Project Title: Realized and Potential larval connectivity along the Oregon

CoastHal Batchelder1, Bill Peterson2, & Jennifer Fisher2

With Contributions from John Osborne (CEOAS Grad. Student) 1

1CEOAS, 104 CEOAS Admin Bldg, OSU, Corvallis, OR

2CIMRS, Hatfield Marine Science Center, Newport, OR

Otter Rock

Cascade Head

Cape Arago

Cape Perpetua

Redfish Rock OuterRedfish Rock Inner

Cape FalconMultiple Uses and Marine

Spatial Planning

MSP in Oregon

Realized Larval Connectivity (RLC) is the number of observed larvae that travel from a specific spawning site to a specific destination site.

RLC is rarely known because the numbers of larvae at time and location of spawning are not known and matching recruits in a specific destination site back to a specific site of origin in situ is difficult; can be done with otolith chemistry, genetics for some species.

More commonly we estimate (using model simulations):

Potential Larval Connectivity (PLC), which is the probability of larval transport from a spawning site to a destination site.

A Simple Potential Connectivity Example

Two Marine Reserves (A & B) providing refuge for Adult Organisms A

B

A B

PLC = func {Δto, Δtd , ΔT, T,Ao,Ad}

ΔT = func {uv,°T, Mixing, M, Life History, Behavior}

T = func {year, day of year}

o d

od

ΔtdΔto ΔT

But, the real world isn’t simple…

One type of connectivity is to estimate PLC between A and B over some time interval

1000

1000 56

2270.227

0.056

And, we are interested in more than the connection among

reserves…Reserves are intended to provide spillover of adults to nearby regions (which can be fished), and so that they provide new recruits to other suitable habitats outside of the borders of the reserves.

A

B

A Bo d

od

o dU3

U2

U4

U1

Origin

U1 A U2 U3 B U4 Sum

A 5 35 63 300 227 10 640

B 0 0 0 24 56 150 230

Destination

Suppose: Mid-summer release of 1000 individuals from both A and B

Note assumption of equal larval supply at A & B

More larvae from A recruit to B than do larvae from B

Potential connectivity assumes equal source strength everywhere…

What if we know that 10X more larvae are produced at B than at A A

B

A Bo d

od

o dU3

U2

U4

U1

Origin

U1 A U2 U3 B U4 Sum

A 5 35 63 300 227 10 640

B 0 0 0 240 560 1500 2300

Destination

Suppose: Mid-summer release of 1000 individuals from A and 10000 individuals from B

More larvae from B recruit to B than do larvae from A, or B is largely self-seeding.

Realized larval connectivity assumes knowledge of abundances of larvae produced or recruited (usually)…

These estimates are hard to know through space and time. Instead, what can we say about realized connectivity if we know the spatial and temporal distribution of larvae in the plankton (from net samples)?

A

B

A Bo d

od

o d

U3

U2

U4

U1

Can we robustly estimate both the site of origin

and the likely destination of meroplanktonic larvae

captured in plankton tows? And thereby construct realized connectivity maps?

Observations

126° W 125° W 124° W 123° W

45° N

46° N

47° N

48° NLa Push

Queets River

Grays Harbor

Willapa Bay

Columbia River

Cape Meares

Cascade Head

_̂

Cape Falcon

Cape Perpetua

Newport

Washington

Oregon

• Newport Line biweekly sampling since 1996 (17 years)

• Large-scale Plankton sampling June and September since 1998 (15 years)

• Data we will use:• Newport biweekly plankton (2009 – 2011)• Large-scale plankton

(2010 – 2011)

Crab Larvae Barnacle Larvae

Lophopanopeus bellus Zoeae stage I

Hemigrapsus spp. Pachygrapsus crassipes Megalopae

Cancer magister Zoeae stage I

Balanus crenatus Nauplii and Cyprid

Realized Connectivity

126° W 125° W 124° W 123° W

45° N

46° N

47° N

48° NLa Push

Queets River

Grays Harbor

Willapa Bay

Columbia River

Cape Meares

Cascade Head

_̂

Cape Falcon

Cape Perpetua

Newport

Washington

Oregon

• Using hindcast physics from the data assimilating real-time Oregon physics forecast model and info on abundance & distribution of meroplanktonic lifestages of barnacles and crabs

• identify most likely destinations of larvae using forward time trajectory modeling

• identify most probable source regions (PDs) and dates of larvae production using backward time trajectory modeling

Outcomes

1) Identification of source and probable destinations of larvae using particle-tracking methods, robust physical representations of ocean circulation, and life history information (incl. depth behaviors of larvae).

2) Results will provide guidance to monitoring and assessment efforts to characterize the the efficacy of OR MR/MPA network. Identification of gaps that might inhibit successful MR/MPA networks.

3) Informal collaboration with CA SG funded PIs (Steve Morgan/Chris Edwards) on similar connectivity project will extend understanding of factors driving larval dispersal, supply and connectivity to most of the CCLME.

Outreach planDissemination of results

• Working with Jeff Feldner, we will determine the most effective avenue for communicating our results• Meetings with targeted resource managers, public

meetings, etc.

HMSC exhibit• We will consult with Bill Hanshumaker on the

development of a display about coastal connectivity and marine reserves; it will compliment the existing exhibit on larval dispersal of oysters in Yaquina Bay (Emily Lemagie and Jim Lerczak)

• Fall 2012- a static display along with hands-on ‘activities’ will be installed

• FY2013- an intern will evaluate the efficacy of our display and will outline deficiencies and ways to better overlap with the existing exhibits

• FY2013- improvements to the display will be made and an intern will assist in transitioning from a static display to a video display