Plant species with ‘fast’ traits are winners in young and high‐diversity plant communities

Abstract Long‐term biodiversity experiments have shown increasing strengths of positive biodiversity–productivity relationships over time, while the species‐level responses to increased plant diversity are highly variable. Plant–soil interactions and resource‐use complementarity offer the potential to explain both overyielding and underyielding in diversity–productivity relationships. However, it is not well understood how community history, that is changing biotic interactions over time, modulates the growth of individual species and whether ‘winners’ (i.e. overyielding species) and ‘losers’ (i.e. underyielding species) differ in their traits. We first used above‐ground biomass data of 66 plant mixtures (with 2, 4, 8, 16 and 60 species) of a long‐term biodiversity experiment (Jena Experiment) to identify plot‐specific ‘winners’ and ‘losers’. Using a subset of two winner and two loser species from each mixture, we then planted individuals (= ‘phytometers’) in resident communities with different histories, that is 14‐year ‘old communities’ and ‘new communities’ on new soil, and measured their performance and traits related to the fast–slow leaf economic trait spectrum (leaf nitrogen, N Leaf , and specific leaf area, SLA). For both, species in the resident communities and the phytometers, we tested whether their assignment as winner or losers can be explained by their leaf economics. In the resident communities, plot‐specific winners had a greater SLA than losers, but only in high‐diversity mixtures and especially in those with an older history, while the relationships to N Leaf varied with community history. In the phytometer experiment, plant individual biomass, formation of flowers, and N Leaf of phytometers decreased, while SLA increased with plant species richness in both history treatments. Phytometer survival and N Leaf were higher in the new communities. In the mixtures, and especially in those with new soil, winner phytometers had higher N Leaf than expected from the monocultures, but did not differ in their performance or other traits from loser ones. In the monocultures, winner phytometers had higher SLA than loser ones. Synthesis . Our results suggest that fast‐growing, high‐nutrient demanding species are winners in high‐diversity mixtures, which can be well predicted from their SLA. However, our results regarding N Leaf suggest that the predictability of species performances changes with age of the experimental communities and that presumably more complex plant–soil interactions in older communities impede simple growth trait‐related explanations.

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Publication Details

Journal
Journal of Ecology
Published
2025-12-14
DOI
https://doi.org/10.1111/1365-2745.70216
Primary Topic
Ecology and Vegetation Dynamics Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Plant species with ‘fast’ traits are winners in young and high‐diversity plant communities

Yanhao Feng, Nico Eisenhauer, Christiane Roscher
Journal of Ecology
Ecology and Vegetation Dynamics Studies
article

Plant species with ‘fast’ traits are winners in young and high‐diversity plant communities

Yanhao Feng, Nico Eisenhauer, Christiane Roscher
article en

Abstract

Abstract Long‐term biodiversity experiments have shown increasing strengths of positive biodiversity–productivity relationships over time, while the species‐level responses to increased plant diversity are highly variable. Plant–soil interactions and resource‐use complementarity offer the potential to explain both overyielding and underyielding in diversity–productivity relationships. However, it is not well understood how community history, that is changing biotic interactions over time, modulates the growth of individual species and whether ‘winners’ (i.e. overyielding species) and ‘losers’ (i.e. underyielding species) differ in their traits. We first used above‐ground biomass data of 66 plant mixtures (with 2, 4, 8, 16 and 60 species) of a long‐term biodiversity experiment (Jena Experiment) to identify plot‐specific ‘winners’ and ‘losers’. Using a subset of two winner and two loser species from each mixture, we then planted individuals (= ‘phytometers’) in resident communities with different histories, that is 14‐year ‘old communities’ and ‘new communities’ on new soil, and measured their performance and traits related to the fast–slow leaf economic trait spectrum (leaf nitrogen, N Leaf , and specific leaf area, SLA). For both, species in the resident communities and the phytometers, we tested whether their assignment as winner or losers can be explained by their leaf economics. In the resident communities, plot‐specific winners had a greater SLA than losers, but only in high‐diversity mixtures and especially in those with an older history, while the relationships to N Leaf varied with community history. In the phytometer experiment, plant individual biomass, formation of flowers, and N Leaf of phytometers decreased, while SLA increased with plant species richness in both history treatments. Phytometer survival and N Leaf were higher in the new communities. In the mixtures, and especially in those with new soil, winner phytometers had higher N Leaf than expected from the monocultures, but did not differ in their performance or other traits from loser ones. In the monocultures, winner phytometers had higher SLA than loser ones. Synthesis . Our results suggest that fast‐growing, high‐nutrient demanding species are winners in high‐diversity mixtures, which can be well predicted from their SLA. However, our results regarding N Leaf suggest that the predictability of species performances changes with age of the experimental communities and that presumably more complex plant–soil interactions in older communities impede simple growth trait‐related explanations.

Journal of EcologyVol. 114(1)
Helmholtz Centre for Environmental Research (DE), German Centre for Integrative Biodiversity Research (DE), Ministry of Agriculture (EE), Leipzig University (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 63%
Ecology and Vegetation Dynamics Studies
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