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Functional rarity and evenness are key facets of biodiversity to boost multifunctionality.

Yoann Le Bagousse-PinguetNicolas GrossHugo SaizFernando T MaestreSonia RuizMarina DacalSergio AsensioVictoria OchoaBeatriz GozaloJohannes H C CornelissenLucas DeschampsCarlos GarcíaVincent MaireRubén MillaNorma SalinasJun-Tao WangBrajesh K SinghPablo García-Palacios
Published in: Proceedings of the National Academy of Sciences of the United States of America (2021)
The functional traits of organisms within multispecies assemblages regulate biodiversity effects on ecosystem functioning. Yet how traits should assemble to boost multiple ecosystem functions simultaneously (multifunctionality) remains poorly explored. In a multibiome litter experiment covering most of the global variation in leaf trait spectra, we showed that three dimensions of functional diversity (dispersion, rarity, and evenness) explained up to 66% of variations in multifunctionality, although the dominant species and their traits remained an important predictor. While high dispersion impeded multifunctionality, increasing the evenness among functionally dissimilar species was a key dimension to promote higher multifunctionality and to reduce the abundance of plant pathogens. Because too-dissimilar species could have negative effects on ecosystems, our results highlight the need for not only diverse but also functionally even assemblages to promote multifunctionality. The effect of functionally rare species strongly shifted from positive to negative depending on their trait differences with the dominant species. Simultaneously managing the dispersion, evenness, and rarity in multispecies assemblages could be used to design assemblages aimed at maximizing multifunctionality independently of the biome, the identity of dominant species, or the range of trait values considered. Functional evenness and rarity offer promise to improve the management of terrestrial ecosystems and to limit plant disease risks.
Keyphrases
  • genome wide
  • climate change
  • human health
  • genetic diversity
  • dna methylation
  • multidrug resistant
  • machine learning
  • risk assessment
  • deep learning
  • artificial intelligence