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Orientador(es)
Resumo(s)
Dispersal of organisms is a ubiquitous aspect of the natural world, with wide implications across scales and
organization levels. Interest in dispersal has risen sharply over the past 30 years, mostly due to the multiple and
rapid global changes ecosystems face. Among the various aspects that may characterize a dispersion event,
dispersal distance is considered a key descriptor in a wide variety of studies across taxonomic groups. Typically,
dispersal distances are defined in the form of dispersal kernels describing the dispersal distance distribution
according to probability density functions. Although numerous methods providing dispersal data exist, there is
still a lack of intuitive and comprehensive approaches and tools to estimate dispersal kernels from such data.
Here we present the dispfit package, an R software application developed to fill this gap. dispfit fits and compares
different families of parameterized functions to describe and predict dispersal distances. It includes 9 well-known
and commonly used distributions, computes goodness-of-fit and model selection statistics, and estimate each
distribution's parameters, along with their first four moments (mean, standard deviation, skewness, and kurtosis).
We describe the main functions included in dispfit and provide an example to illustrate the workflow of the
typical analyses performed within the package. We believe that dispfit will critically contribute to improving the
modelling of species' dispersal distances, thus enhancing the understanding of the ecological and evolutionary
processes involving dispersal movement.
Descrição
Palavras-chave
dispersal distance dispersal kernel distribution function model selection species movement
Contexto Educativo
Citação
Proença-Ferreira, António, et al. “dispfit: An R package to estimate species dispersal kernels.” Ecological Informatics, vol. 75, July 2023, p. 102018.
Editora
Elsevier
