IBASAM (Individual Based Atlantic SAlmon Model) is a simulation model, developed with an individual-based demo-genetic structure and integrating a significant amount of knowledge on [*Salmo salar*](http://www.fishbase.se/summary/Salmo-salar.html). To enhance realism, IBASAM has been developed in the framework of pattern-oriented modelling with multiple patterns validation at population levels using specific data collected over 15 yrs on the Scorff river, France. The genetic transmission of traits is included to allow evolutionary changes in Atlantic salmon life history.
# MODEL DESCRIPTION
See full description of the [IBASAM](model.md)
In the river phase, individuals grew in weight according to individual and stage-dependent growth capacity and influenced by water temperature, population density and river flow. Growth increments in weight were then allocated to fat reserves (Fat) or somatic growth through an increase in body length depending on a variable individual propensity to accumulate fat. Survival in the river was phase dependent, with higher mortality for maturing individuals and during winter. The triggering of sea migration was size dependent 6 months before the run. The smoltification process allows an individual that was in the river (‘parr’) to become physiologically ready to run into the sea (as ‘smolt’). The probability of smolting for an individual followed a reaction norm based on its body length.
-**How does IBASAM work?**
Once at sea, individuals grew in weight following a Gompertz function depending on specific individual characteristics and overall oceanic conditions. In this function, a NoiseSeat factor represented a daily environmental condition for growth. In the absence of EC, NoiseSeat was simply a normal random number centred on MeanNoiseSea = 1 and of variance 0 1. With EC, MeanNoiseSea decreased through time and NoiseSeat was a normal random number with variance 0 1 but centred on the MeanNoiseSea of the year. Each replicate of simulations had consequently different environmental conditions. Fat and body length accumulation were allocated as in the river phase. Survival at sea was size dependent with a clear disadvantage for small individuals.
IBASAM is made of 8 submodels representing fundamental biological processes :
1. Reproduction and reddcreation
2. Emergence from the redds and individual birth
3. Genetic coding and transmission
Six months before reproduction time for riverine parr or returning time for anadromous individuals, the increase in fat content over a temporal window was used as conditioning variable triggering maturation. For an individual j, the binary indicator of the maturation status Matj was set to 1 when its ProjectedFatTheoryj value was above the threshold of maturation pFmidj. This threshold was represented as the phenotypic expression of an underlying genetically coded trait. The later varied individually with an average level dependent on the sex and location of the individual (in river vs. at sea). The ProjectedFatTheoryj was calculated as a linear projection of Fatj over 6 months given the daily rate of change in Fatj of the individual over an evaluation window (61 days in spring for riverine parr, 47 days in autumn for anadromous individuals at sea) (Thorpe et al. 1998).
It also includes 2 environmental submodels :
10. River climate (Water temperature and flow)
11. Ocean climate
The various thresholds (sex and location dependent) were transmitted by the two parents of a fertilized egg to their progeny according to a bi-allelic multilocus system. Thus, for each threshold, each individual had two branches of 20 loci of 0 (unfavourable) or 1 (favourable) to code for the genetic value. The link between the genetic parameters and their phenotypic expression was controlled by a heritability value (h2). This heritability served to decompose the phenotypic variance of the thresholds between genetic and environmental components at the initialization of the simulations. The environmental variance was then applied on the phenotypic expression of the genetically coded thresholds (pFmid expression of gFmid with environmental noise). No mutations were assumed in the model.
For the sake of conciseness, all submodels are not extensively justified here. Please see [Wiki](https://github.com/Ibasam/IBASAM/wiki) and Piou et al. (2012) for further explanations and graphics of some of the mathematical functions used.
Fishery mortality on returning individuals was simulated by the removal of a proportion of each sea age class (1SW or MSW, base proportion of 15%) from the population at the end of summer step, that is after the observation of number of returns and proportions of MSW.
-**How to use IBASAM?**
The reproduction events were simulated according to relevant S. salar literature (Fleming 1996). The mating system allowed mature male parr to fertilize a fraction of the eggs. It selected anadromous males following size dominance while allowing satellite males to fertilize a significant fraction of the eggs. The number of egg per female was size dependent. Egg-to-emergence survival was water temperature, river flow and density dependent.
The IBASAM model was developed in C++ and interfaced as a shared library for R (R Development Core, 2010) to make easy the statistical analyses of model outputs. The C++ source codes and R scripts to create and use the model as R package are available online on Github. More detailed explanations are provided here:
## Biological processes
IBASAM was developed to cover the entire life cycle of S. salar. Thereby processes can be split into specific phases of the life cycle depending on the yearly events and the phases at which they happen. We structured the model in 8 submodels (SM) corresponding to life cycle events and processes:
1.[Reproduction and redd creation](reproduction.md)
2.[Emergence from the redds and individual birth](Emergence.md)
3.[Genetic coding and transmission](Genetic.md)
Growth and survival can be split into specific phases depending on the yearly events of the life cycle in the two time steps (summer and winter). The computational order of life cycle events and processes, together with their length (in days) when relevant, are presented in the figure below.
-**What is IBASAM’ goal?**
IBASAM is a cohesive and novel tool to assess the effect of potential stressors on evolutionary demography of Atlantic salmon. It includes a demo-genetic structure coupled with the explicit representation of individual variability and complex life histories.
## Environmental processes
10. River climate (Water temperature and flow)
11. Ocean climate
-**How to contribute to IBASAM?**
[Contribution guidelines for this project](docs/CONTRIBUTING.md)
[Contents of the folder](docs/contents.md)
Piou, C., Taylor, M. H., Papaïx, J., & Prévost, E. (2015). Modelling the interactive effects of selective fishing and environmental change on Atlantic salmon demogenetics. *Journal of Applied Ecology*, 52(6), 1629-1637. [Link](http://onlinelibrary.wiley.com/doi/10.1111/1365-2664.12512/abstract)
Piou, C., Prévost, E. (2013). Contrasting effects of climate change in continental vs. oceanic environments on population persistence and microevolution of Atlantic salmon. *Global Change Biology*, 19 (3) : 711-723. [Link](http://onlinelibrary.wiley.com/doi/10.1111/gcb.12085/abstract)
Piou, C. & Prévost, E. (2012) A demo-genetic individual-based model for Atlantic salmon populations: Model structure, parameterization and sensitivity. *Ecological Modelling*, 231, 37–52. [Link](http://www.sciencedirect.com/science/article/pii/S0304380012000543)
Changes in life-history traits have been observed in many exploited fish species over past decades. This led to the ‘fisheries-induced evolution’ hypothesis proposing that fisheries may be causing genetic changes to populations through selective harvesting. The submodel [**fishing**](fishing.md) allows to investigate the relative importance of selective fishing and environmental change scenarios on population.
This project is licensed under the terms of the GNU General Public License GPLV3.0.