# Adds an adaptability constraint to a scenario object

Source:`R/add_constraint.R`

`add_constraint_adaptability.Rd`

Adaptability constraints assume that suitable habitat for species in (future) projections might be unsuitable if it is outside the range of conditions currently observed for the species.

Currently only `nichelimit`

is implemented, which adds a simple constrain on
the predictor parameter space, which can be defined through the
`"value"`

parameter. For example by setting it to `1`

(Default),
any projections are constrained to be within the range of at maximum 1
standard deviation from the range of covariates used for model training.

## Usage

```
add_constraint_adaptability(
mod,
method = "nichelimit",
names = NULL,
value = 1,
increment = 0,
...
)
# S4 method for class 'BiodiversityScenario'
add_constraint_adaptability(
mod,
method = "nichelimit",
names = NULL,
value = 1,
increment = 0,
...
)
```

## Arguments

- mod
A

`BiodiversityScenario`

object with specified predictors.- method
A

`character`

indicating the type of constraints to be added to the scenario. See details for more information.- names
A

`character`

vector with names of the predictors for which an adaptability threshold should be set (Default:`NULL`

for all).- value
A

`numeric`

value in units of standard deviation (Default:`1`

).- increment
A

`numeric`

constant that is added to value at every time step (Default:`0`

). Allows incremental widening of the niche space, thus opening constraints.- ...
passed on parameters. See also the specific methods for adding constraints.

## See also

Other constraint:
`add_constraint()`

,
`add_constraint_MigClim()`

,
`add_constraint_boundary()`

,
`add_constraint_connectivity()`

,
`add_constraint_dispersal()`

,
`add_constraint_minsize()`

,
`add_constraint_threshold()`

,
`simulate_population_steps()`

## Examples

```
if (FALSE) { # \dontrun{
scenario(fit) |>
add_constraint_adaptability(value = 1)
} # }
```