Biogeographical boundaries and Monmonier’s algorithm: a case study in the northern Neotropics


  • Michael A. Patten,

    Corresponding author
    1. Oklahoma Biological Survey and Sutton Avian Research Center, University of Oklahoma, 111 E. Chesapeake Street, Norman, OK 73019, USA
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  • Brenda D. Smith-Patten

    1. Sam Noble Oklahoma Museum of Natural History, University of Oklahoma, 2401 Chautauqua Avenue, Norman, OK 73072, USA
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*Michael A. Patten, Oklahoma Biological Survey, University of Oklahoma, 111 E. Chesapeake Street, Norman, OK 73019, USA. E-mail:


Aim  To use Monmonier’s algorithm, a spatially explicit technique, to elucidate positions of biogeographical boundaries in the northern Neotropics.

Location  The northern Neotropics (Isthmus of Tehuantepec, Mexico, south to trans-Andean Colombia).

Methods  We compiled avifaunal lists for 36 forested sites from the literature, museum records, field notes, and web sources. We constructed distance matrices as inverse Jaccard’s similarity, used Monmonier’s algorithm to place biogeographical boundaries, and created bootstrap matrices to determine the relative strength of boundaries.

Results  Biogeographical boundaries with the best support separated lowland (< 1000 m) and montane sites and areas with a distinct historical background, such as seaways, suture zones, volcanic peaks, and former islands.

Main conclusions  Monmonier’s algorithm used with distance (dissimilarity) data effectively identified biogeographical boundaries consistent with historical processes and with past research. Montane sites tended to be circumscribed by sharp boundaries, emphasizing their isolation and higher endemism. Lowland sites, by contrast, tended to be homogeneous, suggesting that dispersal has played a much larger role at low elevations. Former seaways, as in the Nicaraguan Depression and extended Bay of Urabá, yielded boundaries, but typically for highland avifauna only. In addition to providing a rigorous (bootstrap support) and heuristic (direct mapping) means of locating biotic boundaries, Monmonier’s algorithm can be a valuable tool for conservation planning.