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A Spatial Signal of Niche Differentiation in Tropical Forests

  • Stony Brook University
  • University of the Balearic Islands
  • Harvard University
  • University of Illinois at Urbana-Champaign

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Explaining diversity in tropical forests remains a challenge in community ecology. Theory tells us that species differences can stabilize communities by reducing competition, while species similarities can promote diversity by reducing fitness differences and thus prolonging the time to competitive exclusion. Combined, these processes may lead to clustering of species such that species are niche differentiated across clusters and share a niche within each cluster. Here, we characterize this partial niche differentiation in a tropical forest in Panama by measuring spatial clustering of woody plants and relating these clusters to local soil conditions. We find that species were spatially clustered and the clusters were associated with specific concentrations of soil nutrients, reflecting the existence of nutrient niches. Species were almost twice as likely to recruit in their own nutrient niche. A decision tree algorithm showed that local soil conditions correctly predicted the niche of the trees with up to 85% accuracy. Iron, zinc, phosphorus, manganese, and soil pH were among the best predictors of species clusters.

Original languageEnglish
Pages (from-to)445-457
Number of pages13
JournalAmerican Naturalist
Volume203
Issue number4
DOIs
StatePublished - Apr 2024

Keywords

  • Barro Colorado Island
  • machine learning
  • niche differentiation
  • soil nutrients
  • spatial clusters
  • tropical forests

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