Temperate Lakes Research Articles

Rhythm of relationships in a social fish over the course of a full year in the wild

BackgroundAnimals are expected to adjust their social behaviour to cope with challenges in their environment. Therefore, for fish populations in temperate regions with seasonal and daily environmental oscillations, characteristic rhythms of social relationships should be pronounced. To date, most research concerning fish social networks and biorhythms has occurred in artificial laboratory environments or over confined temporal scales of days to weeks. Little is known about the social networks of wild, freely roaming fish, including how seasonal and diurnal rhythms modulate social networks over the course of a full year. The advent of high-resolution acoustic telemetry enables us to quantify detailed social interactions in the wild over time-scales sufficient to examine seasonal rhythms at whole-ecosystems scales. Our objective was to explore the rhythms of social interactions in a social fish population at various time-scales over one full year in the wild by examining high-resolution snapshots of a dynamic social network.MethodsTo that end, we tracked the behaviour of 36 adult common carp, Cyprinus carpio, in a 25 ha lake and constructed temporal social networks among individuals across various time-scales, where social interactions were defined by proximity. We compared the network structure to a temporally shuffled null model to examine the importance of social attraction, and checked for persistent characteristic groups over time.ResultsThe clustering within the carp social network tended to be more pronounced during daytime than nighttime throughout the year. Social attraction, particularly during daytime, was a key driver for interactions. Shoaling behavior substantially increased during daytime in the wintertime, whereas in summer carp interacted less frequently, but the interaction duration increased. Therefore, smaller, characteristic groups were more common in the summer months and during nighttime, where the social memory of carp lasted up to two weeks.ConclusionsWe conclude that social relationships of carp change diurnally and seasonally. These patterns were likely driven by predator avoidance, seasonal shifts in lake temperature, visibility, forage availability and the presence of anoxic zones. The techniques we employed can be applied generally to high-resolution biotelemetry data to reveal social structures across other fish species at ecologically realistic scales.

A 3D numerical modeling of the links between hydrodynamics, dissolved oxygen, and water temperature of a northern rural-urban shallow lake with two distinct basins.

A 3D hydrodynamic model (EFDC) was applied to simulate dissolved oxygen (DO) and temperature (T) (two crucial parameters impacting water quality) throughout Lake St. Charles, a rural-urban shallow lake located North of Quebec City, Canada. Model outputs of T and DO corroborate observations at five monitoring stations within the lake. Simulated results indicated annual cycles of turnovers and stratifications and different behaviors for the deep and shallow basins. For the simulated years, the deep basin was stratified in summer and winter, while the shallow basin was mostly mixed throughout the year. The lake heat budget indicates that during summer with a long retention time, the thermal structure of the lake is principally controlled by net radiation, latent, and sensible heat fluxes. For the rest of the year, the inflow (from the main tributary, the Des Hurons River) and outflow are the main drivers of the lake's thermal structure.

Influence of Denitrification on Cyanobacterial Blooms Trends in Lake Taihu, China

Denitrification is a major process in aquatic ecosystems, and it competes with cyanobacterial growth for nitrogen. However, the effect of denitrification on cyanobacterial blooms under the background of climate change remains unclear. This study explored the interaction between lake denitrification and formation of cyanobacterial blooms, using the historical water quality monitoring data of North Lake Taihu over five years from 2017 to 2021 and via incubation experiments of cyanobacteria and sediment denitrification. The monitoring data showed that algal biomass (Chla as a proxy) primarily peaked during summer and autumn. The seasonal variations in total N concentration showed a completely opposite trend than that of algal biomass, which peaked in winter and spring. Nitrate was the major component of dissolved inorganic nitrogen, and the nitrate concentration was approximately zero in summer and autumn. The total phosphorus concentration varied in the same way as the Chla concentration. The experimental results showed that Cyanobacteria did not grow when the temperature was below 20℃. In comparison, denitrification showed a significant linear relationship with temperatures between 10-25℃ (R2=0.99) and reached the maximum value of (62.98±21.36) μmol·(kg·h)-1 in Lake Taihu at 25℃. Additionally, the nitrate concentration threshold at the maximum denitrification rate was 4 mg·L-1. Cyanobacteria assimilate nitrate for growth, thereby reducing the concentration of nitrate required for denitrification. This study indicated that the advance in lake temperature warming due to climate change may result in earlier growth of cyanobacteria, thereby leading to large amounts of N being assimilated by algae before denitrification, further affecting the dynamics of cyanobacterial blooms. The present results are scientifically important for explaining the mechanism of cyanobacterial bloom rebound in Lake Taihu under the background of recent climate changes.

How Do Extreme Lake Water Temperatures in Poland Respond to Climate Change?

Lakes are vital components of the Earth’s hydrological cycle and are susceptible to the impacts of climate change. Understanding the changes in terms of minimum and maximum lake surface temperatures is crucial for assessing the effects of climate change on freshwater ecosystems. This study focuses on ten lakes in Poland to investigate the impacts of climate change on lake temperatures in different geographical regions. The Mann–Kendall (MK) and Sen tests were employed to analyze trends and changes in minimum and maximum water temperatures, respectively. The results reveal significant increases in the minimum and maximum temperatures, particularly in May and June. Different lakes exhibit varying trends and variability in temperature changes over time, indicating the vulnerability of these ecosystems. The current study also examines the magnitude of annual temperature changes and classifies them into different levels. This analysis highlights the complex relationship between air temperature, seasonal cycles, and lake morphometric characteristics in shaping variations in lake surface water temperature. These findings contribute to understanding the impacts of climate change on Poland’s lakes and provide valuable insights for developing conservation strategies and adaptive measures to protect freshwater resources.

Seasonality and lake water temperature inferred from the geochemistry and sclerochronology of quaternary freshwater bivalves from the Turkana Basin, Ethiopia and Kenya

Reconstructing past environmental variability at short (annual-decadal) time scales is critical for understanding ecosystem change and ecological drivers of evolution. One promising approach to reconstructing that variability is through the use of stable isotope geochemistry and sclerochronology, the study of growth banding in organisms that undergo accretionary growth. We used a combination of sclerochronology, conventional stable isotope ratios and clumped isotope paleotemperatures to improve our understanding of past seasonality and climate variability in the Turkana Basin (Kenya, Ethiopia), which experiences a highly seasonal (tropical semi-desert) climate. In this case study, we apply these approaches to both Early Pleistocene and Holocene bivalve shells (Etheria and Pseudobovaria) to develop a model using various proxies of seasonal-interannual temporal variability in lake temperature and isotope chemistry. We leverage this model to better understand how lakes in the Turkana Basin have changed over short time-scales in the past. One modern (1979) river oyster has exclusively negative δ18O values through ∼1.5 yrs of growth and clumped isotope temperature reconstructions (30.1–31.5 °C) consistent with a river delta provenance. Late Holocene shells show a wider range of isotopic variability within each shell's growth history than the modern sample (∼2‰ for the modern sample vs. 5–7‰ for the Late Holocene samples) and near modern paleotemperatures, suggesting growth under both seasonal Omo flood pulse and lacustrine conditions. Middle Holocene shells exhibit less δ18O variability, consistent with growth in fresher Lake Turkana water at the end of the African Humid Period (12-5 ka), and with both surface water temperatures and water column temperature range similar to the Late Holocene. The Early Pleistocene shells have large seasonal δ18O cycles (4–7‰), with δ18O values comparable to modern and Holocene deltaic shells, and a large range of paleotemperatures (21.8–31.3 °C, including temperatures notably cooler than those measured in the modern lake: 25–31 °C), reflecting growth under significant seasonality in paleo-Omo River runoff. Oxygen isotope cycles suggest high degrees of seasonality of the paleo-Omo River runoff (or that of other major influents) into paleolake Lorenyang at ∼1.6 Ma, which may be similar to modern hydroclimate conditions. Comparison to prior datasets from nearby outcrops in the same basin suggests an increase in hydroclimate seasonality between 1.9 and 1.6 Ma. The combination of clumped isotope paleotemperature estimates from shallow water species such as E. elliptica with TEX86 measurements (derived here from previously published, contemporaneous sediment core studies from the south basin of Lake Turkana), which record temperatures near the oxycline, may provide a new approach to estimating past temperature variability along a vertical profile in lakes, thereby providing information on water column mixing regimes. Our approach greatly expands our toolkit for understanding coupled climate seasonality and variability in the Turkana Basin.

Improvements and Evaluation of the FLake Model in Dagze Co, Central Tibetan Plateau

FLake has been one of the most extensively used lake models in many studies for lake thermal structure simulations. However, due to the scarcity of lake temperature observations, its applicability and performance on lakes over the Tibetan Plateau are still poorly investigated, especially in small- to medium-sized lakes. In this study, based on water profile observations in Dagze Co, a medium-sized lake on the central Tibetan Plateau, the sensitivity of lake thermal features to three key parameters in FLake was investigated. The performance of FLake in reproducing the lake thermal features was evaluated and improved by optimizing these key parameters. The results showed that the FLake model with default parameter settings can generally reproduce the thermal features of Dagze Co, but there are still significant deviations compared to observation. The sensitive experiments demonstrated that the thermal structure of the lake obviously responds to the change in the water extinction coefficient (Kd), friction velocity (u*), and ice albedo (αice). Based on previous studies and sensitive experiments, the three key parameters were set to the optimized value, which substantially improved the performance of FLake. The values of bias and RMSE of simulated lake surface water temperature decreased from 3.08 °C and 3.62 °C to 2.0 °C and 2.48 °C after parameter optimization. The integration of a simple salinity scheme further improved the ability of FLake to reproduce the observed thermal features of Dagze Co. These results will improve our understanding of thermal processes in lakes on the Tibetan Plateau, as well as the applicability of lake models.

Reconstructing 42 Years (1979–2020) of Great Lakes Surface Temperature through a Deep Learning Approach

Accurate estimates for the lake surface temperature (LST) of the Great Lakes are critical to understanding the regional climate. Dedicated lake models of various complexity have been used to simulate LST but they suffer from noticeable biases and can be computationally expensive. Additionally, the available historical LST datasets are limited by either short temporal coverage (<30 years) or lower spatial resolution (0.25° × 0.25°). Therefore, in this study, we employed a deep learning model based on Long Short-Term Memory (LSTM) neural networks to produce a daily LST dataset for the Great Lakes that spans an unparalleled 42 years (1979–2020) at a spatial resolution of ~1 km. In our dataset, the Great Lakes are represented by ~33,000 unstructured grid points and the LSTM training incorporated the information from each grid point. The LSTM was trained with seven meteorological variables from reanalysis data as feature variables and the LST from a historical satellite-derived dataset as the target variable. The LSTM was able to capture the spatial heterogeneity of LST in the Great Lakes well and exhibited high correlation (≥0.92) and low bias (limited to ±1.5 °C) for the temporal evolution of LST during the training (1995–2020) and testing (1979–1994) periods.

DNA metabarcoding reveals spatial and temporal variation of fish eye fluke communities in lake ecosystems

Eye flukes (Diplostomidae) are diverse and abundant trematode parasites that form multi-species communities in fish with negative effects on host fitness and survival. However, the environmental factors and host-related characteristics that determine species diversity, composition, and coexistence in such communities remain poorly understood. Here, we developed a cost-effective cox1 region-specific DNA metabarcoding approach to characterize parasitic diplostomid communities in two common fish species (Eurasian perch and common roach) collected from seven temperate lakes in Estonia. We found considerable inter- and intra-lake, as well as inter-host species, variation in diplostomid communities. Sympatric host species characterization revealed that parasite communities were typically more diverse in roach than perch. Additionally, we detected five positive and two negative diplostomid species associations in roach, whereas only a single negative association was observed in perch. These results indicate that diplostomid communities in temperate lakes are complex and dynamic systems exhibiting both spatial and temporal heterogeneity. They are influenced by various environmental factors and by host-parasite and inter-parasite interactions. We expect that the described methodology facilitates ecological and biodiversity research of diplostomid parasites. It is also adaptable to other parasite groups where it could serve to improve current understanding of diversity, distribution, and interspecies interactions of other understudied taxa.

Summer dynamics of cyanobacteria in an oligo-mesotrophic temperate lake in Northwest Ireland

Despite the potential adverse consequences they can impart on biotopes, cyanobacteria are an understudied component of lake plankton communities in Ireland. This study, in summer 2019, examined cyanobacterial diversity and associated environmental variables in a lake previously impacted by algal blooms, in north-west Ireland. Vertical profiling showed that photosynthetic pigment concentrations were spatially heterogenous for the majority of the survey. However, water column homogeneity was observed towards the end of the survey, coinciding with increases in pigment concentrations. Sunshine hours, nutrient concentrations and wind speed were stable throughout the survey. Spatial homogeneity in pigments was attributed to an increase in minimal temperatures observed in the water column. PCR-DGGE analysis identified patterns in community composition, indicating a rise in cyanobacterial richness concomitant to increase in temperature and photosynthetic pigments. Band sequencing analysis identified phylotypes similar to the toxigenic species Microcystis sp. These were prominent at the end of the survey and coincided with the presence of the mcyE gene and low levels of microcystins, as indicated by real time PCR and ELISA analyses. The summer background presence of toxigenic cyanobacteria with potential bloom-forming capacity highlights the importance of annual lake cyanotoxin monitoring to inform resource management to protect human and animal health.

Somatic growth of pikeperch (Stizostedion lucioperca) in relation to variation in temperature and eutrophication in a Central Europe Lake

Global climate change has been altering freshwater ecosystems by impacting many ecological processes, including individual fish growth. Predictions of responses of local fish populations to future environmental change can draw inferences from past long-term biochronological data. In this study, we reconstructed individual growth pattern of one of the most valuable predatory species in European inland waters, pikeperch (Stizostedion lucioperca), using back-calculated length from their otoliths. Samples were collected at the Lipno reservoir (Czech Republic) between 2008 and 2020. We used linear mixed-effects models to investigate how individual state and environmental conditions affect the somatic growth of the local pikeperch population. We found that individual growth rates increased with temperature and tended to be higher when chlorophyll-a concentration was higher, and water transparency was lower. This suggests the species will likely benefit from the warmer waters predicted in future climate scenarios. However, the decreasing nutrient loading associated with efforts to curb eutrophication in Central Europe may offset these benefits. Together, these results provide a better understanding of how multiple environmental factors, directly and indirectly, influence the somatic growth of pikeperch in long term.

Estimation of evaporation from the water surface using the norm operator

Due to the lack of precipitation in recent years, some regions of Turkey are in danger of drought. This situation increases the importance of planning water resources and makes it necessary to develop water budget calculations. One of the important steps in water budget calculations is the correct estimation of the amount of evaporation. For this reason, a different method has been developed for evaporation estimation and the applicability of this developed method has been tested with the meteorological parameters of Lake Eğirdir, one of most important freshwater resources of Turkey. Eğirdir Lake is located within the borders of Isparta province in the Mediterranean Region, Turkey. Firstly, evaporation estimation models were developed by artificial neural networks (ANN) method using 490 days of air temperature, water temperature, sunshine duration, and solar radiation parameters of Lake Eğirdir. After the meteorological parameters were transformed into a dimensionless form through normalization, the norm function was applied to these parameters as a part of the modeling process. The values obtained by the function are used as input parameters in the N-ANN method. In both cases, the pan evaporation values obtained with different network structures were compared and it was seen that the N-ANN models developed with the norm operator in general gave more appropriate results.

Fire Characteristics and Hydrologic Connectivity Influence Short‐Term Responses of North Temperate Lakes to Wildfire

AbstractDespite increasing wildfires, few studies have investigated seasonal water quality responses to wildfire characteristics (e.g., burn severity) across a large number of lakes. We monitored 30 total lakes (15 burned, 15 control) monthly following the Greenwood Fire in Minnesota, USA, a lake‐rich region with historically prevalent wildfire. We found increases in median concentrations of total nitrogen (68%), total phosphorus (70%), dissolved organic carbon (127%), total suspended solids (71%), and reduced water clarity (48%) and pH (0.45) in burned lakes. Post‐wildfire responses in drainage lakes were often persistent or cumulative throughout the open‐water season, compared to isolated lakes. Total phosphorus (TP) increased linearly with watershed high‐severity burns, and shoreline high‐severity burns explained more variation in TP than lake morphometry and watershed variables. Post‐wildfire chlorophyll‐a responses were nonsignificant and inconsistent, possibly due to light limitation. Our results suggest that increasing wildfires have significant potential to affect water quality of inland lakes.

A mixed-species shoal including fewer heterospecifics is preferred by jack mackerel Trachurus japonicus juveniles

Mixed-species shoals of fishes were reported from various environments such as coral reefs and temperate lakes. The driving mechanism of forming mixed-species shoal can be either haphazard or a preferential choice by an individual. Here, we tested if jack mackerel Trachurus japonicus, a temperate marine pelagic fish, could choose a shoal composition using vision based on a choice experiment. Shoal preference of jack mackerel juveniles was evaluated by presenting shoals comprising one to four heterospecifics (half-lined cardinal Ostorhinchus semilineatus) out of four shoal members to the focal fish. When both conspecific and heterospecific shoals were presented to a single jack mackerel, the focal fish showed a preference for the conspecific rather than heterospecific shoal, indicating that they can choose a conspecific shoal based on the visual information. However, when a focal fish encountered both conspecific and mixed-species shoals including fewer heterospecifics (one out of four individuals), the latter was preferred. The result implies that jack mackerel can judge a preferable composition of shoal using visual information. The inclusion of fewer heterospecifics may be exploiting oddity effects, whereby minority species are exposed to relatively high vulnerability to predators, as well as resulting in reduced competition for food while maintaining predator vigilance in a shoal.

Ice bottom evolution derived from thermistor string-based ice mass balance buoy observations

ABSTRACT Digital information on sea ice extent, thickness, volume, and distribution is crucial for understanding Earth's climate system. The Snow and Ice Mass Balance Apparatus (SIMBA) is used to determine snow and ice temperatures in Arctic, Antarctic, ice-covered seas, and boreal lakes. Snow depth and ice thickness are derived from SIMBA temperature regimes (SIMBA_ET and SIMBA_HT). In warm conditions, SIMBA_ET temperature-based ice thickness may have errors due to the isothermal vertical profile. SIMBA_HT provides a visible ice-bottom interface for manual quantification. We propose an unmanned approach, combining neural networks, wavelet analysis, and Kalman filtering (NWK), to mathematically establish NWK and retrieve ice bottoms from various SIMBA_HT datasets. In the Arctic, NWK-derived total thickness showed a bias range of −5.64 cm to 4.01 cm and a correlation coefficient of 95%−99%. For Baltic Sea ice, values ranged from 1.31 cm to 2.41 cm (88%−98% correlation), and for boreal lake ice, −0.7 cm to 2.6 cm (75%−83% correlation). During ice growth, thermal equilibrium, and melting, the bias varied from −3.93 cm to 2.37 cm, −1.92 cm to 0.04 cm, and −4.90 cm to 3.96 cm, with correlation coefficients of 76%−99%. These results demonstrate NWK's robustness in retrieving ice bottom evolution in different water environments.

Nitrogen mass balance and uptake velocity for eutrophic reservoirs in the Brazilian semiarid region.

The nitrogen (N) cycle from the catchment to the downstream reservoir is complex, particularly the quantification of N losses. However, in order to assess the nitrogen impact in a reservoir ecosystem, simplified models may be applicable regarding the TN load production and the magnitude of lake TN removal. This study presented a methodology to perform and validate a TN mass balance to further calibrate a simplified coefficient for TN losses (vf.) in 29 tropical semiarid reservoirs. The study reservoirs were highly productive ecosystems with an average total nitrogen (TN) concentration, accounting for all measurements in all reservoirs, ranging from 0.59 to 3.84 mg L-1. Regarding the production of TN load, the median values ranged from 4.35 to 2,499.43 t year-1 with median of 80.34 t year-1. The TN loads were estimated through an annual mass balance over a 24-year period. The median of the estimates was compared with reference values obtained by using the export modelling coefficient. The correlation between the median estimated and reference loads resulted in satisfactory agreement (r2 0.88) and reinforced the reliability of the mass balance alternative. From the validated TN loads, the TN uptake velocity (vf) was estimated for all reservoirs (44.9 ± 20.1 m year-1) and could be described as a general function of the water residence time. The reservoirs of the study region have demonstrated higher vf than temperate lakes and reservoirs and similar vf with Latin America/Caribbean ones. As expected, reservoirs of warmer climates tend to present intensified N loss processes compared to lakes and reservoirs of temperate regions. The methodology proposed in the present study can be used to potentially improve water quality management in tropical semiarid reservoirs.

Increasing water temperature of the largest freshwater lake on the Mediterranean islands as an indicator of global warming

Global warming has been monitored for many years. The increase in air temperature and changes in the distribution and frequency of high temperatures are recorded continually. Lakes are one of the important water resources for aquatic ecosystems and water supply, which are significantly affected by global warming. The increase in lake water temperature increases the evaporation from the free lake surface, lowering the lake level, and changes the water quality. In the last few decades, analysis of changes in lake water temperature has been increasing. In situ measurements of water temperature in Vrana Lake on Cres island (Croatia), the largest freshwater lake on the Mediterranean islands, were analysed over 43 years. The results showed that the mean annual lake surface water temperature (LSWT) increased by 0.47 °C decade-1 (p < 0.0001). The increase in the mean annual lake summer surface water temperature (July–September) was 0.44 °C decade-1 (p < 0.0001), and the maximum annual LSWT was 0.56 °C decade-1 (p < 0.0001). All these amounts are in accordance with the published data on the increase in water temperature in the investigated European lakes. The number of days with LSWT higher than 25 °C increased by almost 9 d decade-1. An increase in the minimum LSWT (0.17 °C decade-1) corresponding to isothermal conditions was also determined but was not statistically significant. The minimum mean monthly LSWT increased by 0.36 °C decade-1 (p < 0.0001). Because the increase in water temperature can negatively affect the lake's ecosystem, and become a threat to safe water supply; LSWT, thermal stratification and evaporation should be continuously monitored. The impacts of climate warming on the lake stratification and aquatic ecosystems need to be further investigated.

Agricultural land use and morphometry explain substantial variation in nutrient and ion concentrations in lakes across Canada

Declines in freshwater quality resulting from anthropogenic nutrient input remain a persistent issue worldwide. Yet, we still have a limited understanding of the magnitude and scale at which most lakes have been affected by human activities, namely Land Use/Land Cover (LULC) alterations. In response, the NSERC Canadian Lake Pulse Network has compiled the first nationwide systematic database of lake quality metrics by surveying 664 lakes across 12 ecozones over 3 years. To assess the influence of catchment development on water quality and its spatial variation, we built generally additive models and multivariate regressions to quantify the association between watershed LULC and lake temperature, Secchi depth, as well as chlorophyll- a, limiting nutrient, and ion concentrations. We found that agricultural and urban land use explained the greatest proportion of variation in water quality among LULC categories ( R2 = 0.20–0.29). Overall, our study highlights that drivers of water quality are similar across regions; however, baseline conditions vary, so freshwater ecosystem management strategies must consider their geographic context to better predict where water quality thresholds will be surpassed.

Size-Pattern and Larval-Length–Mass Relationships for the Most Common Chironomid Taxa in the Deep Subalpine Lake Maggiore

For the first time, the size spectra of 28 chironomid genera/species are reported for the most common chironomid taxa in the deep subalpine Lake Maggiore (northwestern Italy). Species-specific length–mass regression models were developed to predict the dry masses of the larval stages of Cladotanytarsus sp., Cryptochironomus sp., Polypedilum bicrenatum, P. nubeculosum, and Stictochironomus pictulus. The predicted dry-mass values differed by less than 20% from the measured values, suggesting that these original equations will be important in chironomid production studies. Regressions at the subfamily level were also developed for case identification at the genus or species level, which is difficult to obtain. The chironomid weights were determined directly and a dry/wet-weight-conversion ratio was estimated. The results were consistent with previously reported results. The relationships between the dry masses and the body lengths were compared with published data for different types of lake all over the world. We found that regression models for other freshwater environments somehow differed from those in Lake Maggiore, albeit slightly. The combination of diversity-based and trait-based approaches improves our knowledge about chironomids and our understanding of the effects of global environmental changes on freshwater biota. This first collection of trait data on summer–autumn chironomid assemblages in a temperate subalpine lake is a valuable contribution to the European trait database. The taxonomic diversity and abundance of chironomids were uploaded for open access on the GBIF platform.

Contrasting dissolved organic matter biodegradation and bacterial cytometric features in oligotrophic and ultraoligotrophic Patagonian lakes

Abstract Biodegradation process of dissolved organic matter (DOM) could be affected by its concentration and quality. Two biodegradation experiments were conducted in two contrasting seasons in two oligotrophic and one ultraoligotrophic temperate lakes, which comprise a natural gradient of dissolved organic carbon (DOC) concentration and quality (including lakes of &amp;lt; 83.33 μM). We examined associations between biodegradation and bacterial cytometric descriptors (i.e. abundance, DNA relative content, etc.) and with different DOM characteristics. The biolabile DOC (BDOC) was higher in shallow oligotrophic lakes, which displayed higher DOC concentration than the deep ultraoligotrophic one. The BDOC was mainly relatable not only to DOC concentration but also with DOM quality [fluorescent terrestrial-humic component normalized by DOC (C2:DOC), lignin content (a*350) and biological index]. We found a positive association between biodegradation process and high nucleic acid–content bacterial group. The bacterioplankton cytometric features were shaped by DOM concentration and quality along the biodegradation process. We concluded that in oligotrophic lakes, DOC concentration was the main driver of BDOC, whereas in ultraoligotrophic lakes, DOM quality played a more central role. This study contributes to better understand the biodegradation process in pristine low-DOC lakes with natural variation in allochthonous DOM inputs and with implications in the biogeochemical cycles.

Daily responses of the planktonic food web to environmental dynamics in the vegetated littoral zone of a large shallow lake

Littoral zones are the most productive areas of shallow lakes and make important contributions to energy transfer to higher trophic levels in aquatic ecosystems. Great habitat heterogeneity characterizes the littoral ecosystems, often encompassing macrophyte covered areas that provide microhabitats with diverse structural complexity, and several effects over the structure and function of biological communities. The effects of macrophytes on trophic interactions are more complex in subtropical lakes than in temperate lakes. The relationships between planktonic food web components and the effects of a highly dynamic environment in structuring plankton communities were studied in a large subtropical shallow lake. The study was conducted for twenty-five consecutive days in the summer of 2016 at two sites (Station 1 and Station 2) in the well-developed littoral zone of Lake Mangueira hosting different plant life forms. Strong spatial variation between sampling stations was evidenced in the density of most of the communities, with the highest means of bacterioplankton, phytoplankton, and ciliates density being recorded at the station surrounded mainly by submerged macrophytes (Station 1). These plants particularly modify microhabitat complexity by increasing the availability and functional diversity of niches. Furthermore, submerged macrophytes tend to accumulate more periphyton biomass, a quality food resource for many consumers. Important grazing relationships, nutrient demands, and trophic structure were assessed through carbon biomass of the communities. Phytoplankton accounted for a greater proportion of the entire plankton community than bacteria, while zooplankton had low carbon biomass of crustaceans and a high dominance of ciliates and rotifers, with a greater grazing impact on bacterioplankton than on phytoplankton. According to RDA and multiple-regression analysis, nutrients and humic substances were the main predictors of variability in the littoral food web components over a short-sampling interval. The carbon biomass of bacteria and metazooplankton were both positively related to humic substances and nutrients at Station 1, as well as the biomass ratio of metazooplankton to phytoplankton and metazooplankton to ciliates. This suggests that humic substances have been metabolized by bacteria and transferred to higher trophic levels through predation. On the other hand, humic substances negatively affected the carbon biomass of bacteria and cyanobacteria at Station 2, suggesting a mostly refractory DOC around the emergent plants. Results indicate that despite the greater importance of bacterial biomass in the energy transfer through zooplankton predation, the efficiency of carbon transfer in algal and bacteria-based food webs was both very low. The effects of macrophytes on the quantity and/or quality of nutrients and substrates for bacteria uptake and phytoplankton requirements, explained the spatial variability of plankton food web components, even over the short distance between stations, as well as the inefficient microbial loop found in the littoral zone inhabited by macrophytes.