Pan-Arctic soil element availability estimations

Arctic soils store large amounts of organic carbon and other elements such as amorphous silica, silicon, calcium, iron, aluminium, and phosphorous. Global warming is projected to be most pronounced in the Arctic leading to thawing permafrost, which in turn is changing the soil element availability....

Full description

Bibliographic Details
Main Authors: Stimmler, Peter, Goeckede, Mathias, Elberling, Bo, Natali, Susan, Kuhry, Peter, Perron, Nia, Lacroix, Fabrice, Hugelius, Gustaf, Sonnentag, Oliver, Strauss, Jens, Minions, Christina, Sommer, Michael, Schaller, Jörg
Format: Text
Language:English
Published: 2022
Subjects:
Online Access:https://doi.org/10.5194/essd-2022-123
https://essd.copernicus.org/preprints/essd-2022-123/
Description
Summary:Arctic soils store large amounts of organic carbon and other elements such as amorphous silica, silicon, calcium, iron, aluminium, and phosphorous. Global warming is projected to be most pronounced in the Arctic leading to thawing permafrost, which in turn is changing the soil element availability. To project how biogeochemical cycling in Arctic ecosystems will be affected by climate change, there is a need for data on element availability. Here, we analysed amorphous silica (ASi), silicon (Si), calcium (Ca), iron (Fe), phosphorus (P), and aluminium (Al) availability from 574 soil samples from the circumpolar Arctic region. We show large differences in ASi, Si, Ca, Fe, P, and Al availability among different lithologies and Arctic regions. We summarized these data in pan-Arctic maps of ASi, Si, Ca, Fe, P, and Al concentrations focussing on the top 100 cm of Arctic soil. Furthermore, we provide values for element availability for the organic and the mineral layer of the seasonally thawing active layer as well as for the uppermost permafrost layer. Our spatially explicit data on differences in the availability of elements between the different lithological classes and regions now and in the future will improve Arctic Earth system models for estimating current and future carbon and nutrient feedbacks under climate change.