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Description

O-Stats, or Pairwise Community-Level Niche Overlap Statistics.

O-statistics, or overlap statistics, measure the degree of community-level trait overlap. They are estimated by fitting nonparametric kernel density functions to each species’ trait distribution and calculating their areas of overlap. 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. '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 (<https://neon-biodiversity.github.io/>). Calculation of O-statistics is described in Read et al. (2018) <doi:10.1111/ecog.03641>, and a teaching module for introducing the underlying biological concepts at an undergraduate level is described in Grady et al. (2018) <http://tiee.esa.org/vol/v14/issues/figure_sets/grady/abstract.html>.

Ostats: O-statistics, or Pairwise Community-Level Niche Overlap Statistics

cranchecks rstudio mirrordownloads Project Status: Active – The project has reached a stable, usablestate and is being activelydeveloped. CRANstatus DOI

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.

Authors

  • Quentin D. Read
  • Arya Yue
  • Isadora E. Fluck
  • Benjamin Baiser
  • John M. Grady
  • Phoebe L. Zarnetske
  • Sydne Record

How to install

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')

Getting started

See the Ostats introduction vignette for more information.

Funding

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.

NSF-1926567 NSF-1926568 NSF-1926569 NSF-1926610

References

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

Metadata

Version

0.2.0

License

Unknown

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