What is he best known for?
The fields of study he is best known for:
- Ecology
- Oceanography
- Climate change
Sebastian Wetterich spends much of his time researching Permafrost, Arctic, Yedoma, Paleontology and Interglacial.
His Permafrost research incorporates elements of Physical geography and Geomorphology.
His work in Yedoma covers topics such as Total organic carbon which are related to areas like Organic matter and Geochemistry.
His Paleontology research is multidisciplinary, relying on both δ18O and δ13C.
The concepts of his Interglacial study are interwoven with issues in Betula nana and Holocene.
His work carried out in the field of Holocene brings together such families of science as Glacial period, Eemian and Tundra.
His most cited work include:
- The Arctic Coastal Dynamics Database: A New Classification Scheme and Statistics on Arctic Permafrost Coastlines (208 citations)
- Sedimentary characteristics and origin of the Late Pleistocene Ice Complex on north-east Siberian Arctic coastal lowlands and islands – A review (136 citations)
- The deep permafrost carbon pool of the Yedoma region in Siberia and Alaska. (124 citations)
What are the main themes of his work throughout his whole career to date?
Sebastian Wetterich mainly focuses on Permafrost, Oceanography, Arctic, Physical geography and Holocene.
His work deals with themes such as Geochemistry, Quaternary and Geomorphology, which intersect with Permafrost.
His work focuses on many connections between Oceanography and other disciplines, such as Sediment, that overlap with his field of interest in Hydrology.
As a part of the same scientific study, Sebastian Wetterich usually deals with the Physical geography, concentrating on Tundra and frequently concerns with Younger Dryas.
His Holocene research includes themes of Glacial period, Pleistocene and Ice wedge.
His research in Thermokarst intersects with topics in Eemian and Interglacial.
He most often published in these fields:
- Permafrost (47.93%)
- Oceanography (29.59%)
- Arctic (27.81%)
What were the highlights of his more recent work (between 2016-2021)?
- Permafrost (47.93%)
- Physical geography (25.15%)
- Arctic (27.81%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Permafrost, Physical geography, Arctic, Holocene and Pingo.
The Permafrost study combines topics in areas such as Aggradation, Radiocarbon dating, δ18O, Quaternary and Geochemistry.
His studies in Physical geography integrate themes in fields like Macrofossil, Tundra and Yedoma.
His Arctic research is under the purview of Oceanography.
In his study, Pollen is strongly linked to Sediment core, which falls under the umbrella field of Oceanography.
His Holocene research integrates issues from Marine isotope stage, Thermokarst, Pleistocene and Ice wedge.
Between 2016 and 2021, his most popular works were:
- Ground-ice stable isotopes and cryostratigraphy reflect late Quaternary palaeoclimate in the Northeast Siberian Arctic (Oyogos Yar coast, Dmitry Laptev Strait) (20 citations)
- Ice wedges as archives of winter paleoclimate: A review. (19 citations)
- Past climate and continentality inferred from ice wedges at Batagay megaslump in the Northern Hemisphere's most continental region, Yana Highlands, interior Yakutia (17 citations)
In his most recent research, the most cited papers focused on:
- Ecology
- Climate change
- Oceanography
His main research concerns Permafrost, Holocene, Physical geography, Arctic and Thermokarst.
His Permafrost study combines topics in areas such as Aggradation, Sediment, Quaternary and Earth science.
In his study, Paleoclimatology is inextricably linked to δ18O, which falls within the broad field of Holocene.
His Physical geography research is multidisciplinary, relying on both Tundra, Ice wedge, Macrofossil, Yedoma and Peat.
Sebastian Wetterich interconnects Glacial period and Interglacial in the investigation of issues within Arctic.
The various areas that he examines in his Thermokarst study include Paleontology, Pingo and Stadial.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
