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Rosario: An algorithm to analyse cyclical data in Ecology.

Tatiana Velásquez-Roa1, Maria A Hurtado-Materon2, Angel L Robles-Fernández3

  • 1Integrative Ecology Lab, Biology Department, Texas State University. 601 University Dr., Texas, 78666., San Marcos, United States of America Integrative Ecology Lab, Biology Department, Texas State University. 601 University Dr., Texas, 78666. San Marcos United States of America.

Biodiversity Data Journal
|June 22, 2026
PubMed
Summary
This summary is machine-generated.

The Rosario algorithm is now available in R, enhancing ecological studies of temporal niche overlap. This statistical tool preserves temporal autocorrelation for realistic time-use scenarios and analyzes multiple species simultaneously.

Keywords:
diel activity patternsniche overlapniche partitioningnull modelphenologyseasonality.

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Area of Science:

  • Ecology
  • Computational Biology
  • Statistical Modeling

Background:

  • Temporal niche overlap is crucial for understanding ecological dynamics.
  • Null models are essential for analyzing ecological patterns by randomizing data.
  • Cyclical phenomena in ecology require specialized analytical tools.

Purpose of the Study:

  • To transition the established Rosario algorithm from Windows software to the R programming environment.
  • To enhance the accessibility and compatibility of temporal autocorrelation analysis within the R ecosystem.
  • To provide a robust tool for analyzing cyclical ecological data and temporal niche overlap.

Main Methods:

  • Implementation of the Rosario algorithm within the R programming language.
  • Preservation of temporal autocorrelation in generated time-use scenarios.
  • Development of a package supporting concurrent overlap analysis for multiple biological entities.

Main Results:

  • The Rosario algorithm is now available as an R package, improving usability and standardization.
  • The R package maintains biological realism in time-use scenarios.
  • The package facilitates concurrent overlap analysis across multiple individuals, species, or populations.

Conclusions:

  • The R version of Rosario enhances the analysis of temporal patterns and niche overlap in ecology.
  • This transition integrates temporal autocorrelation analysis with other R packages like 'activity' and 'overlap'.
  • The Rosario R package offers a comprehensive approach to studying cyclical data and interspecific temporal relationships.