ripstream: quantifying stream temperature response to oregon timber harvest practices jeremy groom...

RipStream: Quantifying stream temperature response to Oregon timber harvest practices

Jeremy Groom1, Liz Dent2, Lisa Madsen3

1OSU Dept. of Forest Engineering Resources & Management2Oregon Dept. of Forestry, 3OSU Dept. of Statistics

In a time before streams…

Oregon Department of Forestry Monitoring

LandslidesPesticidesLeave-treeHAPShadeStream Temperatures

Private Forests Division

Clean Water Act & OR Forestry

Clean Water Act

EPA

DEQ (Water Quality Rules)

Monitoring

Forest Practices ActBoard of Forestry

RipStream – Riparian Function and Stream Temperature

State and Private Forests joint effort

• Objective: Evaluate effectiveness of forest practices rules & strategies at protecting stream temperature, promoting riparian structure

• 33 Sites (18 Private, 15 State, Medium and Small F)

• Dent et al. 2008 JAWRA 44(4):803-813

Rules and Strategies

Private: Forest Practices ActState: Northwest Oregon State Forest

Management Plan

State ForestsPrivate Forests

170 ft25 ft20 ft50 ft70 ft

Limited Entry No Cut

No Cut

Limited Entry

Small & Medium FSmall F

Medium F

RipStream Study Design

Design: 2 years pre-harvest, 5 years post harvest

1W

4W

Control Treatment

Downstream

2W

POINT OF MAXIMUM IMPACT

3W

RipStream – Data and Questions

What questions do we address first?– Regulatory: do our streams meet DEQ

temperature standards post-harvest?– Function: what site characteristics are related to

temperature change post-harvest?

Years of data collection- Stream temperature- Shade- Channel morphology

(gradient, widths, etc.) - Riparian vegetation

(trees, shrubs)

DEQ Water Temperature Standard

Biologically-Based Numeric Criteria – were stream temperatures raised above 16 C or 18 C?

• Not really• Analysis: Relatively straightforward

Protecting Cold Water (PCW) – were streams warmed by > 0.3 C?

• Yes, on private (not State) streams• Analysis: Complex

• 7DayMax

• “Temperature” = 7-day moving average of maximum daily temperatures

Day: 1 2 3 4 5 6 7 8 9 10 11Temp: 11 12 10 11 9 8 9 9 10 10 9

9.7 9.4 10.07DayMax:

Numeric Criteria

Is analysis guidance available? YES

Numeric Criteria exceedance = Any single summer 7DayMax temperature value exceeds 16 C or 18 C

Natural: Control probes 1W & 2WPotential harvest effect: Treatment probe 3W

Numeric Criteria – What’s the big deal?

• Widespread WQ rule type

• EPA guidance (2003) for PNW states

• Lots of effort & research

• Opportunity for evaluation

Numeric Criteria Results: 16 C• Total Number of Sites: 33

– 18 sites exceeded 16 C

• Of those 18 sites:– 3 sites = pre-harvest only

– 10 sites = control (1W, 2W) and treatment (3W) probes during the same year or years

– 3 sites = control probes during pre-harvest years; treatment probes during post-harvest year(s)

– 2 sites = treatment probe post-harvest only

No strong indication that standards exceeded

Protecting Cold Water (>0.3 C)

• Is analysis guidance available? NO.

Lacking in other states

Collaboration with DEQ

Analysis question: For a specific day, has

stream temperature increased by > 0.3 C?

PCW analysis

Looking for change in relationship (e.g., Treatment Reach = 2W and 3W)

Comparing pairs of years (e.g., 2002 & 2004) within a reach (e.g., Upstream Control)

Years are either pre-harvest or post-harvest (can compare pre-pre, pre-post, post-post)

PCW – Analysis Path

1) Which reach year-pair comparison “exceeded” PCW?

2) Created & compared explanatory models of exceedance patterns

– Examined combinations of regulatory distinctions (medium & small streams, State and Private lands)

– Also examined comparison timings (e.g., pre-harvest to post-harvest)

• 3 reaches X 3 time periods = 9 groups

Study Design and the PCW

Pre-pre Pre-post Post-post

UpstreamControl

Treatment

Downstream

1W

4W

2W3W

FLOW

614 comparisons total 65 exceedances

Models

Main Models

1) Null (all categories equal)

2) Reaches differ

3) Timing differs

4) Everything differs

5) Pre-post treatment differs

6) Pre-post Private treatment differs

UpstreamControl

Treatment

Downstream

Pre-pre Pre-post Post-post

Best State Forest Model ?

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Private Pre-PostTreatment

All Other Categories

Pro

bab

ility

of

Exc

eed

ance

Best models

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Private Pre-Post Treatment All Other Categories

Pro

bab

ility

of

Exc

eed

ance Small Streams

Medium Streams

TOP MODEL

40.2%

4.6%

Conclusions (Regulatory)• Numeric Criteria – OK(?)

• PCW – increase in exceedance frequency on Private streams in general

• PCW – State OK

Functional Analysis

Study scope:Preharvest and two years postharvest

33 sites

Questions:

What factors influence changes in Treatment Reach temperature?

Magnitude of temperature change?

What are we quantifying?

• Changes in temperature (downstream – upstream)

• Averaged daily values (July 15 – Aug 23)

– Maximum– Minimum– Average– Flux

1W2W 3W

FLOW

2W-1W = Change in Control Reach

3W-2W = Change in Treatment Reach

What factors control Treatment Reach temperature change?

Gradient

Elevation

Reach length

Control reach temperature change

Azimuth

Watershed area

1W2W 3W

FLOW

Shade

Approach1) Determine appropriate statistical analysis

Linear mixed-effects regression

2) Develop competing explanations (models) of how temperature change controlled18 models, ranked AIC

3) Determine which explanation performed best

4) Examine model results

Best model: Change in maximum temperatures explained by:

-Temperature change in control reach-Treatment reach length-Gradient-Shade

Random: ~ Intercept + Control Temperature|Site

Model values statistically significantModels without shade performed poorly

Maximum Temperatures

0.5 0.6 0.7 0.8 0.9

-10

12

3Shade (95% CI)

Shade Values (%)

Est

imat

ed T

empe

ratu

re C

hang

e (C

)

500 1000 1500

-10

12

3Treatment Reach Length (95% CI)

Treatment Reach Length (m)

Est

imat

ed T

empe

ratu

re C

hang

e (C

)

2 4 6 8 10 12 14

-10

12

3Gradient (95% CI)

Average first quartile of gradient (deg)

Est

imat

ed T

empe

ratu

re C

hang

e (C

)

Other Temperature Metrics

Minimum Temperature: Same top model, same behavior of variables (not as strong)

Average Temperatures: ditto

Flux: Increased daily fluctuations with less shade

Implication: Reductions in shade occurred, linked to increase in daily temperature maximum, minimum, average, and flux

Shade Pre & Post Harvest50

6070

8090

100

Ave

rage

Sha

de P

re-H

arve

st (

%)

PrivateState

5060

7080

9010

0

Ave

rage

Sha

de P

ost-

Har

vest

(%

)

PrivateState

Preharvest and Postharvest

De

gre

es

C

-3-2-1012

-1.0 -0.5 0.0 0.5 1.0

7453 5207

-1.0 -0.5 0.0 0.5 1.0

5103 5558

-1.0 -0.5 0.0 0.5 1.0

5201

5101 5557 5102 5204

-3-2-1012

5202-3-2-1012

7454 5355 5354 5503 5506

7803 5106 5560 7353

-3-2-1012

5104-3-2-1012

5301 5302 5206 5561 5556

5205 5203 7452 5253

-3-2-1012

7854-3-2-1012

7801

-1.0 -0.5 0.0 0.5 1.0

5502 5559

Partial Residual Plot for 33 Sites

Results summary

1) Shade changed and related to temperature change

2) Other parameters seem reasonable

3) Shade is important & needs further exploration-BA, height, blowdown

Next steps• Complete & publish current analysis

• Next analysis: 5 yrs post harvest– Did temperature patterns remain?– Did shade recover?– More detailed examination of

vegetation and shade

Liz Dent (ODF) & Joshua Seeds (DEQ) Private landowners PF monitoring staff (Marganne Allen, Jerry

Clinton, Kevin Nelson, Kyle Abraham, Seasonal Work Force, Stewardship Foresters)

State Forests Program Staff (Jeff Brandt, District Foresters, Field Foresters)

Review Committee Members EPA 319 program

Acknowledgements