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Global patterns of vascular plant alpha diversity.

Francesco Maria SabatiniBorja Jimenez-AlfaroUte JandtMilan ChytrýRichard FieldMichael KesslerJonathan LenoirFranziska SchrodtSusan K WiserMohammed A S Arfin KhanFabio AttoreLuis CayuelaMichele De SanctisJürgen DenglerSylvia HaiderMohamed Z HatimAdrian IndreicaFlorian JansenAníbal PauchardRobert K PeetPetr PetříkValério D PillarBrody SandelMarco SchmidtZhiyao TangPeter M Van BodegomKiril VassilevCyrille ViolleEsteban Alvarez-DavilaPriya DavidarJiří DoležalBruno HéraultAntonio Galán-de-MeraJorge JiménezStephan KambachSebastian Kepfer-RojasNathan KraftFelipe LezamaReynaldo Linares-PalominoAbel Monteagudo MendozaJustin K N'DjaOliver L PhillipsGonzalo Rivas-TorresPetr SklenářKarina L SpezialeBen J StrohbachRodolfo Vásquez MartínezHua-Feng WangKarsten WescheHelge Bruelheide
Published in: Nature communications (2022)
Global patterns of regional (gamma) plant diversity are relatively well known, but whether these patterns hold for local communities, and the dependence on spatial grain, remain controversial. Using data on 170,272 georeferenced local plant assemblages, we created global maps of alpha diversity (local species richness) for vascular plants at three different spatial grains, for forests and non-forests. We show that alpha diversity is consistently high across grains in some regions (for example, Andean-Amazonian foothills), but regional 'scaling anomalies' (deviations from the positive correlation) exist elsewhere, particularly in Eurasian temperate forests with disproportionally higher fine-grained richness and many African tropical forests with disproportionally higher coarse-grained richness. The influence of different climatic, topographic and biogeographical variables on alpha diversity also varies across grains. Our multi-grain maps return a nuanced understanding of vascular plant biodiversity patterns that complements classic maps of biodiversity hotspots and will improve predictions of global change effects on biodiversity.
Keyphrases
  • climate change
  • molecular dynamics
  • cell wall
  • molecular dynamics simulations
  • machine learning
  • big data
  • artificial intelligence