Microbial dynamics in a High Arctic glacier forefield: a combined field, laboratory, and modelling approach

• Published in: Biogeosciences
• Main Authors: Bradley, James, Arndt, Sandra, Šabacká, Marie, Benning, Liane, Barker, Gary, Blacker, Joshua, Yallop, Marian, Wright, Katherine, Bellas, Christopher, Telling, Jonathan, Tranter, Martyn, Anesio, Alexandre
• Other Authors: Institut méditerranéen d'océanologie (MIO), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Mediterranean Institute of Oceanography Marseille, France, Aix Marseille Université (AMU), Queen Mary University of London (QMUL)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2016
• Subjects: [SDE]Environmental Sciences; Arctic; Svalbard; glacier
• Online Access: https://hal.science/hal-04450527; https://hal.science/hal-04450527/document; https://hal.science/hal-04450527/file/bg-13-5677-2016.pdf; https://doi.org/10.5194/bg-13-5677-2016

International audience Abstract. Modelling the development of soils in glacier forefields is necessary in order to assess how microbial and geochemical processes interact and shape soil development in response to glacier retreat. Furthermore, such models can help us predict microbial growth and the fate of Arctic soils in an increasingly ice-free future. Here, for the first time, we combined field sampling with laboratory analyses and numerical modelling to investigate microbial community dynamics in oligotrophic proglacial soils in Svalbard. We measured low bacterial growth rates and growth efficiencies (relative to estimates from Alpine glacier forefields) and high sensitivity of bacterial growth rates to soil temperature (relative to temperate soils). We used these laboratory measurements to inform parameter values in a new numerical model and significantly refined predictions of microbial and biogeochemical dynamics of soil development over a period of roughly 120 years. The model predicted the observed accumulation of autotrophic and heterotrophic biomass. Genomic data indicated that initial microbial communities were dominated by bacteria derived from the glacial environment, whereas older soils hosted a mixed community of autotrophic and heterotrophic bacteria. This finding was simulated by the numerical model, which showed that active microbial communities play key roles in fixing and recycling carbon and nutrients. We also demonstrated the role of allochthonous carbon and microbial necromass in sustaining a pool of organic material, despite high heterotrophic activity in older soils. This combined field, laboratory, and modelling approach demonstrates the value of integrated model–data studies to understand and quantify the functioning of the microbial community in an emerging High Arctic soil ecosystem.