Modelling Vertebrates

Beth Fulton2012

End to End Model

Difference equation− time step assumed (“agreed upon”)

Differential equation− instantaneous (or really tiny time slices)

D.E.

Life history

Biomass

Aggregate Biomass

Recruitment, Migration& Growth

Mortality & metabolism

e.g. Ecopath

Numbers

Abundance

Recruitment& Migration

Mortality

Age Structure

Aging & Growth

Recruitment

Mortality

Stock assessments

Can be “simple” (just age structure) Can be complex (spatial, genetic stocks etc)

Age Structure

Disease/Oxygen limitationVertebrate

Reserve Structure

Nutrients Detritus

Pred CPred B

Pred A

Prey CPrey B

Prey A

Prey availability

Gape limitation

Reproduction

Age structure & Condition

Basic form:

Senescence and disease considered Age structured (age phases; distribution within phases)

− computationally efficient− allows ontogenetic shifts, recovery delay, overfishing

effects Gape limited & can starve (condition impacts survival and

reproduction)

j

Bjolp

spaceoassimpVV

vMMMB

dtdB

,2

oxygen deficient, starvation or quadratic

Atlantis

Transition matrices Explicit formulations (density & food dependent; sedentary; forced; mixed)

Weighting for seasonal migrations (can migrate in & out of model domain)

Smooth and interpolate old to new based on cruising speed

Kalman filter Vertical movements

Movement

‘Stock-recruitment’ relationships

Adults

Rec

ruits

Beverton Holt

Fixed # offspring / adult

Ricker

Reproduction

Others = lognormal, plankton-based…

‘Stock-recruitment’ relationships Based on parental condition and environmental

characteristics (e.g. temp or salinity) Live birth and parental care

Reproduction

Maternal Care

‘Stock-recruitment’ relationships Based on parental condition and environmental

characteristics (e.g. temp or salinity) Live birth and maternal care Young of year recruits

− no explicit larval phase (miss predator-prey switch unless use plankton-based recruitment)

Explicit larvae (advection or connectivity matrices)

Reproduction

Forced distributions

Movement

Forced (seasonal) distributions Density or forage dependent Sedentary Mixed Seasonal migrations must intersect with prey or starve spawn near rearing habitat or juveniles eaten

Movement

Forced (seasonal) distributions Density or forage dependent Sedentary Mixed Seasonal migrations must intersect with prey or starve spawn near rearing habitat or juveniles eaten

Include if needed to represent ecology of interest

− vertical (access prey, benthopelagic coupling), seasonal (within model), migration (out of domain)

Movement

Non-zero values = commitment− interaction that seems unimportant may become critical

Connections can have non-symmetric impacts Use local (cogener) data preferentially Size-relationships predator-prey are consistent across systems Stomach content problems (soft bodies digest rapidly, patchy data, too few links can impact predictions) Isotopes

Diets

Diet Time Series

e.g. seabirds (ontogeny, seasonal migrations)

Quillfeldt et al 2010

Diet & Migration

Bowhead whales – Northern Pacific

Hobson et al 2010

Diet & Migration

Ontogenetic shifts Flexible in space and time

Model vs Obs

Modelling theory

System dynamics

Impacts of perturbation

Form of effective management

− vision statements vs realised

outcomes

− effective monitoring

− ecosystem-based management

− multiple use management

Questions tackled

Atlantis – What, How, Why

small pelagicssquid

zooplankton

baleen whales

birds

pelagic sharks toothed whales

pelagic fish

demersal fish

demersal sharks

infauna

macrophytes

filter feeders zoobenthos

detritus

jellies

phytoplankton

1910

Community Structure

Atlantis – What, How, Why

1910

Atlantis – What, How, Why

2000

Primary Producers

Zooplankton Jellies Squid BenthosForage

FishDemersal Fish Top Predators

2

-6

Inde

x of

eff

ect

size

Temperature + Acidification

Griffiths et al (in review)

Antagonistic interaction

Synergistic interaction

All human pressures together

Interacting Stressors

Audzjionyte et al (in review)

> 20% fishing mortality per year = selecting for smaller fish

FECUNDITY

10-50%

50-90%

Evolution

Evolution

Audzjionyte et al (in review)

Mortality implications

Evolution

Audzjionyte et al (in review)

Biomass implications Predator-prey implications Distribution implications

Possible, but heterogeneity hard… better to use ABM

Behaviour

Thank you