Trophic State Level Research Articles

Anthropogenic dissolved organic matter accumulation fuels greenhouse gas diffusive emissions in urban lakes along trophic state levels

Lakes are an important reservoir of dissolved organic matter (DOM) and also emit large amounts of greenhouse gases (GHGs), such as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Yet, the linkages between quantity and quality of DOM and GHGs emissions are still not well understood. Hence, we investigated how DOM optical properties mediated dissolved GHGs levels and diffusive fluxes along a trophic state level in subtropical urban lakes, China. Our study showed that anthropogenic protein-like DOM (tryptophan- and tyrosine-like components) dominated the DOM pools, comprising 62% of total fluorescence DOM (FDOM). Partial least squares path modeling (PLS-PM) showed that the direct contribution of relative abundance of DOM to CO2 and CH4 diffusion in the highly-eutrophic state was higher than in the mesotrophic and lightly/moderately-eutrophic states. In particular, protein-like DOM primarily accounted for CO2 variations (44%-49%), while humic- and protein-like DOM contributed comparably to CH4 variations (38%-40% vs. 36%-40%). Furthermore, in the lightly/moderately- and highly-eutrophic states, nutrients contributed to DOM, CO2 and CH4 in both direct and indirect ways, while phytoplankton (chlorophyll a, Chl-a) negatively and directly affected carbon emissions. However, only nitrogen content directly contributed to N2O production and diffusion in the mesotrophic and lightly/moderately-eutrophic states. We concluded that protein-like DOM enrichment had the potential to trigger CO2 and CH4 diffusion and this process was largely mediated by nutrient levels. N2O diffusion was found to be mainly influenced by nitrogen loadings and forms. Our findings highlight the urgency for effective strategies to reduce anthropogenic DOM inputs and control nutrient levels to reduce GHGs diffusion in highly human-impacted aquatic systems.

Long-Term Variations of Biogenic Elements and Nutritional Status in Daya Bay, Northern South China Sea

This study explored the variations in the characteristics of the trophic structure of Daya Bay island waters over the last four decades based on the survey findings and research data on biogenic elements (dissolved inorganic nitrogen (DIN), NO2−, NO3−, NH4+, PO43−, and SiO32−) in Daya Bay during 1985–2021. At this time, the DIN concentration increased from 21.14 µg·L−1 to 558.42 µg·L−1 (26.41-fold increase), whereas the SiO32− concentration increased by only 3.6-fold. The PO43− concentrations attained a peak in 2004 and experienced a steady decline over the rest of the survey period. The fractions of NH4+, NO3−, and NO2− in DIN changed from 0.45, 0.40, and 0.15 in 1986 to 0.26, 0.74, and 0.003 in 2021, respectively. Overall, the mean values of NH4+, NO3−, and NO2− accounted for 45.2%, 42.5%, and 12.3%, respectively. The N/P(DIN/PO43−) ratio in Daya Bay increased from 28.08 in the 1980s to 51.63 in the 2010s. Meanwhile, the nutrient limitation conditions showed a gradual shift from N-limited to P-limited conditions. According to the nutrient quality index (NQI) analysis, the trophic state level of Daya Bay waters fell into the oligotrophic category 30 years ago (1985–2002, NQI < 2), whereas it increased from the mesotrophic level in 2005 (NQI = 2.03) to the eutrophic level in 2019 (NQI = 3.33) over the last 20 years. The results based on the eutrophication index (EI) of Daya Bay waters were generally consistent with those based on the NQI, displaying that the trophic level of Daya Bay waters indicated an increasing trend from 2005 to 2019. Moreover, the assessment data in 2021 indicated a decrease in the NQI to 0.90, thereby attaining the oligotrophic level again. This may be related to the decrease in aquacultural area in the bay over the last two years. The correlation analysis among the DIN, PO43−, and nutrient levels of Daya Bay waters indicated that the input of nitrogen and phosphorus was the primary reason for the higher nutrient levels in the water bodies; among them, municipal sewage discharge, aquaculture, and atmospheric deposition from industry are the main factors for the over importation. This indicates that the changes in the biogenic element concentrations led to variations in the trophic structure and level of Daya Bay and may be attributed to population growth and the development of the seaside industry and agriculture in the region.

Análise das correlações entre nitrogênio total e clorofila a em reservatórios do Ceará/Brasil

ABSTRACT Chlorophyll a (Chla) concentration is an important indicator to characterize algal biomass, reflecting water quality and the level of eutrophication of aquatic environments. This study analyzed 4315 total nitrogen (TN) and Chla samples in 155 reservoirs in Ceará, Brazil. Relationships were obtained between TN and Chla through simple linear regression and classified according to the statistical performance of the coefficient of determination (R²). The dynamics of these correlations were examined by analyzing the variance between classification groups concerning watershed, reservoir size, coefficient of variability, and trophic state. The concentration of pollutants was influenced by seasonality, which increased significantly from the wet to the dry period in most basins. The coefficients of determination between Chla and TN for the watersheds followed the trends of classic curves in the literature, with satisfactory models (R² > 0.3) in most reservoirs (53.3%). The variance analysis attested that the models’ performance was affected by the basins, the volumetric variation, and the change in the trophic state levels. There was no significant variance of R² between reservoirs of different sizes.

Spatiotemporal Variations in the Water Quality of Qionghai Lake, Yunnan–Guizhou Plateau, China

Although Qionghai Lake is one of the 11 large and medium-sized lakes (lake area > 25 km2) in the Yunnan–Guizhou Plateau (YGP), there has been little research on its water quality, especially over the long term. Herein, meteorological, hydrologic, trophic, and biochemical indices were investigated over the 2011–2020 period to explore the spatiotemporal variations in water quality in Qionghai Lake. The results showed that the CCME-WQI value for Qionghai Lake ranked between marginal and fair during 2011–2020, that the water quality of Qionghai Lake before 2017 was worse than after 2017, and that the water quality of the western part of Qionghai Lake was worse than that of the eastern part. Total nitrogen and total phosphorus were 0.39–0.51 and 0.019–0.027 mg/L during 2011–2020, respectively, and were the main pollution factors in Qionghai Lake. In addition, Qionghai Lake was at the mesotrophic level, but the chlorophyll and trophic state levels (TLI) increased year by year, and the levels in the western area were higher than in the eastern area. Increased anthropogenic activities (industrialization, urbanization, agricultural intensification, etc.) were the main reasons for the poor water quality of Qionghai Lake before 2017, while, after 2017, effective government environmental restoration and management measures improved the water quality. Moreover, the difference in land-use types within the watershed was the main reason for the spatial heterogeneity of water quality in Qionghai Lake. Potassium permanganate index (CODMn) and ammonia nitrogen content index (NH3-N) were not very high, but both showed seasonal variations. Water transparency (SD) in Qionghai Lake was reduced by sediment input and increased algal biomass, while dissolved oxygen (DO) decreased due to thermal stratification. This study is expected to provide a theoretical reference for understanding changes in the water quality and water environmental protection of Qionghai Lake and the YGP.

Inland Water Trophic State Identification using Remote Sensing data and Machine Learning Approach

Providing information on inland waters’ trophic state levels (oligotrophic, mesotrophic, eutrophic, and hypereutrophic) is considered more effective in communicating the lake’s conditions to the public and policymakers than water quality. It is highly demanding for a straightforward method to estimate inland waters’ trophic state. This study proposes a model for estimating the lake trophic state levels from remote sensing data. We used simulation data to overcome data limitations in building the classification model. The simulation data consists of one nanometer (nm) interval spectra, paired with calculated Secchi Disk Depth (SD in m) representing various water types. We convert the spectra into Landsat band configuration and classify SD into four trophic state levels. We compare four machine learning classification models, i.e., Classification and Regression Trees (CART), k-Nearest Neighbour (k-NN), Support Vector Machine (SVM), Random Forest (RF), and select the best model using the Kappa Index. We apply the selected model to satellite images and estimate trophic state levels of various lakes across time and space. Our result demonstrated that the developed model could robustly identify the lake trophic state levels. This rapid identification procedure could provide valuable spatial and temporal information of the lake’s conditions for the public and policymakers to support inland water sustainable management.

Cyclopoid copepods as indicators of trophic level in South American reservoirs: A new perspective at species level based on a wide spatial-temporal scale

Aiming to identify efficient indicators for reservoir water quality, the abundance of cyclopoid copepods, 11 limnological variables, and a modified trophic state index (TSI) for tropical/subtropical reservoir systems were studied in 30 different reservoirs in South America. A total of 331 fieldwork campaigns, originated from six different studies on a wide spatial–temporal scale were analyzed. Samplings included small to large reservoirs (varying between 6 and 2250 km2 area) with oligo, meso and eutrophic conditions, and places with punctual eutrophication from fish cage farms. Spatial scale ordination was relevant for variables and reservoirs, but the temporal scale was also important in all analyses, positioning the same reservoir sampled in different years contrasting correlations in terms of species and variables. Principal component analysis consistently indicated the importance of chlorophyll, nutrients (phosphorus and nitrogen), turbidity, transparency, and depth for proper ordination of reservoirs according to their trophy. Of all the 13 cyclopoid species identified, ten were planktonic and at the end, after conclusive statistical correlation analysis, five species were selected as efficient water quality indicators. Redundancy analysis related different species with different trophic aspects: Acanthocyclops robustus, Microcyclops anceps and Tropocyclops prasinus were positively associated with chlorophyll and inversely associated with water transparency, Thermocyclops decipiens and T. inversus with electrical conductivity, and slightly associated with chlorophyll and total nutrients (phosphorus and nitrogen), and finally Thermocyclops minutus was positively correlated with transparency. Spearman correlations indicated that only T. inversus abundance was correlated with water temperature, but T. decipiens was not correlated with TSI, which is intriguing because this species has been commonly associated with eutrophic waters. Despite tolerate a wide range of trophic conditions, as pointed in RDA, T. decipiens seems to be replaced by other more resistant species when trophic conditions become too high – hypereutrophic environments. Four other selected species were correlated with TSI, and T. minutus was negatively correlated, confirming its association with oligotrophic waters. From all species found, we conclude that A. robustus, M. anceps, T. prasinus, T. decipiens and T. minutus are good indicators of trophic state level in South American reservoirs.

Nonlinear response of methane release to increased trophic state levels coupled with microbial processes in shallow lakes

Shallow lakes are a crucial source of methane (CH4), a potent greenhouse gas, to the atmosphere. However, large uncertainties still exist regarding the response of CH4 emissions to the increasing trophic levels of lakes as well as the underlying mechanisms. Here, we investigate the CH4 emission flux from lakes with different trophic states in the middle and lower reaches of the Yangtze River basin, China to evaluate the effect of the trophic lake index (TLI) on CH4 emissions. The mean CH4 emission fluxes from mesotrophic, eutrophic, middle-eutrophic, and hyper-eutrophic lakes were 0.1, 4.4, 12.0, and 130.4 mg m−2 h−1, respectively. Thus, the CH4 emission flux ranged widely and was positively correlated with the degree of eutrophication. The relative abundance of methanogens with respect to the total population for the mesotrophic, eutrophic, mid-eutrophic, and hyper-eutrophic states was 0.03%, 0.35%, 0.94%, and 1.17%, respectively. The biogeographic-scale pattern of lakes classified as each of these four trophic states indicated that CH4 emissions could be well-predicted by the NH4+-N concentration in the water column, as both NH4+-N and CH4 were produced during mineralisation of labile organic matter in lake sediment. In addition, the shift from clear to turbid water, which is an unhealthy evolution for lakes, was associated with a nonlinear increase in the CH4 emissions from the studied lakes. In particular, the hypereutrophic lakes functioned as CH4 emission hotspots. Our findings highlight that nutrient levels, as a potential facilitator of CH4 emissions, should be considered in future research to accurately evaluate the greenhouse gas emissions from shallow lakes.

Influencing Factors Analysis of Taiwan Eutrophicated Reservoirs

Treatment cost and quality of domestic water are highly correlated with raw water quality in reservoirs. This study aims to identify the key factors that influence the trophic state levels and correlations among Carlson trophic state index (CTSI) levels, water quality parameters and weather factors in four major reservoirs in Taiwan from 2000 to 2017. Weather (e.g., air temperature, relative humidity, total precipitation, sunlight percentage and cloud cover) and water quality parameters (e.g., pH, chemical oxygen demand, suspended solids (SS), ammonia, total hardness, nitrate, nitrite and water temperature) were included in the principal component analysis and absolute principal component score models to evaluate the main governing factors of the trophic state levels (e.g., CTSI). SS were washed out by precipitation, thereby influencing the reservoir transparency tremendously and contributing over 50% to the CTSI level in eutrophicated reservoirs (e.g., the Shihmen and Chengchinghu Reservoirs). CTSI levels in the mesotrophic reservoir (e.g., Liyutan Reservoir) had strong correlation with chlorophyll-a and total phosphorus. Results show that rainfall/weather factors were the key driving factors that affected the CTSI levels in Taiwan eutrophicated reservoirs, indicating the need to consider basin management and the impacts of extreme precipitation in reservoir management and future policymaking.

Environmental Condition and Trophic Status of Lake Rawa Pening in Central Java

Due to continuous problems of eutrophication, Lake Rawa Pening has been included into the 15 priority lakes in Indonesia to be saved from damage. This study aimed to clarify the current environmental conditions and trophic status of Lake Rawa Pening as a basis to control the eutrophication. Sediment loads, water quality, and nutrient concentrations were measured in the tributaries of lake inflow, within the lake, and at the point of lake outflow. The study was conducted in May, June, July, and August 2013. Water transparency, temperature, pH, turbidity, conductivity, and dissolved oxygen were measured in situ. Nitrogen, nitrate, total phosphorus, orthophosphate, TSS, and chlorophyll-a parameters were analyzed using standard method procedures. The Trophic State Index was used to determine the trophic state level. Hydroclimatological conditions showed that seasonally, fluctuation of water volume and discharge of lake followed the pattern of rainfall fluctuation. The sediment loads and nutrient concentration in the tributary inflow were more abundant than those in the lake and lake outflow. The results indicated that Lake Rawa Pening acts as sediment and nutrient sinks. Spatially and temporally, Lake Rawa Pening showed high variation of water quality. High concentration of nutrients observed during the wet and dry seasons indicated that the nutrients in the lake originated not only from external but also from internal sources. The overall results show that Lake Rawa Pening is a eutrophic lake, in which phosphorus seems to play a major role in causing eutrophication and massive growth of water hyacinth. <br /><br /><br />

Simulation of the Contribution of Phosphorus-Containing Minerogenic Particles to Particulate Phosphorus Concentration in Cayuga Lake, New York

Phosphorus (P) associated with minerogenic particles delivered from watersheds can interfere with the common use of total P (TP) concentration as a trophic state metric in lacustrine systems, particularly proximate to tributary entries, because of its limited bioavailability. The concentration of unavailable minerogenic particulate P (PPm/u), where it is noteworthy, should be subtracted from TP in considering primary production potential and trophic state levels. A first mass balance model for PPm/u is developed and tested here for Cayuga Lake, New York. This is supported by a rare combination of detailed information for minerogenic particle level dynamics for the tributaries and lake, the bioavailability of tributary particulate P (PP), and previously tested hydrothermal/transport and minerogenic particle concentration submodels. The central roles of major runoff events and localized tributary loading at one end of the lake in driving patterns of PPm/u in time and space are well simulated, including (1) the higher PPm/u concentrations in a shallow area (“shelf”) adjoining the inputs, relative to pelagic waters, following runoff events, and (2) the positive dependence of the shelf increases on the magnitude of the event. The PPm/u component of P was largely responsible for the higher summer average TP on the shelf vs. pelagic waters and the exceedance of a TP water quality limit on the shelf. The effective simulation of PPm/u allows an appropriate adjustment of TP values to avoid overrepresentation of potential primary production levels.

The tempo-spatial variations of phytoplankton diversities and their correlation with trophic state levels in a large eutrophic Chinese lake

Lake Chaohu is one of the most eutrophic lakes in China. Research on this lake's seasonal and spatial variations in phytoplankton diversity is needed to understand the distribution of eutrophication, as well as to find appropriate comprehensive biodiversity indices to assess the eutrophication status of the lake. The present study indicated that the Margalef index of all samples was as low as 0.799±0.543 in summer (August 2011) and as high as 1.467±0.653 in winter (February 2012). The Margalef index of the river samples had a high mean value and substantial variation compared with the lake samples. The Peilou index of the lake samples was higher than that of the river samples in summer and autumn (November 2011) but lower than that of the river samples in winter. In spring (May 2012), the Peilou index of the western samples was lower than that of the eastern samples. The spatial distribution of the Shannon–Wiener index was more similar to that of the Peilou index in autumn and winter, while in spring and summer, the spatial distribution was affected by both species richness and evenness. High eutrophication levels occurred in the western lake in spring and summer, whereas high levels occurred in the eastern lake, especially in the middle of the lake, in autumn and winter. The total trophic state index (TSI) in all samples exhibited a significant negative correlation with the Margalef (r=−0.726) and Peilou (r=−0.530) indices but a significant positive correlation with the Shannon–Wiener (r=0.654) index. The partial correlation analysis results implied that these phytoplankton biodiversity indices could serve as synthetic ecological indicators to assess the eutrophication condition of Lake Chaohu.

Modeling Impreciseness of Trophic State Levels for Eutrophication Assessment

Tremendous efforts have been madeto propose numerous indices for quantifyingstates of eutrophication in lentic water bodies over the last decades. Most of the indices are developed or modified considering conventional trophic state indices (e.g., Carlson trophic state index (TSI)) or pre-specified ranges of cause and response variables (e.g., index proposed by Organization of Economic and Cooperation and Development (OECD)), where a strong correlation structure must exist among cause and response variables. Here an attempt is made to model impreciseness or subjectivity of trophic state levels,especially for weakly correlated variables. A generalized framework using fuzzy synthetic evaluation (FSE), analytic hierarchy process (AHP) and the concept of statistical entropyis proposed to assess the trophic state of lentic water bodies. The proposed methodology has been tested with the case study of Jordan lake data set collected from the United States of Geological Survey (USGS) data base.The result shows that, the eutrophication problem is critical mostly during the months of August to October,and the method can efficiently capture the rapid changes in trophic states.The sensitivity of the model has been tested with different weight structures for cause and response variables considered during model development, and the robustness of the model has also been tested with different weighting techniques.

Trophic state level monitoring of Lake Taihu based on in situ measurements of hyperspectral reflectance

富营养化指数是评价水体污染情况的一个重要的综合性指标．通过对高光谱遥感数据和水体富营养化指数的分析,确立了反演水体富营养化水平的高光谱敏感波段,进而用选择的敏感波段和波段组合来建立模型．通过对几个模型的比较,选出了较为理想的估算模型．最后对模型进行精度分析,认为该模型具有一定的可靠性和实用性．从而确定了直接由高光谱遥感数据监测水体富营养化水平的可能性,为实现由高光谱遥感数据开展大范围的水质调查奠定了一定的理论基础．;Trophic state index is an important and synthetic standard for estimating the pollution status of water body. It requires large scale field sampling work and complicated indoor chemical analysis involving traditional analytical techniques, as well as complex calculations applying complicated formulas. In this study, through the analysis of the hyperspectral remote sensing data and the water body trophic state level, the remote sensing reflectance and trophic state index of the water body, Lake Taihu, are calculated, The result of correlative analysis, found the hyperspectral sensitive bands to be inverse to the water-body^, s trophic state index and sensitive bands and bands^, combination (ratio) in established models. The comparative baseline model selected is a power function model TSI_C =68. 76χ^0.5199, with an independent variable of R_717nm. The result, through precision analyses using the other 12 points, found the differences between practice and forecast along half one grading interval, therefore providing reliability and practicability. In conclusion, it is possible to monitor a water-body^,s trophic state index directly with hyperspectral remote sensing data and some evidence for the theoretical basis of investigating water quality in a large scope using hyperspectral remote sensing data is justified.

Differences in the eutrophication dynamics of Ammersee and Starnberger See (Southern Germany), reflected by the diatom succession in varve-dated sediments

Diatom assemblages in the annually laminated sediments of two neighboring, pre-alpine lakes (Ammersee and Starnberger See, Southern Germany) were analyzed and compared year by year. Within both varve records of the last decades, the same 4-phase-succession of planktonic diatom species is preserved, consisting of 1. a dominance of Cyclotella species 2. assemblages of Fragilaria crotonensis, Asterionella formosa and Stephanodiscus minutulus 3. a mass bloom of Aulacoseira islandica, and 4. a dominance of Stephanodiscus species. This diatom sequence is considered as a model of a 'basic species sequence of eutrophication'. Time lags and differences in the duration of the phases between both lakes show evidence of an earlier start for nutrient loading in Starnberger See than in Ammersee, and a faster development to a higher trophic state level in the latter. The different reactions of the lakes are attributed to hydrological differences such as the existence or lack of a major tributary, the size of the catchment area, and the water residence time. The reconstruction of the eutrophication dynamics appears to be reliably hindcast by the inference of total phosphorus (TP) concentrations using weighted averaging regression and calibration techniques. Remarkable differences in the occurrence of some diatoms in both stratigraphies, which are not related to the general changes of the 'basic species sequence of eutrophication' model, may be due to the epilimnetic silica content (e.g. Fragilaria crotonensis) or competitive weaknesses (e.g. Tabellaria flocculosa).