We found that the modelled annual carbon balance of biocrusts is strongly affected by both the environment (mostly air temperature and CO₂ concentration) and physiology, such as temperature response of respiration. However, the relative impacts of these drivers vary across regions with different climates. Uncertainty in driving factors may lead to unrealistic carbon balance estimates, particularly in temperate climates, and may be explained by seasonal variation of physiology due to acclimation.

Carbonyl sulfide (COS) is a useful constraint for estimating photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a novel temperature function for enzyme carbonic anhydrase (CA) activity and optimize conductances using observations. The optimal activity of CA occurs below 40 °C, and Ball–Woodrow–Berry parameters are slightly changed. These reduce/increase uptakes in the tropics/higher latitudes and contribute to resolving discrepancies in the COS global budget.

The sinking velocity of marine particles affects how much atmospheric CO₂ is stored inside our oceans. We measured particle sinking velocities in the Peruvian upwelling system and assessed their physical and biochemical drivers. We found that sinking velocity was mainly influenced by particle size and porosity, while ballasting minerals played only a minor role. Our findings help us to better understand the particle sinking dynamics in this highly productive marine system.

This study shows that atmospheric deposition is the most important source of iron to the upper northern Indian Ocean for phytoplankton growth. This is followed by iron from continental-shelf sediment. Phytoplankton increase following iron addition is possible only with high background levels of nitrate. Vertical mixing is the most important physical process supplying iron to the upper ocean in this region throughout the year. The importance of ocean currents in supplying iron varies seasonally.

Global biogeochemical ocean models are often subjectively assessed and tuned against observations. We applied different strategies to calibrate a global model against observations. Although the calibrated models show similar tracer distributions at the surface, they differ in global biogeochemical fluxes, especially in global particle flux. Simulated global volume of oxygen minimum zones varies strongly with calibration strategy and over time, rendering its temporal extrapolation difficult.

Photosynthesis is critical for life and has been affected by the changing climate. Many parameters come into play while modeling, but traditional calibration approaches face many issues. Our framework trains coupled neural networks to provide parameters to a photosynthesis model. Using big data, we independently found parameter values that were correlated with those in the literature while giving higher correlation and reduced biases in photosynthesis rates.

The shallow-water hydrothermal vents off the Kueishan Island, Taiwan, have the most extreme records of pH values (1.52), temperatures (116 °C), and H₂S concentrations (172.4 mmol mol⁻¹) in the world. White and yellow vents differ in the color and physical and chemical characteristics of emitted plumes. We found that the feeding habits of the endemic vent crabs (Xenograpsus testudinatus) are adapted to their resident vent types at a distance of 100 m, and the trans-vent movement is uncommon.

The capacity for carbon storage (C capacity) is an attribute that determines how ecosystems store carbon in the future. Here, we employ novel data–model integration techniques to identify the carbon capacity of six grassland sites spanning the US Great Plains. Hot and dry sites had low C capacity due to less plant growth and high turnover of soil C, so they may be a C source in the future. Alternately, cooler and wetter ecosystems had high C capacity, so these systems may be a future C sink.

In studies on the relationship between ecosystem functions and climate and plant traits, previously used data-driven methods such as multiple regression and random forest may be inadequate for representing causality due to limitations such as covariance between variables. Based on FLUXNET site data, we used a causal graphical model to revisit the control of climate and vegetation traits over ecosystem functions.

We quantify the impact of optically significant water constituents on surface heating rates and thermal energy fluxes in the western Baltic Sea. During productive months in 2018 (April to September) we found that the combined effect of coloured dissolved organic matter and particulate absorption contributes to sea surface heating of between 0.4 and 0.9 K m⁻¹ d⁻¹ and a mean loss of heat (ca. 5 W m⁻²) from the sea to the atmosphere. This may be important for regional heat balance budgets.

Quantifying vegetation indices is crucial for ecosystem monitoring and modelling. Terrestrial laser scanning (TLS) has potential to accurately measure vegetation indices, but multiple methods exist, with little consensus on best practice. We compare three methods and extract wood-to-plant ratio, a metric used to correct for wood in leaf indices. We show corrective metrics vary with tree structure and variation among methods, highlighting the value of TLS data and importance of rigorous testing.

Here we developed a new burned-area detection algorithm between 2001–2019 across Alaska and Canada at 500 m resolution. We estimate 2.37 Mha burned annually between 2001–2019 over the domain, emitting 79.3 Tg C per year, with a mean combustion rate of 3.13 kg C m⁻². We found larger-fire years were generally associated with greater mean combustion. The burned-area and combustion datasets described here can be used for local- to continental-scale applications of boreal fire science.

Lichens, the dominant vegetation in the Arctic, contain ice nucleators (INs) that enable freezing close to 0°C. Yet the abundance, diversity, and function of lichen INs is unknown. Our screening of lichens across Alaska reveal that most species have potent INs. We find that lichens contain two IN populations which retain activity under environmentally relevant conditions. The ubiquity and stability of lichen INs suggest that they may have considerable impacts on local atmospheric patterns.