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

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.

Material and Methods
Methods of cliff retreat reconstruction


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).
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.

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).

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.

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).

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.
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.