Seagrass meadows are productive ecosystems and bury much carbon. Understanding their role in the global carbon cycle requires knowledge of air–sea CO₂ fluxes and hence the knowledge of gas transfer velocity (k). In this study, k was determined from the dual tracer technique in Florida Bay. The observed gas transfer velocity was lower than previous studies in the coastal and open oceans at the same wind speeds, most likely due to wave attenuation by seagrass and limited wind fetch in this area.

The impact of assimilating different dataset combinations on regional to global-scale C budgets is explored with the ORCHIDEE model. Assimilating simultaneously multiple datasets is preferable to optimize the values of the model parameters and avoid model overfitting. The challenges in constraining soil C disequilibrium using atmospheric CO₂ data are highlighted for an accurate prediction of the land sink distribution.

At the foot of the Himalayas in Nepal, land cover time series and data of environmental drivers show changes in disturbance-dependent grasslands that serve as habitat for endangered megafauna. The changes in surface area and heterogeneity of the grassland patches are attributed to a relocation of the dominant river channel of the Karnali River and associated decline of hydromorphological disturbances and a decrease in anthropogenic disturbances after its establishment as conservation area.

Eighty-million-year-old fossil leaf assemblages suggest a widespread distribution of tropical rainforest in northeastern Africa.

This study examines the multi-annual meteorological history of low-forest-greenness events in Europe's temperate and Mediterranean biome in 2002–2022. We systematically identify anomalies in temperature, precipitation, and weather systems as event precursors, with noteworthy differences between the two biomes. We also quantify the impact of the most extensive event in 2022 (37 % coverage), underlining the importance of understanding the forest–meteorology interaction in a changing climate.

We are among the first to quantify methane emissions from inland water system in the pan-Arctic. The total CH₄ emissions are 36.46 Tg CH₄ yr⁻¹ during 2000–2015, of which wetlands and lakes were 21.69 Tg yr⁻¹ and 14.76 Tg yr⁻¹, respectively. By using two non-overlap area change datasets with land and lake models, our simulation avoids small lakes being counted twice as both lake and wetland, and it narrows the gap between two different methods used to quantify regional CH₄ emissions.