The impact of thawing permafrost on iron mobility in arctic soils: a strontium isotopic approach

Details

Supervisors

Opfergelt, Sophie ; Roux, Philippe

Faculty

Faculté des bioingénieurs

Degree label

Master [120] : bioingénieur en sciences et technologies de l'environnement, à finalité spécialisée

Abstract

enPermafrost degradation in arctic regions fundamentally impacts climate change by exposing vast stocks of organic carbon (OC) to microbial decomposition, thereby amplifying greenhouse gas emissions. Iron (Fe) dynamics play a significant role in stabilising OC through the formation of Fe-OC interactions. However, the mechanisms governing Fe mobility during permafrost thaw still need to be better understood in order to predict arctic carbon feedback under warming climate. In this study, we demonstrate that strontium isotope ratios (⁸⁷Sr/⁸⁶Sr) effectively trace Fe mobilisation in thawing permafrost soils at Eight Mile Lake in Alaska. Under waterlogged conditions resulting from permafrost thaw, we observed increased Fe mobilization from deeper layers via reductive dissolution. This mobilised Fe migrates upwards with the rising water table and eventually reaches oxic zones, where it coprecipitates with dissolved OC to form a 'rusty carbon sink'. We observed these sinks at the surface and at a depth of 30 cm, the latter corresponds to an oxic zone created by an oxic groundwater influx. Although Fe-OC associations accumulate in this oxic zone, they progressively dissolve as redox conditions shift towards more reducing states. Our findings challenge the assumption that Fe-OC interactions provide long-term carbon stabilisation in thawing permafrost. Instead, we present evidence that these “rusty sinks” may act as transient reservoirs that dissolve periodically under reducing conditions, releasing previously sequestered OC for microbial mineralisation into CO₂ or CH4. These insights highlight the importance of studying seasonal variations in Fe mobility in order to accurately incorporate Fe dynamics into arctic carbon models and improve projections of climate feedback.