Overview of sandeel modelling componets

IBMlib: A generic particle tracking package
SLAM: Sandeel Larval Advection Model: sandeel module in IBMlib
SPAM: Sandeel Population Analysis Model: population component ontop SLAM closing the sandel life cycle

IBMlib:

Input:  any database of physical+biogeochemical fields.
State variables: position and condition variables for an ensemble of particles.
Output: particle transport coefficients condition state (e.g. growth, life history attributes), particle survival coefficients.
Synopsis: generic particle tracking library in Fortran 90. Emphasis on object oriented code structure and canonical interfaces.
Functionality:
Input: single control file with distributed reading in flexible tag based format.
Particle initialization: space + time release event operators allows fairly complex particle ensemble releases.
Particle tracking: miscellaneous standard Lagrangian advection + random walk diffusion algorithms.
Output/post processing: data dump subroutines elementary particle ensemble analysis.  Standard code build and command line invocation.  Templates illustrating usage are available.
                                   

SLAM:

Sandeel module in IBMlib implementing current knowledge on sandeel larval biology
Input: any database of physical + biochemical fields (e.g. ECOSMO).
State variables: position, growth, life history attributes.
Output: particle transport paths and history.

Post processing tools allows onversion of particle transport paths into a virtual transport kernel and projection onto transport matrices (T) corresponding to any regional definition. Bioenergetic component computes indices of survival, given successful transport (A). A transport and survival matrix conveys direct impact of climate change on early life stages.

SPAM:

Forward time population simulation component on top of SLAM closes the sandeel life cycle.>

Transport matrices and carrying capacity display direct climate response, predation, fishing pressure and indirect climate response.

Input:    
Spatial/temporary interregional transport matrices (possibly constant in time) 
Spatial/temporary resolved predation pressure (possibly constant in space/time)
Spatial/temporary resolved fishing   pressure (possibly constant in space/time) 
Spatial/temporary resolved carrying capacity (possibly constant in time)

State variables:
Population size and weight resolved on habitable regions and age cohorts at time.

Output:
Population dynamics resolved on habitable regions and age cohorts.
Recruitment resolved on habitable regions.
Catch resolved on habitable regions.
Biomass resolved on habitable regions and age cohorts at time.
Demographic self regulation index resolved on habitable regions at time.

Synopsis:
Formulated independently of any particular definition of habitable regions.
Implemented as object-oriented python super classes with many sub classes realising particular situations.
The model typically runs with spatial resolution 10-100 km.
The model includes adult migration and demographic density effects on growth, survival and fecundity.