Réf. Lopez-Saez & al. 2012a - A

Référence bibliographique complète

LOPEZ SAEZ, J., CORONA , C., STOFFEL, M., ASTRADE, L., BERGER, F., MALET, J.P. 2012. Dendrogeomorphic reconstruction of past landslide reactivation with seasonal precision: the Bois Noir landslide, southeast French Alps. Landslides, Vol. 9, 189–203. - Réf. Lopez Saez & al. 2012a [PDF]

Abstract: The purpose of this study was to reconstruct spatiotemporal patterns of past landslide reactivation in a forested area of the Barcelonnette Basin (Bois Noir landslide, Southern French Alps). Analysis of past events was based on tree ring series from 79 heavily affected Mountain pine (Pinus uncinata Mill. ex Mirb) trees growing near or next to the landslide body. Dendrogeomorphic analysis focused on the presence of compression wood and growth reductions, with the first reaction being used for a dating of past reactivations with seasonal precision. A total of 151 growth disturbances were identified in the samples representing eight different stages of reactivation of the landslide body between 1874 and 2008. The spatiotemporal accuracy of the reconstruction is confirmed by historical records from neighboring sites and by aerial photographs. The onset of compression wood formation allows identifying five stages of landslide reactivation during the dormant season or the very beginning of the growing season of trees, i.e., between early October and late May, and three stages toward the end of the growth period. Monthly rainfall data from the HISTALP database demonstrate that the rainfall during four out of the eight reactivations are characterized by summer rainfall totals (July–August) exceeding 200 mm, pointing to the important role of summer rainstorms in the triggering of events at the Bois Noir landslide body.


Dendrogeomorpholoy - Landslides - Growth disturbances - Seasonal precision - French Alps


Organismes / Contact

Cemagref UR EMGR, 2 rues de la papeterie, BP 76, 38402 Saint-Martin d’ Hères Cedex, France - e-mail: jerome.lopez@cemagref.fr

• Laboratory of Dendrogeomorphology (dendrolab.ch), Institute of Geological Sciences, University of Bern, Baltzerstrasse 1 +3, CH-3012 Bern, Switzerland

• Climatic Change and Climate Impacts, Institute for Environmental Sciences, University of Geneva, 7, chemin de Drize, CH-1227 Carouge-Geneva, Switzerland

• Laboratoire EDYTEM, Bâtiment Belledonne, Campus de Technolac, Université de Savoie–CISM, 73370 France, France

• Institut de Physique du Globe de Strasbourg, CNRS UMR 7516, Université de Strasbourg/EOST, 5 rue René Descartes, 67084 Strasbourg Cedex, France

This research has been supported by the DENDROGLISS program, funded by the MAIF foundation and the Cemagref by the PARAMOUNT program, ‘ImProved Accessibility, Reliability and security of Alpine transport infrastructure related to MOUNTainous hazards in a changing climate’, funded by the Alpine Space Programme, European Territorial Cooperation, 2007–2013. It has also been supported by the EU-FP7 project ACQWA (project no. GOCE-20290).


(1) - Paramètre(s) atmosphérique(s) modifié(s)

(2) - Elément(s) du milieu impacté(s)

(3) - Type(s) d'aléa impacté(s)

(3) - Sous-type(s) d'aléa




Shallow landslides (rotational landslide, flow-type landslide and earthflow)


Pays / Zone

Massif / Secteur

Site(s) d'étude



Période(s) d'observation

French Alps

Barcelonnette Basin (Alpes de Haute-Provence)

Bois Noir landslide

South facing

1600-1680 m a.s.l.



(1) - Modifications des paramètres atmosphériques










Informations complémentaires (données utilisées, méthode, scénarios, etc.)



(2) - Effets du changement climatique sur le milieu naturel










Sensibilité du milieu à des paramètres climatiques

Informations complémentaires (données utilisées, méthode, scénarios, etc.)




(3) - Effets du changement climatique sur l'aléa



Age structure of the stand and growth disturbances: The oldest tree cored at Bois Noir shows 173 tree rings at sampling height (AD 1837), while 50 growth rings (AD 1958) where counted in the youngest tree. Trees growing in or around the landslide body have a mean age of 100 years with a standard deviation of 23 years. The spatial distribution of tree ages was mapped. The age pattern of the stand is heterogeneous in L1, but tends to be more homogenous in the upper part of L2, L3 and in the upper eastern part of L4, near the scarp area, where a majority of trees are 100–120 years old. In the upper western part of L4, P. uncinata are younger with 60–80 years. The spatial gap in the lower part of L3 and L4 is related to the presence of shrubs and young broadleaved trees which were not sampled in this study.

Summary of disturbance in tree ring record: Analysis of the 79 trees sampled on the landslide allowed identification of 151 growth disturbance (GD) relating to past landslide events, with the onset of compression wood (CW) (82 GD, 55%) being more common than abrupt growth reductions (69 GD, 45%). In 1859, the sample size surpassed the n=10 threshold for landslides to be considered events using dendrogeomorphic methods. Sample size increased markedly after 1890 and excelled 50% (n=40) in 1912. The earliest GD observed in the tree ring series was dated to AD 1853; however, this year was not considered a landslide event as only two trees showed reactions. In contrast, the relative number of trees with GD did exceed the 10% threshold in 9 years after AD 1859 and were therefore considered years with landslide reactivation. Apart from the landslide recorded in local archives in 1993, eight additional previously undocumented events took place between 1875 and 2008, namely in 1875, 1897, 1947, 1963, 1977, 1978, 2000, and 2004.

Seasonal timing of CW formation: Analysis of the intra-seasonal position of CW was used to determine the seasonal timing of tilting at Bois Noir landslide. A clear concentration of CW formation was found in early earlywood (EE) (63%). Considering the timing of annual tree ring formation at Bois Noir, tilting is likely to have occurred between October of the previous and April of the current year in 1874–1875, 1896–1897, 1946–1947, 1992–1993, and 2003–2004. For those events where CW formation was initiated during the growth period of trees, it appears that CW formation is much more frequent during the period of latewood formation (latewood, L=32%). In this case, tilting would have occurred between July and September in 1963 and 2000. GD observed in EE 1978 were merged with GD observed in L in 1977. We considered that a unique reactivation occurred between July and September 1977. The onset of CW in EE in 1978 was regarded as delayed CW formation. The relationship between dated events and spatial data is represented in an event response maps. These maps reveal that major events occurred between October and April in 1946–1947 and 1992–1993 and between July and September in 1977 and 2000. They were recorded by trees located in all subunits of the landslide body (L1, L2, L3, and L4). Between July and September 1963 and between October 2003 and April 2004, movements affected trees only in the scarp area and on the upper landslide body, in subunits L1 and L4. The position of these tilted trees suggests a propagation of regressive erosion toward the scarp area.

Relationship between landslide occurrences and meteorological data: The best model derived from CART analyses used only July rainfalls to optimize the splitting of landslide events probabilities. The splitting value for July was 153 mm, and the confusion matrix indicates that the model correctly classified non-landslide years in 98% of the cases. The likelihood of correctly classifying landslide events, however, is only 37%: Three out of eight landslide events occurred when precipitation in July was >153 mm. Several logistic regression models were then tested with the presence/absence of a landslide event as a dichotomous response variable and with monthly, seasonal, and annual rainfall as a single predictor. Analysis again confirmed the primordial role of summer precipitations (July, August) in landslide triggering, and the most parsimonious logistic regression model has been determined [see details in the study]. The likelihood ratio test, significant at p<0.05, indicates that the logit model is better than a null model and the pseudo-R2 value in correctly predicting landslide triggering probability. The probability of a landslide is 8% for 200 mm July+August rainfall and 15% for 240 mm rainfall (i.e., ninth decile threshold for July+August precipitations).


Spatiotemporal accuracy of the reconstruction: Dendrogeomorphic analysis of 300 increment cores and four cross-sections taken from 79 P. uncinata allowed reconstruction of eight reactivations phases of the Bois Noir landslide between 1874 and 2009. The reconstruction added seven previously unknown events to the local landslide chronology and confirmed the mass movement of 1993 depicted in the literature. According to the archival records, six of the reactivation years dated for the Bois Noir landslide are characterized by intense landsliding at other sites within the Barcelonnette Basin. Six references on landslides at other nearby sites have been inventoried for 1963, five for 2003–2004, four for 1977 and 1992–1993, three for 1947, and one for 1875 and 2000 (Amiot and Nexon 1995; Flageollet et al. 1999), but this database is incomplete (Remaître et al. 2010). Only the date of 1897 could not be found at other sites of the basin and therefore remains unconfirmed.

The diachronic analysis of aerial photographs between 1948 and 2007 provides additional evidence for the spatiotemporal accuracy of the dendrogeomorphic reconstruction presented in this paper. The existence of the scarp area in 1948 first of all confirms that landslide reactivation predates the first and only historically dated event at Bois Noir of 1993. The reactivation in 1977, deciphered from tree ring records, is supported by the lengthening of the bare area observed on aerial photographs, in the four subunits, between 1974 and 1982. In addition, significant changes observed at L1 and L4 between 1982 and 2003 corroborate the event response maps for the 1993 and 2000 events. In addition, between 1948 and 1974 and 2003 and 2007, the aerial photographs do not reveal significant changes neither in the landslide body nor in the scarp area, thus supporting the assumption of locally more limited events in 1963 and 2003–2004.

Nonetheless, the reconstructed time series only represent a minimum frequency of reactivation events for the Bois Noir landslide, bust most likely contains a majority of large events for the period considered. In addition, several limitations became apparent as to the potential of tree ring analysis in detecting landslide events. First of all, only reactivations powerful enough to damage (such as topping, tilting, or root damaging), but not killing trees, will remain datable with dendrogeomorphic techniques. Evidences of more destructive events are, in contrast, likely to be lost as dead trees will disappear some time after an event. Second, our reconstruction was limited by the age of the trees established on the landslide body, an element which is partly linked to the frequency of destructive events. Third, it is also obvious that a tree recovering from an initial landslide event and forming very narrow annual rings or CW will be unlikely to develop a signal clearly distinguishable from the first one after a subsequent landslide event (Carrara and O’Neill 2003).

Rainfall conditions for landslide reactivation
: Statistical analyses reveal that four out of eight landslide events (1875, 1897, 1963, and 1977) were triggered when July and summer (July–August) precipitations exceeded 153 and 200 mm, respectively. The results suggest that intense summer rainfalls would play an important role in reactivating landslides at Bois Noir as in the Barcelonnette area: (1) considering the period 1975–2004, the maximum daily rainfall during summer months represents 60% of the monthly totals (Remaître 2006); (2) summer rainstorms can be locally intense, yielding intensities of sometimes more than 50 mm h−1 (Flageollet et al. 1999; Remaître et al. 2010). In detail, the onset of CW in LW 1963 and LW 1977 coincide with intense summer precipitations (254 and 314 mm, respectively), therefore suggesting a synchronism between rainfall occurrences and landslide triggering. Conversely, a delay of a few months is observed between intense precipitations in summers 1874 and 1896 (400 and 261mm, respectively) and the onset of CW in EE 1875 and EE 1897. Two possible explanations exist for this delay: (1) The gradual rise in pore water pressures related to prolonged rainfall events may be the reason for a delayed response to critical triggering conditions (Van Asch and Van Steijn 1991; Matsuura et al. 2008; Razak et al. 2009). (2) On the other hand, it is feasible that the formation of CW was delayed in the present two cases, as shown for other sites by Carrara and O’Neill (2003). However, as the onset of CW formation reveals a synchronous intraannual response of a majority of tilted trees in 1875 and 1897, we tend to reject this hypothesis.

The rainfall threshold determined in our study therefore seems to confirm findings by Flageollet et al. (1999), stating that 104 out of 134 landslides in the neighboring Vars basin would have occurred in seasons with at least 1 month with >100 mm of rainfall. Nevertheless, these thresholds remain indicative as (1) they were determined with a comparably small number of seasonally dated reactivation events (not statistically significant); (2) the very localized impact of thunderstorms and the scarcity of measuring apparatus in the basin do not enable determination of water amounts effectively falling on site triggering (Flageollet et al. 1999) with any precision; and (3) no unique set of measurements exists to characterize rainfall conditions that are likely to trigger slope failures. Guzzetti et al. (2007), for instance, listed 25 rainfall and climate variables used in the literature for the definition of empirical thresholds for the initiation of landslides. Similarly, in the case of the Bois Noir event recorded in 1993, Flageollet et al. (1999) did not attribute the triggering of the event to the above average precipitations in April but to a combination of distant multi-annual factors with seasonal or monthly parameters. In that case, April rainfalls followed five autumn–winter months which were particularly low on rainfall, but after a year (1992) of excess rainfall following a 10-year period with insufficient rainfall. Other factors such as human action or seismic shocking can directly trigger a landslide. At Bois Noir, a forest road constructed in 1981 may have increased liability to landsliding. This hypothesis is supported by a study focusing on the relationship between land use, human activity, and landslides in Vars (Martin, 1996), where 93% of the events counted between 1820 and 1995 have been linked with some human factor, particularly road laying and widening. Similarly, earthquake triggering of landslides is very common, but not quantitatively understood (Tatard et al. 2011). The Ubaye valley is one of the most active seismic zones in the French Alps (Jenatton et al. 2007) and home of the largest earthquake in the French Alps of the last century (5 April 1959, magnitude, 5.5; Jenatton et al. 2007). In 2003–2004, a prolific and protracted earthquake swarm occurred in the wider study region and reached maximum magnitudes of 2.3 in October 2003. It is therefore possible that the landslide reactivation dated to dormancy 2003–2004 could (also) be the result of shaking.


Dendrogeomorphology has been proven to be a powerful tool in adding substantially to the historic record and spatial assessment of past reactivation of landslide events at Bois Noir. Many reactivations, which remained unnoticed, could be identified and mapped and thus help extend the history of landslides back to the late nineteenth century. Comparison of tree ring data with historical records and aerial photographs clearly demonstrates the spatiotemporal accuracy of the reconstruction. Furthermore, the intra-annual dating of past mass movements through the analysis of the intra-annual position of CW allowed inferring triggers of reactivation. Nevertheless, further investigations are needed, particularly at the regional scale, to take account of the complexity of relations between landslides and climatic conditions.








Paramètre de l'aléa

Sensibilité des paramètres de l'aléa à des paramètres climatiques

Informations complémentaires (données utilisées, méthode, scénarios, etc.)

Landslide frequency

The relationship between the actual triggering of landslides and rainfall depends on the characteristics of the movement: Shallow landslides are triggered by heavy rains falling in the hours or days preceding an event, whereas deeper landslides are usually related to the total rainfall recorded over several weeks or months, and deep-seated movements can even be related to the yearly amount of precipitations (e.g., Corominas and Moya 1999; Flageollet et al. 1999; Stefanini 2004). (…)

Study site: The Bois Noir landslide body is 300 m long, 500 m wide, and ranges from 1,600 to 1,680 m a.s.l. in elevation. The Bois Noir slope segment is characterized by an irregular topography with slope gradients ranging between 10° and 35° (Thiery 2007), and the site is covered by P. uncinata and grasslands (Razak et al. 2011). Geology at the study site is characterized by a 15-m-thick top layer of morainic colluvium, underlain by autochthonous CallovoOxfordian black marls (BRGM 1974; Flageollet et al. 1999; Maquaire et al. 2003) which are very sensitive to weathering and erosion (Antoine et al. 1995). The southern part of the Bois Noir slope segment is characterized by outcrops of limestone in the summit crest and is characterized by steep slopes of up to 70°, with extensive scree slopes. The area is characterized by a dry and mountainous Mediterranean climate with strong inter-annual rainfall variability. According to the HISTALP meteorological dataset (Efthymiadis et al. 2006), rainfall at the gridded point closest to the Bois Noir landslide is 1,015±179 mm year−1 for the period 1800–2004. Rainfall can be violent, with intensities overpassing 50 mm h−1, especially during summer storms (Flageollet et al. 1999). Mean annual temperature is 7.5°C with 130 days of freezing per year (Maquaire et al. 2003).

These predisposing geomorphic and climatic factors explain the occurrence of a large landslide complex characterized by different styles of activity with shallow rotational and translational shallow slides in the upper parts of the slope, and shallow earthflows in the lower parts of the slope. The landslide complex usually affects the uppermost 2–6m of the surface deposits. A detailed geomorphologic map has been prepared by Razak et al. (2011) from the analysis of a very dense airborne LiDAR point cloud and an associated very high-resolution DTM of 0.25 m using advanced visualization techniques, the interpretation of multi-temporal aerial images, and field observations in 2009. The geomorphologic map combines information on the landslide types, the affected surface deposits, and the relative age of specific features (cracks, lobes) within the landslide complex.

A dense network of small cracks mostly developed with a radial pattern can be observed in the source area upslope of the active landslide complex. Downhill, the active landslide complex can be subdivided in landslide types of different styles of activity. The upper parts of the source area are characterized by rotational landslide scarps; in the lower parts of the slope, the landslide rigid bodies turn progressively into flow-type bodies characterized by lobes with concentric ridges. Further down, earthflows that reach less steep slopes and that cannot extend laterally are observed and produce pressure ridges.

All the landslide complex has to be interpreted as part of a larger and older landslide affecting more than four times the area of the studied landslide (Razak et al. 2011), and which is characterized by several stages of reactivation.

The aim of this study was to reconstruct spatiotemporal patterns of landslide reactivation at Bois Noir (Barcelonnette Basin, Alpes de Haute-Provence, France). Through the analysis of tree ring series of Mountain pine (Pinus uncinata Mill. ex Mirb) we (1) reconstruct landslide activity and years of reactivation, (2) determine the spatial extent of the landslide complex, (3) assess the seasonality of landslide reactivation for the past 130 years, and (4) establish relationships between landslide reactivation and climate characteristics by comparing the landslide chronology with rainfall records.

Reconstructing landslides events with tree ring series: Dendrogeomorphic techniques have been used to date landslide events in several ways. Tree ages may supply a first but important information on past activity as the oldest undisturbed tree on a landslide body will provide a minimum age of movement. A more detailed analysis of landslide movement involves the interpretation of growth disturbances in annual ring series in trees affected by landslide activity. (…)

Collection and preparation of samples: The Bois Noir landslide complex has been subdivided into four subunits (called L1, L2, L3, and L4) according to the geomorphological map and interpretation of Razak et al. (2011). To avoid misinterpretation, trees growing in sectors influenced by other types of geomorphologic processes (e.g., debris flow, gully erosion) or anthropogenic activity (sylviculture) were disregarded for this analysis. Based on an outer inspection of the stem, P. uncinata trees influenced by past landslide activity were sampled in the four subunits. Four cores per tree were extracted: two in the supposed direction of landslide movement (i.e., upslope and downslope cores) and two perpendicular to the slope. To gather the greatest amount of data on past events, trees were sampled within the tilted segment of the stems. We also collected cross-sections from landslide-damaged trees with poor survival probability. In total, 79 P. uncinata trees were sampled with four cross-sections and 300 increment cores. For each tree, additional data were collected, such as (1) tree height; (2) diameter at breast height; (3) visible defects in tree morphology, and particularly the number of knees; (4) position of the extracted sample on the stem; (5) photographs of the entire tree; and (6) data on neighboring trees. The coordinate of the tree were obtained with an accuracy <1 m with a Trimble GeoExplorer GPS. In addition, 20 undisturbed trees located above the landslide scarps and showing no signs of landslide activity or other geomorphic processes were sampled to establish a reference chronology. Two cores per trees were extracted, parallel to the slope direction and systematically at breast height. This reference chronology represents common growth variations in the area (Cook and Kairiukstis 1990) and enables precise cross-dating and age correction of the cores sampled on the landslide body. The samples obtained in the field were analyzed and the data processed following standard dendrochronological procedures (Braker 2002; Stoffel and Bollschweiler 2009). (…)

Sign of disturbance in the tree ring records: Landslide movement induce several types of growth disturbances (GD) to trees, most commonly in the form of an abrupt reduction in annual ring width and/or the formation of compression wood (CW) on the tilted side of the stem. A reduction in annual ring width over several years is interpreted as damage to the root system, loss of a major limb, or a partial burying of the trunk resulting from landslide activity (Carrara and O’Neill 2003). In this study, growth ring series had to exhibit (1) a marked reduction in annual ring width for at least five consecutive years such that the (2) width of the first narrow ring was 50% or less of the width of the annual ring of the previous year. (…)

Dating of events: Determination of events was based on the number of samples showing GD in the same year and the distribution of the affected trees on the landslide (Bollschweiler et al. 2008). (…)

Meteorological dataset: Dendrogeomorphology will yield dates of landslide reactivation with seasonal accuracy, but the exact date within a dendrochronological year will remain unknown (Corominas and Moya 1999). For these reasons, this study did not focus on the relationship between landslide occurrences and heavy rainfall over short periods. Mean monthly values are considered to provide an appropriate level of resolution for analyses (Hebertson and Jenkins 2003). Monthly homogenized precipitation records were taken from the HISTALP dataset (Efthymiadis et al. 2006) consisting of a dense network of 192 meteorological stations extending back to AD 1800 and covering the Greater Alpine Region. (…)

[see details in the study]


(4) - Remarques générales

Landslides constitute a common mass movement process and a widespread hazard in mountain and hillslope environments (Shroder et al. 2012) where they repeatedly cause damage and destruction to settlements, transportation corridors, or even lead to the loss of life. To avoid damage or fatalities, data are needed on the frequency and magnitude of past events to perform an appropriate hazard assessment (Jakob and Bovis 1996). Such knowledge is also crucial for the understanding of the variability of landslide processes during historical times and for the establishment of relationships between landslide occurrences and their triggers. The easiest way to model the response of landslide activity to precipitation, for instance, is to plot historical precipitation time series against the temporal pattern of landslide activity and to identify a precipitation threshold which effectively discriminates periods with from periods without landslides (Buma 2000).

A major obstacle for such an analysis is the lack of data with satisfying spatial resolution or precision over medium to long timescales and on a continuous basis (Claessens et al. 2006; Thiery et al. 2007). Usually, the temporal distribution of landslide events is estimated at supradecadal timescales and derived from large inventories of historical archives such as narrations, paintings, engravings and other artworks, terrestrial or aerial photographs, satellite images, or incidental statements (Brunsden and Jones 1976; Hovius et al. 1997; Martin et al. 2002). However, difficulties are normally numerous in accessing, extracting, organizing, databasing, and analyzing such data because they have not usually been collated for scientific purposes. Problems may involve conscientiousness of the observer, editing and recording process issues, and the haphazard nature of recorded events in both time and space (Ibsen and Brunsden 1996). Furthermore, archival data are always biased toward catastrophic events (Flageollet et al. 1999) and are undersampled in unpopulated areas (Mayer et al. 2010). Additional bias is introduced when interviewing residents because human memory is short-lived and highly selective, and the record will contain more frequent events of the recent past (Mayer et al. 2010).

Therefore, archival records should be supplemented with other techniques (Ibsen and Brunsden 1996; Jakob 2005). An accurate method for the reconstruction of events on forested landslides is dendrogeomorphology, i.e., the analysis of trees affected by past geomorphic activity (Alestalo 1971; Stoffel and Bollschweiler 2008). Although a catastrophic failure will destroy all trees on a landslide, trees on shallow landslides characterized by small displacement amplitudes and low velocities may survive to reactivation events and conserve externally visible evidence of past events such as topped, tilted, or S-shaped stems, scars on the stem surface, or root breakages (Carrara and O’Neill 2003; Stefanini 2004). The impacts of such external damage is recorded in the tree ring record, and dendrogeomorphic techniques have successfully been applied in the past to reconstruct landslide histories on sites lacking long and complete archival records.

In contrast to rockfall (Stoffel et al. 2005a, b) or debris flows (Stoffel et al. 2008; Bollschweiler et al. 2010) where scars and tangential rows of traumatic resin ducts have been used to assess past process activity with up to monthly resolution (Bollschweiler et al. 2008; Stoffel and Hitz 2008; Schneuwly et al. 2009), dendrogeomorphology has only rarely been used to assess the seasonality of shallow landslides so far. (…)

The approach using tree age on landslide surfaces is not new and goes indeed back to the late nineteenth century when McGee (1893) and Fuller (1912) dated movements in Tennessee and along the Mississippi river. The earliest dendrogeomorphic studies of landslides date back to the 1970s (Alestalo 1971), and the method has been used extensively in the USA and in Quebec. In Europe, tree ring analyses have been used to reconstruct the frequency and extent of landslides events in the French Alps (Braam et al. 1987; Astrade et al. 1998), in the Italian Dolomites (Fantucci and McCord 1996; Fantucci and Sorriso-Valvo 1999; Santilli and Pelfini 2002; Stefanini 2004), in the Spanish Pyrenees (Corominas and Moya 1999), etc. (…)

Landslides represent a major hazard in the Barcelonnette Basin where the combination of predisposing factors (lithology, surface deposits, climate, and land use) create favorable conditions for the triggering of mass movements. Archives yield information on more than 150 landslides in the Barcelonnette Basin since AD 1850 (Amiot and Nexon 1995; Flageollet et al. 1999; Remaître et al. 2010), but only information on one event at Bois Noir, namely in April 1993 (Thiery et al. 2007), is included. This lack of references is partly due to the fact that (1) the Bois Noir landslide complex is not of major interest for risk managers as it does not cause extensive damage to life or property; (2) the Barcelonnette Basin has a relatively low population density, resulting in many slope failures remaining unnoticed; and (3) attention will focus on the extremely active large landslides causing a high potential risk such as La Valette, Super-Sauze, and Poche. However, the presence of tilted and deformed trees, of recent scarps and open cracks, and damages to the forest road crossing the slope clearly indicate that there is scope and reason to believe that the Bois Noir landslide has been subjected to multiple stages of reactivation in the recent past


(5) - Syntèses et préconisations


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