Results and Conclusions from a Decade of Bioassessment Monitoring in Marin County NBWA Watershed Council Meeting February 23, 2010 Chris Sommers (EOA)

Results and Conclusions Results and Conclusions from a Decade of from a Decade of

Bioassessment Monitoring Bioassessment Monitoring in Marin Countyin Marin County

NBWA Watershed Council Meeting

February 23, 2010

Chris Sommers (EOA) &

Terri Fashing (MCSTOPPP)

Ecological Integrity

Slides 2-5 from: Harrington, Jim. 2004. Bioassessment Monitoring. Dept of Fish and Game Aquatic Bioassessment Laboratory. Online presentation: http://www.sacriver.org/documents/2004/water_quality_workshop/Harrington.pdf

Ecological Integrity

From

Degradation: Ecological Integrity

Why Bioassessments?

Interpret effects of physical habitat and water quality • Benthic Macroinvertebrates (BMIs) integrate

effects due to long life cycles/limited migration• BMIs sensitive to site-specific stressors • More direct measure of ecological condition

Sensitive Organisms in Streams

Expected response to stress: abundance and proportion

Plecoptera - Stoneflies

Ephemeroptera - Mayflies

Trichoptera - Caddisflies

Photo Credit: Bene’ DaSilvaPhoto Credit: DFG ABL

Photo Credit: DFG ABL

Tolerant Organisms in Streams

Expected response to stress: abundance and proportion

• Midgeflies• Worms• Leeches• Snails Midge

Photo Credit: CA DFG ABL

MCSTOPPP originally implemented their bioassessment program to:

1. Measure the ecological health of creeks and watersheds in Marin County and detect changes that occur over time;

2. Evaluate potential land use and other stressor-related impacts to the ecological health of creeks and watersheds; and

3. To inform and educate the public about the ecological condition of creeks and watersheds.

Background - Objectives

1. Ecological Condition (Status): • Ecological condition of selected creek sites in Marin County?

2. Changes in Ecological Condition Over Time (Trends):

• Intra-annual and inter-annual variability at selected creek sites?

3. Stressor Impacts: • What natural and human-caused factors relate to patterns of

BMI taxonomic composition at selected creek sites?

4. If MCSTOPPP Conducts Bioassessments in Future :

• What are suggested program adaptations?

Focused Questions

Sampling HistorySample Year Agency/Program Index Period # Sites

1999 MCSTOPPP Fall 17

2000 MCSTOPPP Fall 23

2000 MCSTOPPP Spring 30


2001 SWAMP Spring 30




2005 SWAMP Spring 14


2006 FNC/MCSTOPPP Spring 4

2007 FNC/MCSTOPPP Spring 6


Methods History

Program Protocol Years HabitatBMI

Count

Physical

Habitat

Method

MCSTOPPP & SWAMP

CSBP

(3 samples per reach)

1999 -2004

Target Riffle 900Qualitative PHAB

MCSTOPPP & Friends of Novato Creek

USEPA/SWAMP (composite)

2005-2007

Target Riffle 500Qualitative PHAB

MCSTOPPPSWAMP

(composite)2009 Reach-wide 500*

Qualitative & Quantitative PHAB

*Municipal Regional Permit requires 600 organisms.

Primary Data Evaluation Tools

North Coast Benthic-Index of Biotic Integrity (B-IBI)• Tool used to understand

biological condition• End-point of multi-metric

approach• 257 sites - Marin County

to Oregon/California border

Figure from North Coast B-IBI Development. X axis represents a multivariate watershed condition axis.

North Coast B-IBI Metrics/Scoring

Identified reference and non-reference sites (many Marin County)

Screened 77 Metrics for:1. Sufficient range for scoring2. Responsiveness to watershed scale and reach scale

disturbance variables– Percent watershed unnatural– Percent watershed in agricultural– Road density in local watershed– Qualitative channel alteration score– Percent sand and fine substrates– Conductivity– Total phosphorous

3. Discrimination between Reference and Test sites4. Lack of correlation with other responsive metrics

North Coast B-IBI Metrics/Scoring

Eight metrics selected – weighted equally• EPT Richness • Coleoptera Richness• Diptera Richness• % Intolerant Individuals• % Non Gastropod Scraper Individuals• % Predator Individuals• % Shredder Taxa

Overall Score: • 0-100 Scale – 5 categories• Very good to very poor

Very Good 81-100Good 61-80Fair 41-60Poor 21-40Very Poor 0-20

Primary Evaluation Tools Con’d

Nonmetric Multidimensional Scaling (NMS) Ordination • Evaluate relative similarity of samples based

on BMI taxonomic composition• Generate graph showing sites oriented in

relative space • Distance between site graph points increases

with increasing taxonomic dissimilarity • Evaluate quantitative relationships and

clustering via categorical variables

Primary Evaluation Tools Quantitative Environmental Variables

• Overlay of lines radiating from center of graph• Each line indicates direction and strength of

correlation with the graph axes– Elevation– Precipitation – Substrate size– Qualitative physical habitat assessment (PHAB)

score– Weighted mean habitat type– Canopy cover

Categorical Environmental Variables• Watershed Drainage: Bay or Ocean-draining• Adjacent Land use: urban, mixed, rural residential,

grazing/agriculture, and open space• Flow Regime: Perennial and intermittent flow

Precip r = 0.69

-2.5

-2.5

-1.5 -0.5 0.5 1.5

-1.5

-0.5

0.5

Environmental Variability of 74 Bay Area Reference Sites

Axis 1 (61.8%)

Axi

s 2

(1

7.8

%)

Flow Non-perennialPerennial

What is the ecological condition of selected creek

sites in Marin County?

B-IBI Results from Watersheds

Biotic condition - B-IBI scores 0-100• Less confidence in result with limited data

and/or unexpected score• Validity of averaging scores is questioned

B-IBI Score Ranges – Bayside Watersheds

Very Good

Good

Fair

Poor

Very Poor

Arroyo Corte Madera

Corte Madera Creek

Miller Creek

Novato Creek

Very Good

Good

Fair

Poor

Very Poor

Arroyo Corte Madera

Corte Madera Creek

Miller Creek

Novato Creek

B-IBI Score Ranges – Oceanside Watersheds

Very Good

Good

Fair

Poor

Very Poor

Pacific Ocean Tributaries

LagunitasCreek

Walker Creek

Very Good

Good

Fair

Poor

Very Poor

Pacific Ocean Tributaries

LagunitasCreek

Walker Creek

B-IBI Scores in West Marin Vs. East Marin Watersheds

33%

37%

21%

7%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1

Per

cen

tag

e o

f S

amp

ling

Sta

tio

ns

Very Good

Good

Fair

Poor

Very Poor

Draining into the Pacific Ocean (n = 45)

(Including Tomales Bay)

Draining to North San Francisco Bay (n = 43) 2%

4%

15%

30%

38%

13%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1

Per

cen

tag

e o

f S

amp

ling

Sta

tio

ns

Very Good

Good

Fair

Poor

Very Poor

Graph style borrowed from Ruby 2007. Accessed online: http://www.cccleanwater.org/_pdfs/2007_CCMAP_Report.pdf

What is the intra-annual and inter-annual variability in ecological

condition at selected creek sites?

Seasonal Variations in BMI Community Composition

Seasonal Variations in B-IBI Scores

Site Code

Average B-IBI ScoreDifference between

Fall & Spring Average B-IBI Scores

Land Use ElevationFall Season

SpringSeason

COR060 41 10.5 30.5 Urban 30

MIL060 51.5 32.5 19 Urban 130

MIL020 37.5 20 17.5 Urban 35

MIL040 39 21.5 17.5 Urban 50

MIL050 43 27 16 Urban 85

NOV120 26 11.5 14.5 Urban 30

NOV195 49 38.5 10.5 Ag/Grazing 90

NOV210 50.5 40.5 10 Ag/Grazing 120

ACM110 56.5 49.5 7 Mixed 195

NOV160 25 19.5 5.5 Urban 30

ACM070 15 14.5 0.5 Urban 10

COR120 22.5 26 -3.5 Urban 45

ACM140 62 68.5 -6.5 Mixed 380

Inter-Annual Variation

0

20

40

60

80

100A

CM

140

CO

R29

0

NO

V24

0

AC

M11

0

MIL

080

AC

M10

0

NO

V05

0

CO

R17

1

MIL

060

CO

R08

0

CO

R21

0

CO

R17

0

NO

V19

5

CO

R20

0

MIL

040

NO

V18

0

MIL

020

CO

R12

0

NO

V13

0

NO

V16

0

CO

R14

0

NO

V12

0

NO

V03

0

AC

M07

0

CO

R06

0

NO

V07

0

Incr

ea

sing

Inte

r-A

nnu

al V

aria

bili

ty

Site Code Mean IBI Score Coefficient of VariationNOV160 19 0.05

ACM110 52 0.09

ACM140 65 0.1

MIL020 21 0.11

ACM100 44 0.16

ACM070 13 0.16

NOV240 58 0.19

COR171 39 0.23

COR060 11 0.23

NOV050 39 0.24

MIL040 25 0.26

COR080 37 0.27

MIL060 37 0.28

COR210 34 0.29

NOV030 14 0.3

NOV120 14 0.33

NOV195 33 0.34

COR290 60 0.41

MIL080 44 0.42

COR170 33 0.45

NOV070 7 0.46

COR120 20 0.49

NOV180 23 0.51

NOV130 19 0.59

COR200 25 0.61

Very Good 81-100Good 61-80Fair 41-60Poor 21-40Very Poor 0-20

Inter-Annual Variation

What natural and anthropogenic factors explain

patterns in BMI taxonomic composition and B-IBI scores

at selected creek sites?

Natural Variation?

Bayside vs. Oceanside Watersheds

Flow Regime or Orientation

Average Site-Specific B-IBI Score

Countywide Average

B-IBI Score Flow Regime Site CodeNorth Bay Draining

WatershedsPacific Ocean Draining

Watersheds

Perennial

RDW100 - 76

MIL090 60 -

MIL080 44

LAG380 - 85

LAG335 - 75

LAG190 - 86

LAG180 - 78

Perennial Average B-IBI Score 52 80 72

Intermittent

NOV240 58 -

NOV080 53 -

MRS020 - 78

COR290 60 -

Intermittent Average B-IBI Score 57 78 62

Average B-IBI Score 55 80 67

Anthropogenic Factors – Land Use

Physical Habitat

Arroyo Corte Madera Del

Presidio

ACM140 – ACM del Presidio above Blithedale Park Sign

B-IBI Score - Rating• F1999 70 - Good• S2000 66 – Good• F2000 54 – Fair• S2001 71 – Good• S2009 58 – Fair

ACM100 – Old Mill Creek above Cascade Road Bridge

B-IBI Score - Rating• S2000 48 – Fair• F2000 24 – Poor• S2001 41 – Fair• S2009 50 – Fair

ACM080 – Warner Creek at Boyle Park

B-IBI Score – Rating• S2009 18 – Poor

Corte Madera Creek

COR091 – Bill Williams Creek above Water Main Crossing

S2009 71 - Good

COR210 - San Anselmo Creek At Pacheco (US of Fairfax Creek)F1999 42 – FairS2000 25 – PoorF2000 39 – FairS2004 29 – PoorS2005 45 - FairS2006 28 – PoorS2009 48 – Fair

COR140 - Sleepy Hollow Creek at Drake High School

B-IBI Score - Rating• S2000 26 – Poor• F2000 42 – Fair• S2006 8 – Very Poor• S2009 13 – Very Poor

Miller Creek

MIL040 & MIL041

MIL040• F1999 42 – Fair• S2000 25 – Poor• F2000 36 – Poor• S2001 18 – Very Poor• S2004 31 – Poor

MIL041• S2009 14 – Very Poor

Novato Creek Watershed

NOV140 - Vineyard Creek at Mill Rd.

• S2000 22 – Poor• S2001 36 – Poor• S2006 14 – Very Poor• S2009 10 – Very Poor

NOV070 – Arroyo San Jose at Ignacio

• S2004 4 – Very Poor• S2005 10 – Very Poor• S2009 6 – Very Poor

Lagunitas Creek

Watershed

LAG240 - San Geronimo Creek at White Horse

S2001 84 – Very Good S2009 61 - Good

LAG270 - San Geronimo Creek at Creamery Gulch

S2001 73 – Good S2009 44 - Fair

LAG289 - San Geronimo Creek Downstream of MMWD Driveway

S2009 45 - Fair

West Marin Coastal Creeks

Walker Creek Watershed

Conclusions

Ecological Condition• Results only applicable to selected (targeted) sites• B-IBI scores range from 4 to 89 (v. poor to v. good)

– Low scoring sites > urban land uses upstream

• Sites with “very good” quality rating:– higher elevations with non-urban land uses upstream – considered reference in Draft B-IBI for Bay Area creeks

• B-IBI scores lower and more spatially variable in N. San Francisco Bay draining watersheds

• Reference sites with intermittent flow appear to have similar B-IBI scores to perennial sites

Conclusions Cond Variability in B-IBI Scores

• Intra-Annual Variability (Fall vs. Spring)– Distinctly different BMI communities– Among sites, fall communities more similar than spring – Higher B-IBI scores in fall compared to spring samples

• Inter-annual Variability (Spring Season):– Substantial in less impacted sites (reference)

Difficult to account for natural variability at non-reference sites

– Confounds conclusions on trends in biologic condition at sites– However, IBI Quality Ratings (very poor to very good) generally

consistent at sites Consider 10% error in B-IBI scoreNo trends (clear changes) detected at sites sampled multiple times

Conclusions Con’d

Natural and Anthropogenic Influences• Natural Variation

– Elevation is an important factor (could be natural or land use/urban surrogate)

– Orientation (Ocean vs. Bay) important factor (natural or land use/urban surrogate?)

– Precipitation also likely important (SF Bay B-IBI)– Stratification?

• Anthropogenic Factors– Correlations with habitat type and qualitative PHAB scores– Urban signal

If MCSTOPPP Conducts Future Monitoring…

Recommendations– Review existing monitoring objectives– Create succinct and well defined management

questions and consider:spatial scale, time, indicator type and levels of

confidence desired

– Use management questions to inform future monitoring design (targeted or probabilistic)

– Phase II permit – required monitoring– BASMAA Regional Monitoring Coalition

Example Management QuestionsSMC and RMC Core

Management Questions • Are conditions in creeks/rivers protective, or likely to be

protective, of beneficial uses?

• What is the extent and magnitude of the current or potential problems in creeks/rivers?

• What is the relative urban runoff contribution to the problem(s) in creeks/rivers?

• What are the sources to urban runoff that contribute to creek/river problem(s)?

• Are conditions in creeks/rivers getting better or worse

If Future Monitoring Con’d… Recommendations

• Improve ability to detect trends in ecological condition at sites:

– Establish site-specific monitoring questions– Consider using power analysis to determine

optimal sampling frequencyLook at past temporal variability

– Trends monitoring: different from stormwater program or BMP effectiveness monitoring

Consider spatial extent of implementation and level of change expected 0

20

40

60

80

100

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

B-I

BI S

core

Reference Treatment

If Future Monitoring Con’d…

Recommendations – Natural and Anthropogenic Influences• Detecting BMI stressors and sources is challenging,

especially in non-point situations• Varying spatial and temporal scales• Build conceptual models to guide more refined

assessments• Build models based on primary resource (e.g.

steelhead/Coho) • Additional site-specific complementary information for

hypothesis testing of conceptual model

SCVURPPP Example Multi-Year Monitoring and Assessment Process

Watershed Characterization

Screening Level Monitoring

Conceptual Model Building

Best Management Practice Implementation

Investigative Monitoring & Source identification 4. What are the sources to urban

runoff that contribute to receiving water problem (s)?

1. Are conditions in receiving waters protective, or likely to be protective, of beneficial uses?

3. What is the relative urban runoff contribution to the receiving water problem (s)?

5.Are conditions in receiving waters getting better or worse?

TRENDS2. What is the extent and

magnitude of the current or potential receiving water problems?

SCVURPPP Lessons Learned Screening Level Monitoring (2002-2007)

• Rotating Watershed Approach • Targeted Design (70+ sites)

– Conventional parameters (DO, temp, pH…)– Chemistry (metals and organics)– Aquatic Toxicity– Pathogen Indicators– BMI Bioassessments & Physical Habitat Assessments– Limited Fish Surveys

• All Non-Stormwater Sampling Events (Dry Weather) Contaminant concentrations in creek water and

bedded sediments are consistently below objectives/guidelines

Aquatic habitat condition appears to correlate well with IBI scores

• Significant changes to creek hydrology (via urbanization) and associated alterations to geomorphology and habitat structure

Pesticides (pyrethroids) remain an issue

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Biological Condition

Physical Habitat Quality


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Parting Thoughts….

Assessment of municipal stormwater programs or specific BMP effectiveness can be conducted using many different methods…

Thank You!!

Conceptual (sediment associated) Pollutant Dose and BMI Exposure Relationship

Possible Exposure Period

Se

dim

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t A

ss

oc

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ollu

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Runoff Events or Sediment/Pollutant Transport

Documents

Results and Conclusions from a Decade of Bioassessment Monitoring in Marin County NBWA Watershed Council Meeting February 23, 2010 Chris Sommers (EOA)