Biophysical mechanisms P2

1. Introduction

This lecture builds on Biophysical Mechanisms 1 by shifting from physical processes to animal behaviour, focusing on:

  1. Spatial & temporal scales of seabird distribution

  2. Predator–prey interactions

  3. How prey behaviour + physical features + seabird movement combine to produce patchy seabird distributions

2. Why Are Seabirds Patchy in Space and Time?

2.1 Observed patchiness

  • Seabirds show ephemeral, heterogeneous distributions.

  • Even abundant species appear in clusters, with long stretches of ocean containing no birds.

  • Patchiness occurs at:

    • Regional scales (10s–100s km)

    • Local scales (<10 km)

2.2 Examples

  • Pembrokeshire surveys: long transects with no birds, then sudden aggregations.

  • Spain (Sisargas Islands): extreme patchiness even within 10 km.

Goal of lecture: explain why this patchiness occurs.

3. Two Key Components of Patchiness

The lecture breaks the explanation into two interacting components:

  1. Predator–prey interactions

  2. Animal movement behaviour

These operate across different spatial scales.

4. Component 1: Predator–Prey Interactions

4.1 Physical features revisited

Physical features influence prey abundance and prey accessibility, but at different scales:

Large‑scale features (100s km) → Prey abundance

  • Shelf edges

  • Seamounts

  • Troughs

  • Large tidal fronts
    These create high productivity → more fish overall.

Small‑scale features (1–10 km) → Prey accessibility

  • Internal waves

  • Eddies

  • Shear lines
    These manipulate prey behaviour, making them easier to catch.

Conceptual trade‑off

  • Large scales → abundance matters most

  • Small scales → accessibility matters most

This scale‑dependence is central to understanding seabird patchiness.

5. Prey Behaviour: Why Fish Are Hard to Predict

Fish schools are mobile and responsive, not passive particles. They respond to:

5.1 Physical drivers

  • Tidal transport (e.g., moving inshore at high tide)

  • Diel vertical migration (surface at night, deep by day)

5.2 Biological drivers

  • Searching for plankton

  • Avoiding predators

  • Spawning migrations

  • Seeking preferred temperatures

5.3 Consequence

Even within a productive region, prey moves constantly, so predators may or may not coincide with them at any given moment.

6. Spatial Scale Framework for Prey Distribution

6.1 Ocean scale (10,000 km)

  • Only certain regions are productive.

  • Birds know these regions and travel to them.

6.2 Regional scale (100s km)

  • Prey is somewhere within the productive region.

  • Birds can reliably find prey in general, but not at a specific point.

6.3 Habitat scale (1–10 km)

  • Prey may or may not be present at the moment a bird arrives.

  • Coincidence becomes low probability.

This explains why seabirds appear in patches: they only forage where prey is both present and accessible.

7. Case Study 1: Barrett et al. (2000) – Barents Sea

7.1 System

  • Predator: Common guillemot

  • Prey: Capelin (schooling fish with diel vertical migration)

7.2 Methods

  • Seabird observations from vessel

  • Echo sounders to quantify fish schools

  • Trawls to identify species

7.3 Key finding: Scale‑dependent correlation

Correlation between bird density and fish density:

  • Large scales (100–200 km) → positive correlation
    Birds and fish overlap regionally.

  • Moderate scales (10–20 km) → weak correlation

  • Fine scales (<10 km) → no correlation
    Birds and fish do not co‑occur reliably.

7.4 Interpretation

  • Birds go to the right region, but not necessarily the right spot.

  • Fish move too quickly at fine scales → mismatch.

7.5 Implication

You cannot use fish density as a proxy for bird density at fine scales.

8. Case Study 2: Celtic Sea (2015)

8.1 Species

  • Common guillemot

  • Manx shearwater

  • Prey: herring & sprat

8.2 Methods

  • Seabird observations

  • Echo sounders

  • Water column structure (mixed, stratified, frontal)

8.3 Results

  • Prey biomass highest in mixed water

  • Prey depth shallowest in mixed water

  • Prey prevalence highest in stratified water

  • Seabirds most abundant in frontal regions

8.4 Interpretation

Frontal zones provide the best trade‑off:

  • Enough prey

  • Prey shallow enough

  • Prey encountered frequently

Thus seabirds target optimal compromise zones, not maxima of any single variable.

9. Case Study 3: EcoWIND Accelerate Project (2022–2025)

9.1 Study area

  • Conwy Bay, North Wales

  • Very fine scale (<5 km)

9.2 Additional variables

  • Seabed habitat (substrate type)

  • Turbidity (important for offshore wind farm impacts)

9.3 Findings

  • Fish density similar across habitats

  • Fish prevalence (frequency of encountering schools) varied strongly

  • Seabirds targeted habitats with highest prevalence, not highest density

9.4 Interpretation

At very fine scales, seabirds prefer predictable prey, not abundant prey.

A single fish is enough to feed a chick → reliability > biomass.

10. Component 2: Seabird Movement Behaviour

Seabird movement is also scale‑dependent:

10.1 Large scale (100s km)

  • Birds use memory and experience to travel to productive regions.

10.2 Local scale (1–10 km)

  • Birds use:

    • Area‑restricted search (ARS)

    • Personal information (own experience)

    • Social information (following other birds)

These behaviours help them locate prey patches within productive regions.

11. Summary of Key Concepts

1. Physical features create prey hotspots

  • Large scale → abundance

  • Small scale → accessibility

2. Prey behaviour introduces unpredictability

  • Fish move constantly

  • Coincidence at fine scales is rare

3. Seabird behaviour adapts to this

  • Large scale: memory & experience

  • Fine scale: ARS, social cues, habitat selection

4. Result: Patchy seabird distributions

  • Birds cluster where prey is both present and catchable

  • These conditions occur only in small, transient patches