Environmental Characteristics of Select Managed Ponds in the Sacramento–San Joaquin Delta: Implications for Native Fish Conservation and Research

Open-File Report 2025-1040
Prepared in cooperation with Metropolitan Water District and State Water Contractors
By: , and 

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Acknowledgments

Funding was provided by Metropolitan Water District and State Water Contractors. U.S. Geological Survey staff Justin Clause, Matthew De Parsia, Jeff Gronemyer, Anthony Martinez, Danielle Palm, Matthew Uychutin, Veronica Violette, and Mitch Zheng assisted with fieldwork.

Abstract

The use of wetlands to support native fish research and conservation efforts in the Sacramento–San Joaquin Delta (Delta) of California is a growing priority. The purpose of our study was to examine the physiochemical and biological characteristics of select managed ponds in the Delta to determine if they would be suitable habitats for research involving the conservation of delta smelt (Hypomesus transpacificus). We studied 10 managed ponds distributed across the central part of the Delta situated on Bacon Island and Bouldin Island in San Joaquin County, and Holland Tract and Webb Tract islands in Contra Costa County. The managed ponds had a diversity of physical habitat configurations and were not directly connected to waterways surrounding the islands and, therefore, not affected by tides. We studied the managed ponds from approximately November 2021 to December 2023 to assess water quality, zooplankton, fish, and pesticide metrics. Water levels in the managed ponds were managed to varying degrees and were mostly independent of climate-driven wet-dry seasonality. Water quality conditions varied among ponds and were independent of geographic location. Overall, mean monthly chlorophyll a concentration ranged from 15 to 57 (mean=30) micrograms per liter (µg/L), dissolved oxygen concentration ranged from 4 to 9 (mean=7) milligrams per liter (mg/L), pH was 8, salinity was 1 practical salinity units (PSU), specific conductance ranged from 1,202 to 1,839 (mean=1,471) microsiemens per centimeter (µS/cm), and turbidity ranged from 13 to 24 (mean=19) Formazin Nephelometric Units (FNU). Water temperature thresholds that contribute to stress (21 degrees Celsius [°C]) and mortality (28 °C) of delta smelt were often exceeded during summer and fall, though vertical stratification contributed to lower bottom temperatures in the deepest managed ponds, which could potentially provide thermal refugia for delta smelt so long as dissolved oxygen concentrations are suitable. Zooplankton populations were broadly similar among managed ponds and included calanoid and cyclopoid copepods that would be suitable prey for delta smelt. Overall average total zooplankton biomass, as measured with a Schindler-Patalas trap, was 0.6 µg/L (min=0, max=63.6) and peaked during spring at more than 4 µg/L. Fish populations highly varied among the managed ponds with potential predators of delta smelt such as largemouth bass (Micropterus salmoides) and black crappie (Pomoxis nigromaculatus) present in several of the managed ponds; predator distribution among ponds seemed to have been driven primarily by deliberate stocking to facilitate local fisheries. Measured pesticide concentrations were below U.S. Environmental Protection Agency Aquatic Life Benchmarks except for exceedances of three compounds (diuron [herbicide], clothianidin [insecticide], and deltamethrin [pyrethroid insecticide]) in samples collected from ponds on Bouldin Island and Webb Tract. Overall, most managed ponds seemed suitable to support delta smelt, though physical control of potential predators and summer temperature might be needed. The results provide guidance on how to engineer and manage new managed ponds to support research and conservation efforts for delta smelt and other native fishes.

Introduction

The Sacramento–San Joaquin Delta (Delta) of California was historically a vast inland wetland system (Whipple and others, 2012). Land surface elevation of wetlands kept pace with sea level rise and produced organic peat soils up to 20 meters (m) in depth (Drexler, 2011). The natural system was heavily disturbed and altered starting in the late 1800s when about 95 percent of Delta wetlands were diked and drained to create “islands” for agricultural use (Drexler and others, 2009; Whipple and others, 2012). The drainage of wetlands and associated agricultural practices have contributed to the loss of peat soils and resulted in land surface subsidence up to 7 m below sea level on Delta islands (Weir, 1950; Prokopovich, 1985; Deverel and Rojstaczer, 1996; Lund and others, 2007). This habitat alteration and land subsidence has greatly affected the Delta’s ecology, increased carbon emissions, and, at present, pose a substantial threat to the integrity of the levees built to create the islands (Lund and others, 2007).

Restoration has been conceived as a tool to mitigate the loss of historic wetlands. Restoration in the form of creating managed impounded wetlands on Delta islands has the potential to halt oxidative loss of peat soils and may accrete organic matter, thereby gaining land surface elevation (Miller and others, 2008; Miller and Fujii, 2011). Restored wetlands also may play an important but complicated role for mitigating the effects of climate change. Converting drained peat soils to wetlands can sequester carbon but also may generate high methane emissions (Hemes and others, 2019; Arias-Ortiz and others, 2021). Results of studies of restored experimental wetlands on Delta islands indicate climate benefits are highly variable and may take upwards of two to eight decades to generate net positive greenhouse gas benefits (Deverel and others, 2014; Chamberlain and others, 2018). Considering slow and uncertain land surface elevation gains and climate benefits, there is interest in identifying additional beneficial uses of restored wetlands on Delta islands for conservation purposes. One such purpose under consideration is to use managed wetland ponds as tools to support native fish conservation efforts. A fundamental first step for this effort is examining managed pond habitat characteristics to assess their suitability to support native fish.

The purpose of our study was to examine the physiochemical and biological characteristics of select managed ponds on Delta islands to determine if they would be suitable habitats for studies focused on the conservation of delta smelt (Hypomesus transpacificus). Delta smelt is an imperiled species thought to be on the brink of extinction (Moyle and others, 2016; Hobbs and others, 2017). Recovery of delta smelt is important, among many reasons, because its critical habitat, the Delta, is a key component of California’s water supply and is subject to management actions to protect delta smelt that may affect water supply (Moyle and others, 2018). Supplementation of the wild delta smelt population with artificially propagated fish is considered a vital step in preventing extirpation from the wild (Lessard and others, 2018; Hung and others, 2019). Opportunities for research and rearing of artificially propagated delta smelt are currently limited (Lindberg and others, 2013). Our objective was to determine if managed ponds on Delta islands could be useful tools for research and development aspects of delta smelt reintroduction. One potential application would be to expand the limited existing infrastructure by using managed ponds to rear artificially propagated delta smelt before their release into Delta sloughs or channels (Maynard and others, 2004; Garlock and others, 2014).

Study Area

Our study involved a total of 10 managed ponds distributed across four separate central Delta islands: Bacon Island, Bouldin Island, Holland Tract, and Webb Tract (fig. 1). The managed ponds do not have official names, so we refer to them in a geographical context (Bacon North, and so on; table 1; fig. 1). The managed ponds have a variety of origins, including (1) borrow pits that were created from excavation of material used to repair levees (Bouldin East and Bouldin West), (2) eroded depressions that were not reclaimed after island flooding caused by levee breaks (Holland North), and (3) habitats created and managed for a variety of recreation and conservation purposes (Bacon North, Bacon South, Holland Middle, Holland South, Webb North, Webb Middle, and Webb East). The managed ponds had a diversity of physical configurations (table 1). They ranged in perimeter length from 470 m (Holland Middle) to 2,089 m (Webb East), ranged in surface area from 0.9 hectares (ha; Holland Middle) to 9.1 ha (Bacon North), and ranged in maximum depth from 0.7 m (Holland Middle) to 5.3 m (Bouldin East; table 1). Agriculture was the dominant land use on all islands, and pond perimeters were variably (0 to 100 percent) buffered from agricultural activities by riparian habitat that was broadly characterized into two groups: (1) tules, including other emergent wetland vegetation; and (2) forest, including cottonwoods, willows, and other woody plants (table 1). The managed ponds were not directly connected to sloughs surrounding the islands and were, therefore, not affected by tides. Water levels in the managed ponds were managed to varying degrees for different purposes based on land use activities on specific islands. Water is transported on and off the islands from adjacent sloughs via pumps and can be moved within islands through small canals and other infrastructure; water management activities are not documented quantitatively, and therefore, specific corresponding data are not available. Thus, water depth and associated volume was variable and largely independent of climatic wet-dry seasonality (fig. 2). The Holland Middle and South ponds, which lack inlet/outlet canals, dried up during this study.

1.	The study sites are on four islands in the Sacramento–San Joaquin Delta.
Figure 1.

A, Location of the Sacramento–San Joaquin Delta in California; B, study area within the Sacramento–San Joaquin Delta; and C, managed pond study sites.

Table 1.    

Managed pond study site physical characteristics within the Sacramento–San Joaquin Delta in California.

[ha, hectare; m, meter; %, percentage]

Managed pond Perimeter
(m)
Surface area
(ha)
Depth
(m)
Riparian habitat composition (%)
Agriculture Tules Forest
Bacon North 1,692 9.1 4.2 59 0 41
Bacon South 852 2.9 5.1 37 63 0
Bouldin East 881 4.2 5.3 22 67 11
Bouldin West 1,336 9.6 3.6 61 39 0
Holland Middle 470 0.9 0.7 0 69 31
Holland North 1,449 4.1 3.7 0 27 73
Holland South 1,055 2.5 2.4 0 38 62
Webb East 2,089 1.9 1.8 3 56 41
Webb Middle 850 2.6 0.8 27 55 18
Webb North 1,214 6.3 1.1 15 59 26
Table 1.    Managed pond study site physical characteristics within the Sacramento–San Joaquin Delta in California.
2.	Water levels in the managed ponds were variable over time.
Figure 2.

Water depth time series for managed pond study sites within the Sacramento–San Joaquin Delta in California. The Holland Middle and Holland South Pond study sites do not have complete time series because they dried up during the study.

Methods

We sought to generate a comprehensive baseline assessment of the overall physiochemical and biological characteristics of each managed pond. Our approach involved characterizing aspects of (1) water quality parameters using a combination of continuous and discrete measurements; (2) pesticide concentrations (the primary contaminants of concern) in water, suspended sediment, and bed sediment of managed ponds and adjoining inlet/outlet canals; (3) zooplankton species composition and density; and (4) fish occupancy. The study period was from November 2021 to December 2022.

Water Quality

Various water quality parameters were measured during the duration of the full study period. This included continuous (every 15 minutes) measurements of water temperature (in degrees Celsius [°C]) recorded by HOBO Pro v2 data loggers (Onset, Bourne, Massachusetts). Data loggers were positioned at the approximate center of each managed pond, near the surface and bed of managed ponds greater than 1.5 m in depth (Bacon North, Bacon South, Bouldin East, Bouldin West, Holland North, and Webb East) and only at mid-depth (0.75 m) in managed ponds less than 1.5 m in depth (app. 1; table 1). Discrete measurements of water temperature (°C), dissolved oxygen concentration in milligrams per liter (mg/L), specific conductance in microsiemens per centimeter (µS/cm), salinity in practical salinity units (PSU), turbidity in Formazin Nephelometric Units (FNU), chlorophyll a concentration in micrograms per liter (µg/L), and pH were obtained from handheld YSI EXO2 sondes (Yellow Springs Instruments, Yellow Springs, Ohio). Discrete measurements were made approximately every 2 weeks at the same locations within ponds where the HOBO loggers were positioned.

Additional water quality parameters were measured seasonally, once during winter and once during summer, to characterize baseline conditions. In these seasonal events, we measured concentrations of nutrients (ammonia, nitrate, nitrite, total nitrogen, organic nitrogen, and orthophosphate), metals (barium, calcium, magnesium, manganese, selenium, strontium, and zinc), sediment (suspended), dissolved organic carbon (DOC), chlorophyll a and pheophytin a, and inorganic aspects of water quality (silica and hardness). Water samples for analysis were collected with a Van Dorn sampler at the same locations and depths within ponds where the HOBO loggers were positioned. Water samples for suspended sediment analysis were collected in 1-liter (L) plastic bottles, stored at room temperature, and analyzed at the U.S. Geological Survey (USGS) Sediment Lab in Santa Cruz, Calif. Water samples collected for chlorophyll a, metals, and nutrients were stored on wet ice (less than 24 hours) and refrigerated until filtered in the laboratory. Chlorophyll a samples were prepared by filtering sample water over a 47 millimeter (mm) diameter, 1.7-micrometer (µm) pore size, pre-combusted glass fiber filter. Water samples for metals, nutrients, and dissolved organic carbon analyses were filtered through a 0.45-µm Pall capsule filter using a peristaltic pump. Water samples for metal analysis were collected in a 250-milliliter (mL) acid-rinsed clear polyethylene bottle and preserved with 2 mL of 7.5 normal (N) nitric acid (Ultrex HNO3). Water samples for nutrient analysis were collected in 125-mL amber-plastic bottles. Water samples for DOC analysis were collected in 125-mL glass-amber bottles and preserved with 1 mL of 4.5 N sulfuric acid (H2SO4). Chlorophyll a, metals, nutrients, and DOC samples were analyzed by the USGS National Water Quality Laboratory in Denver, Colorado.

Pesticides

Pesticides were assessed at three separate sampling events, which we term surveys, occurring in March 2022, June 2022, and February 2023. Survey periods were chosen to represent wet and dry seasons. Water, suspended sediment, and bed sediment samples were collected in each managed pond. Additional water samples were collected from select adjoining inlet/outlet canals (app. 2). Managed pond water samples for pesticide analysis were collected in 1-L amber-glass bottles using a weighted bottle sampler at approximately 0.5 m depth. Managed pond water samples for glyphosate analysis were collected by submerging a 50-ml amber-glass vial to a depth of 0.5 m. Managed pond bed sediment samples were collected using an Ekman dredge. The top 2 centimeters (cm) of depositional sediment collected within the dredge was subsampled using a stainless-steel scoop and placed in 250-ml amber-glass jars. Managed pond inlet water samples were collected by hand submerging 1-L and 50-ml amber-glass bottles below the water surface. Managed pond inlet bed sediment samples were collected using a stainless-steel scoop to transfer the top 2 cm of depositional sediment from multiple sites within 1–3 m of each other into 250-ml amber-glass jars.

All samples were placed on wet ice immediately after collection and delivered to the USGS Organic Chemistry Research Laboratory in Sacramento, Calif., for processing and analysis. Water samples and associated filtered residues (suspended sediment) were processed following established procedures (Gross and others, 2024). Bed sediment samples were processed following Black and others (2023).

Water, suspended sediment, and bed sediment samples were analyzed using liquid chromatography (LC) and gas chromatography (GC) with tandem mass spectrometry (MS/MS) following procedures described in Gross and others (2024). Water samples were analyzed for 178 pesticides, suspended sediment samples were analyzed for 173 pesticides, and bed sediment samples were analyzed for 162 pesticides (app. 3, table 3.1). Samples were analyzed using LC/MS/MS followed by GC/MS/MS. Glyphosate samples were analyzed using an enzyme-linked immunosorbent assay (ELISA) microtiter plate (Gold Standard Diagnostics, Davis, California). Analysis was completed on a ChroMate microplate reader (RayBiotech, Peachtree Corners, Georgia) and the absorbance was read at 450 nanometers (nm). Evaluation was performed using a 4-parameter logistic regression. All samples were analyzed in duplicate, and the reported concentrations were the average of the duplicate readings. Method detection and reporting limits for water and suspended sediment pesticide analyses were determined by U.S. Environmental Protection Agency (EPA) guidelines (U.S. Environmental Protection Agency, 2016) and described in Gross and others (2024). For glyphosate analyses by ELISA, the least detectable dose was 50 nanograms per liter (ng/L) and concentrations less than 75 ng/L are below the reporting limit.

Zooplankton

Zooplankton species composition and density were assessed approximately once per month. Samples to characterize zooplankton were collected using a 12-L Schindler-Patalas plankton trap fitted with a 200-ml dolphin bucket with 61-micron mesh and Nitrex filter net (54-mm cod end, 311-mm long, 63 micron). The Schindler-Patalas trap was used because variable water depth and vegetation density within and among managed ponds made it impossible to collect consistent, standardized samples with other methods, such as nets towed or retrieved through the water column. One sample was collected at a depth of approximately 1 m at the same geographical locations within managed ponds where the HOBO loggers were positioned. Samples were preserved in the field in 10-percent formalin and analyzed by a contractor (EcoAnalysts, Moscow, Idaho).

Fish

Each managed pond was comprehensively surveyed once to determine the presence-absence of individual fish species. One or more sampling gear types and methods—beach seine, gillnet, and boat electrofishing—were used, as feasible, in individual managed ponds based on their physical habitat in attempt to capture all species present. Beach seining was done in Bacon North, Bouldin East, Bouldin West, Holland Middle, and Holland South. Electrofishing was done in Bacon South, Bouldin East, Bouldin West, Holland North, Webb East, Webb Middle, and Webb North. Gillnetting was done in Bouldin East, Bouldin West, Holland North, and Webb East. Sampling was done in March and April 2022. The beach seine measured 6 × 1.2 m with 3-mm mesh. The gillnet measured 45.7 × 1.8 m with five equal length panels of 38-, 51-, 64-, 76-, and 89-mm mesh. Electrofishing was done with a Smith Root Model Generator Powered Pulsator pulsed direct current unit powered by a 5.5-horsepower generator mounted on a 3.6-m aluminum boat. All captured fishes were identified to species and released alive.

Data Analysis

Tabular and graphical summaries of data were constructed to assess patterns of measured parameters within and among ponds during the study period. For example, continuous water temperature data were plotted in time series with reference to temperature threshold values that contribute to stress (21 °C) and mortality (28 °C) of delta smelt (Hung and others, 2022). In two cases, we ran a principal components analysis (PCA) to statistically characterize dominant modes of variability within and among managed pond specific characteristics (R Core Team, 2020). These two cases involved: (1) discrete water quality measurements and (2) zooplankton species composition data. For the water quality PCA, we examined select water quality variables measured each month (temperature, dissolved oxygen concentration, turbidity, specific conductance, chlorophyll concentration, and pH), and included measurements taken at the surface or middle depth of each managed pond. For the zooplankton PCA, we included adult life stages of taxa, which consisted of greater than or equal to 1 percent of the overall total biomass reported across all managed ponds. It is noted that we also ran extensive exploratory modeling of data to identify relationships among specific managed ponds, water quality, zooplankton, and fish but ultimately deemed such analyses uninformative because it was apparent that pond management activities (for example, water level management and fish introductions) overwhelmed natural ecological processes.

Data Availability

Continuous and discrete water quality, zooplankton, and fish data are available in a USGS data release from Buxton and others (2023). Seasonal water quality and pesticide data are available from U.S. Geological Survey (2024). Full site lists are in appendixes 1 and 2.

Results

Water Quality

Continuous water temperature measurements indicated that water temperatures ranged from approximately 8 °C in winter to approximately 30 °C in summer, with patterns that were generally similar among ponds (fig. 3), except for Bacon South at the bottom. Seasonal vertical stratification of temperature was also observed. Bottom temperatures were in general, approximately 2–5 °C cooler than surface temperatures from approximately May to October (fig. 3). The delta smelt temperature stress threshold value of 21 °C was exceeded from May through October at the bottom and surface, with occasional surface exceedances also occurring as early as March and as late as November (table 2; fig. 3). The delta smelt temperature mortality threshold value of 28 °C was exceeded intermittently only at the surface from May through October (table 2; fig. 3).

3.	Seasonal water temperature in the managed ponds closely resembled seasonal patterns
                        in air temperature.
Figure 3.

Maximum daily water temperature time series for surface and bottom of managed ponds greater than 1.5 meters (m) in depth within the Sacramento–San Joaquin Delta in California. Temperature ranges exceeding 21 degrees Celsius (°C) and 28 °C are indicated with colored shading and may potentially contribute to delta smelt stress and mortality, respectively (Hung and others, 2022). Data summarized from Buxton and others (2023).

Table 2.    

Percentage of days that the daily maximum water temperature exceeded delta smelt temperature stress threshold of 21 degrees Celsius (°C) and temperature mortality threshold of 28 °C in managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from Buxton and others (2023).

[≥, greater than or equal to]

Pond Position Percentage of days ≥21 °C
delta smelt
stress threshold
Percentage of days ≥28 °C
delta smelt
mortality threshold
Bacon North Surface 46 6
Bottom 38 0
Bacon South Surface 46 4
Bottom 6 0
Bouldin East Surface 44 9
Bottom 30 0
Bouldin West Surface 41 0
Bottom 35 0
Holland North Surface 48 7
Bottom 32 0
Webb East Surface 47 9
Bottom 38 0
Table 2.    Percentage of days that the daily maximum water temperature exceeded delta smelt temperature stress threshold of 21 degrees Celsius (°C) and temperature mortality threshold of 28 °C in managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from Buxton and others (2023).

Monthly discrete water quality measurements indicated a high degree of variability within and among ponds for all measured parameters (fig. 4). Overall, grand mean monthly (averaged across all ponds) chlorophyll a concentration was 30 µg/L, dissolved oxygen concentration was 7 mg/L, pH was 8, salinity was 1 PSU, specific conductance was 1,471 µS/cm, and turbidity was 19 FNU. Ponds greater than 1.5 m in depth (those in which we had surface and bottom measurements) indicated varying degrees of vertical stratification across all parameters as measured by percent difference of surface-to-bottom values (fig. 5). The most consistent pattern of vertical stratification was with temperature, dissolved oxygen concentration, and pH values being generally higher at surface than at bottom from approximately spring to summer, particularly in the deepest ponds (Bacon South, Bacon North, Holland North, Bouldin East, and Bouldin West; fig. 5). Results of the water quality PCA indicated water quality conditions were independent of geography with varying degrees of similarity among individual managed ponds (table 3; fig. 6). On Bacon Island, Bacon North was generally more turbid with higher pH and specific conductance than Bacon South. Similarly, on Bouldin Island, Bouldin West was generally more turbid with higher pH and specific conductance than Bouldin East. Holland Tract managed ponds indicated generally similar water quality conditions except that Holland Middle and Holland South had elevated salinity and specific conductance. Webb Tract managed ponds indicated the highest similarity in water quality parameters among managed ponds on an individual island.

4.	Variability within and among the ponds in water quality characteristics.
Figure 4.

Water quality time series for managed ponds within the Sacramento–San Joaquin Delta in California. The Holland Middle and Holland South pond study sites do not have complete time series because they dried up during the study. Data summarized from Buxton and others (2023).

5.	Vertical stratification occurred in ponds that were greater than 1.5 meters in
                        depth.
Figure 5.

Water quality time series presented as the percent difference of surface relative to bottom, as an indicator of vertical stratification, for managed ponds greater than 1.5 m in depth within the Sacramento–San Joaquin Delta in California. Positive values indicate a water quality parameter showed higher values at the surface, whereas negative values indicate a water quality parameter showed higher values at the bottom. Data summarized from Buxton and others (2023).

Table 3.    

Results of principal components analysis (PCA) completed separately on the discrete water quality measurements (Water quality PCA) and the zooplankton species composition data (Zooplankton PCA) for managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from Buxton and others (2023).

[PC1, principal component 1; PC2, principal component 2; PC3, principal component 3]

Principal component PC1 PC2 PC3
Eigenvalue 1.4 1.2 1.0
Variance 33 23 17
Temperature 0.29 −0.49 0.48
Dissolved oxygen 0.34 0.58 0.30
Turbidity 0.30 −0.42 −0.67
Specific conductance 0.47 0.34 −0.40
Chlorophyll 0.29 −0.36 0.22
pH 0.63 0.02 0.12
Eigenvalue 1.6 1.5 1.3
Variance 14 13 9
Arctodiaptomus dorsalis 0.31 −0.21 0.29
Diacyclops thomasi 0.37 0.23 −0.29
Acanthocyclops robustus −0.08 0.33 0.04
Leptodiaptomus siciloides −0.06 0.45 −0.18
Daphnia pulex 0.11 −0.21 0.06
Mesocyclops edax 0.23 −0.29 −0.08
Ostracoda −0.37 −0.22 −0.38
Daphnia rosea 0.32 −0.20 −0.13
Daphnia magna −0.28 −0.23 −0.43
Diaptomidae −0.14 −0.27 −0.13
Skistodiaptomus pallidus 0.25 −0.20 −0.26
Bosmina longirostris 0.40 0.02 −0.36
Eurycercus sp. 0.12 −0.08 −0.21
Simocephalus sp. −0.21 −0.13 −0.06
Daphnia galeata mendotae 0.17 −0.20 0.13
Acanthocyclops brevispinosus 0.06 0.27 −0.17
Diaphanosoma brachyurum 0.07 −0.06 0.33
Chydorus sphaericus 0.21 0.24 −0.16
Table 3.    Results of principal components analysis (PCA) completed separately on the discrete water quality measurements (Water quality PCA) and the zooplankton species composition data (Zooplankton PCA) for managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from Buxton and others (2023).
6.	Water quality characteristics were unique to each pond.
Figure 6.

Scores from the first and third axes of a principal components analysis performed on discrete water quality data from managed ponds within the Sacramento–San Joaquin Delta in California. Scores are faceted by island to minimize superimposition and improve clarity. Ellipses are 95-percent confidence levels. Water quality parameters with loadings greater than 0.30 are shown for each axis. Data summarized from Buxton and others (2023).

Seasonal water quality measurements indicated high variability in the measured parameters among managed ponds and islands (table 4). See table 4 for absolute values of all measured parameters. Although overall variability was high, within islands, the measured parameters indicated the highest similarity among ponds on Webb Tract. Holland Middle and Holland South generally indicated the highest values across all non-organic parameters. Holland North indicated the highest concentrations of nutrient parameters (total nitrogen=3.1 mg/L; orthophosphate=0.975 mg/L; ammonia=1.956 mg/L). Among the organic parameters, DOC was highest in Bouldin West (58 mg/L) and chlorophyll a was highest in Bacon North (138.2 µg/L).

Table 4.    

Water quality parameters measured in managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from Buxton and others (2023).

[Values are the average (± one standard deviation) of four measurements: (1) winter, surface, (2) winter, bottom, (3) spring, surface, (4) spring, bottom. Abbreviations: mg/L, milligrams per liter; μg/L, micrograms per liter; —, below detection limits; ±, plus or minus]

Parameter Bacon Island Bouldin Island Holland Tract Webb Tract
Bacon
North
Bacon
South
Bouldin
East
Bouldin
West
Holland
Middle
Holland
North
Holland
South
Webb
East
Webb
Middle
Webb
North
Ammonia (mg/L) 0.354±0.14 0.105±0.06 0.038±0.01 0.071±0.02 1.956±1.5 0.048±0.01 0.079±0.01 0.068±0.01
Nitrate (mg/L) 0.029±0.03
Nitrite (mg/L) 0.003±0 0.003±0 0.003±0
Nitrogen, total (mg/L) 2.0±0.12 1.0±1.04 2.4±0.26 2.3±1.49 1.2 3.1±1.63 1.7 1.0±0.47 1.4 1.8
Organic nitrogen (mg/L) 1.3
Orthophosphate (mg/L) 0.542±0.62 0.345±0.26 0.975±0.75 0.082±0.01 0.242±0.17 0.103±0.07
Barium (µg/L) 63±7.74 46±10.81 83±8.07 93±4.62 65 48±4.14 59 64±19 54 73
Calcium (mg/L) 58±4.83 31±5.64 55±9.21 28±1.7 203 35±1.18 264 30±3.35 44 51
Magnesium (mg/L) 38±4.78 21±2.68 32±5.03 120±15.6 101 22±0.99 147 19±0.45 27 30
Manganese (µg/L) 391±364.54 499±941 446±150 6±3.42 747 370±70.25 714 143±82.58 672 805
Selenium (µg/L) 0.17±0.01 0.15±0.02 0.18±0.04 0.09 0.14
Strontium (µg/L) 503±16.92 244±39.26 493±86 512±65.92 1,540 290±1.63 2,080 240±25.58 364 413
Zinc (µg/L) 4 2
Suspended (mg/L) 56±77.6 11+6.53 11±3.43 31±26.73 64±43.3 27±0.71 34±17.5 35±21.21 51±18.68
Organic carbon (mg/L) 22.2±4.43 5.1±1.58 34.8±6.32 58.0±11.79 19.2 9.6±0.49 28.5 10.1±0.59 21.8 27.2
Chlorophyll a (µg/L) 138.2±199.7 15.8±16.2 10.9±13.28 40.6±20.29 0.4 54.7±56.39 0.7 48.7±34.3 27.1 29.0
Pheophytin a (µg/L) 7.9±2.8 8.8±11.47 2.3±1.05 7.8±3.01 0.9 14.6±9.5 1.1 18.0±3.68 22.3 20.0
Silica (mg/L) 10±5.8 11±3.5 11±0.8 29±2.06 5 25±0.13 4 20±3.29 30 35
Hardness (mg/L) 304±8.6 164±24.56 270±43.6 564±68.5 925 177±7.23 1,270 153±10.12 221 249
Table 4.    Water quality parameters measured in managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from Buxton and others (2023).

Pesticides

A total of 35 pesticides were detected in water samples across all 3 surveys: 10 fungicides, 16 herbicides, and 9 insecticides (fig. 7; U.S. Geological Survey, 2024). The most frequently detected pesticides in water samples were methoxyfenozide (insecticide; 94 percent frequency), glyphosate (herbicide; 86 percent), and hexazinone (herbicide; 59 percent; U.S. Geological Survey, 2024). A total of 5 pesticides were detected in suspended sediment samples (deltamethrin [insecticide], dithiopyr [herbicide], p,p’-DDD [insecticide], p,p’-DDE [insecticide], and pendimethalin [herbicide]); though, in general, pesticide detections in suspended sediment samples were infrequent (fig. 7; U.S. Geological Survey, 2024). A total of 23 pesticides were detected in bed sediment samples (assessed only during Survey 1): 2 fungicides, 7 herbicides, 13 insecticides, and the synergist piperonyl butoxide (fig. 7; U.S. Geological Survey, 2024). The most frequently detected pesticides in bed sediment samples were p,p’-DDE (insecticide; 95 percent frequency), bifenthrin (insecticide; 75 percent), and pendimethalin (herbicide; 75 percent).

7.	Pesticides occurred mostly in water and consisted mostly of herbicides.
Figure 7.

Pesticide concentrations in bed sediment (in nanograms per gram), suspended sediment (in nanograms per gram), and water (in nanograms per liter), by contaminant type, collected from managed ponds within the Sacramento–San Joaquin Delta in California. Concentration values are plotted on a log scale to facilitate visualization. Data summarized from U.S. Geological Survey, 2024.

In general, more pesticides, typically in higher concentrations, were detected in the adjoining inlet/outlet of the managed ponds than in the managed ponds themselves (figs. 7, 8). In water samples, 35 pesticides were detected in adjoining inlet/outlet canals versus 25 in managed ponds. In bed sediment samples, 22 pesticides were detected in adjoining inlet/outlet canals versus 19 in managed ponds. Total combined pesticide concentrations in water samples ranged from 3.7 ng/L at Holland Middle to 6,862 ng/L at the west inlet of Webb Tract East (fig. 8). Maximum concentrations of individual pesticides detected in water samples across sites were typically less than 100 ng/L, with the exception of the herbicides diuron (530 ng/L) at Bouldin East inlet, glyphosate (6,823 ng/L) at the west inlet of Webb East, hexazinone (292 ng/L) at Bacon South inlet, pendimethalin (288.1 ng/L) at Bacon South inlet, the diuron degradate DCPMU (134.3 ng/L) at Bouldin East inlet, and the insecticide methoxyfenozide (170.6 ng/L) at Bouldin East inlet (fig. 8; U.S. Geological Survey, 2024). For nearly all samples, herbicides made up the bulk of the total amount of pesticides, which was overwhelmingly composed of glyphosate (fig. 8). Total pesticide concentrations in water were generally higher for samples collected during Survey 2, although that result was heavily affected by samples from Bouldin Island (fig. 8). Total pesticide concentrations in bed sediment samples ranged from 0.5 to 62.0 nanograms per gram (ng/g) and, in most samples, insecticides made up most of the detections (U.S. Geological Survey, 2024). Pesticide concentrations in suspended sediment samples were generally below the method reporting limit but above the method detection limit for the pesticides detected (U.S. Geological Survey, 2024). Pesticide concentrations in bed sediment samples were generally less than 2 ng/g (fig. 7; U.S. Geological Survey, 2024).

8.	The highest overall concentrations of pesticides occurred on Bouldin Island.
Figure 8.

Total pesticide concentrations in water by contaminant type, collected from managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from U.S. Geological Survey, 2024.

Zooplankton

A total of 46 distinct zooplankton taxa were reported across all ponds (Buxton and others, 2023). Of this total, there were 18 taxa that each made up at least 1 percent of the total biomass (table 5). Numerous rare taxa comprised less than 1 percent of the total biomass. Copepod nauplii or copepodites, which were likely not effectively sampled, were excluded from the analysis. Overall total biomass was dominated by calanoid copepods (order Calanoida; 37.4 percent), cladocerans (order Diplostraca; 28.4 percent), cyclopoid copepods (order Cyclopoida; 29.3 percent), and ostracods (class Ostracoda; 4.9 percent; table 5; fig. 9). Arctodiaptomus dorsalis was the dominant calanoid copepod, Daphnia pulex was the dominant cladoceran, and Diacyclops thomasi was the dominant cyclopoid copepod. Ostracods were not identified to a lower taxonomic level of resolution and, therefore, are represented by the class Ostracoda. Overall average total zooplankton biomass was 0.6 µg/L (min=0, max=63.6) and peaked during spring at over 4 µg/L (fig. 9). Results of the zooplankton PCA (table 3) indicated high overlap in species composition among all ponds (fig. 10).

Table 5.    

Zooplankton taxa which consisted of greater than or equal to 1 percent of the overall total biomass in managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from Buxton and others (2023).

[Ostracoda orders are not provided. Abbreviations: μg, microgram; —, no data]

Taxa Order Biomass
(µg)
Percentage of
total biomass
Arctodiaptomus dorsalis Calanoida 533 20.7
Diacyclops thomasi Cyclopoida 291 11.3
Acanthocyclops robustus Cyclopoida 264 10.3
Leptodiaptomus siciloides Calanoida 241 9.4
Daphnia pulex Diplostraca 179 7.0
Mesocyclops edax Cyclopoida 167 6.5
Ostracoda 125 4.9
Daphnia rosea Diplostraca 124 4.8
Daphnia magna Diplostraca 123 4.8
Diaptomidae Calanoida 94 3.7
Skistodiaptomus pallidus Calanoida 94 3.7
Bosmina longirostris Diplostraca 74 2.9
Eurycercus sp. Diplostraca 69 2.7
Simocephalus sp. Diplostraca 53 2.1
Daphnia galeata mendotae Diplostraca 51 2.0
Acanthocyclops brevispinosus Cyclopoida 32 1.2
Diaphanosoma brachyurum Diplostraca 29 1.1
Chydorus sphaericus Diplostraca 28 1.1
Table 5.    Zooplankton taxa which consisted of greater than or equal to 1 percent of the overall total biomass in managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from Buxton and others (2023).
9.	Zooplankton communities in the ponds consisted mostly of copepods.
Figure 9.

Zooplankton biomass time series in managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from Buxton and others (2023).

10.	There was a high degree of similarity in the taxonomic composition of zooplankton
                        communities across the ponds.
Figure 10.

Scores from the first and second axes of a principal components analysis done on zooplankton species composition data from managed ponds within the Sacramento–San Joaquin Delta in California. Scores are faceted by island to minimize superimposition and improve clarity. Ellipses are 95-percent confidence levels. Data summarized from Buxton and others (2023).

Fish

Fish were reported in all managed ponds except Holland South (table 6). Among the managed ponds with fish present, the number of species reported ranged from 1 (Bouldin West, Holland Middle, and Webb Middle) to 8 (Holland North; table 6). Overall, a total of 12 individual species were reported with the most common being bluegill (Lepomis macrochirus) and western mosquitofish (Gambusia affinis), each having occurred in 5 individual managed ponds. Largemouth bass (Micropterus salmoides), a piscivorous species that could potentially prey on delta smelt, was present in four managed ponds, Bacon South, Bouldin East, Holland North, and Webb East. Black crappie (Pomoxis nigromaculatus), another piscivore and potential delta smelt predator, was present in one managed pond, Holland North. Prickly sculpin (Cottus asper) was the only native fish species reported and was present in three managed ponds, Bacon North, Bouldin East, and Webb.

Table 6.    

Fish species reported in managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from Buxton and others (2023).

[X, species detected; —, species not detected]

Taxa Bacon Island Bouldin Island Holland Tract Webb Tract
Bacon
North
Bacon
South
Bouldin
East
Bouldin
West
Holland
Middle
Holland
North
Holland
South
Webb
East
Webb
Middle
Webb
North
Bigscale logperch (Percina macrolepida) X
Black Bullhead (Ameiurus melas) X X
Black Crappie (Pomoxis nigromaculatus) X
Bluegill (Lepomis macrochirus) X X X X X
Brown Bullhead (Ameiurus nebulosus) X
Common Carp (Cyprinus carpio) X X X
Golden Shiner (Notemigonus crysoleucas) X X
Goldfish (Carassius auratus) X X X
Largemouth Bass (Micropterus salmoides) X X X X
Western Mosquitofish (Gambusia affinis) X X X X X
Prickly Sculpin (Cottus asper) X X X
Red Shiner (Cyprinella lutrensis) X X
Total species encountered 2 3 3 1 1 8 0 6 1 7
Table 6.    Fish species reported in managed ponds within the Sacramento–San Joaquin Delta in California. Data summarized from Buxton and others (2023).

Discussion

Managed ponds in the Sacramento–San Joaquin Delta (Delta) of California surveyed in our study indicated a range of physical configurations, water quality characteristics, pesticide concentrations, and biological characteristics. Overall, water quality conditions in the surveyed managed ponds seemed to be driven primarily by a combination of physical habitat conditions and connectivity with adjacent managed ponds. Vertical stratification represented the dominant within-pond mode of variability in water quality conditions and was controlled by depth. Highly connected managed ponds, such as those on Webb Tract, indicated similar water quality conditions, whereas unconnected managed ponds, such as those on Bouldin Island, indicated unique water quality conditions (fig. 6). Terminal ponds with no outlets, Holland Middle and Holland South, indicated elevated salinity and high values across all non-organic water quality parameters, indicating evaporation is likely also an important driver of some aspects of water quality.

Temperature seemed to be the key physiochemical feature that may limit opportunities to support pond rearing of delta smelt. Elevated summer and fall temperatures may compromise delta smelt health and survival and thus may limit potential experimental activities to winter and spring (Komoroske and others, 2015; Jeffries and others, 2016). From May to October, the delta smelt temperature stress threshold value of 21 °C was consistently exceeded and the temperature mortality threshold value of 28 °C was intermittently exceeded (fig. 3). However, temperatures were consistently 2–5 degrees lower at the bottom of the deepest managed ponds (fig. 5), indicating that newly constructed ponds could potentially provide a deep water temperature refugia for delta smelt if properly engineered.

Pesticides were mostly detected at low concentrations but might pose a threat to delta smelt or other fishes under some specific circumstances. Measured contaminant concentrations were generally below EPA Aquatic Life Benchmarks, with just a few exceptions. Two water samples collected during Survey 2 contained pesticides at concentrations that exceeded EPA Aquatic Life Benchmarks. The Bouldin Island East Pond Inlet sample contained the herbicide diuron at a concentration of 530 ng/L, which exceeds the EPA benchmark for toxicity to vascular plants (130 ng/L). The Bouldin Island East Pond sample contained the insecticide clothianidin at a concentration of 58.6 ng/L, which exceeds the EPA benchmark for chronic toxicity to invertebrates (50 ng/L). Three water samples collected during Survey 3 contained pesticides at concentrations that exceeded EPA Aquatic Life Benchmarks. The Bouldin Island East Pond Inlet, Bouldin Island East Pond Center, and Webb Tract Middle Pond Inlet samples contained clothianidin at concentrations of 69.9, 72.8, and 70.3 ng/L, respectively, which exceeds the EPA benchmark for chronic toxicity to invertebrates. The Webb Tract East Pond South Inlet site also had a concentration of 1.4 ng/L of the pyrethroid insecticide deltamethrin in suspended sediments, which was above the EPA acute invertebrate toxicity benchmark of 0.1 ng/L. Six pyrethroid insecticides were detected in bed sediments. Specific pesticides such as fluoridone and glyphosate may be of concern because Jin and others (2018) indicated that fluoridone and glyphosate affected liver estradiol hormone and reduced oxidative enzyme, and fluoridone could affect brain activity in delta smelt. Additionally, Jeffries and others (2015) indicated that permethrin activated genes for protein synthesis and metabolism, and resulted in mortality in delta smelt, but the study used 100 times the concentrations of pesticides that were detected here in this study.

The surveyed managed ponds were all highly productive and seemed to possess food webs that could support delta smelt in terms of type and quantity of available prey. Chlorophyll a concentration, an index of potential primary productivity, indicated the managed ponds were productive, with several managed ponds indicating eutrophic (approximately 10–40 µg/L) or hypereutrophic (greater than 40 µg/L) conditions. Zooplankton populations were broadly similar among managed ponds and included calanoid and cyclopoid copepods that would be suitable prey for delta smelt. Additional research will be needed to estimate the carrying capacity of managed pond food webs to support delta smelt and other native fishes and to determine the potential uptake and bioaccumulation of pesticides (of high concentrations) in zooplankton or key food items of delta smelt.

Managed ponds may support fish species that could potentially prey on delta smelt. Potential predators such as largemouth bass and black crappie were reported in 4 and 1 of the surveyed managed ponds, respectively. The distribution of predators among ponds seemed to have been driven primarily by deliberate stocking to facilitate local fisheries. Overall, the surveyed pond fish communities were unnatural assemblages of species that did not mirror assemblages in adjacent sloughs (Feyrer and Healey, 2003; Nobriga and others, 2005), indicating that sportfish stocking and water management practices controlled fish occupancy.

Overall, the managed ponds surveyed in our study seem to be suitable to support delta smelt and other native fishes, at least during some parts of the year. Indeed, delta smelt experimentally reared during winter 2022–23 in Bouldin East and Bouldin West indicated high survival and good health (Shawn Acuña, Metropolitan Water District, unpub. data, 2025). The biggest challenge to successfully rearing delta smelt in managed ponds in the Delta may be the high summer water temperature. However, this could potentially be mitigated by managing pond depth and water circulation to provide thermal refugia and suitable water quality conditions. Properly engineered and managed ponds seem to hold great promise for research and conservation efforts involving delta smelt and other native fishes.

References Cited

Arias-Ortiz, A., Oikawa, P.Y., Carlin, J., Masqué, P., Shahan, J., Kanneg, S., Paytan, A., and Baldocchi, D.D., 2021, Tidal and nontidal marsh restoration—A trade-off between carbon sequestration, methane emissions, and soil accretion: Journal of Geophysical Research: Biogeosciences, v. 126, no. 12, 22 p. [Available at https://doi.org/10.1029/2021JG006573.]

Black, G.P., Woodward, E.E., Sanders, C.J., Gross, M.S., and Hladik, M.L., 2023, Multiresidue extraction of current-use pesticides from complex solid matrices using energized dispersive guided extraction with analysis by gas and liquid chromatography tandem mass spectroscopy: Chemosphere, v. 327, 23 p. [Available at https://doi.org/10.1016/j.chemosphere.2023.138550.]

Buxton, J.M., Enos, E.R., Feyrer, F.V., and Acuna, S., 2023, Water quality and biological data from ponds on islands of the Sacramento–San Joaquin Delta: U.S. Geological Survey data release. [Available at https://doi.org/10.5066/P97GLG5I.]

Chamberlain, S.D., Anthony, T.L., Silver, W.L., Eichelmann, E., Hemes, K.S., Oikawa, P.Y., Sturtevant, C., Szutu, D.J., Verfaillie, J.G., and Baldocchi, D.D., 2018, Soil properties and sediment accretion modulate methane fluxes from restored wetlands: Global Change Biology, v. 24, no. 9, p. 4107–4121, accessed February 20, 2025, at https://doi.org/10.1111/gcb.14124.

Deverel, S.J., Ingrum, T., Lucero, C., and Drexler, J.Z., 2014, Impounded marshes on subsided islands—Simulated vertical accretion, processes, and effects, Sacramento–San Joaquin Delta, CA USA: San Francisco Estuary and Watershed Science, v. 12, no. 2, 23 p. [Available at https://doi.org/10.15447/sfews.2014v12iss2art5.]

Deverel, S.J., and Rojstaczer, S., 1996, Subsidence of agricultural lands in the Sacramento‐San Joaquin Delta, California—Role of aqueous and gaseous carbon fluxes: Water Resources Research, v. 32, no. 8, p. 2359–2367, accessed February 20, 2025, at https://doi.org/10.1029/96WR01338.

Drexler, J.Z., 2011, Peat formation processes through the millennia in tidal marshes of the Sacramento–San Joaquin Delta: Estuaries and Coasts, v. 34, no. 5, p. 900–911, accessed February 20, 2025, at https://doi.org/10.1007/s12237-011-9393-7.

Drexler, J.Z., de Fontaine, C.S., and Deverel, S.J., 2009, The legacy of wetland drainage on the remaining peat in the Sacramento–San Joaquin Delta, California, USA: Wetlands, v. 29, no. 1, p. 372–386, accessed February 20, 2025, at https://doi.org/10.1672/08-97.1.

Feyrer, F., and Healey, M.P., 2003, Fish community structure and environmental correlates in the highly altered southern Sacramento–San Joaquin Delta: Environmental Biology of Fishes, v. 66, no. 2, p. 123–132, accessed February 20, 2025, at https://doi.org/10.1023/A:1023670404997.

Garlock, T.M., Monk, C.T., Lorenzen, K., Matthews, M.D., and St. Mary, C.M., 2014, Effects of hatchery rearing on Florida largemouth bass Micropterus floridanus resource allocation and performance under semi‐natural conditions: Journal of Fish Biology, v. 85, no. 6, p. 1830–1842. [Available at https://doi.org/10.1111/jfb.12514.]

Gross, M.S., Sanders, C.J., De Parsia, M.D., and Hladik, M.L., 2024, Methods of analysis—Determination of pesticides in filtered water and suspended sediment using liquid chromatography- and gas chromatography-tandem mass spectrometry: U.S. Geological Survey Techniques and Methods, book 5, chap. A12, 33 p., accessed February 20, 2025, at https://doi.org/10.3133/tm5A12.

Hemes, K.S., Chamberlain, S.D., Eichelmann, E., Anthony, T., Valach, A., Kasak, K., Szutu, D., Verfaillie, J., Silver, W.L., and Baldocchi, D.D., 2019, Assessing the carbon and climate benefit of restoring degraded agricultural peat soils to managed wetlands: Agricultural and Forest Meteorology, v. 268, p. 202–214, accessed February 20, 2025, at https://doi.org/10.1016/j.agrformet.2019.01.017.

Hobbs, J.A., Moyle, P.B., Fangue, N., and Connon, R.E., 2017, Is extinction inevitable for delta smelt and longfin smelt? An opinion and recommendations for recovery: San Francisco Estuary and Watershed Science, v. 15, no. 2, 19 p. [Available at https://doi.org/10.15447/sfews.2017v15iss2art2.]

Hung, T.-C., Hammock, B.G., Sandford, M., Stillway, M., Park, M., Lindberg, J.C., and Teh, S.J., 2022, Temperature and salinity preferences of endangered delta smelt (Hypomesus transpacificus, Actinopterygii, Osmeridae): Scientific Reports, v. 12, no. 1, 11 p. [Available at https://doi.org/10.1038/s41598-022-20934-w.]

Hung, T.-C., Rosales, M., Kurobe, T., Stevenson, T., Ellison, L., Tigan, G., Sandford, M., Lam, C., Schultz, A., and Teh, S., 2019, A pilot study of the performance of captive-reared delta smelt Hypomesus transpacificus in a semi-natural environment: Journal of Fish Biology, v. 95, no. 6, p. 1517–1522. [Available at https://doi.org/10.1111/jfb.14162.]

Jeffries, K.M., Connon, R.E., Davis, B.E., Komoroske, L.M., Britton, M.T., Sommer, T., Todgham, A.E., and Fangue, N.A., 2016, Effects of high temperatures on threatened estuarine fishes during periods of extreme drought: Journal of Experimental Biology, v. 219, no. 11, p. 1705–1716. [Available at https://doi.org/10.1242/jeb.134528.]

Jeffries, K.M., Komoroske, L.M., Truong, J., Werner, I., Hasenbein, M., Hasenbein, S., Fangue, N.A., and Connon, R.E., 2015, The transcriptome-wide effects of exposure to a pyrethroid pesticide on the Critically Endangered delta smelt Hypomesus transpacificus: Endangered Species Research, v. 28, no. 1, p. 43–60, accessed February 20, 2025, at https://doi.org/10.3354/esr00679.

Jin, J., Kurobe, T., Ramírez-Duarte, W.F., Bolotaolo, M.B., Lam, C.H., Pandey, P.K., Hung, T.-C., Stillway, M.E., Zweig, L., Caudill, J., Lin, L., and Teh, S.J., 2018, Sub-lethal effects of herbicides penoxsulam, imazamox, fluridone and glyphosate on delta smelt (Hypomesus transpacificus): Aquatic Toxicology, v. 197, p. 79–88, accessed February 20, 2025, at https://doi.org/10.1016/j.aquatox.2018.01.019.

Komoroske, L.M., Connon, R.E., Jeffries, K.M., and Fangue, N.A., 2015, Linking transcriptional responses to organismal tolerance reveals mechanisms of thermal sensitivity in a mesothermal endangered fish: Molecular Ecology, v. 24, no. 19, p. 4960–4981, accessed February 20, 2025, at https://doi.org/10.1111/mec.13373.

Lessard, J., Cavallo, B., Anders, P., Sommer, T., Schreier, B., Gille, D., Schreier, A., Finger, A., Hung, T.-C., Hobbs, J., May, B., Schultz, A., Burgess, O., and Clarke, R., 2018, Considerations for the use of captive-reared delta smelt for species recovery and research: San Francisco Estuary and Watershed Science, v. 16, no. 3, 15 p. [Available at https://doi.org/10.15447/sfews.2018v16iss3art3.]

Lindberg, J.C., Tigan, G., Ellison, L., Rettinghouse, T., Nagel, M.M., and Fisch, K.M., 2013, Aquaculture methods for a genetically managed population of endangered delta smelt: North American Journal of Aquaculture, v. 75, no. 2, p. 186–196. [Available at https://doi.org/10.1080/15222055.2012.751942.]

Lund, J., Hanak, E., Fleenor, E., Howitt, R., Mount, J., and Moyle, P., 2007, Envisioning futures for the Sacramento–San Joaquin Delta: San Francisco, Public Policy Institute of California, 285 p., accessed February 20, 2025, at https://www.policyarchive.org/handle/10207/4802.

Maynard, D., Riley, S., Flagg, T., Iwamoto, R., Mahnken, C., Berejikian, B., Tatara, C., Endicott, R., Atkins, J., Scheurer, J., LaRae, A., Colt, J., Dixon, J., McDowell, G., and Vander Haegen, G., 2004, Development of a natural rearing system to improve supplemental fish quality: Bonneville Power Administration, Final Report 2004, Project No. 199105500, Report DOE/BP-00004768-2, 171 p., accessed February 20, 2025, at https://docs.streamnetlibrary.org/BPA_Fish_and_Wildlife/00004768-2.pdf.

Miller, R.L., Fram, M.S., Fujii, R., and Wheeler, G., 2008, Subsidence reversal in a re-established wetland in the Sacramento–San Joaquin Delta, California, USA: San Francisco Estuary and Watershed Science, v. 6, no. 3, 20 p., accessed February 20, 2025, at https://doi.org/10.15447/sfews.2008v6iss3art1.

Miller, R.L., and Fujii, R., 2011, Re-establishing marshes can turn a current carbon source into a carbon sink in the Sacramento–San Joaquin Delta of California, USA, chap. 1 of Contreras, D.A., ed., River deltas—Types, structures and ecology: New York, Nova Science Publishers, Inc., p. 1–34.

Moyle, P.B., Brown, L.R., Durand, J.R., and Hobbs, J.A., 2016, Delta smelt—Life history and decline of a once-abundant species in the San Francisco Estuary: San Francisco Estuary and Watershed Science, v. 14, no. 2, 30 p. [Available at https://doi.org/10.15447/sfews.2016v14iss2art6.]

Moyle, P.B., Hobbs, J.A., and Durand, J.R., 2018, Delta smelt and water politics in California: Fisheries, v. 43, no. 1, p. 42–50, accessed February 20, 2025, at https://doi.org/10.1002/fsh.10014.

Nobriga, M.L., Feyrer, F., Baxter, R.D., and Chotkowski, M., 2005, Fish community ecology in an altered river delta—Spatial patterns in species composition, life history strategies, and biomass: Estuaries and Coasts, v. 28, no. 5, p. 776–785, accessed February 20, 2025, at https://doi.org/10.1007/BF02732915.

Prokopovich, N.P., 1985, Subsidence of peat in California and Florida: Bulletin of the Association of Engineering Geologists, v. XXII, no. 4, p. 395–420, accessed February 20, 2025, at https://doi.org/10.2113/gseegeosci.xxii.4.395.

R Core Team, 2020, R—The R project for statistical computing: Vienna, Austria, R Foundation for Statistical Computing, https://www.r-project.org.

U.S. Environmental Protection Agency, 2016, Definition and procedure for the determination of the method detection limit, revision 2: U.S. Environmental Protection Agency, Office of Water, EPA 821-R-16-006, 6 p. [Available at https://www.epa.gov/sites/default/files/2016-12/documents/mdl-procedure_rev2_12-13-2016.pdf. Text contains Revision 2 of Code of Federal Regulations, title 40, part 136, appendix B, released as a standalone document.]

U.S. Geological Survey, 2024, USGS water data for the Nation: U.S. Geological Survey National Water Information System database, accessed January 24, 2025, at https://doi.org/10.5066/F7P55KJN.

Weir, W.W., 1950, Subsidence of peat lands of the Sacramento–San Joaquin Delta, California: Hilgardia, v. 20, no. 3, p. 37–56, accessed February 20, 2025, at https://doi.org/10.3733/hilg.v20n03p037.

Whipple, A.A., Grossinger, R.M., Rankin, D., Stanford, B., and Askevold, R.A., 2012, Sacramento–San Joaquin Delta historical ecology investigation—Exploring pattern and process: Richmond, Calif., Prepared for the California Department of Fish and Game and Ecosystem Restoration Program, San Francisco Estuary Institute-Aquatic Science Center [SFEI-ASC], A Report of SFEI-ASC’s Historical Ecology Program, Publication #672, 408 p., accessed February 20, 2025, at https://www.sfei.org/DeltaHEStudy#sthash.2rW7Pdqw.dpbs.

Appendix 1. Water Quality Survey Sample Sites

Table 1.1.    

Water quality survey sample sites in managed ponds within the Sacramento–San Joaquin Delta in California (U.S. Geological Survey, 2024).

[USGS, U.S. Geological Survey]

Managed pond USGS site identifier Latitude Longitude
Bacon North 375955121333601 37.9986 −121.5601
Bacon South 375734121330601 37.9594 −121.5517
Bouldin East 380545121310901 38.0957 −121.5191
Bouldin West 380557121323001 38.0992 −121.5416
Holland Middle 380053121353101 38.0147 −121.5920
Holland North 380137112135201 38.0269 −121.5866
Holland South 380052121354001 38.0145 −121.5945
Webb East 380502121350301 38.0840 −121.5843
Webb Middle 380543121362801 38.0952 −121.6077
Webb North 380551121364201 38.0976 −121.6118
Table 1.1.    Water quality survey sample sites in managed ponds within the Sacramento–San Joaquin Delta in California (U.S. Geological Survey, 2024).

Reference Cited

U.S. Geological Survey, 2024, USGS water data for the Nation: U.S. Geological Survey National Water Information System database, accessed January 24, 2025, at https://doi.org/10.5066/F7P55KJN.

Appendix 2. Pesticide Survey Sample Sites

Table 2.1.    

Pesticide survey sample sites in managed ponds within the Sacramento–San Joaquin Delta in California (U.S. Geological Survey, 2024).

[USGS, U.S. Geological Survey]

Managed pond Location USGS site identifier Latitude Longitude
Bacon North Inlet 375957121332901 37.99934 −121.55818
Bacon North Center 375955121333601 37.99861 −121.56013
Bacon North Inlet 375957121332901 37.96121 −121.55250
Bacon North Center 375955121333601 37.95940 −121.55167
Bouldin East Inlet 380546121311501 38.09627 −121.52101
Bouldin East Center 380545121310901 38.09573 −121.51909
Bouldin West Inlet 380600121322501 38.10010 −121.54028
Bouldin West Center 380557121323001 38.09924 −121.54156
Holland Middle Inlet 380052121353601 38.01459 −121.59347
Holland Middle Center 380053121353101 38.01472 −121.59196
Holland North Inlet 380141121351401 38.02809 −121.58744
Holland North Center 380137112135201 38.02692 −121.58658
Holland South Inlet 380051121353701 38.01432 −121.59367
Holland South Center 380052121354001 37.01447 −121.59449
Holland North Outlet 380124121351201 38.02330 −121.58667
Webb East Center 380502121350301 38.08395 −121.58427
Webb East Inlet 380451121350701 38.08089 −121.58534
Webb East Inlet (West) 380506121352801 38.08511 −121.59123
Webb North Inlet (Middle) 380527121363601 38.09105 −121.61012
Webb Middle Center 380543121362801 38.09517 −121.60768
Webb North Center 380551121364201 38.09756 −121.61179
Table 2.1.    Pesticide survey sample sites in managed ponds within the Sacramento–San Joaquin Delta in California (U.S. Geological Survey, 2024).

Reference Cited

U.S. Geological Survey, 2024, USGS water data for the Nation: U.S. Geological Survey National Water Information System database, accessed January 24, 2025, at https://doi.org/10.5066/F7P55KJN.

Appendix 3. Method Detection and Reporting Limits for Pesticides Dissolved in Water and Sediments Measured by the U.S. Geological Survey Organic Chemistry Research Laboratory

Table 3.1.    

Method detection and reporting limits for pesticides dissolved in water and sediments measured by the U.S. Geological Survey Organic Chemistry Research Laboratory.

[CAS, chemical abstracts service; GC/MS/MS, gas chromatography with tandem mass spectrometry; LC/MS/MS, liquid chromatography with tandem mass spectrometry; MDL, method detection limit; NA, not analyzed; ng/g, nanograms per gram; ng/L, nanograms per liter; NWIS, National Water Information System; RL, reporting limit]

Compound CAS number Chemical class Pesticide type NWIS water and suspended sediment parameter code Water RL
(ng/L)
Water MDL
(ng/L)
Suspended sediment RL
(ng/L)
Suspended sediment MDL
(ng/L)
NWIS sediment parameter code Bed sediment RL
(ng/g)
Bed sediment MDL
(ng/g)
Analytical instrument
Acetamiprid 135410-20-7 Neonicotinoid Insecticide 68302 2.1 1 4.4 2.2 54365 0.209453 0.104726 LC/MS/MS
Acetochlor 34256-82-1 Chloroacetanilide Herbicide 68520 3.1 1.5 3.4 1.7 54366 0.412551 0.206276 LC/MS/MS
Acibenzolar-S-methyl 135158-54-2 Benzothiadiazole Fungicide 51849 10.7 5.3 11.1 5.6 51870 0.794744 0.397372 GC/MS/MS
Allethrin 584-79-2 Pyrethroid Insecticide 66586 3.8 1.9 6.2 3.1 66588 0.807834 0.403917 GC/MS/MS
Atrazine 1912-24-9 Triazine Herbicide 65065 1.7 0.9 2.7 1.4 39631 0.210395 0.105198 LC/MS/MS
Atrazine, Desethyl 6190-65-4 Triazine Herbicide degradate 68552 3.2 1.6 4.5 2.3 4001 0.401855 0.200928 LC/MS/MS
Atrazine, Desisopropyl 1007-28-9 Triazine Herbicide degradate 68550 3.7 1.8 5.6 2.8 4003 0.412079 0.206039 LC/MS/MS
Azoxystrobin 131860-33-8 Strobin Fungicide 66589 1.6 0.8 4.3 2.2 66591 0.200928 0.100464 LC/MS/MS
Benefin (Benfluralin) 1861-40-1 2,6-Dinitroaniline Herbicide 51643 3.6 1.8 6.8 3.4 68878 0.196086 0.098043 GC/MS/MS
Bentazon 25057-89-0 Benzothiadiazine Herbicide 68538 2.5 1.3 NA NA 54421 0.402597 0.201299 LC/MS/MS
Benzobicyclon 156963-66-5 Carbobicyclic Herbicide 54350 2.3 1.2 3.5 1.8 54424 0.470438 0.235219 LC/MS/MS
Benzovindiflupyr 1072957-71-1 Amide Fungicide 52652 2.3 1.2 3.6 1.8 54367 0.227841 0.11392 LC/MS/MS
Bifenthrin 82657-04-3 Pyrethroid Insecticide 65067 1.1 0.6 1.5 0.8 64151 0.212519 0.10626 GC/MS/MS
Boscalid 188425-85-6 Anilide Fungicide 67550 2 1 3.5 1.7 67552 0.432196 0.216098 LC/MS/MS
Boscalid Metabolite - M510F01 Acetyl 661463-87-2 Anilide Fungicide degradate 54349 1.6 0.8 3.3 1.7 54423 0.26395 0.131975 LC/MS/MS
Broflanilide 1207727-04-5 Benzamide Insecticide 54363 3.9 1.9 4.2 2.1 54445 0.262166 0.131083 LC/MS/MS
Bromoxynil 1689-84-5 Nitrile Herbicide NA NA NA NA NA 54434 0.54 0.27 LC/MS/MS
Bromoconazole 116255-48-2 Azole Fungicide 68315 1.9 1 3.8 1.9 68317 0.419085 0.209542 LC/MS/MS
Butralin 33629-47-9 2,6-Dinitroaniline Herbicide 68545 2.5 1.2 3.6 1.8 68880 0.404781 0.20239 LC/MS/MS
Carbaryl 63-25-2 N-Methyl Carbamate Insecticide 65069 1.7 0.8 3.5 1.7 64153 0.207572 0.103786 LC/MS/MS
Carbendazim 10605-21-7 Benzimidazole Fungicide 68548 2.5 1.2 4.9 2.5 NA NA NA LC/MS/MS
Carbofuran 1563-66-2 N-Methyl Carbamate Insecticide 65070 1.3 0.6 3.1 1.5 64154 0.204415 0.102208 LC/MS/MS
Chlorantraniliprole 500008-45-7 Anthranilic diamide Insecticide 51856 1.5 0.7 3.7 1.8 54370 0.213412 0.106706 LC/MS/MS
Chlorfenapyr 122453-73-0 Pyrrole Insecticide 53567 3.6 1.8 5 2.5 54447 0.858716 0.429358 GC/MS/MS
Chlorothalonil 1897-45-6 Substituted Benzene Fungicide 65071 1.9 0.7 18 9 NA NA NA GC/MS/MS
Chlorpyrifos 2921-88-2 Organophosphorus Insecticide 65072 2.4 1.2 3.9 1.9 81404 0.417854 0.208927 LC/MS/MS
Chlorpyrifos oxon 5598-15-2 Organophosphorus Insecticide 68216 2 1 3.9 2 68218 0.239709 0.119854 LC/MS/MS
Clomazone 81777-89-1 Oxazolidinone Herbicide 67562 2.4 1.2 3.6 1.8 67564 0.19082 0.09541 LC/MS/MS
Clothianidin 210880-92-5 Neonicotinoid Insecticide 68221 2 1 5.7 2.8 68223 0.198857 0.099428 LC/MS/MS
Clothianidin des methyl 135018-15-4 Neonicotinoid Insecticide degradate 52660 3.7 1.8 5.6 2.8 54408 0.482081 0.241041 LC/MS/MS
Coumaphos 56-72-4 Organophosphorus Insecticide 51836 2.3 1.1 3.7 1.8 68882 0.505642 0.252821 LC/MS/MS
Cyantraniliprole 736994-63-1 Anthranilic diamide Insecticide 51862 2.2 1.1 3.9 2 54372 0.466417 0.233208 LC/MS/MS
Cyazofamid 120116-88-3 Azole Fungicide 51853 1.7 0.8 3.6 1.8 54373 0.192207 0.096103 LC/MS/MS
Cyclaniliprole 1031756-98-5 Anthranilic diamide Insecticide 54355 2.7 1.4 2.9 1.4 54435 0.548125 0.274063 LC/MS/MS
Cycloate 1134-23-2 Thiocarbamate Herbicide 65073 1.8 0.9 3.4 1.7 64155 0.446684 0.223342 LC/MS/MS
Cyfluthrin 68359-37-5 Pyrethroid Insecticide 65074 1.7 0.8 2.1 1 65109 0.188959 0.094479 GC/MS/MS
Cyhalofop-butyl 122008-85-9 Aryloxyphenoxy propionic acid Herbicide 68360 3 1.5 4.4 2.2 68884 0.214013 0.107006 GC/MS/MS
Cyhalothrin (all isomers) 68085-85-8 Pyrethroid Insecticide 68354 1.2 0.6 1.9 1 68356 0.215611 0.107806 GC/MS/MS
Cymoxanil 57966-95-7 Urea Fungicide 51861 4.6 2.3 4.3 2.2 54374 0.436771 0.218386 LC/MS/MS
Cypermethrin 52315-07-8 Pyrethroid Insecticide 65075 1.8 0.9 2.2 1.1 64156 0.186652 0.093326 GC/MS/MS
Cyproconazole 94361-06-5 Azole Fungicide 66593 2.8 1.4 3.8 1.9 66595 0.208087 0.104043 LC/MS/MS
Cyprodinil 121552-61-2 Pyrimidine Fungicide 67574 4.3 2.1 3.2 1.6 NA NA NA LC/MS/MS
DCPA 1861-32-1 Alkyl Phthalate Herbicide 65076 2.3 1.2 2.5 1.2 62905 0.203906 0.101953 GC/MS/MS
DCPMU 3567-62-2 Urea Herbicide degradate 68231 1.5 0.7 2.6 1.3 NA NA NA LC/MS/MS
DCPU 155998 Urea Herbicide degradate 68226 2.1 1.1 3.5 1.7 NA NA NA LC/MS/MS
Deltamethrin 52918-63-5 Pyrethroid Insecticide 65077 1.4 0.7 2.8 1.4 65110 0.397768 0.198884 GC/MS/MS
Desthio-prothioconazole 120983-64-4 Azole Fungicide degradate 51865 1.3 0.7 2.8 1.4 54375 0.215031 0.107516 LC/MS/MS
Desulfinylfipronil 205650-65-3 Pyrazole Insecticide degradate 66607 1.9 1 2.1 1 68891 0.201768 0.100884 LC/MS/MS
Desulfinylfipronil Amide 1115248-09-3 Pyrazole Insecticide degradate 68570 2.1 1 2.4 1.2 66609 0.43457 0.217285 LC/MS/MS
Diazinon 333-41-5 Organophosphorus Insecticide 65078 2.3 1.1 3.3 1.6 39571 0.211199 0.1056 LC/MS/MS
Diazoxon 962-58-3 Organophosphorus Insecticide degradate 68236 1.5 0.7 4.1 2.1 68238 0.205959 0.102979 LC/MS/MS
3,4-Dichloroaniline 95-76-1 Amine Herbicide degradate 66584 2.3 1.2 2.5 1.2 66585 0.95924 0.47962 LC/MS/MS
3,5-Dichloroaniline 626-43-7 Amine Herbicide degradate 67536 5.6 2.8 5.9 3 67538 0.827873 0.413936 LC/MS/MS
Dichlorvos 62-73-7 Organophosphorus Insecticide 68572 2.4 1.2 1.8 0.9 54376 0.439189 0.219594 LC/MS/MS
Difenoconazole 119446-68-3 Azole Fungicide 67582 2.7 1.3 2.8 1.4 67584 0.396093 0.198047 LC/MS/MS
Dimethomorph 110488-70-5 Morpholine Fungicide 68373 1.4 0.7 5.5 2.8 68375 0.198899 0.09945 LC/MS/MS
Dinotefuran 165252-70-0 Neonicotinoid Insecticide 68379 3.6 1.8 7.3 3.6 54377 0.411789 0.205895 LC/MS/MS
Dithiopyr 97886-45-8 Pyridinecarboxylic acid Herbicide 51837 2.3 1.1 2.5 1.3 68886 0.203937 0.101969 GC/MS/MS
Diuron 330-54-1 Urea Herbicide 66598 1.4 0.7 3.8 1.9 66600 0.265939 0.132969 LC/MS/MS
EPTC 759-94-4 Thiocarbamate Herbicide 65080 2.6 1.3 2.8 1.4 64158 0.880311 0.440156 LC/MS/MS
Esfenvalerate 66230-04-4 Pyrethroid Insecticide 65081 1.5 0.7 2.4 1.2 64159 0.217059 0.108529 GC/MS/MS
Ethaboxam 162650-77-3 Aromatic Amide Fungicide 51855 3 1.5 3.5 1.7 54378 0.373235 0.186617 LC/MS/MS
Ethalfluralin 55283-68-6 2,6-Dinitroaniline Herbicide 65082 5.4 2.7 6.2 3.1 64160 0.211599 0.105799 GC/MS/MS
Etofenprox 80844-07-1 Pyrethroid Ether Insecticide 67604 3.8 1.9 3.4 1.7 67606 0.193598 0.096799 GC/MS/MS
Etoxazole 153233-91-1 Diphenyl Oxazoline Insecticide 68598 2.4 1.2 3.7 1.9 54379 0.256658 0.128329 LC/MS/MS
Famoxadone 131807-57-3 Oxazolidinedione Fungicide 67609 13.9 6.9 18 9 NA NA NA LC/MS/MS
Fenamidone 161326-34-7 Imidazole Fungicide 51848 1.7 0.9 1.9 1 51869 0.215952 0.107976 LC/MS/MS
Fenbuconazole 114369-43-6 Azole Fungicide 67618 1.8 0.9 2.9 1.5 67620 0.212074 0.106037 LC/MS/MS
Fenhexamid 126833-17-8 Anilide Fungicide 67622 17.8 8.9 20.8 10.4 67624 5.114847 2.557423 LC/MS/MS
Fenpropathrin 39515-41-8 Pyrethroid Insecticide 65083 1.6 0.8 3.3 1.7 65111 0.443863 0.221931 GC/MS/MS
Fenpyroximate 134098-61-6 Pyrazole Insecticide 51838 2.8 1.4 4.3 2.2 NA NA NA LC/MS/MS
Fipronil 120068-37-3 Pyrazole Insecticide 66604 1.8 0.9 2.4 1.2 66606 0.214211 0.107106 LC/MS/MS
Fipronil sulfide 120067-83-6 Pyrazole Insecticide degradate 66610 1.5 0.7 1.9 1 66612 0.196602 0.098301 LC/MS/MS
Fipronil sulfone 120068-36-2 Pyrazole Insecticide degradate 66613 1.7 0.9 2.4 1.2 66615 0.207212 0.103606 LC/MS/MS
Flonicamid 158062-67-0 Pyridinecarboxamide Insecticide 51858 1.5 0.8 5 2.5 54380 0.436773 0.218387 LC/MS/MS
Florpyrauxifen-Benzyl 1390661-72-9 Aminopyridine Herbicide 54356 3.1 1.5 3.3 1.7 54436 0.245081 0.122541 LC/MS/MS
Fluazinam 79622-59-6 2,6-Dinitroaniline Fungicide 67636 2.4 1.2 2.8 1.4 67638 0.207404 0.103702 LC/MS/MS
Flubendiamide 272451-65-7 Organofluorine Insecticide NA NA NA NA NA 54381 0.52 0.26 LC/MS/MS
Fludioxonil 131341-86-1 Benzodioxole Fungicide 67640 2.4 1.2 2.7 1.3 NA NA NA LC/MS/MS
Flufenacet 142459-58-3 Anilide Herbicide 51840 3.7 1.8 3.8 1.9 68893 0.201474 0.100737 LC/MS/MS
Fluindapyr 1383809-87-7 Pyrazole Fungicide 54362 2.7 1.3 3.2 1.6 54444 0.204222 0.102111 LC/MS/MS
Flumetralin 62924-70-3 2,6-Dinitroaniline Plant growth regulator 51841 3.4 1.7 3.8 1.9 68895 0.528529 0.264264 LC/MS/MS
Fluopicolide 239110-15-7 Benzamide Pyridine Fungicide 51852 1.6 0.8 3.8 1.9 51873 0.197246 0.098623 LC/MS/MS
Fluopyram 658066-35-4 Amide Fungicide 52646 1.5 0.8 3.6 1.8 54402 0.197873 0.098936 LC/MS/MS
Fluoxastrobin 193740-76-0 Strobin Fungicide 67645 2.8 1.4 3.8 1.9 67647 0.199347 0.099674 LC/MS/MS
Flupyradifurone 951659-40-8 Butenolides Insecticide 52764 1.4 0.7 3.3 1.7 54382 0.221827 0.110914 LC/MS/MS
Fluridone 59756-60-4 Phenylpyridine Herbicide 51864 2.9 1.5 4.2 2.1 54383 0.199638 0.099819 LC/MS/MS
Flutolanil 66332-96-5 Anilide Fungicide 51842 2.6 1.3 3.7 1.9 68897 0.194805 0.097403 LC/MS/MS
Flutriafol 76674-21-0 Azole Fungicide 67653 2.7 1.4 3.8 1.9 67655 0.202849 0.101425 LC/MS/MS
Fluxapyroxad 907204-31-3 Anilide, Pyrazole Fungicide 51851 1.4 0.7 3.4 1.7 51872 0.222944 0.111472 LC/MS/MS
Fomesafen 72178-02-0 Diphenylether Herbicide NA NA NA NA NA 54437 0.9 0.45 LC/MS/MS
Halauxifen-methyl ester 943831-98-9 Methyl Ester Herbicide 54361 1.4 0.7 2.2 1.1 54442 0.200264 0.100132 LC/MS/MS
Hexazinone 51235-04-2 Triazinone Herbicide 65085 1.2 0.6 3.3 1.7 64161 0.207321 0.103661 LC/MS/MS
Imazalil 35554-44-0 Azole Fungicide 67662 3 1.5 NA NA NA NA NA LC/MS/MS
Imidacloprid 138261-41-3 Neonicotinoid Insecticide 68426 2 1 2.1 1 68428 0.207148 0.103574 LC/MS/MS
Imidacloprid desnitro 127202-53-3 Neonicotinoid Insecticide degradate 51857 7.4 3.7 10.8 5.4 NA NA NA LC/MS/MS
Imidacloprid Olefin 115086-54-9 Neonicotinoid Insecticide degradate 52782 6.6 3.3 11 5.5 54413 0.522177 0.261089 LC/MS/MS
Imidacloprid Urea 120868-66-8 Neonicotinoid Insecticide degradate 51859 2.8 1.4 4 2 54384 0.261432 0.130716 LC/MS/MS
5-OH Imidacloprid 380912-09-4 Neonicotinoid Insecticide degradate 54344 4.1 2 4.4 2.2 54415 0.391162 0.195581 LC/MS/MS
Indaziflam 950782-86-2 Alkylazine Herbicide 53960 2.5 1.3 4 2 54403 0.213803 0.106902 LC/MS/MS
Indoxacarb 173584-44-6 Oxadiazine Insecticide 68627 3.2 1.6 3.5 1.7 68899 0.409951 0.204975 LC/MS/MS
Ipconazole 125225-28-7 Triazole Fungicide 52762 2.4 1.2 4.1 2.1 54385 0.216126 0.108063 LC/MS/MS
Iprodione 36734-19-7 Dicarboximide Fungicide 66617 2.4 1.2 3.8 1.9 66618 0.426668 0.213334 LC/MS/MS
Isofetamid 875915-78-9 Amide Fungicide 53569 3.3 1.7 3 1.5 54386 0.20363 0.101815 LC/MS/MS
Kresoxim-methyl 143390-89-0 Strobin Fungicide 67670 2.2 1.1 3.1 1.6 67672 0.260404 0.130202 LC/MS/MS
Malaoxon 1634-78-2 Organophosphorus Insecticide degradate 68240 1.4 0.7 3.8 1.9 68242 0.210589 0.105295 LC/MS/MS
Malathion 121-75-5 Organophosphorus Insecticide 65087 2.2 1.1 4 2 39531 0.219113 0.109557 LC/MS/MS
Mandestrobin 173662-97-0 Strobin Fungicide 54358 3.2 1.6 3.3 1.7 54439 0.199938 0.099969 LC/MS/MS
Mandipropamid 374726-62-2 Amide Fungicide 51854 2.6 1.3 4.6 2.3 54387 0.232985 0.116493 LC/MS/MS
Metalaxyl 57837-19-1 Xylylalanine Fungicide 68437 1.1 0.6 4.4 2.2 68439 0.194749 0.097375 LC/MS/MS
Metalaxyl Alanine 85933-49-9 Xylylalanine Fungicide degradate 54345 2.5 1.3 4 2 54416 0.221448 0.110724 LC/MS/MS
Metconazole 125116-23-6 Azole Fungicide 66620 2.1 1 4.1 2.1 66622 0.207029 0.103515 LC/MS/MS
Methoprene 40596-69-8 Juvenile hormone mimic Insect growth regulator 66623 11.5 5.8 13.5 6.8 NA NA NA GC/MS/MS
Methoxyfenozide 161050-58-4 Diacylhydrazine Insecticide 68647 1.9 1 3.1 1.5 54388 0.205869 0.102935 LC/MS/MS
Methylparathion 298-00-0 Organophosphorus Insecticide NA NA NA NA NA 39601 0.4 0.2 LC/MS/MS
Metolachlor 51218-45-2 Chloroacetanilide Herbicide 65090 3.1 1.5 3 1.5 4005 0.2072 0.1036 LC/MS/MS
Myclobutanil 88671-89-0 Azole Fungicide 66632 1.1 0.6 4.2 2.1 66634 0.196052 0.098026 LC/MS/MS
Naled (Dibrom) 300-76-5 Organophosphorus Insecticide 68654 21.1 10.6 23.7 11.8 NA NA NA LC/MS/MS
Napropamide 15299-99-7 Amide Herbicide 65092 2 1 3 1.5 64164 0.204448 0.102224 LC/MS/MS
Nitrapyrin 1929-82-4 Chloropyridine Nitrogen stabilizer 52763 2.1 1.1 3.3 1.6 54448 0.190152 0.095076 GC/MS/MS
Novaluron 116714-46-6 Benzoylurea Herbicide 68655 4.5 2.2 4.4 2.2 NA NA NA LC/MS/MS
Oryzalin 19044-88-3 2,6-Dinitroaniline Herbicide 68663 3.8 1.9 3.2 1.6 54389 0.834211 0.417106 LC/MS/MS
Oxadiazon 19666-30-9 Unclassified Herbicide 51843 1.7 0.9 3.9 1.9 68903 0.424108 0.212054 LC/MS/MS
Oxathiapiprolin 1003318-67-9 Pyrazole Fungicide 52766 2.7 1.4 3 1.5 54390 0.217217 0.108608 LC/MS/MS
Oxyfluorfen 42874-03-3 Diphenyl ether Herbicide 65093 2.7 1.4 2.5 1.3 64165 0.383934 0.191967 LC/MS/MS
p,p'-DDD 72-54-8 Organochlorine Insecticide degradate 65094 2.7 1.3 2.3 1.1 39311 0.2 0.1 GC/MS/MS
p,p'-DDE 72-55-9 Organochlorine Insecticide degradate 65095 3 1.5 2.5 1.2 39321 0.208799 0.1044 GC/MS/MS
p,p'-DDT 50-29-3 Organochlorine Insecticide 65096 2.7 1.3 3.6 1.8 39301 0.196335 0.098168 GC/MS/MS
Paclobutrazol 76738-62-0 Azole Plant growth regulator 51846 2.2 1.1 4.5 2.3 51867 0.401709 0.200854 LC/MS/MS
Pendimethalin 40487-42-1 2,6-Dinitroaniline Herbicide 65098 2 1 3.9 2 64167 0.389137 0.194568 LC/MS/MS
Penoxsulam 219714-96-2 Triazolopyrimidine Herbicide 51863 4.4 2.2 NA NA 54391 0.489486 0.244743 LC/MS/MS
Pentachloroanisole 1825-21-4 Organochlorine Insecticide degradate 66637 2.3 1.1 4.7 2.3 49460 0.420845 0.210423 GC/MS/MS
Pentachloronitrobenzene 82-68-8 Substituted Benzene Fungicide 66639 2.9 1.4 6 3 49446 0.400941 0.200471 GC/MS/MS
Penthiopyrad 183675-82-3 Pyrazole Fungicide 52769 2.2 1.1 3.9 1.9 54392 0.199366 0.099683 LC/MS/MS
Permethrin 52645-53-1 Pyrethroid Insecticide 65099 1.4 0.7 1.5 0.7 64168 0.396211 0.198106 GC/MS/MS
Phenothrin 26002-80-2 Pyrethroid Insecticide 65100 2.2 1.1 2.6 1.3 65112 0.912072 0.456036 GC/MS/MS
Phosmet 732-11-6 Organophosphorus Insecticide 65101 1.4 0.7 3.3 1.6 64169 0.239977 0.119988 LC/MS/MS
Picarbutrazox 500207-04-5 Pyridine Fungicide 54357 2.7 1.3 3.2 1.6 54438 0.205177 0.102589 LC/MS/MS
Picoxystrobin 117428-22-5 Strobin Fungicide 51850 2.6 1.3 4.1 2 51871 0.199087 0.099544 LC/MS/MS
Piperonyl butoxide 51-03-6 Unclassified Synergist 65102 2.1 1 4.3 2.1 64170 0.247365 0.123683 LC/MS/MS
Prodiamine 29091-21-2 2,6-Dinitroaniline Herbicide 51844 2.2 1.1 4.1 2.1 68905 0.892833 0.446416 LC/MS/MS
Prometon 1610-18-0 Triazine Herbicide 67702 2.9 1.4 2.8 1.4 82402 0.209511 0.104755 LC/MS/MS
Prometryn 7287-19-6 Triazine Herbicide 65103 1.4 0.7 3.3 1.7 78688 0.224362 0.112181 LC/MS/MS
Propanil 709-98-8 Anilide Herbicide 66641 2.5 1.2 3.8 1.9 66642 0.420223 0.210111 LC/MS/MS
Propargite 2312-35-8 Unclassified Insecticide 68677 2.4 1.2 3.4 1.7 NA NA NA LC/MS/MS
Propiconazole 60207-90-1 Azole Fungicide 66643 1.5 0.7 2.6 1.3 66645 0.220249 0.110125 LC/MS/MS
Propyzamide 23950-58-5 Amide Herbicide 67706 2.1 1 3.7 1.9 67708 0.402295 0.201147 LC/MS/MS
Pydiflumetofen 1228284-64-7 Pyrazole Fungicide 54359 2.1 1 4.1 2 54440 0.248793 0.124397 LC/MS/MS
Pyraclostrobin 175013-18-0 Strobin Fungicide 66646 2.9 1.5 3.6 1.8 66648 0.233312 0.116656 LC/MS/MS
Pyridaben 96489-71-3 Pyridazinone Insecticide 68682 2.7 1.4 2.6 1.3 68909 0.240657 0.120329 LC/MS/MS
Pyrimethanil 53112-28-0 Pyrimidine Fungicide 67717 2.6 1.3 2.2 1.1 NA NA NA LC/MS/MS
Pyriproxyfen 95737-68-1 Hormone mimic Insecticide 68683 2.3 1.1 3.3 1.7 54393 0.243426 0.121713 LC/MS/MS
Quinoxyfen 124495-18-7 Quinoline Fungicide 51847 2.3 1.1 3.4 1.7 51868 0.208236 0.104118 LC/MS/MS
Resmethrin 10453-86-8 Pyrethroid Insecticide NA NA NA NA NA 65113 0.88 0.44 GC/MS/MS
Sedaxane 874967-67-6 Anilide, Pyrazole Fungicide 52648 1.8 0.9 3 1.5 54394 0.220046 0.110023 LC/MS/MS
Simazine 122-34-9 Triazine Herbicide 65105 1.7 0.9 2.7 1.4 39046 0.414632 0.207316 LC/MS/MS
Sulfometuron-Methyl 74222-97-2 Sulfonyl urea Herbicide NA NA NA NA NA 54420 0.46 0.23 LC/MS/MS
Sulfoxaflor 946578-00-3 Sulfoximine Insecticide 52767 2.4 1.2 4.8 2.4 54395 0.412498 0.206249 LC/MS/MS
tau-Fluvalinate 102851-06-9 Pyrethroid Insecticide 65106 1.6 0.8 2.1 1.1 65114 0.197193 0.098596 GC/MS/MS
Tebuconazole 107534-96-3 Azole Fungicide 66649 1.3 0.6 4.6 2.3 66650 0.223265 0.111633 LC/MS/MS
Tebuconazole t-Butylhydroxy 212267-64-6 Azole Fungicide degradate 54348 1.3 0.7 NA NA NA NA NA LC/MS/MS
Tebufenozide 112410-23-8 Moulting hormone agonist Insecticide 68692 2.4 1.2 3 1.5 54396 0.200387 0.100193 LC/MS/MS
Tebupirimfos 96182-53-5 Organophosphorus Insecticide 68693 2.5 1.3 4.6 2.3 68913 0.209465 0.104733 LC/MS/MS
Tebupirimfos oxon 1035330-36-9 Organophosphorus Insecticide degradate 68694 1.5 0.8 2.8 1.4 68911 0.212762 0.106381 LC/MS/MS
Tefluthrin 79538-32-2 Pyrethroid Insecticide 67731 1.3 0.7 2.4 1.2 67733 0.196139 0.098069 GC/MS/MS
Tetraconazole 112281-77-3 Azole Fungicide 66654 1.2 0.6 4.6 2.3 66656 0.223293 0.111647 LC/MS/MS
Tetramethrin 7696-12-0 Pyrethroid Insecticide 66657 1.9 0.9 2.7 1.4 66659 0.38649 0.193245 LC/MS/MS
Thiabendazole 148-79-8 Benzimidazole Fungicide 67161 3.4 1.7 4.5 2.2 NA NA NA LC/MS/MS
Thiacloprid 111988-49-9 Neonicotinoid Insecticide 68485 2.5 1.2 4.3 2.2 54398 0.227131 0.113566 LC/MS/MS
Thiamethoxam 153719-23-4 Neonicotinoid Insecticide 68245 1.1 0.5 3.5 1.7 68247 0.206244 0.103122 LC/MS/MS
Thiamethoxam Degradate (NOA-355190) 902493-06-5 Neonicotinoid Insecticide degradate 53568 2.9 1.4 5.2 2.6 54399 0.20702 0.10351 LC/MS/MS
Thiamethoxam Degradate (NOA-407475) Not Available Neonicotinoid Insecticide degradate 53576 5.4 2.7 NA NA NA NA NA LC/MS/MS
Thiobencarb 28249-77-6 Thiocarbamate Herbicide 65107 2.4 1.2 4 2 64171 0.215102 0.107551 LC/MS/MS
Tolfenpyrad 129558-76-5 Pyrazole Insecticide 51866 3.3 1.6 3.5 1.7 54400 0.252219 0.126109 LC/MS/MS
Triadimefon 43121-43-3 Azole Fungicide 67741 1.5 0.8 3.4 1.7 67743 0.392488 0.196244 LC/MS/MS
Triadimenol 55219-65-3 Azole Fungicide 67746 2.4 1.2 2.2 1.1 67748 0.472943 0.236472 LC/MS/MS
Triallate 2303-17-5 Thiocarbamate Herbicide 68710 9.4 4.7 9.6 4.8 68919 0.818329 0.409164 LC/MS/MS
Tribufos 78-48-8 Organophosphorus Defoliant 68711 2.8 1.4 2.2 1.1 39050 0.236903 0.118451 LC/MS/MS
Trifloxystrobin 141517-21-7 Strobin Fungicide 66660 2.6 1.3 4 2 66662 0.204114 0.102057 LC/MS/MS
Triflumizole 68694-11-1 Azole Fungicide 67753 2.5 1.3 3.1 1.6 67755 0.194873 0.097437 LC/MS/MS
Trifluralin 1582-09-8 2,6-Dinitroaniline Herbicide 65108 2.6 1.3 4.3 2.2 62902 0.186783 0.093391 GC/MS/MS
Triticonazole 131983-72-7 Azole Fungicide 67758 2.6 1.3 3.7 1.9 67760 0.199992 0.099996 LC/MS/MS
Valifenalate 283159-90-0 Acylamino Acid Fungicide 54360 2 1 4.8 2.4 54441 0.179406 0.089703 LC/MS/MS
Vinclozolin 50471-44-8 Dicarboximide Fungicide NA NA NA NA NA 67765 0.179406 0.089703 GC/MS/MS
Zoxamide 156052-68-5 Amide Fungicide 67768 1.7 0.8 3.8 1.9 67770 0.3946 0.1973 LC/MS/MS
Table 3.1.    Method detection and reporting limits for pesticides dissolved in water and sediments measured by the U.S. Geological Survey Organic Chemistry Research Laboratory.

Conversion Factors

International System of Units to U.S. customary units

Multiply By To obtain
meter (m) 3.281 foot (ft)
gram (g) 0.03527 ounce, avoirdupois (oz)
hectare (ha) 2.47105 acre

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F = (1.8 × °C) + 32.

Datum

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Supplemental Information

Specific conductance is in microsiemens per centimeter at 25 degrees Celsius (µS/cm at 25 °C).

Concentrations of chemical constituents in water are in either milligrams per liter (mg/L) or micrograms per liter (µg/L).

Abbreviations

DOC

dissolved organic carbon

ELISA

enzyme-linked immunosorbent assay

EPA

U.S. Environmental Protection Agency

FNU

Formazin Nephelometric Units

GC

gas chromatography

LC

liquid chromatography

MS/MS

tandem mass spectrometry

PCA

principal components analysis

PSU

practical salinity units

USGS

U.S. Geological Survey

For more information concerning the research in this report, contact the

Director, California Water Science Center

U.S. Geological Survey

6000 J Street, Placer Hall

Sacramento, California 95819

https://www.usgs.gov/centers/ca-water/

Publishing support provided by the Science Publishing Network,

Sacramento Publishing Service Center

Disclaimers

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested Citation

Feyrer, F.V., Acuña, S., Buxton, J.M., Enos, E.R., Hladik, M.L., Orlando, J., and Young, M.J., 2025, Environmental characteristics of select managed ponds in the Sacramento–San Joaquin Delta—Implications for native fish conservation and research: U.S. Geological Survey Open-File Report 2025–1040, 35 p., https://doi.org/10.3133/ofr20251040.

ISSN: 2331-1258 (online)

Study Area

Publication type Report
Publication Subtype USGS Numbered Series
Title Environmental characteristics of select managed ponds in the Sacramento–San Joaquin Delta—Implications for native fish conservation and research
Series title Open-File Report
Series number 2025-1040
DOI 10.3133/ofr20251040
Publication Date July 23, 2025
Year Published 2025
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) California Water Science Center
Description Report: viii, 35 p.; Data Release
Country United States
State California
County Contra Costa County, San Joaquin County
Other Geospatial Bacon Island, Bouldin Island, Holland Tract Island, Webb Tract Island
Online Only (Y/N) Y
Additional publication details