Several large or several (more) small: designing marine reserve networks for oyster restoration

Brandon Puckett and David EgglestonNorth Carolina State University, Center for Marine Sciences and Technology

Conceptual approach: metapopulations

Discrete populations Spatially dynamic demographics Connected by migration

Two spatial scales:1) Local

2) Regional

Sources (λc > 1) v sinks (λc < 1)

• Growth

• Survival

• Reproduction

Demographics

Conceptual approach: metapopulations

Discrete populations Spatially dynamic demographics Connected by migration

Two spatial scales:1) Local

2) Regional

Sources (λc > 1) & sinks (λc < 1)

Conceptual approach: SLOSS

Conserve Single Large Or Several Small areas? Terrestrial systems: single large Marine systems (limited): several small

Single Large Several SmallOR

Conceptual approach: SLOSS

Conserve Single Large Or Several Small areas? Terrestrial systems: single large Marine systems (limited): several small

baseSeveral Large

Several (more) Small

gametes

fertilized egg trochophore veliger pediveliger

spat

~ 2-3 weeks

~ 1-3 years

weak swimmers

adults

Focal species: eastern oyster

Peaks: June & August

Deep Bay

Ocracoke

Crab Hole

Bluff Point

Mounds of limestone rip-rap

Then: Reserve(s), Now: Reserve networks Must be SELF-SUSTAINING

Reserves contain artificial reefs Distances: 10-125 km Areas: 3-24 ha

Study system: oyster reserves

1)Reserve network self-sustaining?

2)Optimal network design?

Questions

Stopher Slade Stopher Slade

Stage-based matrix model Time step: 2 mo. Initial population = density x

area 10 reserves and 6 size-classes Parameters

Pij: probability of remaining in size class i in reserve j

Gij: probability of growing into size class i + 1 in reserve j

Fij: per capita number of offspring in stage i in reserve j

mjk: probability of dispersal from reserve k to reserve j

Methods: 1) Reserve network self-sustaining?

reserve 1

reserve 2

F21

F22

P12 P22 P32

P11 P21 P31

i

1 32

1 32

G12 G22

G11 G21

m22

m11

m21

m12

F32

F31

Larval pool

Larval pool

Model inputs: growth and survivalJune 2006 cohort Aug 2006 cohort

0

40

80

120

0 0.5 1.0 1.5 2.0 2.5Age (yrs)

LVL

(m

m)

0 0.5 1.0 1.5 2.0 2.5Age (yrs)

0

0.2

0.4

0.6

0.8

1.0

0 0.5 1.0 1.5 2.0 2.5Age (yrs)

Sur

vivo

rshi

p (

%)

0 0.5 1.0 1.5 2.0 2.5

Age (yrs)

30% 40%

45%

30%

Model inputs: growth and survivalJune 2006 cohort Aug 2006 cohort

0

40

80

120

0 0.5 1.0 1.5 2.0 2.5Age (yrs)

LVL

(m

m)

0 0.5 1.0 1.5 2.0 2.5Age (yrs)

0

0.2

0.4

0.6

0.8

1.0

0 0.5 1.0 1.5 2.0 2.5Age (yrs)

Sur

vivo

rshi

p (

%)

0 0.5 1.0 1.5 2.0 2.5

Age (yrs)

30% 40%

30%

45%

Model inputs: reproductive output

0

5

0-15 15-30 30-45 45-60 60-75 75+

0

25

50

75

100

0-15 15-30 30-45 45-60 60-75 75+ 0-15 15-30 30-45 45-60 60-75 75+

Size class Size class

Per

cap

ita la

rval

ou

tput

70%

90%

June 2006 August 2006

Model inputs: connectivity

2006 2007 2008 2009

Connectivity

< 5% < 25% > 25%

Few consistent connections in space or time Mean larval retention ~ 6%

6-8/06

N

< 500k< 5 mil

> 5 mil

λc

< 0.7

< 1.0

> 1.0

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

Results: 1) Reserve network self-sustaining?

8-10/06

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

Results: 1) Reserve network self-sustaining?

10/06-6/07

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

Results: 1) Reserve network self-sustaining?

6-8/07

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

Results: 1) Reserve network self-sustaining?

8-10/07

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

Results: 1) Reserve network self-sustaining?

10/07-6/08

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

Results: 1) Reserve network self-sustaining?

6-8/08

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

Results: 1) Reserve network self-sustaining?

8-10/08

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

Results: 1) Reserve network self-sustaining?

10/08-6/09

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

Results: 1) Reserve network self-sustaining?

6-8/09

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

Results: 1) Reserve network self-sustaining?

8-10/09

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

Results: 1) Reserve network self-sustaining?

0

25

50

75

100

6/06 6/07 6/08 6/09 6/10

Met

apo

pu

lati

on

siz

e (x

106 )

10/09-6/10

Results: 1) Reserve network self-sustaining?

Metapopulation size declined ~ exponentially (λ = 0.7 ± 0.1)

Methods: 2) Optimal design?

Simulations Several large: area x2, x4, x6, x8, x10 Several (more) small: number x2, x4, x6, x8, x10

Site selection algorithm Pool of 187 cultch planting sites Maximize connectivity to and from existing network

several large several (more) smallbase

Connectivity

< 5%< 25%> 25%

10x4x2xBase

Connectivity does not scale up Large connections primarily self-recruitment Connections more consistent

Results: 2) Optimal design?

Connectivity

< 5%< 25%> 25%

Base

Connectivity scales initially Increased number and magnitude of inter-reserve

connections

1004020

Results: 2) Optimal design?

Results: 2) Optimal design?

0

5

10

15

20

0 200 400 600 800 1000

Area (ha)

Lar

val r

eten

tio

n (

%)

0 20 40 60 80 100 120

# of reserves

Several largeSeveral (more) small

**

Several (more) small increases larval retention

Law of diminishing returns

SLASS hybrid optimal

Conclusions

Spatiotemporal variation in demographics w/ (limited) connectivity Proof of metapopulation concept

Current reserve network not capable of persisting Sources, Sinks, and “the metapopulation stoplight”

Several (more) small reserves preferred SLASS—Several Large AND Several Small

Acknowledgements Funding:

NMFS/Sea Grant Population Dynamics Fellowship

NC Sea Grant American Recovery and

Reinvestment Act (NOAA/NCCF) NSA Michael Castagna Student

Grant for Applied Research Raleigh Salt Water Sportfishing Club

Field/Technical Assistance: NC DMF: Stopher Slade and Craig Hardy Ray Mroch Amy Haase Gayle Plaia Ryan Rindone Christina Durham Geoff Bell Erika Millstein Josh Wiggs Michelle Moorman

‘Growers’

‘Survivors’

‘Spawners’

‘Connectors’

Demographic and connectivity summary

‘Spawners’

‘Survivors’

‘Growers’