Assessing oyster population recovery in Chesapeake Bay: Management from a food-web perspective

Assessing oyster population recovery Assessing oyster population recovery in Chesapeake Bay: Management from in Chesapeake Bay: Management from

a food-web perspective.a food-web perspective.

Richard S. FulfordRichard S. Fulford

Denise BreitburgDenise Breitburg Roger NewellRoger Newell

Mike KempMike Kemp Mark LuckenbachMark Luckenbach

Place holder for GCRL

Place holder for VIMS

TroSim-CASMTroSim-CASM Modeling approach Modeling approach

Chesapeake Bay Trophic Simulation Model Chesapeake Bay Trophic Simulation Model (TroSim) (TroSim)

Multi-species bioenergetic modelMulti-species bioenergetic modelBased on CASM Model frameworkBased on CASM Model frameworkDynamic network modelDynamic network modelDaily time-stepDaily time-step

Model single years to view seasonal patterns Model single years to view seasonal patterns

ijiiiijij

jj i

jjijii

i PRpUMtempRwBBBawtempfC

Bt

B,,

,, )(****)(max*

*

Modeling ConsumptionModeling Consumption

CCmaxmax – Maximum Consumption Rate (g/g/d) – Maximum Consumption Rate (g/g/d)

wwi,ji,j – Preference of consumer i for prey j – Preference of consumer i for prey j

aai,j i,j – assimilation efficiency of consumer i – assimilation efficiency of consumer i

eating prey jeating prey j

ff(t) – temperature adjustment of consumption(t) – temperature adjustment of consumption

Consumption follows seasonal patterns in Consumption follows seasonal patterns in both composition and rateboth composition and rate

Modeling Energetic Costs and Modeling Energetic Costs and MortalityMortality

RRmaxmax – maximum respiratory costs (g/g/d) – maximum respiratory costs (g/g/d)

U – Excretory lossesU – Excretory losses

SDA – Costs of consumptionSDA – Costs of consumption

ff(t) – Temperature adjustment of respiration(t) – Temperature adjustment of respiration

rsp(i,t) – Consumer and season specific rsp(i,t) – Consumer and season specific costs of egg productioncosts of egg production

m(i) – Consumer specific natural mortalitym(i) – Consumer specific natural mortality

Model GroupsModel Groups6 producer groups (phytoplankton by size)6 producer groups (phytoplankton by size)

< 2 um, 2-4 um,. 4-10 um, 10-50 um, 50-100 um, > 100 < 2 um, 2-4 um,. 4-10 um, 10-50 um, 50-100 um, > 100 umum

14 Consumer groups in seven categories14 Consumer groups in seven categorieszooplankton, gelatinous zooplankton, pelagic bacteria, zooplankton, gelatinous zooplankton, pelagic bacteria,

pelagic forage fish, benthic invertebrates, benthic pelagic forage fish, benthic invertebrates, benthic bacteria, benthic omnivorous fishesbacteria, benthic omnivorous fishes

3 larval sub-pools3 larval sub-poolsbay anchovy, ctenophores, oystersbay anchovy, ctenophores, oysters

Detritus and nutrient poolsDetritus and nutrient pools

Data SourcesData SourcesTrophic Group Parameters Validation Data/initial biomass

Phytoplankton COASTES, Sellner, Gallegos CBMP

Copepods Kiroboe, Bundy, Kimmel CBMP

Microzooplankton Kiroboe, Bundy, Heinbokel CBMP

Ctenophores Kremer, Reeve, Grove CBMP

Sea Nettles Purcell, Larson, Hansson Purcell 1994

Pelagic bacteria S. Bartell C. GilmourC. Gilmour

Bay Anchovy Luo and Brandt 1993 Wang and Houde, Jung and Houde

Menhaden Rippetoe 1993 J. Uphoff MDNR (ECOPATH)

Onreef inverts Hagy 2000, Dauer Luckenbach, Harding

Offreef inverts Hagy 2000, Dauer CBMP

Oysters R. Newell R. Mann, Jordan et al. 2002

Reef associated fish Rogers, Healey Breitburg, Abbe

Non-reef associated fish Fishbase, Moser and Hettler Jung and Houde 2000 rel. to anchovy

Benthic bacteria S. Bartell C. GilmourC. Gilmour

Project ObjectivesProject Objectives

Main bay Model – Mesohaline Baywide Main bay Model – Mesohaline Baywide average average

Tributary Model – Patuxent and Choptank Tributary Model – Patuxent and Choptank RiversRivers

< 2 microns

2-4 microns

4-10 microns

10-50 mic

50-100 mic

> 100 microns

Phytoplankton

Bay Anchovy

Oysters

Acartia tonsa

Microzoopnktn

Sea Nettles

Ctenophores

POC

Pelagic Prey Fish

Benthic

Zooplankton

On-reef inverts

Off-reef inverts

DOCN P Si

Benthic Bacteria

HNAN

Pelagic Bacteria

Detrital Pools

Atlantic Menhaden

Oyster Larvae

Anchovy Larvae

Ctenophore Larvae

Larval Pools

Gelatinous Zooplankton

Non reef fish

Reef-assoc. fish

< 2 microns

2-4 microns

4-10 microns

10-50 mic

50-100 mic

> 100 microns

Phytoplankton

Bay Anchovy

Atlantic menhaden

Oysters

Acartia tonsa

Microzoopnktn

Sea Nettles

Ctenophores

Detrital Pools

Pelagic Prey Fish

Gelatinous Zooplankton

Benthic Planktivores

Zooplankton“Lost”

Model Linkage DynamicsModel Linkage DynamicsDaily N, P, Si and inorganic TSS concentrationsDaily N, P, Si and inorganic TSS concentrations

Light, temperature and nutrient limitation of primary productivityLight, temperature and nutrient limitation of primary productivity

DO dynamics and water column stratificationDO dynamics and water column stratification

Benthic-pelagic coupling and sediment resuspension dynamicsBenthic-pelagic coupling and sediment resuspension dynamics

Daily removals by top piscivoresDaily removals by top piscivores

Water Quality Models

TroSim-CASM Fishery Production Models

Decision Support System - NOAA Coastal Ocean Program Funding

Data suggest oyster recoveryData suggest oyster recoverywill …will …

reduce phytoplankton biomass and reduce phytoplankton biomass and particulate matter in water columnparticulate matter in water column

increase water clarityincrease water clarity

decrease production of other planktivoresdecrease production of other planktivores

possibly decrease production of higher possibly decrease production of higher level consumers via bottom-up effectslevel consumers via bottom-up effects

Have similar effects as nutrient reductionHave similar effects as nutrient reduction

Modeling Oyster RecoveryModeling Oyster Recovery

Modeled 10X, 25X, and 50X scenariosModeled 10X, 25X, and 50X scenarios

Assume threshold relationship between oysters Assume threshold relationship between oysters and sea nettlesand sea nettles

Assume linear relationship between oyster Assume linear relationship between oyster density, reef-associated fish, and on-reef density, reef-associated fish, and on-reef invertebratesinvertebrates

Assume no relationship between oyster density Assume no relationship between oyster density and off-reef invertebratesand off-reef invertebrates

Ex. 25X oysters = 25X on-reef inverts, 25X RAF, 10X SNEx. 25X oysters = 25X on-reef inverts, 25X RAF, 10X SN

Phytoplanton Biomass

0.00

0.20

0.40

0.60

0.80

1.00

1 31 61 91 121 151 181 211 241 271 301 331 361

Model Day

Bio

ma

ss

(g C

m-3

)Current Oyster Biomass 10X Oyster Biomass

25X Oyster Biomass 50X Oyster Biomass

Inorganic Seston Concentration

0369

121518

1 31 61 91 121 151 181 211 241 271 301 331 361

Model Day

TSS

(mg

L-1

)

Phytoplankton Biomass ReductionPhytoplankton Biomass Reduction

0

1

2

3

4

5

6

7

8

9

Current Biomass 10X Biomass 25X Biomass 50X Biomass

ug

ch

l-a

L-1

Food web model

Water Qualtiy Model

Water quality model output from Noel and Cerco 2005 Table 1 - MD output

Phytoplankton Response to Oyster Recovery

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

>100 um 50-100 um 10-50 um 4-10 um 2-4 um <2 um

10X oysters25X Oysters50X Oysters50% Nut reduction

Consumer Response to Oyster Recovery

-0.7-0.6-0.5-0.4-0.3-0.2-0.1

00.1

Copepods Microzoop HNAN Ctenophores Menhaden Bay Anchovy

10X oysters25X Oysters50X Oysters50% Nut reductionC

han

ge

in t

ota

l an

nu

al P

rod

uct

ion

(p

rop

ort

ion

)


-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

>100 um 50-100 um 10-50 um 4-10 um 2-4 um <2 um



-0.7-0.6-0.5-0.4-0.3-0.2-0.1

00.1



han

ge

in t

ota

l an

nu

al P

rod

uct

ion

(p

rop

ort

ion

)


-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

>100 um 50-100 um 10-50 um 4-10 um 2-4 um <2 um



-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1Copepods Microzoop HNAN Ctenophores Menhaden Bay Anchovy


han

ge

in t

ota

l an

nu

al P

rod

uct

ion

(p

rop

ort

ion

)

Oyster Recovery and DetritusOyster Recovery and Detritus

Response to oyster restoration

0

1

2

3

4

5

6

1 31 61 91 121 151 181 211 241 271 301 331 361Model day

Par

ticu

late

org

anic

mat

ter

(g C

m-3

)

Current 10X 25X 50X

Oyster Recovery and Light Oyster Recovery and Light PenetrationPenetration

Light factor

0

0.2

0.4

0.6

0.8

1

1 31 61 91 121 151 181 211 241 271 301 331 361

Model day

d-1

Current 10X25X 50X


-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

>100 um 50-100 um 10-50 um 4-10 um 2-4 um <2 um



-0.7-0.6-0.5-0.4-0.3-0.2-0.1

00.1



han

ge

in t

ota

l an

nu

al P

rod

uct

ion

(p

rop

ort

ion

)

Model results suggest oyster Model results suggest oyster recovery will …recovery will …

reduce phytoplankton biomass and inorganic particulate reduce phytoplankton biomass and inorganic particulate matter in water columnmatter in water column

improve water clarity locally but reduced effect regionallyimprove water clarity locally but reduced effect regionally

decrease production of zooplankton but not menhadendecrease production of zooplankton but not menhaden

decrease bay anchovy production by 30-40% yrdecrease bay anchovy production by 30-40% yr-1-1

– likely to affect production of top piscivores likely to affect production of top piscivores

decrease ctenophore productiondecrease ctenophore production

– likely to reduce predation on oyster larvaelikely to reduce predation on oyster larvae

Have a larger effect on 2Have a larger effect on 2o o production than nutrient production than nutrient reduction due to seasonalityreduction due to seasonality

Documents

Assessing oyster population recovery in Chesapeake Bay: Management from a food-web perspective