Shallow Translational Landslides Research Articles

Holocene hillslope evolution through extreme rainfall induced landslides in the mountainous region of Rio de Janeiro, Brazil: Geochronology and paleoenvironmental evidence

AbstractGeomorphological, geochronological and paleoenvironmental data were integrated to examine how Holocene environmental changes have influenced geomorphic responses, particularly recurrent landslides and colluvial deposition on the steep slopes of the Rio de Janeiro mountains. This study focuses on a pilot hillslope (32°) with a concave‐up topographic hollow and associated shallow translational landslides, enhancing our understanding of how extreme climatic events shaped landscape evolution in the region prior to significant human impact. Recently, the hillslope was reactivated by a shallow landslide triggered by the extreme rainfall event of January 2011, which resulted in over 3600 landslides in the region. Subsequent deep gullying exposed a deposit (>3 m) containing buried, organic‐rich colluvial layers. Comprehensive analysis was conducted on sedimentological, geochronological (AMS 14C), palynological, taphonomic and carbon isotope (δ13C) data from this deposit. The geochronological results indicate that the hillslope's evolution involves recurrent shallow translational landslides throughout the Holocene, with organic colluvial layers dating from 10 148 cal years BP at the base to 663 cal years BP at the top. Charcoal fragments of various sizes suggest frequent paleofires during the Holocene. Palynological and taphonomic analyses reveal post‐fire herbaceous‐shrubby vegetation and ferns (Asteraceae, Poaceae, Alchornea, Baccharis, Celtis and Polypodium), with predominant pollen grains and spores showing mechanical damage indicative of high transport energy and physical stress conditions. The rarefied post‐fire vegetation and pioneer forest genera identified in the deposit are associated with a hydrological and mechanical dynamics that likely created less stable conditions on the slope system, promoting the occurrence of shallow landslides throughout the Holocene.

A century of urban landslides: the legacy and consequences of altering riverbank landscapes

Urban landslides are a deadly and costly hazard. Human actions, such as altering the grade, composition and vegetation-cover of hillslopes, can increase the threat of mass movements. Here, we use an interdisciplinary approach to examine the spatial distribution, timing and cause of landslides affecting a state highway and adjacent buildings along the top of a steep, urban riverbank in the mid-latitude, humid-temperate state of Vermont. Using over 100 years of mapping, photographs and written records, we demonstrate that most mass movements in our field area occurred on slopes oversteepened by the addition of uncompacted artificial fill, added without engineering considerations. Emplaced atop glacial and post-glacial sediment with low hydraulic conductivity, the fill, having little to no cohesion, expanded buildable areas, but the new infrastructure sat on unstable ground. Over the following decades, repeated failures ( n = 20), mostly shallow translational landslides in fill material along with several deeper-seated rotational slides, sent buildings, trees and segments of road into the river below. Solutions include incentivizing the removal of structures built on fill and limiting further filling activities through changes in zoning regulations and more effective enforcement of existing municipal codes. The approach we use provides a framework for similar geographical settings and can inform urban planning and risk assessment. Supplementary material : Supplementary photographs and imagery, and a list of references for all historical photographs and maps used in this study, are available at https://doi.org/10.6084/m9.figshare.c.7103608 Thematic collection: This article is part of the Engineering Geology and Hydrogeology of the Anthropocene collection available at: https://www.lyellcollection.org/topic/collections/engineering-geology-and-hydrogeology-of-the-anthropocene

Practical Considerations in the Design of Passive Free Piles in Sliding Soil

The stabilisation of shallow translational landslides can be carried out by using large diameter concrete piles, with the aim of increasing the available strength along the slip surface. In the following article, 3D numerical models of a free-head flexible pile embedded into a translational type of landslide are studied. The landslide model has a given inclination angle, β, and a thickness, D, while the reinforced concrete pile has a fixed diameter, d, and a length, D + L, in the perspective of studying the failure modes B1, BY and B2 of free-head flexible piles. In this category of piles, collapse is reached with the formation of plastic hinges. Both the soil and the concrete are modelled with simple constitutive models, such as Mohr–Coulomb for soil and the elastic-perfectly plastic for the concrete pile, in order to carry out the design approaches provided by Eurocode, as well as to highlight some practical aspects of soil–structure interaction during the landslide displacements. The results highlight how the achievement of the shear strength in a flexible free-head concrete pile generally precedes the achievement of the ultimate bending moment associated with the development of plastic hinges. Furthermore, the axial load supported by the pile may itself contribute to the overall strength available along the slip surface.

Hydro-geomorphological conditions for the classification of terrain susceptibility to shallow translational landslides: a geo-hydro ecological approach

This work is part of the review of methodological procedures for the analysis and classification of terrain susceptibility to shallow translational landslides, following the geohydro ecological approach. The pilot area is located in Nova Friburgo (RJ), specifically in the D’Antas Creek basin (53 km2). At this stage of the work, geomorphological parameters and indices were evaluated, including slope angle, curvature, drainage efficiency index (DEI) and topography position index (TPI), seen as relevant in regulating the hydrological and mechanical behavior of soils. The results obtained were intersected with an inventory of landslide scars (n = 382) referring to the extreme rainfall event in January 2011, which occurred in the highland region, called Região Serrana, of the state of Rio de Janeiro. This intersection allowed an evaluation between these parameters and the slopes rupture. The concentration of landslide area per class subsidized the establishment of weights for each of the adopted classes, based on the AHP method. A readjustment of the slope angle classes was proposed, as well as the inclusion of the standard curvature in the construction of the Hydro-Geomorphological Conditions Map. The results were promising, with a concentration of 88.74% (0.85 km2) of the landslide areas in the class of high erosive potential.

Modelling and analysing failure modes of buried pipelines perpendicularly crossing landslide boundaries

The pipeline response to shallow translational landslides is investigated using semianalytical and numerical methods. The orthogonality of a pipeline and the landslide boundary is considered in this study. In the finite element (FE) analyses, ground movements are simplified as spatially distributed horizontal transverse deformation. The pipe-soil interaction is modelled accounting for large ground deformation, inelastic material behavior, and special contact conditions at the soil–pipe interface. Pipeline failure patterns are summarized based on a series of FE models with varying diameter thickness ratios of the pipe and soil conditions. According to the FE analysis results and the published literature, the existing failure criteria are evaluated and extended to cover new failure modes. The dynamic evolution in the predominant failure modes due to the pipe elongation effects is investigated. A semianalytical solution for the sliding distance to the onset of pipe wall wrinkling is given. In addition, a pipeline failure criterion is proposed based on the relative stiffness. This dimensionless parameter is correlated with failure features, including failure modes, sliding distances to failure initiation, and failure positions. The reliability of the proposed FE model and failure prediction methodology is validated using published results from centrifuge tests and FE analyses. Simple charts for failure prediction in terms of relative stiffness parameters are provided. The proposed approach allows efficient and reliable safety evaluation on X65 steel pipelines subjected to horizontal transverse ground deformation without conducting numerical modelling.

SUPPORT VECTOR MACHINE FOR LANDSLIDE ACTIVITY IDENTIFICATION BASED ON VEGETATION ANOMALIES INDICATOR

Landslide activity identification is critical for landslide inventory mapping. A detailed landslide inventory map is highly required for various purposes such as landslide susceptibility, hazard, and risk assessments. This paper proposes a novel approach based on vegetation anomalies indicator (VAI) and applying machine learning method namely support vector machine (SVM) to identify status of natural-terrain landslides. First, high resolution airborne LiDAR data and satellite imagery were used to derive landslide-related VAIs, including tree height irregularities, canopy gap, density of different layer of vegetation, vegetation type, vegetation indices, root strength index (RSI), and distribution of water-loving trees. Then, SVM is utilized with different setting of parameter using grid search optimization. SVM Radial Basis Function (RBF) recorded the best optimal pair value with 0.062 and 0.092 misclassification rate for deep seated and shallow translational landslide, respectively. For landslide activity classification, SVM RBF recorded the best accuracy value for both deep seated and shallow translational landslides with 86.0 and 71.3, respectively. Overall, VAIs have great potential in tackling the landslide activity identification problem especially in tropical vegetated area.

ALICE (Assessment of Landslides Induced by Climatic Events): A single tool to integrate shallow and deep landslides for susceptibility and hazard assessment

The increasing evolution of urban areas in landslide-prone regions and the modification of precipitation due to global climate change have led to a growing need for landslide hazard assessment (LHA) for local land management and security services. LHA is based on the definition of the spatial and temporal probability of landslide occurrences and is split into three steps: (i) a phenomenon inventory, (ii) a landslide susceptibility analysis, and (iii) a landslide hazard analysis. Nevertheless, in practice, essential information is often missing, and LHA corresponds most of the time to landslide susceptibility assessment acquired by expert knowledge. This article presents a physical-based model (ALICE – Assessment of Landslides Induced by Climatic Events) that can integrate different types of landslides (shallow and deep) with different sizes. This tool can be used at the meso or broader scale (1:25,000 to 1:10,000) of work according to expert knowledge. However, a calibration must be carried out to fit observations and to take uncertainties into account. Thus, a specific strategy is applied to the model on a study site located in the French South Alps where numerous different landslide types were observed and analyzed. After calibration on a small representative area, the best-fitted parameters are applied to a larger area for different types of landslides. Three landslide susceptibility maps (shallow translational landslides, rotational landslides and complex landslides) are produced, and the different susceptibility classes are compared with a landslide susceptibility map produced by a geomorphological approach. The different susceptibility envelopes computed by the model are well integrated into the high-susceptibility envelopes defined by the so-called expert geomorphological approach. Thus, the tool makes it possible to improve the mapping of potentially unstable areas by taking into account parameters, such as the groundwater level in different surficial formations or the geotechnical values of landslide-prone formations, that experts are not always able to integrate. ALICE is therefore proven to be a useful tool for mapping potential landslide-prone areas if the tool is well calibrated, taking into account the expert vision of the field, different landslide types, and different triggering factors, including rainfall and seismic acceleration.

Assessing shallow landslide hazards using the TRIGRS and SHALSTAB models, Serra do Mar, Brazil

The hillslopes of the Serra do Mar, a system of escarpments and mountains that extend more than 1500 km along the southern and southeastern Brazilian coast, are regularly affected by heavy rainfall that generates widespread mass movements, causing large numbers of casualties and economic losses. This paper evaluates the efficiency of susceptibility mapping for shallow translational landslides in one basin in the Serra do Mar, using the physically based landslide susceptibility models SHALSTAB and TRIGRS. Two groups of scenarios were simulated using different geotechnical and hydrological soil parameters, and for each group of scenarios (A and B), three subgroups were created using soil thickness values of 1, 2, and 3 m. Simulation results were compared to the locations of 356 landslide scars from the 1985 event. The susceptibility maps for scenarios A1, A2, and A3 were similar between the models regarding the spatial distribution of susceptibility classes. Changes in soil cohesion and specific weight parameters caused changes in the area of predicted instability in the B scenarios. Both models were effective in predicting areas susceptible to shallow landslides through comparison of areas predicted to be unstable and locations of mapped landslides. Such models can be used to reduce costs or to define potentially unstable areas in regions like the Serra do Mar where field data are costly and difficult to obtain.

Sensitivity analysis of shallow planar landslides in residual soils on south Pennine hillslopes, Derbyshire, UK

Rainfall-induced shallow planar landslides on residual soil slopes are common mass movement processes on the southern Pennine slopes of Derbyshire, UK. They can be densely distributed across the region following intense rainfall events, frequently causing damage to infrastructure. This paper considers the results of slope stability sensitivity analyses using a simplistic Infinite Slope Stability Analysis (ISSA) model in shallow residual soils on the south Pennine hillslopes in Derbyshire. The results of the sensitivity analyses demonstrate how the factor of safety against shallow planar sliding changes as one geotechnical parameter is varied. An awareness of the variables involved in shallow planar translational landslides along with the knowledge of critical thresholds of certain geotechnical parameters establishes a basic context which assists the geotechnical engineer in the selection of key variables and making the correct engineering decisions in terms of remedial stabilisation solutions. The simple ISSA model used has limitations and recommendations are provided for improved field investigation methodology and modification of the simplistic ISSA model.

A novel genetic algorithm for optimization of conditioning factors in shallow translational landslides and susceptibility mapping

Genetic algorithm (GA) is an effective approach in selecting the best factors without considering all possible combinations in landslide susceptibility mapping (LSM). The approach experienced a local optimal solution for hazard mapping. In this study, we propose a novel genetic algorithm (NGA) for solving the problems of optimal precision in selecting conditioning factors based on the crossover and mutation. In the southwestern part of China, including Wenchuan, Ludshan, and Ludian areas, the findings of this study confirm the applicability of NGA, which has a strong robustness compared to GA obviously. Results indicated that the highest area under curve (AUC) of GA is 93.47, 83.45, and 82.21% in Wenchuan, Lushan, and Ludian, respectively. Cumulative error of the precision (∆R) is 3.19, 10.48, and 6.05%, and error of the highest precision (∆P) is 0.01, 0.03, and 0.12% for Wenchuan, Lushan, and Ludian, respectively. Compared to the GA, the highest accuracy of NGA is 93.48% (Wenchuan), 83.48% (Lushan), and 82.28% (Ludian). It also revealed that ∆R is 0.77, 1.26, and 1.82%, and ∆P is 0.00, 0.04, and 0.05% for Wenchuan, Lushan, and Ludian, respectively. By comparing with GA, the novel approach of NGA has stronger robustness and higher accuracy on selecting the optimal conditioning factors of landslide. Additionally, the relationship of landslide occurrence with controlling factors was assessed in every study area. According to the results, lithology, distance to roads, elevation, and slope were regarded as the most effective factors for shallow translational landslides. These factors implied that internal structure and composition of rock, anthropogenic activity, and topography factors posed the main impacts on landslide occurrence. Finally, we implemented landslide susceptibility assessment in three study areas. Results showed that high landslide susceptibility was in the east and northeastern parts of Wenchuan; central region northward of Lushan; and southwest, central region, and west of Ludian.

The influence of forest cover on landslide occurrence explored with spatio-temporal information

Multi-temporal landslide inventories in widely forested landscapes are scarce and further studies are required to face the challenges of producing reliable inventories in woodland areas. An elaboration of valuable empirical relationships between shallow landslides and forest cover based on recent remote sensing data alone is often hampered due to constant land cover changes, differing ages of landslides within a landslide inventory and the fact that usage of different data sets for mapping might lead to various systematic mapping biases. Within this study, we attempted to overcome these difficulties in order to explore the effect of forest cover on shallow landslide occurrences. Thus, forest dynamics were examined on the basis of 9 orthophoto series from 1950s to 2015, distinguishing 3 forest classes, based on the wood type. These classes were furthermore distinguished in 12 subclasses, considering stand density and age. A multi-temporal landslide inventory was compiled for the same period based on the aerial photography, 2 airborne LiDAR imageries, 8 field surveys and archive data. We derived topographical parameters (slope, topographical positioning index and convergency index) from the digital elevation model for areal correction and accounting for topographical confounders within a logistic regression model. Empirical relationships were assessed by means of (a) areal changes of forests and logged areas, (b) spatio-temporal distribution of shallow translational landslides, (c) frequency ratios and (d) logistic regression analysis. The findings revealed that forests increased by 16.2% from 1950s to 2015. 311 landslides of 351 in total that where mapped in total could be assigned to the observed time series and were considered for our analyses. Frequency ratios and odds ratios indicated a stabilising effect of all forest classes on landslide occurrences. Odds ratios observed for the models based on aggregated data sets (3 forest classes) indicated provided evidence that forest was constantly estimated to be less prone to slope failure than their non-forested counterparts. The chances for forest classes to be affected by shallow landslides were estimated to be considerably lower whenever topographic predictors were as well included in the model. A detailed inspection of the statistical results suggests that the obtained empirical relationships should be interpreted with care. Challenges in the mapping procedures of forests and landslides, implications of the applied methods and potential pitfalls are discussed.

The 27 July 2011 debris flows at Umyeonsan, Seoul, Korea

On 27 July 2011, a total of 33 debris flows occurred in Umyeonsan, Seoul, Korea, resulting in 16 fatalities and extensive damage to houses, roads, and other properties. The debris flows originated during an intense rainstorm with a peak intensity of 112.5 mm/h and a cumulative rainfall of 306.5 mm over 16 h. The debris flows were triggered by a combination of two processes: (1) shallow translational landslides in colluvium at the ridge crest along a fault plane associated with the Chugaryeong Fault Zone and (2) the progressive entrainment of loose material due to surface water runoff in the channel. The ensuing debris flows extensively eroded the colluvial deposits overlying the bedrock along their paths and transported large quantities of soil and woody debris. Two watersheds with catastrophic debris flows in the study area were chosen for a forensic investigation to analyze the geomorphological features of the debris flow gullies and to study several factors influencing the debris flows. The debris flow activity was found to be primarily related to rainfall, as well as to the loose, compressible colluvium overlying the gneiss bedrock, the watershed topography with >30° slopes, and the vegetation.

Integração de dados espaciais em SIG para avaliação da susceptibilidade de ocorrência de deslizamentos

SPATIAL DATA INTEGRATION IN GIS FOR LANDSLIDE SUSCEPTIBILITY PREDICTION. Improper land use is an important factor for the occurrence and intensification of natural hazards. Therefore, a correct hazard zonation is of extreme significance for the adequate planning of human activities. The main objective of this study, applied to a test site in the North of Lisbon (Fanhões-Trancão), is the application of a comprehensive methodology for landslide susceptibility evaluation at a regional scale. The methodological framework is supported by a relational database for GIS processing that includes maps of landslides and of conditioning factors (i.e. slope, aspect/geological structure, lithology, superficial deposits and land use). These maps were produced from detailed field surveys or derived from existing documents. Since the occurrence of distinct types of landslides is influenced differently by the conditioning factors, shallow translational landslides were chosen as an example for the application of the methodology. The susceptibility model is based on statistical and probabilistic algorithms that establish the relationships between the landslides and the conditioning factors (favourability functions), and allow the evaluation and validation of the map layers (independent variables) to be incorporated in the model. The spatial data integration in GIS environment is based in the bayesian interpretation of the favourability function, a technique that ranks the susceptibility values of landslide occurrence from 0 to 1. For model evaluation, following a cross-validation procedure, a random sample of the shallow translational landslides was used.

Biotic controls on shallow translational landslides

ABSTRACTIn undisturbed tropical montane rainforests massive organic layers accommodate the majority of roots and only a small fraction of roots penetrate the mineral soil. We investigated the contribution of vegetation to slope stability in such environments by modifying a standard model for slope stability to include an organic layer with distinct mechanical properties. The importance of individual model parameters was evaluated using detailed measurements of soil and vegetation properties to reproduce the observed depth of 11 shallow landslides in the Andes of southern Ecuador. By distinguishing mineral soil, organic layer and above‐ground biomass, it is shown that in this environment vegetation provides a destabilizing effect mainly due to its contribution to the mass of the organic layer (up to 973 t ha− 1 under wet conditions). Sensitivity analysis shows that the destabilizing effect of the mass of soil and vegetation can only be effective on slopes steeper than 37.9°. This situation applies to 36% of the study area. Thus, on the steep slopes of this megadiverse ecosystem, the mass of the growing forest promotes landsliding, which in turn promotes a new cycle of succession. This feedback mechanism is worth consideration in further investigations of the impact of landslides on plant diversity in similar environments. Copyright © 2012 John Wiley & Sons, Ltd.

How can statistical models help to determine driving factors of landslides?

Landslides are a hazard for humans and artificial structures. From an ecological point of view, they represent an important ecosystem disturbance, especially in tropical montane forests. Here, shallow translational landslides are a frequent natural phenomenon and one local determinant of high levels of biodiversity. In this paper, we apply weighted ensembles of advanced phenomenological models from statistics and machine learning to analyze the driving factors of natural landslides in a tropical montane forest in South Ecuador. We exclusively interpret terrain attributes, derived from a digital elevation model, as proxies to several driving factors of landslides and use them as predictors in our models which are trained on a set of five historical landslide inventories. We check the model generality by transferring them in time and use three common performance criteria (i.e. AUC, explained deviance and slope of model calibration curve) to, on the one hand, compare several state-of-the-art model approaches and on the other hand, to create weighted model ensembles. Our results suggest that it is important to consider more than one single performance criterion.Approaching our main question, we compare responses of weighted model ensembles that were trained on distinct functional units of landslides (i.e. initiation, transport and deposition zones). This way, we are able to show that it is quite possible to deduce driving factors of landslides, if the consistency between the training data and the processes is maintained. Opening the ‘black box’ of statistical models by interpreting univariate model response curves and relative importance of single predictors regarding their plausibility, we provide a means to verify this consistency.With the exception of classification tree analysis, all techniques performed comparably well in our case study while being outperformed by weighted model ensembles. Univariate response curves of models trained on distinct functional units of landslides exposed different shapes following our expectations. Our results indicate the occurrence of landslides to be mainly controlled by factors related to the general position along a slope (i.e. ridge, open slope or valley) while landslide initiation seems to be favored by small scale convexities on otherwise plain open slopes.

Selecting and weighting spatial predictors for empirical modeling of landslide susceptibility in the Darjeeling Himalayas (India)

In this paper, we created predictive models for assessing the susceptibility to shallow translational rocksliding and debris sliding in the Darjeeling Himalayas (India) by empirically selecting and weighting spatial predictors of landslides. We demonstrate a two-stage methodology: (1) quantifying associations of individual spatial factors with landslides of different types using bivariate analysis to select predictors; and (2) pairwise comparisons of the quantified associations using an analytical hierarchy process to assign predictor weights. We integrate the weighted spatial predictors through multi-class index overlay to derive predictive models of landslide susceptibility. The resultant model for shallow translational landsliding based on selected and weighted predictors outperforms those based on all weighted predictors or selected and unweighted predictors. Therefore, spatial factors with negative associations with landslides and unweighted predictors are ineffective in predictive modeling of landslide susceptibility. We also applied logistic regression to model landslide susceptibility, but some of the selected predictors are less realistic than those from our methodology, and our methodology gives better prediction rates. Although previous predictive models of landslide susceptibility indicate that multivariate analyses are superior to bivariate analyses, we demonstrate the benefit of the proposed methodology including bivariate analyses.

Dynamics of active‐layer detachment failures, Fosheim Peninsula, Ellesmere Island, Nunavut, Canada

AbstractDozens of fresh active‐layer detachments were observed on the Fosheim Peninsula in late‐summer 2005 following one week of high air temperatures and nearly continuous bright sunshine. One of these shallow translational landslides started as a minor movement on an upper, steeper slope segment but over several days its front propagated 250 m downslope at velocities of 2–9 m h−1. A second, smaller active‐layer detachment developed within less than 2 hours and subsequent movement was limited. Effective stress analyses can explain the initiation of these landslides on moderate gradients. Movements across extremely low‐angled slope segments, however, likely require both dynamic loading from the moving mass and very low basal undrained shear strengths produced by high porewater pressures. The lengthy development of the large active‐layer detachment helps explain stratigraphic and morphologic features previously observed in these slope failures. Copyright © 2007 John Wiley & Sons, Ltd.

February floods in the lower North Island, 2004: Catastrophe – causes and consequences

Abstract: The February 2004 Manawatu floods in New Zealand were the result of a naturally occurring, although unusual, storm. Up to 300 mm of rain fell on the already saturated ground of the lower North Island over two days, generating substantial and rapid runoff from catchment slopes. Rivers rose quickly, inundating unprotected farmland and properties and in places breaching stopbanks. There was widespread slope failure in the hill country of the lower North Island, affecting an area of ca. 7500 km2. Slopes under scrub, plantation forest and native bush were not as badly affected as those under pasture, where slopes typically failed by shallow translational landsliding. Flooding caused catastrophic channel change in a number of small to medium sized channel systems in the upland fringes. Whilst the occurrence of landsliding and channel changes during an extreme event such as this is natural, the intensity of both landsliding and channel erosion was exacerbated by human activity within the catchments.

Late Pleistocene sediments and environmental change at Plaza Creek, Falkland Islands, South Atlantic

Late Pleistocene organic-rich sediments exposed in coastal bluffs near the head of Plaza Creek, East Falkland, have yielded conventional and AMS 14C dates of between 36 and 28 ka BP, and possess a pollen spectrum dominated by grasses, indicating a vegetation assemblage similar to that of the present day. Although some sample dates are anomalous and contamination by non-contemporaneous carbon cannot be ruled out entirely, the age estimates are consistent with evidence and dates from Antarctica, South America and the amphi-North Atlantic for climate shifts to interstadial conditions at around that time. The organic-rich units are developed in and enclosed by deposits attributed to processes of periglacial mass wasting. Grain-size characteristics suggest that these sediments may have been emplaced by solifluction, shallow translational landsliding and surface wash in at least five mass-wasting episodes. Some of the mass-wasting sediments might correlate with solifluction deposits above and below a podsolic soil dated to 26 ka BP at San Carlos, East Falkland, and with periods of cirque and valley glaciation identified in the uplands of the Falkland Islands. The similarity between late Pleistocene interstadial, Holocene and present-day pollen assemblages, and the lack of vegetation change within these periods, is characteristic of most cool temperate Southern Ocean islands, and may reflect the lack of sensitivity of the vegetation to climate change and/or a lack of climate variability for the time intervals covered. © 1998 John Wiley & Sons, Ltd.

Late Pleistocene sediments and environmental change at Plaza Creek, Falkland Islands, South Atlantic

Late Pleistocene organic-rich sediments exposed in coastal bluffs near the head of Plaza Creek, East Falkland, have yielded conventional and AMS 14C dates of between 36 and 28 ka BP, and possess a pollen spectrum dominated by grasses, indicating a vegetation assemblage similar to that of the present day. Although some sample dates are anomalous and contamination by non-contemporaneous carbon cannot be ruled out entirely, the age estimates are consistent with evidence and dates from Antarctica, South America and the amphi-North Atlantic for climate shifts to interstadial conditions at around that time. The organic-rich units are developed in and enclosed by deposits attributed to processes of periglacial mass wasting. Grain-size characteristics suggest that these sediments may have been emplaced by solifluction, shallow translational landsliding and surface wash in at least five mass-wasting episodes. Some of the mass-wasting sediments might correlate with solifluction deposits above and below a podsolic soil dated to 26 ka BP at San Carlos, East Falkland, and with periods of cirque and valley glaciation identified in the uplands of the Falkland Islands. The similarity between late Pleistocene interstadial, Holocene and present-day pollen assemblages, and the lack of vegetation change within these periods, is characteristic of most cool temperate Southern Ocean islands, and may reflect the lack of sensitivity of the vegetation to climate change and/or a lack of climate variability for the time intervals covered. © 1998 John Wiley & Sons, Ltd.