Inferring plant ecosystem organization from species occurrences

S. Azaele, R. Muneepeerakul, A. Rinaldo, I. Rodriguez-Iturbe

    Research output: Contribution to journalArticlepeer-review

    30 Scopus citations


    In this paper, we present an approach capable of extracting insights on ecosystem organization from merely occurrence (presence/absence) data. We extrapolate to the collective behavior by encapsulating some simplifying assumptions within a given set of constraints, and then examine their ecological implications. We show that by using the mean occurrence and co-occurrence of species as constraints, one is able to capture detailed statistics of a plant community distributed across a vast semiarid area of the United States. The approach allows us to quantify the species' effective couplings: Their frequencies exhibit a peak at zero and the minimal pairwise model is able to capture about 80% of the ecosystem structure. Our analysis reveals a relatively stronger impact of the species network on uncommon species and underscores the importance of species pairs experiencing positive couplings. Additionally, we study the associations among species and, interestingly, find that the frequencies of groups of different species, which the approach is able to capture, exhibit a power-law-like distribution.

    Original languageEnglish (US)
    Pages (from-to)323-329
    Number of pages7
    JournalJournal of Theoretical Biology
    Issue number2
    StatePublished - Jan 21 2010


    • Ecological interactions
    • Ising model
    • Maximum entropy
    • Occurrence data
    • Power law
    • Species associations

    ASJC Scopus subject areas

    • Statistics and Probability
    • Modeling and Simulation
    • Biochemistry, Genetics and Molecular Biology(all)
    • Immunology and Microbiology(all)
    • Agricultural and Biological Sciences(all)
    • Applied Mathematics


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