11-16-2017

The South Atlantic LCC’s Third Thursday Web Forum Intersections between coastal protection and fisheries

Call in for audio: 866-720-8724 2917595555#

• Introduction

• Monthly topic – interactive with questions and discussion

• Preview of next webinar

• LCC staff updates

• Questions and discussion about updates

2

Agenda

3

Simeon Yurek

Intersections between coastal protection and fisheries

11-16-17

Intersections between coastal protection and fisheries

Third Thursday Web Forum 16 November 2017

Simeon Yurek, Ph.D. U.S. Geological Survey, Wetland and Aquatic Research Center

South Atlantic Landscape Conservation Cooperative Raleigh, NC

Overview:

• Summary of coastal restoration objectives and tradeoffs

• Phase 1: Oyster reef-building model & preliminary results

• Phase 2: Spatial framing of landscape conservation

Broad conservation questions

• What will our landscape look like in the future and what will the value of its resources be?

• How does uncertainty about ecosystem dynamics and future conditions affect how and what we conserve today?

• Does our understanding of the current value of the landscape differ from the potential future value, when many different future outcomes are possible?

• How can policy and land use planning scale between large regional or national scales (e.g., Conservation Blueprint) to smaller local scales, where stakeholder values, decision strategy, and scientific understanding of ecological dynamics and risk are identified explicitly?

Develop simulation modeling that: • Predicts ecological responses to management decisions and actions,

under varying scenarios of uncertainty in environment and policy

• Quantifies expected value and associated risk of resources that are of interest to stakeholders

• Promotes learning from predictions as new information becomes available

Research approach

Coastal Resilience and Human Vulnerability

Ecosystem service Ecosystem process Bioeconomic model

valuation method

Water quality improvement Reduce Chlorophyll a & turbidity, denitrification, algae production, bacteria removal

Replacement cost of using sewage treatment plant to remove nitrogen, nitrogen credit market

Seashore stabilization Shoreline stabilization Cost of a sill to stabilize salt marsh and seagrass habitat, value of protected habitats

Carbon burial Bury carbon dioxide Traded carbon pollution credits

Habitat provisioning for mobile fish and invertebrates

Increased fish production Commercial dockside landings value, recreational fisher willingness to pay for improved fishing

Habitat for epibenthic fauna Increased epibenthic faunal production and biodiversity Already captured in fish values

Diversification of the landscape Synergies among habitats NA

Oyster production Increased oyster production Commercial oyster dockside value, recreational value-license program

(from Grabowski et al. 2012 Bioscience)

Ecosystem services provided by oyster reef habitat

Mutual Protection (Habitat Mosaic)

(Meyer et al. 1997; Piazza et al. 2005; Scyphers et al. 2011)

Oyster reef: • Attenuates wave energy • Reduces marsh erosion rates • Deposits sediment/nutrients

Salt marsh: • Attenuates wave energy • Provides habitat structure for reefs

(e.g., channel geomorphology)

Living Shoreline & Oyster Reef Restoration

Marsh expansion

Wave attenuation

www.southernenvironment.org

Oyster Reef Restoration

• Regulating Services: Coastal wetlands and reefs buffer wave energy

• Provisioning Services: High economic value for harvest

• Tradeoff = Harvest can disrupt coastal ecology (reduces protection service) Setting “no take” reserves reduces available harvest

Tradeoffs in Ecosystem Services

vs.

Oyster Harvest Coastal protection

Restoration paradigm: • Harvest and coastal protection tend to be viewed and implemented exclusive of each other • Can be funded/managed by separate authorities (State DNRs, DEQs, NGOs) • Restoration may be too expensive for one agency alone (some exceptions)

Commercial • Mariculture • Hatchery production

(larvae/seed) • Shellfish leases

Conservation • Living shorelines • No take reserves Mediation

???

In practice, these tradeoffs fall along a conservation-commercial management axis

Example: public seed source reefs (Louisiana DWF)

Uncertainty

Environmental variation (process) • Global change • Frequency of major storms (H3+) • Freshwater availability/flows • Organic/inorganic particulates (food/turbidity)

Structural (model) • Stock-recruitment relationships • Energy budgets (age dependent) • Age-size structure • Mortality (natural and predator) • Local plasticity, adaptation (genetics)

State / partial observability • Monitoring frequency, spatial coverage • Growth studies Controllability • Regulations, seasons, legal lengths • Closures • Restoration budgets

Marsh migration predictions (NOAA)

https://coast.noaa.gov/data/digitalcoast/pdf/slr-marsh-migration-methods.pdf

Unconsolidated shore

Saline wetlands

Freshwater wetlands

Developed

Upland Charleston, SC

Edisto Is.

Kiawah Is.

Santee R.

Cape Romain NWR

Pritchards Is.

https://coast.noaa.gov/data/digitalcoast/pdf/slr-marsh-migration-methods.pdf

Unconsolidated shore

Saline wetlands

Freshwater wetlands

Upland

Marsh migration predictions (NOAA)

Developed

Charleston, SC

Edisto Is.

Kiawah Is.

Santee R.

Cape Romain NWR

Pritchards Is.

Conservation Blueprint 2.2

Charleston

Edisto Is.

Kiawah Is.

Santee R.

Cape Romain NWR

Pritchards Is.

Decision analysis framework

Decisions (Management options)

Objectives &

Values

adapted from Peterman et al. 1998

... … … …

Simulated Ecosystem Responses

(Under uncertainty)

Current Understanding

Resource (Stakeholder interest)

EVA EV…, Harvest EV…, Protection EVD

… … … … EVN

Future Expected

Values

Harvest α2 β2 γ2 δ2

α3 β3 γ3 δ3

α4 β4 γ4 δ4

Protection

PolicyA

α1 β1 γ1 δ1 PB

PC

PD

PN

Policy decision

Oyster Reef States

Low Dredged High

1 - 2 m

0.3 - 0.6 m

0.1 - 0.3 m

after Lenihan 1999

Reef height and oyster dynamics study (Colden et al. 2017)

Modeling wave attenuation (Allen & Webb 2011)

Wave in

Wave out

Oyster Reef

(Wave out)

(Wave in)

Modeling wave attenuation (Allen & Webb 2011)

Wave in Wave out Reef width

Reef height

(Wave out)

(Wave in)

Equations from Van der Meer et al. (2015)

adult

reef height & area

boxes (intact shell)

spat (recruits)

shell (crushed)

larvae

β1 β2

β3 survival = 2e-6

degradation

(adapted from Powell, Hofmann, Klinck, Soniat, LaPeyre, Wang, et al., Pine et al.)

transfers dependency Oyster population biology

Oyster population biology

adult

reef height & area

(adapted from Powell, Hofmann, Klinck, Soniat, LaPeyre, Wang, et al., Pine et al.)

boxes (intact shell)

spat (recruits)

shell (crushed)

larvae

β1 β2

β3

degradation

transfers dependency

food availability

salinity variance disease predators

survival = 2e-6

0 5 10 15 20 age (years)

Energy Budget (Age-based)

Rodhouse (1978) european flat oyster

Adapted for IBM

Growth, Respiration, & Mortality

Growth = Feeding – Respiration (from Powell et al. 1991-1995)

Feeding Rate (g t-1 i-1) = f (assimilation, food value (g chla L-1), filtration rate (L t-1), salinity, temperature, turbidity (TSS g L-1), variancei, lengthi) Respiration rate (g t-1 i-1) = f (O2 (µL L-1), salinity (θs=10,15), temperature (θt = 20)) Mortality (pi t-1) = f (natural survival, life span (6-20y), predation, burial, fishing, disease) *predation probability is sized-based, higher for small-intermediate sized individuals functional response based on prey density and predator self-interference Mortality larvae (ni t-1) = f (survivorship, fixed rate)

Water data

Skrine creek

Gamete production & GSI

Reef morphology

• Total volume = f(crushed shell weight) + f(boxes)

• Solve for height (h), where total volume V = Vbase + Vspill area

• Reef surface area = Σ area top panel & 4 side panels (trapezoids)

• Estimates cultch area for recruitment

*boxes have a higher total volume than crushed shell due to void space

Base area

Spillover area

from Bahr 1981

Recruitment & Available area

• Total available area = Total area – occupied area + β1 box area + β2 living shell area • Occupied area = Σi=1:n 2/9 lengthi

2 (i.e., 2D flat area) • Number of spat (recruiting) = Total available area * spat per area • When reef is fully covered, some oysters have to die before new recruits can attach

*oysters recruit to the sides also (not pictured here)

Results (100 year simulation)

Results mortality (spat per area = 0.006)

Results: Weight-age of dead oysters

*uses length-weight relationship for visualization

Comparison with empirical study of NC reserve reefs (Puckett et al. 2012)

Oyster IBM results

Length-at-age models

*uses length-weight relationship for visualization

(49-60)

Comparison with empirical study of NC reserve reefs (Puckett et al. 2012)

spa = 0.005

Varying recruitment parameters

spa = 0.008

spa = 0.007

Spatial Application (example for South Carolina) Restoration

Spatial Plan (Portfolio)

Decision analysis framework

Decisions (Management options)

Objectives &

Values

adapted from Peterman et al. 1998

... … … …

Simulated Ecosystem Responses

(under uncertainty)

Current Understanding

Resource (Stakeholder interest)

EVA EV…, Harvest EV…, Protection EVD

… … … … EVN

Future Expected

Values

Harvest α2 β2 γ2 δ2

α3 β3 γ3 δ3

α4 β4 γ4 δ4

Protection

PolicyA

α1 β1 γ1 δ1 PB

PC

PD

PN

Policy decision

Coastal steward preference

Fisher preference

after King et al. (2015)

ES Tradeoff: Biophysical and Value constraints

MCDA Tradeoff (Biophysical constraints)

MPT Analysis (Value constraints)

Fisher value Coastal

steward value

wf,h wf,wa wcs,h wcs,wa

+ +

Coastal steward preference

Fisher preference

MPT Analysis (Value constraints)

wf,h wf,wa wcs,h wcs,wa

+ +

Risk efficiency frontier

Fisher value Coastal

steward value

• Oyster IBM combines metabolic modeling at individual level (feeding rates, growth, respiration), with population dynamics (natural mortality, predation, fishing, disease)

• Draws heavily from existing models: - metabolic (Powell, Hoffman, Klinck, et al.) - population dynamics (Pine et al., Wang et al.) - shell deposition and degradation (Klinck, Powell, Soniat et al.) • Reef morphology included, and age-size structure is dynamic

• Energy budget links tissue, gonad, and shell (theoretical for now, but see DEB modeling for Louisiana – Romain Lavaud)

• New probability based parameters for recruitment to crushed shell, live oysters,

and boxes (intact shell of recently dead adults)

Summary of model developments

• Apply model across the landscape

• Include bathymetry data, and best approximations of time series of environmental conditions (salinity, chloropyhll a, turbidity)

• Simulate uncertainty scenarios (e.g., harvest, shell/larvae restoration),

• Estimate wave attenuation for given reef heights and water depths using Van der Meer equations

• Compare coastal protection values to associated conservation priority value for different areas across the landscape

• Compare tradeoffs in harvest, coastal protection, and risk

Next steps

Thank you!

Collaborators Rua Mordecai South Atlantic Landscape Conservation Cooperative Mitch Eaton DOI Southeast Climate Science Center Bill Pine, Peter Frederick, Ed Camp University of Florida Julien Martin, Fred Johnson, Hongqing Wang USGS Wetland and Aquatic Research Center Megan LaPeyre USGS & Louisiana Fish and Wildlife Coop Unit Romain Lavaud Fisheries and Oceans Canada Hadi Charkhgard, Zulqarnain Haider, Changhyun Kwon University of South Florida

Next Third Thursday Web Forum 2-15-2018 10:00 am To be determined!

47

To be determined!

• Blueprint 2.2 released!

• Southeast Conservation Adaptation Strategy symposium at SEAFWA conference

48

LCC staff updates

49

Blueprint 2.2 released

50

secassoutheast.org

51

How to get involved with your cooperative

• Join the South Atlantic LCC web community

• Connect with a staff or other cooperative member

• Explore the Conservation Blueprint southatlanticlcc.org/blueprint

southatlanticlcc.org

52 52

Questions?