DEVELOPMENT OF EFFECTIVENESS MONITORING PROTOCOLS FOR

AQUATIC HABITAT CONDITIONS ON THE TONGASS NATIONAL FOREST:

A TLMP INFORMATION NEED

Richard D. Woodsmith

Mason D. Bryant

Richard T. Edwards

STUDY PLAN 

DEVELOPMENT OF EFFECTIVENESS MONITORING PROTOCOLS FORAQUATIC HABITAT CONDITIONS ON THE TONGASS NATIONAL FOREST:

A TLMP INFORMATION NEED 

R.D. WOODSMITH AND M.D. BRYANTU.S.D.A., Forest Service, Pacific Northwest Research Station,

2770 Sherwood Lane, Suite 2A, Juneau, AK 99801-8545, U.S.A.  

COOPERATORS:PNW RESEARCH: Richard Woodsmith, Mason Bryant

KETCHIKAN AREA: Ted Geier, Ron MedelKETCHIKAN RANGER DISTRICT

SAMPLE REACH LOCATIONS

OBJECTIVE

Develop, test, and refine application and analysis protocols for effectiveness monitoring of aquatic habitat in southeast Alaska

Select variablesSensitive to disturbanceObjective and preciseEfficient

Field proceduresChannel conditionSalmonid densities

Analysis proceduresChannel condition changeSalmonid density response

Ecological responses Future research

APPLICATIONS OF EFFECTIVENESS MONITORING PROTOCOLS

ISSUE: Managers of public lands require an efficient, repeatable, and defensible assessment of aquatic habitat condition for a number of applications:

Effectiveness monitoring -- determine the effectiveness of management standards and guidelines

Restoration needs

Restoration design and evaluation

Habitat risk assessment

SLOPE

P M H

Slo

pe

0.000

0.005

0.010

0.015

0.020

0.025

Pristine ModerateHeavy

BED WIDTH

P M H

Wbe

d

0

5

10

15

20

25

30

35

BANKFULL DEPTH

P M H

d bf

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

MEDIAN BED SURFACE GRAIN SIZE

P M H

D50

0.00

0.02

0.04

0.06

0.08

0.10

LAND USE INTENSITY

We take a cumulative effects approach by sampling floodplain-type, gravel-bed streams,

generally low in the drainage network.

We take advantage of southeastern Alaska’s abundance of pristine channel habitat, as a

standard for comparison.

Variation is large and effectiveness monitoring variables need to be

sensitive, precise, and efficient.

Bauer, S.B. and Ralph, S.C. 1999. EPA-910-R-99-014.

You call this a pool??

POOL DEFINITION

MEAN BED WIDTH (m)

0 5 10 15 20 25 30 35 40

MEA

N R

ESID

UA

L P

OO

L D

EPTH

(m

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

MEAN RESIDUAL DEPTH (m)

(0.02 Wbed) + 0.05 (m)

PREVIOUS POOL MINIMUM (WFPB)

VARIABLE SELECTION

Sensitive, Objective, and Precise:

Pool Spatial Density (Pools*Wbed /L)

Pool Depth (dr / dbf )

Bed Surface Grain Size (D50 /D50p)

Width:Depth Ratio (Wbed/dbf )

Relative Submergence (dbf /D50)

PROTOCOL OUTLINE

Reach location randomly selected in stream of

interest

Elevational surveys with level and rod Longitudinal profile (20 channel widths)Cross sections (every 5 channel widths)

Pool inventory and residual depth measurements

Grain size distribution (at every cross section)

Site characterizationLWD inventoryPhotos and sketch of reachRiparian stand densityDrainage area

Watershed condition (for interpretation)% Drainage area harvestedRoad densityOther land useGeology, soils, climate, etc.

OBSERVER VARIABILITY

Cre

w D

iffer

ence

(%

)

0

10

20

30

40

50

60

70

80

90

100

Wbed

dbfWbed/dbf

Length

Slopedr dr/dbf

PoolsPools*W

bed/L

D50

D50/D

50p

dbf/D50

POOL DENSITY

1996 1997 1998 1999 2000 2001

PO

OLS

* W

bed

/ L

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

PAINTED CREEK 1 PAINTED CREEK 2 PAINTED CREEK 3 PRINCESS CREEK 1 PRINCESS CREEK 2 PRINCESS CREEK 3

WIDTH TO DEPTH RATIO

1996 1997 1998 1999 2000 2001

Wbe

d /

d bf

9

10

11

12

13

14

15

16

17

18

SCALED RESIDUAL DEPTH

1996 1997 1998 1999 2000 2001d r

/ d

bf

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

0.75

0.80

0.85

SCALED BED GRAIN SIZE

1996 1997 1998 1999 2000 2001

D50

/ D

50p

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4RELATIVE SUBMERGENCE

1996 1997 1998 1999 2000 2001

d bf /

D50

20

40

60

80

100

120

140

160

TEMPORAL VARIABILITY

Slop

e

Slop

e_yr

CH

AN

GE (%

)

-60

-40

-20

0

20

40

60

80

100

120

TEMPORAL CHANGE IN VARIABLES

Pls*

W/L

Pls*

W/L_

yr

CH

AN

GE (%

)

-100

-50

0

50

100

150

200

250

300

dr/dbf

dr/dbf

_yr

dbf/D50

dbf/D50

_yr

D50/D50

p

D50/D50

p_y

r

Wbed/dbf

Wbed/dbf

_yr

D50

D50_y

r

POOL DENSITY

P M H

PO

OLS * W

bed

/ L

0.0

0.5

1.0

1.5

2.0

2.5

3.0SCALED RESIDUAL POOL DEPTH

P M H

dr / d

bf

0.0

0.2

0.4

0.6

0.8

1.0

1.2

SCALED GRAIN SIZE

P M H

D50

/ D

50p

0.0

0.5

1.0

1.5

2.0

2.5RELATIVE SUBMERGENCE

P M H

dbf / D

50

0

10

20

30

40

50

60

70

80

90

100

110

PRISTINEMODERATEHEAVY

LAND USE INTENSITY

WIDTH TO DEPTH RATIO

P M H

Wbed

/ dbf

0

5

10

15

20

25

30

MONITORING VARIABLE DISTRIBUTION

Are there distinct channel conditions for different land use intensities?

Variable P vs. M P vs. H M vs. H

log (Wbed / dbf) 1.000 (0.85)

0.001* (0.98)

0.009* (0.85)

log (Pools*Wbed /L) 1.000 (0.57)

0.062* (0.82)

0.081* (0.57)

log (dr /dbf) 1.000 (0.52)

0.013* (0.77)

0.244 (0.52)

log (D50 /D50p) 1.000 (0.42)

0.065* (0.64)

0.613 (0.42)

log (dbf /D50) 1.000 (0.44)

0.435 (0.68)

0.160 (0.44)

Contrast

ANOVA RESULTS

Bonferroni multiple contrasts of channel condition variables among P, M, and H; α = 0.10; power of the test is given in parentheses.

Power as a Function of Sample Size

One-way ANOVA for Log (Pools*W/L)

Po

we

r

Number of Cases Per Cell

f= 0.377; Levels= 3 (H, M, P); Alpha=.10; Tails=2

0.0

0.2

0.4

0.6

0.8

1.0

0 10 20 30 40 50

TIME1996 1997 1998 1999 2000 2001

PO

OLS * W

bed

/ L

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

2.1

PAINT1

PAINT2

PAINT3

PRINC2

PRINC3

PRINC1

PAINT1

PAINT2

PAINT3

PRINC1

PRINC2

PRINC3

TREND ANALYSIS

Surveys / yr 3 3

Princess 1 12 6

Princess 2 29 12

Princess 3 13 6

Painted 1 13 6

Painted 2 15 7

Painted 3 9 4

Number of years required to detect a trend in pool spatial density

18 9

1 1

22 10

>30 20

19 9

13 6

80% Power 60% Power

α = 0.2 α = 0.4

- 2% / yr - 3% / yr

19 8

POWER OF TREND ANALYSIS

DESIGN Collaboration

Land managers Resource specialists Researchers Statisticians

Definition of the specific question -- what are

the objectives / contrasts Effectiveness of current guidelines Cumulative effects Restoration priorities

EXECUTION

Well trained personnel Carefully designed protocols

Pool density Pool depth Width:depth ratio Substrate grain size distribution Relative submergence Other variables as appropriate

CONCLUDING REMARKS

EFFECTIVENESS MONITORING

ANALYSIS Contrast regional land use categories Analyze trends Feedback to execution (power analyses)

INTERPRETATION

1. Watershed and landscape conditions Watershed size Geology and soils Climate and vegetation

2. Geomorphic processes Flood frequency regime Mass movement

3. Disturbance history (background and land use) Glaciation Climatic extremes Intense storms Road building Timber harvesting

CONCLUSIONS Relative magnitude of effects of broad

categories of land use

ADAPTIVE MANAGEMENT

CONCLUDING REMARKS

OBJECTIVE Determine the relationship

between salmonid densities (number of fish/m2) and channel condition

ANALYSIS OF SALMONID POPULATIONS

METHODS

20 of 66 reaches sampled

Randomly selected habitat units used as "fish sampling units" (FSU)

FSU's saturated with traps for complete sampling

Population estimates through "removal method" (White et al., 1982; Bryant, 2000)

ANALYSIS

Salmonid densities as a function of channel condition were examined through a series of independent linear regressions for each species and variable

RESULTS

Salmonid Relationships are complex and variable

Habitat useFull vs. partial recruitmentDolly Varden, steelhead, and

cutthroat trout found at low densities

Availability of refuge habitat (only main stems were sampled)

Limiting factors may differ seasonallySummer droughtFall floodsWinter temperatures

External factorsFishing pressurePredationOcean productivity

Salmonid Population Trends (Painted Creek)

0

0.2

0.4

0.6

0.81

1.2

1.4

1.6

1.8

1997 1998 1999 2000

Year

Mean

Den

sity (

fish/

m**2

)

DV

COF

COP

CT

SH

Coho fry Coho parr Dolly Varden Steelhead Cutthroat

D50 0.192 0.585 (-) 0.063 0.410 0.260

Wbed 0.215 0.930 0.744 0.331 0.572

dbf 0.083 0.183 0.351 0.513 0.759

Wbed / dbf 0.562 0.445 0.571 0.567 0.518

Axs (= Wbed * dbf) 0.095 0.532 0.462 0.262 0.968

Number of pools 0.012** 0.729 0.091 0.605 0.706

dr 0.531 0.967 0.575 0.359 0.587

Pools * Wbed/L 0.011** 0.836 0.157 0.782 0.967

dr / dbf 0.125 0.172 0.581 0.820 0.698

D50 / D50p 0.136 0.154 (-) 0.057 0.434 0.158

SALMONID DENSITY AS A FUNCTION OF CHANNEL CONDITION

Coho Salmon Fry

00.5

11.5

22.5

33.5

4

0 10 20 30 40 50 60

Number of Pools

Den

sity

of F

ish

LWD (m-1) Coho Fry Coho parr Dolly Varden Steelhead Cutthroat

Trees 0.763 0.002** 0.631 0.905 0.197Rootwads 0.721 0.208 0.087 0.180 0.701Root wads with boles 0.564 0.208 0.455 0.824 0.875Key logs 0.212 0.158 0.945 0.437 0.354Key root wads 0.881 0.857 0.119 0.184 0.449

Probability > F: α=0.05

SALMONID DENSITY AS A FUNCTION OF LARGE WOODY DEBRIS

Coho Salmon Parr

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 0.2 0.4 0.6 0.8 1 1.2

Pieces of Large wood per meter

Den

sity

of F

ish

COHO AS AN INDICATOR SPECIES

Fry and parr utilize small streams broadly distributed throughout the channel network

Associated with specific seasonal habitats

Important part of life cycle spent in freshwater

FUTURE RESEARCH OPPORTUNITIES

Ecosystem approach

Understanding stream structures and processes that function to effectively support fish and other biota

Availability of food resources

Reach nutrient stocksoNutrient cycling and retention

Allochthonous inputs

Primary productionoPhysical and chemical controls

Secondary productionoControlling variablesoMagnitude and distribution

Ecosystem metabolism

FUTURE RESEARCH OPPORTUNITIES

Wetland-stream interactionsCarbon and nutrient inputsEffects on stream processes

What are the effects of channel structure on ecological processes controlling

Food abundanceFood qualityProductivityBiological diversity

     

Role of surface/subsurface interactionsProductivityStabilityDiversity

ControlsSlopeSubstrate textureChannel planform and topographyLWD, boulders, obstructionsSediment supply

FUTURE RESEARCH OPPORTUNITIES

RECOVERY FROM DISTURBANCE

How do background disturbances and management decisions influence these key processes?

FUTURE RESEARCH OPPORTUNITIES