Open AccessHow do trees respond to species mixing in experimental compared to observational studies?
Author(s) -
Kambach Stephan,
Allan Eric,
BilodeauGauthier Simon,
Coomes David A.,
Haase Josephine,
Jucker Tommaso,
Kunstler Georges,
Müller Sandra,
Nock Charles,
Paquette Alain,
Plas Fons,
Ratcliffe Sophia,
Roger Fabian,
RuizBenito Paloma,
SchererLorenzen Michael,
Auge Harald,
Bouriaud Olivier,
Castagneyrol Bastien,
Dahlgren Jonas,
Gamfeldt Lars,
Jactel Hervé,
Kändler Gerald,
Koricheva Julia,
Lehtonen Aleksi,
Muys Bart,
Ponette Quentin,
Setiawan Nuri,
Van de Peer Thomas,
Verheyen Kris,
Zavala Miguel A.,
Bruelheide Helge
Publication year - 2019
Publication title -
ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.17
H-Index - 63
ISSN - 2045-7758
DOI - 10.1002/ece3.5627
Subject(s) - biodiversity , tree (set theory) , ecology , species diversity , productivity , mixing (physics) , biology , plant species , consistency (knowledge bases) , mathematics , computer science , artificial intelligence , mathematical analysis , physics , quantum mechanics , economics , macroeconomics
For decades, ecologists have investigated the effects of tree species diversity on tree productivity at different scales and with different approaches ranging from observational to experimental study designs. Using data from five European national forest inventories (16,773 plots), six tree species diversity experiments (584 plots), and six networks of comparative plots (169 plots), we tested whether tree species growth responses to species mixing are consistent and therefore transferrable between those different research approaches. Our results confirm the general positive effect of tree species mixing on species growth (16% on average) but we found no consistency in species‐specific responses to mixing between any of the three approaches, even after restricting comparisons to only those plots that shared similar mixtures compositions and forest types. These findings highlight the necessity to consider results from different research approaches when selecting species mixtures that should maximize positive forest biodiversity and functioning relationships.