Improving the realism of random walk movement analyses through the incorporation of habitat bias. Proulx, C., L., Proulx, L., & Blouin-Demers, G. Ecological Modelling, 269:18-20, Elsevier B.V., 2013. ![Improving the realism of random walk movement analyses through the incorporation of habitat bias [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website abstract bibtex The removal and fragmentation of natural landscapes by anthropogenic features have led to a decrease in biodiversity throughout the world. Spatial tools that use animal movement data are becoming increasingly important to determine the effects of landscape modifications on various processes related to population persistence. Several studies have found that the correlated random walk model is useful to investigate the spatial dynamics of animal populations. Here we present an Animal Movement Analysis program that uses a derivation of the random walk to model animal movement. Our Random Walk Generator allows the user to incorporate habitat bias in movement for an organism. The incorporation of habitat bias greatly improves the realism of the analysis of movement patterns via random walks, making it a better model to inform management decisions. ?? 2013 Elsevier B.V.
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abstract = {The removal and fragmentation of natural landscapes by anthropogenic features have led to a decrease in biodiversity throughout the world. Spatial tools that use animal movement data are becoming increasingly important to determine the effects of landscape modifications on various processes related to population persistence. Several studies have found that the correlated random walk model is useful to investigate the spatial dynamics of animal populations. Here we present an Animal Movement Analysis program that uses a derivation of the random walk to model animal movement. Our Random Walk Generator allows the user to incorporate habitat bias in movement for an organism. The incorporation of habitat bias greatly improves the realism of the analysis of movement patterns via random walks, making it a better model to inform management decisions. ?? 2013 Elsevier B.V.},
bibtype = {article},
author = {Proulx, Catherine L. and Proulx, Lorraine and Blouin-Demers, Gabriel},
journal = {Ecological Modelling}
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