Quantifying Tropical Plant Diversity Requires an Integrated Technological Approach.
DNA
artificial intelligence
plant biodiversity
spectroscopy
technology
tropical botany
Journal
Trends in ecology & evolution
ISSN: 1872-8383
Titre abrégé: Trends Ecol Evol
Pays: England
ID NLM: 8805125
Informations de publication
Date de publication:
12 2020
12 2020
Historique:
received:
09
05
2020
revised:
04
08
2020
accepted:
12
08
2020
pubmed:
12
9
2020
medline:
23
2
2021
entrez:
11
9
2020
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 32912632
pii: S0169-5347(20)30218-4
doi: 10.1016/j.tree.2020.08.003
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
1100-1109Informations de copyright
Copyright © 2020 Elsevier Ltd. All rights reserved.