collaborative adaptive management team (camt...

Collaborative Adaptive Management Team (CAMT) Investigations: Using New Modeling Approaches to Understand Delta Smelt State Salvage Patterns at the State Water Project and Central Valley Project

Lenny Grimaldo, PhD (ICF)Matt Nobriga (USFWS)William Smith (USFWS)

2016 Bay-Delta Science Conference

Disclaimer

The viewpoints expressed today are those of the authors and do not necessarily reflect the opinions of the U.S. Department of the Interior or the U.S. Fish and Wildlife Service

The Bigger PictureFactors affecting

Entrainment

FWSRPA 1 Existing Management Framework

L~ OMR

Population consequences

Assessment of Impacts

Proposal I Proposal II Proposal Ill Proposal IV

Scoping Team Review

Elevate to CAMT

The Bigger Picture

Why revisit the salvage data?

2008 USFWS Biological Opinion

Previous research did not consider:

1. Finer-scale variability of salvage dynamics (i.e., what drives salvage during first flush periods)

2. Other potentially important predictor variables (e.g., predators, water temperature, etc)

3. Fish behavior during first flush events

4. Population-level impacts (i.e., salvage scaled to previous FMWT abundance)

New conceptual models

DRIVERSWinter Storms

DRIVERS Freshet EventSeasonal Trigger

PHYSICAL RESPONSES

OMR & SJR Flows

Turbidity Distribution

SPECIES RESPONSES

Smelt Dispersal

SPECIES RESPONSES

Prey Availability

Density of Smelt in the South Delta

MANAGEMENT ACTIONS

Operation of Cross Channel

GatesPumping

CONSEQUENCESSalvage &

Entrainment

Conceptual Model for Factors Affecting Entrainment of Adult Delta Smelt at Water Projects Facilities

via Scott Hamilton

2015 CAMT Progress Report

Delta smelt movements during first flush

San Francisco Bay

SacramentoRiver

Suisun Bay

San Joaquin River

Napa River

Sommer et al. 2011

SWPCVP

3.6 km/day

Migration vs diffuse dispersal?


San Francisco Bay

SacramentoRiver

Suisun Bay

San Joaquin River

Napa River

Murphy and Hamilton 2013

SWPCVP

3.6 km/day



San Francisco Bay

SacramentoRiver

Suisun Bay

San Joaquin River

Napa River

Murphy and Hamilton 2013

SWPCVP

3.6 km/day


Both models support turbidity bridge CM

Delta Smelt likely employ a combination of unidirectional and diffuse movements during winter storms

2006

80000

60000

40000

20000

400000

300000

200000

100000

0

120967248241

5000

0

-5000

-10000

120967248241

40

30

20

10

0

SAC

Days since Decemeber 1 st

OUT

OMR Total Salvagecfs

2006

80000

60000

40000

20000

400000

300000

200000

100000

0

120967248241

5000

0

-5000

-10000

120967248241

40

30

20

10

0

SAC

Days since Decemeber 1 st

OUT

OMR Total Salvagecfs

Behaviors are complicated! Stay for Ed’s talk

Delta Smelt likely employ a combination of unidirectional and diffuse movements during winter storms

Figure 6, Grimaldo et al. 2009

First flush storms historically led to high Delta Smelt salvage250 ........,l9"'!)~3-------------~ 3 _.._ Salvuge

200

150

100

50

J211f U

IJJ7 mJ/s I

-. ,' ,..""

o ~----~----~~~-4oo ~------------~~--------------~

1996 /• 300

1 \ Y IJIII

J

~ :wo I ' 611mVs \ ~

:w:l ..... .., 100 ;:...

:"l bJ)

.s 0 >

0 5 120

-:;I

00 100 -~ t':l

XO > -;:; 60 rn

"a i5

40 !- 20

0

500

400

300

200

100

0

2(100 I 2 mu 70 7 nd/.s

11

*'

61 () I 12 1

2 -- Outnow •••••• Turbidily

0

- I

-2 J

2 0 ~

:a 0

Ul OJ)

t: 11.1 > t':l

~ ~

0 ::I 0.

-i -I = .....

~

.5 > 0

E ~

X ....... ~

0"

-2 0: -<

4 ,... ;a

) "" ::1 ~ i»

2 2.. t':l > -;;

~· c.. ....... rn

0 r:i 0

- I !-

-2

3

2

u

- I

-2

250

200

150

100

50

0

- I

o ~ .. ~~~----~~~-----~ -2 500 4

400

300

200

100

I')

600

50[)

401)

300

2:00

IOU

0 250

200

150

100

50

j}

l l 6 .1 91 121

3 0 = 2 5 9 < :>.>

0 i5.. -1:: - I &

c.: ? -· - ---...:

) ~ "' 2 ;::; 0. ~ a r::; · 0

0 = -1

-2

4

3

2

0

- I

-l -3

Salvage can be over or nearly over before population estimates are confidently assessed from the Spring Kodiak Trawl

Figure 11, Kimmerer 2008

First flush storms historically led to high Delta Smelt salvage

Too few fish caught in fall nowadays to provide reliable adult abundance estimates, especially using the FMWT net (SKT gear better net)


0

200

400

600

800

1000

1200

1400

1967

1969

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

2013

2015

711


Too few fish caught in fall nowadays to provide reliable adult abundance estimates, especially using the FMWT net (SKT gear better net)


0

200

400

600

800

1000

1200

1400

1967

1969

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

2013

2015

711

Why not use the SKT starting in September?


Figure 11, Kimmerer 2008 Source: Matsuishi 2014

Could potentially allow for salvage (losses) to be evaluated in context of recruit-per-spawner models


Revised analyses-Focus on conditions that explain salvage during first flush

12010896847260483624121

5000

4000

3000

2000

1000

0

Days since December 1st

Cum

ulat

ive

salv

age

1992-1993

12010896847260483624121

5000

4000

3000

2000

1000

0

Days since December 1st

Cum

ulat

ive

salv

age 50th percentile

25th percentile

• GLM negative binomial models

• GAM

• Boosted Regression Trees -describe response surface-rather than one best model, average over MANY poorly fitting models-method to sort through MANY potential variables-interactions are automatically included-stepped predictions identify thresholds between high and low risk conditions

Revised analyses-Focus on conditions that explain salvage during first flush

Variables considered- Old and New

4000

020

000

0 40000

0

2000

00

0 10000

5000

0 10000

5000

0 30000

1500

00 806040 16

0800 16128 100

050

00 50

02500

160000800000100000500000400000200000010000500001600080000400002000008060401608001612810005000

SAC

SJR

TOT

SWP

EXPORT

OMR

X2

CCF NTU

Mallard Wat. Temp

Vernalis SSC

Freeport SSC

Also, predators at SWP and CVP

GLM Negative Binomial Model Summary

Model Run

Exports OMR Water Temp

VernalisSSC

Freeport SSC

CCF NTU Outflow PFMWT Bestmodel r-square

25th X X X 0.52

50th X X X 0.54

Annual X X X X 0.65

OMR flow (cfs)

Clift

on C

ourt

Tur

bidi

ty (N

TU)

1 000050000-5000-1 0000

1 40

1 20

1 00

80

60

40

20

> – – – – < 25

25 5050 7575 1 00

1 00 1 251 25

CVPSWP and

Adult Delta Smelt Salvage (1993-2014)

SWP and CVP Exports (cfs)

Clift

on C

ourt

Tur

bidi

ty (c

fs)

1 40001 20001 00008000600040002000

1 40

1 20

1 00

80

60

40

20

> – – – – < 1 0

1 0 2020 3030 4040 50

50

CVSWP and

CombinedSmeltDelta

Adult Delta Smelt Salvage (1993-2014)- 25 Percentile

Boosted Regression Tree Results

Physical PC rotations Relative influence (Rank) full 25th 50th

PCl PC2 PC3 PC4 Variable dataset percentile percentile interpretation Outflow PRJEXP.OMR.SSC CCC.NBAQ.X2 MISDIV

lambda 4.59 1.98 1.31 1.00 Phy.PC.PRJEXP.OMR.SSC 0.28 (1) 0.24 (1) 0.29 ( 1)

l:umulative varian~.:e explained 0.38 0.55 0.66 0.74 FMWT 0.20 (2) 0. 19 (3) 0.23 (2)

Bio.PC.Bull.Pminn 0.13 (3) 0.19 (2) 0.12 (4) Freeport. SSC Phy.PC. CCC.NBAQJC2 0. 10 (4) 0.05 (6) 0.14 (3) Vernalis. SSC

Spawn. day 0.05 (5) 0.08 (4) 0.04 (7) CCC

PRJEXP -o1Q8 -Dl'l Bio.PC .. SWPS:MB.CVPcrappie 0.05 (6) 0.05 (7) 0.05 (5)

NBAQ 4UO Phy.PC.MISDIV 0.03 (7) 0.03 ( 10) 0.04 (6) PREC Bio.PC.CVPpminnS:MB. SWPcrappie 0.03 (8) 0.01 (13) 0.02 (10) MISDV Bio.PC .. CVPL:MBcrappie 0.03 (9) 0.03 (8) 0.01 (11) WEST

RIO ..QJJD Phy.PC.Outflow 0.03 (10) 0.02 (11) 0.02 (9)

OUT ~ Mallard. Temp 0.03 ( 11) 0.07 (5) 0.03 (8)

O::viR ~02 Bio.PC.Blackbass.Pminn 0.03 (12) 0.03 (9) 0.01 (13) X2 ~ Bio.PC.CVPbullCHN.SWPbass 0.02 (13) 0.02 (12) 0.01 (12)

Small differences between facilities but same story

AIC 5 units lower than base model

AIC 2 units lower than base model



PHYSICAL RESPONSES

OMR & SJR Flows


SPECIES RESPONSES

Smelt Dispersal

SPECIES RESPONSES

Prey Availability


MANAGEMENT ACTIONS


GatesPumping


Entrainment


ExportsOutflow Suspended sediment/Turbidity

Conceptual Model Review

Predation

Conceptual Model Review

Some questions best answered by other approaches-Hydrodynamic models-Tagged fish releases-Predator studies



PHYSICAL RESPONSES

OMR & SJR Flows


SPECIES RESPONSES

Smelt Dispersal

SPECIES RESPONSES

Prey Availability


MANAGEMENT ACTIONS


GatesPumping


Entrainment


ExportsOutflow Suspended sediment/Turbidity

Predation

CCF NTU

Delta more complex than can be gleamed from single stations

Seriously, stay for the next talk

Acknowledgements

Funding SourcesSFCWA (Proposal Development)DWR and Reclamation

Delta Smelt Scoping Team (led by Steve Culberson and Scott Hamilton)Investigator Team (Ed Gross, Pete Smith, Rob Latour, Michael MacWilliams, Josh Korman) Bruce DiGennaroJason HassrickLeAnne RojasJillian BurnsAndrew KalmbachTara Morgan KingJennifer SibillaJames GleimDean Messer

Broad recognition that ecosystem-based management is preferred to single-species management

Gable FJ. 2005. A large marine ecosystem voluntary environmental management system approach to fisheries practices.

Ecosystem management focuses on:

-Functions of the environment

-Species communities rather than individual species

-Responses in terms of growth and survival rates, not numbers of fish per se

collaborative adaptive management team (camt...

Documents