Large Eutrophic Lake Research Articles

Atmospheric CO2 absorption and counteraction by CH4 emission across contrasting habitats in a large eutrophic lake

Lakes are a crucial component of global carbon cycling and play a key role in the global CO2 and CH4 budgets. Intensified anthropogenic activity contributes to eutrophication, and reduces macrophytes while increasing phytoplankton in shallow lakes. However, the information on how the CO2 and CH4 fluxes at water–air interface temporally varies across habitats dominated by various primary producers in lakes and how CH4 emission counteracts CO2 adsorption is limited. In this study, in situ fluxes of CO2 and CH4 were measured monthly for one year at four sites in Lake Taihu, China. These sites had contrasting habitats dominated by high-density phytoplankton, low-density phytoplankton, floating-leaved macrophytes, and submerged macrophytes. We found that the CO2 fluxes ranged from − 439 ± 385 to − 106 ± 348μmol m−2h−1 and the CH4 fluxes ranged from 1.96 ± 3.79 to 10.7 ± 14.8μmol m−2h−1. The fluxes of CO2 and CH4 were mainly regulated by water pH, phosphorus levels, and sediment organic carbon. All four habitats acted as sinks of atmospheric CO2 and sources of atmospheric CH4, and the habitats with high-density phytoplankton showed the highest CO2 absorption and strongest CH4 emission. Generally, the CH4 emission counteracted 7–69 % of the atmospheric CO2 absorption in the four sites. These results collectively revealed that in a large, shallow eutrophic lake, habitats dominated by various primary producers consistently adsorb atmospheric CO2, even being counteracted by CH4 emission. These findings provide valuable insights for understanding carbon cycling and CO2 and CH4 dynamics across the water–air interface in shallow lakes.

Lacustrine groundwater discharge-derived carbon and nitrogen to regulate biogeochemical processes as revealed by stable isotope signals in a large shallow eutrophic lake

Eutrophic shallow lakes are hotspots of carbon (C) and nitrogen (N) accumulation and transformation, and are increasingly recognized as important sources of greenhouse gases (GHGs: CO2, CH4 and N2O). Lacustrine groundwater discharge (LGD) is a crucial component of the water budget and terrestrial material delivery for lakes, but its interplays with intrinsic CN biogeochemical processes remain less tackled. In this study, C and N ingredients and multiple stable isotopes (δ2H, δ18O, δ13C, and δ15N) were measured seasonally in groundwater, river water and lake water of a large eutrophic shallow lake in eastern China. The results revealed that groundwater is enriched with various forms of C and N that have similar sources and pathways as surface water in the lake and rivers. The isotope balance model also indicated that LGD derived C and N contribute significantly to lake inventories in addition to river runoff. These allochthonous C and N provide extra substrates for related biogeochemical processes, such as algae proliferation, organic matter degradation, methanogenesis and denitrification. Simultaneously, the excess oxygen consumption leads to depletion and hypoxia in the lake, further facilitating the processes of methanogenesis and denitrification. LGD functions not only as an external source of C and N that directly increases GHG saturations, but also as a mediator of internal CN pathways, which significantly affect hypoxia formation, GHG productions and emissions in the eutrophic lake. This study highlights the unrevealed potential regulation of LGD on biogeochemical processes in the eutrophic lake, and underscores the need for its consideration in environmental and ecological studies of lakes both regionally and globally.

Significant diurnal variations in nitrous oxide (N2O) emissions from two contrasting habitats in a large eutrophic lake (Lake Taihu, China)

Algae and macrophytes in lake ecosystems regulate nitrous oxide (N2O) emissions from eutrophic lakes. However, knowledge of diurnal N2O emission patterns from different habitats remains limited. To understand the diurnal patterns and driving mechanisms of N2O emissions from contrasting habitats, continuous in situ observations (72 h) of N2O fluxes from an algae-dominated zone (ADZ) and reed-dominated zone (RDZ) in Lake Taihu were conducted using the Floating Chamber method. The results showed average N2O emission fluxes of 0.15 ± 0.06 and 0.02 ± 0.04 μmol m−2 h−1 in the ADZ and RDZ in autumn, respectively. The significantly higher (p < 0.05) N2O fluxes in the ADZ were mainly attributed to differences in nitrogen (N) levels. The results also showed significant diurnal differences (p < 0.05) in the N2O emission fluxes within the ADZ and RDZ, and daytime fluxes were significantly higher (p < 0.05) than nighttime fluxes. The statistical results indicated that N2O emissions from the ADZ were mainly driven by diurnal variations in N loading and the dissolved oxygen (DO) concentration, and those from the RDZ were more influenced by DO, redox potential, and pH. Finally, we determined the proper time for routine monitoring of N2O flux in the two habitats. Our results highlight the importance of considering diverse habitats and diurnal variations when estimating N2O budgets at a whole-lake scale.

Temporal shifts in the phytoplankton network in a large eutrophic shallow freshwater lake subjected to major environmental changes due to human interventions

Phytoplankton communities are crucial components of aquatic ecosystems, and since they are highly interactive, they always form complex networks. Yet, our understanding of how interactive phytoplankton networks vary through time under changing environmental conditions is limited. Using a 29-year (339 months) long-term dataset on Lake Taihu, China, we constructed a temporal network comprising monthly sub-networks using “extended Local Similarity Analysis” and assessed how eutrophication, climate change, and restoration efforts influenced the temporal dynamics of network complexity and stability. The network architecture of phytoplankton showed strong dynamic changes with varying environments. Our results revealed cascading effects of eutrophication and climate change on phytoplankton network stability via changes in network complexity. The network stability of phytoplankton increased with average degree, modularity, and nestedness and decreased with connectance. Eutrophication (increasing nitrogen) stabilized the phytoplankton network, mainly by increasing its average degree, while climate change, i.e., warming and decreasing wind speed enhanced its stability by increasing the cohesion of phytoplankton communities directly and by decreasing the connectance of network indirectly. A remarkable shift and a major decrease in the temporal dynamics of phytoplankton network complexity (average degree, nestedness) and stability (robustness, persistence) were detected after 2007 when numerous eutrophication mitigation efforts (not all successful) were implemented, leading to simplified phytoplankton networks and reduced stability. Our findings provide new insights into the organization of phytoplankton networks under eutrophication (or re-oligotrophication) and climate change in subtropical shallow lakes.

A hybrid algorithm for estimating total nitrogen from a large eutrophic plateau lake using Orbita hyperspectral (OHS) satellite imagery

Total nitrogen concentration (CTN) enrichment is the primary cause of natural water eutrophication. Accurately estimating CTN and its spatiotemporal dynamics is crucial for formulating monitoring and control measures to alleviate lake eutrophication. A hybrid model was proposed for estimating CTN in optically complex inland waters by incorporating the relationship between CTN and water optical active components for Zhuhai-1 Orbita hyperspectral (OHS) imagery. Compared with other semi-analytical algorithms, the re-adjusted reference wavelength QAA716 shows the best performance in aph(λ) retrieval. The hybrid model for CTN estimation achieves an root mean square deviation (RMSD) of 0.20 mg/L, a mean absolute percentage deviation (MAPD) of 6.96 %, and a unbiased mean absolute percentage deviation (UMAPD) of 6.96 %, with aph(569) accuracy exerting the greatest influence. Ground-satellite synchronous validation demonstrates robust performance, with an RMSD of 0.28 mg/L, a MAPD of 14.49 %, and a UMAPD of 14.92 %. The hybrid model was applied to OHS observations of Lake Dianchi from April 2019 to September 2021. The analysis revealed a generally decreasing trend in CTN during this timeframe. The above results demonstrate that the robustness and applicability of the proposed CTN hybrid model for inland waters with complex optical properties. Furthermore, satellite-based data products provide valuable information for formulating lake management strategies.

Sediment Phosphorus Supply and Availability in the Algal-Dominated Zone of a Large Eutrophic Lake (Lake Taihu)

Sediment Phosphorus Supply and Availability in the Algal-Dominated Zone of a Large Eutrophic Lake (Lake Taihu)

Effects of habitat regime type on fish diversity in a large eutrophic lake

Effects of habitat regime type on fish diversity in a large eutrophic lake

The collapse and re-establishment of stability regulate the gradual transition of bacterial communities from macrophytes- to phytoplankton-dominated types in a large eutrophic lake.

Eutrophic lakes often exhibit two alternative types: macrophytes-dominated (MD) and phytoplankton-dominated (PD). However, the nature of bacterial community types that whether the transition from the MD to the PD types occurs in a gradual or abrupt manner remains hotly debated. Further, the theoretical recognition that stability regulates the transition of bacterial community types remains qualitative. To address these issues, we divided the transition of bacterial communities along a trophic gradient into 12 successional stages, ranging from the MD to the PD types. Results showed that 12 states were clustered into three distinct regimes: MD type, intermediate transitional type and PD type. Bacterial communities were not different between consecutive stages, suggesting that the transition of alternative types occurs in a continuous gradient. At the same time, the stability of bacterial communities was significantly lower in the intermediate type than in the MD or PD types, highlighting that the collapse and re-establishment of community stability regulate the transition. Further, our results showed that the high complexity of taxon interactions and strong stochastic processes disrupt the stability. Ultimately, this study enables deeper insights into understanding the alternative types of microbial communities in the view of community stability.

Quantification of Diffusive Methane Emissions from a Large Eutrophic Lake with Satellite Imagery.

Lakes are major emitters of methane (CH4); however, a longstanding challenge with quantifying the magnitude of emissions remains as a result of large spatial and temporal variability. This study was designed to address the issue using satellite remote sensing with the advantages of spatial coverage and temporal resolution. Using Aqua/MODIS imagery (2003-2020) and in situ measured data (2011-2017) in eutrophic Lake Taihu, we compared the performance of eight machine learning models to predict diffusive CH4 emissions and found that the random forest (RF) model achieved the best fitting accuracy (R2 = 0.65 and mean relative error = 21%). On the basis of input satellite variables (chlorophyll a, water surface temperature, diffuse attenuation coefficient, and photosynthetically active radiation), we assessed how and why they help predict the CH4 emissions with the RF model. Overall, these variables mechanistically controlled the emissions, leading to the model capturing well the variability of diffusive CH4 emissions from the lake. Additionally, we found climate warming and associated algal blooms boosted the long-term increase in the emissions via reconstructing historical (2003-2020) daily time series of CH4 emissions. This study demonstrates the great potential of satellites to map lake CH4 emissions by providing spatiotemporal continuous data, with new and timely insights into accurately understanding the magnitude of aquatic greenhouse gas emissions.

Synchronism of sediment erosion and deposition processes during high-turbidity events in a large shallow lake

High-turbidity events (HTEs) frequently occur in shallow lakes and can deeply influence lake ecosystems. However, the processes of sediment erosion and deposition are not fully understood. To investigate these processes, two investigative campaigns that integrate bed sediment measurements, sediment settling experiments, in-situ observations, or a hydrodynamics-sediment model were conducted to quantitatively study wind-induced HTEs in Lake Taihu, China. Cohesive sediments were massively entrained from the lakebed by wind waves when the wind speed exceeded its critical value of 7 m s−1, as estimated by water depth, triggering HTEs with turbidity waves of > 100 nephelometric turbidity units. The suspended sediment concentration was the net sediment flux of erosion (average: 5.9 mg m−2 s−1) and deposition (average: 5.5 mg m−2 s−1), which occurred synchronously for most of the HTEs and resulted in high temporal variation in suspended sediment concentration. This synchronism was determined by the critical erosional stress of lakebed sediments, which was spatially heterogeneous (0.017–0.055 N m−2) in a large lake. Equations for erosion and deposition processes were derived following the investigative campaigns and used to develop a cohesive sediment transport model for simulating HTEs in Lake Taihu. Simulations indicate that the synchronism of sediment erosion and deposition led to a near-lakebed turbid water layer during an HTE, which sustained the sediment lutocline in Lake Taihu. Further investigation should be conducted on the role of the near-lakebed turbid water layer during endogenous pollution in large eutrophic lakes.

Environmental heterogeneity affecting spatial distribution of phytoplankton community structure and functional groups in a large eutrophic lake, Lake Chaohu, China

The growth and development of phytoplankton are influenced by physico-chemical parameters, which can also affect the spatial distribution of phytoplankton community structure. However, it is unclear whether environmental heterogeneity caused by multiple physico-chemical factors can affect the spatial distribution of phytoplankton and its functional groups. In this study, we investigated the seasonal variation and spatial distribution of phytoplankton community structure and its relationships with environmental factors in Lake Chaohu from August 2020 to July 2021. We recorded a total of 190 species from 8 phyla, which were divided into 30 functional groups, including 13 dominating functional groups. The average annual phytoplankton density and biomass were (5.46 ± 7.17) × 107 cells/L and 4.80 ± 4.61 mg/L, respectively. The density and biomass of phytoplankton were higher in summer ((14.64 ± 20.34) × 107 cells/L, 10.61 ± 13.16 mg/L) and autumn ((6.79 ± 3.97) × 107 cells/L, 5.57 ± 2.40 mg/L), with the M and H2 of dominant functional groups. The dominant functional groups were N, C, D, J, MP, H2, and M in spring, whereas functional groups C, N, T, and Y dominated in winter. The distribution of phytoplankton community structure and dominant functional groups exhibited significant spatial heterogeneity in the lake, which was consistent with the environmental heterogeneity of the lake and could be classified into four locations. Location I had higher phytoplankton density and biomass than the other three locations. Additionally, dominant functional groups M, C, and H2 were present throughout the lake, and all 13 dominant functional groups were observed in Location II. Our findings suggest that environmental heterogeneity is a key factor influencing the spatial distribution of phytoplankton functional groups in Lake Chaohu.

Hydrodynamic effects on the ability of bottom traps to capture nutrient-rich sediments in shallow eutrophic lakes

Hydrodynamics are the key factor influencing sediment resuspension, transport and nutrient release in large shallow lakes. However, the hydrodynamic responses of bottom traps during pollutant capture remain unclear. In this study, a large eutrophic shallow lake was selected to carry out a field test of deep traps at the lake bottom. Based on observations of the lake current around the trap, the sedimentation rate of the particles in the trap and the nutrient content of the captured sediments, combined with the numerical simulation of the waves outside the trap, the effects of lake currents and waves on the sediment deposition in the traps were studied, and the response of the nutrient content of the sediments captured in the deep traps to the changes in lake currents and waves was analyzed. The results showed that the strong hydrodynamic force significantly promoted sediment deposition in the trap and enhanced the ability of the trap to capture sediments with high nutrient contents. The influences of waves and lake currents on the bottom trap capture of polluted sediments varied among different periods. Waves played the leading role in winter and spring, accelerating sediment capture in the bottom traps near the southern shore of eastern Lake Chaohu during this period. In summer, the lake current was the main dynamic factor contributing to the rapid deposition of particulate matter and the capture of sediments with high nutrient contents in the bottom traps of western Lake Chaohu. The multiple stepwise linear regression model based on lake current and wave data explained 37.6 % of the sediment deposition in the trap, and the model built for a single bottom trap explained more than 80 % of the deposition. After correcting the sediment deposition thickness in the trap by considering the water content of the sediment, the quantitative relation yield better inversion results for the sediment deposition process, and different thicknesses in the bottom trap were linked to different sediment deposition periods. According to the hydrodynamic strength in 2020, the thickness of the highly contaminated sediments captured by traps CC1-CC5 was calculated to be 1.09–1.93 m, and the corresponding TN and TP were 26.66–68.53 kg and 6.84–19.89 kg, respectively. This study provides a scientific analysis and guidance for the evaluation of endogenous nutrients captured by lake bottom trap methods.

Patterns in sources and forms of nitrogen in a large eutrophic lake during a cyanobacterial harmful algal bloom

AbstractWestern Lake Erie experiences an annual, toxic cyanobacterial harmful algal bloom (cyanoHAB), primarily caused by excess anthropogenic inputs of nitrogen (N) and phosphorous (P). Because the non‐N fixing cyanobacteria species Microcystis dominates these blooms, N availability is hypothesized to play a central role in cyanoHAB progression, as well as production of the N‐rich toxin microcystin. Many previous studies focused on nitrate because it is the most abundant N substrate during bloom initiation. However, recent work implicated reduced N substrates like ammonium and dissolved organic N (DON) in promoting greater bloom biomass and longevity. To examine the relative importance of oxidized and reduced N substrates to phytoplankton during different bloom stages, we measured concentrations and natural abundance δ15N isotope values of dissolved N substrates and phytoplankton biomass throughout the entirety of the 2020 cyanoHAB in Western Lake Erie. The results provide the first data on DON dynamics and composition in Western Lake Erie, and suggest that phytoplankton, including Microcystis, likely relied on N regenerated from the DON pool in later bloom stages. In addition, the stable isotope data confirm the importance of nitrate delivered via the Maumee River to cyanobacterial growth and toxin production.

Real-Time Identification of Cyanobacteria Blooms in Lakeshore Zone Using Camera and Semantic Segmentation: A Case Study of Lake Chaohu (Eastern China)

The surface water in the lakeshore zone is the primary area where cyanobacteria bloom floats intensively. In lake water environment monitoring, it has become pressing to accurately identify the distribution and accumulation coverage area of cyanobacteria blooms in the surface water of the lakeshore zone. This study proposes a real-time and dynamic monitoring technology for cyanobacteria blooms in surface water using a shore-based camera monitoring network. The specific work is as follows: Chaohu Lake, a large eutrophic lake in China, is selected as the research object. The multithreading technology is used to dynamically obtain the hourly video images of 43 cameras around Chaohu Lake. The semantic segmentation method is used to identify the cyanobacteria blooms in the video images, calculate the coverage of cyanobacteria blooms, and draw the spatial distribution map of cyanobacteria blooms in the lakeshore zone of Chaohu Lake. To improve the accuracy of cyanobacteria blooms recognition, we use the ResNet-50 network to integrate three semantic segmentation models, namely FCN, U-net, and DeeplabV3+. By comparing the cyanobacteria blooms results identified by the three methods, it is found that the boundary of the cyanobacteria blooms results identified by DeeplabV3+(ResNet-50) is clear, which is more consistent with the real spatial information of the distribution of cyanobacteria blooms and is more suitable for monitoring the hourly dynamic changes of cyanobacteria blooms in the Chaohu Lake lakeshore zone. The results demonstrated that the time requirement of monitoring cyanobacteria blooms in real time on an hourly basis could be met by utilizing technology that uses multiple threads. The OA (Overall Accuracy), MPA (Mean Pixel Accuracy), IOU (Intersection Over Union) of cyanobacteria blooms, and the IOU of water values of the DeeplabV3+(ResNet-50) were the highest, which were 0.83, 0.82, 0.71, and 0.74, and the RMSE between the predicted and real cyanobacterial blooms coverage of 43 cameras was 6.65%. The above values show that DeeplabV3+(ResNet-50) is this technology’s most suitable semantic segmentation model. This technique can provide technical support for the scientific development of a cyanobacteria blooms management plan in the lakeshore zone of Chaohu Lake by calculating the coverage area of cyanobacteria blooms and drawing the spatial distribution map of cyanobacteria blooms in the lakeshore zone.

Large Methane Emission from the River Inlet Region of Eutrophic Lake: A Case Study of Lake Taihu

Lakes are important natural sources of atmospheric methane (CH4), which should be considered in global CH4 budget estimations. However, the CH4 emissions from lakes can be highly variable, and the emissions from the river inlet region were less studied, which seriously hamper our understanding of CH4 budget estimates of lakes. Here, field measurements from over six years (2012 to 2017) at Lake Taihu, a large eutrophic shallow lake with a complicated river network, were conducted to address the issue. Results show that the river inlet region of the lake was a hot spot of CH4 emission. The CH4 emission at the river inlet region with an annual mean value of 0.183 mmol m−2 d−1 was seven times higher than that at pelagic region (0.028 mmol m−2 d−1). Peak CH4 emission occurred in warm seasons, and the lowest in cold seasons at the pelagic region, but peak emission occurred in cold seasons at the river inlet region. The seasonal CH4 emission at the pelagic region can be explained by water temperature; however, less temperature dependency of CH4 emission at the river inlet region was found. The variability of CH4 emission was linked to pollution loadings, and CH4-rich water in the inflowing river likely sustained the large CH4 emission of river inlet region.

Rainstorms drive export of aromatic and concurrent bio-labile organic matter to a large eutrophic lake and its major tributaries

Lakes are hotspots for global carbon cycling, yet few studies have explored how rainstorms alter the flux, composition, and bio-lability of dissolved organic matter (DOM) in inflowing rivers using high-frequency monitoring. We conducted extensive campaigns in the watershed of Lake Taihu and made daily observations for three years in its two largest inflowing tributaries, River Dapu and River Yincun. We found higher DOC, bio-labile DOC (BDOC), and specific UV absorbance (SUVA254) levels in the northwestern inflowing regions compared with the remaining lake regions. DOC and BDOC increased during rainstorms in River Dapu, and DOC declined due to local dilution and BDOC increased during rainstorms in River Yincun. We found that rainstorms resulted in increased DOM absorbance a350, SUVA254, and humification index (HIX) and enhanced percentages of humic-like fluorescent components, %polycyclic condensed aromatic and %polyphenolic compounds as revealed from ultrahigh-resolution mass spectrometry (FT-ICR MS), while spectral slope (S275-295) and the percentages of protein-like C1 and C3 declined during rainstorms compared with other seasons. This can be explained by a combined flushing of catchment soil organic matter and household effluents. The annual inflows of DOC and BDOC to Lake Taihu were 1.15 ± 0.18 × 104 t C yr−1 and 0.23 ± 0.06 × 104 t C yr−1 from River Dapu and 2.92 ± 0.42 × 103 t C yr−1 and 0.53 ± 0.07 × 103 t C yr−1 from River Yincun, respectively, and the fluxes of DOC and BDOC from both rivers increased during rainstorms. We found an elevated frequency of heavy rainfall and rainstorms in the lake watershed during the past six decades. We conclude that an elevated input of terrestrial organic-rich DOM with concurrent high aromaticity and high bio-lability from inflowing rivers is likely to occur in a future wetter climate.

Contrasting diversity patterns and community assembly mechanisms of bacterioplankton among different aquatic habitats in Lake Taihu, a large eutrophic shallow lake in China

Eutrophication leads to the degradation of lake habitat types from macrophyte-dominated habitats (MDH) to algae-dominated habitats (ADH), which is a common environmental problem faced by many lakes. However, the variations in diversities and community assembly processes of bacterioplankton in the process of lake eutrophication have not been thoroughly elucidated. Here, we contrasted bacterial diversity patterns and processes of community assembly among ADH, MDH, and other habitats (OH) of Lake Taihu, a large shallow eutrophic lake in China with strong wind-induced disturbances. We found that the bacterial diversity patterns and potential functions between ADH and MDH were significantly different. Moreover, the contributions of purely environmental variables to the bacterial diversity patterns of all habitat types were much higher than those of spatial variables. However, the relative importance of stochasticity in the bacterial community assembly of each habitat type was much higher than that of determinism. Intriguingly, ‘undominated’ stochastic processes shape the diversity patterns of bacterioplankton in ADH, MDH, and OH of Lake Taihu. These findings demonstrate that the degradation of lake habitats caused by eutrophication can profoundly change the diversity and potential function patterns of the bacterioplankton community in lake ecosystems. Although the distinct diversity patterns of the bacterioplankton among the different aquatic habitats in Lake Taihu can be affected by deterministic processes (local environmental variables), they were dominated by stochastic processes (drift). Our study confirms that strong, disordered, wind-induced disturbances in shallow lakes could lead to strong hydrologic mixing, thus increasing the randomness of bacterial community assembly in each habitat.

Characterization of internal phosphorus loading in the sediment of a large eutrophic lake (Lake Taihu, China)

Lake Taihu suffers from severe algal blooms every year, which is attributed primarily to the release of sediment phosphorus (P), namely the internal P loading. However, the overall internal P loading and the P hotspots in sediment have not been fully studied. This paper presents several methods, including sequential P extraction, the use of diffusive gradient in thin film (DGT), and intact core incubation to give a detailed investigation of sediment internal P loading as well as its roles in algal dominated zones (ADZs) and grass dominated zones (GDZs) in Lake Taihu. Sediment microbial composition was also analyzed to investigate its relationship with P fractions. The results indicate that the total P and the mobile P fraction in the ADZ sediments are generally higher than those of the GDZ sediments. The percentage of sediment mobile P to TP is similar to the mobile P in their distributions. In contrast, calcium bound P accounts for most of the TP in GDZ, while mobile P contributes the most to TP in ADZ. Overall, sediment can release 256 tons of TP and 217 tons of soluble reactive phosphorus (SRP) over a period of six months in the warmer seasons. Similarly, a high concentration of DGT-measured P was observed in ADZs that are recognized as P hotspots in Lake Taihu. Sediments in ADZ and GDZ was dominated by the bacteria Firmicutes and Proteobacteria, respectively and which were closely related with mobile P and calcium bound P in sediment, respectively. GZD seems to be able to retain more P in sediments, thereby reducing its contribution to of internal P loading. These results indicate that the difference in sediment composition between ADZ and GDZ affects their roles in sediment internal P loading, therefore, different management strategies should be used to combat sediment internal P loads in the two zones.

Benefit-risk assessment of consuming fish and shrimp from a large eutrophic freshwater lake, China

In this study, contents of fatty acids, essential trace elements (Fe, I, Zn, Se, Cu, Mo, Cr) and non-essential trace elements (As, Cd, Hg, Ni, Pb) were quantified in fish and shrimp species from large eutrophic Chaohu Lake, southeastern China. Total fat acids in the samples were 0.10–2.41 g/100 g, in which DHA+EPA were 0.03–0.24 g/100 g. Mean content of essential trace elements (μg/g) in fish and shrimp species followed the order of Fe (10.3)>Cu (9.9)>Zn (7.7)>Cr (1.42)>Se (0.337)>Mo (0.285)>I (0.023). The As, Cd, Hg, Ni, Pb content in the samples were <4.5–218, 14–97, 3–47, 4200–11300 and 144–1130 μg/kg, respectively, which was below the national maximum limit with the exception of Pb content in several samples. Benefit-risk assessment for fish and shrimp consumption was conducted on the basis of nutrients and contaminants. To achieve the recommended 250 mg of DHA+EPA daily intake, results of benefit-risk assessment indicated that fish and shrimp consumption can be major source of Se, Cu, Mo and Cr intake, whereas fish consumption was potential non-carcinogenic risk exposure for Ni. Benefit-risk assessment contributed to the identification of main benefits and hazards of freshwater fish and shrimp consumption for general inland population in China, especially those residing in middle and lower reaches of the Yangtze River.

The role of internal nitrogen loading in supportingnon‐N‐fixing harmful cyanobacterial blooms in the water column of a large eutrophic lake

AbstractWestern Lake Erie cyanobacterial harmful algal blooms (cyanoHABs) occur every summer as a result of anthropogenic nutrient loading. Although the physiological importance of nitrogen (N) in supporting bloom biomass and toxin production is established, the role of internal N recycling in the water column to support bloom maintenance is not as well understood. Over three field seasons (2015–2017), we collected water from western Lake Erie and employed bottle incubations with15N‐ammonium () enrichments to determine regeneration and potential uptake rates in the water column. Potential uptake rates followed spatial and seasonal patterns, with greatest rates measured nearest the Maumee River inflow and during peak bloom months (August and September). Regeneration followed a similar spatial pattern but was greatest in early summer (June and July) and supported ~ 20–60% of potential demand during the height of the bloom. Basin‐wide internal regeneration during the April–October period could supply at 60–200% of annual external N loading to the western basin. These results help explain how non‐N‐fixing cyanoHABs in Lake Erie and other large, eutrophic lakes continue producing biomass and N‐rich toxins long after spring nutrient loads are exhausted or transported to other areas. Internal N loads are ultimately driven by external N loads; in low precipitation years, external nutrient loads result in smaller blooms, producing less substrate for subsequent internal N loads. Overall, these findings, along with others, confirm that both internal and external N loading must be considered when evaluating cyanoHAB management strategies.