Next Article in Journal
Bengal Delta, Charland Formation, and Riparian Hazards: Why Is a Flexible Planning Approach Needed for Deltaic Systems?
Previous Article in Journal
Gloeotrichia cf. natans (Cyanobacteria) in the Continuous Permafrost Zone of Buotama River, Lena Pillars Nature Park, in Yakutia (Russia)
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Water
Volume 15
Issue 13
10.3390/w15132372
water-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Importance of Assessing Water Quality in Tributaries: A Case Study in an Urban Waterway Using Zebrafish (Danio rerio)

by
Sabine Malik
1,
Annastelle Cohen
2,
Stephen E. MacAvoy
1 and
Victoria P. Connaughton
3,*
1
Department of Environmental Science, American University, Washington, DC 20016, USA
2
Department of Biology, American University, Washington, DC 20016, USA
3
Department of Biology, Center for Neuroscience and Behavior, American University, Washington, DC 20016, USA
*
Author to whom correspondence should be addressed.
Water 2023, 15(13), 2372; https://doi.org/10.3390/w15132372
Submission received: 5 May 2023 / Revised: 8 June 2023 / Accepted: 15 June 2023 / Published: 27 June 2023
(This article belongs to the Section Water Quality and Contamination)
Browse Figures
Versions Notes

Abstract

:
Tributaries are important for fish recruitment and diversity. Here, we examine the biological impact of inorganic and organic contaminants in Paint Branch stream (PBS), a tributary of the Anacostia river in Washington D.C. The Anacostia has suffered severe ecological damage because of decades of pollution and deposited wastewater runoff; however, PBS, which connects to the northern part of the river, is forested and less urbanized, suggesting higher water quality. However, the impact of PBS water on early fish development has not been studied. To address this question, we examined if chronic (28 day) exposure to water collected from PBS can support the proper early development of zebrafish (Danio rerio), a vertebrate model in toxicological studies. We assessed their overall growth and swimming behaviors and correlated these results with a water quality analysis. The water chemistry identified high levels of calcium, sodium, and nitrate in PBS water samples. A gas chromatography–mass spectroscopy analysis of extracted non-polar compounds in the water column revealed siloxanes (congeners D6–D10) were the only component identified with >90% certainty. In our fish experiments, we observed age-dependent increases in growth and eye development, consistent with normal development. In contrast, general swimming behaviors showed an early increase in angular velocity at 7 days postfertilization (dpf; p = 0.001) and a decreased total distance traveled at 14 dpf (p = 0.015) for PBS-treated larvae. Using the open field test, we observed that the PBS-treated fish made fewer visits to the edge at 7 (p = 0.01), 14 (p < 0.001), and 21 dpf (p = 0.038) and spent significantly more time at the edge at 21 dpf (p < 0.001). Fewer visits to the center were also noted at 14 and 21 dpf, suggesting reduced overall movement at these two ages in response to chronic PBS water exposure. Interestingly, by 28 dpf, no differences were noted in any parameter measured. Overall, these results indicate zebrafish larvae grew well in PBS water; however, their reduced movement and anxiogenic behavior suggested subtle behavioral abnormalities. The identified chemicals likely originated from runoff or sewage and have potentially deleterious consequences for fish living in PBS or migrating to/from upstream spawning/nursery locations.

1. Introduction

Conservation and remediation efforts in freshwater systems typically focus on rivers and larger streams, no doubt because of their high visibility and recreational use. Recent studies examining tributaries that feed into these larger water systems have suggested that conservation/remediation should also focus on smaller waterways [1,2,3,4]. Tributaries serve as spawning and/or nursery areas for a variety of freshwater fish species, and recent work comparing ichthyoplankton abundance in tributaries vs. their connected rivers has identified higher numbers of eggs and larval fish from a greater diversity of species within tributaries [3].
Despite these positives, there are threats to tributary habitats [5]. For example, the presence of physical barriers, such as dams or other man-made structures, block fish movement, hampering the ability of adult fish to reach spawning grounds [6]. The numbers of eggs and larvae found in tributaries with dams is significantly reduced compared to those of un-dammed tributaries [2,4]. Another concern is weather-related changes in habitats. Heavy rains can change sediment composition [7] and increase discharge from more upstream locations, which alters the substrate, making it less favorable for egg laying [7] and potentially harming the development of fertilized eggs that have been buried. Finally, chemicals (pollutants, nutrient loads, etc.) that enter tributaries through runoff or other sources can compromise water quality. High nutrient (nitrate) loads in small tributaries cause large algal blooms [8,9], which reduce the amount of oxygen [8]. High nitrate levels can also cause respiratory problems in fish [8,10], decrease the activity, growth, and survival of freshwater amphibians, fish, and arthropods [11], and increase their susceptibility to other, concurrent stressors [8,10,11]. Pollutants and other chemicals can also enter tributaries from runoff, wastewater, or sewage effluent, further altering water quality. Given the role of tributaries in fish reproduction and the fact that fish in certain developmental stages often display increased susceptibility to altered water quality, assessing water quality, flow, and dynamics in tributaries will reveal significant information relevant to young-of-the-year fish recruitment and overall species diversity.
The purpose of this study was to directly address how water quality in a tributary impacts the survival, growth, and development of fish larvae. To our knowledge, there are few studies that have addressed this question in a controlled setting. This type of study is relevant because it (1) indicates the overall health of the tributary, (2) indicates the presence of specific chemicals, (3) addresses whether larval fish are able to survive in/adapt to water quality in a tributary nursery area, and (4) is directly relevant to remediation/conservation efforts. Our experiments focus on Paint Branch stream, an understudied tributary of the Anacostia river in Washington, DC.
Paint Branch stream (PBS) is part of a ~54 km2 urban watershed located outside of Washington DC in Montgomery County and Prince George’s County, Maryland [12]. The Paint Branch watershed is part of the northeast branch of the larger Anacostia river watershed [13,14] which drains DC. The upper two-thirds of the Paint Branch watershed is in a special protected area with a large, forested buffer along the river, reduced development [15], and a native population of spawning brown trout [12,16]. Moving downstream toward its convergence with the Anacostia river, PBS encounters increased urbanization [12] and altered flow, which is associated with changes in carbon cycling [14] and stream temperature [17]. There is also a progressive downstream loss of macroinvertebrate species diversity [18]. Nonetheless, compared to other sites along the Anacostia river, Paint Branch river is rated ‘excellent for fish communities’ [19]. The U.S. Geological Survey (USGS) has been monitoring the water quality of PBS at a site near College Park, Maryland (station 01649190) since 2007 [20]. This site, which is also the sampling location for this work (Figure S1), is characterized as 57% urban, 7% agriculture, 33% forested/undeveloped, and 2% wetland [20].
PBS’s progressive increase in downstream urbanization has led to concerns about successful fish reproduction. In fact, brown trout stocks, which spawn in the upstream tributaries of the Paint Branch watershed, have been declining, with only five adults observed in 2018 [7]. Hypothesized reasons for the decreased numbers of returning adults include the blockage of fish passages [6] and loss of appropriate substrate for egg laying [7]. Another possibility is altered water quality causing the overall poor survival of eggs/larvae/juveniles over time. The Anacostia watershed is historically known to have measurable concentrations of various legacy chemicals and persistent pollutants, some of which have been identified in PBS [15]. A biomonitoring study with clams placed in PBS showed the accumulation of polyaromatic hydrocarbons (PAHs), metals, pesticides, and polychlorinated biphenyls (PCBs) [21]. These compounds are known to alter fish behavior, growth, and/or survival [22,23,24,25,26,27,28,29,30,31]. Our recent work correlating water quality with larval fish growth and behavior using water collected from more downstream regions of the Anacostia [32,33] identified siloxanes, a component of personal care products, as a major contaminant at both sites. Larval zebrafish raised in these water samples displayed behavioral changes, with differences in growth and survival between the two sites.
Zebrafish, a vertebrate model organism, is one of the most common fish species used in toxicology [34,35,36]. The choice of zebrafish is because their externally developing embryos and larvae are small and numerous, allowing for high-throughput screening of compounds and behavioral testing with large sample sizes. In addition, the sequencing of the zebrafish genome and its amenability to a variety of molecular techniques (mutant and transgenic lines, CRISPR-Cas9 genome editing, etc.) provide a system in which potential cellular mechanisms causing changes in behavior can be assessed. In fact, the US Environmental Protection Agency supports the use of zebrafish in toxicological analyses [35,37]. While we acknowledge that zebrafish are not indigenous to PBS nor the Anacostia River, their status as a model organism and use in this work will provide relevant information that could be applied to native fish species.
In this manuscript, we describe the results of our experiments, which assessed how larval zebrafish grow and develop in water collected from Paint Branch stream. Our hypothesis was that their growth and development would be directly correlated with the PBS’s water quality. We tested this hypothesis by raising zebrafish larvae for 28 days in water samples collected directly from Paint Branch stream. Growth and developmental differences were assessed with anatomical and behavioral endpoints; a water chemistry analysis and gas chromatography–mass spectroscopy were used to evaluate the water quality.

2. Materials and Methods

2.1. Sampling Site and Water Collection

Water samples from PBS were collected in Fall 2020 in three 19 L carboys. Our sampling site was Paint Branch park, located in College Park, MD, near a USGS monitoring station. Water samples (500 mL/filter) were filtered through Whatman glass fiber filters with a diameter of 4.7 cm and pore size of 1.2 μm using a vacuum pump. Filters were then dried for 2 h at 60 °C. Collected water samples were divided into 1 L Nalgene bottles and either stored in an incubator at 28 °C or frozen (−20 °C) for later use.

2.2. Inorganic Water Chemistry

During the same water sampling trip, a water column sample was collected for water chemistry analysis. The sample was collected using 500 mL acid (HCl)-washed HDPE bottles. All samples were insulated and sent to Cornell’s Nutrient Analysis Lab (https://cnal.cals.cornell.edu/, accessed on 6 June 2023) for analysis of water nutrients and inorganics (pH, hardness, sodium absorption ratio (SAR), alkalinity, total concentration of dissolved substances (TDS), calcium (Ca), magnesium (Mg), sodium (Na), potassium (K), iron (Fe), manganese (Mn), zinc (Zn), aluminum (Al), arsenic (As), boron (B), barium (Ba), beryllium (Be), cadmium (Cd), chromium (Cr), copper (Cu), cobalt (Co), molybdenum (Mo), nickel (Ni), lead (Pb), total phosphorus (P), sulfur (S), silicon (Si), strontium (Sr), titanium (Ti), vanadium (V), nitrate (NO3−), and ammonium (NH4+)). Methodology for nutrient and inorganic ion analysis was based on EPA requirements (Standard Methods for the Examination of Water and Wastewater, http://www.standardmethods.org/, accessed on 6 June 2023). A Colorimetric Bran-Luebbe Automated Ion Analyzer was used for NH4+, PO43−, and NO3−. Elements were analyzed by plasma atomic emission spectrometry (ICP-AES), which determines trace elements, including metals, in solutions.

Quality Assurance/Quality Control

For ammonia analysis, every 20 samples analyzed had one sample duplicate and one sample spiked at low and high levels (http:www/standardmethods.org/, accessed on 6 June 2023). The relative percent difference (RPD) of the duplicate was within 20%. For nitrate analysis, there was a blank (<0.001 mg/L) and standard check every 20 sample cups. The standard recovery was between 90 and 110% for all runs. Additionally, duplicates were run every 20 samples. The RPD for the standard was within 20%. For orthophosphate analysis, reading of a standard and duplicate was performed every 12 samples and at the end of the run. Standards were within 10% of actual value (for further details, see EPA Method 356.1). For ICP elemental analysis of water samples, blanks (reagent water) were analyzed regularly to ensure there were no memory effects or contamination. A spiked sample was used each run to ensure recovery was within 10% of actual value. For further details of elemental analysis methods, please refer to EPA Method No. 6010-B.

2.3. Gas Chromatography–Mass Spectroscopy (GC-MS)

Dried filters were placed in glass thimbles at a density of 7–9 filters/thimble. Each thimble’s contents were run through a Soxhlet extraction for 16–18 h using 99.9% dichloromethane as a solvent [38]. Round bottom flasks collected the products of the extractions before they were rotary-evaporated to remove any extra solvent. To separate fatty acids and lipids, 1 M KOH in 70% EtOH was added to each flask and heated for 3 h under reflux. Following saponification, rotary evaporation was again used to remove excess solvent. Samples were washed with 10 mL 99.9 % hexane, followed by two more washes of 5 mL 99.9% hexane each. Using a separatory funnel, fatty acids were isolated and stored in a freezer (4 °C) until further processing.
Fatty acid samples were neutralized (to pH of 5–6) using HCl (33–38%). In a separatory funnel, a hexane wash separated any remaining EtOH solution from the neutral fatty acids. The EtOH was discarded, and rotary evaporation removed any remaining solvent from the neutralized fatty acids. Next, to produce more robust samples, a methyl ester was created by adding 0.5 mL of 1 M BF3CH2OH to the fatty acid sample, heating it at 60 °C for 8 min, and transferring it to a separatory funnel with 10 mL 99.9% hexane. The samples were washed with two 5 mL portions of saturated KCl. BaCl2 was added to the separatory funnel, and the bottom layer was removed and discarded. The top layer (hexane) was added to a beaker containing Na2SO4 to remove water. The sample sat for 15 min before it was pipetted into a 5 mL vial. If necessary, vials were vacuum-desiccated to concentrate the fatty acid methyl ester. Fatty acid samples were then analyzed using GC–MS. Prior to GC–MS, samples were resuspended in 1 mL 99.9% hexane before 1 μL was injected into the sample port of an Rxi®-5ms fused silica column. Samples were run over a 20 min period with temperatures from 50 °C to 250 °C.

2.4. Animals and Treatment Exposures

Fertilized wildtype zebrafish (Danio rerio) eggs were obtained from a commercial supplier (Aquatic Tropicals, Live Aquaria, Rhinelander, WI, USA). Once in the lab, eggs were cleaned, staged, and placed in Petri dishes containing either filtered PBS water or filtered control (system) water. Each treatment was established with 160 eggs (40 eggs × 4 petri dishes) and incubated at 28 °C (Heratherm, ThermoFisher, Waltham, MA, USA). The larvae were reared to 28 days postfertilization (dpf). A 50% water change occurred every other day. Experimental dishes were checked daily, and any debris was removed. After 48 h postfertilization (hpf), larvae were fed AP100 powdered food. This diet was supplemented with live brine shrimp (Artemia salina) starting at 8 days (d) pf.

2.5. Behavioral and Morphological Assessment

After each week of exposure, i.e., 7, 14, 21, and 28 dpf, a subsample of 5 larvae was removed from each treatment and placed into a 6-well plate (1 fish per well) for behavioral assessment. Larvae were allowed to acclimate for 1 min in the recording chamber, after which time their behavior was recorded for 10 min using EthoVision XT motion-tracking software (ver. 15; Noldus Information Technology). Lighting was provided by a light plate (Avtek) located below the 6-well plate. After each recording period, all larvae were euthanized in 0.02% tricaine methanesulfonate solution and preserved in a 4% paraformaldehyde solution for later analysis.
Anatomical differences were assessed by measuring two different parameters: notochord length (anterior end of the snout to the posterior end of the notochord) and eye diameter (measured anterior to posterior). These endpoints were selected because they are easily measured and because differences in growth (notochord length) and vision (morphology and/or function) are often used as endpoints in toxicological studies with zebrafish. Preserved larvae were photographed using a Leica microscope and LAN X software (ver. 5.1; Leica), and measurements were made with Image J (ver. 1.53a; https://imagej.nih.gov/ij/download.html, accessed on 15 May 2023).
Fixed larvae were then transferred to 70% ethanol, dehydrated, embedded in paraffin, and sectioned (5 µm sections) (AML Laboratory, Inc., St. Augustine, FL, USA). Sections were stained with hematoxylin and eosin (H & E) to assess gross anatomical changes in internal structures (eye). H&E-stained slides were photographed using an Olympus BX 51 microscope fitted with a Xfinity 1-1 camera (firmware ver. 9.78; Lumenera) and imaged using Xfinity Capture software. Retinal architecture was assessed by measuring thickness of different retinal layers on H&E-stained slides. Measurements were made in central retina, behind the lens.

2.6. Statistical Analysis

Changes in behavior were determined by analyzing the videos beginning at 5 min (halfway through the 10 min recording time) for a total duration of 5 min to account for any disturbances during the initial recording period. Each recording was analyzed at 30-s time bins for the following parameters: distance moved (mm), angular velocity (deg/sec), visits to edge, visits to center, time at edge (sec), and time in center (sec). The “center” zone was designated to be the area in the inner 50% of the well. These data were then averaged and analyzed using a two-way ANOVA, followed by the Tukey post hoc test (IBM SPSS, ver. 26). All results were evaluated at α = 0.05.
For anatomical assessment, notochord length, eye diameter, and retinal layer measurements were each taken three times and averaged. Eye diameter measurements were normalized to length prior to statistical analysis. Differences in all morphological measurements were assessed using a two-way ANOVA followed by the Tukey posthoc test and evaluated at an α-level of 0.05.

3. Results

3.1. Water Chemistry and Pollutant Analysis

The analysis of the filtered PBS water samples identified high calcium and sodium concentrations (highlighted in Table 1). The nitrate in the PBS water samples was also very high, approximately two times what would be considered normal for a freshwater stream.
The GC/MS analysis of the PBS water samples identified only five compounds with ≥ 90% certainty using the NIST database. All these compounds are cyclic volatile methyl siloxanes. The specific siloxanes identified were dodecamethylcyclohexasiloxane (D6), tetradecamethylcycloheptasiloxane (D7), hexadecamethylc yclooctaslioxane (D8), octadecamethyl cyclononasiloxane (D9), and eicosamethyl cyclodecasiloxane (D10). The blanks injected before and after the samples did not show siloxane beyond the column background.

3.2. Zebrafish Larvae Grow Well in PBS Water

The morphological analysis of zebrafish larvae reared in PBS water identified a significant age-dependent increase in overall length (p < 0.001; Figure 1a). However, no effects of the treatment (p = 0.595) or treatment*age interaction were identified (p = 0.925). The normalized eye diameter measurements (Figure 1b) did not differ with respect to either treatment (p = 0.638) or age (p = 0.081), nor was there a treatment*age interaction (p = 0.173), though the measurements were smaller at 21 and 28 dpf compared to the measurements at 7 dpf and 14 dpf. Clearly, the larvae raised in the filtered PBS water grew well (Figure 2).

3.3. Exposure to PBS Water Did Not Alter Eye Development

Vision-based functional studies in zebrafish [39] show reduced optomotor responses following developmental exposure to heavy metals [40] and endocrine disruptors [41,42] as well as altered retinal anatomy and photoreceptor ultrastructure after developmental PCB exposure [43]. Similarly, the eyes of the golden grey mullet were found to accumulate heavy metals [44,45], and electroretinograms identified altered retinal physiology in tambaqui after pesticide exposure [46]. Altered vision reduces feeding success and predator avoidance, two behaviors in fish that depend on a functioning visual system.
Our data showed a trend of reduced overall eye size observed at 21 dpf and 28 dpf. We wondered if this may be due to exposure-induced changes in the retina, which could lead to reductions in overall eye size. To determine if the observed differences in eye size were due to gross morphological changes in retinal anatomy, we examined the retinal architecture (Figure 3), focusing specifically on differences in retinal layer thicknesses.
Our analysis identified an age-dependent increase in the total retinal thickness (Figure 4a, p < 0.001), inner-plexiform layer thickness (IPL, Figure 4c, p = 0.003), and thickness of the photoreceptor layer (PL, Figure 4f, p < 0.001). In each case, the measurements at 7 dpf were significantly smaller than the measurements at 14, 21, or 28 dpf. In addition, the measurements of larvae raised in PBS water were consistently smaller than the controls at 7 dpf, though there were no significant effects of treatment and no treatment*age interaction was observed. No significant differences in thickness were observed for either the ganglion cell layer (GCL, Figure 4b) or the outer plexiform layer (OPL, Figure 4e), though the measurements from PBS-treated fish were again smaller than those of the controls at 7 dpf. The inner nuclear layer thickness (INL, Figure 4d) was significantly affected by the treatment (p = 0.042); however, subsequent t-tests performed at each time point did not identify significant differences.

3.4. Behavioral Differences Were Observed in PBS-Treated Larvae

In contrast to our anatomical data, the larvae raised in the PBS water showed differential and time-dependent effects on their behavior (summarized in Table 2). Overall, at 7 dpf, most of the behaviors assessed were not significantly different between the treatment groups. After 14 dpf, however, the PBS-treated fish were moving less overall and spending more time at the edge of the dish. Increased time at the edge was also observed at 21 dpf, when the PBS-treated larvae also made fewer visits to both the edge and the center. Interestingly, at 28 dpf, no behavioral differences between the PBS-treated larvae and controls were noted for any parameter measured (Table 2; Figure 5 and Figure 6).
More specifically, the angular velocity measurements (Figure 5a) were significantly affected by age (p < 0.027) and there was a significant treatment*age interaction (p = 0.023), though there were no main effects of the treatment (p = 0.207). This significant interaction is likely due to the increased velocity measurements observed in the PBS-treated larvae 7 dpf compared to those of the controls. These data also revealed an interesting trend in which the angular velocity measurements of the PBS-treated larvae decreased from 7 to 21 dpf, while the measurements from the control larvae increased. The lowest overall angular velocity measurements for both treatments, however, were observed at the time point of 28 dpf.
The total distance traveled also decreased with age (p < 0.001) with no main effects of treatment (p = 0.427; Figure 5b) and no significant interaction (p = 0.349). For this parameter, larvae in either treatment group moved the greatest distances at 7 dpf, with steady decreases in distance over the 4-week time frame. The total distance was significantly reduced in the PBS-treated larvae 14 dpf compared to that of the controls (Table 2; Figure 5b); the distance traveled at the other ages was comparable between treatments.
Thigmotaxis is a behavior used to identify anxiety, and it is characterized by a preference for the edge of a chamber. To assess this behavior, we used the open field test and quantified where the larvae were in the recording chamber (the edge vs. center; as in [35,47]) and how frequently they moved between these two compartments (the time at edge vs. time at center). Our results show that the time spent at the edge of the recording dish (Figure 6a) was significantly affected by the treatment (p = 0.004), and there was a significant treatment*age interaction (p = 0.002). More specifically, the larvae raised in the PBS water spent more time at the edge of the dish compared to the controls at 7 dpf, 14 dpf, and 21 dpf, with significance at 21 dpf. The frequency of visits to the edge of the dish (Figure 6c) was also significantly affected by the treatment (p = 0.005) and age (p < 0.001), though there was no significant interactive term (p = 0.165). The larvae raised in the PBS water made fewer visits to the edge during the first three weeks of exposure. Fewer visits to the edge and a longer period of time at the edge suggest that once the PBS larvae reached the edge, they remained there.
The time in the center of the chamber (Figure 6b) was also significantly affected by the treatment (p = 0.029), and a significant interaction was observed (p < 0.001), with the larvae reared in the PBS water spending less time in the center at 21 dpf. The frequency of visits to the center (Figure 6d) displayed a significant treatment*age interaction (p = 0.001), but no main effects of treatment (p = 0.054) or age (p = 0.076) were recorded. The larvae reared in the PBS water made significantly fewer visits to the center at 14 dpf and 21 dpf. At 7 dpf and 28 dpf, in contrast, the number of visits to the center was similar to that of the controls. Reduced visits to both the center and edge suggest increased immobility in the larvae reared in the PBS water.

4. Discussion

As an upstream tributary ~19 km away from the tidal mouth of the Anacostia river, PBS, with its relative lack of anthropogenic disruption, is described as having better water quality than other parts of the river [19]. The upper reaches of the stream are part of a special protected area, which further limits human inputs and the effects of urbanization [15]. Indeed, one third of PBS is forested and undeveloped [14,20]. Nonetheless, the progressively increasing urbanization of PBS as you go downstream results in allochthonous inputs, as evidenced by the large terrestrial dissolved inorganic carbon inputs to the stream [14]. Pesticides, industrial metabolites, per-/polyfluoroalkyl substances, and organophosphate flame retardants have also been identified in PBS’s surface waters [15]. The goal of this work was to identify how compounds present within PBS water may impact larval fish growth and behavior.

4.1. PBS Water Samples Had High Levels of Calcium, Sodium, and Nitrate

The water samples used in this study were collected during the Fall of 2020. Though we only collected water at a single site at a single time, we believe our data to be representative of that time of year in PBS. Supporting evidence for this conclusion comes from data collected from the USGS sampling site at the same location (Figure S2). The data collected from May 2019 to 2023, a time period selected because it shows data before and after our sampling date, show seasonal trends in terms of dissolved oxygen, pH, turbidity, and stream flow (Figure S2). Seasonal variations in these parameters, as well as discharge, sediment load, and mineral content, have also been reported by others [17,20]. Importantly, the annual measurements of these parameters from July to January are consistent each year. This suggests that our water chemistry analyses from Fall 2020 are representative of the conditions in PBS during that time.
We observed high calcium (Ca), sodium (Na), and nitrate (NO3) in our PBS water samples. Cations derived from silicate mineral weathering have high Ca/Na (ratios higher than eight were previously reported by [48]) and low Ca/K ratios. The Anacostia watershed is largely underlain by silicate minerals (metamorphosed mica and quartz rich clays, mostly metagraywacke); however, the river water is chemically distinct from what normally drains silicate-derived soils. Not only is the Ca/Na ratio observed to be very low (1.33), but the Ca/K ratio is very high (6.0). This suggests that the weathering of silicate minerals is not the source of cations. Examining the ratio of Ca/Sr can yield clues to calcium sources in some circumstances. In the absence of carbonate rocks, it would be highly unusual for the Ca/Sr ratios to be above 200. Yet, in PBS, the ratio is 211. In a watershed lacking carbonates, a ratio this high is derived from the chemical weathering of concrete. In the Washington DC area, Portland concrete is used, and it has a Ca/Sr ratio between 260 and 305 [49]. Taken as a whole, the cations suggest that “urban karst” is driving the stream chemistry combined with road salt, which persists through all seasons. The pH of the rainfall in the Washington DC area is 4.9, yet the stream water’s pH is ~8.0. This is a very high pH for natural waters in a humid, non-carbonate environment. It is highly likely that the acidic precipitation is being buffered by the limestone-bearing concrete, and Ca, Na, and Mg are released as reaction products. This has been observed in the urban main stem of the Anacostia but has not been reported for tributaries to date [50].
Calcium or other ions within the water are consumed either through uptake across the fish’s gills or the fish drinking the water followed by uptake across their intestines [51] and/or kidneys. High calcium levels can protect fish from heavy metal (zinc) toxicity by outcompeting zinc for the uptake carrier [51]. The observed concentration of zinc in our water samples was very low, which, coupled with the high calcium levels, suggests there is little-to-no threat of zinc toxicity in PBS. Further, cadmium (Cd), cobalt (Co), iron (Fe), chromium (Cr), arsenic (As), Copper (Cu), and lead (Pb) were not detected in our PBS samples, indicating an absence of heavy metals within this tributary.
A metric that can be used to assess natural vs. anthropogenic sources of nitrate in freshwater is the Si:NO3 ratio. Rivers that are not impacted by anthropogenic nitrate have ratios above 10. Rivers majorly impacted by agriculture or sewage have ratios closer to one [52]. PBS has a ratio of three, and it is likely that its high nitrate level is derived from leaking wastewater pipes.
For aquatic plants, NO3 is a major nutrient, with high levels associated with algal blooms and rapid growth [8]. In contrast, elevated constant nitrate levels have deleterious effects on fish. High NO3 levels as a stress can increase susceptibility to other/additional stressors, such as hypoxia and temperature changes [8,10]. Nitrate that is taken up by a fish enters its red blood cells and binds to hemoglobin, preventing the hemoglobin from binding to oxygen. This causes a reduction in oxygen levels in the fish’s blood; changes in gill structure/morphology are also noted [8,10]. A meta-analysis of published data focusing on the impact of NO3 levels [11] reported that NO3 exposure decreases growth and survival and increases developmental deformities in exposed fish. Juvenile rainbow trout exposed to elevated NO3 for 3 months displayed differences in their swimming behaviors and non-monotonic effects on their swimming velocity [53]. Changes in swimming behaviors were also observed in NO3-treated juvenile silver perch [8]. Adult zebrafish exposed to NO3 spent increased time in the bottom of a novel tank, a stress response that was correlated with reduced brain levels of GABA and glutamine [54]. The high NO3 levels in our PBS samples may have contributed to the anxiety-like behaviors we observed in the zebrafish larvae.

4.2. Siloxanes Are a Major Contaminant at PBS

We previously reported the presence of siloxanes in water samples collected from both Washington Navy Yard (WNY) [33] and Bladensburg Waterfront Park (BWP) [32], two other locations along the Anacostia river. These sites are more downstream than PBS, located at the confluence of the northwest and northeast branches of the river (BWP) and close to the mouth of the river (WNY). The presence of siloxanes at BWP and WNY, as well as PAH and PCBs, is largely due to the sampling locations being near legacy toxic sites and/or near other sources of input, whereas PBS is more rurally located. Nonetheless, our analysis identified siloxanes as a significant contaminant in PBS.
Siloxanes are major components of personal care and household products (reviewed in [55,56]). Siloxanes enter waterways through sewage effluent [57,58] and washoff/wastewater [59,60,61], with measurable levels found in aquatic habitats worldwide [57,58,62,63,64,65,66,67,68]. The siloxanes identified here were congeners D6 through D10. These are cyclic (vs. linear) compounds, denoted by ‘D’, with 6–10 denoting the number of repeating -Si(CH3)2-O- groups [55,69]. Most published studies reporting siloxane levels in the environment have identified D4 and D5 as the two most prevalent species. Interestingly, we did not observe these two siloxanes in our samples at our criterion level. Smaller siloxanes (D3–D6) tend to be more associated with rivers, whereas larger species (up to D16) appear to be more associated with industrial use (reviewed in [69]). D8 and D9 have also been found in some plant extracts [69].
Of the siloxanes we identified, the most information in the literature relates to D6 (and to a lesser extent D7), likely because D6 is often found in water samples that also contain D4 and D5 [60,62]. D6 and D7 are also in a variety of personal care products (toothpaste, body wash, lotion) [60] as well as fish tissues collected in China [62] and Canada [70]. D6–D9 [55] and D10 [71] are components of baking moulds, and measurable levels are observed in air or particulate matter after baking/oven use [71,72]. D6–D9 have also been identified in sediment samples from industrialized coastal bays in South Korea [73]. The identification of these siloxanes, which have both residential and industrial uses, in our PBS water samples is logical given that our sampling location is near the University of Maryland and various housing developments in an area characterized as 57% urbanized.

4.3. How Does Exposure to PBS Water Affect Fish Growth?

To assess the potential impact of PBS water quality on early fish growth and development, we performed controlled experiments with zebrafish, a well-known model for toxicological studies.
We observed similar growth rates for both notochord length and eye diameter measured from zebrafish larvae raised in control or PBS water, suggesting the larvae within Paint Branch stream do not show any differences (either later or earlier in development) in their growth as a result of exposure. We also see no differences in retinal development (retinal layer thicknesses), except for age-related changes. Retinal development in zebrafish begins at 24 hpf [74], which is when our experimental exposures began. The eyes are a large, dominant structure in zebrafish larvae, with a formed retina observed at hatching (48–72 hpf). The organization of the zebrafish retina is like that of other vertebrates. The light-absorbing rod and cone photoreceptors (in the PL) have their terminals in the OPL, where they are presynaptic to bipolar and horizontal cells. The cell bodies of second-order bipolar and horizontal cells, along with amacrine cells, are found in the INL. The IPL includes bipolar cell terminals, which are presynaptic to ganglion cells (GCL). Axons of ganglion cells form the optic nerve, which relays the signal to the brain.
At 72 hpf, all layers and cell types are evident. In the PL, rod photoreceptors are slowly added as the larvae grow. The observed differences in overall retinal thickness, IPL thickness, and PL thickness likely reflect the age-dependent addition of rods to the zebrafish retina, which begins at 8 dpf and continues until 14–15 dpf [75] when the rods are mature and rod signaling is robust [76]. Indeed, spectral sensitivity functions contain few or no rod contributions until 3 weeks of age [77], supporting the later addition of this cell type. As rod photoreceptors are added into the retinal network, the PL thickness increases, resulting in a greater overall retinal thickness. Increased IPL thickness with age similarly reflects the addition of cells into the existing retinal network. Importantly, after the large increase in layer thickness between 7 and 14 dpf, the layer measurements were not significantly different between the treatments. Some parameters (OPL thickness, GCL thickness, INL thickness) were smaller, though not significantly, in the PBS-treated larvae at 28 dpf, suggesting a delayed effect. Overall, our results show that retinal lamination occurred properly in the PBS-treated larvae, indicating that their retinal-based vision function, which is important for capturing prey, is intact.
In contrast to the anatomical data, their behavior showed treatment-specific effects. Their general swimming behavior, measured as total distance traveled, and angular velocity were only significantly affected at 7 dpf (velocity) and 14 dpf (distance); however, during the entire exposure period, the angular velocity decreased with the increasing duration of the fish’s exposure to the PBS water, resulting in a steady decrease in the distance traveled with time. The results of the open field test revealed that the larvae raised in the PBS water increased the time they spent at the edge of the recording chamber and reduced their movement progressively from 7 dpf to 21 dpf compared to those of controls. These behavioral changes suggest anxiety-like behaviors, which can impact survival by decreasing exploratory behavior [78], resulting in reduced foraging and predator avoidance abilities. Interestingly, we found significant differences after 2 and 3weeks of exposure (i.e., at 14 and 21 dpf), but not at the time point at 28 dpf. These results could be due to the non-monotonic effects of exposure or the presence of compensatory/regulatory mechanisms within the fish themselves because of continued exposure. Non-monotonic responses have been previously identified in zebrafish adults exposed to different concentrations of fluoxetine [79] and heavy metals [80] as well as in zebrafish larvae exposed to antidepressants [81] and endocrine disruptors [41]. In this study, however, the same water sample was used for all of the experiments, suggesting that the duration of exposure, and not necessarily the concentration of each chemical, is an important consideration.
Zebrafish are not a resident species in PBS or the Anacostia river. However, as a model organism, results from zebrafish studies such as this one are applicable to other species. For PBS, this species is the brown trout. After hatching, trout larvae must navigate within their habitat to find food, and juveniles make their way downstream. The ability of these young-of-the-year fish to survive within the stream/tributary habitat is a significant consideration, particularly because at this life stage, they are migrating downstream into more urban (polluted) areas and/or moving between adjacent river branches. The survival of freshwater fish during their early life stages is heavily affected by weather/storm events which can drastically change the water temperature, pH, and/or quality [82]. Our work suggests that water chemistry and contaminant levels also contribute to the decreased potential survival of young fish, which jeopardizes subsequent population growth.
We previously showed that zebrafish larvae raised in water collected at more downstream locations of the Anacostia river (i.e., BWP and WNY) also showed increasing growth with age [32,33], consistent with the hypothesis that larval fish can survive and grow in the Anacostia river. However, specific growth differences for each sampling site were noted. After 4 weeks of exposure, the zebrafish larvae raised in water from WNY at 28 dpf were significantly larger and wider than the controls, with increased eye diameters [33]. In contrast, the zebrafish larvae raised in water from BWP were larger after 1 week of exposure (7 dpf), a transient effect that was no longer significant at 14 dpf [32]. A follow-up experiment exposing zebrafish to specific siloxane species (D4, D5, and D4H [32]) revealed siloxane-specific differences in survival: zebrafish larvae chronically exposed to D4 or D5 did not survive past 11 dpf. At 7 dpf, the D4- and D5-exposed larvae had reduced startle responses and spent less time in the center of the chamber, indicating reduced overall movement. These findings correlate well with those of the BWP-raised larvae, which also show reduced time in the center of the chamber at 7 dpf [32]. Our current data add to this by identifying siloxanes in an upstream tributary of the Anacostia river and by showing that larval fish raised in water from this tributary have altered behaviors. Siloxanes are clearly a prevalent contaminant in the Anacostia river, and there is a strong correlation between exposure to these compounds and stress-like responses in larval fish.

5. Conclusions

Paint Branch stream is an understudied tributary of the Anacostia river that has a high level of ecological significance. Our water chemistry analysis of collected samples revealed high calcium, sodium, and nitrate levels, consistent with contamination from urban runoff. Our data also show evidence of both natural/terrestrial changes (i.e., weathering, perhaps impacted by humans) and direct human inputs (siloxanes). The zebrafish raised in the PBS water displayed no overall differences in their growth. However, behaviorally, the larvae raised in the PBS water had increased immobility and thigmotaxis, which are anxiogenic responses. Interestingly, most of their behavioral effects revealed non-monotonic responses, and differences in behavioral responses were often not observed until at/after 2 weeks of exposure, suggesting the effects of prolonged exposure were slow to develop. These results may be due to the high nitrate and/or siloxane levels observed in the PBS water, consistent with published reports. Changes in behavior, but not overall growth, suggest subtle effects of chemicals/compounds present in the water that target cellular pathways and circuits. These behavioral differences could impact their subsequent development and foraging/predator avoidance behaviors. This change in behavior could ultimately reduce overall fish survival in this tributary, which may help to explain the reduction in brown trout populations. We suggest that remediation efforts within the Anacostia should continue in PBS.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w15132372/s1, Figure S1: Map of the Anacostia River watershed showing different subwatersheds within the boundaries; Figure S2: Water quality measurements from May 2019–May 2023 collected at USGS Station #16049190 (Paint Branch Stream).

Author Contributions

Conceptualization, S.E.M. and V.P.C.; Data curation, S.E.M. and V.P.C.; Formal analysis, S.M. and A.C.; Funding acquisition, V.P.C.; Methodology, S.M., A.C., S.E.M. and V.P.C.; Project administration, V.P.C.; Supervision, S.E.M. and V.P.C.; Writing—original draft, S.M. and V.P.C.; Writing—review and editing, S.M., A.C., S.E.M. and V.P.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by a seed grant from DC-WRRI/UDC/USGS, grant # 2020DC118B to VPC.

Institutional Review Board Statement

All procedures were approved by the Institutional Care and Use Committee at American University (protocols #19-03, #22-04).

Data Availability Statement

Data are available from the authors by request.

Acknowledgments

The authors would like to thank the members of the Zebrafish Ecotoxicology, Neuropharmacology, and Vision Lab for their help in zebrafish husbandry and discussions of our data.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. McReynolds, A.; Hoff, M.; Sikora, A.; Nau, C.; Pietraszek, M.; Bartelme, C.; Christie, M.; Hoffman, S.; Hayer, C.; Forsythe, P. Adult and larval fish assemblages vary among small tributary mouths of Green Bay, Michigan. Can. J. Zool. 2021, 99, 319–329. [Google Scholar] [CrossRef]
  2. Phomikong, P.; Udduang, S.; Fukushima, M.; Srichareondham, B.; Rattanachamnong, D.; Jutagate, T. Larval fish assemblage patterns in three tributaries of Mekong River in Thailand. Indian J. Fish. 2018, 65, 1–15. [Google Scholar] [CrossRef]
  3. Sarai da Silva, P.; Miranda, L.; Makrakis, S.; Assumpcao, L.d.; Dias, J.P.; Makrakis, M. Tributaries as biodiversity preserves: An ichthyoplankton perspective from the severely impounded Upper Parana River. Aquat. Conserv. Mar. Freshw. Ecosyst. 2019, 29, 258–269. [Google Scholar] [CrossRef]
  4. Vasconcelos, L.; Alves, D.; Camara, L.d.; Hahn, L. Dams in the Amazon: The importance of maintaining free-flowing tributaries for fish reproduction. Aquat. Conserv. Mar. Freshw. Ecosyst. 2020, 31, 1106–1116. [Google Scholar] [CrossRef]
  5. Reid, A.; Carlson, A.; Creed, I.; Eliason, E.; Gell, P.; Johnson, P.; Kidd, K.; MacCormack, T.; Olden, J.; Ormerod, S.; et al. Emerging threats and persistent conservation challenges for freshwater biodiversity. Biol. Rev. 2019, 94, 849–873. [Google Scholar] [CrossRef] [Green Version]
  6. Hedgberg, C.; Schlindwein, P.; Cohen, S.; Jacobs, S. Natural Fish Passage Structures in Urban Streams. Part I: Hydrologic and Resource Issues. UC Davis: Road Ecology Center. 2001. Available online: https://escholarship.org/uc/item/65q7g3cw (accessed on 8 June 2023).
  7. Pipkin, W. Brown trout’s survival in Anacostia tributary an upstream struggle. Bay Journal, 12 August 2019; p. 7. [Google Scholar]
  8. Gomez Isaza, D.; Cramp, R.; Franklin, C. Exposure to nitrate increases susceptibility to hypoxia in fish. Physiol. Biochem. Zool. 2021, 94, 124–142. [Google Scholar] [CrossRef]
  9. Mooney, R.; Stanley, E.; Rosenthal, W.; Esselman, P.; Kendall, A.; McIntyre, P. Outsized nutrient contributions from small tributaries to a Great Lake. Proc. Natl. Acad. Sci. USA 2020, 117, 28175–28182. [Google Scholar] [CrossRef]
  10. Rodgers, E.; Opinion, A.; Isaza, D.G.; Raskovic, B.; Poleksic, V.; Broeck, G.D. Double whammy: Nitrate pollution heightens susceptibility to both hypoxia and heat in a freshwater salmonid. Sci. Total Environ. 2021, 765, 142777. [Google Scholar] [CrossRef]
  11. Gomez Isaza, D.; Cramp, R.; Franklin, C. Living in polluted waters: A meta-analysis of the effects of nitrate and interactions with other environmental stressors on freshwater taxa. Environ. Pollut. 2020, 261, 114091. [Google Scholar] [CrossRef]
  12. Eyes of Paint Branch. Basic Watershed Information. Available online: http://www.eopb.org/watershed_info/paint_branch_basics.php (accessed on 26 July 2022).
  13. CHEARS. Anacostia Watershed Map. Available online: https://chears.org.viewMap.php?id=16 (accessed on 26 July 2022).
  14. Smith, R.; Kaushal, S. Carbon cycle of an urban watershed: Exports, sources, and metabolism. Biogeochemistry 2015, 126, 173–195. [Google Scholar] [CrossRef]
  15. Guardian, M.; He, P.; Bermudez, A.; Duan, S.; Kaushal, S.; Rosenfeldt, E.; Aga, D. Optimized suspect screening approach for a comprehensive assessment of the impact of best management practices in reducing micropollutants transport in the Potomac River watershed. Water Res. X 2021, 11, 100088. [Google Scholar] [CrossRef] [PubMed]
  16. Bernhardt, E.; Palmer, M. Restoring streams in an urbanizing world. Freshw. Biol. 2007, 52, 738–751. [Google Scholar] [CrossRef]
  17. Nelson, K.; Palmer, M. Stream temperature surges under urbanization and climate change: Data, models, and responses. J. Amer. Water Res. Assoc. 2007, 43, 440–452. [Google Scholar] [CrossRef]
  18. Moore, A.; Palmer, M. Invertebrate biodiversity in agricultural and urban headwater streams: Implications for conservation and management. Ecol. Applic. 2005, 15, 1169–1177. [Google Scholar] [CrossRef]
  19. Anacostia Watershed Restoration Partnership. Anacostia River Watershed Restoration Plan and Report, Final Draft; Metropolitan Washington Council of Governments: Washington, DC, USA, 2010; 163p.
  20. Miller, C.; Chanat, J.; Bell, J. Water Quality in the Anacostia River, Maryland and Rock Creek, Washington, DC: Continuous and Discrete Monitoring with Simulations to Estimate Concentrations and Yields of Nutrients, Suspended Sediment, and Bacteria: US Geological Survey Open-File Report 2013–2014; USGS, Department of the Interior: Washington, DC, USA, 2013; 37p.
  21. Phelps, H. Corbicula biomonitoring in the Anacostia Watershed; University of the District of Columbia: Washington, DC, USA, 2003; 17p. [Google Scholar]
  22. Berninger, J.; Tillitt, D. Polychlorinated biphenyl tissue-concentration thresholds for survival, growth, and reproduction in fish. Environ. Toxicol. Chem. 2019, 38, 712–736. [Google Scholar] [CrossRef] [Green Version]
  23. Brun, N.; Panlilio, J.; Zhang, K.; Zhao, Y.; Ivashkin, E.; Stegeman, J.; Goldstone, J. Developmental exposure to non-dioxin-like polychlorinated biphenyls promotes sensory deficits and disrupts dopaminergic and GABAergic signaling in zebrafish. Commun. Biol. 2021, 4, 1129. [Google Scholar] [CrossRef]
  24. Garai, P.; Banerjee, P.; Mondal, P.; Saha, N. Effect of heavy metals on fishes: Toxicity and bioaccumulation. J. Clin. Toxicol. 2021, 11, 001. [Google Scholar]
  25. Geier, M.; Chlebowski, A.; Truong, L.; Simonich, S.M.; Anderson, K.; Tanguay, R. Comparative developmental toxicity of a comprehensive suite of polycyclic aromatic hydrocarbons. Arch. Toxicol. 2018, 92, 571–586. [Google Scholar] [CrossRef]
  26. Green, A.; Planchart, A. The neurological toxicity of heavy metals: A fish perspective. Comp. Biochem. Physiol. Part C 2018, 208, 12–19. [Google Scholar] [CrossRef] [PubMed]
  27. Hamilton, T.; Krook, J.; Szaszkiewicz, J.; Burggren, W. Shoaling, boldness, anxiety-like behavior and locomotion in zebrafish (Danio rerio) are altered by acute benzo[a]pyrene exposure. Sci. Total Environ. 2021, 774, 147702. [Google Scholar] [CrossRef]
  28. Rani, R.; Sharma, P.; Kumar, R.; Hajam, Y. Effects of heavy metals and pesticides on fish. In Bacterial Fish Diseases; Academic Press: Cambridge, MA, USA, 2022; pp. 59–86. [Google Scholar]
  29. Shah, Z.; Parveen, S. A review on pesticides pollution in aquatic ecosystem and probable adverse effects on fish. Pollut. Res. 2020, 39, 309–321. [Google Scholar]
  30. Singleman, C.; Zimmerman, Z.; Harrison, E.; Roy, N.; Wirgin, I.; Holtzman, N. Toxic effects of polychlorinated biphenyl congeners and aroclors on embryonic growth and development. Environ. Toxicol. Chem. 2021, 40, 187–201. [Google Scholar] [CrossRef] [PubMed]
  31. Vignet, C.; Frank, R.; Yang, C.; Wang, Z.; Shires, K.; Bree, M.; Sullivan, C.; Norwood, W.; Hewitt, L.; McMaster, M.; et al. Long-term effects of an early-life exposure of fathead minnows to sediments containing bitumen. Part I: Survival, deformities, and growth. Environ. Pollut. 2019, 251, 246–256. [Google Scholar] [CrossRef]
  32. Jessup, W.; Wiegand, J.; Delbridge-Perry, M.; MacAvoy, S.; Connaughton, V. Developmental effects of siloxane exposure in zebrafish: A comparison study using laboratory-mixed and environmental water samples. J. Appl. Toxicol. 2022, 42, 1986–2004. [Google Scholar] [CrossRef]
  33. Wilken, R.; Imanalieva, A.; MacAvoy, S.; Connaughton, V. Anatomical and behavioral assessment of larval zebrafish (Danio rerio) reared in Anacostia River water samples. Arch. Environ. Contam. Toxicol. 2020, 78, 525–535. [Google Scholar] [CrossRef]
  34. Fitzgerald, J.; Konemann, S.; Krumpelmann, L.; Zupanic, A.; Berg, C.v. Approaches to test the neurotoxicity of environmental contaminants in the zebrafish model: From behavior to molecular mechanisms. Environ. Toxicol. Chem. 2020, 40, 989–1006. [Google Scholar] [CrossRef]
  35. Horzmann, K.; Freeman, J. Making waves: New developments in toxicology with the zebrafish. Toxicol. Sci. 2018, 163, 5–12. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Kabashi, E.; Brustein, E.; Champagne, N.; Drapeau, P. Zebrafis models for the functional genomics of neurogenetic disorders. Biochim. et Biophys. Acta-Mol. Basis Dis. 2011, 1812, 335–345. [Google Scholar] [CrossRef] [Green Version]
  37. Padilla, S.; Corum, D.; Padnos, B.; Hunter, D.; Beam, A.; Houck, K.; Sipes, N.; Kleinstreuer, N.; Knudsen, T.; Dix, D.; et al. Zebrafish developmental screening of the ToxCast Phase 1 chemical library. Reprod. Toxicol. 2012, 33, 174–187. [Google Scholar] [CrossRef]
  38. Barnes, P.; Brassell, S.; Comet, P.; Eglinton, G.; McEvoy, J.; Maxwell, J.; Wardroper, A.; Volkman, J. Preliminary lipid analyses of core sections 18, 24, and 30 from hole 402A. Age 1979, 1000, 298–308. [Google Scholar]
  39. Chen, X.-F.; Lin, Z.-C.; Qi, Z.; Caii, Z.; Chen, Z.-F. Effects of pollutant toxicity on the eyes of aquatic life monitored by visual dysfunction in zebrafish: A review. Environ. Chem. Lett. 2023, 21, 1177–1201. [Google Scholar] [CrossRef]
  40. LeFauve, M.; Connaughton, V. Developmental exposure to heavy metals alters visually-guided behaviors in zebreafish. Curr. Zool. 2017, 63, 221–227. [Google Scholar] [CrossRef] [Green Version]
  41. Crowley-Perry, M.; Barberio, A.; Zeino, J.; Winston, E.; Connaughton, V. Zebrafish optomotor response and morphology are alteredc by transient developmental exposure to bisphenol-A. J. Dev. Biol. 2021, 9, 14. [Google Scholar] [CrossRef]
  42. Gould, C.; Wiegand, J.; Connaughton, V. Acute developmental exposure to 4-hydroxyandrostenedione has a long-term effect on visually-guided behaviors. Neurotoxicol. Teratol. 2017, 64, 45–49. [Google Scholar] [CrossRef]
  43. Wang, Y.-P.; Hong, Q.; Qin, D.-n.; Kou, C.-Z.; Zhang, C.-M.; Guo, M.; Guo, Z.-R.; Chi, X.; Ting, M.-L. Effects of embryonic exposure to polychlorinated biphenyls on zebrafish (Danio rerio) retinal development. J. Appl. Toxicol. 2011, 32, 186–193. [Google Scholar] [CrossRef]
  44. Pereira, P.; Raimundo, J.; Araujo, O.; Canario, J.; Almeida, A.; Pacheco, M. Fish eyes and brain as primary targets for mercury accumulation—A new insight on environmental risk assessment. Sci. Total Environ. 2014, 494–495, 290–298. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Pereira, P.; Raimundo, J.; Canario, J.; Almeida, A.; Pacheco, M. Looking at the aquatic contamination through fish eyes—A faithful picture based on metals burden. Mar. Pollut. Bull. 2013, 77, 375–379. [Google Scholar] [CrossRef] [PubMed]
  46. Soares, P.; Andrade, A.d.; Santos, T.; Silva, S.d.; Silva, J.d.; Santos, A.d.; Souza, E.S.; Cunha, F.d.; Teixera, V.; Cadena, M.; et al. Acute and chronic toxicity of the benxoylurea pesticide, lufenuron, in the fish Colossoma macropomum. Chemosphere 2016, 161, 412–421. [Google Scholar] [CrossRef]
  47. Hong, X.; Zha, J. Fish behavior: A promising model for toxicology research. Sci. Total Environ. 2019, 686, 311–321. [Google Scholar] [CrossRef] [PubMed]
  48. Bu, H.; Song, X.; Zhang, Q.; Burford, M. Strontium concentrations and isotope ratios in a forest-river system in the South Qinling Mts. China. Water Res. 2016, 93, 91–97. [Google Scholar] [CrossRef] [PubMed]
  49. Goguel, R.; St John, D. Chemical identification of Portland cements in New Zealand concretes. Cem. Concr. Res. 1993, 23, 59–68. [Google Scholar] [CrossRef]
  50. Connor, N.; Sarraino, S.; Frantz, D.; Bushaw-Newton, K.; MacAvoy, S. Geochemical characteristics of an urban river: Influences of an anthropogenic landscape. Appl. Geochem. 2014, 47, 209–216. [Google Scholar] [CrossRef]
  51. Loro, V.; Wood, C. The roles of calcium and salinity in protecting against physiological symptoms of waterborne zinc toxicity in the euryhaline killifish (Fundulus heteroclitus). Comp. Biochem. Physiol. Part C 2022, 261, 109422. [Google Scholar] [CrossRef]
  52. Maybeck, M. Global occurrence of major elements in rivers. In Surface and Ground Water, Weathering, and Soils; Drever, J., Ed.; Treatise on Geochemistry; Elsevier-Pergamon: Oxford, UK, 2005; pp. 207–233. [Google Scholar]
  53. Davidson, J.; Good, C.; Welsch, C.; Summerfelt, S. Comparing the effects of high v. low nitrate on the health, performance, and welfare of juvenile rainbow trout Oncorhynchus mykiss within water recirculating aquaculature systems. Aquacult Eng. 2014, 59, 30–40. [Google Scholar] [CrossRef] [Green Version]
  54. Garcia-Jaramillo, M.; Beaver, L.; Truong, L.; Axton, E.; Keller, R.; Prater, M.; Magnusson, K.; Tanguay, R.; Stevens, J.; Hord, N. Nitrate and nitrite exposure leads to mild anxiogenic-like behavior and alters brain metabolomic profile in zebrafish. PLoS ONE 2020, 15, e0240070. [Google Scholar] [CrossRef]
  55. Cederberg, T.; Jensen, L. Siloxanes in Silocone Products Intended for Food Contact: Selected Samples from the Norwegian Market in 2016; National Food Institute, Technical University of Denmark: Kgs Lyngby, Denmark, 2017. [Google Scholar]
  56. Mojsiewicz-Pieńkowska, K.; Jamrógiewicz, M.; Szymkowska, K.; Krenczkowska, D. Direct Human Contact with Siloxanes (Silicones)—Safety or Risk Part 1. Characteristics of Siloxanes (Silicones). Front. Pharmacol. 2016, 7, 132. [Google Scholar] [CrossRef] [Green Version]
  57. Hong, W.-J.; Jia, H.; Liu, C.; Zhang, Z.; Sun, Y.; Li, Y.-F. Distribution, source, fate and bioaccumulation of methyl siloxanes in marine environment. Environ. Pollut. 2014, 191, 175–181. [Google Scholar] [CrossRef]
  58. Kirkegaard, A.; Bignert, A.; McLachlan, M. Cyclic volatile methylsiloxanes in fish from the Baltic Sea. Chemosphere 2013, 93, 774–778. [Google Scholar] [CrossRef] [PubMed]
  59. Lassen, C.; Hansen, C.L.; Mikkelsen, S.H.; Maag, J. Siloxanes-consumption, toxicity and alternatives. Environ. Proj. 2005, 1031, 1–111. [Google Scholar]
  60. Luo, Y.; Yuan, T.; Wang, W.; Kannan, K. Concentrations and assessment of exposure to siloxanes and synthetic musks in personal care products from China. Environ. Pollut. 2011, 159, 3522–3528. [Google Scholar] [CrossRef] [PubMed]
  61. Wang, D.-G.; Norwood, W.; Alaee, M.; Byer, J.; Brimble, S. Review of recent advances in research on the toxicity, detection, and occurrence and fate of cyclic volatile methyl siloxanes in the environment. Chemosphere 2013, 93, 711–725. [Google Scholar] [CrossRef]
  62. Guo, W.; Dai, Y.-J.; Chu, X.; Cui, S.; Sun, Y.; Li, Y.-F.; Jia, H. Assessment bioaccumulation factor (BAF) of methyl siloxanes in crucian carp (Carassius auratus) around a siloxane production factory. Ecotoxicol. Environ. Saf. 2021, 213, 111983. [Google Scholar] [CrossRef]
  63. Pelletier, M.; Isabel, L.; Armellin, A.; McDaniel, T.; Martin, P.; McGoldrick, D.; Clark, M.; Moore, S. Influence of wastewater effluents on the bioaccumulation of volatile methylsiloxanes in the St. Lawrence River. Sci. Total Environ. 2022, 806, 151267. [Google Scholar] [CrossRef]
  64. Radermacher, G.; Rudel, H.; Wesch, C.; Bohnhardt, A.; Koschorrek, J. Retrospective analysis of cyclic volatile methylsiloxanes in archived German fish samples covering a period of two decades. Sci. Total Environ. 2020, 706, 136011. [Google Scholar] [CrossRef] [PubMed]
  65. Sanchis, J.; Llorca, M.; Pico, Y.; Farre, M.; Barcelo, D. Volatile dimethylsiloxanes in market seafood and freshwater fish from the Xuquer River, Spain. Sci. Total Environ. 2016, 545–546, 236–243. [Google Scholar] [CrossRef] [PubMed]
  66. Wang, W.; Cho, H.-S.; Kim, K.; Park, K.; Oh, J.-E. Tissue-specific distribution and bioaccumulation of cyclic and linear siloxanes in South Korean crucian carp (Carassius carassius). Environ. Pollut. 2021, 288, 117789. [Google Scholar] [CrossRef] [PubMed]
  67. Warner, N.; Nost, T.; Andrade, H.; Christensen, G. Allometric relationships to liver tissue concentrations of cyclic volatile methyl siloxanes in Atlantic cod. Environ. Pollut. 2014, 190, 109–114. [Google Scholar] [CrossRef]
  68. Xue, X.; Jia, H.; Xue, J. Bioaccumulation of methyl siloxanes in common carp (Cyprinis carpio) and in an estuarine food web in Northeastern China. Arch. Environ. Contam. Toxicol. 2019, 76, 498–507. [Google Scholar] [CrossRef]
  69. Rucker, C.; Kummerer, K. Environmental Chemistry of Organosiloxanes. Chem. Rev. 2014, 115, 4660524. [Google Scholar] [CrossRef]
  70. McGoldrick, D.; Letcher, R.; Barresi, E.; Kieir, M.; Small, J.; Clark, M.; Sverko, E.; Backus, S. Organophosphate flame retardants and organosiloxanes in predatory freshwater fish from locations across Canada. Environ. Pollut. 2014, 193, 254–261. [Google Scholar] [CrossRef]
  71. Katz, E.; LUnderberg, D.; Brown, W.; Day, D.; Jimenez, J.; Nazaroff, W.; Goldstein, A.; DeCarlo, P. Large emissions of low-volatility siloxanes during residential oven use. Environ. Sci. Technol. Lett. 2021, 8, 519–524. [Google Scholar] [CrossRef]
  72. Fromme, H.; Witte, M.; Fembacher, L.; Gruber, L.; Hagl, T.; Smolic, S.; Fiedler, D.; Sysoltseva, M.; Schober, A. Siloxane in baking moulds, emission to indoor air and migration to food during baking with an electrick oven. Environ. Int. 2019, 126, 145–152. [Google Scholar] [CrossRef]
  73. Lee, D.; Park, M.-K.; Lee, I.-S.; Choi, S.-D. Contamination characteristics of siloxanes in coastal sediment collected from industrialized bays in South Korea. Ecotoxicol. Environ. Saf. 2019, 182, 109457. [Google Scholar] [CrossRef] [PubMed]
  74. Schmitt, E.; Dowling, J. Early retinal development in the zebrafish, Danio rerio: Light and electron microscopic analyses. J. Comp. Neurol. 1999, 404, 515–536. [Google Scholar] [CrossRef]
  75. Branchek, T.; Bremiller, R. The development of photoreceptors in the zebrafish, Brachydanio rerio. I. Structure. J. Comp. Neurol. 1984, 224, 107–115. [Google Scholar] [CrossRef]
  76. Morris, A.; Fadool, J. Studying rod photoreceptor development in zebrafish. Physiol. Behav. 2005, 86, 306–313. [Google Scholar] [CrossRef] [Green Version]
  77. Bilotta, J.; Saszik, S.; Sutherland, S. Rod contributions to the electroretinogram of the dark-adapted developing zebrafish. Dev. Dyn. 2001, 222, 564–570. [Google Scholar] [CrossRef]
  78. Golla, A.; Ostby, H.; Kermen, F. Chronic unpredictable stress induces anxiety-like behaviors in young zebrafish. Sci. Rep. 2020, 10, 10339. [Google Scholar] [CrossRef]
  79. Al Shuraiqi, A.; Al-Habsi, A.; Berry, M. Time-, dose- and transgenerational effects of fluoxetine on the behavioural responses of zebraafish to a conspecific alarm substance. Environ. Pollut. 2021, 270, 116164. [Google Scholar] [CrossRef] [PubMed]
  80. Renieri, E.; Sfakianakis, D.; Alegakis, A.; Safenova, I.; Buha, A.; Matovic, V.; Tzardi, M.; Dzantiev, B.; Divanach, P.; Kentouri, M.; et al. Nonlinear responses to waterborne cadmium exposure in zebrafish. An In Vivo study. Environ. Res. 2017, 157, 173–181. [Google Scholar] [CrossRef] [PubMed]
  81. Suryanto, M.; Audira, G.; Uapipatanakul, B.; Hussain, A.; Saputra, F.; Siregar, P.; Chen, K.-C.; Hsiao, C.-D. Antidepressant screen demonstrated non-monotonic responses to amitriptyline, amoxapine and sertraline in locomotor activity assay in larval zebrafish. Cells 2021, 10, 738. [Google Scholar] [CrossRef] [PubMed]
  82. Houde, E. Differences between marine and freshwater fish larvae: Implications for recruitment. ICES J. Mar. Sci. 1994, 51, 91–97. [Google Scholar] [CrossRef]
Water 15 02372 g001 550
Figure 1. Morphological measurements of larvae raised in filtered water from Paint Branch stream (PBS) or control water. Notochord length (a) and eye diameter (b) were measured from a subset of larvae (n = 5 per treatment) collected at each time point. Age-dependent increases in notochord length were observed. No significant differences in eye diameter were observed, though measurements were smaller at 21 and 28 dpf (days postfertilization). Values are means ± SE. Bars with the same letters are not significantly different.
Figure 1. Morphological measurements of larvae raised in filtered water from Paint Branch stream (PBS) or control water. Notochord length (a) and eye diameter (b) were measured from a subset of larvae (n = 5 per treatment) collected at each time point. Age-dependent increases in notochord length were observed. No significant differences in eye diameter were observed, though measurements were smaller at 21 and 28 dpf (days postfertilization). Values are means ± SE. Bars with the same letters are not significantly different.
Water 15 02372 g001
Water 15 02372 g002 550
Figure 2. Morphological analysis of larval growth. Following measurements, larvae from each exposure age and treatment group were embedded in paraffin, sectioned, and labeled using H&E. Adjacent sections of the same larva are combined to view the whole specimen. There is a clear increase in growth with age (7 days postfertilization, dpf, to 28 dpf), supporting the observed morphological measurements.
Figure 2. Morphological analysis of larval growth. Following measurements, larvae from each exposure age and treatment group were embedded in paraffin, sectioned, and labeled using H&E. Adjacent sections of the same larva are combined to view the whole specimen. There is a clear increase in growth with age (7 days postfertilization, dpf, to 28 dpf), supporting the observed morphological measurements.
Water 15 02372 g002
Water 15 02372 g003 550
Figure 3. Morphological analysis of eye development. We see no qualitative differences in eye morphology at any of the subsampling ages (7 days postfertilization, dpf, 14 dpf, 21 dpf, and 28 dpf), and all retinal layers are evident. Top image shows the different retinal layers assessed: total retinal thickness, ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer (INL), outer plexiform layer (OPL), and photoreceptor layer (PL). Measurements were performed from central retina, behind the lens.
Figure 3. Morphological analysis of eye development. We see no qualitative differences in eye morphology at any of the subsampling ages (7 days postfertilization, dpf, 14 dpf, 21 dpf, and 28 dpf), and all retinal layers are evident. Top image shows the different retinal layers assessed: total retinal thickness, ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer (INL), outer plexiform layer (OPL), and photoreceptor layer (PL). Measurements were performed from central retina, behind the lens.
Water 15 02372 g003
Water 15 02372 g004 550
Figure 4. Quantification of retinal layer thicknesses. To assess potential changes in eye structure, individual retinal layers were measured for the following: (a) total retinal thickness, (b) ganglion cell layer—GCL, (c) inner plexiform layer—IPL, (d) inner nuclear layer—INL, (e) outer plexiform layer—OPL, and (f) photoreceptor layer—PL. Significant age-dependent differences were noted for (a) overall retinal thickness, (c) IPL, and (f) PL. For all these measurements, values at 7 dpf were significantly smaller than values at 14, 21, and 28 dpf. INL thickness (d) was significantly affected by the treatment (p = 0.042, asterisk), though subsequent analysis did not identify the cause of this significance. Values are presented as means ± SE. Measurements were performed with 3–6 larvae per age per treatment. Bars with the same letters are not significantly different.
Figure 4. Quantification of retinal layer thicknesses. To assess potential changes in eye structure, individual retinal layers were measured for the following: (a) total retinal thickness, (b) ganglion cell layer—GCL, (c) inner plexiform layer—IPL, (d) inner nuclear layer—INL, (e) outer plexiform layer—OPL, and (f) photoreceptor layer—PL. Significant age-dependent differences were noted for (a) overall retinal thickness, (c) IPL, and (f) PL. For all these measurements, values at 7 dpf were significantly smaller than values at 14, 21, and 28 dpf. INL thickness (d) was significantly affected by the treatment (p = 0.042, asterisk), though subsequent analysis did not identify the cause of this significance. Values are presented as means ± SE. Measurements were performed with 3–6 larvae per age per treatment. Bars with the same letters are not significantly different.
Water 15 02372 g004
Water 15 02372 g005 550
Figure 5. Total distance and angular velocity measurements. Total distance and angular velocity measurements of zebrafish larvae reared in filtered water from Paint Branch stream (PBS, white bars) until aged 7, 14, 21, or 28 days postfertilization (dpf). (a) Angular velocity measurements were significantly affected by age (p < 0.001) but no main effects of treatment (p = 0.668) and no significant interaction (p = 0.057) were observed. For (b) total distance traveled, it was mainly affected by age (p < 0.001), but no main effects of treatment were observed (p = 0.852), though fish raised in PBS water moved significantly less at 14 dpf (asterisk). The significant interactive effect (p = 0.002) likely comes from the decrease in distance moved at 14 dpf. Values are means ± SE. Bars with the same letters are not significantly different.
Figure 5. Total distance and angular velocity measurements. Total distance and angular velocity measurements of zebrafish larvae reared in filtered water from Paint Branch stream (PBS, white bars) until aged 7, 14, 21, or 28 days postfertilization (dpf). (a) Angular velocity measurements were significantly affected by age (p < 0.001) but no main effects of treatment (p = 0.668) and no significant interaction (p = 0.057) were observed. For (b) total distance traveled, it was mainly affected by age (p < 0.001), but no main effects of treatment were observed (p = 0.852), though fish raised in PBS water moved significantly less at 14 dpf (asterisk). The significant interactive effect (p = 0.002) likely comes from the decrease in distance moved at 14 dpf. Values are means ± SE. Bars with the same letters are not significantly different.
Water 15 02372 g005
Water 15 02372 g006 550
Figure 6. Treatment significantly affected where zebrafish larvae were in the recording chamber. Overall, larvae spent more time at the edge of the dish (a) compared to the center (b). Time spent at the edge (a) was significantly affected by treatment (p = 0.001), and there was a significant treatment*age interaction (p = 0.006). Time at the age increased at 21 and 28 dpf for PBS-treated larvae, with significance noted at 21 dpf (asterisk). (b) Time in the center was also significantly affected by treatment (p = 0.016), and a treatment*age interaction was observed (p = 0.002), with larvae reared in PBS water spending significantly less time in the center at 21 dpf (asterisk). Treatment significantly affected frequency of visits to the edge (c) (p = 0.001) versus the center of the dish (d), as did age (p < 0.001). PBS-treated larvae made significantly fewer visits to the edge (c) at 7, 14, and 21 dpf (asterisks). Fewer visits to the center were also noted at 14 and 21 dpf (d).
Figure 6. Treatment significantly affected where zebrafish larvae were in the recording chamber. Overall, larvae spent more time at the edge of the dish (a) compared to the center (b). Time spent at the edge (a) was significantly affected by treatment (p = 0.001), and there was a significant treatment*age interaction (p = 0.006). Time at the age increased at 21 and 28 dpf for PBS-treated larvae, with significance noted at 21 dpf (asterisk). (b) Time in the center was also significantly affected by treatment (p = 0.016), and a treatment*age interaction was observed (p = 0.002), with larvae reared in PBS water spending significantly less time in the center at 21 dpf (asterisk). Treatment significantly affected frequency of visits to the edge (c) (p = 0.001) versus the center of the dish (d), as did age (p < 0.001). PBS-treated larvae made significantly fewer visits to the edge (c) at 7, 14, and 21 dpf (asterisks). Fewer visits to the center were also noted at 14 and 21 dpf (d).
Water 15 02372 g006
Table
Table 1. Water chemistry analysis of samples collected from Paint Branch stream in Fall 2020. Values for both nutrients (measured at characteristic wavelengths using ICP-AES (see methods)) and general water parameters are given. ND = not detected = 0.00 mg/L. Water quality analysis was performed by Cornell Nutrient Analysis Lab.
Table 1. Water chemistry analysis of samples collected from Paint Branch stream in Fall 2020. Values for both nutrients (measured at characteristic wavelengths using ICP-AES (see methods)) and general water parameters are given. ND = not detected = 0.00 mg/L. Water quality analysis was performed by Cornell Nutrient Analysis Lab.
ParameterValue
pH7.98
soluble salts0.4 mmho/cm
hardness107 mg eq CaCO3/L
SAR0.9 mmol/L
Element/Nutrient
(wavelength in nm)		concentration
(mg/L)
Al (396.152 nm)0.08
As (189.042 nm)ND
B (249.677 nm)ND
Ba (455.404 nm)0.07
Be (313.042 nm)ND
Ca (317.933 nm)27.5
Cd (214.438 nm)ND
Co (228.616 nm)ND
Cr (267.716 nm)ND
Cu (324.754 nm)ND
Fe (259.941 nm)ND
K (766.491 nm)4.6
Li (670.780 nm)0.02
Mg (279.079 nm)9.3
Mn (257.611 nm)ND
Mo (202.095 nm)ND
Na (589.592 nm)20.6
Ni (231.604 nm)ND
P (213.618 nm)0.2
Pb (220.353 nm)ND
S (182.034 nm)3.8
Si (212.412 nm)3.6
Sr (407.771 nm)0.1
Ti (334.941 nm)ND
V (292.464 nm)ND
Zn (213.856 nm)0.01
NH4-N0.05
NO3, NO2-N1.2
Table
Table 2. Summary of behavioral results. Changes in swimming behaviors (left) were assessed by comparing responses of larvae raised in filtered water collected from Paint Branch stream (PBS) with control larvae (C) maintained in system water until 7, 14, 21, or 28 days postfertilization (dpf). NS indicates no significant difference in the observed behavior. > indicates which treatments resulted in significantly greater values, with parameters showing significance highlighted in bold.
Table 2. Summary of behavioral results. Changes in swimming behaviors (left) were assessed by comparing responses of larvae raised in filtered water collected from Paint Branch stream (PBS) with control larvae (C) maintained in system water until 7, 14, 21, or 28 days postfertilization (dpf). NS indicates no significant difference in the observed behavior. > indicates which treatments resulted in significantly greater values, with parameters showing significance highlighted in bold.
Behavior Assessed7 dpf14 dpf21 dpf28 dpf
Total distance movedNS
p = 0.841		C > PBS
p = 0.015		NS
p = 0.868		NS
p = 0.474
Angular velocityPBS > C
p = 0.001		NS
p = 0.15		NS
p = 0.266		NS
p = 0.312
Time in center of dishNS
p = 0.668		NS
p = 0.995		C > PBS
p < 0.001		NS
p = 0.754
Visits to centerNS
p = 0.793		C > PBS
p = 0.05		C > PBS
p < 0.001		NS
p = 0.745
Time at edge of dishNS
p = 0.072		NS
p = 0.503		PBS > C
p < 0.001		NS
p = 0.752
Visits to edgeC > PBS
p = 0.01		C > PBS
p < 0.001		C > PBS
p = 0.038		NS
p = 0.782
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Malik, S.; Cohen, A.; MacAvoy, S.E.; Connaughton, V.P. The Importance of Assessing Water Quality in Tributaries: A Case Study in an Urban Waterway Using Zebrafish (Danio rerio). Water 2023, 15, 2372. https://doi.org/10.3390/w15132372

AMA Style

Malik S, Cohen A, MacAvoy SE, Connaughton VP. The Importance of Assessing Water Quality in Tributaries: A Case Study in an Urban Waterway Using Zebrafish (Danio rerio). Water. 2023; 15(13):2372. https://doi.org/10.3390/w15132372

Chicago/Turabian Style

Malik, Sabine, Annastelle Cohen, Stephen E. MacAvoy, and Victoria P. Connaughton. 2023. "The Importance of Assessing Water Quality in Tributaries: A Case Study in an Urban Waterway Using Zebrafish (Danio rerio)" Water 15, no. 13: 2372. https://doi.org/10.3390/w15132372

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop