Wetlands as a potential multifunctioning tool to mitigate eutrophication and brownification.

Eutrophication and brownification are ongoing environmental problems affecting aquatic ecosystems. Due to anthropogenic changes, increasing amounts of organic and inorganic compounds are entering aquatic systems from surrounding catchment areas, increasing both nutrients, total organic carbon (TOC), and water color with societal, as well as ecological consequences. Several studies have focused on the ability of wetlands to reduce nutrients, whereas data on their potential to reduce TOC and water color are scarce. Here we evaluate wetlands as a potential multifunctional tool for mitigating both eutrophication and brownification. Therefore, we performed a study for 18 months in nine wetlands allowing us to estimate the reduction in concentrations of total nitrogen (TN), total phosphorus (TP), TOC and water color. We show that wetland reduction efficiency with respect to these variables was generally higher during summer, but many of the wetlands were also efficient during winter. We also show that some, but not all, wetlands have the potential to reduce TOC, water color and nutrients simultaneously. However, the generalist wetlands that reduced all four parameters were less efficient in reducing each of them than the specialist wetlands that only reduced one or two parameters. In a broader context, generalist wetlands have the potential to function as multifunctional tools to mitigate both eutrophication and brownification of aquatic systems. However, further research is needed to assess the design of the generalist wetlands and to investigate the potential of using several specialist wetlands in the same catchment.

Analysis of taiga and tundra lake browning trends from 2002 to 2021 using MODIS data.

Lakes in taiga and tundra regions may be silently undergoing changes due to global warming. One of those changes is browning in lake color. The browning interacts with the carbon cycle, ecosystem dynamics, and water quality in freshwater systems. However, spatiotemporal variabilities of browning in these regions have not been well documented. Using MODIS remote sensing reflectance at near ultraviolet wavelengths from 2002 to 2021 on the Google Earth Engine platform, we quantified long-term browning trends across 7616 lakes (larger than 10 km2) in taiga and tundra biomes. These lakes showed an overall decreased trend in browning (Theil-Sen Slope = 0.00015), with ∼36% of these lakes showing browning trends, and ∼1% of these lakes showing statistically significant (p-value <0.05) browning trends. The browning trends more likely occurred in small lakes in high latitude, low ground ice content regions, where air temperature increased and precipitation decreased. While temperature is projected to increase in response to climate change, our results provide one means to understand how biogeochemical cycles and ecological dynamics respond to climate change.

Comparison of Two Water Color Algorithms: Implications for the Remote Sensing of Water Bodies with Moderate to High CDOM or Chlorophyll Levels.

The dominant wavelength and hue angle can be used to quantify the color of lake water. Understanding the water color is important because the color relates to the water quality and its related public perceptions. In this paper, we compared the accuracy levels of two methods in calculating dominant wavelength and hue angle values using simulated satellite data calculated from in situ reflectance hyperspectra for 325 lakes and rivers in Minnesota and Wisconsin. The methods developed by van der Woerd and Wernand in 2015 and Wang et al. in 2015 were applied to simulated sensor data from the Sentinel-2, Sentinel-3, and Landsat 8 satellites. Both methods performed comparably when a correction algorithm could be applied, but the correction method did not work well for the Wang method at hue angles < 75°, equivalent to levels of colored dissolved organic matter (CDOM, a440) > ~2 m-1 or chlorophyll > ~10 mg m-3. The Sentinel-3 spectral bands produced the most accurate results for the van der Woerd and Wernand method, while the Landsat 8 sensor produced the most accurate values for the Wang method. The distinct differences in the shapes of the reflectance hyperspectra were related to the dominant optical water quality constituents in the water bodies, and relationships were found between the dominant wavelength and four water quality parameters, namely the Secchi depth, CDOM, chlorophyll, and Forel-Ule color index.

Continuous Monitoring of Suspended Particulate Matter in Tropical Inland Waters by High-Frequency, Above-Water Radiometry.

Water and sediment discharges can change rapidly, and low-frequency measurement devices might not be sufficient to elucidate existing dynamics. As such, above-water radiometry might enhance monitoring of suspended particulate matter (SPM) dynamics in inland waters. However, it has been barely applied for continuous monitoring, especially under partially cloudy sky conditions. In this study, an in situ, high-frequency (30 s timestep), above-water radiometric dataset, collected over 18 days in a tropical reservoir, is analyzed for the purpose of continuous monitoring of SPM concentration. Different modalities to retrieve reflectance spectra, as well as SPM inversion algorithms, were applied and evaluated. We propose a sequence of processing that achieved an average unsigned percent difference (UPD) of 10.4% during cloudy conditions and 4.6% during clear-sky conditions for Rrs (665 nm), compared to the respective UPD values of 88.23% and 13.17% when using a simple calculation approach. SPM retrieval methods were also evaluated and, depending on the methods used, we show that the coefficient of variation (CV) of the SPM concentration varied from 69.5% down to 2.7% when using a semi-analytical approach. As such, the proposed processing approach is effective at reducing unwanted variability in the resulting SPM concentration assessed from above-water radiometry, and our work paves the way towards the use of this noninvasive technique for high-frequency monitoring of SPM concentrations in streams and lakes.

Water Color Identification System for Monitoring Aquaculture Farms.

This study presents a vision-based water color identification system designed for monitoring aquaculture ponds. The algorithm proposed in this system can identify water color, which is an important factor in aquaculture farming management. To address the effect of outdoor lighting conditions on the proposed system, a color correction method using a color checkerboard was introduced. Several candidates for water-only image patches were extracted by performing image segmentation and fuzzy inferencing. Finally, a deep learning-based model was employed to identify the color of these patches and then find the representative color of the water. Experiments at different aquaculture sites verified the effectiveness of the proposed system and its algorithm. The color identification accuracy exceeded 96% for the test data.

Afforestation driving long-term surface water browning.

Increase in surface water color (browning), caused by rising dissolved organic carbon (DOC) and iron concentrations, has been widely reported and studied in the last couple of decades. This phenomenon has implications to aquatic ecosystem function and biogeochemical carbon cycling. While recovery from acidification and changes in climate-related variables, such as precipitation and length of growing season, are recognized as drivers behind browning, land-use change has received less attention. In this study, we include all of the above factors and aim to discern their individual and combined contribution to water color variation in an unprecedentedly long (1940-2016) and highly resolved dataset (~20 times per month), from a river in southern Sweden. Water color showed high seasonal variability and a marked long-term increase, particularly in the latter half of the dataset (~1980). Short-term and seasonal variations were best explained by precipitation, with temperature playing a secondary role. All explanatory variables (precipitation, temperature, S deposition, and land-use change) contributed significantly and together predicted 75% of the long-term variation in water color. Long-term change was best explained by a pronounced increase in Norway spruce (Picea abies Karst) volume-a measure of land-use change and a proxy for buildup of organic soil layers-and by change in atmospheric S deposition. When modeling water color with a combination of explanatory variables, Norway spruce showed the highest contribution to explaining long-term variability. This study highlights the importance of considering land-use change as a factor behind browning and combining multiple factors when making predictions in water color and DOC.

Hotspots of biotic compositional change in lakes along vast latitudinal transects in northern Canada.

Ecotones mark zones of rapid change in ecological structure at various spatial scales. They are believed to be particularly susceptible to shifts caused by environmental transformation, making them key regions for studying the effects of global change. Here, we explored the variation in assemblage structure of aquatic primary producer and consumer communities across latitudinal transects in northeastern North America (Québec-Labrador) to identify spatial patterns in biodiversity that indicated the location of transition zones across the landscape. We analyzed species richness and the cumulative rate of compositional change (expressed as beta-diversity) of diatoms and chironomids to detect any abrupt shifts in the rate of spatial taxonomic turnover. We used principal coordinates analysis to estimate community turnover with latitude, then applied piecewise linear regression to assess the position of ecotones. Statistically significant changes in assemblage composition occurred at 52 and 55°N, corresponding to the transition between closed- and open-crown forest, and to the southern onset of the forest tundra (i.e., the forest limit), respectively. The spatial distribution of ecotones was most strongly related to air temperature for chironomids and to vegetation- and soil-related chemical attributes of lake water for diatoms, including dissolved organic carbon content and water color. Lakes at mid- to high-latitudes currently face pressures from rapidly rising temperatures, accompanied by large increases in organic carbon inputs from their catchments, often leading to browning and its associated effects. The biota at the base of food webs in lakes located in transition zones are disproportionately affected by the cascading effects of these multi-factorial changes, concurrent with pronounced terrestrial greening observed in these regions. Similar patterns of biotic shifts have been observed along alpine aquatic transects, indicating the potential for widespread restructuring of cold, high-altitude and high-latitude freshwater communities due to global change.

An Automatic Stationary Water Color Parameters Observation System for Shallow Waters: Designment and Applications.

Measurements of the above-water spectrum and concerned water color parameters (WCPs) are crucial for research and applications in water environment remote sensing. Due to the lack of system integration and automatization, conventional methods are labor-intensive, time-consuming, and prone to subjective influences. To obtain a highly accurate and long-term consistent spectrum and concurrent WCPs (Chl-a (chlorophyll-a), turbidity, and CDOM (Colored Dissolved Organic Matter)) data with a relatively low cost, an Automatic Stationary Water Color Parameters Observation System (AFWCPOS) was developed. Controlled by an automatic platform, the spectral and WCPs data were collected by TriOS RAMSES hyperspectral spectroradiometers and WETLabs ECO (Environmental Characterization Optics) fluorometers following the measurement protocol. Experiment and initial validations of AFWCPOS were carried out in Poyang Lake, the largest freshwater lake in China, from 20 to 28 July 2013. Results proved that the spectral data from AFWCPOS were highly consistent with the commonly used portable SVC (Spectra Vista Corporation) HR-1024 field spectroradiometer, with the coefficient of determination (R2) of 0.96, unbiased percent difference (UPD) of 0.14, and mean relative difference (MRD) of 0.078. With advantages of continuous and high degrees of automation monitoring, the AFWCPOS has great potential in capture diurnal and inter-diurnal variations in the test site of Poyang Lake, as well as another high-dynamic shallow coastal and inland waters, which will benefit routine water quality monitoring with high quality and high-frequency time-series observations. In addition, a successful case based on Landsat 8 OLI (Operational Land Imager) image and in-situ data collected by AFWCPOS showed it's potential in remote sensing applications. The spatial distribution of Chl-a, turbidity, and CDOM were mapped, which were explainable and similar to previous researches. These results showed our system was able to obtain reliable and valuable data for water environment monitoring.

A national-scale assessment on the spatial and temporal variations in water color for urban lakes in China.

Monitoring the variations of lake water quality is essential for urban water security and sustainable eco-environment health. However, it is challenging to investigate the water quality of urban lakes at large scales due to the need for large-amount in situ data with diverse optical properties for developing the remote sensing inversion algorithms. Forel-Ule Index (FUI), a proxy of quantifying water color, whose calculation does not require in situ data of specific properties, can comprehensively reflect water quality conditions. However, the spatial and temporal distribution of water color in Chinese urban lakes is still poorly understood. To fill this research gap, this study investigated the spatial distribution of water color in 523 urban lakes (area > 0.5 km2) in China using the FUI derived from the high-quality Multi-Spectral Instrument (MSI) data onboard Sentinel-2 during the ice-free period (April-October) from 2019 to 2022. The monthly and seasonal variation patterns of water color in urban lakes were also analyzed. Our results show that green domain is the most common color of urban lakes, with about 86 % of urban lakes in China being green, and non-green lakes accounting for only 14 % of the total number of lakes. The monthly variation of FUI in urban lakes across the country and multiple geographic regions is basically the same. The monthly average FUI first increases, then decreases, and then rebounds. We also found that the seasonal variation of water color in most urban lakes in southern and northern China is opposite. This study helps to comprehensively understand the spatial and temporal variation of water color and quality of urban lakes in China, providing key basic information for the protection and governance of urban lakes.

A new method for accurate inversion of Forel-Ule index using MODIS images - revealing the water color evolution in China's large lakes and reservoirs over the past two decades.

The Forel Ule water color index (FUI) based on satellite inversion can characterize the comprehensive characteristics of water quality on a large spatiotemporal scale. The high-frequency observations and rich historical data of the MODIS surface reflectance product (MODIS-500 m) provide important data support for monitoring the FUI of inland lakes. However, MODIS-500 m has only three bands in the visible light range, resulting in significant uncertainty in FUI inversion. To address this problem, this study developed an improved FUI inversion model using 500 synthetic spectra covering natural waters. The model, with a performance threshold set at 170° (FUI = 8), used a segmented algorithm across the entire color space. Validated with on-site measurement datasets (3500 samples), the model exhibited excellent performance, with mean relative error (MRE) and root mean square error (RMSE) of 1.71 % and 3.63°, respectively. Compared to existing models, it was more suitable for long-term FUI inversion in various types of lakes, particularly in eutrophic regions. Subsequently, the model was applied to MODIS-500 m observations from 2000 to 2022, revealing the spatiotemporal dynamics of FUI in 180 large lakes and reservoirs (hereinafter referred to as lakes) in China. The results indicated that the long-term mean FUI in the study area was 9, with 7 and 12 in the western and eastern regions, respectively, showing a distinct spatial distribution of "blue in the west and green in the east." The mean change rate of hue angle for all lakes was -0.085°/yr, showing an overall decreasing trend. Environmental factors' relative contributions to long-term water color changes in each lake region were quantified using the multiple general linear model (GLM). Although each lake region exhibited different driving forces, they were primarily influenced by vegetation, lake surface area, and anthropogenic factors. Additionally, the seasonal types of lake water color were analyzed, with the west and east showing opposite patterns, reflecting the significant influence of topographic features and seasonal changes in climate on water color. The research results provide techniques for accurate inversion of FUI using MODIS-500 m data, while deepening the understanding of long-term water color changes in inland lakes in China.

Four-decade dynamics of the water color in 61 large lakes on the Yangtze Plain and the impacts of reclaimed aquaculture zones.

The lakes on the Yangtze Plain, a critical source of freshwater and fisheries for hundreds of millions of people in China, have lost a considerable portion of their surface area due to reclamation since the 1950s. Landsat satellites can provide long-term collections of high-resolution images and thus offer great potential for hindcasting the lake reclamations of aquaculture zones and their long-term impacts on the lacustrine water color. Using Landsat observations from 1984 to 2018 and a Forel-Ule index (FUI) model, we studied the water color dynamics of 61 lakes on the Yangtze Plain. Three distinct change patterns were found among the 61 examined lakes, and 25 of the 61 lakes showed statistically significant changes in the annual hue angle values (P < 0.05). We further collected environmental parameter datasets (runoff, normalized difference vegetation index (NDVI), and wind speed) and a lacustrine reclamation dataset, and measured the concentrations of chlorophyll-a (Chl-a) and dissolved organic carbon (DOC) from two field trips. We investigated their correlations with water color change from different facets. The results showed that the long-term water color in 33 of the 61 lakes exhibited significant correlations with environmental factors. The reclaimed aquaculture zones in this region have caused differences in the water color between the reclaimed area and that in adjacent natural waters. The Chl-a and DOC levels derived from field surveys further confirmed that reclaimed aquaculture zones increased light-absorbing materials in the water and may deteriorate water quality. This study is an important step forward in understanding the water quality changes in lake ecosystems affected by human impacts and natural variability.

Artificial ditching of catchments and brownification-connected water quality parameters of lakes.

We studied the connections between lake water quality and the density of artificial ditching in lake catchments. Water color and the concentrations of dissolved organic carbon (DOC) and iron (Fe) in lake water increased with increasing ditch density. Additionally, the water color:DOC ratio increased along a ditch density gradient because ditching had a stronger effect on color than on DOC. This was mainly due to the positive effect of ditching on the Fe concentration in lakes. Color:DOC ratio was strongly dependent on Fe up to Fe concentrations of 1-1.5 mg L-1. Thus, the water color of lakes with Fe concentrations < 1 mg L-1 will respond especially strongly to the effects of catchment ditching. The effects of ditching were strongest in catchments with high peatland coverage due to their high ditch density and high storage of organic carbon and Fe. The long-lasting effects of ditching should be taken into account when studying the factors governing lake brownification.

Larval fish body growth responses to simultaneous browning and warming.

Organisms are facing global climate change and other anthropogenic pressures, but most research on responses to such changes only considers effects of single drivers. Observational studies and physiological experiments suggest temperature increases will lead to faster growth of small fish. Whether this effect of warming holds in more natural food web settings with concurrent changes in other drivers, such as darkening water color ("browning") is, however, unknown. Here, we set up a pelagic mesocosm experiment with large bags in the Baltic Sea archipelago, inoculated with larval Eurasian perch (Perca fluviatilis) and zooplankton prey and varying in temperature and color, to answer the question how simultaneous warming and browning of coastal food webs impact body growth and survival of larval perch. We found that browning decreased body growth and survival of larval perch, whereas warming increased body growth but had no effect on survival. Based on daily fish body growth estimates based on otolith microstructure analysis, and size composition and abundance of available prey, we explain how these results may come about through a combination of physiological responses to warming and lower foraging efficiency in brown waters. We conclude that larval fish responses to climate change thus may depend on the relative rate and extent of both warming and browning, as they may even cancel each other out.

[Comprehensive Classification Method of Urban Water by Remote Sensing Based on High-Resolution Images].

Urban water is a significant part of the urban ecosystem. Therefore, a comprehensive evaluation method of the water environment was proposed based on domestic high-resolution images. The relationships between the spectral characteristics and water quality parameters of urban water were analyzed based on sampling in Nanjing, Wuxi, Changzhou, and Yangzhou from 2017 to 2019. An index named the U-FUI (urban Forel-Ule index) suitable for urban water based on GF-2 images was proposed to achieve the classification of urban water on the basis of the international standard chroma conversion model and the Forel-Ule index. Independent verification data showed that the recognition accuracy of the classification model could reach 72%. The results indicated that urban water can be classified into six classes from Ⅰ to Ⅵ, which represent water colors of blue, light green, dark green, yellow, yellowish brown, and dark grey, respectively, according to the U-FUI. Among them, the water quality of U-FUI Ⅰ water is good, but is rarely distributed in urban water. The concentrations of chlorophyll-a in U-FUI Ⅱ-Ⅲ water are higher than those of the other classes; the concentrations of total suspended solids, particularly inorganic suspended solids, of U-FUI Ⅳ-Ⅴ water are higher than those of the other classes; and the water quality of U-FUI Ⅵ water is poor and the water quality parameters are different from those of the other classes. Meanwhile, the method was successfully applied to the GF-2 image of Nanjing on April 9, 2018. The results showed that the urban water in Nanjing is mainly composed of U-FUI Ⅱ-Ⅳ water, whereas the distribution of U-FUI Ⅰ, Ⅴ, and Ⅵ water is lower in the city. The spatial distribution characteristics were consistent with the results of in-situ sampling in the same period.

Invertebrates are declining in boreal aquatic habitat: The effect of brownification?

Surface water browning affects boreal lakes in the Northern Hemisphere. This process is expected to increase with global warming. Boreal lakes are the most numerous lakes on Earth. These ecosystems are particularly sensitive to disturbances due to their low biodiversity compared to other aquatic environments. The recent darkening of surface water is expected to hinder key ecosystem processes, particularly through lower primary productivity and loss of biodiversity. However, studies based on long-term data collections have rarely been conducted on the ecological consequences of water browning on aquatic food webs, especially concerning its impacts on invertebrate communities. For the first time, our analysis based on two decades of data collection in Finnish lakes highlighted a relation between water browning and a decline in aquatic macroinvertebrate abundances. Aquatic invertebrates are the main food resource for many secondary predators such as fish and waterbirds, hence such effect on their populations may have major consequences for boreal ecosystem functioning.

Regional measurements and spatial/temporal analysis of CDOM in 10,000+ optically variable Minnesota lakes using Landsat 8 imagery.

Information on colored dissolved organic matter (CDOM) is essential for understanding and managing lakes but is often not available, especially in lake-rich regions where concentrations are often highly variable in time and space. We developed remote sensing methods that can use both Landsat and Sentinel satellite imagery to provide census-level CDOM measurements across the state of Minnesota, USA, a lake-rich landscape with highly varied lake, watershed, and climatic conditions. We evaluated the error of satellite derived CDOM resulting from two atmospheric correction methods with in situ data, and found that both provided substantial improvements over previous methods. We applied CDOM models to 2015 and 2016 Landsat 8 OLI imagery to create 2015 and 2016 Minnesota statewide CDOM maps (reported as absorption coefficients at 440 nm, a440) and used those maps to conduct a geospatial analysis at the ecoregion level. Large differences in a440 among ecoregions were related to predominant land cover/use; lakes in ecoregions with large areas of wetland and forest had significantly higher CDOM levels than lakes in agricultural ecoregions. We compared regional lake CDOM levels between two years with strongly contrasting precipitation (close-to-normal precipitation year in 2015 and much wetter conditions with large storm events in 2016). CDOM levels of lakes in agricultural ecoregions tended to decrease between 2015 and 2016, probably because of dilution by rainfall, and 7% of lakes in these areas decreased in a440 by ≥3 m-1. In two ecoregions with high forest and wetlands cover, a440 increased by >3 m-1 in 28 and 31% of the lakes, probably due to enhanced transport of CDOM from forested wetlands. With appropriate model tuning and validation, the approach we describe could be extended to other regions, providing a method for frequent and comprehensive measurements of CDOM, a dynamic and important variable in surface waters.

New spectroscopic method for true color determination in natural water with high agreement with visual methods.

True water color (TWC) is an important water quality indicator. However, despite many efforts for standardization of methods for TWC determination, there is still no consistency between visual and spectroscopic techniques. This study demonstrates that standard spectroscopic methods overestimate visual data from 21 to 47%, depending on methods involved. To retrieve relevant true water color values from spectral data, a new spectroscopic method is proposed. The method is based on the mathematical model of color perception by the standard observer implementing the dE2000 color difference in the L∗a∗b color space as calculated between blank and water samples. The method showed good agreement with the visual methods (comparator method and determination in Nessler cylinders) and the mean values between these methods. The mean relative difference between the proposed method and the mean of the two visual methods is only 2%. The method precision is independent from TWC in all measurement ranges and has Sr 0.3 mgPt-Co L-1 (df = 98), which is at least three times lower than for the standard methods. As such, it shows higher accuracy and precision. As a result, the proposed method can be used for TWC determination in environmental samples from 3.3 to 500 mgPt-Co L-1 with SD 0.3 mgPt-Co L-1 in all measuring ranges, making sample dilution unnecessary.

Distribution and availability of mercury and methylmercury in different waters from the Rio Madeira Basin, Amazon.

Waters from the Amazon Basin have distinct physicochemical characteristics that can be optically classified as "black", "clear" and "white". We studied the distribution of total-Hg (THg) and methyl-Hg (MeHg) in these waters and respective suspended solids, sediment, phytoplankton, zooplankton, and benthic macroinvertebrates (BM) in the Madeira River Basin. Compared with the other types of water, the more acidic "black" kind had the highest THg and MeHg concentrations. The trend (black > clear > white) occurred for the concentrations of THg and MeHg in sediments and in the biotic compartment (plankton, macroinvertebrates). Organic Hg accounted for a small percentage (0.6-0.4%) of the THg in sediments but was highest in water (17-15%). For plankton and BM, the biota sediment accumulation factor (BSAFs) of MeHg (53-125) were greater than those of THg (4.5-15); however, the BSAF trend according to water type (black > clear > white) was only significant for MeHg. Sediment THg is correlated with all forms of Hg in biotic and abiotic matrices. The results indicate that water acidity in the Amazon is an important chemical characteristic in assessing Hg contamination of sediments and bioaccumulation in the aquatic food web. The differences in the BSAFs between THg and MeHg support the use of this factor for evaluating the bioaccumulation potential of sediment-bound Hg. The results add information critical to assessing environmental and health risks related to Hg methylation and potential fish-MeHg contamination, especially in tropical aquatic environments.

[Analysis of Absorption Characteristics of Urban Black-odor Water].

The urban black-odor water body has become a serious problem of urban water environment and identifying their optical characteristics in urban areas is the prerequisite and basis for their detection by remote sensing. A total of 85 samples of urban black-odor water, from Changsha, Nanjing, and Wuxi, were collected from 2016 to 2017, and a total of 80 samples were collected from non-black-odor (smelly) water samples. The water quality parameters such as suspended matter and the absorption coefficient were measured. The results showed that:①The total black-odor water body particulate matter absorption coefficients and non-pigmented particulate matter absorption coefficients were generally higher than those for non-black-odor water bodies and they had a certain degree of discrimination at 440 nm, but their effect was not significant. The absorption of relatively high levels of particulate matter in black-odor water was mainly due to high absorption of non-pigmented particles. In the data collected, non-pigmented particles in black-odor water accounted for more than 50% of the total particles. ② The Colored Dissolved Organic Matter (CDOM) absorption coefficients for black-odor water bodies and non-black-odor water bodies differed. The average absorption coefficient of CDOM at 440 nm for black-odor water bodies was 1.7 times higher than that for non-black-odor water bodies. Thus, the black-odor water body can be distinguished by using the slope of the absorption coefficient curve fitted in the characteristic wavelength band of 440 nm, as well as in different wavelength bands; the overall effect is good. However, as the wavelength increases, the discrimination effect decreases. Analysis of the absorption characteristics of urban black-odor water bodies will provide effective technical support for their detection by remote sensing and supervision, and the density of CDOM in black-odor water was generally high, which could be used as an important reference for identification.

Life history constraints explain negative relationship between fish productivity and dissolved organic carbon in lakes.

Resource availability constrains the life history strategies available to organisms and may thereby limit population growth rates and productivity. We used this conceptual framework to explore the mechanisms driving recently reported negative relationships between fish productivity and dissolved organic carbon (DOC) concentrations in lakes. We studied populations of bluegill (Lepomis macrochirus) in a set of lakes with DOC concentrations ranging from 3 to 24 mg/L; previous work has demonstrated that primary and secondary productivity of food webs is negatively related to DOC concentration across this gradient. For each population, we quantified individual growth rate, age at maturity, age-specific fecundity, maximum age, length-weight and length-egg size relationships, and other life history characteristics. We observed a strong negative relationship between maximum size and DOC concentration; for instance, fish reached masses of 150 to 260 g in low-DOC lakes but <120 g in high-DOC lakes. Relationships between fecundity and length, and between egg size and length, were constant across the DOC gradient. Because fish in high-DOC lakes reached smaller sizes but had similar fecundity and egg size at a given size, their total lifetime fecundity was as much as two orders of magnitude lower than fish in low-DOC lakes. High DOC concentrations appeared to constrain the range of bluegill life history strategies available; populations in high-DOC lakes always had low initial growth rates and high ages at maturity, whereas populations in low-DOC showed higher variability in these traits. This was also the case for the intrinsic rates of natural increase of these populations, which were always low at the high end of the DOC gradient. The potentially lower capacity for fish populations in high-DOC lakes to recover from exploitation has clear implications for the sustainable management of recreational fisheries in the face of considerable spatial heterogeneity and ongoing temporal change in lake DOC concentrations.