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Contaminant Concentrations in Sport Fish from San Francisco Bay: 2014

San Francisco Estuary Institute (SFEI) | January 1st, 2014

Summary

This summary report presents results from a 2014 survey of contaminants in San Francisco Bay sport fish, as well as an additional 2015 sampling of sport fish in Artesian

This summary report presents results from a 2014 survey of contaminants in San Francisco Bay sport fish, as well as an additional 2015 sampling of sport fish in Artesian Slough in Lower South Bay. This monitoring effort represents the seventh round of sport fish contaminant monitoring conducted by the Regional Monitoring Program for Water Quality in San Francisco Bay (RMP). This technical report is intended for agency staff charged with managing water quality issues related to bioaccumulation of contaminants in San Francisco Bay. The RMP began sport fish monitoring in 1997, following a pilot study conducted by the Bay Protection and Toxic Cleanup Program in 1994. Data collected through this monitoring program provides updates on the status and long-term trends of contaminants in Bay sport fish, and are used to update human health consumption advisories and evaluate the effectiveness of regulatory and management efforts to reduce the impacts of contaminants of concern in the Bay. Key analyses in this report include comparisons of concentrations to human health and regulatory thresholds, spatial trend evaluation, and temporal trend evaluation. Mercury, polychlorinated biphenyls (PCBs), dioxins, selenium, polybrominated diphenyl ethers (PBDEs), and perfluoroalkylated substances (PFASs) were analyzed across sixteen fish species collected at eight locations in San Francisco Bay and Artesian Slough. Fish species were selected based on a number of criteria, including species that are popular for consumption, are sensitive indicators of problems (accumulating relatively high concentrations of contaminants), are widely distributed, represent different exposure pathways (benthic vs. pelagic), and have been monitored in the past. Concentrations were compared to numeric human health thresholds established by the California Office of Environmental Health Hazard Assessment (OEHHA) for mercury, PCBs, selenium, and PBDEs. Results were also compared to regulatory thresholds for mercury, PCBs, and selenium, as well as non-regulatory screening value for dioxins, which have been established in Total Maximum Daily Load (TMDL) regulations by the San Francisco Bay Regional Water Quality Control Board (Water Board). The OEHHA fish consumption advisory is primarily driven by human exposure risks to mercury and PCBs. The 2014 data show that mercury and PCB concentrations remain high and widespread, indicating that these contaminants continue to pose the greatest human and wildlife health risks. Mercury concentrations exceeded OEHHA’s no consumption threshold for the sensitive population (women 18-45 and children 1-17) in several white sturgeon and striped bass samples, while PCB concentrations exceeded the no consumption threshold in Pacific sardine and white sturgeon samples. The spatial distribution of contamination has remained consistent over time, reflecting current knowledge of contaminated source areas targeted for management activities. Recent data showed no clear evidence of Bay-wide declines in either mercury or PCBs, although progressively lower PCB concentrations have been observed in recent years near Berkeley and in San Pablo Bay.

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Development of Recommended Flow Targets to Support Biological Integrity Based on Regional Flow-ecology Relationships for Benthic Macroinvertebrates in Southern California Streams

Southern California Coastal Water Research Project | March 23rd, 2017

Summary

Changes to instream flow are known to be one of the major factors that affect the health of biological communities. Regulatory, monitoring, and management programs are in

Changes to instream flow are known to be one of the major factors that affect the health of biological communities. Regulatory, monitoring, and management programs are increasingly using biological community composition, particularly benthic invertebrates, as one measure of instream conditions, stormwater project performance, or regulatory compliance with NPDES or other requirements and regulations. Understanding the relationship between changes in flow and changes in benthic invertebrate communities is, therefore, critical to informing decisions about ecosystem vulnerability, causes of stream and watershed degradation, and priorities for future watershed management. There are many approaches to developing flow-ecology relationships that relate hydrologic change to responses in instream biological communities that can be used to establish management targets. The Ecological Limits of Hydrologic Alteration (ELOHA) framework (Poff et al. 2010) provides a way to assess the effect of flow alteration on the condition of biological communities (vs. individual taxa) on a regional basis. Consequently, it is a useful approach for setting targets across a wide range of geographies and stream types where comprehensive detailed site-specific investigations are not practical. The framework includes elements of stream classification, estimation of flow alteration and development of flow ecology relationships based on the response of biological communities to changes in flow.

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DRERIP Ecosystem Conceptual Model: Delta Aquatic Foodweb

California Department of Fish and Wildlife (CDFW) | October 3rd, 2008

Summary

This model is a stylization of the actual food web dynamics of the Sacramento-San Joaquin Delta, which are highly dynamic. The region itself comprises a variety of habita

This model is a stylization of the actual food web dynamics of the Sacramento-San Joaquin Delta, which are highly dynamic. The region itself comprises a variety of habitats, determined by salinity regimes, residence time, hydrology, benthos and physical structure. These physical parameters, or drivers, determine species composition and trophic relationships. The Delta is a tidal system which is subject to varying water inflow. Because inflow and outflow vary as the result of anthropogenic alterations and water management needs, habitats are not static. Rather they are subject to hourly, daily, seasonal and inter-annual variation, and different organisms respond in different ways to these time scales, depending upon their own life histories. Thus salinity and temperature regimes may create different outcomes from food web interactions, based upon how species distributional and recruitment patterns overlap. In general, food web linkages are not static or linear. Organisms switch feeding strategies opportunistically, and these patterns of variability in feeding strategy tend to increase with trophic level. Many organisms, particularly plankton, undergo many generations in the course of a year, and selective forces may allow for rapid evolution which can alter habitat preferences or other life history characteristics. The Delta food web is further dynamic in that new species are regularly introduced into the Estuary, competing with, replacing, or preying upon other organisms. For example, the overbite clam, Corbula amurensis, was introduced in 1986, precipitating a cascade of changes that are still not wholly understood. Zebra and quagga mussels are expected to invade the Delta within the next few years, and will bring further changes. The topology of a food web model will be necessarily complex given these factors. Even without such variability, the potential linkages create a spider web of relationships that is difficult if not impossible to disentangle. In order to create a working model of the Delta food web that is useful for education, for hypothesis?generation, and for management decision?making, it is necessary to create limits to what linkages will be examined. In order to do this, this Delta food web model focuses on organisms that supply food for fish. This is particularly important given the recent concern for pelagic organism decline, which is described mostly for fishes, some of which are listed as endangered or threatened. A key assumption is that fish are integrators of ecosystem function. Also included in the model are invasive organisms that have a large impact on food web dynamics (such as C. amurensis), as are organisms that are particularly abundant (such as the copepod Limnoithona tetraspina), whether or not they are used directly by fish.

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DRERIP Ecosystem Conceptual Model: Mercury

California Department of Fish and Wildlife (CDFW) | January 24th, 2008

Summary

Mercury has been identified as an important contaminant in the Delta, based on elevated concentrations of methylmercury (a toxic, organic form that readily bioaccumulates

Mercury has been identified as an important contaminant in the Delta, based on elevated concentrations of methylmercury (a toxic, organic form that readily bioaccumulates) in fish and wildlife. There are health risks associated with human exposure to methylmercury by consumption of sport fish, particularly top predators such as bass species. Original mercury sources were upstream tributaries where historical mining of mercury in the Coast Ranges and gold in the Sierra Nevada and Klamath-Trinity Mountains caused contamination of water and sediment on a regional scale. Remediation of abandoned mine sites may reduce local sources in these watersheds, but much of the mercury contamination occurs in sediments stored in the riverbeds, floodplains, and the Bay-Delta, where scouring of Gold-Rush-era sediment represents an ongoing source. Conversion of inorganic mercury to toxic methylmercury occurs in anaerobic environments including some wetlands. Wetland restoration managers must be cognizant of potential effects on mercury cycling so that the problem is not exacerbated. Recent research suggests that wetting-drying cycles can contribute to mercury methylation. For example, high marshes (inundated only during the highest tides for several days per month) tend to have higher methylmercury concentrations in water, sediment, and biota compared with low marshes, which do not dry out completely during the tidal cycle. Seasonally inundated flood plains are another environment experiencing wetting and drying where methylmercury concentrations are typically elevated. Stream restoration efforts using gravel injection or other reworking of coarse sediment in most watersheds of the Central Valley involve tailings from historical gold mining that are likely to contain elevated mercury in associated fines. Habitat restoration projects, particularly those involving wetlands, may cause increases in methylmercury exposure in the watershed. This possibility should be evaluated. The DRERIP mercury conceptual model and its four submodels (1. Methylation, 2. Bioaccumulation, 3. Human Health Effects, and 4. Wildlife Heath Effects) can be used to understand the general relationships among drivers and outcomes associated with mercury cycling in the Delta. Several linkages between important drivers and outcomes have been identified as important but highly uncertain (i.e. poorly understood). For example, there may be significant wildlife health effect of mercury on mammals and reptiles in the Delta, but there is currently very little or no information about it. The characteristics of such linkages are important when prioritizing and funding restoration projects and associated monitoring in the Delta and its tributaries.

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Ecological Condition Assessments of California’s Perennial Wadeable Streams (2000 through 2006)

California State Water Resources Control Board (SWRCB) | October 15th, 2007

Summary

The struggle to adequately monitor the condition of waterbodies with limited financial resources is a challenge faced by water resource agencies worldwide. For a resource

The struggle to adequately monitor the condition of waterbodies with limited financial resources is a challenge faced by water resource agencies worldwide. For a resource agency to adequately meet its obligations to monitor and assess the condition of its waterbodies it must provide information at both the site-specific scale and the scale of the entire resource. This dual obligation requires different monitoring strategies. Traditional targeted monitoring (in which site locations are selected to meet specific monitoring goals) is essential for answering many key water quality monitoring questions (e.g., what is the condition of specific sites, how do site conditions vary seasonally and annually, where are the best and worst sites, what are the primary water quality problems at specific sites, what are the effects of specific watershed activities and/or BMPs). Although this approach can generate much valuable water quality data, it is unable to provide information about the overall condition of large populations of resources (e.g., all streams, lakes or wetlands in a state) unless the monitoring entity is prepared to perform a complete census of the targeted resource. Site specific monitoring approaches are also unable to provide an objective context for interpreting the data they generate. However, the perspective provided from this context is a necessary logical foundation for a sound monitoring program. In the US, the need for a broader context for interpreting the results of targeted monitoring data has driven the development of alternate sampling designs at both the state and federal level. To meet this need, the U.S. EPA established its Environmental Monitoring and Assessment Program (EMAP), a long term research program designed to develop the tools and techniques needed for cost-effectively answering the fundamental status and trends questions in the Clean Water Act. The EMAP studies are based on a probabilistic survey design in which each sampling location represents a known proportion of the total resource of interest (e.g., percent of total stream length) with known statistical confidence. This design permits the inference of resource conditions for large geographic regions with a relatively small investment in sampling (Ringold et al. 1996, Olsen et al. 1999, Stevens and Olsen 2004). After completing assessments of the condition of Eastern lakes and the condition of wadeable streams in the Middle-Atlantic states, the EPA initiated a similar assessment of streams in the western states (WEMAP), which included a high density of sites in California. For the first time in 2006, the state of California used data from a probability survey to derive the condition assessments of its perennial streams in its 305(b) report to the US EPA (Ode and Rehn 2005, California State Water Resources Control Board 2006). These reports were developed to meet California’s obligation to monitor its compliance with the goal of biotic integrity stipulated under Clean Water Act §305(b). Prior to these report, the ABL has presented results of the Southern Coastal California intensification area (Rehn and Ode 2004), Northern Coastal California intensification area (Rehn et al. 2005) as demonstration projects. As the EPA’s Western EMAP sampling effort ended in 2003, the EPA strongly encouraged western states to continue the EMAP monitoring approach in their own state monitoring programs. Two monitoring programs in the California State Water Resources Control Board, the recently established Surface Water Ambient Monitoring Program (SWAMP) and the Non-Point Source Program (NPS) expressed interest in probabilistic sampling. In concert with (and with funding from) their counterparts in the EPA Region 9 Non-point Source Programs and Office of Water, NPS and SWAMP developed the California Monitoring and Assessment Program (CMAP) to provide an additional four years of statewide probabilistic sampling to support continued ecological condition assessments. The study designs used for these condition assessments were developed by the EPA’s Office of Research and Development. Since the state and federal NPS programs brought a strong interest in the relationship between non-point source pollution sources and aquatic life use, the sampling design was adapted to include an explicit stratification by landuse/ landcover.

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Ecological Condition Assessments of California’s Perennial Wadeable Streams: Highlights from the Surface Water Ambient Monitoring Program’s Perennial Streams Assessment (PSA ) (2000-2007)

California State Water Resources Control Board (SWRCB) | October 1st, 2011

Summary

Since 2000, California has conducted three successive probability surveys of its perennial streams and rivers, each with a focus on biological endpoints. These surveys ar

Since 2000, California has conducted three successive probability surveys of its perennial streams and rivers, each with a focus on biological endpoints. These surveys are now combined and are managed collectively by the Surface Water Ambient Monitoring Program (SWAMP) under its Perennial Streams Assessment (PSA) program. In 2010, SWAMP’s Perennial Streams Assessment (PSA) conducted the State Water Board’s eleventh continuous year of probability monitoring of perennial, wadeable streams. To date, the program has collected biological data (invertebrates, algae) and associated chemical and habitat data from approximately 850 probabilistic sites statewide. These surveys have produced a wealth of data that can and should be used to inform many decisions made by California’s water resource agencies. For example, the assessments in the 2006 California Water Quality Assessment Report (Clean Water Act Section 305(b) Report) were based in large part on data from these surveys. Data from these surveys were also used in the development of the 2010 Integrated Report. This report highlights some of the most significant results from the first eight years of PSA and demonstrates some ways that these data can go beyond 305(b) and 303(d) applications to improve California’s water quality programs. The results presented in this summary represent just a fraction of the potential uses of data generated by these ongoing surveys. As the data et becomes more robust, it will continue to support multiple uses for years to come. This report is organized around four questions that were used to frame management objectives for the State Water Board’s Non-Point Source Program (NPS), a major partner in PSA’s development: 1. What is the condition of California’s streams? 2. Is stream condition changing over time? 3. What is the relative condition of streams draining agricultural, urban and forested regions? 4. Which stressors have the strongest associations with biological condition? Future SWAMP reports will highlight the application of PSA data to various State Water Board water quality programs, including links to regional monitoring objectives.

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Ecological Health in the Nation’s Streams, 1993–2005

U.S. Geological Survey (USGS) | July 2nd, 2013

Summary

This report summarizes a national assessment of the ecological health of streams done by the U.S. Geological Survey's (USGS) National Water-Quality Assessment Program (NA

This report summarizes a national assessment of the ecological health of streams done by the U.S. Geological Survey's (USGS) National Water-Quality Assessment Program (NAWQA). Healthy functioning stream ecosystems provide society with many benefits, including water purification, flood control, nutrient recycling, waste decomposition, fisheries, and aesthetics. The value to society of many of these benefits is substantial; for example, sportfishing in the United States generates an estimated annual economic output of $125 billion, including more than 1 million jobs (National Research Council, 2005; American Sportfishing Association, 2008). Continued monitoring and assessment of the Nation’s streams is needed to support informed decisions that will safeguard this important natural and economic resource. The quality of streams and rivers is often assessed with measures of the chemical or physical properties of water. However, a more comprehensive perspective is obtained if resident biological communities are also assessed. Guidelines to protect human health and aquatic life have been established for specific physical and chemical properties of water and have become useful yardsticks with which to assess water quality. Biological communities provide additional crucial information because they live within streams for weeks to years and therefore integrate through time the effects of changes to their chemical or physical environment. In addition, biological communities are a direct measure of stream health—an indicator of the ability of a stream to support aquatic life. Thus, the condition of biological communities, integrated with key physical and chemical properties, provides a comprehensive assessment of stream health.

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Effects of wildfire on benthic macroinvertebrate assemblages in Southern California streams and implications for bioassessment monitoring programs

California State Water Resources Control Board (SWRCB) | June 13th, 2012

Summary

Wildfires are common in arid regions of southern California, sometimes burning as much as half a million acres in a season. These fires often cause dramatic impacts to th

Wildfires are common in arid regions of southern California, sometimes burning as much as half a million acres in a season. These fires often cause dramatic impacts to the vegetation and soils of regional watersheds and, consequently, to the streams that drain them. Water quality programs that monitor and regulate these systems have to account for the influence of these factors upon water quality measurements when making monitoring and regulatory decisions. This is true for traditional water quality measures (nutrients, metals, contaminants, etc.), but is especially important for integrative ecological condition indicators like bioassessment, the use of resident biological communities to infer water quality condition.

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Evaluation of the California State Water Resource Control Board’s Bioassessment Program

California State Water Resources Control Board (SWRCB) | May 15th, 2009

Summary

The State of California’s bioassessment, monitoring and assessment (M&A), and water quality standards (WQS) programs were reviewed in January 2008 using the

The State of California’s bioassessment, monitoring and assessment (M&A), and water quality standards (WQS) programs were reviewed in January 2008 using the U.S. EPA’s Critical Technical Elements and Programmatic Review process (Barbour and Yoder 2008; Quasney and Yoder 2008), which evaluates key components of these state programs and existing and planned capacities. The review process results in technical, policy, and management recommendations for building, refining and maintaining functional and effective bioassessment and M&A tools that support the full spectrum of WQS and management programs. This review was conducted by a two-person review team with national expertise at evaluating, building, and implementing state and tribal programs. Bioassessment, the use of resident aquatic biota as direct indicators of the biological integrity of water bodies, is a powerful tool for water resource regulatory programs. The need for state water quality agencies to develop and maintain robust bioassessment programs is underscored by the National Research Council’s critical review of state TMDL, M&A, and WQS programs (National Research Council 2001). The NRC’s review makes clear that all states need better biological endpoints, adequate M&A, and tiered aquatic life uses (TALU) in order to develop and refine appropriate and effective WQS that result in more accurate and appropriate protection for biological resources. While the federal Clean Water Act (CWA) has long required states to protect and restore the chemical, physical, and biological integrity of the nation’s waters, the California Water Boards have only recently begun to develop the tools, expertise and capacity that they will need in order to implement modernized WQS that protect biological integrity. However, because of the substantial investment in the development of bioassessment tools made since the mid-1990s by the state’s Department of Fish and Game, California is now positioned to initiate the process of integrating bioassessments into its WQS and monitoring and assessment programs via the development and implementation of narrative and numeric biocriteria.

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Final Technical Report #1: Condition Assessment of Coastal Streams in Southern and Central California

California Department of Fish and Wildlife (CDFW) | July 1st, 2004

Summary

Historical assessments of stream condition have usually focused on describing the chemical quality of streams. As we have made progress in controlling chemical problems�

Historical assessments of stream condition have usually focused on describing the chemical quality of streams. As we have made progress in controlling chemical problems it has become obvious that the ultimate concern is actually the health of the plants and animals that inhabit these streams (EPA 2000). Streams in good ecological condition provide habitat for diverse aquatic communities, and provide clean drinking water and recreational opportunities for people. Biological organisms in a stream integrate the many chemical and physical stressors that act on the stream ecosystem, thus stream condition can be determined by assessing appropriate biological indicators, or combinations of these indicators, called indices. California’s Aquatic Bioassessment Lab recently developed a benthic index of biotic integrity (B-IBI) for the central and southern coasts of California (Ode et. al. in review). The index is based on benthic macroinvertebrate (BMI) samples collected from 275 sites in this region by the US Forest Service, US EPA and regional Water Quality Control Boards. The index defines the composition of BMI assemblages when human disturbance is absent or minimal (reference conditions), and because it is based on metrics that are responsive to key stressor gradients, it allows detection of potential ecological impairment when BMI samples from test sites are compared to reference conditions. Thus, the B-IBI provides a yardstick for measuring ecological conditions, and allows us to categorize site conditions as either “Good”, “Fair” or “Poor” based on BMI assemblages.

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Lost Horse Valley 7-051
Lower Kingston Valley 6-021
Lower Mojave River Valley 6-040
Lucerne Valley 7-019
Malibu Valley 4-022
Means Valley 7-017
Mesquite Valley 6-029
Middle Amargosa Valley - 6-020
Middle Mojave River Valley 6-041
Mission Valley 9-014
Modoc) 5-004
Morongo Valley 7-020
Morro Valley 3-041
Napa-Sonoma Valley - Napa-Sonoma Lowlands 2-002.03
Needles Valley 7-044
Ocotillo-Clark Valley 7-025
Ogilby Valley 7-035
Ojai Valley 4-002
Orocopia Valley - 7-031
Owens Valley - Fish Slough 6-012.02
Owens Valley 6-012.01
Owl Lake Valley 6-088
Pahrump Valley 6-028
Palo Verde Mesa 7-039
Palo Verde Valley 7-038
Pamo Valley 9-024
Panamint Valley 6-058
Peach Tree Valley 3-032
Petaluma Valley 2-001
Pilot Knob Valley 6-051
Pinto Valley 7-006
Pipes Canyon Fault Valley 7-049
Pittsburgh Plain 2-004
Piute Valley 7-045
Pleasant Valley 4-006
Potrero Valley 9-029
Poway Valley 9-013
Raymond 4-023
Red Pass Valley 6-024
Redding Area - Anderson 5-006.03
Redding Area - Bowman 5-006.01
Redding Area - Enterprise 5-006.04
Redding Area - Millville 5-006.05
Redding Area - South Battle Creek 5-006.06
Rice Valley 7-004
Riggs Valley 6-023
Russell Valley 4-020
Sacramento Valley - Antelope 5-021.54
Sacramento Valley - Bend 5-021.53
Sacramento Valley - Butte 5-021.70
Sacramento Valley - Colusa 5-021.52
Sacramento Valley - Corning 5-021.51
Sacramento Valley - Los Molinos 5-021.56
Sacramento Valley - North American (5-021.64)
Sacramento Valley - North Yuba 5-021.60
Sacramento Valley - Red Bluff 5-021.50
Sacramento Valley - Solano 5-021.66
Sacramento Valley - South American 5-021.65
Sacramento Valley - South Yuba 5-021.61
Sacramento Valley - Sutter 5-021.62
Sacramento Valley - Vina 5-021.57
Sacramento Valley - Wyandotte Creek 5-021.69
Sacramento Valley - Yolo 5021.67
Salinas Valley - 180/400 Foot Aquifer 3-004.01
Salinas Valley - Atascadero Area 3-004.11
Salinas Valley - East Side Aquifer 3-004.02
Salinas Valley - Forebay Aquifer 3-004.04
Salinas Valley - Langley Area 3-004.09
Salinas Valley - Monterey 3-004.10
Salinas Valley - Paso Robles Area 3-004.06
Salinas Valley - Upper Valley Aquifer 3-004.05
Saline Valley 6-017
Salt Wells Valley 6-053
San Antonio Creek Valley 3-014
San Dieguito Creek 9-012
San Elijo Valley 9-023
San Felipe Valley 7-027
San Fernando Valley 4-012
San Gabriel Valley 4-013
San Jacinto 8-005
San Joaquin Valley - Chowchilla 5-022.05
San Joaquin Valley - Cosumnes (5-022.16)
San Joaquin Valley - Delta-Mendota 5-022.07
San Joaquin Valley - East Contra Costa 5-022.19
San Joaquin Valley - Eastern San Joaquin 5-022.01
San Joaquin Valley - Kaweah 5-022.11
San Joaquin Valley - Kern 5-022.14
San Joaquin Valley - Kings 5-022.08
San Joaquin Valley - Madera 5-022.06
San Joaquin Valley - Merced 5-022.04
San Joaquin Valley - Modesto 5-022.02
San Joaquin Valley - Pleasant Valley 5-022.10
San Joaquin Valley - Tracy 5-022.15
San Joaquin Valley - Tulare Lake 5-022.12
San Joaquin Valley - Tule 5-022.13
San Joaquin Valley - Turlock 5-022.03
San Joaquin Valley - Westside 5-022.09
San Joaquin Valley - White Wolf 5-022.18
San Juan Valley 9-001
San Luis Obispo Valley 3-009
San Luis Rey Valley - Lower San Luis Rey Valley 9-007.02
San Luis Rey Valley - Upper San Luis Rey Valley 9-007.01
San Marcos Area 9-032
San Mateo Valley 9-002
San Onofre Valley 9-003
San Pasqual Valley 9-010
Santa Barbara 3-017
Santa Clara River Valley - Fillmore 4-004.05
Santa Clara River Valley - Mound 4-004.03
Santa Clara River Valley - Oxnard 4-004.02
Santa Clara River Valley - Piru 4-004.06
Santa Clara River Valley - Santa Clara River Valley East 4-004.07
Santa Clara River Valley - Santa Paula 4-004.04
Santa Clara Valley - East Bay Plain 2-009.04
Santa Clara Valley - Niles Cone 2-009.01
Santa Clara Valley - San Mateo Plain 2-009.03
Santa Clara Valley - Santa Clara 2-009.02
Santa Cruz Mid-County 3-001
Santa Margarita 3-027
Santa Maria River Valley - Arroyo Grande 3-012.02
Santa Maria River Valley - Santa Maria 3-012.01
Santa Maria River Valley 3-012.02
Santa Maria Valley 9-011
Santa Rosa Valley - Santa Rosa Plain 1-055.01
Santa Ynez River Valley 3-015
Scott River Valley 1-005
Searles Valley 6-052
Seven Oaks Valley 8-008
Shasta Valley 1-004
Sierra Valley 5-012.01
Silver Lake Valley 6-034
Simi Valley 4-009
Soda Lake Valley 6-033
South San Diego River Valley 9-015
Superior Valley 6-049
Temecula Valley 9-005
Terwilliger Valley 7-026
Thousand Oaks Area 4-019
Tule Lake 1-002-01
Twentynine Palms Valley 7-010
Ukiah Valley 1-052
Upper Kingston Valley 6-022
Upper Mojave River Valley 6-042
Upper Ojai Valley 4-001
Upper Santa Ana Valley - Chino 8-002.01
Upper Santa Ana Valley - Cucamonga 8-002.02
Upper Santa Ana Valley - Rialto-Colton 8-002.04
Upper Santa Ana Valley - Riverside-Arlington 8-002.03
Upper Santa Ana Valley - San Bernardino 8-002.06
Upper Santa Ana Valley - San Timoteo 8-002.08
Upper Santa Ana Valley - Temescal 8-002.09
Upper Santa Ana Valley - Yucaipa 8-002.07
Vallecito-Carrizo Valley 7-028
Ventura River Valley - Lower Ventura River 4-003.02
Ventura River Valley - Upper Ventura River 4-003.01
Vidal Valley 7-042
Ward Valley 7-003
Warren Valley 7-012
West Salton Sea
Wingate Valley 6-019
Yuma Valley 7-036

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