c(
person("Andrew", "Marx", , "andrewjmarx@ufl.edu", role = c("aut", "cre", "cph"),
comment = c(ORCID = "0000-0002-7456-1631")
),
person("Robert", "Fletcher", , , role = c("ctb"),
comment = c(ORCID = "0000-0003-1717-5707")
),
person("Miguel", "Acevedo", , , role = c("ctb"),
comment = c(ORCID = "0000-0002-8289-1497")
),
person("Jorge", "Sefair", , , role = c("ctb"),
comment = c()
),
person("Chao", "Wang", , , role = c("ctb"),
comment = c()
)
)
An implementation of the framework described in "Toward a unified
framework for connectivity that disentangles movement and mortality in space
and time" by Fletcher et al. (2019) <doi:10.1111/ele.13333>.
Incorporates both resistance and absorption with spatial absorbing Markov
chains (SAMC) to provide several short-term and long-term predictions for
metrics related to connectivity in landscapes.
knitr, rmarkdown, testthat, ggplot2, png, viridis, gifski,
gganimate
'RcppExports.R' 'samc-class.R' 'check.R' 'data.R'
'visitation.R' 'dispersal.R' 'distribution.R' 'map.R'
'mortality.R' 'samc.R' 'survival.R'
Andrew Marx [aut, cre, cph] (<https://orcid.org/0000-0002-7456-1631>),
Robert Fletcher [ctb] (<https://orcid.org/0000-0003-1717-5707>),
Miguel Acevedo [ctb] (<https://orcid.org/0000-0002-8289-1497>),
Jorge Sefair [ctb],
Chao Wang [ctb]

'RcppExports.R' 'samc-class.R' 'check.R' 'data.R'
'visitation.R' 'dispersal.R' 'distribution.R'
'internal-functions.R' 'map.R' 'mortality.R' 'samc.R'
'survival.R'

'RcppExports.R' 'samc-class.R' 'check.R' 'cond_passage.R'
'data.R' 'visitation.R' 'dispersal.R' 'distribution.R'
'internal-functions.R' 'locate.R' 'map.R' 'mortality.R'
'samc.R' 'survival.R'

Implements functions for working with absorbing Markov chains. The
implementation is based on the framework described in "Toward a unified
framework for connectivity that disentangles movement and mortality in space
and time" by Fletcher et al. (2019) <doi:10.1111/ele.13333>, which applies
them to spatial ecology. This framework incorporates both resistance and
absorption with spatial absorbing Markov chains (SAMC) to provide several
short-term and long-term predictions for metrics related to connectivity in
landscapes. Despite the ecological context of the framework, this package
can be used in any application of absorbing Markov chains.