Lake Dynamics Research Articles

Evolution of the Miocene megalake in the western Qaidam Basin, northwestern China

Thick Miocene lacustrine deposits have been identified across the Qaidam Basin on the northeast Tibetan Plateau, indicative of a relatively unified megalake then. How this megalake evolved at its final stage and associated controlling factors, e.g., global climate or tectonic uplift, remain largely elusive. Here we use the KC-1 well, drilled at the depo-center of the western Qaidam Basin, to investigate the megalake evolution over the mid- and late Miocene. A set of lipid biomarker indices, namely β-carotane/n-C36, gammacerane index, terrigenous/aquatic ratio and long-chain saturated ketone content, altogether indicate substantial lake level fluctuations, with lower lake level at the intervals of ~18–17 Ma, 13.5–11.5 Ma, 10.5–8 Ma and 7–6 Ma, and higher level at the intervals of ~17–13.5 Ma, 11.5–10.5 Ma, 8–7 Ma and 6–5 Ma, superimposed on the long-term shrinking trend. Direct comparison with existing regional and global temperature records suggests that such lake dynamics was largely associated with global climatic conditions, i.e., shrinking under relatively cool conditions and vice versa, for both its long-term evolution and secondary fluctuations. It thus appears that global climatic conditions had controlled the megalake status during the mid- and late Miocene, whereas tectonic activities then might have also contributed to its long-term gradual demise.

The Effects of Lake Representation on the Regional Hydroclimate in the ECMWF Reanalyses

AbstractLakes are an integral part of the geosphere, but they are challenging to represent in Earth system models which either exclude lakes or prescribe properties without simulating lake dynamics. In ECMWF Interim reanalysis (ERA-Interim), lakes are represented by prescribing lake surface water temperatures (LSWT) from external data sources, while the newer generation ERA5 introduces the FLake parameterization scheme to the modelling system with different LSWT assimilation data sources. This study assesses the performance of these two reanalyses over three regions with the largest lakes in the world (Laurentian Great Lakes, African Great Lakes, and Lake Baikal) to understand the effects of their simulation differences on hydrometeorological variables. We find that differences in lake representation alter the associated hydrological and atmospheric processes and can affect regional hydroclimatic assessments. There are prominent differences in LSWT between the two datasets which influence the simulation of lake-effect snowstorms in the Laurentian winters and lake-land breeze circulation patterns in the African region. Generally, ERA5 has warmer LSWT in all three regions for most months (by 2-12 K) and its evaporation rates are up to twice the magnitudes in ERA-Interim. In the Laurentian lakes, ERA5 has strong biases in LSWT and evaporation magnitudes. Over Lake Baikal and the African Great Lakes, ERA5 LSWT magnitudes are closer to satellite-based datasets, albeit with warm bias (1-4 K), while ERA-Interim underestimates the magnitudes. ERA5 also simulates intense precipitation hotspots in lake proximity that are not visible in ERA-Interim and other observation-based datasets. Despite these limitations, ERA5 improves the simulation of lake-land circulation patterns across the African Great Lakes.

Effect of water-level fluctuations on methane and carbon dioxide dynamics in a shallow lake of Northern China: Implications for wetland restoration

Shallow lakes are characterized by strong hydrological fluctuations, affecting their biochemistry and carbon (C) balance. This study explored carbon dioxide (CO2) and methane (CH4) flux under strong water-level fluctuations in a shallow lake while also addressing its implications regarding wetland restoration. The DeNitrification-DeComposition (DNDC) model, a process-based biogeochemical model, was used to simulate CO2 and CH4 flux under intensive water-level fluctuations in Lake Baiyangdian (BYD), Northern China. Results showed that: (i) the DNDC model was able to reasonably capture CO2 and CH4 dynamics, which were determined to be extremely sensitive to water-depth fluctuations at a −10 cm to 10 cm range; (ii) the lowest CO2 flux was observed at a 40-day duration, while the trend in annual CH4 flux was to increase as inundation time increased, changing from −2.27 kg C/ha/y to 1.57 kg C/ha/y; and (iii) CO2 and CH4 flux increased under higher fluctuation frequencies, wherein CO2 flux was lowest in January and February and CH4 flux increased from December to March under certain frequencies. Our results indicate that water-level fluctuations (e.g., water depth, duration, frequency, and timing) affected both CO2 and CH4 flux. As it pertains to water diversion projects used for shallow lake restoration initiatives, the optimum approach, pertinent to water yields, diversion time, and duration, should first be considered carefully. Results from this study provide useful information for assisting policymakers with respect to reducing gaseous C emissions during ecological water transfer project regulations in shallow lakes.

Lake thermal structure drives interannual variability in summer anoxia dynamics in a eutrophic lake over 37 years

Abstract. The concentration of oxygen is fundamental to lake water quality and ecosystem functioning through its control over habitat availability for organisms, redox reactions, and recycling of organic material. In many eutrophic lakes, oxygen depletion in the bottom layer (hypolimnion) occurs annually during summer stratification. The temporal and spatial extent of summer hypolimnetic anoxia is determined by interactions between the lake and its external drivers (e.g., catchment characteristics, nutrient loads, meteorology) as well as internal feedback mechanisms (e.g., organic matter recycling, phytoplankton blooms). How these drivers interact to control the evolution of lake anoxia over decadal timescales will determine, in part, the future lake water quality. In this study, we used a vertical one-dimensional hydrodynamic–ecological model (GLM-AED2) coupled with a calibrated hydrological catchment model (PIHM-Lake) to simulate the thermal and water quality dynamics of the eutrophic Lake Mendota (USA) over a 37 year period. The calibration and validation of the lake model consisted of a global sensitivity evaluation as well as the application of an optimization algorithm to improve the fit between observed and simulated data. We calculated stability indices (Schmidt stability, Birgean work, stored internal heat), identified spring mixing and summer stratification periods, and quantified the energy required for stratification and mixing. To qualify which external and internal factors were most important in driving the interannual variation in summer anoxia, we applied a random-forest classifier and multiple linear regressions to modeled ecosystem variables (e.g., stratification onset and offset, ice duration, gross primary production). Lake Mendota exhibited prolonged hypolimnetic anoxia each summer, lasting between 50–60 d. The summer heat budget, the timing of thermal stratification, and the gross primary production in the epilimnion prior to summer stratification were the most important predictors of the spatial and temporal extent of summer anoxia periods in Lake Mendota. Interannual variability in anoxia was largely driven by physical factors: earlier onset of thermal stratification in combination with a higher vertical stability strongly affected the duration and spatial extent of summer anoxia. A measured step change upward in summer anoxia in 2010 was unexplained by the GLM-AED2 model. Although the cause remains unknown, possible factors include invasion by the predacious zooplankton Bythotrephes longimanus. As the heat budget depended primarily on external meteorological conditions, the spatial and temporal extent of summer anoxia in Lake Mendota is likely to increase in the near future as a result of projected climate change in the region.

Microbial succession and dynamics in meromictic Mono Lake, California.

Mono Lake is a closed‐basin, hypersaline, alkaline lake located in Eastern Sierra Nevada, California, that is dominated by microbial life. This unique ecosystem offers a natural laboratory for probing microbial community responses to environmental change. In 2017, a heavy snowpack and subsequent runoff led Mono Lake to transition from annually mixed (monomictic) to indefinitely stratified (meromictic). We followed microbial succession during this limnological shift, establishing a two‐year (2017–2018) water‐column time series of geochemical and microbiological data. Following meromictic conditions, anoxia persisted below the chemocline and reduced compounds such as sulfide and ammonium increased in concentration from near 0 to ~400 and ~150 µM, respectively, throughout 2018. We observed significant microbial succession, with trends varying by water depth. In the epilimnion (above the chemocline), aerobic heterotrophs were displaced by phototrophic genera when a large bloom of cyanobacteria appeared in fall 2018. Bacteria in the hypolimnion (below the chemocline) had a delayed, but systematic, response reflecting colonization by sediment “seed bank” communities. Phototrophic sulfide‐oxidizing bacteria appeared first in summer 2017, followed by microbes associated with anaerobic fermentation in spring 2018, and eventually sulfate‐reducing taxa by fall 2018. This slow shift indicated that multi‐year meromixis was required to establish a sulfate‐reducing community in Mono Lake, although sulfide oxidizers thrive throughout mixing regimes. The abundant green alga Picocystis remained the dominant primary producer during the meromixis event, abundant throughout the water column including in the hypolimnion despite the absence of light and prevalence of sulfide. Our study adds to the growing literature describing microbial resistance and resilience during lake mixing events related to climatic events and environmental change.

Mapping the spatiotemporal variability of salinity in the hypersaline Lake Urmia using Sentinel-2 and Landsat-8 imagery

The spatiotemporal dynamic of salinity concentration (SC) in saline lakes is strongly dependent on the rate of water flow into the lake, water circulation, wind speed, evaporation rate, and the phenomenon of salt precipitation and dissolution. Although in-situ observations most reliably quantify water quality metrics, the spatiotemporal distribution of such data are typically limited and cannot be readily extrapolated for either long-term projections or extensive areas. Alternatively, remotely sensed imagery has facilitated less expensive and a stronger ability to estimate water quality over a wide range of spatiotemporal resolutions. This study introduces an adaptive learning model that leverages in-situ measurements, satellite imagery, and machine learning algorithms to estimate the spatiotemporal changes of water surface SC in saline lakes. We demonstrate the applicability of the framework by using high-resolution Sentinel-2 and Landsat-8 satellite data in the Lake Urmia (LU), where 130 points were sampled in April and July 2019 for the model calibration and validation purposes. The results showed that Artificial Neural Network (ANN) yields the most accurate relationship between SC and water surface reflectance (R2 = 0.94; NRMSE = 6.9%; MAE = 12.3 ppt) as compared to Adaptive Network-based Fuzzy Inference System (ANFIS), and Multiple Linear Regression (MLR) models. A sharp distinction in SC between the LU’s northern and southern parts was observed during high flows due to the limitation on north–south water mixing imposed by the lake’s middle causeway. Nevertheless, the impact of causeway on water circulation at the other seasons is minimum. A hysteretic relationship was also found between the lake water volume and the lake-averaged SC due to the distinct role of bed-salt dissolution and high evaporation rate at different seasons. A tight agreement between the SC variations in the southern part and the whole lake proved that the southern part dominantly controls SC dynamics in the whole lake.

Internal positive feedback promotes water quality improvement for a recovering hyper-eutrophic lake: A three-dimensional nutrient flux tracking model

Nutrient dynamics in lakes are determined by the combined effects of external and internal nutrient fluxes. However, the feedback loop of nutrient fluxes and water quality changes is still an open question. An integrated three-dimensional flux tracking approach based on the Environmental Fluid Dynamics Code model was established to quantify the long-term dynamic changes in external and internal processes in Lake Dianchi (one of the three most hyper-eutrophic lakes in China), and to explore the potential causes of water quality improvement during 2012–2018. The long-term trends and relative influences of nutrient fluxes on water quality were identified. The results showed that the inflow flux was the largest input source and declined by 50% between 2003 and 2012, which was followed by a stable trend from 2012 to 2018. The second largest input source was benthic release, which exhibited a significant interannual reduction. Algae sedimentation was the largest removal process, and declined by 45% between 2012 and 2018. An integrated analysis demonstrated that, following an external loading reduction prior to 2012, the positive feedback of internal fluxes promoted water quality improvement during 2012–2018. Considering the long timescale of the nutrient-flux feedback mechanism, reducing external loading is still the top priority for a long-term virtuous cycle of water quality in the process of eutrophic lake restoration.

Decoding the dramatic hundred-year water level variations of a typical great lake in semi-arid region of northeastern Asia

Lakes in arid and semi-arid regions are experiencing dramatic variations in water level and volume, which has caused severe ecological and social problems. Long-term study of the lake dynamics in arid/semi-arid regions could provide particular insights into the mechanisms driving lake variations, while hydro-meteorological data were usually limited in these regions, especially before the instrumental period. In the present study, we focused on a typical great lake – Hulun Lake in semi-arid region in northern China, simulated the hydrological processes from 1904 to 2016 using SWAT model, CRUNCEP7 reanalysis data, and sparse records of lake level during 1900s–1950s, and investigated the mechanisms driving the dramatic variations of the lake at the hundred-year time scale. Results illustrated that the simplified Penman equation by Valiantzas (2006) could reproduce the evaporation dynamics of Hulun Lake, with monthly R2 being 0.93–0.95. The long-term simulation since 1904 reproduced runoff dynamics, which were consistent with the dramatic variations of lake level over hundred years. The largest water level increase (~5.0 m in 1950s) and decrease (~4.5 m in 2000s) during 1904–2016 were jointly affected by river runoff, lake evaporation, and precipitation into the lake. Both the positive/negative phase and the multi-decadal trend of PDO clearly influenced the hydrological cycle of Hunlun Lake, especially for the period of 1904–1950 with low lake levels. Overall, the present study provided a methodology for investigating the hundred-year hydrological processes for lakes in semi-arid regions in northeastern Asia.

Complex interactions between meteorological parameters and the thermal regime of two tropical, high altitude crater lakes (Nevado de Toluca, Mexico)

Using long-term time series of meteorological and water-column parameters, the dynamics of two lakes separated by about 500 m from each other by a central lava dome, located at 4207 m above sea level in the volcano crater of Nevado de Toluca, Mexico were explored. Because of the strong wind-forcing previously measured on the volcano slope and the proximity of the lakes, wind-mixing was expected, with similar dynamics in both lakes. However, the meteorological parameters in the crater were significantly different than on the slope of the volcano, due to the dome and the high walls of the crater, which weakened wind speeds, modified wind direction, and reduced exposure to solar radiation by almost 20% in the crater compared to on the volcano slope. The rate and depth of thermal penetration into each lake differed by an order of magnitude, related with differential insolation due to crater wall shading, along with differences in transparency, most likely due to differential algal growth and suspended matter. At times, rapid surface cooling occurred during periods of reduced insolation and calm winds, leading to strong vertical convection and the formation of a characteristic step profile in the water column rather than the predicted wind mixing. These results are important for interdisciplinary studies of these and other alpine lakes and, in particular for biophysical coupling in these unique hydrological systems.

A Novel Method for Automated Supraglacial Lake Mapping in Antarctica Using Sentinel-1 SAR Imagery and Deep Learning

Supraglacial meltwater accumulation on ice sheets can be a main driver for accelerated ice discharge, mass loss, and global sea-level-rise. With further increasing surface air temperatures, meltwater-induced hydrofracturing, basal sliding, or surface thinning will cumulate and most likely trigger unprecedented ice mass loss on the Greenland and Antarctic ice sheets. While the Greenland surface hydrological network as well as its impacts on ice dynamics and mass balance has been studied in much detail, Antarctic supraglacial lakes remain understudied with a circum-Antarctic record of their spatio-temporal development entirely lacking. This study provides the first automated supraglacial lake extent mapping method using Sentinel-1 synthetic aperture radar (SAR) imagery over Antarctica and complements the developed optical Sentinel-2 supraglacial lake detection algorithm presented in our companion paper. In detail, we propose the use of a modified U-Net for semantic segmentation of supraglacial lakes in single-polarized Sentinel-1 imagery. The convolutional neural network (CNN) is implemented with residual connections for optimized performance as well as an Atrous Spatial Pyramid Pooling (ASPP) module for multiscale feature extraction. The algorithm is trained on 21,200 Sentinel-1 image patches and evaluated in ten spatially or temporally independent test acquisitions. In addition, George VI Ice Shelf is analyzed for intra-annual lake dynamics throughout austral summer 2019/2020 and a decision-level fused Sentinel-1 and Sentinel-2 maximum lake extent mapping product is presented for January 2020 revealing a more complete supraglacial lake coverage (~770 km2) than the individual single-sensor products. Classification results confirm the reliability of the proposed workflow with an average Kappa coefficient of 0.925 and a F1-score of 93.0% for the supraglacial water class across all test regions. Furthermore, the algorithm is applied in an additional test region covering supraglacial lakes on the Greenland ice sheet which further highlights the potential for spatio-temporal transferability. Future work involves the integration of more training data as well as intra-annual analyses of supraglacial lake occurrence across the whole continent and with focus on supraglacial lake development throughout a summer melt season and into Antarctic winter.

Seasonal variations in food web dynamics of floodplain lakes with contrasting hydrological connectivity in the Southern Gulf of Mexico

Floodplains are some of the most productive and diverse ecosystems on Earth. The Usumacinta River Basin, in the Southern Gulf of Mexico, hosts several floodplain lakes, whose integrity is threatened by water resource development. We aimed to investigate how food webs in these ecosystems vary in relation to their hydrological connectivity and seasonal flood cycles. To do this, we combined analysis of water quality and stable isotopes in two lakes with permanent connection to the Usumacinta River and two isolated lakes during dry, early rainy and late rainy season. Significant differences in chlorophyll-a, nutrients and suspended solids were reflected in distinct trophic dynamics among lakes. Stable isotope analysis revealed that fish from all lakes relied predominantly on autochthonous primary production, but while phytoplankton was the dominant resource for fish in the isolated lakes, aquatic macrophytes made the highest contribution to consumers’ production in the connected lakes. Fish tended to have broader isotopic niches during the early rainy season, likely reflecting consumption of a wider range of resources following the first flow pulses of the year. Our study highlights the importance of hydrological connectivity and natural flow regimes to maintain the outstanding biodiversity and fishery yield of these floodplain ecosystems.

Using Remote Sensing to Understand the Total Suspended Matter Dynamics in Lakes Across Inner Mongolia

An exponential function model was developed based on the red band from Landsat and in situ data. The model performed well, the calibration determination coefficient ( R 2) was 0.82 and validation metrics root-mean-square error, mean absolute percent error, and bias was 8.23 mg/L, 30% and −2.35 mg/L, respectively. Then, the time series of total suspended matter (TSM) concentrations for the lakes across Inner Mongolia were presented using the Landsat data from 1984–2019. The results showed that the number of the lakes with TSM decrease was slightly more than that with TSM increase (57% versus 43%). A total of 70.72% of those lakes had a changing rate less than 1 mg/L/yr in TSM, while the other 29.28% had a changing rate more than 1 mg/L/yr. In some lakes (24.2%), the coefficient of variation was greater than 102% indicating significant spatial variation. The TSM less than 20 mg/L mainly appeared in the reservoirs. Based on different environmental backgrounds, this study showed comprehensive estimates (increasing and decreasing regions) of TSM concentrations. Finally, the relative roles of several factors to the TSM changes were quantified and examined at different scales. The responses of TSM changes to NDVI representing vegetation coverage indicated that vegetation played an important role for most lakes. Whilst wind speed and precipitation significantly affected a few lakes. For most lakes, the TSM were affected by multiple factors, where a single factor could not be highlighted. Nevertheless, a comprehensive analysis of the factors surrounding a lake remains relevant for determining the possible trend (better or worse) of its TSM variation.

Spatial distribution of zooplankton in response to ecological dynamics in tropical shallow lake: insight from Lake Malombe, Malawi

This study assessed zooplankton density and Chl-a amount to understand their spatial and seasonal variation in Lake Malombe. Samples were collected for analysis during the hot, dry season (HDS) and cool, dry, windy season (CDWS). The zooplankton identified were Tropodiaptomus cunningtoni (TC), Mesocyclops aequatorialis aequatorialis (MAA), Thermocyclops neglectus (TN), Bosmina longirostris (BL), Diaphanosoma spp. (DS), and Nauplii. These zooplankton groups belong to copepods, Cyclopidae, Cladocera, Ctenopod, and Rotifers. Chl-a exhibited a substantial seasonal variation, with the highest concentration observed in HDS and lowest in CDWS. Zooplankton such as T. cunningtoni, M. aeq. aequatorialis, T. neglectus, B. longirostris, Diaphanosoma spp, Nauplii, and Rotifer increased during the HDS. The water temperatures (WT), pH, Dissolved Oxygen (DO), and Chl-a positively correlated with all zooplankton densities. Sodium (Na+) and Potassium (K+) ions positively correlated with TC, MAA, DS, Nauplii, and Rotifers. Chloride ion (Cl-) positively correlated with DS, Rotifers, while Carbonate ion (CO3 2-) positively correlated with TC. Bicarbonate (HCO3 -) correlated positively with DS and Rotifers, while TDS correlated negatively with BL, Nauplii, and Rotifers. Nitrite affected zooplankton density negatively, while SRP had a positive effect. The study revealed that physical-chemical variables, some significant ions, and Chl-a are the most critical factors influencing the spatial and seasonal variation of zooplankton density in the lake. These findings demonstrate the interaction between physical-chemical variables, Chl-a, and zooplankton and highlight the significance of ecological understanding of the complex dynamics of the food web system in shallow tropical lakes such as Lake Malombe- under the changing climate.

Water quality dynamics of floodplain lakes in relation to river flooding and cattle grazing

Floodplain water quality is naturally regulated by river floods, but is increasingly affected by anthropogenic activities. Accordingly, we evaluated the combined influence of river flooding (pre- and post-flood periods) and rotational grazing (cattle presence or absence) on water quality of floodplain lakes. We hypothesised that river floods decrease the concentrations of most water constituents and dilute grazing effects on water quality, and that differences in cattle pressure (i.e. grazing duration) promote differences in water quality among lakes. Nutrient concentration decreased after the flood through washing-out and dilution, but other water constituents showed different responses. Contrary to expectations, water-quality changes in relation to cattle presence or absence occurred only after the flood, with higher turbidity and phosphorus during periods with than without cattle. Finally, water-quality variability among lakes was attributed to their different sizes (and therefore dilution capacities), but not to differences in cattle pressure. Our results suggest that river–floodplain connectivity and grazing location in areas with large lakes are important for preserving water quality. Pre-flood changes in water quality in relation to cattle presence or absence could have been obscured by wind-driven sediment resuspension, which has important effects during shallow-water stages, and by high phosphorus concentration, which can prevent removal during periods without cattle.

Response of lake dynamics to climate change in the Hala Lake Basin of Tibetan Plateau from 1986 to 2015

Response of lake dynamics to climate change in the Hala Lake Basin of Tibetan Plateau from 1986 to 2015

Climate-Change Induced Permafrost Degradation in Yakutia, East Siberia


 Current climate change in the northern regions is a well-recognized phenomenon. In central Yakutia (the Sakha Republic), the long-term trend displays a consistent mean annual air temperature (MAAT) increase from −9.6˚C (1980) to −6.7˚C (2019), corresponding to an average 0.07˚C annual rise, with pronounced temperature anomalies in the last decade. The analyzed meteorological records of the past 40 years indicate a progressing climate change pattern of increased MAAT and mean annual precipitation (MAP) that occurs in 5 – 7 yr cycles. The complex interactions of regional climatic variations with local geological and environmental conditions influence the frozen ground’s thermal balance, which, in turn, impacts thermokarst development. Co-acting factors of temperature rise and higher precipitation rates activate thermokarst lake dynamics and lake expansion following snow- and rainfall-rich preceding years. April experiences the greatest warming trend with a present (2020) 5˚C rise from 1980 with shortening of the winter season. Climate warming together with natural forest fires and anthropogenic activities (pastoral practices and logging) contribute to the taiga landscape opening due to reduced albedo and the greater exposure to solar radiation. The regional hydrologic network undergoes restructuring caused by drained meltwater released from the degraded cryolithozone with peaks of the fluvial discharge in late spring and early summer generating bank erosion. The negative effects of the progressing ground thaw, which are particularly observed in lowland locations, pose risks to local settlements and generate major environmental and engineering problems in the formerly permafrost-stable central and northern areas of Siberia.

The setup and relaxation of spring upwelling in a deep, rotationally influenced lake

AbstractStrong and sustained winds can drive dramatic hydrodynamic responses in density‐stratified lakes, with the associated transport and mixing impacting water quality, ecosystem function, and the stratification itself. Analytical expressions offer insight into the dynamics of stratified lakes during severe wind events. However, it can be difficult to predict the aggregate response of a natural system to the superposition of hydrodynamic phenomena in the presence of complex bathymetry and when forced by variable wind patterns. Using an array of current, temperature, and water quality measurements at the upwind shore, we detail the hydrodynamic response of deep, rotationally influenced Lake Tahoe to three strong wind events during late spring. Sustained southwesterly winds in excess of 10 m s−1 drove upwelling at the upwind shore (characteristic of non‐rotational upwelling setup), with upward excursions of deep water exceeding 70 m for the strongest event. Hypolimnetic water, with elevated concentrations of chlorophyll a and nitrate, was advected toward the nearshore, but this water rapidly returned to depth with the relaxation of upwelling after the winds subsided. The relaxation of upwelling exhibited rotational influence, highlighted by an along‐shore, cyclonic front characteristic of a Kelvin wave‐driven coastal jet, with velocities exceeding 25 cm s−1. The rotational front also produced downwelling to 100 m, transporting dissolved oxygen to depth. More complex internal wave features followed the passage of these powerful internal waves. Results emphasize the complexity of these superimposed hydrodynamic phenomena in natural systems, providing a conceptual reference for the role upwelling events may play in lake ecosystems.

Aquatic food webs in deep temperate lakes: Key species establish through their autecological versatility

Microbial planktonic communities are the basis of food webs in aquatic ecosystems since they contribute substantially to primary production and nutrient recycling. Network analyses of DNA metabarcoding data sets emerged as a powerful tool to untangle the complex ecological relationships among the key players in food webs. In this study, we evaluated co-occurrence networks constructed from time-series metabarcoding data sets (12months, biweekly sampling) of protistan plankton communities in surface layers (epilimnion) and bottom waters (hypolimnion) of two temperate deep lakes, Lake Mondsee (Austria) and Lake Zurich (Switzerland). Lake Zurich plankton communities were less tightly connected, more fragmented and had a higher susceptibility to a species extinction scenario compared to Lake Mondsee communities. We interpret these results as a lower robustness of Lake Zurich protistan plankton to environmental stressors, especially stressors resulting from climate change. In all networks, the phylum Ciliophora contributed the highest number of nodes, among them several in key positions of the networks. Associations in ciliate-specific subnetworks resembled autecological species-specific traits that indicate adaptions to specific environmental conditions. We demonstrate the strength of co-occurrence network analyses to deepen our understanding of plankton community dynamics in lakes and indicate biotic relationships, which resulted in new hypotheses that may guide future research in climate-stressed ecosystems.

Marine lakes as biogeographical islands: a physical model for ecological dynamics in an insular marine lake, Palau

Marine lakes are emerging ecological and evolutionary natural experimental systems, with genetically isolated resident populations that exhibit extreme population dynamics and rapid phenotypic change. Marine lakes are posited to be marine islands, however, unlike terrestrial islands for which rich models have been developed over the past half-century, we know little of the mechanisms driving changes in marine lakes. This is a critical knowledge gap in efforts to reconcile theory on, or distinguish differences among, island and island-like systems. To reduce this critical knowledge gap, we present a mathematical model describing marine lakes based on a case study of Jellyfish Lake (Ongeim’l Tketau, Mecherchar: OTM), Palau. Empirical data show that marine lakes exhibit delayed and reduced tidal motions, suggesting exchange of a limited amount of water with the neighboring (‘mainland’) ocean. Our model tracks changes in lake level, allowing determination of an exchange rate that is a physical null model for biological colonization and a proxy for colonization distance in island biogeography theory. In addition, we track horizontally averaged in-lake quantities such as salinity and temperature (i.e., marine weather, climate) and stratification (i.e., habitat) — that are known to influence resident species’ distributions and population dynamics — by solving an advection-diffusion equation. We find that weather, ocean conditions, groundwater, and exchanges through tunnels determine the abiotic environment in OTM. By comparing simulations and data, we estimate the difficult-to-measure properties of the surrounding groundwater — the ‘matrix’ in the vernacular of habitat islands — and give a range of realistic values for the effective diffusion coefficient. This coefficient is found to increase in a tropical storm, suggesting that other drivers can be important during perturbations.

Ecosystem-Scale Oxygen Manipulations Alter Terminal Electron Acceptor Pathways in a Eutrophic Reservoir

Lakes and reservoirs globally are experiencing unprecedented changes in land use and climate, depleting dissolved oxygen (DO) in the bottom waters (hypolimnia) of these ecosystems. Because DO is the most energetically favorable terminal electron acceptor (TEA) for organic carbon mineralization, its availability controls the onset of alternate TEA pathways (for example, denitrification, manganese reduction, iron reduction, sulfate reduction, methanogenesis). Low DO concentrations can trigger organic carbon mineralization via alternate TEA pathways in the water column and sediments, which has important implications for greenhouse gas production [carbon dioxide (CO2) and methane (CH4)]. In this study, we experimentally injected supersaturated DO into the hypolimnion of a eutrophic reservoir and measured concentrations of TEAs and terminal electron products (TEPs) in the experimental reservoir and an upstream reference reservoir. We calculated the electron equivalents yielded from each TEA pathway and estimated the contributions of each TEA pathway to organic carbon processing in both reservoirs. DO additions to the hypolimnion of the experimental reservoir promoted aerobic respiration, suppressing most alternate TEA pathways and resulting in elevated CO2 accumulation. In comparison, organic carbon mineralization in the reference reservoir’s anoxic hypolimnion was dominated by alternate TEA pathways, resulting in both CH4 and CO2 accumulation. Our ecosystem-scale experiments demonstrate that the alternate TEA pathways that succeed aerobic respiration in lakes and reservoirs can be manipulated at the ecosystem scale. Moreover, changes in the DO dynamics of freshwater lakes and reservoirs may result in concomitant changes in the redox reactions in the water column that control organic carbon mineralization and greenhouse gas accumulation.