Sarian Kosten

Small inland waters are important greenhouse gas (GHG) sources; however, most field campaigns rely on daytime-only measurements collected at multi-week intervals, potentially biasing flux estimates. We present the Buoyant Emission Recorder for Temporal High-Frequency Analyses (BERTHA), a mid-cost automated floating chamber system for high-frequency measurements of CO₂ and CH₄ fluxes on multiple spatial scales. We describe the system’s design and test how empirically derived pressure and water vapour correction factors for the mid-cost CO₂ and CH₄ sensors increase the accuracy of reported concentrations and derived flux estimates. Here, we found a 17–37 % (CO₂) and 4–9 % (CH₄) higher mean flux estimate with pressure compensation during the 97-day measuring period. Compensation for water vapour resulted in much smaller differences (~1–2 % increase). Additionally, we calculated the mean CO₂ and CH₄ emission using high-frequency measurements during 97 days and simulated alternative measurement scenarios based on the full dataset and evaluated how well these ‘reference means’ could be approached by 1) single, daytime-only chamber flux measurements at daily to monthly intervals, and 2) short-term (2–3 days) automated chamber deployments every two–three weeks combined with machine learning-based gap-filling. Results of the simulation analysis showed that daytime-only measurements consistently and strongly underestimated the reference CO₂ mean. CH₄ emissions matched the reference mean well for daily, but not for monthly measurements (>90 % and ~23 % of simulations deviated 2 reference mean, with 89 % and 48 % of means being within ±20 % of the reference mean, for campaign intervals of two and three weeks, respectively. We conclude that high-frequency chamber measurements using mid-cost GHG analysers combined with empirical pressure corrections provide accurate emission estimates, a robust benchmark for evaluating reduced measurements strategies and gap-filling approaches, and potential for improved process-based understanding of GHG fluxes when combined with ancillary high-frequency measurements.

Small inland waters are important greenhouse gas (GHG) sources; however, most field campaigns rely on daytime-only measurements collected at multi-week intervals, potentially biasing flux estimates. We present the Buoyant Emission Recorder for Temporal High-Frequency Analyses (BERTHA), a mid-cost automated floating chamber system for high-frequency measurements of CO2 and CH4 fluxes on multiple spatial scales. We describe the system’s design and test how empirically derived pressure and water vapour correction factors for the mid-cost CO2 and CH4 sensors increase the accuracy of reported concentrations and derived flux estimates. Here, we found a 17–37 % (CO2) and 4–9 % (CH4) higher mean flux estimate with pressure compensation during the 97-day measuring period. Compensation for water vapour resulted in much smaller differences (~1–2 % increase). Additionally, we calculated the mean CO2 and CH4 emission using high-frequency measurements during 97 days and simulated alternative measurement scenarios based on the full dataset and evaluated how well these ‘reference means’ could be approached by 1) single, daytime-only chamber flux measurements at daily to monthly intervals, and 2) short-term (2–3 days) automated chamber deployments every two–three weeks combined with machine learning-based gap-filling. Results of the simulation analysis showed that daytime-only measurements consistently and strongly underestimated the reference CO2 mean. CH4 emissions matched the reference mean well for daily, but not for monthly measurements (>90 % and ~23 % of simulations deviated <20 % of the reference mean, respectively). Short-term automated chamber campaigns, gap-filled using machine learning closely reproduced the CO2 reference mean, with 89 % and 48 % of means being within ±20 % of the reference mean, for campaign intervals of two and three weeks, respectively. We conclude that high-frequency chamber measurements using mid-cost GHG analysers combined with empirical pressure corrections provide accurate emission estimates, a robust benchmark for evaluating reduced measurements strategies and gap-filling approaches, and potential for improved process-based understanding of GHG fluxes when combined with ancillary high-frequency measurements.

Rotifers are diverse bioindicators in shallow lakes, but aggregate metrics can obscure the direction and magnitude of their responses to eutrophication. Here, we analysed rotifer communities across 83 South American shallow lakes spanning a broad eutrophication gradient to interpret taxon-specific contributions to community change. Ten species met stringent identification criteria (purity and reliability ≥ 0.85), with four consistently sensitive (decreasers) and six tolerant (increasers), seven of which belonged to the Brachionidae family. Community thresholds for sensitive taxa occurred under oligotrophic–mesotrophic conditions (lowest along the Toledo index, TSI _Tol , at 38.8), preceding conventional than eutrophic classification limits, whereas tolerant taxa shifted under hypertrophic conditions (highest along the Cunha index, TSI _Cun , at 59.9). Notably, the threshold for sensitive taxa along Carlson index, TSI _Car , was 49, indicating that community decline began during the mesotrophic–eutrophic transition. Community structure did not differ across climatic zones, but overall biodiversity metrics, particularly species richness and taxonomic diversity, were lower above the average community change point, with the strongest decline observed along the Toledo index. Beyond underscoring the importance of local environmental factors and trophic index selection, we recommend taxon-specific threshold analyses on time series within regions to evaluate the consistency of ecological thresholds across broad latitudinal gradients. We further recommend that monitoring programs incorporate rotifer abundance and frequency as sensitive early indicators of eutrophication.

Freshwater ecosystems are major natural sources of methane (CH ₄ ) and carbon dioxide (CO ₂ ), with large amounts of these gases being produced in sediments. Bioturbators such as Tubifex spp. have been proposed to alter the dynamics of both gases as they inhabit the sediment–water interface, influencing biogeochemical processes. Although eutrophication generally leads to strong shifts in the benthic community, Tubifex spp. tolerate eutrophication. However, their role in modulating greenhouse gas (GHG) emissions requires further elucidation. We used 24 microcosm to assess the presence of Tubifex spp. on diffusive and ebullitive CH ₄ and CO ₂ emissions across three eutrophic sediments: one with clay (C) and two with peat, containing low and high organic matter content (P-lom and P-hom, respectively). The effects of Tubifex on carbon emissions varied across emission pathways and were modulated by sediment types. Tubifex presence tended to alter diffusive CH ₄ and CO ₂ fluxes, leading to higher mean CO ₂ and total mean CH ₄ emissions in P-lom sediments, whereas weak effects of bioturbation were observed in P-hom and C sediments. The variation in effects was likely associated with sediment-dependent differences in Tubifex bioturbation intensity, as well as Tubificid-mediated shifts in interactions among organic carbon dynamics, CH ₄ -cycling microbial abundances, nutrient availability and gaseous carbon fluxes. We did not find evidence that Tubifex affected ebullitive CH ₄ emissions, sediment oxygenation or the abundance of methanogens and methanotrophs in the sediment. We conclude that to incorporate their effects in GHG emission estimates, more context-dependent insights are needed.

Agricultural drainage ditches have been recently identified as hotspots of methane (CH ₄ ), carbon dioxide (CO ₂ ), and nitrous oxide (N ₂ O) emissions. Ditches often experience inputs of fertilizers from adjacent agricultural fields, which increases the availability of organic carbon and nutrients in ditch sediments, thereby fueling greenhouse gas (GHG) production. Here, we quantify the effects of two types of fertilizers (manure and artificial fertilizer) on GHG dynamics from agricultural drainage ditch sediments subjected to oxic and anoxic conditions. We first measured rates of potential sediment N ₂ O production, CH ₄ production, and aerobic CH ₄ oxidation under different fertilizer doses. We observed that manure additions (expressed here as ammonium (NH ₄ ⁺ ) dose, referring to the resulting NH ₄ ⁺ concentration in a given bottle after addition) strongly stimulated CH ₄ and N ₂ O production. Methane production rates increased approximately threefold as a result of manure additions, ranging from 18.4 to 61.7 µmol CH ₄ gDW ⁻¹ d ⁻¹ , whereas N ₂ O production rates increased approximately 16-fold, and varied from 0.1 to 1.6 µmol N ₂ O gDW ⁻¹ d ⁻¹ across manure doses. Aerobic CH ₄ oxidation was also stimulated by manure addition, while at resulting NH ₄ ⁺ concentrations above 2 mmol L ⁻¹ , oxidation rates declined. In contrast, artificial fertilizer caused immediate inhibition of CH ₄ and N ₂ O production and aerobic CH ₄ oxidation, even at the lowest NH ₄ ⁺ concentration tested (0.05 mmol L ⁻¹ ). Focusing on the effects of manure on GHG emissions, we observed that under anoxic conditions, sediment cores receiving high manure inputs emitted approximately 3.5 times more GHGs (in CO ₂ -equivalents) than anoxic controls (no manure) and about 5.5 times more than oxic controls. Methane was the dominant driver of increased emissions at higher manure doses. As fertilizer use continues to rise globally, these results highlight the importance of implementing climate-smart water and nutrient management strategies in ditches and adjacent grasslands to mitigate climate trade-offs.

Many inland waters are shrinking due to shifts in climate and water diversion for human uses. As they dry out, their exposed sediments emit large amounts of carbon dioxide (CO ₂ ) to the atmosphere. However, current global estimates of CO ₂ emissions from dry inland waters are derived exclusively from bare sediment dark‐chamber measurements that do not account for the colonization of desiccated areas by vegetation. To understand the impact of vegetation on CO ₂ emissions from dry sediments, we analyzed 164 dry inland water bodies across five climatic regions and five inland water body types (lakes, ponds, reservoirs, streams and wetlands). On average, within vegetated zones, vegetation occupied 47 ± 35% in measured biomass quadrants. Light‐induced decreases in instantaneous CO ₂ emissions in vegetated dry sediments were lower (mean ± SD = −3.7 ± 12.9 mmol CO ₂ m ⁻² hr ⁻¹ ) than increases during dark conditions (14.7 ± 20.1 mmol CO ₂ m ⁻² hr ⁻¹ ). Diel (24‐hr) CO ₂ emissions from dry, vegetated sediments (mean ± SD = 100 ± 261 mmol CO ₂ m ⁻² d ⁻¹ ) were 25% lower than in bare sediments (133 ± 245 mmol CO ₂ m ⁻² d ⁻¹ ). These results indicate that vegetation can partially off‐set sediment respiration, although the magnitude of this effect is insufficient to switch dry beds from net sources to net sinks of carbon.

Freshwater lakes, despite covering only ~ 3% of Earth’s surface, are among the largest natural sources of methane to the atmosphere. Current global estimates of lake methane emissions, however, remain uncertain and likely underestimated due to the scarcity of long-term and high resolution datasets and the spatial and temporal complexity of freshwater lakes. Methane fluxes from lakes are influenced by many factors such as lake depth, organic matter input, seasonal biogeochemical dynamics and vegetation composition, making upscaling from individual systems challenging. In this study, we investigate the temporal dynamics of methane emissions from a shallow peat lake in the Netherlands. The lake is characterized by rich submerged vegetation dominated by two species: Potamogeton perfoliatus and Nitellopsis obtusa. Continuous eddy covariance (EC) measurements of methane fluxes, collected since December 2021, were combined with various water quality data to assess seasonal and interannual variabilities. Our results show a clear seasonal pattern, with substantially higher methane emissions during summer months (average of 165 mg m-2 d-1), compared to autumn, winter and spring (average of 50, 15 and 68 mg m-2 d-1, respectively). Through strong positive correlations, both water and air temperature were identified as the main drives of methane emissions, with the redox potential at the lake water-sediments interface also showing strong negative correlation. Interestingly, two distinct emission peaks were observed each early summer and again in late summer to early autumn. These peaks are likely linked to the macrophyte life cycle, with an early-season peak preceding full plant development, a mid-summer decrease possibly associated with oxygen input from the vegetation, and a late-season increase due to plant decomposition. These findings highlight the role of aquatic vegetation in methane release from shallow peat lakes. Better quantifying these temporal drivers is important to improve regional and global methane budgets.

Exposed sediments from dry inland waters are an important component of the global carbon cycle, and their extent is increasing worldwide due to climate change and intensified human water use. These dry sediments often become colonized by terrestrial vegetation, which can counterbalance the mineralization of exposed organic matter through photosynthesis, thereby reducing overall CO2 emissions. However, current CO2 flux estimates from dry sediments are largely derived from bare sediments, meaning that the potential role of vegetation has been overlooked. To assess the role of vegetation in modulating CO2 fluxes from dry sediments, we conducted a global study across 164 dry inland waterbodies (including lakes, ponds, reservoirs, streams, and wetlands) spanning a wide range of climatic regions from arid to polar. At each site, we measured CO2 fluxes from vegetated and bare dry sediments using a standardized chamber-based method under two conditions: dark (capturing respiration only) and light (capturing both respiration and photosynthesis). On average, within vegetated zones, vegetation occupied 47 ± 35% in measured biomass quadrants.Our results showed that under light conditions, instantaneous CO2 fluxes were lower in vegetated sediments (mean ± SD = – 3.7 ± 12.9 mmol CO2 m⁻² h⁻¹) compared to bare sediments (5.4 ± 12.7 mmol CO2 m⁻² h⁻¹), suggesting that photosynthesis contributed to decrease CO2 emissions to the atmosphere. In contrast, under dark conditions, vegetated sediments exhibited larger positive CO2 fluxes (14.7 ± 20.1 mmol CO2 m-2 h-1) than bare sediments (5.4 ± 8.2 mmol CO2 m-2 h-1), likely due to plant respiration. Across ecosystem types and climatic zones, average net CO2 emissions over a full diel cycle were 25% (± 358) lower from vegetated than from bare sediments, indicating that vegetation can partially offset sediment respiration.Upscaling these fluxes to the ecosystem level considering vegetation cover, revealed that all waterbody types still function as net carbon sources. When exploring the potential effect of vegetation on previously published estimates only based on bare sediments, we found that global CO2 fluxes from dry sediments could be suppressed by 10% (± 111%) due to the effect of vegetation.