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Metabolism is a key property of lake ecosystem functioning, but logistical challenges make it difficult to estimate across remote regions. The steady-state dissolved oxygen (DO) stable isotope method (18O method) estimates metabolism from discrete water samples and thus enables large-scale surveys. However, this method relies on the assumptions that the upper mixed layer DO saturation (DO%) relative to its isotopic composition (δ18ODO) is at a steady state and that an increase in DO% results in a proportional decrease in δ18ODO. The applicability of these assumptions has not been broadly assessed for small, low-productivity lakes with predominantly benthic metabolism. We evaluated the 18O method in these types of systems by surveying 184 Arctic lakes in Sweden and found that the method consistently produces realistic estimates of metabolism in well-mixed conditions and when water temperatures were relatively stable. Under such conditions, results from the 18O method agreed with those from the free-water diel DO method, and rates derived from both methods responded similarly to environmental drivers. In contrast, we found that the 18O method frequently generated unrealistic metabolic rates when temperatures were rising. Increasing temperatures may increase DO% irrespective of δ18ODO in the upper mixed layer and promote lake stratification, both violating the assumptions of the 18O method and preventing benthic metabolism from being integrated by surface water samples. We conclude that the 18O method is a powerful tool for studying metabolism in Arctic lakes across large spatial gradients, provided that temperature dynamics and vertical stratification are considered.

As climate change and nutrient pollution intensify, understanding how millions of lakes will respond to such forcings as a global or regional collective has become urgent and yet capturing their role in Earth's system remain neither conceptually unified nor empirically constrained. Here we introduce a framework that aggregates individual lake hypsography and functional attributes into composite lakes globally, across climate zones or 1-degree Earth system grid cells. We find that globally, lake shape mirrors land rather than ocean, with shallow areas dominating. This structure reveals systematic differences between glaciated and non-glaciated regions and between colder and warmer climate zones. At the 1-degree Earth system grid cells, composite lakes group into five distinct clusters. Globally, an estimated 43% of lake volume and sediment surface area lie within the mixed layer. A composite mixed layer volume-to-sediment-surface-area ratio reveals dominant water column influence and biogeochemical sensitivities, with strong contrasts across climates and glacial histories. The proposed framework advances quantifying and understanding the collective role of lakes across spatial scales in Earth's system.

Current estimates of carbon dioxide (CO2) evasion from Arctic lakes are highly uncertain because few studies integrate seasonal variability, specifically evasion during spring ice-melt. We quantified annual CO2 evasion for 14 clear-water Arctic lakes in Northern Sweden through mass balance (ice-melt period) and high-frequency loggers (open-water period). On average, 80% (SD: ± 18) of annual CO2 evasion occurred within 10 d following ice-melt. The contribution of the ice-melt period to annual CO2 evasion was high compared to earlier studies of Arctic lakes (47% ± 32%). Across all lakes, the proportion of ice-melt : annual CO2 evasion was negatively related to the dissolved organic carbon concentration and positively related to the mean depth of the lakes. The results emphasize the need for measurements of CO2 exchange at ice-melt to accurately quantify CO2 evasion from Arctic lakes.

Inland waters play a critical role in the carbon cycle by emitting significant amounts of land-exported carbon to the atmosphere. While carbon gas emissions from individual aquatic systems have been extensively studied, how networks of connected streams and lakes regulate integrated fluxes of organic and inorganic forms remain poorly understood. Here, we develop a process-based model to simulate the fate of terrestrial dissolved organic carbon (DOC) and carbon dioxide (CO₂) in artificial inland water networks with variable topology, hydrology, and DOC reactivity. While the role of lakes is highly dependent on DOC reactivity, we find that the mineralization of terrestrial DOC is more efficient in lake-rich networks. Regardless of typology and hydrology, terrestrial CO₂ is emitted almost entirely within the network boundary. Consequently, the proportion of exported terrestrial carbon emitted from inland water networks increases with the CO₂ versus DOC export ratio. Overall, our results suggest that CO₂ emissions from inland waters are governed by interactions between the relative amount and reactivity of terrestrial DOC and CO₂ inputs and the network configuration of recipient lakes and streams.

The deep porewater of northern peatlands stores large amounts of carbon dioxide (CO2). This store is viewed as a stable feature in the peatland CO2 cycle. Here, we report large and rapid fluctuations in deep porewater CO2 concentration recurring every autumn over four consecutive years in a boreal peatland. Estimates of the vertical diffusion of heat indicate that CO2 diffusion occurs at the turbulent rather than molecular rate. The weakening of porewater thermal stratification in autumn likely increases turbulent diffusion, thus fostering a rapid diffusion of deeper porewater CO2 towards the surface where net losses occur. This phenomenon periodically decreases the peat porewater CO2 store by between 29 and 90 g C m−2 throughout autumn, which is comparable to the peatland’s annual C-sink. Our results establish the need to consider the role of turbulent diffusion in regularly destabilizing the CO2 store in peat porewater.

Inland waters receive a significant quantity of carbon (C) from land. The fate of this C during transit, whether it is emitted to the atmosphere, accumulated in sediments or transported to the ocean, can considerably reshape the landscape C balance. However, these different fates of terrestrial C are not independent but are instead linked via several catchment and aquatic processes. Thus, according to mass conservation, any environmental change inducing a shift in a particular C fate should come at the expense of at least one other fate. Nonetheless, studies that have investigated C emission, accumulation and transport concertedly are scarce, resulting in fragmented knowledge of the role of inland waters in the global C cycle. Here, we propose a framework to understand how different C fates in aquatic systems are interlinked and covary under environmental changes. First, to explore how C fates are currently distributed in streams, rivers, reservoirs and lakes, we compiled data from the literature and show that 'C fate allocation' varies widely both within and among inland water systems types. Secondly, we developed a framework that integrates C fates in any inland water system by identifying the key processes underlying their linkages. Our framework places the partitioning between the different C forms, and how this is controlled by export from land, internal transformations and hydrology, as central to understanding C fate allocation. We argue that, by focusing on a single fate, studies could risk drawing misleading conclusions regarding how environmental changes will alter the role of inland waters in the global C cycle. Our framework thus allows us to holistically assess the consequences of such changes on coupled C fluxes, setting a foundation for understanding the contemporary and future fate of land-derived C in inland water systems.

To determine the drivers of phytoplankton biomass, we collected standardized morphometric, physical, and biological data in 230 lakes across the Mediterranean, Continental, and Boreal climatic zones of the European continent. Multilinear regression models tested on this snapshot of mostly eutrophic lakes (median total phosphorus [TP] = 0.06 and total nitrogen [TN] = 0.7 mg L⁻¹), and its subsets (2 depth types and 3 climatic zones), show that light climate and stratification strength were the most significant explanatory variables for chlorophyll a (Chl a) variance. TN was a significant predictor for phytoplankton biomass for shallow and continental lakes, while TP never appeared as an explanatory variable, suggesting that under high TP, light, which partially controls stratification strength, becomes limiting for phytoplankton development. Mediterranean lakes were the warmest yet most weakly stratified and had significantly less Chl a than Boreal lakes, where the temperature anomaly from the long-term average, during a summer heatwave was the highest (+4°C) and showed a significant, exponential relationship with stratification strength. This European survey represents a summer snapshot of phytoplankton biomass and its drivers, and lends support that light and stratification metrics, which are both affected by climate change, are better predictors for phytoplankton biomass in nutrient-rich lakes than nutrient concentrations and surface temperature.

Estimating air-water gas transfer velocities (k) is integral to understand biogeochemical and ecological processes in aquatic systems. In lakes, k is commonly predicted using wind-based empirical models, however, their predictive performance under conditions that differ from their original calibration remains largely unassessed. Here, we collected 2222 published k estimates derived from various methods in 46 globally distributed lakes to (1) evaluate the predictions of a selection of six available wind-speed based k models for lakes and (2) explore and develop new empirical models to predict k over global lakes. We found that selected k models generally performed poorly in predicting k in lakes. Model predictions were more accurate than simply assuming a mean k in only 2-39% of all lakes, however, we could not identify with confidence the specific conditions in which some models outperformed others. We developed new wind-based models in which additional variables describing the spatial coverage of k estimates and the lake size and shape had a significant effect on the wind speed-k relationship. Although these new models did not fit the global dataset significantly better than previous k models, they generate overall less biased predictions for global lakes. We further provide explicit estimates of prediction errors that integrate methodological and lake-specific uncertainties. Our results highlight the potential limits when using wind-based models to predict k across lakes and urge scientists to properly account for prediction errors, or measure k directly in the field whenever possible.

Increased incorporation of terrestrial organic matter (t-OM) into consumer biomass (allochthony) is believed to reduce growth capacity. In this study, we examined the relationship between crustacean zooplankton allochthony and production in a boreal lake that displays strong seasonal variability in t-OM inputs. Contrary to our hypotheses, we found no effect of allochthony on production at the community and the species levels. The high-frequency seasonal sampling (time-for-space) allowed for estimating the efficiency of zooplankton in converting this external carbon source to growth. From the daily t-OM inputs in the lake (57-3,027 kg C/d), the zooplankton community transferred 0.2% into biomass (0.01-2.36 kg C/d); this level was of the same magnitude as the carbon transfer efficiency for algal-derived carbon (0.4%). In the context of the boundless carbon cycle, which integrates inland waters as a biologically active component of the terrestrial landscape, the use of the time-for-space approach for the quantifying of t-OM trophic transfer efficiency by zooplankton is a critical step toward a better understanding of the effects of increasing external carbon fluxes on pelagic food webs.

Here, we investigate the importance of net CH₄ production and emissions in the carbon (C) budget of a small productive lake by monitoring CH₄, CO₂, and O₂ for two consecutive years. During the study period, the lake was mostly a net emitter of both CH₄ and CO₂, while showing positive net ecosystem production. The analyses suggest that during the whole study period, 32% +/- 26% of C produced by net ecosystem production was ultimately converted to CH₄ and emitted to the atmosphere. When converted to global warming potential, CH₄ emission (in CO₂ equivalents) was about 3-10 times higher than CO₂ removal from in-lake net ecosystem production over 100-yr and 20-yr time frames, respectively. Although more work in similar systems is needed to generalize these findings, our results provide evidence of the important greenhouse gas imbalance in human-impacted aquatic systems.