The ‘Ostats’ package calculates overlap statistic to measure the
degree of community-level trait overlap by fitting nonparametric kernel
density functions to each species’ trait distribution and calculating
their areas of overlap (Mouillot et al. 2005, Geange et al. 2011, Read
et al. 2018). For instance, the median pairwise overlap for a community
is calculated by first determining the overlap of each species pair in
trait space, and then taking the median overlap of each species pair in
a community. This median overlap value is called the O-statistic (O for
overlap). The Ostats()
function calculates separate
univariate overlap statistics for each trait, while the
Ostats_multivariate()
function calculates a single
multivariate overlap statistic for all traits. O-statistics can be
evaluated against null models to obtain standardized effect sizes. Grady
et al. (2018) provide a teaching module that goes into detail about how
to interpret the results presented in Read et al. (2018).
‘Ostats’ is part of the collaborative Macrosystems Biodiversity Project Local- to continental-scale drivers of biodiversity across the National Ecological Observatory Network (NEON). For more information on this project, see the Macrosystems Biodiversity Website.
To install the stable version of the package from CRAN, type the following into your R prompt.
install.packages('Ostats')
The development version of the package has more recent updates but may not be as thoroughly tested as the stable CRAN version. To install the development version, type the following into your R prompt.
remotes::install_github('NEON-biodiversity/Ostats')
See the Ostats introduction vignette for more information.
National Science Foundation Division of Environmental Biology (Population & Community Ecology, MacroSysBIO & NEON-Enabled Science); Awards to P.L. Zarnetske (Michigan State University); S. Record (Bryn Mawr College); Ben Baiser (University of Florida); Angela Strecker (Western Washington University).
The National Ecological Observatory Network is a program sponsored by the National Science Foundation and operated under cooperative agreement by Battelle. This material is based in part upon work supported by the National Science Foundation through the NEON Program.
Geange, S.W., S. Pledger, K.C. Burns, and J.S. Shima. 2011. A unified analysis of niche overlap incorporating data of different types. Methods in Ecology and Evolution 2(2):175-184. https://doi.org/10.1111/j.2041-210X.2010.00070.x
Grady, J.M., Q.D. Read, S. Record, P.L. Zarnetske, B. Baiser, K. Thorne, and J. Belmaker. 2018. Size, niches, and the latitudinal diversity gradient. Teaching Issues and Experiments in Ecology 14: Figure Set #1.
Mouillot, D., W. Stubbs, M. Faure, O. Dumay, J.A. Tomasini, J.B. Wilson, and T. Do Chi. 2005. Niche overlap estimated based on quantitative functional traits: A new family of non-parametric indices. Oecologia 145(3):345-353. https://doi.org/10.1007/s00442-005-0151-z
Read, Q.D., J.M. Grady, P.L. Zarnetske, S. Record, B. Baiser, J. Belmaker, M.-N. Tuanmu, A. Strecker, L. Beaudrot, and K.M. Thibault. 2018. Among-species overlap in rodent body size distributions predicts species richness along a temperature gradient. Ecography 41(10):1718-1727. https://doi.org/10.1111/ecog.03641