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Greedy nearest-neighbor approach to quantify site revisitation: Comparing two sympatric raven species

Bar Ashkenazi1,2,3,*, Miguel de Guinea2,3,*, Michael Assaf1,†, and Ran Nathan2,3,‡

  • *These authors contributed equally to this work.
  • †Contact author: michael.assaf@mail.huji.ac.il
  • ‡Contact author: ran.nathan@mail.huji.ac.il
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Phys. Rev. Research 8, 043149 – Published 10 November, 2026

DOI: https://doi.org/10.1103/z84g-799z

Abstract

A central challenge in movement ecology is to describe ecologically meaningful residence sites from raw tracking data due to heterogeneous sampling frequency and uncertain site boundaries. Here, we develop a greedy nearest-neighbor clustering approach with local reassignment and polygon-based site construction that generates timestamped sequences of site visits for each tracked individual, and apply it to 9 years of global positioning system (GPS) data from two sympatric raven species in the Dead Sea region—the fan-tailed raven (Corvus rhipidurus) and the brown-necked raven (C. ruficollis). Using the resulting visitation sequences, we quantify recursion patterns using the non-Markovian individual mobility model (IMM), which captures the balance between novel-site discovery β and preferential return α. The inferred dynamics are consistent with IMM predictions and reveal clear interspecific differences: brown-necked ravens continue to discover new sites at a higher rate (lower β), whereas fan-tailed ravens show a steeper concentration of visits among top-ranked sites. Entropy analyses further separate the species, with brown-necked ravens exhibiting higher site entropy and higher conditional entropy of site-to-site transitions. Together, these results provide a robust framework for describing interspecific differences in movement strategies that can be used to infer memory from GPS data and suggest distinct space-use strategies in two closely related sympatric species.

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Phys. Rev. Research 8, 043149– Published 10 November, 2026
  • Received 28 February 2026
  • Accepted 24 September 2026
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