<p class="IOPAbsText"><span lang="EN-GB">Digital Elevation Models (DEMs) recorded by LiDAR are now available for large areas, providing an opportunity to map small landforms for the first time in high resolution and over larger areas. &#160;The majority of these small earth surface structures is of anthropogenic origin, and their formation is often ancient. The newly visible microrelief can therefore reflect the imprints of centuries or millennia of past land uses. Among the anthropogenic structures identified in the new high-resolution DEMs, Relict Charcoal Hearths (RCHs) are particularly widespread and abundant. RCHs are remains of past charcoal burning and mainly found in pre-industrial mining areas of Europe and North America. They normally have a relative height of fewer than 50 centimetres on flat terrain and a horizontal dimension ranging from about 5-30 metres. Despite the small spatial dimensions, RCHs can reach significant land coverage due to their enormous numbers. Recent LiDAR data show that a remarkable area of our landscape has this human fingerprint from the past. We therefore need to ask about its effect on soil landscapes and ecosystems in general. The growing relevance of RCHs is also noticeable in the rising number of RCH case studies that have been conducted. This study reviews the state of knowledge about RCHs mainly by addressing three coupled legacies of historic charcoal burning: the geomorphological, the pedological, and the ecological legacy. We are going to present recent findings on these three legacies.</span></p>
Abstract In the past decade, numerous studies have successfully mapped thousands of former charcoal production sites (also called relict charcoal hearths) manually using digital elevation model (DEM) data from various forested areas in Europe and the north‐eastern USA. The presence of these sites causes significant changes in the soil physical and chemical properties, referred to as legacy effects, due to high amounts of charcoal that remain in the soils. The overwhelming amount of charcoal hearths found in landscapes necessitates the use of automated methods to map and analyse these landforms. We present a novel approach based on open source data and software, to automatically detect relict charcoal hearths in large‐scale LiDAR datasets (visualized with Simple Local Relief Model). In addition, the approach simultaneously provides both general as well as domain‐specific information, which can be used to further study legacy effects. Different versions of the methodology were fine‐tuned on data from north‐western Connecticut and subsequently tested on two different areas in Connecticut. The results show that these perform adequate, with F1‐scores ranging between 0.21 and 0.76, although additional post‐processing was needed to deal with variations in LiDAR quality. After testing, the best performing version of the prediction model (with an average F1‐score of 0.56) was applied on the entire state of Connecticut. The results show a clear overlap with the known distribution of charcoal hearths in the state, while new concentrations were found as well. This shows the usability of the approach on large‐scale datasets, even when the terrain and LiDAR quality varies.
Core Ideas Charcoal hearth remains are a widespread legacy of historic iron production. Soils on charcoal hearth remains are a carbon sink. Soils on charcoal hearths are classified as Anthropic Udorthents. Historic charcoal hearth remains provide a unique archive of the long‐term interaction between biochar, soil development, and plant growth. Charcoal as raw material was crucial for production of iron in iron works, and hence numerous charcoal hearths can be found in the forests near historic iron works in Europe and in the eastern United States. Charcoal hearths are round to elliptical forms often around 10 m in diameter and consist of several‐decimeter‐thick layers that contain charcoal fragments, ash, and burnt soil. We studied the soil chemistry of 24 charcoal hearths and compared them with the surrounding “natural” soils in the northern Appalachians of northwestern Connecticut. The thickness of the topsoils on the charcoal hearths and their carbon content are remarkably higher than in the surrounding topsoils. The presence of residual products from charcoal production classifies the soils as Anthropic Udorthents (US Soil Taxonomy) or Spolic Technosols (Humic) according to the World Reference Base for Soil Resources. The widespread occurrence of charcoal hearth remains, and their high spatial density in different ecosystems underlines their importance for further pedological research.
Die Produktion von Holzkohle in Meilern war bis zur Erschliesung groser Braun- und Steinkohlevorkommen eine bedeutende Form der Waldnutzung in vielen Gebieten Mitteleuropas. Als Relikte der Kohlerei sind charakteristische Kleinreliefformen und Bodenveranderungen an ehemaligen Meilerstellen daher weit verbreitet. Boden auf Meilerstandorten sind im Wesentlichen durch eine technogene, kohlereiche Substratschicht an der Bodenoberflache sowie durch Einflusse von Auflast und Hitze auf die darunterliegenden fossilen Oberbodenhorizonte verandert. Das Ziel unserer Untersuchung ist eine Charakterisierung der raumlichen Verbreitung und der Bodeneigenschaften, insbesondere des Bodenwasserhaushalts, von historischen Meilerplatzen in Brandenburg. Erste Ergebnisse zeigen eine deutlich weitere Verbreitung von Meilerrelikten als bisher fur das nordosteuropaische Tiefland beschrieben und geben Hinweise auf Auswirkungen der charakteristischen Bodenveranderungen auf die Verteilung der Bodenfeuchte an den Standorten. Eine Kartierung von groseren Meilerfeldern auf Basis hochaufgeloster digitaler Gelandemodelle belegt, dass Meilerrelikte in mehreren Waldgebieten Brandenburgs in groser Zahl und teils hoher raumlicher Dichte vorkommen. Aus einer Kartierung einzelner Standorte geht fur die bisher bearbeiteten Untersuchungsgebiete hervor, dass in historischen Holzkohleproduktionsgebieten bis zu 3% der Bodenoberflache durch die Relikte der Kohlerei beeinflusst sind. Ergebnisse von Infiltrationsmessungen und Farbtracerversuchen zeigen eine sehr hohe raumliche Variabilitat der Wasserinfiltration im kohlereichen, technogenen Substrat, einen verstarkten praferentiellen Fluss in den technogenen Substraten und den fossilen Oberboden und eine dadurch bedingte besonders heterogene Verteilung der Bodenfeuchte unter den Meilerplatzen. Die hohe Anzahl von Meilerrelikten in den Waldern Deutschlands und der Einfluss von Meilerrelikten auf den Wasserhaushalt bestatigen, dass eine ausfuhrlichere Berucksichtigung technogener Substrate in der Bodenkundlichen Kartieranleitung empfehlenswert ist.
Abstract Background Ridge and furrow (RIFU) systems and associated soils are a widespread legacy of medieval agriculture, are archives of historical land use, and might affect recent ecosystems. Open questions about RIFU formation and potential legacy effects still exist, especially related to physical soil properties. Aims Our aims were (1) to characterize the soil properties of RIFU soils and (2) to compare the drought sensitivity and the growth resistance in extremely dry years of trees growing on ridges and furrows, respectively. Methods We studied soil physical (bulk density, saturated soil hydraulic conductivity, and texture) and chemical (soil pH, soil organic matter, and nitrogen content) properties and the climate sensitivity of tree growth on RIFU systems for three study sites in Prignitz, Germany. Results RIFU systems showed a high spatial heterogeneity of soil stratigraphy due to ridge construction and increased accumulation of soil moisture and organic matter in furrows due to post‐abandonment pedogenesis. Slight spatial differences in soil physical properties were found, with increased air capacity in ridge soils and higher available water contents in furrow soils. No differences in drought sensitivity were observed for trees growing on ridges and furrows, except for a wet site, where trees in furrows showed a higher sensitivity. Resistance in dry years tended to be similar or increase from furrows to ridges. Conclusions The results reflect a spatial differentiation of stratigraphy and post‐abandonment pedogenesis on abandoned RIFU systems and suggest an adaption to different moisture conditions through RIFU construction. Differences in drought sensitivity of tree growth with relative land surface could only be detected for one of the three sites, where trees were found to be less drought sensitive on ridges.
Iron-cyanide (Fe-CN) complexes have been detected at Manufactured Gas Plant sites (MGP) worldwide.The risk of groundwater contamination depends mainly on the dissolution of ferric ferrocyanide.In order to design effective remediation strategies, it is relevant to understand the contaminant's fate and transport in soil, and to quantify and mathematically model a release rate.The release of iron-cyanide complexes from four contaminated soils, originating from the former MGP in Cottbus, has been studied by using a column experiment.Results indicated that long-term cyanide (CN) release is governed by two phases: one readily dissolved and one strongly fixed.Different isotherm and kinetic equations were used to investigate the driving mechanisms for the ferric ferrocyanide release.Applying the isotherm equations assumed an approach by which two phases were separate in time, whereas the multiple first order equation considered simultaneous occurrence of both cyanide pools.Results indicated varying CN release rates according to the phase and soil.According to isotherm and kinetic models, the long-term iron cyanide release from the MGP soils is a complex phenomenon driven by various mechanisms parallely involving desorption, diffusion and transport processes.Phase I (rapid release) is presumably mainly constrained by the transport process of readily dissolved iron-cyanide complexes combined with desorption of CN bound to reactive heterogeneous surfaces that are in direct contact with the aqueous phase (outer-sphere complexation).Phase II (limited rate) is presumably driven by the diffusion controlled processes involving dissolution of precipitated ferric ferrocyanide from the mineral or inner-sphere complexation of ferricyanides.CN release rates in phase I and II were mainly influenced by the pH, organic matter (OM) and the total CN content.The cyanide release rates increased with increasing pH, decreased with low initial CN concentration and were retarded by the increase in OM content.
[https://www.flickr.com/photos/57221817@N07/23217319770/in/dateposted-public/] Alan Turing adopted a pragmatic view of intelligence. If one cannot tell a behavioral (e.g., linguistic) difference between the results of human vs. machine intelligence, the latter finally has been achieved by definition . In a similar vain social, today’s web macro-entrepreneurs simply define intelligence as giving “right” responses. The computation of these responses is best be achieved by machine “learning” and massive “big data” statistics . [https://www.flickr.com/photos/57221817@N07/22885934823/in/dateposted-public/] Yet, introspective research shows that human intelligence functions entirely different. Its kernel is the creative construction of deterministically predicting models of, albeit subjectively carved out, domains in the world. However well a statistical prediction, it can in principle never provide a theory of man . But of course it can exterminate psychology. As is also true for many older technologies, big data statistics “reverse-engineers” the demands of the people who use their outcomes. It mirrors not only taste preferences but also memories we may have long hoped to forget. By thus constraining the input to our “selves” they further constrict our behavior repertoire thereby improving our predictability still further. [https://www.flickr.com/photos/57221817@N07/23486973946/in/dateposted-public/] We may thus become the uncreative drones , the Web 2.0 protagonists already conceive us to be. Like a self-fulfilling prophecy statistical behavior prediction will produce the objects it already describes. And yet, although our predictability will be maximized, so will our sense of individuality , because computing the combination of “character items” mirrored back on us will effectively single each of us out for control and consumer purposes. [https://www.flickr.com/photos/57221817@N07/22885935373/in/dateposted-public/] Let us further assume that a society consisting of such drones is stable because it only needs technical and administrative engineers. We live in our narcissistic data suits feeling free and happy. The ultimate question will then be: Is such a social end state heaven – or is it hell? Artwork: Sylvia Eckermann, SINGULARIUM , 2015. Interpassive sculpture, sound. Polystyrene sheets and mirrors, 4 loudspeakers, monitor, camera, computer, 160 x 160 x 80 cm. Composition of voices: Szely. Sources Thomas Raab, 2015. Data Driven Narcissism: How Will “Big Data” Feed Back on Us? Journal of Consciousness Studies, 22 (9-10), 215-228. Thomas Raab, 2015. Die Netzwerk-Orange (The Network Orange , a SF novel). Wien: Luftschacht.
