ORD’s Environmental Monitoring and

Assessment Program (EMAP)

Sound Science for Measuring Ecological Condition

www.epa.gov/emap

Key EPA Monitoring Questions

• What are the current conditions of our ecosystems?

• Where are the conditions improving or declining?

• What stresses are associated with declines?

• Are our management programs and policies working?

What’s at Stake?• >$1B/y spent on monitoring

• Condition of estuaries, coastlines, streams, rivers, wetlands and lakes are still unknown.

• Effectiveness of protection and restoration programs and policies are often unknown

GOALS of EMAP• Develop the scientific basis for consistent,

unbiased, cost-effective measurement of the condition of the Nation’s aquatic ecosystems– Status– Trends

• Build state and tribal capacity for monitoring condition and transfer our technology

• Make data generally available to all stakeholders (STORET)

No additionalSampling (continue to Monitor as part of 5-year cycle)

Condition

Waterbody has high Probability of Impairment

305(b)Reports

WaterbodyImpairment Confirmed

303(d) List

TMDL Development

States conductProbability survey With suite of indicators

Remediation

Intensive sampling to confirm impairment

State of theEnvironmentReports

Associated Stressors

Point Source

Non-pointSource

Likelihood Criteria

Dose - Response

Comparison of # of Expected 303(d)Sites to known sites

< or >=

Accept State 303(d) list

Probability of ImpairmentAssessmentModels

Waterbody has low Probability of Impairment

De-list

WaterbodyNot impaired

Diagnosis

Integrated Integrated Monitoring Monitoring

Waterbody has Moderate Probability of impairment

Standards

Science Behind the Scenes

Population Identification

Variable Density Approaches

Frame Development

Spatial Balance

Panel Rotation

Variance Estimation

Status (Trends)

Index Construction

Index Calibration

Index Regionalization

Reference Condition

Ecoregion Framework

IndicatorsDesigns

=10%

23%

37%31%

10%15%

32%

43%

15%

28%

44%14%

35%

3%

32%

30%

Assessments

Partnerships

Analysis

Data

Field Sampling

Training

+

CWA: Resource Monitoring Needs

National Implementation

National Demonstration

Regional Demonstration

R-EMAP/Small Scale Tests

Impl

emen

tatio

n

Lan

d c

ove

r/u

se

Ind

icat

ors

Des

ign

Cla

ssif

icat

ion

Str

ata

Ref

eren

ceC

on

dit

ion

s

Nat

ion

ally

Co

nsi

sten

tD

esig

n

Science Barriers

CoastalCoastal

StreamsStreams

Large RiversLarge Rivers

Great LakesGreat Lakes

LakesLakes

WetlandsWetlands

Res

ou

rce

Are

as

EMAP Extramural Research Areas

• Coastal Initiative – 60% to State Co-ops• Western Pilot – 60% to State Co-ops • GRI – 60% to State and other Co-ops • R-EMAP – 100% to EPA Regions • STAR – 100% to Academic Research Institutions

STAR GrantsWestern Pilot

R-EMAPCoastal Initiative

GRI

EMAP Design Approach• Probabilistic Design Framework – Randomized statistical designs

that allow interpretation of monitoring data with known uncertainty, extrapolation to the entire population of interest with a small sample size, and the ability to statistically aggregate similar data to larger geographic areas

• Classification - meaningful groupings within resource types and/or ecosystem types to allow better statistical design and analysis

• Biological Indicators - Direct measures of aquatic ecosystem condition, integrates stressors, and the public can relate to them

– Streams, rivers, estuaries, lakes, reservoirs, wetlands

Probabilistic Survey Design Advantages• Representative and allows inference to system of interest• Adaptable to resource characteristics• Adjusts sample sizes to meet precision requirements • Adaptable to temporal and spatial scales of interest• Unbiased• Cost-effective

FullySupporting

87%

Not Supporting

13%

Traditional Targeted Monitoring

FullySupporting

13%

Not Supporting

87%

Probability Survey

Fully Supporting

95%

NotSupport

ing5%

Fully Supporting

75%

Not Supporting

25%

Delaware

Nebraska

Traditional Targeted Monitoring Probability Survey

Condition of streams

EMAP Uses Biological Indicators• Historic Aquatic Indicators – Measured

physical/chemical characteristics and related them to the biological condition of an aquatic system

• Aquatic Biological Indicators – Direct measure of condition of aquatic ecosystem, integrates stressors, and the public can relate

• Eutrophication of NE US lakes – 4219 mostly problem lakes sampled by states for 305(b)

– 2756 non-random lakes censused (Rohm et al. 1995)

– 344 lakes with EMAP probability design (11,076 lakes total)

• Alabama reduced the cost of estuarine monitoring by ~33%, and can now report on all estuarine waters

Effectiveness of Design%

Im

pair

ed L

akes

Sam

plin

g co

sts

Fish IBI

17%

17%

36%

31%

Proportion of Stream Length

(InsufficientData)

Good

Fair

Poor

% of Stream Length0% 10% 20% 30% 40%

Riparian Habitat

Sedimentation

Mine Drainage

Acidic Deposition

Tissue Contamination

Phosphorus

Acid Mine Drainage

24%

25%

14%

11%

10%

5%

1%Nitrogen

5%

Potential Stressors

0% 10% 20% 30% 40%

Introduced Fish 34%

Stream Conditions in MAHA

Degraded 30 ± 6%

Undegraded70 ± 6%

Degraded18 ± 8%

Undegraded82 ± 8%

Louisianian Province Virginian Province

Metals 42%

Toxicity 4%Contaminants 28%

Low D.O.

Habitat 14%

Unknown10% Unknown

39%

Contaminants 10%Both2%

Low DissolvedOxygen 49%

Condition

Stressors Associated with Degraded Condition

Estuarine Conditions

0

10

20

30

40

50

1991-93 1997-98

% a

rea

wit

h im

pair

ed b

enth

os

Statistical Change DetectionChange in Percent Area of Chesapeake Bay with Impaired Benthic Community

*

EMAP National Demonstrations

• Estuaries – All 24 marine coastal states monitoring with core EMAP design and indicators

• Streams – Mid-Atlantic States and 12 Western States

• Great Rivers – Mississippi River Basin

No additionalSampling (continue to Monitor as part of 5-year cycle)

Condition

Waterbody has high Probability of Impairment

305(b)Reports

WaterbodyImpairment Confirmed

303(d) List

TMDL Development

States conductProbability survey With suite of indicators

Remediation

Intensive sampling to confirm impairment

State of theEnvironmentReports

Associated Stressors

Point Source

Non-pointSource

Thresholds of Impairment

Dose - Response

Comparison of # of Expected 303(d)Sites to known sites

< or >=

Accept State 303(d) list

Probability of ImpairmentAssessmentModels (2 levels)

Waterbody has low Probability of Impairment

De-list

WaterbodyNot impaired

Diagnosis

Integrated Monitoring Integrated Monitoring and Assessmentand Assessment

Waterbody has Moderate Probability of impairment

Standards

1

2

3 5 8

4

6,79,10

101010

10

10

10

Example of Integrated Monitoring and Assessment with Maryland Biological Stream Survey Data

MBSS probability survey for benthic IBI and fish IBI measures of stream condition (impairment for BIBI < 3, FIBI < 3), chemical and physical measurements taken, land cover data available

Analysis:cumulative distribution functions (cdfs)conditional probabilitiesconditional cdfs

1

Condition of Streams in Maryland

54% of 1st order stream miles are impaired (BIBI < 3)

40% of 2nd order stream miles are impaired (BIBI < 3)

47% of 1st order stream miles are impaired (FIBI < 3)

24% of 2nd order stream miles are impaired (FIBI < 3)

Benthic IBI

Fra

ctio

n o

f Str

ea

m M

iles

1 2 3 4 5

0.0

0.2

0.4

0.6

0.8

1.0

stream order = 1

Benthic IBI

Fra

ctio

n o

f Str

ea

m M

iles

1 2 3 4

0.0

0.2

0.4

0.6

0.8

1.0

stream order = 2

Fish IBI

Fra

ctio

n o

f Str

ea

m M

iles

1 2 3 4

0.0

0.2

0.4

0.6

0.8

1.0

stream order = 1

Fish IBI

Fra

ctio

n o

f Str

ea

m M

iles

1 2 3 4 5

0.0

0.2

0.4

0.6

0.8

1.0

stream order = 2

2

3

4

Associated Stressors 5

MBSS-derived thresholds of impairment:• pH < 5• ANC < 200 μeq/l• Nitrate-nitrogen > 2 mg/l• DO < 5 ppm• Sulfate > 24 mg/l• DOC > 8.0 ppm

Conditional probability thresholds of impairment:

1st order steams: DO < 5, DO > 12 pH < 6, pH > 8

NO3 < 5, <15SO4 < 40-50Temp <5, temp > 25Hilsenoff <1, Hilsenhoff > 6

2nd order steams: DO < 3, DO > 11 pH < 5, pH > 8.5

NO3 < ?SO4 < 75Temp <10, temp > 28Hilsenoff <2,

Thresholds of Impairment 6

7

0 20 40 60 80 100

Percent Fines (< 2mm) in Substrate

0.0

0.2

0.4

0.6

0.8

1.0

Pro

ba

bil

ity o

f B

en

thic

Im

pa

ct

in S

tre

am

s

Percent Fines in Substrate

British Columbia

Conditional value

7

8800 stream miles stream miles in MD66% 1st order - 580817% 2nd order

Impaired Streams in Maryland

7304 miles in 1st and 2nd order streams

3725 miles of 1st and 2nd order streams should be on 303(d) List based on benthic impairment

8

Agriculture on >3% Slopes

Probability of Impairment Models

URBAN

be

nth

ic ib

i

0 20 40 60 80

0.0

0.2

0.4

0.6

0.8

1.0

stream order 1

URBAN

be

nth

ic ib

i

0 20 40 60 80

0.0

0.2

0.4

0.6

0.8

1.0

stream order 2

URBAN

fish

ibi

0 20 40 60 80

0.0

0.2

0.4

0.6

0.8

1.0

stream order 1

URBAN

fish

ibi

0 20 40 60 80

0.0

0.2

0.4

0.6

0.8

1.0

stream order 2

Combine condition information with land cover data to predict probability of impairment

9

Data to Drive Modeling

Spatial Models for Probability of Impairment

10

Probability of Stream Benthic Probability of Stream Benthic Impairment for Exceeding Levels of Impairment for Exceeding Levels of

Catchment UrbanizationCatchment Urbanization

0 20 40 60 80

Urban = Percent of Catchment Area Urbanized

0.0

0.2

0.4

0.6

0.8

1.0

Pro

babi

lity

of B

enth

ic Im

pairm

ent w

hen

Urb

an E

xcee

ded

Maryland Biological Stream Survey 1995-97 2nd order streams

10