binCounts

A convenience function to count the values (optionally log-transformed) falling within given equal-range bins.

Provides functions to generate and analyze spatially-explicit individual-based multistate movements in rivers,
heterogeneous and homogeneous spaces. This is done by incorporating landscape bias on local behaviour, based on
resistance rasters. Although originally conceived and designed to simulate trajectories of species constrained to
linear habitats/dendritic ecological networks (e.g. river networks), the simulation algorithm is built to be
highly flexible and can be applied to any (aquatic, semi-aquatic or terrestrial) organism, independently on the
landscape in which it moves. Thus, the user will be able to use the package to simulate movements either in
homogeneous landscapes, heterogeneous landscapes (e.g. semi-aquatic animal moving mainly along rivers but also using
the matrix), or even in highly contrasted landscapes (e.g. fish in a river network). The algorithm and its input
parameters are the same for all cases, so that results are comparable. Simulated trajectories can then be used as
mechanistic null models (Potts & Lewis 2014, <DOI:10.1098/rspb.2014.0231>) to test a variety of 'Movement Ecology'
hypotheses (Nathan et al. 2008, <DOI:10.1073/pnas.0800375105>), including landscape effects (e.g. resources,
infrastructures) on animal movement and species site fidelity, or for predictive purposes (e.g. road mortality risk,
dispersal/connectivity). The package should be relevant to explore a broad spectrum of ecological phenomena, such as
those at the interface of animal behaviour, management, landscape and movement ecology, disease and invasive species
spread, and population dynamics.

Miguel Porto

SiMRiv

Simulating Multistate Movements in River/Heterogeneous
Landscapes

Lorenzo Quaglietta

Erida Gjini

binCounts function

<dl> <dt>data</dt>
<dd>a numeric vector with the data.</dd> <dt>range</dt>
<dd>the closed data range in which to divide bins, as a two-element numeric vector. Values falling outside <code>range</code> are discarded.</dd> <dt>nbins</dt>
<dd>the number of bins to split the data. Result is guaranteed to have this number of bins, irrespective of data.</dd> <dt>log</dt>
<dd>whether or not to log-transform data and ranges before binning.</dd></dl>

Arguments

Count values in given bins — binCounts

<dl>

 <dt>data</dt>
<dd>a numeric vector with the data.</dd>

 <dt>range</dt>
<dd>the closed data range in which to divide bins, as a two-element numeric vector. Values falling outside <code>range</code> are discarded.</dd>

 <dt>nbins</dt>
<dd>the number of bins to split the data. Result is guaranteed to have this number of bins, irrespective of data.</dd>

 <dt>log</dt>
<dd>whether or not to log-transform data and ranges before binning.</dd>

</dl>

binCounts: Count values in given bins

Description

Usage

Value

Arguments

Details

See Also