Annual Reporting Meeting – Day 1 (January 18, 2011)

List of Presentations

No. Title of Presentation Author / Presenter

Day 1 – January 18, 2011

1 Update on Water Quality and 2010 Sand Input Paul Grams, David Topping

2 Goal 8: Long Term Monitoring for Changes in Sediment Storage

“Sed Trend”

Paul Grams, Matt Kaplinski, and  

Joe Hazel

3 FY10: Sandbar and Campsite Monitoring in Colorado River in

Marble and Grand Canyons

Joe Hazel, Matt Kaplinski, Rod

Parnell, and Nathan Schott

4 Sediment from the Colorado River —1965 to 2009 Nina Kilham, John Schmit, ...

5 Update to TWG on Campsite Monitoring and other Recreation

Projects (Goal 9)

Helen Fairley

6 Ground Cover  and Stability of Aeolian Landscapes Amy Draut

7 Rainbow Trout Early Life Stage Survival FY 2010 TWG Report Josh Korman

8 Linking whole‐river carbon cycling to quantitative food webs in

the Colorado River

Kevin Donner, Holly Welland,

Sarah Zahn, Kate Behm, . . .  

9 Modeling Population Dynamics of Rainbow Trout in Lees Ferry

and Marble Canyon

Josh Korman, Carl Walters, Andy

Makinster, Lew Coggins, . . .

10 The natural history of Western Honey Mesquite in Grand

Canyon, A Changing Ecology

Gwendolyn Waring, Barbara

Ralston, Larry Stevens, and

Steven Archer

11 Terrestrial Riparian Vegetation Monitoring on the Colorado

River Corridor: Glen Canyon Dam to Lake Mead

David J. Cooper and Jennifer R.

Jones

12 Grand Canyon National Park Vegetation Mapping Project Mike Kearsley, Mark Nebel,  

and Kass Green

13 CRMP Mitigation Program Summary
1/19/2011

1

Update on Water Quality and 

2010 Sand Input

U.S. Department of the Interior

U.S. Geological Survey

GCDAMP Annual Reporting Meeting

January 18, 2011

Paul Grams and David Topping

2010 Water Temperature at Lees Ferry 

and Diamond Creek (RM 225)

elsius

15

16

17

18

19

20

LEES FERRY

1992-2010 LEES FERRY

RIVER MILE 225

1996-2010 RIVER MILE 225

COLORADO RIVER TEMPERATURE AT LEES FERRY AND RM 225

Degrees Ce

7

8

9

10

11

12

13

14

10/1/2009 1/1/2010 4/1/2010 7/1/2010 10/1/2010 1/1/2011

2010 was an average year

2010 Specific Conductance at Lees Ferry 

and Diamond Creek (RM 225)

900

1,000

1,100

LEES FERRY

1992-2010 LEES FERRY

RIVER MILE 225

2003-2010 RIVER MILE 225

NTIMETER AT 25o C 600

700

800

10/1/2009 1/1/2010 4/1/2010 7/1/2010 10/1/2010 1/1/2011 MICROSIEMENS PER CEN

Turbidity at RM 30 and RM 87

RIVER MILE 30

RIVER MILE 87

1,000

10,000

100,000 TRIC UNITS (FNU)

10/1/2009 1/1/2010 4/1/2010 7/1/2010 10/1/2010 1/1/2011

1

10

100

,

FORMAZIN NEPHELOME

Flux monitoring for managing sediment 

and sandbars

 Flux monitoring:

 Tracks tributary sediment inputs and mainstem 

transport at five locations to track status of the 

sediment “bank account.”

 Provides the information needed to time high 

fl f b ildi db t f ll i d f flows for building sandbars to follow periods of

sand accumulation.

Mainstem flow

Mainstem flow and sediment

Tributary flow and sediment

Sediment budget reach

RM 0-30 – upper Marble Canyon

RM 30-61 – lower Marble Canyon

RM 61-87 – eastern Grand Canyon

RM 87-166 – central Grand Canyon

RM 166-225 – western Grand Canyon

USGS Sediment Flux Monitoring Program in 

Grand Canyon 

David Topping

Ronald Griffiths

Thomas Sabol

Nicholas Voichick

Karen Vanaman

Draft data subject to revision. DAY 1 OF 2. 

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1/19/2011

2

Sand budget from end of 2008 HFE to 

August 17, 2010 

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0

10,000

20,000

30,000

40,000

50,000

POST-2008 HFE MASS-BALANCE SAND BUDGET BETWEEN RIVER-MILES 0 AND 30

WATER DISCHARGE

MASS-BALANCE UNCERTAINTY ENVELOPE

CH RELATIVE TO AFTER

2008 HFE (million metric tons)

DISCHARGE AT

RIVER-MILE 30 (ft3/s)

1-7-11 (before increase in operations)

-2.0

-1.5

-1.0

-0.5

0.0

0.5

2008 2009 2010

SAND MASS IN REAC

RECESSION OF MARCH 

Sand budget positive for period

owing to recent Paria River floods.

Planned higher dam operations will export

most of this sand from this reach by the spring.

CALENDAR YEAR

Preliminary results – subject to review and revision

Sand budget from end of 2008 HFE to 

August 17, 2010 

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0

10,000

20,000

30,000

40,000

50,000

POST-2008 HFE MASS-BALANCE SAND BUDGET BETWEEN RIVER-MILES 30 AND 61

WATER DISCHARGE

MASS-BALANCE UNCERTAINTY ENVELOPE

CH RELATIVE TO AFTER

2008 HFE (million metric tons)

DISCHARGE AT

RIVER-MILE 61 (ft3/s)

1-7-11 (before increase in operations)

-2.0

-1.5

-1.0

-0.5

0.0

0.5

2008 2009 2010

SAND MASS IN REAC

RECESSION OF MARCH 

Sand budget likely slightly negative for period. 

Rise in sand budget near end of period

owes to export of Paria-supplied 

sand from upper Marble Canyon. 

CALENDAR YEAR

Preliminary results – subject to review and revision

Sand budget from end of 2008 HFE to 

August 17, 2010 

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0

10,000

20,000

30,000

40,000

50,000

POST-2008 HFE MASS-BALANCE SAND BUDGET 

BETWEEN RIVER-MILES 61 AND 87

WATER DISCHARGE

MASS-BALANCE UNCERTAINTY ENVELOPE

CH RELATIVE TO AFTER

2008 HFE (million metric tons)

DISCHARGE AT

RIVER-MILE 87 (ft3/s)

1-7-11

(before increase in operations)

-2.0

-1.5

-1.0

-0.5

0.0

0.5

2008 2009 2010

SAND MASS IN REAC

RECESSION OF MARCH 2

Sand budget likely slightly negative for period. 

Minimal sand from summer 2010 LCR floods 

retained in reach owing to higher dam releases.

CALENDAR YEAR

Preliminary results – subject to review and revision

Sand budget from end of 2008 HFE to 

August 17, 2010 

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0

10,000

20,000

30,000

40,000

50,000

POST-2008 HFE MASS-BALANCE SAND BUDGET BETWEEN RIVER-MILES 87 AND 225

WATER DISCHARGE

MASS-BALANCE UNCERTAINTY ENVELOPE

CH RELATIVE TO AFTER

2008 HFE (million metric tons)

DISCHARGE AT

RIVER-MILE 225 (ft3/s)

1-7-11 (before increase in operations)

-2.0

-1.5

-1.0

-0.5

0.0

0.5

2008 2009 2010

SAND MASS IN REAC

RECESSION OF MARCH 

Sand budget likely slightly positive for period

owing to retention of some of the sand supplied

during summer 2010 LCR floods.

CALENDAR YEAR

Preliminary results – subject to review and revision

Sand update: January 7, 2011

 RM 0 to RM 30, 

 Budget is currently positive (Jan. 7, 2011) between 1.0 and 1.8 million metric tons.

 Does not include recent change in operations

 RM 30 to RM 61

 Budget is currently slightly negative, between 0 and -0.2 million metric tons.

 Slight rise at end of period is transfer of fall 2010 inputs from upper to lower 

Marble Canyon.

 RM 61 to 87

 Budget is currently slightly negative, between 0 and -0.7 million metric tons.

 Not much retention of summer 2010 Little Colorado River inputs.

 RM 87 to 225

 Budget is currently positive (Jan. 7, 2011) between 0 and 0.7 million metric tons.

 Retention of some of the summer 2010 Little Colorado River floods.

Preliminary results – subject to review and revision

Summary

 Water temperature at Lees Ferry and Diamond Creek 

is about average.

 Specific conductance (salinity) is low.

 Turbidity in Marble Canyon has been relatively high.

 There were above average sand inputs in July 

through October 2010.

 Winter fluctuating flows (currently 13,000 to 20,000 cf ) ill t d fs) will export sand.

Preliminary results – subject to review and revision

Draft data subject to revision. DAY 1 OF 2. 

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3

Other Goal 7 FY 2010 

Accomplishments/Products

 Monitoring

 Flow, temperature, water quality and sediment data collected 

processed and reported

 9 published papers, including HFE reports (USGS reports, 

journal articles, and proceedings papers)

 Through a cost-sharing and savings agreement with Arizona 

Water Science Center, implemented flow and sediment 

monitoring on Kanab and Havasu Creeks monitoring on Kanab and Havasu Creeks

 Modeling

 4 published papers (USGS reports, journal articles, and 

proceedings papers)

 Use of sand routing model in 2011 hydrograph development

 Knowledge transfer of sand routing model to Reclamation 

for use in HFE Environmental Assessment

 Continued efforts towards development of working 3D eddy 

model

Goal 7 FY 2011

 Monitoring

 Continued operation of monitoring stations, reporting of 

data, and publication of methods and results

 Work with database and web staff to improve accessibility to 

data

 Modeling

 Use of sand routing model (DEPENDING ON INTEREST AND 

NEED)

 Sandbar stability experiments still underway at ASU (now 

with very little GCDAMP support)

 3D eddy model development still underway at USGS in 

Golden, CO (for now, with USGS base funding and very little 

GCDAMP support)

Draft data subject to revision. DAY 1 OF 2. 

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Goal 8: Long Term Monitoring for 

Changes in Sediment Storage

“SedTrend”

U.S. Department of the Interior

U.S. Geological Survey

GCDAMP Annual Reporting Meeting

January 18, 2011

Phoenix AZ

Paul Grams, Matt Kaplinski, and Joe Hazel

Purposes of SedTrend Channel Mapping Project

 Provides long-term monitoring for changes 

in sand storage to evaluate effects of dam 

operations over periods of several years.

 Provides channel topography for modeling.

 Provides data to evaluate the degree to 

which sandbar monitoring sites are 

representative of system-wide changes in 

sandbars

 Provides channel topography for 

characterization and evaluation of aquatic 

habitat.

2

Strategic Science Questions that 

motivate Goal 8 Monitoring

 AMWG Priority 3: What is the best flow regime? 

(GCDAMP goals 1–11)

– Is there a “Flow-Only” operation (i.e., a strategy for dam 

releases, including managing tributary inputs with 

BHBFs, without sediment augmentation) that will restore 

and i i db h bi d d l i l ? d maintain sandbar habitats over decadal timescales?

Strategic Science Questions that 

motivate Goal 8 Monitoring

 AMWG Priority 3: What is the best flow regime? 

(GCDAMP goals 1–11)

– Is there a “Flow-Only” operation (i.e., a strategy for dam 

releases, including managing tributary inputs with 

BHBFs, without sediment augmentation) that will restore 

and i i db h bi d d l i l ? d maintain sandbar habitats over decadal timescales?

• High flows rebuild sandbars. 

• We’ve also learned that the cost can be net erosion from the 

channel and lower parts of sandbars.

• Sandbars erode again following high flows  Need to repeat high 

flows to maintain bars.

• Thus, the part of the question about “maintaining sandbars over 

decadal timescales?” remains unanswered.

What have we learned?

Strategic Science Questions that 

motivate Goal 8 Monitoring

 AMWG Priority 3: What is the best flow regime? 

(GCDAMP goals 1–11)

– Is there a “Flow-Only” operation (i.e., a strategy for dam 

releases, including managing tributary inputs with 

BHBFs, without sediment augmentation) that will restore 

and i i db h bi d d l i l ? d maintain sandbar habitats over decadal timescales? 

• Will multiple high flows conducted over a period of several years 

result in net increases in sandbar area and volume?

• With the available sand supply (i.e. tributary inputs) is the 

approach of using repeated floods to build sandbars sustainable?

What questions will we want to answer if there are repeated 

high flows over the next 10 years?

These are the fundamental sediment-related high flow 

science questions. How will they be addressed?

Strategic Science Questions that 

motivate Goal 8 Monitoring

 Will multiple high flows conducted over a period 

of several years result in net increases in sandbar 

area and volume?

 Addressed by monitoring sandbars above 8,000 

cfs stage.

– Annual (with high flows) to every-other year (without 

high flows) monitoring of long-term sandbar monitoring 

sites (NAU sites).

– Systemwide monitoring every 4 years by overflights.

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Strategic Science Questions that 

motivate Goal 8 Monitoring

 With the available sand supply (i.e. 

tributary inputs) is the approach of using 

repeated floods to build sandbars 

sustainable?

 Addressed by repeat channel mapping

The “Sand Cycle” in Grand Canyon

• With the available sand supply (i.e. tributary inputs) is the 

approach of using repeated floods to build sandbars sustainable?

Tributary Channel and 

High elevation 

sandbars

High flows

sand inputs low eddy 

storage

Low-elevation 

sandbars

Downstream; Lake 

Mead

All flows

Sandbars are built with sand 

from the channel and lowelevation parts of eddies

The “Sand Cycle” in Grand Canyon

• With the available sand supply (i.e. tributary inputs) is the 

approach of using repeated floods to build sandbars sustainable?

Tributary 

Channel 

and low 

High 

elevation 

High flows

Tributary 

sand inputs

and low 

eddy 

storage

elevation 

sandbars

Low-elevation 

sandbars

Downstream; Lake Mead

All flows

Large channel and low-eddy 

storage = high capacity for 

building sandbars

The “Sand Cycle” in Grand Canyon

• With the available sand supply (i.e. tributary inputs) is the 

approach of using repeated floods to build sandbars sustainable?

Tributary 

Channel and low eddy 

storage

High elevation sandbars

High flows

sand inputs

Low-elevation 

sandbars

Downstream; Lake Mead

Small channel and low-eddy 

All flows

storage = low capacity to 

build sandbars

The “Sand Cycle” in Grand Canyon

 The savings account analogy:

– The low-eddy and channel storage is the bank account.

– Sandbars are the dividend

• With the available sand supply (i.e. tributary inputs) is the 

approach of using repeated floods to build sandbars sustainable?

– Downstream export is the rent.

 Monitoring sandbars is monitoring the dividend

– Appropriate for tracking status of sandbars

– Not appropriate for predicting future dividends (sandbar 

condition)

 Bottom line:

– To be able to explain observed trends in sandbars over the next 10 years, we need to monitor the bank account.

Conceptual model for interpretation of repeat 

channel mapping information

ve 8,000 cfs”

gain

Probably 

good news!

Mining 

sand from 

storage

Would not know 

the difference 

between success 

and potential 

future downward 

Without Channel 

Mapping:

“Channel and eddies below 8,000 cfs”

loss gain

“Sandbars abov

loss

Mining 

sand and 

losing 

sandbars

Accumulating 

sand, not 

building bars -

Could be 

having more 

floods!

future downward 

spiral.

Would not know 

the difference 

between really bad 

news (not enough 

sand) and not so 

bad news.

12

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Analysis and Interpretation of Channel 

Mapping Data: 2008 HFE

Demonstrates the 

difference between 

high- and lowelevation response

2

3

4

ENCE STAGE RATIO

E-HFE SAND VOLUME

65R

44L

Net Eddy Deposition

Net Eddy Erosion

gain

bove 8,000 cfs”

0 0.5 1 1.5 2

BELOW REFERENCE STAGE RATIO

OF POST- TO PRE-HFE SAND VOLUME

0

1

ABOVE REFERE

OF POST- TO PR

Style 1

Style 4

Style 2

Style 3

03L

44L

172L

87L

“Response below 8,000 cfs”

loss gain

“Response a

loss

Hazel and others (2010) 13

May 2002 to May 2009: RM 42 to 45

Elevation 

Change (cm)

May 2002 to May 2009: RM 44 

(Eminence Break camp)

Elevation 

Change (cm)

May 2002 to May 2009: RM 45 

(Willie Taylor camp)

Elevation 

Change (cm)

May 2009 near RM 36

 There is a lot of sand on the bed in 

some locations

– Is the amount increasing or 

decreasing?

Analysis and Interpretation of Channel Mapping: 

Data from short reaches 2002 to 2009

ve 8,000 cfs”

gain

“Response below 8,000 cfs”

loss gain

“Response abov

loss

18

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Results from repeat channel mapping 

of short reaches: 2000 to 2009

 Comparison of responses above and below 8,000 cfs stage

– High- and low-elevation responses are often opposite, 

sometimes they are similar

 Reflects response to HFEs

 Reflects periods of sand accumulation

 Reflects periods of sandbar erosion

 Small fraction of changes in sand storage are above 8 000 Small fraction of changes in sand storage are above 8,000 

cfs stage

– Up to 25% when HFEs build sandbars

– Usually less than 5% under normal operations

 Short reaches (up to 10 mi) NOT representative of long 

reaches (~ 30 mi)

 To explain the responses and make interpretations about 

prospects for sandbar maintenance over long time periods, 

we need to conduct these analyses over longer reaches.

Within short (1.5 to 3 mile) reaches, sandbar 

monitoring sites (NAU sites) are representative of 

all sandbar changes above 8,000 cfs stage

Outstanding questions that continued repeat 

channel mapping will help answer

 Is the approach of using repeated HFEs to build 

and maintain sandbars sustainable over long 

(decadal) periods of time?

 Are the sandbar monitoring sites representative 

of changes over long (~30 mi) reaches? 

 Can we monitor sand storage by subsampling?

– Once we’ve done some repeat mapping of long reaches, 

we may be able to devise an appropriate subsampling 

scheme.

SedTrend Channel Mapping: 2010-2012

2011

 Complete reports that are in progress on the data 

collected between 2000 and 2009.

 Map RM 61-87 and process those data.

 2012 

 Compare 2011 data with previous mapping for the parts 

of the RM 61-87 reach where data are available and publish 

rep p ort on that comparison.

 Map either RM 0-30 or RM 166-225.

22

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FY10: Sandbar and Campsite Monitoring in 

Colorado River in Marble and Grand Canyons

U.S. Department of the Interior

U.S. Geological Survey

Joe Hazel, Matt Kaplinski, Rod Parnell, and Nathan Schott

Annual Reporting Meeting

January 18, 2011

Strategic Science Questions pertaining to 

sandbars and campsites

 Is there a “flow-only” operation that will rebuild and 

maintain sandbar habitats over decadal timescales?

 Will multiple high flows conducted over a period of 

several years result in net increases in sandbar area 

and volume?

 Determine and track the effects of ROD operations on 

the size, quality, and distribution of camping beaches in 

the Colorado River ecosystem.

Where is the sand?

~50 to 90% of the sand in Marble Canyon is stored in eddies. About 90% of 

the sand in eddies is stored below the stage elevation reached by a flow of 

8,000 ft3/s (Hazel et al., 2006, J. Geophys. Res., 11).

Study Design

1) Topographic field surveys 

annually and in some 

years more frequently 

between 1990 and 2009 

at long-term study sites 

distributed throughout 

the river corridor

2) Bathymetric surveys were 

collected in the 1990s 

and before and after the 

2004 HFE and 2008 HFE

Grams et al., 2010, FISC

2008 HFE styles of topographic response

2

3

4

CE STAGE RATIO

HFE SAND VOLUME

65R

Net Eddy Deposition

Net Eddy Erosion

Style 1 was net 

increase in volume 

(fill) at all elevations 

above and below 

reference stage 

(45% of the study 

sites)

0 0.5 1 1.5 2

BELOW REFERENCE STAGE RATIO

OF POST- TO PRE-HFE SAND VOLUME

0

1

2

ABOVE REFEREN

OF POST- TO PRE-H

Style 1

Style 4

Style 2

Style 3

03L

44L

172L

87L

Style 2 was net 

decrease in volume 

(scour) in the eddy 

and channel below 

reference stage and 

net fill in the eddy 

above base flow 

stage (37% of the 

sites)

Hazel et al., SIR 2010-5015

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Example of Style 1 and Style 2 response

15

20

25

15

20

25

tom of pool in meters

Volume change by elevation increment, 47R

dVi 02/04 

1996

dVi 08/09 

2000

dVi 02/03 

Bar-building

0

5

10

0

5

10

‐4000 ‐3000 ‐2000 ‐1000 0 1000 2000 3000

Elevation above bott

Volume change, m3

dVi 02/03 

2008

8k wsl

45k wsl

Erosion Deposition

Intervening dam operations erode bars

osion rate, in ft3/day

1,000

1,500

2,000

2,500

3,000

Marble Canyon

Grand Canyon

1996 

HEF

2004 

2008 

HEF

Ero

Mean of daily discharge for period between 

surveys, ft3/s

0

500

0 5,000 10,000 15,000 20,000

HEF

Grams et al., 2010, FISC March 11, 2008 (~8,000 ft3/s) June 4, 2008 (~10,500 ft3/s)

1.2

1.4

1.6

me Relative to

6 Volume (m3)

30,000

40,000

50,000

Mean Daily

from Glen Can

1996 HEF 2004 HEF 2008 HFE

Changes in Sandbar Size in Marble Canyon and 

Eastern Grand Canyon, 1996-2009

10/20 bars are the same or larger in size than the 1996 pre-HFE condition

0.4

0.6

0.8

1.0

Median Volum

February 1996

Year

0

10,000

20,000

y Discharge

nyon Dam (ft3/s)

1996 1998 2000 2002 2004 2006 2008 2010

Above 8,000 ft3/s, n=20

Below 8,000 ft3/s, n=16

1.2

1.4

1.6

me Relative to

6 Volume (m3)

30,000

40,000

50,000

Mean Daily

from Glen Can

1996 HEF 2004 HEF 2008 HFE

Changes in Sandbar Size in Central and Western 

Grand Canyon, 1996-2009

20/20 bars are the same or larger in size than the 1996 pre-HFE condition

0.4

0.6

0.8

1.0

Median Volum

February 1996

Year

0

10,000

20,000

y Discharge

nyon Dam (ft3/s)

1996 1998 2000 2002 2004 2006 2008 2010

Above 8,000 ft3/s, n=20

Below 8,000 ft3/s, n=16

What is the 

future 

desired 

condition? 

In October 2009 the 

sandbars in Marble 

Canyon stored about the 

same volume of sand but 

are much smaller in area 120,000 50,000

30,000

35,000

40,000

45,000

50,000

Sand Bar Area (m2)

0

10,000

20,000

30,000

40,000

50,000

Daily Mean Discharge

from Glen Canyon Dam (ft3/s)

1996 HEF 2004 HEF 2008 HFE

compared to 1990.

The sand has been 

moved to higher 

elevations and the bars 

are not bigger.

50,000

60,000

70,000

80,000

90,000

100,000

110,000

Sand Bar Volume (m3)

Year

0

10,000

20,000

30,000

40,000

Daily Mean Discharge

from Glen Canyon Dam (ft3/s)

1996 HEF 2004 HEF

1990 1994 1998 2002 2006 2010

2008 HFE

Rubin et al.,

2002,EOS, AGU, 83

What is the 

future desired 

condition? 

5,000

NAU and USU, unpubl., data

1986 1990 1994 1998 2002 2006

0

1,000

2,000

3,000

4,000

Sand Bar Volume (m3)

1991-1995

Interim Flows

Jan. 18, 1986

Schmidt Survey ROD Operations

The sandbar at Saddle 

was twice the size in 

1986 than 1990.

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The potential role of powerplant capacity flows to 

build bars?

0.8

1

1.2

dation

73% inundated by 31,000 ft3/s

0 20 40 60

River Mile

0.2

0.4

0.6

0.8

Percent Inund

31,000 cfs

45,000 cfs

Redwall Cavern

73% inundated by 31,000 ft /s

88% inundated by 45,000 ft3/s

31,000 inundation depth=3.2 m

45,000 inundation depth=4.1 m

15

20

25

m of pool in meters

Volume change by elevation increment, 55L

dVi 02/04 

1996

dVi 08/09 

2000

There is a substantial difference in deposit thickness that can 

result from that difference in inundation depth

0

5

10

-4000 -3000 -2000 -1000 0 1000 2000 3000

Elevation above bottom

Volume change, m3

dVi 11/12 

2004

dVi 02/04 

2008

8k wsl

31k wsl

Erosion Deposition

1.2

1.4

1.6

Relative to

olume (m3)

30 000

40,000

50,000

Mean D

from Glen C

1996 HEF 2004 HEF 2008 HFE

Changes in Sandbar Size in Marble Canyon and 

Eastern Grand Canyon, 1996-2009

Deposition by the two 31,000 ft3/s in 2000 were not effective in

bar building or slowing the erosion rate between 1996 and 2000

0.4

0.6

0.8

1.0

Median Volume R

February 1996 Vo

Year

0

10,000

20,000

30,000

aily Discharge

Canyon Dam (ft3/s)

1996 1998 2000 2002 2004 2006 2008 2010

Above 8,000 ft3/s, n=20

Below 8,000 ft3/s, n=16

Campsite changes 1999-2009

25% and 55% of the area measured in 1999 remains in

noncritical and critical reaches, respectively

2008 HFE

2004 HFE

Strategic Science Questions pertaining to 

sandbars and campsites

 Is there a “flow-only” operation that will rebuild and 

maintain sandbar habitats over decadal timescales?

The results from the 2008 HFE show that floods timed with tributary-supplied

sand can build bars. Questions remain whether this is a sustainable approach

for Marble Canyon over decadal timescales. 

 Will multiple high flows conducted over a period of 

several years result in net increases in sandbar area 

and volume?

There are distinct longitudinal differences in sandbar volume that suggest

this has occurred in central and western Grand Canyon. 

 Determine and track the effects of ROD operations on 

the size, quality, and distribution of camping beaches in 

the Colorado River ecosystem.

The 2008 HFE resulted in short-term campsite area gains but campsite area 

continues to decline in both critical and noncritical reaches. 

Anticipated products in FY2011:

Hazel, J.E., Jr., Kaplinski, M., Schott, N., Parnell, R., Grams, P., and Ross, R., in progress, Sand Storage 

Measured at Selected Sites in Colorado River in Marble and Grand Canyons, Arizona, 1990-2009: U.S. 

Geological Survey Scientific Investigations Report 20xx-xxxx, xx p. 

Kaplinski, M., Grams, P., Hazel, J.E., Gushue, T., Tusso, R., Kohl, K., Shott, N., in progress, Monitoring 

Fine-Sediment Volume in the Colorado River Ecosystem, Arizona: Construction and Analysis of Digital Elevation 

Models, U.S. Geological Survey Scientific Investigations Report. 

Parnell, R., Kaplinski, M., Hazel, J.E., Jr., and Schott, N., in progress, Campsite Area Measurements in Marble 

and Grand Canyons, 1998-2009: U.S. Geological Survey Data Series Report. 

Draft data subject to revision. DAY 1 OF 2. 

TWG review document, DO NOT CITE, reproduce, or distribute.

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1/19/2011

1

EVACUATION OF 

FINE SEDIMENT 

FROM THE 

COLORADO

RIVER– 1965 TO 

2009

FY 2010 Project Annual Reporting Meeting for 

TWG

Nina E. Kilham, John C. 

Schmidt, Joseph M. Wheaton, 

Paul E. Grams

With a little help from: Alan Howard, Bill 

Emmett, Tim Randle, and Matt Kaplinski

Below Redwall Cavern RM 33.50L

Downstream view from the site

More sand

More sand More sand

January 15, 1890; Stanton expedition January 3, 1992; Robert H. Webb (~daily mean 13,400 

ft3/s)

March 30, 1999 (~daily mean 13,600 ft3/s)

New vegetation

April 4, 2009 (~8,000 ft3/s)

Less sand

New vegetation

New vegetation

Photo compilation M. Majerova (Utah 

St t )

What do first principles tell 

us? Borland’s 

illustration of 

Lane’s (1955) 

concept, drawn 

by Vitaliano

Balance between the energy of the

river provided by flowing water to

transport sediment, and the

sediment load supplied to the river.

INCISIO 63% 

N 95% of 

sediment 

cut-off

reduction 

in 2-yr 

flood

Topping et al., 2003

In Glen Canyon, sediment deficit, bed incision occurred ....

Pools

Grams et al., 2007

0

2

4

6

8

10

1950 1960 1970 1980 1990 2000 2010

R18

R16

R14

R10

R8

R1

BED DEGRADATION, IN METERS b) YEAR

2.5 km

4.3 km

7.5 km

12.8 km

15.0 km

23.9 km

Coarse bouldery rapids prevent bed 

adjustment in Grand Canyon. With low 

sediment supply and steep channel 

slope, mass balance deficit remains and 

available fine sediment is efficiently 

removed from system.

Magirl et al., 2005

Magirl et al., 2005

Draft data subject to revision. DAY 1 OF 2. 

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1/19/2011

2

RM 42.3-45.5

Minimum Surface

Transient Storage

Key Questions

 Is there evidence for a wave of pool 

evacuation downstream from Glen Canyon 

Dam?

 How fast did ( ) or is the Colorado adj g ustin to 

sediment trapping behind the dam?

Why do these questions matter?

 We know that the sand for building sandbars (during floods) comes 

from the channel.

 We know that floods use (by transporting downstream and building 

sandbars) about as much sand as tributaries supply.

 We do NOT know the long term trend of sand storage in the 

channel.

 If negative, the capacity to use high flows to build sandbars will 

decrease.

 Must be extremely careful about scheduling of high flows and consider the 

effect of intervening dam operations.

 If positive, the capacity to use high flows to build sandbars is great.

 Opportunity to be more aggressive with high flows and intervening operations.

 If neutral, the capacity to use high flows to build sandbars is likely 

adequate.

 Intermediate approach.

1965

1976

1984

Photo from William Emmett

2000

Photo from Matt Kaplinski

June 20 [camped at Buck Farm]

"After dinner, we stayed up well into the night — at least, those of us 

who lasted – telling tall tales and partaking of libation. Here comes the 

famous barracuda story and the infamous pistol shooting. Nine bottle so 

far — what a crew!"

Historic Datasets

Year Data Source Instrument Discharge WSE* Path Total

m cms m m m

Jun‐65 Leopold/Emmett Heathkit, MI‐11A Fishfinder 0.3 1372 1 2.5 2.7

Jul‐76 Howard/Dolan reported in Dolan et al., 19780.3 578 0.4 2.5 2.5

Mar‐84 USGS/BOR

reported by Tim Randle as a

total error high WSE of .6

low .15 0.15 678‐708 0.6 2.5 2.6

1992‐1995 Graf sonic‐depth sounder 0.39 194‐558 0 0 0.4

Aug‐00 FIST

Reson SeaBat 8124

multibeam‐sonar ** 0.088 227 0 0 0.1

May‐02 FIST Reson SeaBat 8124 0.074 227 0 0 0.1

Jun‐04 FIST Reson SeaBat 8124 0.063 227 0 0 0.1

Nov‐04 FIST Reson SeaBat 8124 0.048 227 0 0 0.0

Dec‐04 FIST Reson SeaBat 8124 0.05 227 0 0 0.1

May‐09 GCMRC Garmen GPS Fish Finder 0.15 227 0.32 0 0.4

*Reported by MaGirl et al., 2008

**SDEz Reported in Table 4 of Kaplinski et al., 2009

Draft data subject to revision. DAY 1 OF 2. 

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3

 Sources of Uncertainty:

 Instrument?

 Boat path (longitudinal 

and lateral position)?

 Water surface?

Path 

1

Path 

50

Photo from Matt Kaplinski

President 

Harding Rapid

Eminence 

Riffle

Anasazi

Riffle

Reference rapids 

helped locate the 

old traces

TWIG 2010 - Utah State University

Willy Taylor

President Harding Rapid

Willy Taylor

Eminence 

Riffle

Anasazi Riffle

Water Surface

Depths were 

converted to 

elevations using 

modeled water 

surface 

elevations.

Channel Bed

Magirl et al., 2005

RM 

1.2

BLACK bars show the 

additive uncertainty for 

each depth.

RED boxes show the range 

of the annual pool 

elevation measured by 

GCMRC.

RED: most 

active BLUE: 

least active

RM 

43.6

RED boxes show the range 

of the annual pool 

elevation measured by 

GCMRC.

BLACK bars show the 

additive uncertainty for 

each depth.

RED: most 

active BLUE: 

least active

Draft data subject to revision. DAY 1 OF 2. 

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1/19/2011

4

#2 (Paria) 3 pools

2004, 2009 deepest

#3 (20s) 2 pools

1976 deepest #4 (Redwall) 7 pools

2004 deepest

#5 (Hansborough) 5 

pools

#9 (Aisles) 2 pools 2004 deepest #6 (Kwagunt) 3 

pools

1965, 1984 deepest

#7 (Tapeats) 4 

pools

1984 deepest

#8 (Cremation) 4 

pools

( )p

#11 (Diamond) 1 

pools

#10 (Granite) 1 

pools

 The first analysis of the amount of sediment stored in 

pools in the main channel of the Colorado River 

between Glen Canyon and Hoover Dams from 1965 

to 2009.

 This information can be used to assess the location of 

l t t d it d th l ti hi b t

What this analysis means...

ong-term study sites, and the relationship between 

the mobilization and storage of sediment in the main 

channel and the more intensively monitored eddies. 

 This information will help understand long-term trends 

of sand storage and thereby make more informed 

decisions about dam operations, such as high flows, 

to restore sandbars.

Draft data subject to revision. DAY 1 OF 2. 

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Update to TWG on Campsite 

Monitoring and other Recreation 

Projects (Goal 9)

U.S. Department of the Interior

U.S. Geological Survey

Projects (Goal 9)

Helen Fairley 

TWG Annual Reporting Workshop, Phoenix, AZ

January 18, 2011

FY 2010 Recreation Projects

1. Monitor Changes in Campsite Area & Quality  C () ampsite area measurements (NAU repeat surveys)

 Evaluate vegetation encroachment at campsites

 Evaluate change using remotely sensed imagery and repeat 

photographs (AAB, Bob Webb, Weeden photo matches)

2. Develop GIS Develop GIS-Based Campsite Atlas Based Campsite Atlas 

3. Recreation Safety in Relation to Flows Study

Evaluating Role of Vegetation 

Encroachment in Campsite Area Change

 1998-2007: NAU campsite area/sand bar surveys 

showed campsite area declining more rapidly than 

sand bar area and volume

 Kaplinski et al (2005, 2010) hypothesizes that 

vegetation encroachment explains the difference

 In the 2010-2011 BWP, GCMRC proposed conducting 

an interdisciplinary remote sensing project involving an interdisciplinary remote sensing project involving

comparisons of 2002, 2005, and 2009 imagery; one 

component involves quantifying rate and amount of 

vegetation encroachment at campsites using imagery 

 Processing of 2009 imagery is well underway but not 

yet completed (see DASA presentation tomorrow)

 Evaluating vegetation encroachment on campsites is 

on hold until 2009 imagery is available for analysis

Compile repeat photography to track 

vegetation encroachment at campsites 

 In addition to analyzing aerial imagery, GCMRC is 

compiling photo-matches to supplement other 

sources of information documenting effects of 

riparian vegetation on campable area in the CRE 

 Adopt-A-Beach photographs

 Robert H Webb repeat of Stanton photos, 1890 to 1990 and 

1990 to 2010

 Weeden photo matches 1973 to 2007-2010

 J. Schmidt photo matching project

Adopt-A-Beach

 In 1196, GCRG started this project as an expedient 

way to monitor effects of 1996 high flow and engage 

river guides in a “citizen science” initiative

 Project has been continuous since 1996 

 In 2010, volunteer river guides adopted 44 beaches;

river guides continue to match photos & document 

observations about change on a written form

 In the fall, GCRG compiles the data, prepares annual 

report, posts photos on GCRG website

 2009 report distributed to TWG by Lynn Hamilton 

July 2010; FY2010 report currently in progress

Buck Farm Camp, RM 41.2

March 1996 April 5, 2002

May 25, 2009

March, 1996

July 10, 2004

April 5, 2002

Draft data subject to revision. DAY 1 OF 2. 

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Talking Heads Camp, RM 133.7

April 17 1996 July 15 1998

Sept 20, 2006 June 8, 2009

April 17, 1996 July 15, 1998

Robert H Webb is matching Stanton 

photos from 1890, 1990-91 and 2010-11

GIS Atlas Project: Revelant SSQs

Atlas will be a data repository & research tool for use in 

future research & monitoring projects addressing:

 How do varying flows positively or negatively affect campsite 

attributes?

 How to varying flow regimes positively or negatively affect 

group encounter rates, campsite competition, and other 

important social parameters known to be important variables of 

visitor experience?

 How do dam controlled flows affect visitors’ recreation 

experience, and what are optimal flows for maintaining a high 

quality recreational experience?

GIS Atlas Project Summary

 USGS (GCMRC) and NPS (GRCA) worked collaboratively in 

2007-2009 to develop GIS-based campsite atlas maps and match 

1973 Weeden photographs 

 Atlas is designed to serve as primary data repository and 

research tool for future campsite monitoring in the CRE

 500+ t d hi t i l id tifi d 220 tl 500+ current and historical camps identified; ~ 220 currently 

actively managed by NPS (NPS primary sites)

 Atlas will be used to track change and archive data from GCD 

AMP & CRMP monitoring projects

 NPS already using some atlas elements (e.g., maps) to monitor 

recreation impacts and capacity changes

IN 2010, NPS compiled camp maps and 

basic data into proto-DVD for river runners 

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GIS Atlas Shortfalls

 Project is behind schedule – several reasons:

 GCRMC decided to upgrade GIS software and 

servers and to redesign website in 2009: this has 

taken longp y er than anticipated and delayed 

installation/testing of pilot atlas in 2010 as planned

 NPS lost staff in 2008-2009, some positions were 

not backfilled; NPS GIS technician working on this 

project was assigned other work priorities

GIS Atlas 2010 Accomplishments

 Campsite field mapping completed in 2007-2009; mapped data 

transferred to GIS and has been updated through FY2009

(Field work accomplished in conjunction with NAU sand bar/campsite 

monitoring, NPS CRMP monitoring, and GC Youth trips)

 500+ current and “legacy” campsites identified & input to GIS

 4400+ photographs of campsites dig 4400+ photographs of campsites digitized entered into photo , entered into photo

database, linked to GIS data

 400+ documents about GRCA campsites scanned -- approx. 30 

key reports will be made available with the first atlas 

 As of December 2010, GCRMC DASA staff installed new 

version of ArcServer (GIS software). Now are developing and 

testing a proto-type version of the atlas on internal website 

Project Schedule (2011)

 Enter 2010 NPS data and additional photographs into 

database – winter/spring 2011

 Finalize customized code to link GIS data, photos, 

and reports and test on internal web – winter/spring 

2011

 Prepare introductory web pages, refine web delivery 

software, etc . – spring 2011

 Serve first public version of the atlas – summer 2011

Recreation Safety in Relation to Flows

 Primary SSQ

 How can safety and navigability 

be reliably measured in relation 

to flows?

 Secondary SSQ Secondary SSQ

 What are the drivers for 

recreational experiences in the 

CRE, and how important are 

flows relative to other drivers in 

shaping recreational 

experience outcomes?

Recreation Safety in Relation to Flows

Project Summary:

 Original plan was to compile and 

analyze all GCES, NPS, and other 

relevant data on recreation safety in 

relation to Colorado River flows

 NPS requested change in scope to NPS requested change in scope to focus on literature review, review of 

other safety monitoring programs, 

review of options for monitoring 

safety in relation to flows

 Research is being conducted 

through coop with Northern Arizona 

University (2 Yr NAU Masters Thesis)

Recreation Safety in Relation to Flows:

2010 Accomplishments and Next Steps:

 NAU graduate student (Kelly McGill) started project 

in summer 2009; data collection mostly completed in 

2010; write up in progress now (winter 2011)

1) Compiled currently available river recreation safety data from Grand 

Canyon National Park 

2) Researched what other safety Researched what other safety-related studies have been conducted related studies have been conducted in other parts of the US and how other river management agencies 

across the nation have address safety issues 

3) Identified knowledgeable experts in river recreation safety and conducted interviews with them 

4) Conducted informal, voluntary survey of Grand Canyon river guides 

 Draft thesis anticipated late winter-spring 2011

 Final report anticipated summer 2011

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Ground cover and stability 

of aeolian landscapes

U.S. Department of the Interior

U.S. Geological Survey

TWG Annual Reporting Meeting

January 18, 2011

Amy Draut 

Research Geologist

U.S. Geological Survey, Santa Cruz, CA

Wind-blown sand forms aeolian dunes

Weather stations tell us where wind carries 

sand from river sandbars; landscape 

processes near archeological sites

Weather station Sand traps

New river sand moves inland by wind

Controlled floods can supply new windblown sand where wind direction is right

Aeolian landscapes form downwind 

of river sandbars

WIND

Measure ground cover

Compare ground cover on aeolian landscapes 

that get new wind-blown sand (after controlled 

floods) with those that don’t get new sand

Draft data subject to revision. DAY 1 OF 2. 

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Modern vs. Relict aeolian landscapes

Some get new sand from modern sandbars Others don’t.

These sites have an HFE These don’t

sandbar just upwind

Measured ground cover in 2 groups of dune-fields

Open sand space

Box-and-whisker plots:

3rd quartile (x0.75)

Median (2nd quartile, x0.5)

1st quartile (x )

GC-Modern GC-Relict

These don’t These sites get modern windblown sand supply after HFEs

1st quartile (x0.25)

Outliers: any points > 1.5 

times the inter-quartile range 

(box length)

Whiskers: highest and 

lowest non-outlier points

Open sand space

t-test tells you how 

different two groups are

t-test  p value 

Low p values mean the

GC-Modern GC-Relict

These don’t

p < 0.00001

Low p values mean the

two groups are 

significantly different

These sites get modern windblown sand supply after HFEs

Biologic soil crust

p < 0.005

GC-Modern GC-Relict

These don’t These sites get modern windblown sand supply after HFEs

Vegetation cover

Other factors also 

affecting vegetation (e.g., 

non-native Russian Thistle 

explosions)

GC-Modern GC-Relict

These don’t

But still, p < 0.05

These sites get modern windblown sand supply after HFEs

Draft data subject to revision. DAY 1 OF 2. 

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Sand transport by wind

p < 0.00005

GC-Modern GC-Relict

These don’t These sites get modern windblown sand supply after HFEs

Aeolian dunes without modern sand supply:

Have:

More biologic crust

More vegetation More vegetation

Less open sand

Less sand transport

... compared with places that still get sand supply

Relict aeolian landscapes –

Implications for archeological site stability

Less sand movement 

on ground surface = 

crusts stabilize soil,

dunes less mobile.

BUT too little BUT, too little

windblown sand to fill 

small gullies

Small gullies become 

large gullies

Modern aeolian landscapes with sand supply –

Implications for archeological site stability

More sand movement 

on ground surface = 

dunes shift, migrate

Artifacts 

covered/uncovered by 

dunes

Windblown sand can 

fill small gullies

Gullies can heal

How “natural” are the GC aeolian 

dunes with modern sand supply?

 Grand Canyon has had 3 controlled floods in past 

15 years

 How do aeolian landscapes compare in a place that 

has spring floods making big sandbars EVERY has spring floods making big sandbars EVERY

year?

Draft data subject to revision. DAY 1 OF 2. 

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Colorado River, Cataract Canyon, Utah

 16 river-miles below 

confluence of Green and 

Colorado Rivers, above 

Lake Powell

 Mostly (well, more) 

nat lh d l d tural hydrology and

sediment supply

 Canyonlands NP

 No GCMRC support

Cataract Canyon

Spring flood in 2010 around 54,000 cfs

Cataract Canyon

Big new sandbars left by spring flood...

Cataract Canyon

... forming aeolian dunes downwind

Open sand space

Cataract aeolian 

landscapes just downwind 

of annual flood deposits 

(n=13) very similar to 

those in Grand Canyon 

GC-Modern GC-Relict CAT-Modern

p > 0.05

that get sand from 

occasional HFEs

Biologic soil crust

Cataract aeolian 

landscapes just downwind 

of annual flood deposits 

(n=13) very similar to 

those in Grand Canyon 

GC-Modern GC-Relict CAT-Modern

that get sand from 

occasional HFEs

p > 0.05

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Results: Vegetation cover

Inconclusive, but still 

shows no significant 

difference between 

Cataract and Grand 

Canyon’s modern aeolian 

GC-Modern GC-Relict CAT-Modern

p > 0.05

dune fields

Grand Canyon’s vs. Cataract’s 

aeolian landscapes

 No significant differences between ground cover on 

Cataract aeolian dunes that get sand from flood 

deposits every year and those in Grand Canyon that 

only get sand occasionally from HFEs

 Good news! HFEs are effectively simulating “natural” 

conditions of ground cover on those aeolian dunes 

that can get modern sand supply

Conclusions

 Two types of aeolian landscape in Grand Canyon:

 Modern (get new sand supply after HFEs)

 Relict (no modern sand supply = changes in 

vegetation, soil crust, open sand, transport)

 Stabilityp g of landscapes and archeological sites 

controlled by different processes in modern vs. relict 

aeolian dunes

 HFE sand blowing inland effectively reproduces 

“natural” ground-cover conditions on modern dunefields (similar to Cataract’s aeolian dunes supplied by 

annual flood sand)

Going in to 

Lake Powell

Coming out of 

Lake Powell

Flows in Cataract vs. what would be 

in Grand Canyon

Loss of sand supply to relict dunes: 

Does it matter yet?

 Flood of 170,000 cfs 

can supply sand to 

source areas for the 

canyon’s largest 

relict dune fields

FEET PER SECOND

Flood frequency curve 

by Topping et al., 2003

 Last was in 1921

 Would have ~40 yr 

return interval

 So, Yes it does 

matter by now

RETURN PERIOD, IN YEARS

DISCHARGE, IN CUBIC 

Draft data subject to revision. DAY 1 OF 2. 

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Normalizing sand-transport rates: 

used local 4-minute wind and rain data

(Mass in sand traps / # of days to accumulate it) per cm

q 1.8 d

D



g

u*

3

x 107 = Dimensionless #

Don’t have u* (shear velocity), so substitute u2m

(wind velocity) in Bagnold (1941) transport equation

q  2.78 

g

  u*  u*t   u*  u*t

2

q  0.83 d

D



 

0.75 

g

u*

3

Kawamura (1951)

Zingg (1953)

You can use other transport equations instead, doesn’t change results.

2007

2010

Aeolian (wind-blown) sand

Fluvial (river) sandbar

WIND

Draft data subject to revision. DAY 1 OF 2. 

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1

Rainbow Trout Early Life Stage Survival

FY 2010 TWG Report

J hK os orman

Ecometric Research

January 18, 2011

Why Monitor Early Life History Stages of 

Rainbow Trout in the Lees Ferry Reach?

1. Survival for early life stages of rainbow trout in the Lees Ferry 

reach ultimately determines the number of juveniles recruiting to 

the adult population, which over the long term controls the trend in 

adult abundance.

2. Very difficult to evaluate flow effects on population trends 

without monitoring early life stages.

 Flow very likely effects more sensitive early life stages

 Long lag until those stages recruit to adult population typically monitored.

 Effects of multiple flow regimes often confounded (e.g., HFE-FSF)

3. Adult abundance in the Lees Ferry reach effects the tailwater

fishery and possibly native fish abundance

Redd Counts

Non-native fish

suppression flows

Record of Decision

flows (MLFF)

Redd elevations

80%

100%

Expt. High Fluctuation Yrs. Control Yrs. (normal operations)

Flow

Elevation

(kcfs)

0%

20%

40%

60%

Feb Mar May Feb Mar May Feb Mar May Feb Mar May

2003 2004 2006 2007

% of Redds

15-20

12-15

8-12

5-8

<5

(kcfs)

600

800

1000

ance (x 1000)

2003

2004

2006

2007

2008

2009

2010

Seasonal Trend in Age-0 Abundance in the

Lees Ferry Reach, 2003-2010

0

200

400

Age-0 abunda

Apr May Jun Jul Aug Sep Oct Nov Dec

Effects of Non-native Fish Suppression Flows and the 

2008 High Flow Experiment on Early Survival

Draft data subject to revision. DAY 1 OF 2. 

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2

200

300

400

500

2007

Apr. May June July Aug. Sept. Oct. Nov. Dec.

(a)

300

400

500

2008 (b)

e (m3

s

1

)

Fall Steady 

Flow (FSF) 

Effects

200

300

Apr. May June July Aug. Sept. Oct. Nov. Dec.

Date

Discharge 200

300

400

500

Aug.-28 Aug.-29 Aug.-30 Aug.-31 Sept.-01 Sept.-02 Sept.-03 Sept.-04 Sept.-05 Sept.-06

MLFF (2007)

FSF (2008)

(c)

Transition

Fall Is age-0 survival 

higher during 

transition and fall 

periods under 

FSF?

Mortality Rates by 

Year and Period

Mortality 

Differences 

Between Flow 

R i eg mes

Net Survival by 

Flow Regime

Timing of Age-0 Habitat Use Critical to Developing 

Effective Non-Native Suppression Flows

Low-angle habitat

Preferred by smaller age-0 trout, May-July

Likely more sensitive to variation in flow

Daily Min. Flow

Daily Max. Flow

7 m

High-angle habitat

Preferred by larger age-0 trout, July-Winter

Likely less sensitive to variation in flow

Low-velocity-shallow habitat

suitable for small age-0 trout

60

80

100

ance (x 1000)

Low-Angle

High-Angle

Ontogenetic Habitat Shift from Low- to 

High-Angle Shorelines

2004

0

20

40

60

Date

Age-0 Abunda

Apr. May June July Aug. Sept. Oct. Nov. Dec.

60

80

100

in low-angle habitat

2004

2006

2007

2008

2009

2010

Timing of Low-Angle Habitat Use

0

20

40

Month

% of population 

May June July Aug. Sept. Oct. Nov. Dec.

Conclusions

1. Flow-dependent incubation losses of 25-50% in non-native fish 

suppression flow years were not large enough to reduce abundance of age0 trout because of a strong density-dependent survival response following 

emergence.

2. Stock-recruit curve indicates that as few as 300 redds are required to 

sustain Lees Ferry population. Perhaps not many redds required near LCR 

(Nankoweep, mainstem mainstem) to sustain a small local population. ) to sustain a small local population.

3. 2008 High Flow Experiment increased survival rates of recently emerged 

trout over four-fold in 2008 and over 2-fold in 2009 (no effect by 2010). 

But n=1 - 1.5, so don’t give up on HFEs quite yet!

4. No substantive effect of the Fall Steady Flow Regime on age-0 trout 

abundance by late fall.

Draft data subject to revision. DAY 1 OF 2. 

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3

Management Opportunities

1. Trout suppression flows should occur in May-July when fry are still in 

flow-sensitive low-angle habitat, and when most of density-dependence 

has probably already occurred.

2. Higher GCD release volumes this year may stimulate trout production:

– Cleaner substrate in LF and MC

– Steadier flows during critical juvenile rearing period

– Increased ‘pasture area’ due to greater width leading to increased growth/survival

4. High releases provide a unique cost-effective opportunity to test trout 

suppression flows (egg or juvenile suppression).

FY 2010 Accomplishments

• GCMRC and AGF completed all sampling planned for 2010 

(5 redd surveys and 4 fry surveys, no otoliths analyzed).

• USGS open-file report on 2008 HFE, and Trans. Am. Fish. 

Soc. And Reg. Rivers papers on HFE and non-native fish 

suppressi fl bli h d i ion flows, published or in press.

• Two manuscripts describing Fall Steady Flow effects and 

trends in habitat use in 2nd stage of review for Can. J. Fish. 

Aquat. Sci.

• Information from RTELSS used in ecosystem modelling and 

non-native fish control structured decision making process.

Acknowledgements

• Funding: Glen Canyon Dam Adaptive Management Program

• Logistics and Field Work: Dave Foster, Matt Kaplinski, Mike Yard, 

Carol Fritzinger, Arizona Game and Fish, and many others.

• Data Interpretation: Data Interpretation: T de M li e s, Mik Y d L Mike Yard, Lew C i ogg ns, St M t ll Steve Martell, 

Carl Walters, Eric Parkinson, Mike Bradford

• Otolith Microstructure: Steve Campana, Bill Pine

Considerable Variation in Early Survival Rates 

Among Weekly Cohorts in 2008 Only (flood year)

0.00

0.02

0.04

0.06

0.08

0.10

Dec Feb Apr Jun Aug

Proportion

2003

0.10 2004

0.00

0.02

0.04

0.06

0.08

0.10

Dec Feb Apr Jun Aug

2007

0.10 2008

HFE

0.00

0.02

0.04

0.06

0.08

Dec Feb Apr Jun Aug

Proportion 0.00

0.02

0.04

0.06

0.08

0.10

Dec Feb Apr Jun Aug Hatch Date

Proportion

2006

0.00

0.02

0.04

0.06

0.08

Dec Feb Apr Jun Aug

back

calculated

predicted

(flow effect)

HFE

0.00

0.02

0.04

0.06

0.08

0.10

Dec Feb Apr Jun Aug

Hatch Date

2009

Flood

Effect of 2008 Controlled Flood on Seasonal 

Variation in Early Survival Rates

0.06

0.08

0.10

rtion

relatively poor survival relatively good survival

0.00

0.02

0.04

Dec Feb Apr Jun Aug

Hatch Date

Propo

backcalculated 

from age-0 catch

predicted fom 

spawn timing

Flood HFE

Inter-annual Differences in Early Survival Rates 

Before and After March 15

<March 15 >March 15

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1

Linking whole‐river carbon cycling

to quantitative food webs in the

Colorado River

Robert O. Hall, Jr. University of Wyoming

Emma Rosi‐Marshall   Cary Inst. of Ecosystem Studies

Colden Baxter   Idaho State University

Ted Kennedy GCMRC

Wyatt Cross                                 Montana State University

Kevin Donner, Donner, Holly Wellard, Wellard,  Sarah Zahn, Kate Behn, Amber Ulseth and Dustin

Kincaid

Goal 1

Protect or improve the aquatic food base so that it 

will support viable populations of desired 

species at higher trophic levels.

Overarching Questions

1.  To what degree are fishes food limited?  Where does

the food base come from?

2.  How do patterns of carbon flow through the food web

affect fishes?

3. How do dam operations affect all of these things?

These questions require an ecosystem approach based

upon flows of energy.

To address questions we have...

1. Measured inputs, stocks, outputs, and transport of

primary production and terrestrial inputs in the

Colorado River.

2. Measured secondary production of components of food

web.

3. Identified trophic linkages to estimate what resources

support higher trophic levels.

4.  Quantified organic matter flow in the Colorado River

food web from basal resources to fishes.

Why an ecosystem approach based on energy flows?

1. Animal population dynamics depends on ecosystem

properties such as

a. Amount, source and quality of food

b. Physical template (flow,  turbidity, temperature)

c. Competition and predation with other animals

d. Interaction of the above

2. Energy flow allows a common currency from everything from  

organic matter inputs to fish production

Units:

grams organic matter

meter2 year

Energy is more or less

equivalent to organic

matter

Why is measuring production, and not

just biomass, important?

Your neighbor’s lawn

January – 1 ton

March – 1 ton

June – 1 ton

September – 1 ton

December – 1 ton

1 ton

Your Answer

3 tons

0.5 ton

0.5 ton

0.5 ton

Feb

Apr

July

Nov

0.5 ton

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2

Lees Ferry

30

Sampling regime

Seasonally‐ due to remote location

Monthly‐ needed to get an accurate

estimation of 2nd prod.

60

125 165

225

Increased trout production despite 

reduced total prey production 

following the 2008 controlled flood

In revision, Ecological Applications

Pre-flood Post-flood

Production Trout 

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3

Filamentous algae

28.3 g/m2/yr

29.8 g/m2/yr

12.9 g/m2/yr

Overall ~60% Decrease

The 2008 artificial flood stimulated production 

of key invertebrate taxa

Quantitative Food Webs

Reduced flows to invertebrates

Increased flows to trout

Midge and black fly drift increased after the flood

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4

• Increase in trout production despite a 

decrease in total invertebrate production

• The few taxa that support most trout

Summary

The few taxa that support most trout

production increased following the flood 

(both in production and drift)

• Artificial floods appear to improve 

resource conditions for non-native 

rainbow trout

Downstream Food Webs

Upstream input

Metabolism

Reaeration

An oxygen budget for a river reach

Measured empirically

Downstream export

Groundwater input

Easily measured using recording oxygen sensors

GPP PAR CRt  

Estimate metabolism by fitting below model to data.

Minimize negative log-likelihood function. 

Time 

interval

Estimating primary production parameters

Ct  Co 

GPP

zt

 PARt

PAR



CRt

zt

 KCs C0 t

Van de Bogert et al. 2007

O2 O2

saturation 

deficit

Gas 

exchange 

rate

Fraction of 

light over 

interval

Scaling gas exchange across long reaches

Towards oxygen

saturation

Colorado River has among highest rates of gas 

exchange ever measured

Draft data subject to revision. DAY 1 OF 2. 

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5

GPP = 2.6 g O2m-2 d-1

9.2

9.4

9.6

9.8

10

10.2 data

saturation concentration

model

9

18:00 00:00 06:00 12:00 18:00 00:00 06:00

Primary production varies through time

2006 2007 2008

Suspended sediment regulates variation in GPP 

4

5

6

7

0

1

2

3

0 0.5 1 1.5 2 2.5 3 3.5

Log suspended sediment concentration (mg/L)

-0 2

0

0.2

0.4

0.6

Post flood

Small effect of experimental high flows?

-1

-0.8

-0.6

-0.4

-0.2

0 50 100 150 200 250 300 350 400 Site location (km downstream)

Allochthonous material

During periods of high

turbidity, a lot of

allochthonous organic

matter also enters the

river.

This allochthonous

material may be an

important food resource.

Organic Matter Inputs to

Downstream Ecosystem

Source Annual Inputs 

(organic matter metric 

tons)

Annual Inputs

(organic matter g/m2)

Lake Powell & 

Tailwater POM / DOM

4,400 / 40,000 128 / 1167

Litter Inputs from 

Riparian Zone

500 14

Algal Production 

Downstream

2000-5000 60-150

Tributary 

Allochthonous Inputs

400,000 13,000

But low primary production relative to trib inputs does not mean

low importance to food webs!

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6

2nd production of invertebrates

in downstream reaches

For reference: Lees Ferry production ~27 g AFDMm‐2y‐1

Lees Ferry post‐flood ~ 12 g AFDMm‐2y‐1

Production attributable to autochthonous and

allochthonous resources

From Wellard, H.A. MS Thesis 2010

Production Attributed to Autochthonous 

and Allochthonous Organic Matter

%

20

40

60

80

100

Invertebrate diets versus d13C

-22

-20

Macroinvertebrate diets versus δ13C

Black flies

NZMS

KM 0

BLK

GAM

NZMS

CHIR

0

Downstream 

sites

BLK

GAM

NZMS

CHIR

Autochthonous (Diatoms + Fila. Algae)

Allochthonous (A. Detritus + Leaf Material) 

0 20 40 60 80 100

d13C -34

-32

-30

-28

-26

-24

δ13C

NZMS

Gammarus

Chironomids

January

June

September

% Diatoms in diets

0.4

0.5

0.6

0.7

0.4

0.5

0.6

0.7 Simulium Gammarus

Algae consumption by invertebrates tracks primary 

production

0

0.1

0.2

0.3

01234567

GPP (gO2 m-2 d-1)

0

0.1

0.2

0.3

01234567

Holly Wellard, unpublished

20

40

60

80

100 A

Suspended sediments influence GPP

and invertebrate diets

Terrestrial Diet

0

20 r = 0.493

p < 0.001

0

1

2

3

4

5

6

7

0 0.5 1 1.5 2 2.5 3 3.5

Log suspended sediment concentration (mg/L)

Time-Averaged Turbidity

Algal Diet

The downstream food web...

1. Base of food web varies with turbidity

2. Invertebrate production is much lower than

Lees Ferry

3. Invertebrate resource consumption tracks

primary production

4. Despite Despite huge inputs of tributary tributary‐derived derived

allochthonous material, algal production

supports ~1/2 of the downstream invertebrate

production

Brown Trout (Salmo trutta)

Humpback Chub (Gila cypha)

Rainbow Trout (Oncorhynchus mykiss)

Current Fish Assemblage Production and food base of downstream fishes

Speckled Dace (Rhynicthys osculus)

Flannelmouth Sucker (Catastomus latipinnis)

Bluehead Sucker  (Catastomus discobulus)

Fathead Minnow (Pimephales promelas)

Channel Catfish (Ictalurus puntatus)

Common Carp (Cyprinus carpio)

Red Shiner (Cyprinella lutrensis)

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7

0 7

Year 1

n (g afdm/m2/yr)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

FMS

BHS

RBT

BNT

CRP

HBC

FHM

SPD

RSH

PKF

Fish 

production is 

comparable 

across sites

Year 2

Year 2

River Mile

0 30 60 125 165 225

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Production

Year 3 on of Production

0.4

0.6

0.8

1.0 Large Fishes (TL>150mm)

Production attributable to different resources

FMS BHS HBC RBT CRP YBH BNT CCF

Proportio 0.0

0.2

0.4

Benthic organic matter 

Chironomidae 

Simuliidae 

Other invertebrates 

Fish 

Other 

n (g afdm/m2/yr) 0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Detritus 

Cladophora 

Terr. plant material 

Chironomidae 

Simuliidae 

Gammarus 

Other aq. invert. 

Terrestrial invertebrate 

Potamopyrgus 

Fish 

Other 

Year 1 Year 2

Trophic basis of fish production

River Mile

0 30 60 125 165 225

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Fish production

Year 2 Year 3

Production / Demand – Blackflies

2007

on/Demand (g AFDM/m2/yr)

0 5

1.0

1.5

2.0 2008 Production 

Demand 

*

Year 2 Year 3

River Mile

0 60 225

Productio 0.0

0.5

0 60 225

‐ Blackfly production = or < demand by fishes

‐ Resource is tracked by assemblage through space, time

Production / Demand – Midges

2007

on/Demand (g AFDM/m2/yr)

0.4

0.6

0.8

1.0

1.2

1.4

2008 Production 

Demand 

*

*

*

*

Year 2 Year 3

River Mile

0 60 225

Productio 0.0

0.2

0 60 225

‐ Midge production > or = demand by fishes

Competition—Natives vs. Non‐Natives

Schoener’s coefficient of competition

‐ Diet composition/overlap

‐ Assimilation efficiencies

Accounts for...

‐ Availability

‐ Consumption rate

> 1 = competition between groups stronger than within

< 1 = competition within groups stronger than between

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8

Competition—Natives vs Non‐natives

efficient of Competition

1

2

3

4

5

2007 

2008 

Year 2

Year 3

‐ River mile 0 would far exceed all other sites

River Mile

0 30 60 125 165 225

Co 0

1

‐ Coefficient exceeds 1 at sites with large rainbow trout populations

‐ Coefficients increased in Year 3 due to RBT increase

Findings

1. To what degree are fishes food limited?  Where does the food base come

from?

Evidence for food limitation at all sites including Lees Ferry.  In Lees

Ferry, algae forms the base of the food web.  Downstream, base of food

web varies with turbidity.

2.  How do patterns of carbon flow through the food web affect fishes?

Fish production production is most likely limited limited by a few invertebrate species invertebrate species that

constitute their preferred prey.  Diets of downstream fishes are

broader than Lees Ferry.  Competition between natives and non‐natives

likely during especially years of high RBT abundance.

3. How do dam operations affect all of these things?

The 2008 artificial flood stimulated rainbow trout production.  We have

not yet seen strong evidence of flood effects on downstream food webs

or fish production.  

Core Monitoring

CMIN 1.1.1 Determine and track the composition and biomass of 

primary producers [primary production] below Glen Canyon 

Dam in conjunction with measurements of flow, nutrients, 

water temperature, and light regime.

CMIN 1.2.1 Determine and track the composition and biomass of 

benthic invertebrates [benthic invertebrate production] below 

Glen Canyon Dam in conjunction with measurements of Glen Canyon Dam in conjunction with measurements of

flow, nutrients, water temperature, and light regime.

CMIN 1.5.1 Determine and track the composition and bio-mass 

of drift in the Colorado River in conjunction with 

measurements of flow, nutrients, water temperature, and 

light regime.

Next Steps...

1. Continuous estimates of primary production

from Lees Ferry

2. Carbon budget for Lees Ferry and downstream

3. Analyze stable isotope data to further link

animal production with base of food web

4. Synthesize downstream downstream invertebrate invertebrate

production data

5. Settle upon a suite of monitoring protocols

6. Conduct food base PEP

7. Implement core food base monitoring

FY2010 Accomplishments

2 Journal articles

3 USGS Reports

2 Masters Theses

5 Presentations to AMP committees

5 Presentations at National Meetings

Mean annual biomass of prey items (g m-2) Species Impact (y-1) = Annual consumption by trout (g m-2 y-1) 

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9

What fuels invertebrate production in

downstream reaches?

80

100

A. S.arcticum Y1

a 40

60

80

100

0

20

40

60

80

100

A. S.arcticum Y1 Y2 Y3

B. G. lacustris

Y1 Y2 Y3

n

portion

From Wellard, H.A. MS Thesis 2010

0

20

40

60

Autochthonous

resources

Allochthonous

resources

RM0 D MT D HT

RM 0

Downstream MT

Downstream HT

0

20

40

60

80

100

Site and Season

RM 0

Downstream MT

Downstream HT

RM 0

Downstream MT

Downstream HT

0

20

40

60

80

100

Percent Area

0

20

Y1 Y2 Y3

Y1 Y2 Y3

C. NZMS

D. Chironomid

Diet Proportion

Diet Prop

(high quality

resource AE= 0.4)

(low quality

resource AE= 0.1)

Flannelmouth Sucker

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

Bluehead Sucker

0.006

0.009

0.012

0.015

Rainbow Trout

Common Carp Brown Trout

Humpback Chub

0 30 60 125 165 225

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

(g AFDM/m2/yr) 0.000

0.003

Speckled Dace

0.000

0.003

0.006

0.009

0.012

0.015

Fathead Minnow

Fish

0 30 60 125 165 225

Detritus 

Cladophora 

Terr. Plant Material 

Chironomidae 

Simuliidae 

Other Aquat 

Terr Inv. 

Potamopyrgus 

Other 

Production (

Production varies by  habitat

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1

Modelling Population Dynamics of Rainbow Trout

in Lees Ferry and Marble Canyon

Josh Korman, Carl Walters, Andy Makinster,

Lew Coggins, Bill Persons, Mike Yard

Objectives of Modelling

1. Estimate the inter‐annual trend in recruitment of juveniles to the adult

populations and relate to dam operations.

2. Estimate how many trout migrate from Lees Ferry to Marble Canyon

each year and magnitude of ‘local’ recruitment in Marble Canyon.

3. Estimate the time of year when outmigration occurs and size of fish

that move.

4. Determine how well data and model can distinguish among competing

hypotheses about recruitment and outmigration dynamics.

Model Structure

(1990‐2010, monthly time

step, 2 reaches)

Recruitment

Growth, Mortality

stocking

Growth, Mortality

Lees Ferry Marble Canyon

emigration

Year and seasonal deviates

#’s Alive by Age

and Length

Predicted Catch by Length

Capture Probability‐Length

Observed Catch by Length

Effort

#’s Alive by Age

and Length

Predicted Catch by Length

Observed Catch by Length

Effort

Removals

Statistical Fitting

The Data

Lees Ferry

Marble

Canyon Control Reach Total

# of Trips 60 51 24 135

# Years with Trips 20 ('91‐'10) 17 ('91‐'10) 5 ('03‐'06, '09)

Average # Trips per Year 3.00 3.00 4.80

Average Eff t or per T ir p (Hrs) 5 90 . 6 27 . 9 11 . 6 61 .

Average Proportion Shoreline Sampled per Trip 0.14 0.04 0.45 0.21

Total Fish Captured Across Trips 59,093 15,699 12,687 87,479

Age‐0 abundance in Lees Ferry reach (‘04‐’09)

Total abundance in control reach (’03‐’06)

Size‐at‐age data from otoliths in Lees Ferry (<100 mm, ’04‐’09)

Proportion of hatchery fish in population (‘91‐’96)

Prior on extent of recruitment in MC from spawning surveys

Other Data that can be used in fitting:

Effort Distribution over Space and Time

Effort (hrs)

0-20

-15-0

Canyon Dam

• Lees Ferry has been

consistently sampled

• Marble Canyon (MC)

much less so, big hole

‘95‐’98. Most effort in

lower MC

Year

19911992199319941995199619971998199920002001200220032004200520062007200820092010

0-60

40-60

20-40

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Wi

Sp

Su

Fa

Miles Downstream from Glen 

• Must aggregate MC data

and model entire reach

as a whole

• Lots of variation in

location of sampling in

MC can lead to biases in

MC abundance trend

600

800

('000s)

LF

MC

RTELSS

Recruitment Trend from Global Model

1996

Flood?

2008

Flood

Summer

Steady

Flow?

1990 1995 2000 2005

0

200

400

Year

Recruitment 

Steadier

Flows Lower

Flows?

Flow?

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2

Outmigration: Seasonal Timing and Fish Size

2 4 6 810 12

0.0

0.2

0.4

0.6

0.8

1.0

Monthly Variation in Proportion Moving

Month

0 100 200 300 400 500

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Fork Length (mm)

Proportion Moving

1990

1991

1992

1993

1994

1995

1996

1998 1997

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

Population Trends Lees Ferry

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

0

10

20

30

40

50 Abundance (> 150 mm)

Local Recruitment * 20

Outmigrants * 4

n 1000s)

Population growth

in Marble Canyon

mostly driven by

immigration from

Lees Ferry, but note

some local

recruitment

Marble Canyon

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

0

50

100

150 Abundance (> 150 mm)

Local Recruitment * 2

LF immigrants * 2

MC Pop Size (control reach)

Year

# of Fish (i

Emigration Rate vs. Recruitment from Global Model

High emigration in

some flood and

post‐flood years 15

20

ation in Yr 't+1' ('000s)

1993

1996

1997

0 200 400 600 800 1000

0

5

10

LF Recruitment in Yr 't' ('000s)

Monthly Emigra

19901991

1992 1994

1995

1998

1999

2000

2001 2002 2003

2004 2005

2006

2007

2008

Fit to

Aggregated

Lees Ferry

Year

Catch (/hr)

Feb

May

Nov

Feb

May

Aug

Nov

Mar

May

Oct

Apr

Jul

Dec

May

Dec

Mar

Apr

Aug

Nov

Apr

Sep

Dec

Apr

Aug

Nov

May

Oct

Dec

Mar

Jun

Sep

Dec

Apr

Jun

Oct

Mar

Jun

Oct

Apr

Aug

Nov

Apr

Jul

Nov

Apr

Jun

Nov

Apr

Jun

Oct

Apr

Jul

Oct

Mar

Jul

Oct

Apr

Jul

Nov

Apr

19911992199319941995199619971998199920002001200220032004200520062007200820092010

0

100

200

300

400 Predicted

Observed

CPE by Reach Marble Canyon

Year

Catch (/hr)

Jan

Mar

MayJun

Jul

Sep

Nov

Jan

Mar

MayJul

Aug

Sep

Oct

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

JulJun

Aug

Jun

Sep

Jun

Jul

Aug

MarFeb

Apr

Apr

May

Apr

May

Apr

May

Apr

May

Mar

Sep

Feb

Mar

Mar

Apr

May

19911992199319941998199920002001200220032004200520062007200820092010

0

50

100

150

200

250

What the Model

Actually Fits to:

Catch by 10 mm

Length Class

100 200 300 400 500

0

2

4

6

8

10

12

LF-1991-Feb

ch (/hr)

100 200 300 400 500

0

2

4

6

8

10

LF-1991-May

100 200 300 400 500

0

2

4

6

8

LF-1991-Nov

100 200 300 400 500

0

1

2

3

4

5

LF-1992-Feb

100 200 300 400 500

0

1

2

3

4

5

LF-1992-May

100 200 300 400 500

0

1

2

3

4

5

6

LF-1992-Aug

100 200 300 400 500

0

1

2

3

4

5

6

7

LF-1992-Nov

100 200 300 400 500

0

1

2

3

4

5

6

LF-1993-Mar

100 200 300 400 500

0

2

4

6

8

LF-1993-May

100 200 300 400 500

0

2

4

6

8

LF-1993-Oct

100 200 300 400 500

0

2

4

6

8

10

12

14

LF-1994-Apr

100 200 300 400 500

0

2

4

6

8

10

LF-1994-Jul

Fork Length (mm)

Catc

100 200 300 400 500

0

2

4

6

8

10

LF-1994-Dec

100 200 300 400 500

0

5

10

15

LF-1995-May

100 200 300 400 500

0

5

10

15

20

LF-1995-Dec

100 200 300 400 500

0

2

4

6

8

10

12

14

LF-1996-Mar

100 200 300 400 500

0

2

4

6

8

10

12

LF-1996-Apr

100 200 300 400 500

0

2

4

6

8

10

LF-1996-Aug

100 200 300 400 500

0

2

4

6

8

10

LF-1996-Nov

100 200 300 400 500

0

2

4

6

8

LF-1997-Apr

100 200 300 400 500

0

5

10

15

20

25

30

35

LF-1997-Sep

100 200 300 400 500

0

5

10

15

20

25

LF-1997-Dec

100 200 300 400 500

0

5

10

15

20

LF-1998-Apr

100 200 300 400 500

0

5

10

15

LF-1998-Aug

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

MC-1992-Sep

ch (/hr)

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

MC-1992-Oct

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

MC-1993-Jan

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

3.0

MC-1993-Feb

100 200 300 400 500

0

1

2

3

MC-1993-Mar

100 200 300 400 500

0.0

0.5

1.0

1.5

MC-1993-Apr

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

MC-1993-May

100 200 300 400 500

0

1

2

3

4

5

6

7

MC-1993-Jun

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

MC-1993-Jul

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

MC-1993-Aug

100 200 300 400 500

0.0

0.5

1.0

1.5

MC-1993-Sep

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

3.0

MC-1993-Oct

Mysterious

appearance of

large fish in June 2000.

Likely a sampling

artefact : <1 hr effort

for all samples

between 95‐99.

Fork Length (mm)

Catc

100 200 300 400 500

0.0

0.5

1.0

1.5

MC-1993-Nov

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

3.0

MC-1994-Jul

100 200 300 400 500

0

5

10

15

MC-1998-Jun

100 200 300 400 500

0

5

10

15

MC-1998-Aug

100 200 300 400 500

0

5

10

15

MC-1999-Jun

100 200 300 400 500

0

5

10

15

MC-1999-Sep

100 200 300 400 500

0

5

10

15

MC-2000-Jun

100 200 300 400 500

0

2

4

6

8

10

12

14

MC-2000-Jul

100 200 300 400 500

0

5

10

15

20

MC-2000-Aug

100 200 300 400 500

0

2

4

6

8

10

12

MC-2001-Mar

100 200 300 400 500

0

5

10

15

MC-2002-Feb

100 200 300 400 500

0

5

10

15

MC-2002-Apr

Draft data subject to revision. DAY 1 OF 2. 

TWG review document, DO NOT CITE, reproduce, or distribute.

Date: 1/19 DRAFT DO NOT CITE. 37
1/19/2011

3

Data Not Sufficient

to Distinguish

Among Competing

Models

Lees Ferry

Catch (/hr)

19911992199319941995199619971998199920002001200220032004200520062007200820092010

0

100

200

300

400

Marble Canyon

Catch (/hr)

19911992199319941998199920002001200220032004200520062007200820092010

0

50

100

150

200

250 Global

Fixed pRec in MC

Fixed Move Size

No MC Rec

No Outmigration

Main Conclusions from Modelling

• Two major recruitment events over last two decades

– 1997, 2008. 2008 caused by HFE. Best bet is that 1997 caused by 1996 HFE

– Magnitude of 1997 event uncertain (limited MC sampling)

– Surprisingly,  little evidence of downstream movement from 2000 recruitment event

• Marble Canyon population could be supported mostly by  immigrants from Lees

Ferry, but models that allow limited and considerable recruitment in Marble

Canyon also fit the data well.

• Data are also not sufficient to distinguish among alternate models that predict

differences in seasonal timing and size at outmigration.

• FY2011 work will focus on improving calculations of uncertainty in model

predictions to provide reliable comparison of alternate models. Simulation to

evaluate future monitoring efforts.

• Large‐scale and long‐term mark‐recapture program, coupled with more

extensive sampling in Marble Canyon,  required to evaluate these dynamics and

efficacy of PBR removal program

Data Limitations

1. Inconsistent sampling in Marble Canyon

– No or very little sampling in some years

– Effort distribution among reaches in Marble Canyon very inconsistent

2. No information on size‐at‐age and how it varies among reaches

– Makes it difficult difficult to assign recruitment recruitment (birth) (birth) year for fish of a given size

– Leads to large uncertainty in assignment of recruitment and outmigration to

particular years

– This in turn makes it difficult to evaluate factors that drive recruitment and

outmigration

3. No information on relationship between vulnerability to sampling

and fish size, and variation in catchability between Lees Ferry and

Marble Canyon

Data Collection Required to Meet Information Needs

1. PIT tag ~ 25% of Lees Ferry age‐0 population in Fall each year (~15,000)

2. Recapture pit tags in PBR and in LCR Reach

– Large cost of recapture in these areas already covered by removal program

3. Recapture Recapture pit tags in Marble Canyon between between PBR and LCR

– Dedicate one AGF nonnative trip to Marble Canyon only

– This effort would be needed even in the absence of tagging to improve estimates

from model (consistent sampling in MC)

4. Conduct small‐scale mark‐recapture experiments in Lees Ferry and Marble

Canyon to define size‐dependent vulnerability functions.

5. Integrate mark‐recapture data with catches of unmarked fish into existing

model to derive reliable estimates of key population dynamic parameters

Proportion emigrating at age 1

0.1 0.25 0.5

RTELSS LF Age‐0 recaptures 201

Expected Recaptures from Each

Annual Marked Cohort

AGF LF Age‐1 recaptures 94 79 52

PBR Age‐1 recaptures 220 550 1,101

MC recaptures (not including PBR and upper

LCR) 16 39 79

LCR recaptures (upper stratum) 102 256 511

Spatial Gradient in Abundance in Marble Canyon

• 2000‐2002 and 2008‐ 2010 high abundance periods.

• Upstream‐downstream gradient in density apparent.

Catch Per Effort (#/hr)

0-20

-15-0

Canyon Dam

• Gradient is a bit variable through time, but lower MC always lower density than upper MC.

• Must adjust MC data to account for the temporal variability in location of sampling with respect to density gradient.

Year

1993199320002002200320042005200620072007200820092010

0-60

40-60

20-40

Sp Fa

Su

Sp

Sp

Sp

Sp

Sp Sp

Fa

Sp

Sp

Sp

Miles Downstream from Glen 

Draft data subject to revision. DAY 1 OF 2. 

TWG review document, DO NOT CITE, reproduce, or distribute.

Date: 1/19 DRAFT DO NOT CITE. 38
1/19/2011

4

Very Limited Recruitment Below Lees Ferry

Lees Ferry Marble Canyon

Upper LCR Reach 2000

2000

2008

Evidence for Outmigration from Lees Ferry

2009

100 200 300 400 500

0

2

4

6

8

10

12

14

LF-1998-Nov

h (/hr)

100 200 300 400 500

0

2

4

6

8

10

12

LF-1999-May

100 200 300 400 500

0

5

10

15

LF-1999-Oct

100 200 300 400 500

0

5

10

15

LF-1999-Dec

100 200 300 400 500

0

2

4

6

8

10

12

LF-2000-Mar

100 200 300 400 500

0

5

10

15

20

25

LF-2000-Jun

100 200 300 400 500

0

5

10

15

20

25

30

35

LF-2000-Sep

100 200 300 400 500

0

5

10

15

20

25

LF-2000-Dec

100 200 300 400 500

0

5

10

15

20

25

30

LF-2001-Apr

100 200 300 400 500

0

5

10

15

20

25

LF-2001-Jun

100 200 300 400 500

0

5

10

15

20

LF-2001-Oct

100 200 300 400 500

0

5

10

15

LF-2002-Mar

Fork Length (mm)

Catch

100 200 300 400 500 100 200 300 400 500 100 200 300 400 500 100 200 300 400 500

100 200 300 400 500

0

2

4

6

8

10

12

14

LF-2002-Jun

100 200 300 400 500

0

2

4

6

8

10

12

LF-2002-Oct

100 200 300 400 500

0

5

10

15

LF-2003-Apr

100 200 300 400 500

0

2

4

6

8

10

12

LF-2003-Aug

100 200 300 400 500

0

2

4

6

8

10

12

LF-2003-Nov

100 200 300 400 500

0

2

4

6

8

10

LF-2004-Apr

100 200 300 400 500

0

2

4

6

8

10

LF-2004-Jul

100 200 300 400 500

0

5

10

15

20

LF-2004-Nov

100 200 300 400 500

0

2

4

6

8

LF-2005-Apr

100 200 300 400 500

0

2

4

6

8

10

12

LF-2005-Jun

100 200 300 400 500

0

2

4

6

8

LF-2005-Nov

100 200 300 400 500

0

1

2

3

4

5

6

LF-2006-Apr

Can’t see cohort.

Emergence timing

problem:

Model does not

allow the width in

emergence timing

curve to vary among

years. Spread of

emergence timing

ll i 2007 d

100 200 300 400 500

0

2

4

6

8

LF-2006-Jun

ch (/hr)

100 200 300 400 500

0

1

2

3

4

5

6

LF-2006-Oct

100 200 300 400 500

0

1

2

3

4

5

6

LF-2007-Apr

100 200 300 400 500

0

2

4

6

8

10

12

LF-2007-Jul

100 200 300 400 500

0

2

4

6

8

10

12

LF-2007-Oct

100 200 300 400 500

0

2

4

6

8

10

LF-2008-Mar

100 200 300 400 500

0

5

10

15

20

25

LF-2008-Jul

100 200 300 400 500

0

20

40

60

80

100

LF-2008-Oct

100 200 300 400 500

0

5

10

15

20

25

LF-2009-Apr

100 200 300 400 500

0

10

20

30

40

LF-2009-Jul

100 200 300 400 500

0

5

10

15

20

25

LF-2009-Nov

100 200 300 400 500

0

5

10

15

LF-2010-Apr

smaller in 2007 and

2008 than in 2009.

Fork Length (mm)

Catc

100 200 300 400 500

0

1

2

3

4

MC-1991-Jan

100 200 300 400 500

0

2

4

6

8

10

12

MC-1991-Mar

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

MC-1991-May

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

MC-1991-Jun

100 200 300 400 500

0

1

2

3

4

MC-1991-Jul

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

MC-1991-Sep

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

MC-1991-Nov

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

MC-1992-Jan

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

3.0

MC-1992-Mar

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

3.0

MC-1992-May

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

MC-1992-Jul

100 200 300 400 500

0.0

0.5

1.0

1.5

2.0

2.5

3.0

MC-1992-Aug

100 200 300 400 500

0

5

10

15

MC-2003-Apr

ch (/hr)

100 200 300 400 500

0

2

4

6

8

10

12

MC-2003-May

100 200 300 400 500

0

2

4

6

8

MC-2004-Apr

100 200 300 400 500

0

2

4

6

8

10

MC-2004-May

100 200 300 400 500

0

2

4

6

8

MC-2005-Apr

100 200 300 400 500

0

2

4

6

8

MC-2005-May

100 200 300 400 500

0

2

4

6

8

10

MC-2006-Apr

100 200 300 400 500

0

1

2

3

4

MC-2006-May

100 200 300 400 500

0

2

4

6

MC-2007-Mar

100 200 300 400 500

0

2

4

6

8

10

MC-2007-Sep

100 200 300 400 500

0

2

4

6

8

10

MC-2008-Feb

100 200 300 400 500

0

2

4

6

8

MC-2008-Mar

Fork Length (mm)

Catc

100 200 300 400 500

0

5

10

15

MC-2009-Mar

100 200 300 400 500

0

5

10

15

20

25

MC-2010-Apr

100 200 300 400 500

0

10

20

30

40

MC-2010-May

2003‐2004:

Age 1+ present

and growing over

winter

No age 1+ fish

recruiting in 2006

The Really

Good Stuff!

100 200 300 400 500

0

2

4

6

8

Control-2003-Jan

100 200 300 400 500

0

2

4

6

8

10

Control-2003-Feb

100 200 300 400 500

0

5

10

15

Control-2003-Mar

100 200 300 400 500

0

2

4

6

8

10

Control-2004-Jan

100 200 300 400 500

0

1

2

3

4

5

6

7

Control-2004-Feb

100 200 300 400 500

0

2

4

6

8

10

12

Control-2004-Mar

ch (/hr)

100 200 300 400 500

0

1

2

3

4

5

Control-2005-Jan

100 200 300 400 500

0

1

2

3

4

5

Control-2005-Feb

100 200 300 400 500

0

1

2

3

4

5

Control-2005-Mar

100 200 300 400 500

0

2

4

6

Control-2006-Jan

100 200 300 400 500

0

1

2

3

4

5

Control-2006-Feb

100 200 300 400 500

0

2

4

6

8

10

Control-2006-Mar

2003‐2004:

Age 1+ continue to

grow and merge

into 2+ size classes

100 200 300 400 500

0

2

4

6

8

Control-2003-Jul

100 200 300 400 500

0

2

4

6

8

10

12

Control-2003-Aug

100 200 300 400 500

0

5

10

15

Control-2003-Sep

100 200 300 400 500

0

1

2

3

4

5

6

Control-2004-Jul

Fork Length (mm)

Catc

100 200 300 400 500

0

1

2

3

4

5

6

Control-2004-Aug

100 200 300 400 500

0

1

2

3

4

5

6

Control-2004-Sep

100 200 300 400 500

0

1

2

3

4

Control-2005-Jul

100 200 300 400 500

0

1

2

3

4

5

6

Control-2005-Aug

100 200 300 400 500

0

1

2

3

4

5

Control-2005-Sep

100 200 300 400 500

0

1

2

3

4

5

Control-2006-Jul

100 200 300 400 500

0

2

4

6

Control-2006-Aug

100 200 300 400 500

0

2

4

6

8

10

12

Control-2009-May

Draft data subject to revision. DAY 1 OF 2. 

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Date: 1/19 DRAFT DO NOT CITE. 39
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5

Comparison of Outmigration

Trend Across Models

 per Month (in 1000s)

15

20

25

30 Global

Fixed pRec in MC

Fixed Move Size

No MC Rec

No Outmigration

Year

Outmigrants

0

5

10

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

What outmigration

rate should be

used?

Information Needs to Evaluate Efficacy of PBR and

LCR Mechanical Removal Programs and Factors that

Drive Outmigration and Abundance at the LCR

1. Annual number of outmigrants (Lees Ferry Management)

– What drives outmigration

2. Details Details on seasonal timing seasonal timing and size of outmigrants outmigrants, and residence residence

period in PBR

– Improve efficiency of PBR removal

3. Number of escapees that make it to LCR

– Effective harvest rate of PBR removal

4. Extent of local recruitment in Marble Canyon (below PBR)

Draft data subject to revision. DAY 1 OF 2. 

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Date: 1/19 DRAFT DO NOT CITE. 40
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1

The natural history of Western Honey

Mesquite in Grand Canyon, A Changing

Ecology

• Gwendolyn Waring, Barbara Ralston, Larry

S d S h Stevens and Steven Archer

Substrate Statistic Mean #/1000 m2 Mean BD (mm) Mean #/1000 m2 Mean BD (mm)

Sandbar Mean 2.1 72.1 0.7 24.5

stdev 1.34 35.31 0.81 15.12

n 11 6 11 3

t 1.796 1.943 1.796 2.353

95% CI 0.7235 28.0116 0.4410 20.5404

Debris Fan Mean 3.9 31.2 6.6 45.6

stdev 2.77 31.10 3.67 32.61

n 16 15 18 14

t 1.746 1.753 1.734 1.761

95% CI 1.2101 14.0775 1.5015 15.3501

Channel Mean 0.1 16.9 1.4 ---

Margin stdev 0.17 18.60 2.81 ---

n 11 11 12 ---

t 1.796 1.796 1.782 ---

95% CI 0.0901 10.0705 1.4453 ---

Sandbar Mean 7.3 56.6 --- ---

Backchannel stdev 0.00 33.52 --- ---

n 1 1 --- ---

t 6.314 6.314 --- ---

95% CI 0.0000 211.6451 --- ---

Cobblebar Mean 2.3 25.8 --- ---

stdev 0.30 37.34 --- ---

n 2 2 --- ---

t 2.920 2.920 --- ---

95% CI 0.6199 77.0982 --- ---

Grand Total Mean 3.5 40.0 5.4 44.6

stdev 2.82 35.56 4.09 32.28

n 41 35 41 17

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2

Species Under Away Χ2 P

Acacia greggii 1 2 0.167 >0.5

Atriplex canescens 0 1 0.500 >0.3

Baccharis emoryi 17 14 0.145 >0.5

Baccharis salicifolia 54 28 4.122 0.031

Baccharis sarothroides 72 41 4.252 0.034

Baccharis sergiloides 0 1 0.500 >0.3

Prosopis glandulosa 11 6 0.735 >0.3

Salix exigua 12 3 5.400 0.02

Tamarix spp. 42 22 3.125 0.010

Pluchea sericea 44 17 5.975 0.021

Draft data subject to revision. DAY 1 OF 2. 

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3

Variable Depth Pre-dam terraces Post-dam terraces TOTAL

Under away under Away under away

δN 0-5 cm 3.32±0.55 1.84±1.22 1.92±0.37 1.81±0.27 2.77±0.40 1.83±0.65

5-10 cm 1.58±0.41 3.28±0.33 1.52±0.56 2.25±0.66 1.56±0.32 2.87±0.35

pooled 2.45±0.39 2.56±0.64 1.72±0.30 2.01±0.28 2.15±0.27 2.31±0.37

δC 0-5 cm -22.14±0.85 -12.68±2.9 -

12.07±2.20

-7.58±1.78 -18.1±1.6 -10.3±1.8

5-10 cm -19.88±1.49 -8.71±2.38 -

11.98±2.29

-7.84±2.69 -16.7±1.6 -8.31±1.7

pooled -21.00±0.87 -10.69±1.9 -

11.54±1.47

-8.01±1.44 -17.04±1.2 -9.40± 1.2

% N 0-5 cm 0.088±0.015 0.009±0.00

2

0.028±0.00

9

0.030±0.01

7

0.064±0.01

2

0.019±0.00

8

5-10 cm 0.100±0.032 0.003±0.00 0.032±0.00 0.013±0.00 0.073±0.02 0.008±0.00

3 6 5

7

1 3

pooled 0.094±0.017 0.006±0.00

2

0.029±0.00

5

0.021±0.00

8

0.067±0.01

2

0.013±0.00

4

% C 0-5 cm 1.043±0.171 0.263±0.09

2

0.870±0.22

6

1.297±0.67

5

0.974±0.13

3

0.740±0.33

5-10 cm 1.481±0.422 0.210±0.03

7

0.952±0.18

6

1.020±0.30

9

1.27±0.27 0.584±0.18

pooled 1.262±0.227 0.236±0.04

8

0.873±0.13

4

1.103±0.33

3

1.10±0.15 0.654±0.18

C:N 0-5 cm 12.33±0.590 48.36±20.4

4

38.52±6.52 56.08±11.0

1

22.81±4.24 51.87±11.7

3

5-10 cm 16.64±1.69 46.05±10.2

2

39.79±8.32 76.28±29.8

8

25.90±4.5 58.14±13.3

pooled 14.49±1.01 47.20±10.9

0

40.58±4.85 63.04±12.6

5

25.43±3.13 54.40±8.25

Basar Basa Plse

(N = 8) Post-dam Post-dam Post-dam Post-dam

Variabl

e

Predam (8)Postdam (8)Under 

(4)

Away 

(4)

Under 

(2)

Away 

(2)

Under 

(5)

Away 

(5)

Unde

r (1)

Away 

(1)

δ15N

0.38±0.

81

-

1.57±0.

88

-

1.69±1.

03

-

2.69±1.

93

1.43±1.

66

-

0.52±1.

75

4.45±4.

00

6.74±0.

9 7 34 2.08 1.78

δ13C -

25.8±0.

71

-

26.5±0.

57

-

26.8±3.

15

-

28.9±1.

66

-

26.2±1.

59

-

26.1±0.

41

-

27.1±0.

94

-

26.6±1.

19 -28.4 -26.9

% N 2.91±0.

17

3.10±0.

23

1.01±0.

33

0.82±0.

23

1.64±0.

41

1.55±1.

37

1.09±0.

21

1.28±0.

63 1.23 1.24

% C 48.11±1

.05

47.86±0

.49

48.69±1

.05

47.72±1

.31

46.67±0

.96

46.18±0

.30

39.96±1

.10

40.47±2

.32 46.00 47.84

C:N 16.6±0.

74

15.5±1.

07

50.0±14

.54

60.3±18

.77

28.8±6.

56

31.2±27

.74

37.6±7.

25

37.3±20

.27 37.3 38.6

Foliar Prgl Basar

Comparison

pre- vs. postdam under-away under-away

d15N 0 003 * 0.003 * 0 157 . 0 462 .

d13C 0.260 0.157 0.527

%N 0.099 1.000 0.527

%C 0.260 0.157 0.462

C:N 0.04 trend 1.000 0.527

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1

TERRESTRIAL RIPARIAN VEGETATION MONITORING

ON THE COLORADO RIVER CORRIDOR: GLEN

CANYON DAM TO LAKE MEAD

DAVID J. COOPER & JENNIFER R. JONES

DEPARTMENT OF FOREST, RANGELAND AND WATERSHED STEWARDSHIP

COLORADO STATE UNIVERSITY, FORT COLLINS, CO 80523

Statisticians: Starcevich, Schweiger, Olsen, Urquhart

MONITORING OBJECTIVE

This protocol is designed to assess status and

detect trends in terrestrial riparian resources on

the main stem of the Colorado River in the

Grand Canyon from Glen Canyon Dam to

Separation Canyon, river kilometer 0 to 411.3

Specific Core Monitoring Objectives

(2008 PEP & 2010 TWG Review)

1. Determine and track the patch number, patch

distribution, composition and area of the NHWZ,

OHWZ, and sand beach communities as measured at

5‐year or other appropriate intervals based on life

cycles of the species and rates of change for the

community. (6 2 1 . . , see USGS 2010)

2. Determine and track the distribution and abundance

of non‐native species in the Colorado River ecosystem as measured at 5‐year or other appropriate intervals

based on life cycles of the species and rates of change

for the community. (6.5.1)

3. Determine status and trends in species composition

and structure of riparian vegetation.

GCMRC Management Objectives

• Maintain

– marsh, seep, and spring communities

– NHWZ and OHWZ communities

– sand‐beach communities

– Southwestern Willow Flycatcher habitats

– & reduce non‐native species

• These objectives will be informed by trends

detected by this protocol

Survey Design • Statistical based survey designs are scientifically

defensible and cost effective for large scale

monitoring (Olsen et al. 1997)

• This design is based on a framework developed by

EPA’s EMAP (Environmental Monitoring &

Assessment Assessment Program) Program) developed developed by Olsen, Urquhart Urquhart

• Adopted by the NPS Inventory & Monitoring

Program

• Both have mandated the use of probability survey

designs (every site has a known statistical probability

of being sampled, some more habitats common than

others)

Previous Monitoring Program

– Statistical based – but no stratifications other than

vertical

– Sample sites not placed in a geomorphic context

– Plot placement based on stage elevations, and plots

not fixed, can move as stage/discharge relations

change

– Plots small

This Protocol

– Stratifies using large and local‐scale geomorphic

drivers known to influence vegetation composition

and dynamics

– Use larger permanently marked plots

– Increased sampling frequency

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2

Target Population

• All terrestrial riparian resources from river to

top of Old High Water Zone

– Shoreline features such as bars and marshes

• Sample sites must be:

– Accessible by boat

– Sampled safely

– Cause no impacts to sensitive resources, i.e. Cultural

• The sample frame is the spatially explicit portion

of the target population from which sample

sites are chosen

Survey Design

Sites were selected using a generalized random

tessellation stratified (GRTS) survey design with

sampling directed at three scales

1. Landscape‐scale geomorphic reaches

(Schmidt and Graf 1990)

2. Local‐scale debris fan eddy landforms

3. The elevation/flood frequency, water table

depth gradient within each landform

Landscape Scale Strata

Strata based on geomorphic reaches, influence

of major tributaries, and regional vegetation

GLEN CANYON

Stratum

20 sample points

(green) and 50

oversample points

(blue) in each

landscape stratum

Local Scale

(Webb and Griffith 2001)

• Landforms influence vegetation due to variance in disturbance, sediment texture,

erosion, etc.

• Ideally sample sites are selected from a discrete population of all target features

• No complete GIS layers are available for Grand Canyon that delineate ALL local scale

features from which sample sites can be selected

• Site to be inspected by GCMRC staff to assess geomorphic setting of each point

• 5 points of each landform type, selected in each stratum

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3

• GRTS provides an ordered list of spatially

balanced sites

• Sites evaluated in numbered order until the

sample size was reached for each geomorphic

feature in each stratum

• Spring 2011 field visit to verify site classification

• Site verification will include all sites in the GRTS

ordered list (20+50 in each stratum, 280 sites),

• Allows inclusion probabilities for population

estimate of each geomorphic feature to be

calculated

Panel Design

• Pure panel (Fuller 1999)

– All sites are visited in each sample period

– Simple method for estimating net change between

sample periods

• Sample every other year

• Could miss some inter‐annual variability

• No intra‐annual sampling

• N of sites limited by work that can be

accomplished in one river trip

Response Design

• Focuses on vascular plants

• Measure canopy coverage by species

• Other biota and physical variables can be added

• Detailed SOPs (Standard Operating Procedures)

sh ld ou be dl d eve oped by GCMRC st ff a t i o nsure

that data collection is standardized

• Example SOPs are in other NPS I&M protocols

Sampling

• One transect

• Orthogonal to

river

• Permanent

marker at top

of both OHWZ

• Plots 2x10 m

• 1.5 m elev.

drop (survey or laser

range finder)

Plot corners with numbered caps

Vegetation Sampling

• Canopy cover of vascular plants in each

permanent plot

• 1 m2 and 20 m2 plots

• Herbaceous species in 1 m2 plots

• Cover and height of woody plants in 20 m2 Cover and height of woody plants in 20 m plots

Suggested Metrics • Vegetation

– Species diversity

– Cover/presence of non‐native species

– National Wetland Indicator Status (NWI)

– Dominant species

• Abi i ot c

– Surface texture

– Changes in stage elevation

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4

Data Collection, Management

• Field crew training and SOPs

are essential for repeatability

• Electronic or manual data

collection

• Data management follows follows

protocol of GCMRC

• Each trip sample 80 transects,

with 5‐20 plots each

Status and Trends • Summary statistics for status after each sample period

• Population estimates including mean, variance, and

standard deviation of each metric

– Compare vegetation metrics between

– Strata (4), geomorphic feature (4), elevation zone (3‐7)

– Combinations of above

• Use data to test null hypothesis that no change has

occurred in each metric between sample periods

• Vegetation composition compared at all 3 scales using

ordination techniques

• Trend analysis should be conducted every two years  

Reference Sites

• Suggested by 2008 terrestrial PEP

• Compare GC vegetation with

• Riparian reference sites in Cataract Canyon

• Largest Largest canyon reach above Glen Canyon dam

that is relatively intact hydrologically

• Coordinate/collaborate with NPS Upper

Colorado River I&M program

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1

Grand Canyon National Park

Vegetation Ma etation Mapping Project

National Park Service

U.S. Department of the Interior

Grand Canyon National Park

E X P E R I E N C E Y O U R A M E R I C A

g pp g j

Mike Kearsley, Mark Mike Kearsley, Mark Nebel – NPS / GRCA S&RM NPS / GRCA S&RM

Kass Green Kass Green – Kass Green Associates Kass Green Associates

Overview of Presentation

 Background

 Phase 1 Methods

 Results

 Methods Changes for Phase 2

Background

 Project Motivation

 Project Scope

 GRCA

 PARA (LAKE)

 Existing Vegetation Maps

 QualitiesQualities

 Shortcomings

Background

 FGDC Standards

 National Map Accuracy Standard

 National Veg. Classification Standard

 Metadata Standard

 Taxonomy Standard

 Accuracy Assessment Requirements

 Minimum Mapping Unit

Background

 Procurement

 FedBizOpps

 Request for Qualifications

 Request for Proposals

 Commercial Fixed Commercial Fixed-Price Contract Price Contract

 Best Value Award

 Kass Green Associates (Alta Vista)

Project Phases

Phase 1

Phase 3

Phase 2

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Phase 1 Methods

 Developing the Classification Key

 NatureServe.org (NVCS) Classification

 Phase 1: 89 NVC Associations

 Overall: 164 Associations

 KGA Field Key

 25 Drafts25 Drafts

 27 Map Classes

 Model to NVC Association

Phase 1 Methods

 Example Key Rules

Phase 1 Methods

 Imagery

 ADS40 airborne ADS40 airborne digitial digitial

imagery ( imagery (Fugro Horizons for Horizons for 

NAIP) June 2007 NAIP) June 2007

 One meter spatial resolution

 Delivered as 4 band DOQQs 

 Deep shadows

 Mosaiced Mosaiced / cut into regions. / cut into regions. ADS40 IR image showing deep 

shadows in bright shadows in bright Angel Canyon

Phase 1 Methods

 Image Segmentation

 Trimble Trimble eCognition eCognition software software

 Separate Algorithms for Rim Separate Separate Algorithms Algorithms for Rim

(Above/ Below) and Shadow

 Reviewed by NPS

 Edited by KGA personnel

 Not perfect, but acceptable 

considering depth of shadow ADS40 IR image showing deep 

shadows in bright shadows in bright Angel Canyon

Example Segmentation Spectral Fidelity of the ADS40 

Imagery Allowed for Segmentation 

Even in Deep Shadows

Not perfect, Not perfect,

but pretty 

good 

considering 

the depth of 

the shadows

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3

Phase 1 Methods

 Acquire Independent Variables

 Imagery Variables

 ADS40 (incl. adaptive texture of IR)

 Landsat

 Edaphic Factors

 DEM-derived derived 

 Fire History / Intensity

 Geospatial modeling (SLAP)

Phase 1 Methods

 Calibration Data

 Digital field forms

 720 NPS points 720 NPS points

 500 KGA Segments

 Subset of points 

randomly withheld for 

accuracy assessment

Screen shot of field form running 

in ArcMap 9.3

Stratifying Samples for Use in 

CART Verses Accuracy 

Assessment

Park Service

classification plots &

observation plots

Random number

generator used to

select  sites based

on NS label

PS segments for

accuracy assessment

PS segments for

mapping Ancillary Data

Ancillary Data

Ancillary Data

Segmented 

Imagery

CART

KGA field  

collected

sample

segments

KGA office

collected

sample

segments

Random number

generator used to

select  segments

based on map key

label

KGA segments

for mapping

KGA segments for

accuracy

assessment

Vegetation 

Type Map

CART

Accuracy

Assessment

Error Matrix

Park Service plots

converted to segments

Phase 1 Methods

 CART Modeling & Editing

Imagery

Geology

Slope Position

Sample Segments

 Rules developed in See5 from samples applied to all segments 

and exported to ArcGIS to create vegetation map

Rulequest See5.0

Hydrology

Distance to Meadows

Fire History/Intensity

Etc.

Vegetation Map

Rules

Phase 1 Methods

 Preliminary Review

 KGA Field Trips

 May and June 2010

 226 additional sites visited / edited

 NPS Validation

 August 2010, draft map

 Stratified by map class, randomized

 47 sites, South 47 sites, South- and North Rims and North Rims

 72% agreement (62% SR; 91% NR)

Phase 1 Results

 Maps and data delivered

 Segments labeled to NVC Association

 Accuracy Assessment at “Map to” class

 NVC Alliances and Associations

 Below-rim to Life Form (to Phase 2) rim to Life Form (to Phase 2)

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4

Phase 1 Results

 1982 vs. 2010 maps for Phase 1 area

1982 Vegetation Map 2010 Vegetation Map

Phase 1 Results

Phase 1 Results

 Accuracy Assessment Pha se 1 Error Ma trix - All Are a s

MAP

Abies concolor - Pseudotsuga menziesii Dry Forest Alliance 81 4 1 4 4 1 2 97 84%

Abies lasiocarpa - Picea engelmannii Southern Rocky Mountain Dry Forest Alliance 3 68 3 1 75 91%

Arctostaphylos - Quercus turbinella Shrubland Alliance 9 1 10 90%

Artemisia bigelovii Shrubland Alliance 9 9 100%

Artemisia tridentata Shrubland Alliance 0 15 15 100%

Bare Land 0 3 1 4 0%

Below Rim Conifer 31 31 100%

Below Rim Deciduous Shrub 1 21 11 33 64%

Below Rim Evergreen Shrub 1 16 3 20 80%

Below Rim Pinus edulis - Juniperus spp. 1 1 35 37 95%

Ceanothus fendleri / Poa fendleriana Shrub-Steppe Shrubland 3 3 100%

Picea pungens / Carex siccata Forest 2 4 36 3 1 1 47 77%

Pinus edulis - Juniperus osteosperma / Artemisia Woodland Alliance 8 11 19 42%

Pinus edulis - Juniperus osteosperma / Cercocarpus - Quercus Woodland Alliance with evergreen shrub u 1 8 2 11 73%

Pinus edulis - Juniperus osteosperma / Grass - Forb Understory Woodland Alliance 1 15 16 94%

Pinus ponderosa / Amelanchier - Quercus Woodland Alliance 1 25 6 2 34 74%

Pinus ponderosa Forest and Woodland with Herbaceous Understory Alliance 1 12 6 19 63%

Pinus ponderosa Forest and Woodland with Shrub Understory Alliance 4 1 5 80%

Pinus ponderosa Savanna Alliance 2 1 10 20 1 84 2 120 70%

Populus tremuloides - Ceanothus fendleri / Carex spp. Shrubland 1 36 1 6 44 82%

Populus tremuloides / Carex siccata Forest 1 1 12 3 1 18 67%

Populus tremuloides / Robinia neomexicana Shrubland 2 1 3 67%

Pseudotsuga menziesii / Symphoricarpos oreophilus Forest 6 6 100%

Quercus gambelii Shrubland Alliance 1 1 26 1 29 90%

Southern Rocky Mountain Montane-Subalpine Grassland Group 1 54 55 98%

88 76 11 9 15 0 33 23 31 39 4 41 8 9 29 37 39 5 102 37 14 5 7 31 67 760

92% 89% 82% 100% 100% 0% 94% 91% 52% 90% 75% 88% 100% 89% 52% 68% 31% 80% 82% 97% 86% 40% 86% 84% 81% 81%

Accuracy Assessment Results

 Overall accuracy of 81%

 Largest source of confusion (14% of confusion) is 

between Pinus ponderosa Savanna Alliance and 

Pinus ponderosa Forest and Woodland with 

Herbaceous Understory Alliance which is confusion Herbaceous Herbaceous Understory Understory Alliance Alliance which is confusion confusion

between two different grass understory species

 Next largest source of confusion (8%) is between 

Pinus edulis Pinus edulis - Juniperus osteosperma / Artemisia Juniperus osteosperma / Artemisia 

Woodland Alliance and Pinus edulis Woodland Alliance and Pinus edulis - Juniperus Juniperus 

osteosperma / Grass osteosperma / Grass - Forb Understory Woodland Forb Understory Woodland 

Alliance. When shrub cover is sparse, as it is in the 

canyon, it is very easy to confuse shrub and grass.

Moving to Phase 2

 Changes in Methods / Emphasis

 ArcGIS 10 Image Processing

 New Field Equipment (Trimble Yuma)

 Imagery (‘05 film, WorldView2)

 Sparse vegetation = field emphasis and 

more landform / solar inputs

 Classification is complete, Field Key is 

completecomplete

Thank You

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5

Grand Canyon National Park U.S. Department of the Interior

National Park Service

CRMP Mitigation Program Summary

Since 2007:

• Completed 115 campsite and attraction site assessments (out of 234) 

along the river corridor 

• Installed multiple long-term monitoring photopoints at 36 campsites

• Completed crucial mitigation actions at 39 sites including:

 Planting

 Pruning

 Trail maintenance and re-routing

 Social trail obliteration

 Campsite delineation and obliteration

 Social trail obliteration

For 2011:

• Have 66 site re-assessments scheduled

• Have 50 new site assessments scheduled

• Have 24 crucial mitigation action sites selected and scheduled for work

Grand Canyon National Park U.S. Department of the Interior

National Park Service

Soap Creek Project

Grand Canyon National Park U.S. Department of the Interior

National Park Service

Soap Creek Project

In 2008, completed Phase I

• Collected native plant cuttings and seed

• Established new campsites near river

• Obliterated vast network of social trails

• Obliterated log constructed staircase

In 2009, completed Phase II

• Began 125 square meter campsite closure 

with active planting 

• Planted 65 native nursery and salvage plants 

• Installed 8 experimental ollas

• Began watering experiments between 

traditional berms and olla irrigation

In 2010, started Phase III

• Planted another 265 native nursery and salvage plants

• Installed 22 new ollas

• Replaced mortality from original planting and continued 

watering experiments 

Grand Canyon National Park U.S. Department of the Interior

National Park Service

November 2008 November 2010

Grand Canyon National Park U.S. Department of the Interior

National Park Service

What are the effects of campsite use on vegetation as 

a result of implementation of the 2006 CRMP? 

– First trip Spring 2007

– To date: Spring and Fall for 4 years

– 66 camps total ~ 39-41 visited each trip

Monitoring Design:

– Series of 7 panels:

CRMP Monitoring Program Summary

• Panel 1 repeats each time

• Panels 2-7 rotate every 3 years

– Campsites randomly selected representing:

• Small, medium, and large campsites

• Low, moderate, and high use

– New high water zone (35,000 cfs) – 66 transects

– Old high water zone (90,000 cfs) – 31 transects

– 50 meter transects

• Vegetation cover by species

• Substrate cover

• Vegetation structure

Year Season 1 2 3 4 5 6 7 

Total

Sites

2007 Spring 15 10 10 10 45 

Fall 15 10 10 10 45 

2008 Spring 15 10 10 10 45 

Fall 15 10 10 10 45 

2009 Spring 14 8 9 9 40 

Fall 14 9 9 9 41 

2010 Spring 14 9 9 9 41 

Fall 14 9 8 9 42 

2011 Spring 14 9 8 8 39 

Fall 14 8 8 9 39 

Year Season 1 2 3 4 5 6 7 

Total

Sites

2007 Spring 15 10 10 10 45 

Fall 15 10 10 10 45 

2008 Spring 15 10 10 10 45 

Fall 15 10 10 10 45 

2009 Spring 14 8 9 9 40 

Fall 14 9 9 9 41 

2010 Spring 14 9 9 9 41 

Fall 14 9 8 9 42 

2011 Spring 14 9 8 8 39 

Fall 14 8 8 9 39 

Grand Canyon National Park U.S. Department of the Interior

National Park Service

 Are there any detectable changes in total vegetation 

cover or structure?

 Do we see an increase in exotic plant cover?

 Does species richness remain stable?

 Is there a loss of microbiotic soils or an increase in 

bare soil or sand?

 I th h i th b f t t ?

Management Questions

Is there a change in the number of mature trees?

 How does any detectable change vary among 

campsite size and use level?

January 2011 

Revisiting protocols and presenting preliminary 

results along with recommendations for future 

monitoring and expansion below Diamond 

Creek and to attraction sites.

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6

Grand Canyon National Park U.S. Department of the Interior

National Park Service

Invasive Plant Species Management Summary

Park managers are directed to give high priority to control and management of exotic species 

that can be easily managed and have substantial impacts on the Park’s resources.

Ravenna grass – Saccharum ravennae

 Ongoing control program since early 1990s

 Manual removal of more than 30,000 plants

 Volunteer efforts have been integral to success

Pampus grass – Cortaderia selloana

 Currently manageable, but need to continue 

working with Glen Canyon to control upriver 

populations

 Need to work with local nurseries to discontinue 

 Found huge new population in 2006! stock

 Found first individuals up a side canyon in 2010

Grand Canyon National Park U.S. Department of the Interior

National Park Service

Russian olive – Elaeagnus angustifolia

 Only scattered individuals in park

 Working with Glen Canyon to remove all upriver 

trees (removed 49 in fall 2010)

 Park staff will continue to monitor all sites and 

remove any new individuals found

Sahara mustard – Brassica tournefortii

 Thrives on wind-blown sand deposits & disturbance

 Early flowering – monopolizes resources

 Found at Lees Ferry in 2003

 Removed 239,833 plants

 Coordinating efforts with Glen Canyon staff

Other Species We Focus On:

 Siberian elm (Ulmus pumila)

 Camelthorn (Alhagi maurorum)

 Russian thistle (Salsola tragus)

 Perennial pepperweed (Lepidium latifolium)

 African mustard (Malcolmia africana)

Grand Canyon National Park U.S. Department of the Interior

National Park Service

Tamarisk Management Project Summary • Tamarisk control in side canyons began in 2002

• Tamarisk removed from over 130 project areas 

using hand tools and herbicide

• 287,281 tamarisk trees removed from side 

canyons along 217 miles of river

• Over 45,000 volunteer hours ($911,250) donated

• Provided hands-on stewardship opportunities

• Botanists documented 15 new plant species

• P j t i d i t ti l iti Project received international recognition

Grand Canyon National Park U.S. Department of the Interior

National Park Service

Future Project Plans

Continue cyclic maintenance of 130+ project sites

Remove tamarisk from additional side canyons using same methodology 

(compatible with proposed wilderness setting and character)

Continue monitoring every 3-5 years

Expand project and partnerships

Set appropriate goals based on past data analysis (e.g. increasing native 

species abundance and richness)

Pro-actively, aggressively, and comprehensively prepare for 

tamarisk leaf beetle’s spread in Grand Canyon National Park!

Diorhabda carinulata

In 2009:

• completed sweep surveys at 277 sites

• found 6 larvae (RM 4.5 and RM 12)

• no adults found

• no surveys below Diamond Creek 

• no surveys between Glen Canyon Dam 

and Lees Ferry

Grand Canyon National Park U.S. Department of the Interior

National Park Service

In partnership with USGS-Biological Resources Division with support 

from Grand Canyon Association, we were able to:

• Design a simple sampling and monitoring system that utilizes a subset of the Colorado 

River Monitoring Plan sites

• Complete 6 rounds of sampling in the river corridor 

• Complete sampling in partnership with Glen Canyon NRA from Lees Ferry to Glen 

Canyon Dam

• Install temporary instruments to gather microclimate information

• Train rangers park staff and volunteers in beetle monitoring Train rangers, park staff, and volunteers in beetle monitoring

• Compile existing data sets for baseline conditions habitat conditions

• Continue partnership with Grand Canyon Youth 

Grand Canyon National Park U.S. Department of the Interior

National Park Service

The beetle moved MUCH faster than anticipated! 

Beetles are found at stock tanks near Tuweep, up side canyons (Stone Creek, 

Kanab Creek, etc), and non-continuously from Glen Canyon Dam to Diamond Creek.

Beetles are found in abundance in Glen Canyon NRA.

What Did We Find in 2010?

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Grand Canyon National Park U.S. Department of the Interior

National Park Service

By September 2010:

• there were obvious signs of defoliation for the first 30 miles and sporadically from 

river mile 138-180

• In areas where beetles were present, there was 80-95% defoliation of tamarisk 

• Beetles were more/less distributed the length of Kanab Creek

• No sign of beetles yet between Diamond Creek and Lake Mead NRA

Grand Canyon National Park U.S. Department of the Interior

National Park Service

What is GRCA’s plan for 2011 and Beyond?

Continue to sample for the tamarisk beetle in the river corridor

• Work will be completed a minimum of 3 times each summer to capture all of the 

beetle’s life phases

• Support will be provided by Grand Canyon Youth and NPS river trips

• Standard monitoring protocols will be followed

• Data will be provided to the Tamarisk Coalition and will be available to the public

• C ti t hi ith USGS Continue partnership with USGS-Bi l i l R Di i i Biological Resources Division

Prepare public outreach information and brochures

Expand partnerships with Lake Mead and Glen Canyon NRAs

Prioritize areas for active restoration with a focus on areas near 

documented southwestern willow flycatcher nesting sites

Seek funding for post-beetle site restoration

Continue seed collection & plant propagation for active restoration 

in the Colorado River corridor

Grand Canyon National Park U.S. Department of the Interior

National Park Service Grand Canyon National Park U.S. Department of the InteriorNational Park Service

Tamarisk Leaf Beetle Background

• Identified in 1992 as a potential biological control agent

• Extensive testing completed by USDA Animal and Plant Health Inspection 

Service (APHIS)

• Highly specialized on tamarisk

• First beetles released in 2001; by 2006 populations were released in 6 states

• There have been no approved active releases in Arizona and there is a 

current ban on releases on NPS lands current ban on releases on NPS lands

Adult females lay 

up to 500 eggs

Larvae emerge 

from eggs – live 

27 days (3 stages 

or instars)

Final instar 

pupates into 

cocoon

Adults emerge 

from cocoon

Adults copulate

Genetic work in 2009 changed the 

name from Diorhabda elongata to 

Diorhabda carinulata – the species 

found in GRCA

Draft data subject to revision. DAY 1 OF 2. 

TWG review document, DO NOT CITE, reproduce, or distribute.

Date: 1/19 DRAFT DO NOT CITE. 54