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Beyond the Field: R and predictive ecology

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  • Babanezhad, Hooman
  • Naqinezhad, Alireza

Abstract

Ecological modelling has advanced from basic mathematical models, focused on the dynamics of a single population, to multifaceted and predictive frameworks over a 50-year time span that range from individuals to entire biomes. The development of the open-source R programming language has greatly transformed this modelling advancement and has increased accessibility, transparency, and reproducibility. Furthermore, R has facilitated the integration of real-time data streams and advanced technologies, such as artificial intelligence and mechanistic modeling. This viewpoint describes the history of R, its contribution to contemporary predictive ecology, and the innovative workflow connecting in situ data and models. Looking forward, integrating R-based modeling frameworks with field expertise will be essential for producing actionable ecological insights, informing conservation and policy decisions, and addressing the challenges of rapidly changing ecosystems.

Suggested Citation

  • Babanezhad, Hooman & Naqinezhad, Alireza, 2026. "Beyond the Field: R and predictive ecology," Ecological Modelling, Elsevier, vol. 516(C).
    • Handle: RePEc:eee:ecomod:v:516:y:2026:i:c:s0304380026000979
    DOI: 10.1016/j.ecolmodel.2026.111568
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