detail before the root was actually cut and data recorded on the stratigraphic position, distance of the root section from the tree trunk, aspect, and slope (for a complete description of the method, see Corona et al., 2011b). The horizontal distance between the root and the cliff surface (Er) was determined with a depth gage (accuracy ±1 mm); in cases where the distance between the root and the cliff exceeded 25 cm, a metal ruler (±5 mm) was used instead. Root sample locations were recorded using a Trimble GeoExplorer (with < 1 m accuracy) and roots were then positioned in a geographical information system (GIS; ArcGIS 10.1; Kennedy, 2009) as geo-objects, where erosion rates could be linked as attributes to each single root section.

In the field, the root sampling strategy was defined according to geomorphic units (i.e. rocky point, pocket beach) and to the stratigraphic profile of the cliffs (Figures 2A and 2B). Samples were distributed within the two geomorphic units and the four strata of the stratigraphic profile. In order to determine Nrex, sampled roots were then cut into discs about 2 cm thick and air-dried for ~30 days, before they were prepared for macroscopic analysis (i.e. sanded sequentially with 60, 80, 320, and 600 grit-sanding belts). Ring-width data were obtained on four radii per cross-section using a LINTAB measurement device (Rinn and Jäkel, 1996). Thereafter, we prepared root discs for microscopic analysis. Small cubes were cut from the cross-sections (maximum 2 cm × 4 cm) from which micro-sections where cut with a Reichert sliding microtome (thickness of cuts ~15 μm). The microsections were treated with sodium hypochlorite (NaOCl) solution, deionized water, and soluble safranin before they were dehydrated with alcohol and xylol (Schweingruber, 1978; Arbellay et al., 2012). The microsections were mounted on slides, embedded in Canada balsam, and dried at 60°C for 24 hours. Microsections were then observed and photographed with a digital imaging system under optical microscopy. Measurement of cell lumen area in earlywood tracheids was performed with the semi-automated WinCELL2005 software. Following Rubiales et al. (2008), cell lumen area was determined through an averaging of 12 cell measurements per growth ring. In addition, and in order to detect potential anatomical changes that could occur before root exposure (Corona et al., 2011b) and to assess the maximum depth at which anatomical changes may occur, we compared cell changes in exposed sections with those observed in buried sections embedded into the cliff (−2 to −18 cm, Table 3) (Corona et al., 2011b).

Table 3. Characterization of root sections and erosion rates determined from wood anatomical changes
ID tree ID of cross section Geomorphic unit Stratum Ex (cm) Age (years) Year of exposure NRex (years) Erosion rate (root section scale, cm yr−1) Erosion rate (root scale, cm yr−1)
1 1 Pb 2 5.2 18 2000 12 0.4 0.9
1 2 Pb 2 10.5 19 2000 12 0.875
1 3 Pb 1 14.5 20 2000 12 1.2
1 4 Pb 1 13 19 2000 12 1.08
3 1 Rp 4 45 28 1996 16 2.81 2.7
3 2 Rp 3 50 28 1994 18 2.78
3 3 Rp 2 62 26 1994 18 3.44
3 4 Rp 2 60 28 1994 18 3.33
3 5 Rp 1 60 26 1994 18 3.33
3 6 Rp 1 55 28 1991 21 2.61
3 7 Rp 1 34 29 1996 16 2.12
3 8 Rp 1 18 29 1998 14 1.28
4 1 Rp 3 27.5 15 2004 8 3.05 2.4
4 2 Rp 3 23 14 2005 7 3.28
4 3 Rp 3 21 13 2003 9 2.33
4 4 Rp 2 13.7 15 2004 8 1.71
4 5 Rp 2 8.5 17 2006 6 1.41
5 1 Rp 4 28 15 2004 8 3.5 3.9
5 2 Rp 4 34.5 14 2004 8 4.31
5 3 Rp 4 (B) −3 15
5 4 Rp 4 (B) −10 17
5 5 Rp 4 (B) −18 16
6 1 Pb 3 6.5 22 2002 10 0.65 1.5
6 2 Pb 3 15 20 2002 10 1.5
6 3 Pb 3 22.5 26 2002 10 2.25
7 1 Pb 3 4.5 19 2002 10 0.45 0.6
7 2 Pb 3 4 19 2002 10 0.4
7 3 Pb 3 9.5 19 2002 10 0.95
8 1 Pb 3 5 23 2002 10 1.05 1.05
8 2 Pb 3 10.5 20 2002 10 1.05
9 1 Pb 3 17.5 18 2005 7 2.5 1.9
9 2 Pb 3 6 18 2006 6 2.91
9 3 Pb 3 12.5 19 2005 7 1.78
9 4 Pb 3 12 19 2002 10 1.2
9 5 Pb 3 12 18 2004 8 1.5
10 1 Pb 2 15 22 2001 11 1.36 0.9
10 2 Pb 2 5 23 2001 11 0.45
11 1 Pb 3 43 20 1996 16 2.68 1.7
11 2 Pb 2 10.5 19 1998 14 0.75
12 1 Pb 3 50 28 1995 17 2.94 2.4
12 2 Pb 2 33.5 27 1995 17 1.97
13 1 Pb 3 8 20 2001 11 0.72 0.6
13 2 Pb 3 4 20 2003 9 0.44
14 1 Pb 2 2 15 2006 6 3.33 2.5
14 2 Pb 2 17.8 14 2006 6 2.96
15 1 Pb 3 21 26 1997 15 1.4 1.6
15 2 Pb 3 21.5 28 2000 12 1.79
16 1 Pb 4 87 35 1995 17 5.11 3.9
16 2 Pb 4 48 33 1998 14 3.42
16 3 Pb 3 48 34 2000 12 4
16 4 Pb 3 37.5 36 2000 12 3.125
16 5 Pb 3 (B) −2 32
16 6 Pb 3 (B) −8 33
16 7 Pb 3 (B) −13 37
17 1 Pb 4 54 33 1997 15 3.6 3.3
17 2 Pb 3 36 27 2000 12 3
  • Note: Pb = pocket beach; Rp = Rocky point; B = buried.

Results

Anatomical changes in roots

The innermost rings of the roots sampled were dated to between ad 1976 (R16.4) and 1999 (R4.3), with a mean root age of 22 years and a standard deviation of ±6 years (Table 3). The wood anatomical structure of the exposed root sections R17.1 and R17.2, shown in Figure 3 for the years 1988–2011 and 1989–2011, respectively, illustrates anatomical changes that occurred in each section after exposure. Both samples were taken half way up the cliff (strata 2 and 3). These roots show thin cell walls and large cell lumina in earlywood tracheids until 1996 (R17.1) and 1999 (R17.2), respectively. From 1997 (2000) onwards, root rings form thicker-walled tracheids and more stem-like wood structures, with very distinct latewood and cell lumen area reductions > 50% (from 2560 to 982 μm2, or −62% for R17.1; and from 3600 to 900 μm2, or −75%, for R17.2, respectively). Similar sudden and sharp relative reductions in cell lumen area as those described earlier are observed for all exposed roots chosen for analysis between 1991 and 2006 (mean: 2000; Table 3). Conversely, the buried parts of the roots sampled in this study (i.e. R5.3 to R5.5 and R16.5 to R16.7, located at depth ranging from −2 to −18 cm within the strata) are characterized by large tracheids with thin and poorly lignified cell walls as typical for buried roots.

Heights of the exposed parts of the 50 cross-sections of roots – as measured in the field (Er) – varied from 2 to 87 cm (mean: 30.4 cm), representing an overall mean erosion rate of 2.1 ± 1.2 cm yr−1 at the study site.

Variability of erosion rates

At the scale of individual roots, erosion rates varied between 0.6 (R7 and R13) and 3.9 cm yr−1 (R5 and R16, Table 3). The largest erosion values were observed in roots (R3, R4, R5) sampled at Pointe de la Tufière located in the northeast (NE) part of the study site (Figure 4) and where the cliff is exposed directly to waves and storm surges. As a consequence, cliff retreat varies between 2.3 and 3.9 cm yr−1 here. Conversely, those roots sampled on cliffs backing La Courtade pocket beach (R1, R6–R10, R13, R15), sometimes protected by a vegetation buffer (R13, R15), recorded remarkably lower erosion rates ranging from 0.6 to 1.9 cm yr−1.

Details are in the caption following the image
Cliff retreat map reconstructed from anatomical changes in exposed roots. Squares, on the right panels, represent mean erosion rates as computed for each of the 16 sampled roots. Dots, on the left panels, represent erosion rates as computed for each of the 50 sections. [Colour figure can be viewed at wileyonlinelibrary.com]

At the root section scale, heterogeneous erosion rates are reconstructed for sections within the same root. For example, high variability between sections of the same root is observed in R11. Here the ratio between the smallest and largest erosion rates is 1:3.6 (R11.2 in stratum 2 with 0.75 cm yr−1; R11.1 in stratum 3 with 2.7 cm yr−1). Similar differences are observed in R1 with a ratio of 1:3 between R1.1 (stratum 2, 0.4 cm yr−1) and R1.3 (stratum 1, 1.2 cm yr−1). According to the stratigraphic profile, highest erosion rates are reconstructed for root sections located in the upper part of the profile, i.e. in the sandy-gravelly stratum 4 (3.8 ± 0.8 cm yr−1). Conversely, lower (1.8–2 cm yr−1), but more variable, cliff retreat rates are measured in strata 1 (sandy stratum), 2, and 3 (torrential strata, Figure 5).

Details are in the caption following the image
Comparison of cliff retreat for each stratum derived from anatomical changes in tree roots. 1. Sandy stratum, 2. Torrential deposits with decimetric debris, 3. Torrential deposit with centimetric debris, 4. Top sandy-gravelly stratum.

Reconstruction of cliff profiles

Dendrogeomorphic analyses do not only allow detection of root exposure processes with annual resolution, but also enable reconstruction of past cliff surface positions with centimetric precision. The use of exposed roots intersecting several strata therefore also allows the reconstruction of the spatio-temporal evolution of cliff profiles, as exemplified in Figure 6. The combined analysis of root positions and years of exposure thus provides a chronological framework to study cliff evolution and permits determination of erosion processes. By way of example, erosion at the level of root R3 occurred in three stages. The first stage corresponds to the first year of root exposure in 1991 at the level of sample R3.6, where anatomical changes can be observed in the cell structure of the root. This portion of the root was located in a top layer of fine sand (stratum 1). By contrast, no significant cell variations are observed in the other sections in that year. The second stage occurred in 1994 when anatomical changes start to occur in sections R3.2 to R3.5. This stage corresponds to a marked retreat in strata 1, 2, and 3, and is interpreted as the impact of a small landslide out of the notch in the weak sandy stratum. The third stage was initiated in 1996 and corresponds to a slow evolution of the top of the profile (stratum 4) as revealed by anatomical changes in R3.1 and to a delayed exposure of the foot cliff revealed by the exposure of R3.8 in 1998.

Details are in the caption following the image
Evolution of cliff profiles since 1991 exemplified from root R3. Determination of exposure years was based on the sharp decrease of cell lumen area of earlywood tracheids. [Colour figure can be viewed at wileyonlinelibrary.com]

Discussion

Occurrence of anatomical changes in buried roots

In this study, we investigate the wood anatomical reaction of roots of P. halepensis Mill. to denudation and determine the timing of cliff retreat in the sandy-gravelly cliffs of Porquerolles Island. Anatomical reactions in roots have been used repeatedly to assess exposure dates, but never so far in a marine context. Recent work by Corona et al. (2011a, 2011b) in marly badlands of the southern French Alps demonstrated that changes in root cell anatomy and the related reduction of tracheid cell lumen area start to emerge as soon as the soil is reduced to about 3 cm, thus resulting in a bias of reconstructed sheet erosion. In order to ascertain for the existence of this bias in coastal cliffs, we based our analysis on a systematic and high resolution, quantitative assessment of changes in cell lumen area in exposed as well as buried roots sampled at various depths below the current cliff surface (Table 3).

Results demonstrate that the reduction in cell lumen area of earlywood tracheids does not occur in buried sections of the root, thus confirming that the reduction in the earlywood tracheids lumen area corresponds exactly to the year at which the root section was exposed. At our study site, this absence of a bias can be explained by the milder climatic conditions of Porquerolles Island where frost is unusual. In the southern French Alps, by contrast, the triggering of anatomical changes in buried roots is attributed to freeze–thaw cycles that increase the vulnerability of the xylem to cavitation (Pittermann and Sperry, 2003). Also the results demonstrate that the abrupt cellular metamorphosis observed after exposure is induced by instantaneous erosion processes. Similarly, sharp reductions of the cell sizes in roots have been observed in Fraxinus excelsior L. root sections exposed along riverbanks in the Swiss Alps (Hitz et al., 2008a). At the same time, values found in the present study clearly differ from the gradual evolution of cell lumen areas observed in the marly badlands of the southern French Alps (Corona et al., 2011b). Such differences result from the nature of erosion processes involved in root exposure at each of the regions: i.e. continuous and regular erosion processes such as rill-wash in the badlands of Draix (Rovéra and Robert, 2005), and the sudden processes such as landslides or wall collapses at Porquerolles Island, or debris-flow events in the Swiss torrents.

Reliability of erosion rates derived from dendrogeomorphic measurements

At Porquerolles, average erosion rates derived from root-ring analysis of P. halepensis Mill. are reaching rates up to 20 times higher than those calculated using tree roots in continental environments (soil erosion, bank erosion, and gully retreat) (Table 2). Such discrepancies are probably related to the high sensitivity of the soft sandy-marly deposits to sudden erosion processes resulting from the mechanic impact of waves and swells at the foot of the cliffs. In detail, erosion rates are highest in the top (stratum 4) and basal (stratum 1) sandy strata (≥ 2 cm yr−1). Similar results have been obtained at Carry-le-Rouet (Provence, France), where erosion rates three times higher in sandy-marly deposits than in calcarenite or conglomeratic deposits (Premaillon et al., 2016), thus confirming that soft lithologies are more affected by erosion than indurated deposits (as also reported elsewhere by Moore and Griggs, 2002; Collins and Sitar, 2008; Lee, 2008; Young et al., 2009b).

Erosion rates at our site vary between 0.6 and 3.9 cm yr−1, with maxima observed on rocky points (at the root scale) and in stratum 4 (at the root section scale). By contrast the lowest retreat rates are reconstructed in those portions of the cliff protected by La Courtade pocket beach. These results are in line with Earlie et al. (2015a) who observed strong spatial variability (0.01–0.37 m yr−1) in the recession rates of cliffs located on the south-western UK peninsula in relation with varying boundary conditions (i.e. rock mass characteristics, cliff geometries, beach morphology) and forcing parameters (i.e. significant wave height and peak wave period) (Earlie et al., 2015b).

Quite interestingly, and despite their wide geographic extent over the Mediterranean region, only a very limited literature exists on rock coast recession, especially in soft rock lithologies (Earlie et al., 2015b). Giuliano (2015), for instance, estimated erosion rates in Mediterranean sandy-gravelly cliffs of the Massif de la Nerthe (Carry-le-Rouet, France) through the comparison of (i) yearly-resolved LiDAR data with (ii) a multi-decadal, diachronic analysis of orthorectified aerial photographs covering the period 1924–2011. Cliff retreats derived from both methods are 1.1 cm yr−1 over a 17 month period and 4 ± 0.3 cm yr−1 over a 88-year period, respectively (Giuliano, 2015). These erosion rates are within the range of erosion rates reconstructed from exposed roots at Porquerolles Island (0.6–3.9 cm yr−1). Our results are also comparable with cliff retreat rates (2–6 cm yr−1) derived from diachronic analyses in the Calanque des Maures (France, Figure 1) on similar lithology (Giuliano, 2015). Apart from the methods used to derive erosion rates (i.e. photogrammetry, LiDAR and diachronic analysis versus root exposure), discrepancies between Porquerolles and Carry-le-Rouet may result from the different resolution of both studies. While Giuliano (2015) computed quasi-continuous cliff retreat rates for a 1-km long coastline at Carry-Le-Rouet, our study site is restricted to La Tufière headland and two locations points along one beach and does not exceed a total length of 150 m.

Noteworthy, and in a Mediterranean context (Figure 7, Table 1) the cliff retreat rates derived from dendrogeomorphic reconstructions are much smaller than those measured in sandy-silty environments of Greece (50 cm yr−1, Xeidakis et al., 2007), in bio-calcarenites of Italy (20 cm yr−1, Andriani and Walsh, 2007), and in the quartzose environments of Israel (20 cm yr−1, Zviely and Klein, 2004) (Table 1, Figure 7). At the hemispheric scale, by contrast, our results are in the same order of magnitude as erosion rates derived from 257 photogrammetric analyses on sandstone cliffs in the Algarve region (1.9 cm yr−1, Marques, 1997), North Yorkshire (3 cm yr−1, Agar, 1960) or the Larache region (Morocco, 8 cm yr−1, Marques, 2003). Conversely, they are low compared to those available for California on sandstone and sand-claystone cliffs (15–30 cm yr−1, Moore and Griggs, 2002; Young et al., 2009b; Table 1, Figure 7) and for macrotidal cliffs in northern Europe (10–50 cm yr−1) (see e.g. Dewez et al., 2007; Lim et al., 2010; Dewez et al., 2013; Letortu et al., 2014; Michoud et al., 2015).

Details are in the caption following the image
Map showing coastal cliff retreat rates obtained from the literature. Identifiers are the same as in Table 1. [Colour figure can be viewed at wileyonlinelibrary.com]

However, even if the Mediterranean context is not prone to frequent and spectacular cliff collapse events like those of the chalk cliffs of northern Europe (e.g. Duperret et al., 2002; Costa et al., 2004; Regard et al., 2012; Dewez et al., 2013), acceptability of risk in the vicinity of cliffs is subjected to increasing residential, touristic, and economic pressures (Giuliano, 2015).

Contributions and limitations of the approach

The centimetric resolution of dendrogeomorphic reconstructions and the multi-decadal time windows typically covered by roots facilitate the comparison of averaged erosion rates with meteorological records. Dendrogeomorphic analyses also require less time to be accomplished and exhibit a much better cost–benefit ratio than most other techniques used to infer erosion (Table 4). The analysis of sequential aerial photography and satellite imagery, sometimes supplemented by historic maps, has remained the main method to reconstruct decadal-scale records of cliff recession (Table 1). These sources cover roughly the same time windows (up to one century) as tree roots but at a much lower spatial resolution as a result of (i) shrinkage and stretching of the physical document over time, in addition to (ii) general issues of accuracy and precision associated with map production in the case of old maps (Snyder, 1987); as well as a result of (iii) the intervals between image acquisition, in the case of aerial surveys, that do not permit to detect overly slow or very rapid changes along rock coasts (Trenhaile, 2011). The dendrogeomorphic approach may be also considered as very complementary to the shorter time series obtained through repeat monitoring and on long-term erosion rates derived from radioisotopes (Regard et al., 2012). Erosion pins, for example, have proven useful in changes caused by weathering effects, but remain limited spatially as the surface of surveyed plots rarely exceeds a few square meters and furthermore monitoring of the nail networks is most often limited to a few years (Lim et al., 2005). Similarly, terrestrial LiDAR provides resources to study the spatial distribution of sea-cliff activity and erosional processes at sub-annual timescales (e.g. Lim et al., 2005; Young et al., 2009a; Lim et al., 2010; Quinn et al., 2010; Young et al., 2011; Barlow et al., 2012), but typically only over very short periods that does not exceed a few years. Similarly, terrestrial laser scanning (TLS) from the beach or shore platform can monitor changes in the cliff face, including the detachment of rock fragments of only a few centimeters in size up to large falls, slides, and flows (Rosser et al., 2005) though facilitating high resolution three-dimensional (3D) mapping of sea cliff morphologies. Similarly, high precision measurements such as repeat drone surveys coupled with seismic and/or wave data or video surveillance, enable sea–cliff interactions to be captured (see e.g. Letortu et al., 2018). Yet, such a quantitative characterization of sea–cliff activity remains a challenging task mainly due to the frequent sampling intervals required to capture such short duration, spatially heterogeneous and often non-linear natural phenomena (Katz and Mushkin, 2013). On larger timescales, typically in the range 100–10 000 years, the use of radio-nuclides (e.g. Regard et al., 2012) provides important time-averaged constraints for the cumulative geomorphic effect of the suite of erosional processes that drive coastal cliff retreat, but possibly lacks the temporal resolution to identify causes and drivers of erosion. In all of the earlier examples, the replication of measurements and spatial resolution of results are often hampered by the cost of measurements and heavy instrumentation. On a spatial plan, our study refines future sampling protocols in the cliff context. Reconstructions will be more accurate if samples are acquired carefully every 10 cm on the same root. This first study also reveals that, in the case of cliffs, sub-horizontal root sections represent the most valuable specimens to establish mean erosion rates for a given stratum. In addition, vertical sections can be used as complementary data in order to reconstruct the evolution of the cliff profile. Documentation of such detailed patterns of annual cliff profile evolution will enable comparison of rates of geomorphic processes with hydrodynamic and climatic events that have affected the major study area over the past decades.

Table 4. Advantages and limitations of common and root-based techniques to measure coastal cliff erosion (adapted from Trenhaile, 2011)
Technique Advantages Disadvantages
Ground surveys Very accurate Poor temporal and spatial coverage
Easily repeatable Time consuming (therefore expensive)
Historical maps Inexpensive Low accuracy
Widely available Ambiguous cliff/bluff edge position
Very long temporal coverage (since 1850s)
Good spatial coverage
Aerial photographs unrectified Inexpensive Low accuracy
Widely available Ambiguous cliff/bluff position in two-dimensions
Good temporal coverage (since 1920s)
Good spatial coverage
Rectified partially Widely available Ambiguous cliff/bluff position in two-dimensions
Good temporal coverage (since 1920s) Hardware/software for processing may be expensive
Good spatial coverage
Improved accuracy over unrectified
Fully Widely available Processing time consuming
Good temporal coverage (since 1920s) Required software expensive
Good spatial coverage
Very high accuracy
Cliff/bluff edge can be digitized in 3D
LiDAR Good spatial coverage Expensive
Very high accuracy Poor temporal coverage
Cliff edge may not be captured in data
Dendrogeomorphology (exposed root) Inexpensive Presence/absence of trees
Quantification of erosion rates in undocumented areas Problem of non-homogeneous spatial distribution
Multi-decadal, continuous reconstructions Data on averaged rates
Cover a large range of processes Not available for intense processes
Easy realization (excellent cost–benefit ratio) Destructive sampling
Method calibrated Increased uncertainty with increasing timescale
Intermediate time window (years, decades, centuries)
Quantification at the plot scale

In summary, the main advantages of the dendrogeomorphic approach to quantify cliff retreat relate to (i) the quantification of cliff retreat in undocumented areas, (ii) with annual resolution. The approach is complementary of the shorter time series obtained with repeat monitoring or more coarsely resolved records obtained from aerial photographs or cosmogenic radio-nuclide as it enables (iii) to quantify cliff retreat rates with a centimetric resolution and to reconstruct the evolution of the cliff geometry, at the plot scale, for intermediate time window (up to one century) thus offering (iv) the possibility to infer micro-geomorphic and climatic controls on the timing of cliff retreat.

Conversely, the key limitation of root-based analyses of erosion is related to the presence of trees and shrubs in the study area and to the age of roots available for analysis. Dendrogeomorphic reconstructions of erosion rates are also limited to partly exposed, alive roots with growing tips still in the ground (Krause and Eckstein, 1993; Stoffel et al., 2013). Indeed, the water absorbing part – or terminal system – of the root needs to remain underground to work properly and to prevent the death of the root. It implies that an exposed part of a living root is older than the erosion process (Vandekerckhove et al., 2001; Hitz et al., 2008a). In addition, the method relies on a sufficient number of exposed trees and roots (two or three roots per tree, five to 10 trees) and data processing requires the destruction of samples. Furthermore, recent advances in vegetation-based reconstructions of erosion indicate that large exposed roots would underestimate the real values of the erosion rates (Haubrock et al., 2009; Bodoque et al., 2011; Stoffel et al., 2013). In a similar way, roots exposed over different periods in time and/or showing different ages may exhibit significant discrepancies in mean erosion rates. Finally, many of the ecosystems in regions with distinct seasons and the presence of trees are clearly dominated by broadleaved species (angiosperms). Despite their abundance, not least in areas affected by erosion, they have only rarely been used so far to reconstruct erosion processes, presumably as a result of their more complex wood anatomy and the existence of frequent growth anomalies (Cherubini et al., 2003). Some of the limitations of reconstructions with Mediterranean broadleaves have been illustrated by Bodoque et al. (2005). Roots of broadleaved trees growing in the more temperate climatic zones of Europe appear to be less affected by cambium stress and the formation of false or double rings and therefore have been used occasionally to infer erosion processes in the past (Malik, 2006; Hitz et al., 2008a, 2008b). Based on the earlier limitations and in an attempt to increase accuracy of reconstructions (while reducing the effect of biases), further calibration and validation of dendrogeomorphic results are needed on sites where erosion rates are monitored continuously and with high accuracy.

Conclusion

The analysis of anatomical changes in exposed tree roots for the quantification of erosion rates is fairly recent, and only starts to be applied to various geomorphic and geological contexts (refer to Stoffel et al. [2013] for a recent review). In the past, the approach was mainly used for the reconstruction of abrupt and severe erosion pulses resulting from gullying or torrential activity and for the quantitative analysis of continuous and areal erosion processes. In this study, we demonstrate that decadal erosion rates from exposed roots of P. halepensis Mill. can be used to infer the evolution of cliff profiles with high accuracy and precision in Quaternary sediments cliffs. Average erosion rates derived from root rings of Aleppo pine are highest on rocky points and at the top of sandy-gravelly strata of the slope profile. Results obtained with the dendrogeomorphic approach do not differ significantly from erosion rates from the literature obtained with more sophisticated and/or continuous measurements. The approach presented in this paper thus adds significantly to the methods available to understand sea cliff evolution and facilitates identification of areas of rapid erosion. The present study confirms the usefulness and importance of dendrogeomorphic approaches for the quantification of erosion in soft coastal rock environments, particularly for coastal areas where instrumental data are scarce or completely missing, and calls for more research in these environments.

Acknowledgements

This research has been supported by ANR CAPTIVEN (Capteurs et données pour la qualité environnementaledes eaux et des sols). The authors acknowledge the valuable input from anonymous referees and ESPL's editorial team.

      The full text of this article hosted at iucr.org is unavailable due to technical difficulties.