Research Key Concepts and Career Journey

Energy: The Currency of Life

  • All organism activities require energy. It's crucial to understand how animals obtain energy and use it for various functions.
  • Consumption of food transfers energy through marine ecosystems, influencing productivity.
  • Predators play a key role in this energy transfer.

Energy Allocation in Predators

  • When predators consume prey, energy goes to:
    • Metabolism (routine activities, digestion).
    • Growth (tissue growth, reproduction).
    • Waste (egestion and excretion).

Factors Affecting Energy Allocation

  • Biotic Factors
    • Activity levels.
    • Foraging mode.
    • Body size.
    • Life history characteristics.
  • Abiotic Factors
    • Oxygen levels.
    • Temperature.
    • Salinity.
    • pH.
  • Most energy consumed is used for metabolism.

Temperature and Metabolism

  • Temperature significantly affects metabolism, a focus of research.
  • Relationship between temperature and metabolic rate:
    • Standard Metabolic Rate (SMR): Increases exponentially with temperature for ectothermic species.
    • Maximum Metabolic Rate: Increases to a threshold, then declines.
    • Aerobic Scope: The difference between maximum and standard metabolic rate.
  • Metabolism dictates consumption, influencing activity, foraging, and space requirements.

Climate Change Impacts

  • Ocean temperatures are expected to rise significantly.
  • It's crucial to understand predators' physiological requirements to predict how they'll respond to future climate scenarios.
  • Key Concepts: Temperature, oxygen consumption, and activity influences.

Horn Shark Metabolic Sensitivity to Temperature

  • Research project at Cal State, Long Beach, with Dr. Chris Lowe.
  • Study: Metabolic sensitivity of horn sharks to temperature.
  • Horn sharks are important kelp forest predators.
  • Experiment: Measured oxygen consumption of horn sharks at different temperatures using a respirometer.
  • Metabolic rate (mg O2/kg per hour) increased with temperature.

Modeling Metabolic Costs

  • Modeled minimum metabolic costs using historical sea surface temperature data.
  • Year on X-axis, Standard Metabolic Rate (kJ/kg per day) on Y-axis, colored by temperature.
  • Observed annual variability in temperature and metabolic rate.
  • El Niño Southern Oscillation events (warm water from Mexico) increased temperatures in Southern California.
  • Increase in metabolic rates by 23% in 2017.
  • Paper provided a baseline for the current physiological state of horn sharks.
  • Climate change increases storm surge and wave action in coastal areas.

Fish Swimming and Kinematics Course

  • Six-week course at Friday Harbor Lab, San Juan Island, Washington.
  • Investigated how metabolic rates vary in unsteady, directional flow regimes (wave surge, storm surge, tides).
  • Typical swim tunnel respirometry studies measure oxygen consumption in steady flow, which isn't representative of dynamic coastal ecosystems.

Experiment with Unsteady Flow

  • Programmed a swim tunnel respirometer to reverse directions, imitating a wave surge.
  • Fish constantly changed directions as flow moved forward and backward.
  • Compared to unidirectional flow, where fish experienced the same velocity differences but didn't have to turn around.

Results

  • Turning and reorienting in the water column increased metabolic rates by 50% compared to swimming in a steady flow environment.
  • Demonstrated the need to incorporate the added costs associated with dynamic coastal habitats when estimating energy requirements.

PhD at Florida International University

  • PhD in the Predator Ecology and Conservation lab with Dr. Juan Papasau.
  • Studied two contrasting ecosystems: coral reefs and the pelagic environment.
  • Coral reefs: High abundance and biodiversity.
  • Pelagic environment: Low abundance and biodiversity.
  • Predator morphology and swimming mode differ greatly between these ecosystems.

Coral Reef Predator: Nassau Grouper

  • Ecologically and economically important species.
  • Slow-growing ambush predators.
  • Listed as critically endangered on the IUCN Red List due to predictable aggregate spawning behavior during the full moon (November to March).
  • Fishermen easily overfish them at known spawning locations.

Pelagic Species: Dolphin Fish (Dorado or Mahimahi)

  • Important commercial and recreational fishery species.
  • Fast-growing, active foraging fish in an oligotrophic environment.

Climate Change Impact on Trophic Demand of Marine Predators

  • Consumption requirements of ectothermic predators depend on size and temperature.
  • It's essential to consider the effect of temperature on both predators and prey, relative abundance, body size, and the rate and magnitude of response to temperature changes.
  • Difficult to understand food web-scale dynamics and predict how climate change will influence them.
  • Need to determine how species will fare under different climate scenarios.

Reef Flattening

  • Loss of structural complexity following coral mortality and bioerosion.
  • Threatens species richness and diversity.

Nassau Grouper Trophic Demand

  • Measured in two major reef habitats: complex hard coral habitat and flatter soft coral habitat.
  • Objectives:
    • Estimate how consumption rates of Nassau grouper vary under future climate scenarios.
  • Measured maximum and standard metabolic rates and their relationship to body mass and temperature.

Methods

  • Used intermittent flow respirometry to measure maximum and standard metabolic rates of Nassau grouper at two seasonal temperatures across a range of body sizes.
  • Derive the relationship between metabolic rate and activity output using acceleration transmitters.
  • These acceleration transmitters are similar to a Fitbit or smartwatch.
  • Tagged Nassau grouper in the Zuma Keys land and sea park using an array of acoustic receivers and tags.
  • Receivers logged date, time, unique ID, activity, and depth.

Data Analysis

  • Correlated mean activity with tag outputs.
  • Estimated field metabolic rates.
  • Incorporated climate change scenarios using two representative concentration pathway scenarios from the Intergovernmental Panel on Climate Change:
    • 1.5 degree Celsius increase in temperature.
    • 3.1 degree Celsius increase in temperature (extreme scenario).

Consumption Estimation

  • Needed a relationship between metabolic rate, body mass, temperature, and activity.
  • Incorporated a growth parameter for immature mature individuals.
  • Accounted for waste lost as egestion and excretion.
  • A 7.5kg Nassau grouper would need to consume about 2.2% of their body weight per day, or about three 15cm French grunts per day.
  • Consumption would increase by 11% under a 1.5 degrees Celsius increase scenario and 24% under a 3.1 degrees Celsius increase scenario.

Trophic Demand Variation Across Habitats

  • Used fish survey data from 85 reef sites in the Bahamas, on two dominant habitats: Orbcealla hard coral-dominated reef and gorgonian plain habitat.
  • Incorporated effects of protected status inside and outside the Exuma Keys Land and Sea Park.
  • Estimated trophic demand by dividing prey productivity by the consumption of groupers on each reef habitat.

Reef Surveys

  • 47 reef sites had 136 total Nassau groupers.
  • 19 were Orbcealla reefs, and 28 were Gorgonian Plain reefs.
  • More Nassau groupers observed on Gorgonian Plain reefs (77 compared to 59).
  • The size of Nassau groupers was significantly larger on Orbcealla reefs.

Results

  • High vertical relief habitats had fewer but larger Nassau groupers, leading to higher consumption rates per year.
  • Orbcealla reefs had significantly more than double the prey productivity than Gorgonian Plain habitats.
  • Trophic demand was highest in the Gorgonian Plain habitat.
  • The effect of temperature was greatest in low-complexity reefs with low productivity.
  • No effect of protected status; only reef type mattered.
  • The proportion of prey consumed was larger on Gorgonian plain reefs.

Summary: Grouper Consumption Rates

  • Consumption rates could increase up to 24% with a more than three degrees Celsius increase in temperature.
  • Groupers may consume up to 5% of the available prey productivity in low complexity habitats.
  • The effects of climate change might be dampened by increased prey productivity.
  • It's important to preserve complex reef habitats that support increased population sizes of both predators and prey.

Vertical Energy Seascapes and Diving Behavior in Dolphin Fish

  • Pelagic environment: Prey is sparse and patchy; predators are energy speculators.
  • Energy minimizers (e.g., oceanic whitetip) live a slower-paced lifestyle.
  • Energy maximizers (e.g., tuna and dolphin fish) live a fast-paced lifestyle, characterized by high energy expenditure, growth rates, digestion rates, and metabolic rates.

Diving Considerations

  • Searching for prey vertically in the water column.
  • Ectothermic fish must return to the surface after diving.
  • Repetitive bounce dives.
  • Travel costs are vertical.

Study Objectives

  • Estimate the field metabolic rates of free-ranging dolphin fish.
  • Measured routine metabolic rates at the Animal Research and Care Center at the Monterey Bay Aquarium using an annual respirometer.
  • Attached an acceleration data logger to the fish, measuring surge, heave, and sway.
  • Estimated tidal frequency from the sway axis as a proxy for swimming speed.
  • Derived a relationship between tidal frequency and routine metabolic rate.

Field Study

  • Tagged wild dolphin fish off the coasts of Mexico and Japan with acceleration data logger packages programmed to detach after 24 to 48 hours.
  • Characterized diving behavior and associated energetic costs by splitting the dive profile into descending and ascending phases.

Results

  • During the daytime, there's high variability in metabolic cost during descent, even down to 60+ meters.
  • During nighttime descent, fish spend significantly less energy and there's very little variability.
  • Ascent is energetically costly due to the need to beat the tail to swim up to the surface.

Hidden Markov Model

  • Used the Hidden Markov model which allows us to predict or estimate two behavioral states for these fish by looking at the frequency distribution of tailbeats.
  • Used to predict two behavioral states based on tailbeat frequency:
    • State 1: Low activity state, low tailbeat frequency.
    • State 2: High activity state, high tailbeat frequency.
  • During the day, fish in the ascending phase are almost always in a high activity state.
  • During the nighttime descent phase, fish are mostly in a low activity state, likely gliding down to conserve energy.

Diving Behavior

  • Observed that when they're at the bottom or they've reached their desired depth, They are in that red high activity state and potentially chasing prey, maybe getting chased by a predator.
  • When they are at the surface, they're spending time in that blue low activity state and conserving energy.

Vertical Energy Landscape

  • Questions focused on optimal foraging theory.
  • Created a vertical energy landscape, estimating the cost to dive to each depth and return to the surface.
  • Fish rarely dive below their isothermal layer depth (ranging from 21 to 65 meters).
  • The cost to dive to their isothermal layer depth and return ranged from 1000 to 3000 kJ/kg.
  • Ascending was much more costly than descending.
  • Gliding during descent could reduce energetic costs by about 29%.
  • Night behavior was indicative of foraging and searching for vertically migrating prey.
  • The isothermal layer depth was important for limiting dive depth, and the energy landscape played a secondary role.

Research Impact

  • Data provide important insights for predicting the resource requirements of commercially important fisheries species.
  • New insights into future energetic trophic models, furthering our understanding of the complex pelagic ecosystem.

Postdoc at the University of Michigan

  • Working in Abaco, the Bahamas, with Dr. Jacob Ager in the Coastal Conservation Lab.
  • Using white brant as a model species; they forage in seagrass beds at night and remain on reefs during the day.
  • Studying habitat patch selection using an acoustic array surrounding artificial reefs.

Data Analysis

  • Extracted step length (distance between positions) and turning angles (trajectory).
  • Built a two-state Hidden Markov Model using step length and turning angle data streams.
    • State 1: Short step lengths and frequent turning (milling around, staying in one space).
    • State 2: Long step lengths and infrequent turning (high directionality, transiting).
  • State 1: Resting on the reef or foraging in a seagrass patch.
  • State 2: Transiting to and from a seagrass patch back to the reef.

Spatial Analysis

  • Colored fish positions based on state: green (state 1) and blue (state 2).
  • During the day, fish spend time around reef locations in the green state.
  • At night, there's a spread of fish positions, with blue corridors forming between reefs and seagrass beds.
  • Clusters of green points indicate foraging in seagrass bed locations.

Foraging Behavior Classification

  • Classified foraging if the fish move more than 1.5 meters off the reef.
  • Grunt spent more time foraging than resting overall.
  • While resting, they're mostly in state 1.
  • While foraging, their time is split 50/50 between state 1 and state 2.
  • State 1 is likely search time in a patch; state 2 is likely travel time to and from the patch.

Current Research Directions

  • Estimating different foraging bouts.
  • Incorporating an energetics component.
  • Testing optimal foraging behavior.
  • Using stable isotope and nutrient excretion data.
  • Are they going to high-quality seagrass patches that are close by or do they need to travel further to get those high-quality patches

Final Conclusion

  • Energy is the currency of life, and understanding how marine predators spend it is crucial.
  • Advancements in technology (acceleration transmitters and data loggers) allow for the quantification of energetic costs of free-ranging animals.
  • This furthers our understanding of the ecological role of marine predators in a changing climate.