dc.creatorMorales, Juan Manuel
dc.creatorDi Virgilio, Agustina Soledad
dc.creatordel Mar Delgado, María
dc.creatorOvaskainen, Otso
dc.date.accessioned2018-11-16T18:38:06Z
dc.date.accessioned2022-10-15T05:57:06Z
dc.date.available2018-11-16T18:38:06Z
dc.date.available2022-10-15T05:57:06Z
dc.date.created2018-11-16T18:38:06Z
dc.date.issued2017-09
dc.identifierMorales, Juan Manuel; Di Virgilio, Agustina Soledad; del Mar Delgado, María; Ovaskainen, Otso; A General Approach to Model Movement in (Highly) Fragmented Patch Networks; Amer Statistical Assoc & Int Biometric Soc; Journal Of Agricultural Biological And Environmental Statistics; 22; 3; 9-2017; 393-412
dc.identifier1085-7117
dc.identifierhttp://hdl.handle.net/11336/64631
dc.identifierCONICET Digital
dc.identifierCONICET
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4352402
dc.description.abstractLandscape heterogeneity can often be represented as a series of discrete habitat or resource patches surrounded by a matrix of non-habitat. Understanding how animals move in such networks of patches is important for many theoretical and applied questions. The probability of going from one patch to another is affected in a non-trivial way by the characteristics and location of other patches in the network. Nearby patches can compete as possible destinations, and a particular patch can be shadowed by neighboring patches. We present a way to account for the effects of the spatial configuration of patches in models of space use where individuals alternate between spending time in a patch and moving to other patches in the network. The approach is based on the original derivation of Ovaskainen and Cornell (J Appl Probab 40:557–580, 2003) for a diffusion model that considered all possible ways in which an individual leaving a particular patch can eventually reach another patch before dying or leaving the patch network. By replacing the theoretical results of Ovaskainen and Cornell by other appropriate functions, we provide generality and thus make their approach useful in contexts where diffusion is not a good approximation of movement. Furthermore, we provide ways to estimate time spent in the non-habitat matrix when going from patch to patch and implement a method to incorporate the effect of the history of previous visits on future patch use. We present an MCMC way to fit these models to data and illustrate the approach with both simulated data and data from sheep moving among seasonally flooded meadows in northern Patagonia.Supplementary materials accompanying this paper appear online.
dc.languageeng
dc.publisherAmer Statistical Assoc & Int Biometric Soc
dc.relationinfo:eu-repo/semantics/altIdentifier/url/http://link.springer.com/10.1007/s13253-017-0298-1
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.1007/s13253-017-0298-1
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectLANDSCAPE CONNECTIVITY
dc.subjectMEMORY
dc.subjectMETAPOPULATION
dc.subjectPATCH TRANSITION
dc.subjectSPATIAL CONFIGURATION
dc.titleA General Approach to Model Movement in (Highly) Fragmented Patch Networks
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/publishedVersion


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