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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
Global models and predictions of plant diversity based on advanced machine learning techniques
New Phytologist, Volume 237, No. 4, Year 2023
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Description
Despite the paramount role of plant diversity for ecosystem functioning, biogeochemical cycles, and human welfare, knowledge of its global distribution is still incomplete, hampering basic research and biodiversity conservation. Here, we used machine learning (random forests, extreme gradient boosting, and neural networks) and conventional statistical methods (generalized linear models and generalized additive models) to test environment-related hypotheses of broad-scale vascular plant diversity gradients and to model and predict species richness and phylogenetic richness worldwide. To this end, we used 830 regional plant inventories including c. 300 000 species and predictors of past and present environmental conditions. Machine learning showed a superior performance, explaining up to 80.9% of species richness and 83.3% of phylogenetic richness, illustrating the great potential of such techniques for disentangling complex and interacting associations between the environment and plant diversity. Current climate and environmental heterogeneity emerged as the primary drivers, while past environmental conditions left only small but detectable imprints on plant diversity. Finally, we combined predictions from multiple modeling techniques (ensemble predictions) to reveal global patterns and centers of plant diversity at multiple resolutions down to 7774 km2. Our predictive maps provide accurate estimates of global plant diversity available at grain sizes relevant for conservation and macroecology. © 2022 The Authors. New Phytologist © 2022 New Phytologist Foundation.
Authors & Co-Authors
Kreft, Holger
Germany, Gottingen
Georg-august-universität Göttingen
Taylor, Amanda
Germany, Gottingen
Georg-august-universität Göttingen
Schrader, Julian
Germany, Gottingen
Georg-august-universität Göttingen
Australia, Sydney
Macquarie University
Essl, Franz
Austria, Vienna
Universität Wien
van Kleunen, Mark
Germany, Konstanz
Universität Konstanz
China, Linhai
Taizhou University
Pergl, Jan
Czech Republic, Prague
Academy of Sciences of the Czech Republic
Pyšek, Petr
Czech Republic, Prague
Academy of Sciences of the Czech Republic
Czech Republic, Prague
Charles University
Stein, Anke
Germany, Konstanz
Universität Konstanz
Winter, Marten
Germany, Leipzig
German Centre for Integrative Biodiversity Research Idiv Halle-jena-leipzig
Barcelona, Julie F.
New Zealand, Christchurch
University of Canterbury
Fuentes, Nicol
Chile, Biobio
Universidad de Concepcion
Inderjit,
India, New Delhi
University of Delhi
Karger, Dirk Nikolaus
Switzerland, Birmensdorf
Eidgenössische Forschungsanstalt Für Wald, Schnee Und Landschaft Wsl
Kartesz, John T.
United States, Chapel Hill
Biota of North America Program
Nishino, Misako
United States, Chapel Hill
Biota of North America Program
Nickrent, Daniel Lee
United States, Ithaca
Cornell University
Nowak, Arkadiusz Sebastian
Poland, olsztyn wm
Uniwersytet Warminsko-mazurski w Olsztynie
Poland, Warszawa
Polish Academy of Sciences
Patzelt, Annette
Germany, Freising
Hochschule Weihenstephan-triesdorf
Pelser, Pieter B.
New Zealand, Christchurch
University of Canterbury
Wieringa, Jan J.
Netherlands, Leiden
Naturalis Biodiversity Center
Weigelt, Patrick
Germany, Gottingen
Georg-august-universität Göttingen
Statistics
Citations: 18
Authors: 21
Affiliations: 18
Identifiers
Doi:
10.1111/nph.18533
ISSN:
0028646X
Research Areas
Genetics And Genomics