Columbia River Flows, Salmon, and Columbia River Flows, Salmon, and - - PowerPoint PPT Presentation

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Columbia River Flows, Salmon, and Columbia River Flows, Salmon, and - - PowerPoint PPT Presentation

Jun 03, 2023 121 likes •500 views

Columbia River Flows, Salmon, and Columbia River Flows, Salmon, and O Ocean Conditions Ocean Conditions O C C diti diti Kurt L. Fresh Kurt L. Fresh NOAA Fisheries, NWFSC NOAA Fisheries, NWFSC NOAA Fisheries, NWFSC NOAA Fisheries, NWFSC

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SLIDE 1

Columbia River Flows, Salmon, and Columbia River Flows, Salmon, and O C diti O C diti Ocean Conditions Ocean Conditions

Kurt L. Fresh Kurt L. Fresh NOAA Fisheries, NWFSC NOAA Fisheries, NWFSC NOAA Fisheries, NWFSC NOAA Fisheries, NWFSC Funding Support Primarily From BPA and NOAA

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Why Study Salmon in the Ocean? H i h R l d M i Ri ? How is that Related to Managing Rivers?

  • Understand the role of ocean conditions on

U de sta d t e o e o ocea co d t o s o growth and survival of Columbia River salmon.

– Provide the context for recovery actions in the Basin. – Determine the relative roles of hydrosystem, freshwater and marine factors on salmon survival in the Columbia River Basin the Columbia River Basin.

  • Support the FCRPS, BIOP.
  • Provide information that can be used in adaptive

Provide information that can be used in adaptive management of fish and the hydrosystem in the Columbia River Basin.

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SLIDE 3

Ocean survival vs a s mmar metri

Snake River Salmon

SAR (Smolt to Adult) (survival from LGR to LGR) versus: In‐river survival

(LGR to BON)

Ocean survival

(BON to BON)

a summary metric

  • f ocean conditions

Hatchery Spring Chinook

R)

  • BON)

Wild Steelhead

Survival (SAR vival (BON to Total S Ocean Surv

Hatchery Steelhead

Survival data include 2000‐2009 and come from: http://www.cbr.washington.edu/trends/index.php

In‐river Survival Ocean Survival Ocean Indicator *

* This metric is a combination of food resources and other physical and biological conditions in the ocean

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SLIDE 4

Why Study Salmon in the Ocean?

1. Absolute survival in all life stages is important for conservation and recovery

  • In‐river survival may not contribute much to forecasts,

but 50% in‐river survival still reduces returns by 50%

  • Upstream of Lower Granite Dam (LGR): adult survival and

f l l h hl bl d h egg‐fry‐smolt survival are highly variable and have a strong influence on population dynamics 2. Variability in survival is important for forecasting

  • Most of the variability in SAR (survival from LGR to LGR)
  • Most of the variability in SAR (survival from LGR to LGR)

comes from variability in the ocean

  • In‐river variability is more important for steelhead than

for Chinook salmon for Chinook salmon

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SLIDE 5
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SLIDE 6
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SLIDE 7

HOW TO BE A SALMON HOW TO BE A SALMON Variations on a Theme

  • Differences between species (7).
  • Differences within species between groups of

Differences within species between groups of individuals‐ populations (dozens)

– A more or less discrete breeding group of salmon.

  • Spawning location

Spawning location

  • Body size and age at maturity.
  • Timing of life history events
  • Differences between individuals within a

population

– Life history type.

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SLIDE 8

The Ocean Program The Ocean Program

  • BPA Funding

BPA Funding

– NOAA + OSU, OHSU, UW: 1998 to present Canada DFO 1999 to 2012 (phasing out) – Canada DFO, 1999 to 2012 (phasing out) – Kintama, 2005‐2011

Oth F di

  • Other Funding

– NOAA

  • In kind (salary, equipment)
  • Other sampling platforms.
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SLIDE 9

Sampling methods

  • Juvenile salmon with

surface trawl: sometimes with a small mesh liner

  • Plankton nets
  • Other: buckets, CTDs
  • Acoustics
  • Bird and marine mammal
  • bservations
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SLIDE 10
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SLIDE 11

48° N

Sampling Design

48 N

La Push Queets River

Washington

  • Newport Line biweekly
  • ceanographic and

47° N

Grays Harbor Will B

g p plankton sampling since 1996 (17th year)

46° N

Willapa Bay Columbia River

  • Juvenile salmon sampling

in May June and

Cape Meares Cape Falcon

Oregon

in May, June and September since 1998 (15th year)

45° N

Cascade Head

Newport

(15th year)

126° W 125° W 124° W 123° W

^ _

Cape Perpetua

Newport

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SLIDE 12

What We Have Learned What We Have Learned

  • Learned a lot about salmon in the ocean

Learned a lot about salmon in the ocean. Some highlights.

  • We can use our science to help identify ways
  • We can use our science to help identify ways

that we can affect salmon performance (growth/survival) during early ocean life (growth/survival) during early ocean life (adaptive management) I j l h f h

  • Its not just salmon; there are uses of other

data from the ocean project.

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SLIDE 13

Conceptual Model

H2

Salmon

H1 H3: Plume Structure H3: Plume Structure H4: Hydropower System H5: Freshwater vs. Ocean Survival H5: Freshwater vs. Ocean Survival

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SLIDE 14

What Have We Learned: Some Highlights

The First Several Months at Sea Are Critical to Many Columbia y River Salmon Stocks An Example: Early Ocean Growth is Early Ocean Growth is Critical to Survival of Yearling Stocks

  • f Chinook Salmon
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SLIDE 15

Variability Between and Within Stocks i H h R d O in How they Respond to Ocean Conditions

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SLIDE 16

Spatial distribution is stock‐specific stock specific

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SLIDE 17

Snake River Sub‐yearling Fall Chinook Snake River Yearling Spring Chinook

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SLIDE 18

We Can Use Our Science We Can Use Our Science

  • We can use our understanding of how the

We can use our understanding of how the

  • cean influences juvenile salmon to:

– Affect the environment or habitats the fish – Affect the environment or habitats the fish

  • ccupy.

– Affect the fish Affect the fish – Predict or forecast how fish will respond to ocean conditions. conditions.

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SLIDE 19

Fl E di O Vi Flow‐ Expanding Our View

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SLIDE 20

Flow ‐ The Plume

F h t f th C l bi Ri i i ith th Freshwater from the Columbia River mixing with the ocean

  • River water

di h d discharged into coastal

  • cean every

WA

  • utgoing tide
  • Freshwater

pool pool propagates

  • ffshore

OR Synthetic aperture radar image, July 2003

Courtesy D. Jay, Portland State University

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SLIDE 21

Three marine regions of the plume

Far field plume days Near field plume‐ hours y Recirculating plume Hours to days

Photo off North Head Lighthouse, looking west

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SLIDE 22

Plume is not Simply Local and Focused Near the Mouth of the River Near the Mouth of the River

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SLIDE 23

Columbia River Plume

8‐day Composites : May 1999 day Composites : May 1999

The Plume is Dynamic in Space and Time The Plume is Dynamic in Space and Time

y p y y p y

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SLIDE 24

Plume Affects Growth and Adult Returns

Snake River spring Chinook

‐2 yr) eturns (‐

Mid‐upper Columbia River spring Chinook

Adult re

pp p g from Tomaro et al. 2012 and

  • J. Miller et al. (In prep.)
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SLIDE 25

Predators

ALTERNATIVE PREY ABUNDANT NOT

Plume can Affect

Forage Fish Abundant NOT Juvenile Salmon

Avian Predation

Percent Eaten by Predators Percent Eaten by Predators

Low Salinity Large Plume

ALTERNATIVE PREY ABUNDANT IS

Predators

Forage Fish Abundant ARE Juvenile Salmon

Percent Eaten by Predators

High Salinity S ll Pl

Predators

Percent Eaten

Small Plume

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SLIDE 26

We Affect Attributes of the Plume We Affect Attributes of the Plume

  • About 44% of variability in plume

volume is explained by Bonneville river discharge. Coastal winds explains ~30% of the plume b l variability

  • We can predict features of the

plume in advance. – Weeks to years. – Due to climate change, restoration.

From Antonio Baptitsta, OHSU

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SLIDE 27

River flow Total fish abundance Caspian tern predation

l i i

p p

  • n salmon

Flow is Important in The Estuary

www.birdresearchnw.org

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SLIDE 28

We Can Affect the Fish

  • We can manipulate

We can manipulate

– Time, size, abundance of hatchery fish being released released. – How hatchery and wild fish move downstream and how fast they get to the ocean: flow/spill, and how fast they get to the ocean: flow/spill, barging

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SLIDE 29

Interannual variation in timing of marine entry Snake River Mid‐upper Columbia River

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SLIDE 30

Forecasting Forecasting

  • Adaptive management When should we be

Adaptive management. When should we be concerned about low returns and what can we do about it do about it.

  • Harvest.

H h

  • Hatchery management.
  • Life cycle modeling and early warning

indicators.

  • Understanding ocean ecology of salmon.

g gy

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SLIDE 31

Develop Forecasting Models‐ First Generation

Ecosystem Indicators 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

PDO (December-March)

14 6 3 10 7 15 9 13 11 8 5 1 12 4 2

PDO (May-September)

9 4 6 5 10 14 13 15 11 12 2 8 7 3 1

ONI Jan-June

15 1 1 6 11 12 10 13 7 9 3 8 14 4 5

46050 SST (May-Sept)

13 8 3 4 1 7 15 12 5 14 2 9 6 10 11

NH 05 Upper 20 m T winter prior (Nov-Mar)

15 9 6 8 5 12 13 10 11 4 1 7 14 3 2

NH 05 Upper 20 m T (May-Sept)

13 10 12 4 1 3 15 14 7 8 2 5 11 9 6

NH 05 Deep Temperature

15 4 8 3 1 11 12 13 14 5 2 10 9 6 7

NH 05 Deep Salinity

15 3 6 2 5 13 14 9 7 1 4 11 12 8 10

Copepod Richness Anomaly

15 2 1 6 5 11 10 14 12 9 7 8 13 3 4

  • N. Copepod Biomass Anomaly

14 10 6 7 4 13 12 15 11 9 3 8 5 1 2

  • S. Copepod Biomass Anomaly

15 3 5 4 2 10 12 14 11 9 1 7 13 8 6

Biological Transition

14 10 6 5 7 13 9 15 12 2 1 4 11 3 8

Winter Ichthyoplankton

15 7 2 4 5 14 13 9 12 11 1 8 3 10 6

Chinook Juv Catches (June)

14 3 4 12 8 10 13 15 9 7 1 5 6 11 2

Coho Juv Catches (Sept)

11 2 1 4 3 6 12 14 8 9 7 15 13 5 10

Mean of Ranks

13.8 5.5 4.7 5.6 5.0 10.9 12.1 13.0 9.9 7.8 2.8 7.6 9.9 5.9 5.5

RANK of the Mean Rank

15 4 2 6 3 12 13 14 10 9 1 8 11 7 4

Principle Component Scores (PC1)

6.56

  • 2.22
  • 2.95
  • 1.60
  • 2.12 2.08 3.12

4.21 1.10 -0.30 -4.39 -0.91 1.13 -1.76 -1.96

Principle Component Scores (PC2)

  • 0.51

0.04

  • 0.24
  • 0.76
  • 1.96 -1.53 2.55 -0.43 -0.66

1.07 -0.50 0.96 -0.74 1.36 1.35

Ecosystem Indicators not included in the mean of ranks or statistical analyses Physical Spring Trans (UI Based)

3 6 14 12 4 9 11 15 9 1 5 2 7 8 13

Upwelling Anomaly (Apr-May)

7 1 13 3 6 10 9 15 7 2 4 5 11 13 11

Length of Upwelling Season (UI Based)

6 2 14 9 1 10 8 15 5 3 7 3 11 13 11

g p g ( )

6 9 8 5 5 3 3 3

NH 05 SST (May-Sept)

10 6 5 4 1 3 15 13 8 12 2 14 9 7 11

Copepod Community Structure

15 3 5 7 2 12 11 14 13 8 1 6 10 9 4

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SLIDE 32

C t t B ill

( l h )

2

Spring Chinook Salmon Adult Returns

Counts at Bonneville (plus harvest)

R2 = 0.81

  • Oceanic Nĩno Index
  • Pacific Decadal Oscillation

L l fi h i iti 2013= 221,000

  • Larval fish species composition

Actual= 113,000 Actual= 113,000

Counts at Ice Harbor

R2 = 0.82

  • Copepod species richness
  • Copepod species composition

2013= 97 000

  • Timing of biological transition

97,000

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SLIDE 33

Spring Chinook Salmon Adult Returns Spring Chinook Salmon Adult Returns

Counts at Priest Rapids Dam

R2 = 0.69

  • Pacific Decadal Oscillation
  • Larval fish biomass
  • Larval fish species composition

2013= 20,000

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SLIDE 34

Adaptive Management: In Season Forecasting

Early Warning System

More salmon survive when there are more winter fish larvae (for example: sand lance, smelts, rockfish, anchovies)

  • Estimates of winter fish larvae biomass can be made as early as April

350000

  • Estimates of winter fish larvae biomass can be made as early as April

Bonnevile Dam rs

250000 300000 350000 2000 2001 2002

R2 =70.7%; p = 0.0007

dult returns to B 5/31 lag 2 year

150000 200000 2003 2004 2005 2006 2007 2008

ing Chinook ad 3/15-

50000 100000 2009 2010

Winter ichthyoplankton biomass of salmon prey (log C mg/m3)

  • 2.6
  • 2.4
  • 2.2
  • 2.0
  • 1.8
  • 1.6
  • 1.4
  • 1.2
  • 1.0

Spr

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SLIDE 35

Climate Change and The Ocean Program Climate Change and The Ocean Program

Evidence of climate change that we are already Evidence of climate change that we are already seeing:

  • Increased variability of the PDO (since 1998, changes in sign

y ( , g g every 5 years rather than every 20‐30 years as seen in the past). U lli i th th C lif i C t i t ti l t

  • Upwelling in the northern California Current is starting later

and the length of the upwelling season is shorter.

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SLIDE 36

10 15 20

Pacific Decadal Oscillation

s PDO

10

  • 5

5 10

Spring Chinook Salmon 123,131 average count

r of adults pawn

300000 400000 1970 1980 1990 2000 2010

  • 15
  • 10
  • f numbe

rning to s

  • 100000

100000 200000

Ad l S i Chi k B ill i

1970 1980 1990 2000 2010

Anomaly retu

  • 200000

100000

Adult Spring Chinook at Bonneville continue to track the PDO although the recent highly negative (and near record values) of the PDO have not resulted in record returns of Chinook -- recall that d i 2001 d 2002 record returns were seen in 2001 and 2002.

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SLIDE 37

Credits: NOAA Bill Peterson Bob Emmett Ric Brode r NOAA‐‐‐Bill Peterson, Bob Emmett, Ric Brodeur, Kym Jacobson, Jen Zamon, Curtis Roegner, Brian Beckman, Tom Wainwright, David Teel, Brian Burke, Laurie Tom Wainwright, David Teel, Brian Burke, Laurie Weitkamp, and others Non‐ NOAA: Antonio Baptista, Jessica Miller, John Horne, Cheryl Morgan Elizabeth Daly, and many others