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Movement Map distribution
Map distributions are activated when the movement.distribution.method.spX parameter is set to maps.
Species distribution maps can generally be obtained from niche modelling.
A single map distribution can be defined either using CSV or NetCDF files.
CSV maps parameters
| Parameter | Description |
|---|---|
| movement.randomwalk.range.sp# | Number of adjacent cells a species can use during random walk (foraging) |
| movement.file.map# | Name of the CSV file that contains the distribution map |
| movement.species.map# | Name of the species associated with the map. |
| movement.initialAge.map# | Minimum age (in years) when to use the map. |
| movement.lastAge.map# | Maximum age (in years) when to use the map. |
| movement.initialYear.map# | Minimum simulation time (in years) when to use the map. |
| movement.lastYear.map# | Maximum simulation time (in years) when to use the map. |
| movement.years.map# | Array of years during when to use the map. (instead of setting initial and final year) |
| movement.steps.map# | Array of time-steps during when to use the map |
NetCDF maps parameters
| Parameter | Description |
|---|---|
| movement.netcdf.enabled | True if NetCDF maps are provided |
| movement.species.map# | Species to which the movement map is associated |
| movement.file.map# | NetCDF file containing the spatial distribution maps |
| movement.nsteps.year.map# | Number of time steps per year associated with the file. |
| movement.initialAge.map# | Minimum age (in years) when to use the map. |
| movement.lastAge.map# | Maximum age (in years) when to use the map. |
| movement.variable.map# | Name of the NetCDF variable containing the spatial distribution file. |
One map is associated to a unique species for a given age span, year span and season. The full spatial distribution of a species can be represented using as many maps as necessary to cover different age spans and/or year spans and/or seasons. Let's now have a look at each parameter in detail.
Note that the CSV file has the same number of rows and columns as the OSMOSE grid. The distribution area can be defined using either a presence/absence map (1 for presence, 0 for absence) or a map of probability of presence (containing values ranging from 0 to values <1).
The same CSV file can be used to define different maps.
If the file path is set to null it means that the schools concerned by this map are out of the simulated domain
(e.g., migrating species).
% See the parameter mortality.out.rate.sp for mortality rate of species momentarily out of the simulated area.
When a school comes back to the simulated area, it will be randomly located on a new map (the one corresponding to the species and age class of the school at the current time step of the simulation).
Several maps can be defined for representing the spatial distribution of a single species. For example:
#Map 0
movement.map0.species = euphausiids
movement.map0.file = maps/mymap_euphau1.csv
movement.map0.age.min = 0
movement.map0.age.max = 0.2
movement.map0.year.min = 0
movement.map0.year.max = 40
movement.map0.season = 0;1;2;3;4;5;6;7;8;9;10;11;12;13;14;15;16;17;18;19;20;21;22;23
#Map 1
movement.map1.species = euphausiids
movement.map1.file = maps/mymap_euphau2.csv
movement.map1.age.min = 0.2
movement.map1.age.max = 1
movement.map1.year.min = 0
movement.map1.year.max = 40
movement.map1.season = 0;1;2;3;4;5;6;7;8;9
#Map 2
movement.map2.species = euphausiids
movement.map2.file = maps/mymap_euphau3.csv
movement.map2.age.min = 0.2
movement.map2.age.max = 1
movement.map2.year.min = 0
movement.map2.year.max = 40
movement.map2.season = 10;11;12;13;14;15;16;17;18;19;20;21;22;23
By increasing the number of maps, the description of the spatial distribution can be as detailed and refined as you want, as long as you have such information. It will allow for instance to create some maps for eggs (an egg in Osmose is a new school of age zero that is created during the reproduction process), some maps for the juveniles and some maps for the adults, as many as necessary to describe ontogenetic migrations.
From one time step to an other, the movement manager checks whether a given school remains in the same map or should "jump" to an other map (e.g. eggs map to juvenile map or adults in summer to adults in winter).
In the latter case (change of map), the schools are relocated randomly in the new map. The cell selection algorithm is as follows:
- A random cell is selected, whose probability value is
$P(i, j)$ - A random number is drafted, which is called
$R$ . - If
$P(i, j) < R \times P_{max}$ , the operation is repeated. Else, the cell is selected.
graph TD;
id1["Random draft of <br>cell (probability P)"]
id2("Random draft of value<br>between 0, 1 (value R)")
id3{P < R x Pmax ?}
id4(Select cell)
id1 --> id2
id2 --> id3
id3 -->|True| id4
id3 -->|False| id1
In the former case (same map), the movement manager mimics foraging movement with a random-walk that moves schools to immediately adjacent cells within their distribution area.