Quantifying Tropical Plant Diversity Requires an Integrated Technological Approach

Frederick C. Draper, Timothy R. Baker, Christopher Baraloto, Jerome Chave, Flavia Costa, Roberta E. Martin, R. Toby Pennington, Alberto Vicentini, Gregory P. Asner

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

Tropical biomes are the most diverse plant communities on Earth, and quantifying this diversity at large spatial scales is vital for many purposes. As macroecological approaches proliferate, the taxonomic uncertainties in species occurrence data are easily neglected and can lead to spurious findings in downstream analyses. Here, we argue that technological approaches offer potential solutions, but there is no single silver bullet to resolve uncertainty in plant biodiversity quantification. Instead, we propose the use of artificial intelligence (AI) approaches to build a data-driven framework that integrates several data sources – including spectroscopy, DNA sequences, image recognition, and morphological data. Such a framework would provide a foundation for improving species identification in macroecological analyses while simultaneously improving the taxonomic process of species delimitation.

Original languageEnglish (US)
Pages (from-to)1100-1109
Number of pages10
JournalTrends in Ecology and Evolution
Volume35
Issue number12
DOIs
StatePublished - Dec 2020

Keywords

  • DNA
  • artificial intelligence
  • plant biodiversity
  • spectroscopy
  • technology
  • tropical botany

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics

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