Lobster Ecosystem�Modeling + Monitoring

NNA Lobster Network All-Hands Meeting

21 November 2024

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Andrew Goode

Overarching Research Goals / Objectives

Monitoring

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• Collaborate with The Lobster Institute, The Gulf of Maine Lobster Foundation, and NOAA to help expand benthic temperature monitoring by the Environmental Monitoring on Lobster Traps (eMOLT) program.

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Modeling

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• Integrate multiple avenues of early lobster life history research to develop a Larval Life History Model to simulate drift, growth, mortality, and settlement of larval / Postlarval lobsters.

Monitoring: eMOLT

Why?

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• Provides critical benthic temperatures and water column profiles necessary to tune the hydrodynamic models to real conditions in the Gulf of Maine

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How?

• in situ temperature-depth sensors, satellite transmission of data in near-real time

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eMOLT 2024

• In 2024 the NNA program and GOMLF added 10 new participating lobstermen to the eMOLT program ranging from Bucks Harbor to Kittery
• 12 Temperature-Depth Sensors
• 12 DO Sensors

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• NNA Total: 18 new participants

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• Add Pete’s figure*****

NNA

All eMOLT

Modeling

Objective:

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• Integrate HYCOM-NEMURO products to particle tracking simulations

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Larval Tracking Simulations

SSB Distribution

Hatch

Phenology

Prey Field

Modified Mortality

Settlement Potential

Large-scale Settlement Relationships

Environmental

Characteristics

Larval Development

Modeling: Previous All Hands Discussion

Larval Tracking Simulations

SSB Distribution

Hatch

Phenology

Prey Field

Modified Mortality

Settlement Potential

Large-scale Settlement Relationships

Environmental

Characteristics

Larval Development

Modeling: Today’s Topic – development and mortality

Larval Tracking Simulations

SSB Distribution

Hatch

Phenology

Prey Field

Modified Mortality

Settlement Potential

Large-scale Settlement Relationships

Environmental

Characteristics

Larval Development

Modeling: revisiting development and mortality

Modeling: revisiting development and mortality

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• What about temperature dependence?

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Modeling: revisiting development and mortality

• Literature review of stage-specific temperature-dependent relationships to larval stage duration

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• Revisit MacKenzie (1988) data for temperature-dependent, stage-specific larval mortality

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• Q: Can we refine these relationships with existing data, and what inferences can we gain from the two?

Larval development

Results

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• Comparable equations to MacKenzie (1988)

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• Improves eq. fit to results from 7 studies

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• Especially at low temperatures where the MacKenzie eqs. perform poorly

Larval mortality

Results

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• MacKenzie (1988) data (Table 1), were able to generate daily mortality rates that varies with temperature.

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• 2^nd order polynomials with decreasing sensitivity to temperature with advancing larval stage

Survival

Results

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• Non-linear relationships between temperature and development/mortality create unique, non-linear functional relationships between larval survival and temperature.

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• Cumulative survival is largely dictated by patterns established/experienced as a stage I larva.

Fitness

New questions

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• Can larval fitness (Survival / Max Survival) be used to investigate patterns of larval habitat suitability?

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• How has larval habitat suitability changed over space/time?

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• How do these patterns relate to lobster settlement patterns (the end result of successful survival and settlement to the early benthic stage)

Fitness Over Space

Results

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• Larval Fitness estimates show significant variation in larval habitat suitability across NOAA statistical areas.
• Highest along Mid-coast ME

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• Fitness changes inshore/offshore, but the patterns aren’t the same everywhere

SST Regime Shifts

Larval Fitness Regime Shifts

Non-linear Responses Make a Difference

• Rapid changes in the thermal environment have caused shifts in regional larval habitat suitability.

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• Non-linear relationships to temperature cause heterogeneous responses to habitat suitability given similar changes in temperature

Fitness and Post-larval Settlement

• Regional declines in settlement correspond to regime shift phenology of larval fitness
• How well do they relate?

Fitness vs Settlement

• Linear mixed effect model
• Relationship between fitness and settlement rate varies over statistical areas due to spawner biomass, connectivity, benthic habitat suitability, etc.
• Statistical area as random effects to slope and intercept to address regional patterns

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• Model R² = 0.21

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• A significant part of the story that needs to be accounted for

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Tracking Simulations

Start

End

Integration Needs

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• HYCOM-NEMURO zooplankton abundances
• Tracking Using HYCOM

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Larval Tracking Simulations

SSB Distribution

Hatch

Phenology

Prey Field

Modified Mortality

Settlement Potential

Large-scale Settlement Relationships

Environmental

Characteristics

Larval Development

Next Steps

• Integrate spawner biomass weighting, egg hatch phenology, revised temperature-dependent development and mortality to estimate annual larval supply and distribution.

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• Use benthic thermal habitat, post-larval supply phenology, and large-scale settlement behavior dynamics to estimate annual post-larval supply.

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• Relate supply to regional settlement

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• Use zooplankton abundance to evaluate its ability to affect the relationship between post-larval supply and settlement density