the south atlantic lcc’s third thursday web forum ......2017/11/16 · 11-16-2017 the south...
TRANSCRIPT
11-16-2017
The South Atlantic LCC’s Third Thursday Web Forum Intersections between coastal protection and fisheries
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• Introduction
• Monthly topic – interactive with questions and discussion
• Preview of next webinar
• LCC staff updates
• Questions and discussion about updates
2
Agenda
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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!
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To be determined!
• Blueprint 2.2 released!
• Southeast Conservation Adaptation Strategy symposium at SEAFWA conference
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LCC staff updates
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Blueprint 2.2 released
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secassoutheast.org
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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
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Questions?