Farah Abi-Akar (MDE) - Maryland Department of Natural Resources ...

Biological Stressor 

Identification Process: 

Addressing Maryland’s Nontidal 

Biological Impairments 

Maryland Department of the Environment 

TMDL Development Program 

Prepared for the Maryland Water Monitoring Council Annual Conference 

6 December 2012 

Farah Abi-Akar, Lee Currey

Overview 

• Background 

• Methods 

• Results

Background

Background 

• Clean Water Act’s Total 

Maximum Daily Loads 

(TMDLs) 

Allowable in-stream limits 

Point & non-point sources 

Are developed when a Water 

Quality Standard is not met, 

and when tech. standards 

aren’t enough

Background 

• MD Water Quality Standards (WQS) 

For a body of water, the combination of: 

• A designated use, and 

• The water quality criteria designed to protect that 

use. 

Designated uses include swimming, drinking, 

shellfish harvest, protection of aquatic life 

• DNR’s Benthic Index of Biological Integrity (BIBI) 

and Fish Index of Biological Integrity (FIBI)

Background 

• WQS not met 

Watershed gets listed on MD’s 303(d) list of 

impaired waters (Integrated Report). 

Assessment Unit Designated Use Cause Indicator 

Liberty Reservoir 

Aquatic Life and 

Wildlife 

Sedimentation/siltation 

Unknown 

Liberty Reservoir 


Wildlife 

Phosphorus (Total) 

Dissolved Oxygen 

Antietam Creek 


Wildlife 

Cause Unknown 

Fish and Benthic IBIs

Background 

• WQS not met 

Watershed gets listed on MD’s 303(d) list of 

impaired waters (Integrated Report). 

Need a TMDL to fix it. 

• Listed for sediment TMDL to reduce sediment. 

• Listed for nitrogen TMDL to reduce nitrogen. 

• Listed for biology TMDL to reduce… what 

–What TMDL(s) should we develop to improve 

biology What is making fish & benthics

What is responsible 

for reducing fish & 

benthics’ biological 

integrity 

We need to find the guilty 

stressors in each watershed. 

Round up the suspects and 

begin investigation! 

Biological 

Stressor 

IDentification

How the BSID works

Domain 

• Freshwater (non-tidal) 

• Stream orders 1-4 

• 8-digit watershed scale

Data 

• DNR’s Maryland Biological Stream Survey 

Rounds 2 and 3 (2000-2009) 

Conditions & biology paired 

Most comprehensive 

Consistent sampling & analysis methods 

• Land use: Chesapeake Bay Program 

Spatially consistent (vs: RESAC + NCLD) 

More detail in urban areas 

Consistent with TMDL Program 

• & RESAC Impervious, & State Roads

Data 

• Acknowledgements 

MDE BSID Section 

MD DNR MBSS 

Chesapeake Bay Program 

EPA ORD 

University of Maryland 

Versar 

Programs: SAS and R

Goal: Compare Bio to Stressors 

• How Using case-control statistics 

Commonly used in epidemiology: 

Mantel-Haenszel Odds or Risk Ratios 

Categorizes all samples into groups, then 

compares numbers in each group. 

Groups characterized by: 

• Biology: or 

• Stressor: Above or Below 

• Region and order


1. Bio 

Cases vs. Controls 

FIBI < 3 

FIBI ≥ 3 

BIBI < 3 

BIBI ≥ 3 

# in 8-digit watershed # in physiographic region


Controls grouped by: 

1. Bio 

1 st 2 nd + 

Eastern Piedmont 

Highland 

1 st 2 nd + 

1 st 2 nd + 

Coastal


2. Stressors 

Potential culprits: 

•Habitat 

•Sediment 

•Water Chemistry 

•Acid sources 

•Land use – Agriculture 

•Land use – Anthropogenic 

•Land use – Urban


2. Stressors 

Every 8-digit watershed gets investigated for 

every one of these stressors.


2. Stressors 

Stressor above limit vs. Stressor below limit


Stressor Thresholds 

2. Stressors 

• A.K.A. Defining the line between and 

for each stressor 

• Some are already defined in COMAR, by 

DNR, or in literature, e.g.: 

Low lab pH:



2. Stressors 

• What about stressors without defined 

thresholds 

High conductivity 

Low shading 

Low % forest in 60-meter buffer 

• Made our own. 

Includes R1 & non-random 

Nice big sample sizes (72-304)



2. Stressors 

• Compared stressor levels, 

within BIBI & FIBI groups, 

within regions. 

• 80% confidence intervals 

• Strengthen analysis with 

bootstrapping (10,000x)

High Conductivity, 

Highland 

1. Do these overlap 

No they are 

statistically different. 

Threshold set at 

mean of Fair.


Yes they are not 


Low % Forest, 

Coastal 


No they are 


Threshold set at the 

mean of Poor & Fair.

… for all potential stressors, for all regions.

Goal: Compare Bio to Stressors


Two-way contingency table: every stressor, every watershed


• Hypothesis: Sub-par biology will be 

correlated to sub-par water quality. 

Or,


Odds Ratio = ad 

bc 

= 

• One odds ratio per watershed, per stressor 

• If the OR > 1, the result is significant. The 

stressor is likely to be impacting biology. 

• Mantel-Haenszel exact test, 90% CI p value

Thanks to odds ratios, 

probable stressors 

have been ID’d in each 

watershed. 

Now, how much risk do 

we attribute to each

Attributable Risk 

• The portion of samples with poor to very poor 

biological conditions as a result of the stressor 

The % of cases that are the stressor’s “fault” 

AR 

Proportion 

cases 

- 

Proportion 

controls 

AR 

 

 

 

 

a 

a 

 

c 

 

 

 

 

 

 

 

b 

b 

 

d

Attributable Risk 

• ARs are also combined by category: 

Stressors 

• Sediment 

• Habitat 

• Water Chemistry 

Sources 

• Acid sources 

• Land use – Agriculture 

• Land use – Anthropogenic 

• Land use – Urban

Results

Stressor 

above 

Cases 

6 

Controls 

9 

Example: 

Seneca Creek, 

Impervious Surface 

Stressor 

below 

4 

163

Example: Seneca Creek, 

Impervious Surface 

Cases 

Controls 

Stressor 

above 

Stressor 

below 

6 

4 

9 

163 

Odds Ratio ≈ 

ad 

bc ≈ 6*163 

9*4 

≈ 27 

6 9 

Attributable Risk ≈ % cases - % controls ≈ - ≈ 55% 

10 172 

Therefore: 

• Yes, impervious surface is a possible bio stressor in 

Seneca Creek. 

• Estimated risk attributable to impervious surface: 55%

Group Stressor AR 

Sources - Agr High % of agriculture in watershed 29% 29% 96% 

Sources - Low % of forest in watershed 45% 47% 

Anthropogenic Low % of forest in 60m buffer 18% 

Sources - Urban High % of impervious surface in 60m buffer 49% 59% 

High % of impervious surface in watershed 55% 

High % of high-intensity developed in watershed 38% 

High % of low-intensity developed in watershed 57% 

High % of medium-intensity developed in watershed 58% 

High % of early-stage residential in watershed 44% 

High % of residential developed in watershed 57% 

High % of roads in watershed 52% 

High % of high-intensity developed in 60m buffer 19% 

High % of low-intensity developed in 60m buffer 55% 

High % of medium-intensity developed in 60m buffer 49% 

High % of early-stage residential in 60m buffer 25% 

High % of residential developed in 60m buffer 58% 

High % of roads in 60m buffer 10% 

Sediment Epifaunal substrate poor 18% 18% 96% 

Instream Habitat Concrete/gabion present 18% 48% 

Instream habitat structure poor 10% 

Riffle/run quality marginal to poor 28% 

Water Chemistry High chlorides 34% 76% 

High conductivity 62% 

High orthophosphate 22% 

High lab pH 18% 

High total nitrogen 54%

Seneca Output: What wasn’t there 

• Atmospheric deposition present 

• Agricultural acid source present 

• AMD acid source present 

• Organic acid source present 

• High % of agriculture in 60m buffer 

• Low % of wetland in watershed 

• Low % of wetland in 60m buffer 

• High % of rural developed in watershed 

• High % of rural developed in 60m buffer 

• Extensive bar formation present 

• Moderate bar formation present 

• Bar formation present 

• Channel alteration moderate to poor 

• Channel alteration poor 

• High embeddedness 

• Epifaunal substrate marginal to poor 

• Moderate to severe erosion present 

• Severe erosion present 

• Silt clay present 

• Beaver pond present 

• Channelization present 

• Instream habitat structure marginal to 

poor 

• Pool/glide/eddy quality marginal to poor 

• Pool/glide/eddy quality poor 

• Riffle/run quality poor 

• Velocity/depth diversity marginal to poor 

• Velocity/depth diversity poor 

• No riparian buffer 

• Low shading 

• Acid neutralizing capacity below chronic 

level 

• Acid neutralizing capacity below episodic 

level 

• Dissolved oxygen < 5mg/l 

• Dissolved oxygen < 6mg/l 

• Low dissolved oxygen saturation 

• Low field pH 

• High field pH 

• Low lab pH 

• High sulfates 

• Ammonia acute with salmonid present 

• Ammonia acute with salmonid absent 

• Ammonia chronic with salmonid present 

• Ammonia chronic with salmonid absent 

• High total phosphorus

# Watersheds Impacted per Stressor 

impsurf 1 

COND_LAB1 

bimpsurf 1 

CL1 

WB_MURB1 

X60M_MURB1 

WB_ROAD1 

SO4_LAB1 

X60M_ROAD1 

X60M_LURB1 

X60M_FRST1 

WB_REHML1 

WB_LURB1 

EPI_SUB2 

X60M_REHML1 

X60M_HURB1 

CHANNELbin1 

X60M_AGRI1 

WB_HURB1 

WB_FRST1 

INSTRHAB2 

INSTRHAB1 

TP1 

EPI_SUB1 

VEL_DPTH2 

X60M_REEARL1 

RIFFQUAL1 

WB_REEARL1 

LDOSAT_FLD1 

DO_FLD2 

RIFFQUAL2 

POOLQUAL2 

O_PHOS1 

DO_FLD1 

X60M_RUHML1 

WB_RUHML1 

TN1 

RIP_WID1 

EMBEDDED1 

WB_AGRI1 

PH_LAB1 

CONCRETEbin1 

CHAN_ALT2 

WB_WETL1 

AR_FORM_MEbin1 

POOLQUAL1 

CHAN_ALT1 

ANC_LAB1 

PH_FLD1 

ERODSV_Sbin1 

ERODSV_Mbin1 

BAR_FORM_Ebin1 

VEL_DPTH1 

SHADING1 

X60M_WETL1 

PH_LAB2 

ACIDAGRbin1 

ANC_LAB2 

ACIDADbin1 

BEAVPNDbin1 

ACIDAMDbin1 

TANc2bin1 

TANc1bin1 

PH_FLD2 

BAR_FORMbin1 

ACIDORGbin1 

TANa2bin1 

TANa1bin1 

SILTCLAYbin1 

0 

0 

0 

1 

1 

1 

1 

1 

8 

666 

4 55 4 

13 

13 

13 

10 11 

11 

11 12 

12 

9 10 

10 

10 

17 

16 17 

17 

17 

16 

15 16 

16 

16 

43 44 

35 36 37 43 

35 

35 

34 

31 32 

32 

32 33 

33 

30 

30 

29 

29 

27 

27 

26 

25 

20 21 

21 22 24 

19 

19 

0 10 20 30 40 

Statewide 

Top 5 stressors/sources 

1. Impervious surface 

2. Conductivity 

3. Chloride 

4. Medium-intensity 

development 

5. Roads 

5. SO 4 

Bottom 5 stressors/sources 

1. Silt/clay presence 

2. Ammonia 

3. Organic acid source 

4. Bar formation 

5. pH > 8.5 

Watersheds

BSID Output 

• Analysis of stressors and interrelationships

BSID Output 

• Watershed-specific 

reports

Summary 

• Challenges 

Sample sizes limited 

Uncertainty inherent in thresholds 

Accounting for “all” stressors 

One stressor at a time 

• But… 

Provides a systematic, quantitative means of 

addressing non-tidal biological impairments. 

Analysis strengthened in several ways (sample size, 

bootstrapping, land use consistency…)

What’s next 

• Analysis of results & 

interrelationships 

• Updating of existing reports & 

writing new ones 

• Development of appropriate 

water quality criteria and/or 

TMDLs to address results

Maryland Department of the Environment 

TMDL Development Program 

Biological Stressor Identification Section 

Allison O’Hanlon 

AOHanlon@mde.state.md.us 

Shirley Kirby 

Skirby@mde.state.md.us 

Farah Abi-Akar 

FAbi-Akar@mde.state.md.us 

BSID Website 

http://www.mde.state.md.us/programs/Water/TMDL/ 

Pages/Programs/WaterPrograms/tmdl/bsid_studies.aspx 

1800 Washington Boulevard | Baltimore, MD 21230-1718 

410-537-3000 | TTY Users: 1-800-735-2258 

www.mde.state.md.us

Farah Abi-Akar (MDE) - Maryland Department of Natural Resources ...

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