Deltaic and Coastal Sediments as Recorders of Mediterranean Regional Climate and Human Impact Over the Past Three Millennia

International audienc

High-resolution prediction of organic matter concentration with hyperspectral imaging on a sediment core

In the case of environmental samples, the use of a chemometrics-based prediction model is highly challenging because of the difficulty in experimentally creating a well-ranged reference sample set. In this study, we present a methodology using short wave infrared hyperspectral imaging to create a partial least squares regression model on a cored sediment sample. It was applied to a sediment core of the well-known Lake Bourget (Western Alps, France) to develop and validate a model for downcore high resolution LOI550 measurements used as a proxy of the organic matter. In lake and marine sediment, the organic matter content is widely used, for example, to reconstruct carbon flux variations through time. Organic matter analysis through routine analysis methods is time- and material-consuming, as well as not spatially resolved. A new instrument based on hyperspectral imaging allows high spatial and spectral resolutions to be acquired all along a sediment core. In this study, we obtain a model characterized by a 0.95 r prediction, with 0.77 wt% of model uncertainty based on 27 relevant wavelengths. The concentration map shows the variation inside each laminae and flood deposit. LOI550 reference values obtained with the loss on ignition are highly correlated to the inc/coh ratio used as a proxy of the organic matter in X-ray fluorescence with a correlation coefficient of 0.81. This ratio is also correlated with the averaged subsampled hyperspectral prediction with a r of 0.65

Fusion of multiresolution hyperspectral and fluorescence images for the analysis of sediment cores

For solids environmental samples, spectroscopic properties can be analyzed but their interpretation is difficult due to the lack of common referential. For the spectroscopic images, pixels are relatively spatially referenced but in most cases, each sensor has his own spatial resolution.The sample used in this work is the first 30cm of a sedimentary core from the Lake Le Bourget (Western Alps), characterized by a stratified area corresponding to last eutrophic conditions of the lake.The aim of this work is to combine four images, (1) two hyperspectral images (9x15cm²): VNIR (98 bands, pixel: 60µm) and SWIR (144 bands, pixel: 189µm), and (2) two fluorescence images (2x10cm²; sub-sample of the previous one) using excitation wavelengths of 266nm and 355nm (1024 bands each, pixel: 100µm). Each hyperspectral data can be resume with a structured grayscale image. With these, it is possible to calculate a micro-deformation model (digital image correlation) and registered them with the same spatial dimension. Applying ARSIS method [1], a pixel level data fusion model is created to fuse all the spectra in a unique spatial cube with the optimal resolution using wavelet spatial transform (decomposition in 4 images: details, vertical, horizontal and diagonal). The new cube can be used as a new instrument.The ARSIS method allows to create a correlation model between the wavelet functions for all the resolution images used. This correlation can be used to add spatial structures to the low spatial resolute data calculated with wavelet transform

Micrometric mapping of total organic carbon in lake sediment cores combining fusion of multiresolution hyperspectral images and PLSR analysis

PosterSedimentary cores are used, thanks to their physical, chemical and biological properties, to infer past climate and environment. Sampling methods (millimetre or centimetre) and routine analysis are destructive and non-spatially resolved methods that consume time and material. The use of hyperspectral imaging makes it possible to have micrometric area in each point of the core. We use two hyperspectral cameras, the VNIR (spectral range: 400-1000nm, spatial resolution: 60μm) and the SWIR (spectral range: 1000-2500nm, spatial resolution: 189μm). Usually each camera is used separately. The goal of this work is to show the combination of sensor increase performance predictions. A pixel-level data fusion based on the ARSIS method [1] is applied to create a unique cube at the optimal resolution. This new cube can be used with a usual PLSR method to develop a model for the total organic carbon.Three cores from the lakes Le Bourget, Annecy and Geneva (Western Alps) are been tested (approximately 60cm long and 9cm width each). For both samples, the results show an increase prediction performance rather than data used separately. In the unique cube, the selected wavelength (chlorophyll area (nm), C-H bonds ( nm) and O-H bonds ( nm)) corresponds to those selected by each sensor. Although the analyzes were performed on bulk samples (5 mm x 90 mm x 45 mm slices), the prediction model provides access to the mapping of the surface with a micrometric resolution (the 60μm pixel can be interpreted as relevant information)

Benthic foraminiferal response to sedimentary disturbance in the Capbreton canyon (Bay of Biscay, NE Atlantic)

Living (Rose Bengal stained) and dead benthic foraminifera were investigated at 6 deep-sea sites sampled in the Capbreton canyon area (Bay of Biscay, France). Three sites were located along the canyon axis at 301 m, 983 m and 1478 m and 3 stations were positioned on adjacent terraces at 251 m, 894 m and 1454 m. Sedimentary features indicate that frequent sedimentary disturbances of different magnitudes occur along the Capbreton canyon axis and adjacent terraces. Such environmental conditions cause the presence of very particular benthic environments. Along the 6 studied sites, different foraminiferal responses to various sedimentary patterns are observed revealing the complexity of this canyon environment. Some sites (Gitan 3 (canyon axis), Gitan 5 (canyon axis) and Gitan 6 (terrace)) are characterized by moderate to low standing stocks and low diversity and are mainly dominated by pioneer taxa such as Fursenkoina brady, Reophax dentaliniformis and Technitella melo suggesting a recent response to turbidite deposits recorded at these sites. Others sites (Gitan 1 and Gitan 2) show extremely high standing stocks and are mainly dominated by the opportunistic Bolivina subaenariensis and Bulimina marginata. Such faunal characteristics belonging to a more advanced stage of ecosystem colonization indicates strongly food-enriched sediment but extremely unstable conditions. Moderate standing stocks and diverse assemblage composed of species such as Uvigerina mediterranea and U. peregrina has only been observed at the terrace site Gitan 4. More stable sedimentary conditions recorded at this terrace seem to be suitable to the development of a dense and diverse foraminiferal community. Numerous neretic allochtonous species were observed in the dead foraminiferal fauna. These allochthonous species mainly originate from shelf areas (< 60 m)

Hyperspectral imaging for lake sediment cores analysis

PosterThe aim of this presentation is to overview some applications of hyperspectral imaging for core sediment analysis in paleoenvironmental studies. Sampling methods (millimetre or centimetre) and routine analyses are destructive and non-spatially resolved methods that consume time and material. Hyperspectral Imaging is a way to have the advantages of spectroscopy (non-destructive, fast analysis) and of imaging (high resolution, information is spatially referenced). coupling hyperspectral imaging with data mining methods makes possible to study several proxies at micrometric scale in each area of the core.Two hyperspectral cameras are used, a Visible-Near InfraRed VNIR (spectral range: 400-1000nm, spatial resolution: 60μm) and a Short Wave InfraRed SWIR (spectral range: 1000-2500nm, spatial resolution: 189μm). The two datasets produced can be fused in a unique one used to model environmental proxies. This methodology was achieved on a core from the lake Le Bourget (Western Alps, 53cm long and 9cm width). Quantitative prediction models can be made with partial least squares regression PLSR. This method links spectra with a reference analysis by the creation of a regression model. Assuming a scale homogeneity, it can be spread to all the spectra of the hyperspectral image to predict high spatially resolved proxies. Total Organic Carbon and Grain Size class models have been developed with a validation determination coefficient of 0.86 for TOC and 0.85 for clay. Concentration maps are used to study variation inside each stratigraphic unit event at the scale of laminae.These datasets can be used for classification. Based on pattern recognition and artificial neural network, it is possible to classify the type of lithology defined by the user, for example: summer or winter lamina, floods with labelled areas of less than 1% of the image. For varved sediments, this method can be used to count the varve and apply statistics on them

Hyperspectral Imaging for high resolution, non-destructive and fast analysis of sediment cores : application to Lake Le Bourget and Black Sea sediment cores.

Sedimentary archives are used to infer past climate and environment thanks to their physical and chemical properties. Sampling methods (millimetric or centimetric) and routine analysis are time and material consuming. The use of some specific spectroscopic methods and data analysis, allow to develop and perform some robust methods capable of (i) fast high resolution (ii) performed at low costs (iii) non-destructive and (iv) monitor concentration variations of major sediment compounds. X-ray fluorescence spectroscopy is one of these techniques, but it is able to detect just mineral geochemistrys. Whereas hyperspectral imaging (VNIR 400-1000 nm, SWIR 1000-2500 nm) allow, behind each voxel (a pixel with several wavelengths), to define spectral fingerprint of organic or mineral chemical compounds. This type of data can be analyzed by statistical techniques. Many (pseudo-) univariate coefficients are available for the quantification of some molecules (RABD845 for BPhe a, RABD660-670 for chlr-a and chlorins). But in this study we choose to applied multivariate methods that take into account all spectra variations. To achieve such study we can use technic that usually applied in classical spectroscopy or for satellite data that can be unsupervised or supervised. For unsupervised techniques, without any prior knowledge of the sample, exploratory algorithms are used to determine groups in the data. Then, these groups can be interpreted with the comparison to other analytical methods. It is possible to find pure signal that corresponds to one or several organic or mineral sedimentary compounds by (i) endmembers techniques, (ii) spectral unmixing, or (iii) clustering. For supervised techniques, we can use the knowledge of sample chemical and physical properties to create prediction models, then it is possible to observe variations of a specific property along the core. To develop qualitative and quantitative model for focused spectral properties we can applied classification and regression techniques. They allow to discriminate spectral domains or some wavelengths for some interest property. In the present study, Lake Le Bourget (Savoie, France) and Black Sea (Northwest margin) sediment cores are used. From this two different environmental systems we could create and test several prediction models. The high-resolution acquisition is done with two hyperspectral cameras: VNIR (400-1000 nm) and SWIR (1000-2500 nm) with spatial resolution of several dozen micrometers. Both sensors are well designed to create predictive models for either physical or chemical properties. In order to improve prediction models and make them more robust, we can pair these two cameras and add XRF core scanner data. For the black sea sediment, we use unsupervised techniques to determine groups and define interesting spatial areas to take samples for analytic analysis. Whereas for the Lake le Bourget sediment, several previous studies allow us to have many available data, thus supervised techniques are used to observe along core variations. For some properties, we could try to use models of the Lake Le Bourget in the Black Sea data, for example if we create a grain-size model, chemical elements ratio or organic compounds

Hyperspectral Imaging for high resolution, non-destructive and fast analysis of sediment cores : application to Lake Le Bourget and Black Sea sediment cores.

Sedimentary archives are used to infer past climate and environment thanks to their physical and chemical properties. Sampling methods (millimetric or centimetric) and routine analysis are time and material consuming. The use of some specific spectroscopic methods and data analysis, allow to develop and perform some robust methods capable of (i) fast high resolution (ii) performed at low costs (iii) non-destructive and (iv) monitor concentration variations of major sediment compounds. X-ray fluorescence spectroscopy is one of these techniques, but it is able to detect just mineral geochemistrys. Whereas hyperspectral imaging (VNIR 400-1000 nm, SWIR 1000-2500 nm) allow, behind each voxel (a pixel with several wavelengths), to define spectral fingerprint of organic or mineral chemical compounds. This type of data can be analyzed by statistical techniques. Many (pseudo-) univariate coefficients are available for the quantification of some molecules (RABD845 for BPhe a, RABD660-670 for chlr-a and chlorins). But in this study we choose to applied multivariate methods that take into account all spectra variations. To achieve such study we can use technic that usually applied in classical spectroscopy or for satellite data that can be unsupervised or supervised. For unsupervised techniques, without any prior knowledge of the sample, exploratory algorithms are used to determine groups in the data. Then, these groups can be interpreted with the comparison to other analytical methods. It is possible to find pure signal that corresponds to one or several organic or mineral sedimentary compounds by (i) endmembers techniques, (ii) spectral unmixing, or (iii) clustering. For supervised techniques, we can use the knowledge of sample chemical and physical properties to create prediction models, then it is possible to observe variations of a specific property along the core. To develop qualitative and quantitative model for focused spectral properties we can applied classification and regression techniques. They allow to discriminate spectral domains or some wavelengths for some interest property. In the present study, Lake Le Bourget (Savoie, France) and Black Sea (Northwest margin) sediment cores are used. From this two different environmental systems we could create and test several prediction models. The high-resolution acquisition is done with two hyperspectral cameras: VNIR (400-1000 nm) and SWIR (1000-2500 nm) with spatial resolution of several dozen micrometers. Both sensors are well designed to create predictive models for either physical or chemical properties. In order to improve prediction models and make them more robust, we can pair these two cameras and add XRF core scanner data. For the black sea sediment, we use unsupervised techniques to determine groups and define interesting spatial areas to take samples for analytic analysis. Whereas for the Lake le Bourget sediment, several previous studies allow us to have many available data, thus supervised techniques are used to observe along core variations. For some properties, we could try to use models of the Lake Le Bourget in the Black Sea data, for example if we create a grain-size model, chemical elements ratio or organic compounds

Linking Danube River activity to Alpine Ice-Sheet fluctuations during the last glacial (ca. 33–17 ka BP): Insights into the continental signature of Heinrich Stadials

Offshore archives retrieved from marine/lacustrine environments receiving sediment from large river systems are valuable Quaternary continental records. In the present study, we reconstruct the Danube River activity at the end of the last glacial period based on sedimentological, mineralogical and geochemical analyses performed on long-piston cores from the north-west Black Sea margin. Our data suggest that the Danube River produced hyperpycnal floods throughout the ca. 33–17 ka period. Four main periods of enhanced Danube flood frequency, each of 1.5–3 kyr duration, are recorded at ca. 32.5–30.5 ka (equivalent to the first part of Heinrich Stadial –HS– 3), at ca. 29–27.5 ka (equivalent to Greenland Stadial 4), at ca. 25.3–23.8 ka (equivalent to HS 2) and at ca. 22.3–19 ka. Based on mineralogical and geochemical data, we relate these events to enhanced surface melting of the Alpine Ice Sheet (AIS) that covered ∼50,000 km2 of the Danube watershed at the Last Glacial Maximum (LGM). Our results suggest that (i) the AIS growth from the inner Alps to its LGM position in the northern Alpine foreland started from ca. 30.5 ka, ended no later than ca. 25.3 ka, and was interrupted by a melting episode ca. 29–27.5 ka; (ii) the AIS volume drastically decreased from ca. 22.3 to 19 ka, as soon as summer insolation energy at the AIS latitude increased; and (iii) HSs strongly impacted the AIS mass balance through enhanced summer surface melt. This, together with evidence of severely cool winters and the rapid expansion of sea ice in the North Atlantic, implies strong seasonality in continental Europe during stadials

Are deep-sea ecosystems surrounding Madagascar threatened by land-use or climate change?

In this short communication, we present a multidisciplinaty study of sedimentary records collected from a deep-sea interfluve proximal to the mouths of major northwestern Madagascan rivers. For the last 60 years, the seafloor has been repeatedly disturbed by the deposition of organic rich, tropical, terrestrial sediments causing marked reductions in benthic biodiversity. Increased soil erosion due to local land-use, deforestation and intensifying tropical cyclones are potential causes for this sedimentary budget and biodiversity shift. Our marine sedimentary records indicate that until now, these conditions have not occurred within the region for at least 20,000 years