GeoRoundup: the highlights of EGU Journals published during July!

Each month we feature specific Divisions of EGU and during the monthly GeoRoundup we put the journals that publish science from those Divisions at the top of the Highlights section. For July, the divisions we are featuring are Biogeosciences (BG) and Hydrological Sciences (HS). They are served by the journals: Biogeosciences (BG), Geoscientific Model Development (GMD), Hydrology and Earth System Sciences (HESS) and SOIL.

Featured highlights

Biogeosciences:

Isotopomer labeling and oxygen dependence of hybrid nitrous oxide production – 17 July 2024

Nitrous oxide, a potent greenhouse gas, accumulates in regions of the ocean that are low in dissolved oxygen. We used a novel combination of chemical tracers to determine how nitrous oxide is produced in one of these regions, the eastern tropical North Pacific Ocean. Our experiments showed that the two most important sources of nitrous oxide under low-oxygen conditions are denitrification, an anaerobic process, and a novel “hybrid” process performed by ammonia-oxidizing archaea.

Linking geomorphological processes and wildlife microhabitat selection: nesting birds select refuges generated by permafrost degradation in the Arctic – 26 July 2024

In the Arctic tundra, climate change is transforming the landscape, and this may impact wildlife. We focus on three nesting bird species and the islets they select as refuges from their main predator, the Arctic fox. A geomorphological process, ice-wedge polygon degradation, was found to play a key role in creating these refuges. This process is likely to affect predator–prey dynamics in the Arctic tundra, highlighting the connections between nature’s physical and ecological systems.

Hydrology and Earth System Sciences:

Hydro-pedotransfer functions: a roadmap for future development – 29 July 2024

Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.