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  • 1
    Publication Date: 2023-01-21
    Description: Charcoal‐rich Technosols on century‐old relict charcoal hearths (RCHs) are the subject of ongoing research regarding potential legacy effects that result from historic charcoal production and subsequent charcoal amendments on forest soil properties and forest ecosystems today. RCHs consist mostly of Auh horizons that are substantially enriched in soil organic carbon (SOC), of which the largest part seems to be of pyrogenic origin (PyC). However, the reported range of SOC and PyC contents in RCH soil also suggests that they are enriched in nonpyrogenic SOC. RCH soils are discussed as potential benchmarks for the long‐term influence of biochar amendment and the post‐wildfire influences on soil properties. In this study, we utilised a large soil sample dataset (n = 1245) from 52 RCH sites in north‐western Connecticut, USA, to quantify SOC contents by total element analysis. The contents of condensed highly aromatic carbon as a proxy for black carbon (BC) were predicted by using a modified benzene polycarboxylated acid (BPCA) marker method in combination with diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy‐based partial least square regression (r2 = 0.89). A high vertical spatial sampling resolution allowed the identification of soil organic matter (SOM) enrichment and translocation processes. The results show an average 75% and 1862% increase in TOC and BPCA‐derived carbon, respectively, for technogenic Auh horizons compared to reference soils. In addition to an increase in aromatic properties, increased carboxylic properties of the RCH SOC suggest self‐humification effects of degrading charcoal and thereby the continuing formation of leachable aromatic carbon compounds, which could have effects on pedogenic processes in buried soils. Indeed, we show BPCA‐derived carbon concentrations in intermediate technogenic Cu horizons and buried top/subsoils that suggest vertical translocation of highly aromatic carbon originating in RCH Auh horizons. Topmost Auh horizons showed a gradual decrease in total organic carbon (TOC) contents with increasing depth, suggesting accumulation of recent, non‐pyrogenic SOM. Lower aliphatic absorptions in RCH soil spectra suggest different SOM turnover dynamics compared to reference soils. Furthermore, studied RCH soils featured additional TOC enrichment, which cannot be fully explained now. Highlights BC to TOC ratio and high resolution vertical SOC distribution in 52 RCH sites were studied. RCH soils non‐BC pool was potentially different to reference soils. RCH soils feature TOC accumulation in the topmost horizon. There is BC translocation into buried soils on RCH sites.
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Keywords: ddc:631.4 ; benzene polycarboxylated acid marker (BPCA) ; black carbon ; charcoal degradation ; charcoal kiln ; pyrogenic carbon ; relict charcoal hearth ; biochar
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2023-06-27
    Keywords: Age, 14C AMS; Age, dated; Age, dated material; Age, dated standard deviation; AWI_PerDyn; AWI Arctic Land Expedition; Changeable; COMPCORE; Composite Core; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; GLAMAP; Permafrost Research (Periglacial Dynamics) @ AWI; PG1238; RU-Land_1996_Taymyr; Sample code/label; Taymyr96; Labaz_Lake_Expedition; δ13C, organic carbon; δ13C, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 94 data points
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  • 3
    Publication Date: 2023-06-27
    Keywords: Albit/standard ratio; Aluminium; Aluminium oxide; AWI_PerDyn; AWI Arctic Land Expedition; Barium; Calcite/standard ratio; Calcium; Calcium oxide; Carbon, organic, total; Carbon, total; Carbon/Nitrogen ratio; Carbon in carbonate; Cerium; Changeable; Chloride; Chromium; Cobalt; COMPCORE; Composite Core; Conductivity; Conductometry; Copper; DEPTH, sediment/rock; Dolomite/standard ratio; Element analyser, ELTRA; Element analyser CHN, LECO; Grain size, LASER Particle Sizer; IC (Reimann et al., 1998, NGU-GTK-CKE spec.publ. Trondheim); ICP-OES, Inductively coupled plasma - optical emission spectrometry; Iron, aqueous phase; Iron oxide, Fe2O3; Lead; Loss on ignition; Magnesium; Magnesium oxide; Manganese; Manganese oxide; Median, grain size; Molybdenum; Nickel; Niobium; Nitrogen, total; Orthoclas/standard ratio; Permafrost Research (Periglacial Dynamics) @ AWI; PG1238; pH; Phosphorus, aqueous phase; Phosphorus pentoxide; Potassium; Potassium oxide; Pyrite/standard ratio; Quartz/standard ratio; Rubidium; RU-Land_1996_Taymyr; Silica, aqueous phase; Silicon dioxide; Sodium ion; Sodium oxide; Strontium; Sulfate; Sulfite; Sulfur, total; Sum; Taymyr96; Labaz_Lake_Expedition; Thorium; Titanium; Titanium dioxide; Uranium; Vanadium; X-ray diffraction (XRD); X-ray fluorescence (XRF); Yttrium; Zinc; Zirconium
    Type: Dataset
    Format: text/tab-separated-values, 2019 data points
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  • 4
    Publication Date: 2023-06-27
    Keywords: AWI_PerDyn; AWI Arctic Land Expedition; Carbon, organic, total; Carbon, total; Carbon/Nitrogen ratio; Carbon in carbonate; Changeable; COMPCORE; Composite Core; DEPTH, sediment/rock; Element analyser, ELTRA; Element analyser CHN, LECO; Nitrogen, total; Permafrost Research (Periglacial Dynamics) @ AWI; PG1239; RU-Land_1996_Taymyr; Sulfur, total; Taymyr96; Labaz_Lake_Expedition
    Type: Dataset
    Format: text/tab-separated-values, 891 data points
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  • 5
    Publication Date: 2024-04-20
    Keywords: Carbon, organic, particulate, flux; DATE/TIME; DEPTH, water; Global Environmental Change: The Northern North Atlantic; NB2; Nitrogen, organic, particulate, flux per day; Seston, flux; SFB313; SFB313Moorings; Trap, sediment; TRAPS; δ13C, organic carbon; δ15N, organic matter
    Type: Dataset
    Format: text/tab-separated-values, 120 data points
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  • 6
    Publication Date: 2024-04-20
    Keywords: Carbon, organic, particulate, flux; DATE/TIME; DEPTH, water; Global Environmental Change: The Northern North Atlantic; Nitrogen, organic, particulate, flux per day; Seston, flux; SFB313; Trap; TRAP; VP-2/3/4; δ13C, organic carbon; δ15N, organic matter
    Type: Dataset
    Format: text/tab-separated-values, 60 data points
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  • 7
    Publication Date: 2024-05-15
    Keywords: AWI_PerDyn; AWI Arctic Land Expedition; Calculated from mass/volume; Changeable; COMPCORE; Composite Core; Density, wet bulk; DEPTH, sediment/rock; Magnetic susceptibility, volume; Multi-Sensor Core Logger; Permafrost Research (Periglacial Dynamics) @ AWI; PG1238; RU-Land_1996_Taymyr; Taymyr96; Labaz_Lake_Expedition; Velocity, compressional wave; Water content, wet mass
    Type: Dataset
    Format: text/tab-separated-values, 3300 data points
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  • 8
    Publication Date: 2024-05-15
    Keywords: AWI_PerDyn; AWI Arctic Land Expedition; Calculated from mass/volume; Changeable; COMPCORE; Composite Core; Density, wet bulk; DEPTH, sediment/rock; Magnetic susceptibility, volume; Multi-Sensor Core Logger; Permafrost Research (Periglacial Dynamics) @ AWI; PG1239; RU-Land_1996_Taymyr; Taymyr96; Labaz_Lake_Expedition; Velocity, compressional wave; Water content, wet mass
    Type: Dataset
    Format: text/tab-separated-values, 4109 data points
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  • 9
    Publication Date: 2021-07-21
    Description: Due to complicated backgrounds and unclear target orientation, automated object detection is difficult in the field of archaeology. Most of the current convolutional neural network (CNN) object‐oriented detection techniques are based on a faster region‐based CNN (R‐CNN) and other one‐stage detectors that often lack adequate processing speeds and detection accuracies. Recently, the two‐stage detector Mask R‐CNN technique achieved impressive results in object detection and instance segmentation problems and was successfully applied in the analysis of archaeological airborne laser scanning (ALS) data. In this study, we outline a modified Mask R‐CNN technique that reliably and efficiently detects relict charcoal hearth (RCH) sites on light detection and ranging (LiDAR) data‐based digital elevation models (DEMs). Using image augmentation and image preprocessing steps combined with the deep learning‐based adaptive gradient method with a dynamic bound on the learning rate (AdaBound) optimization technique, we could improve the model's accuracy and significantly reduce its training time. We use DEMs based on high‐resolution LiDAR data and the visualization for archaeological topography (VAT) technique that give images with a very strong contrast of the terrain and the outline of the sites of interest in the North German Lowland. Therefore, the model can identify RCH sites with an average recall of 83% and an average precision of 87%. Techniques such as the modified Mask R‐CNN method outlined here will help to greatly improve our knowledge about archaeological site densities in the realm of historical charcoal production and past human‐landscape interactions. This method provides an accurate, time‐efficient and bias‐free large‐scale site mapping option not only for the North German Lowland but potentially for other landscapes as well.
    Description: German Research Foundation (DFG)
    Keywords: 622.1 ; 930.1 ; anthropogenic geomorphology ; automated detection ; charcoal hearth ; deep learning ; Mask R‐CNN ; object detection
    Type: article
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