Summary Decades of studies have demonstrated links between biodiversity and ecosystem functioning, yet the generality of the relationships and the underlying mechanisms remain unclear, especially for forest ecosystems.Using 11 tree‐diversity experiments, we tested tree species richness–community productivity relationships and the role of arbuscular (AM) or ectomycorrhizal (ECM) fungal‐associated tree species in these relationships.Tree species richness had a positive effect on community productivity across experiments, modified by the diversity of tree mycorrhizal associations. In communities with both AM and ECM trees, species richness showed positive effects on community productivity, which could have resulted from complementarity between AM and ECM trees. Moreover, both AM and ECM trees were more productive in mixed communities with both AM and ECM trees than in communities assembled by their own mycorrhizal type of trees. In communities containing only ECM trees, species richness had a significant positive effect on productivity, whereas species richness did not show any significant effects on productivity in communities containing only AM trees.Our study provides novel explanations for variations in diversity–productivity relationships by suggesting that tree–mycorrhiza interactions can shape productivity in mixed‐species forest ecosystems. 
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                            Weak reciprocal relationships between productivity and plant biodiversity in managed grasslands
                        
                    
    
            Abstract Relationships between plant biodiversity and productivity are highly variable across studies in managed grasslands, partly because of the challenge of accounting for confounding's and reciprocal relationships between biodiversity and productivity in observational data collected at a single point in time. Identifying causal effects in the presence of these challenges requires new analytical approaches and repeated observations to determine the temporal ordering of effects.Though rarely available, data collected at multiple time points within a growing season can help to disentangle the effects of biodiversity on productivity and vice versa. Here we advance this understanding using seasonal grassland surveys from 150 managed grassland sites repeated over 2 years, along with statistical methods that are relatively new in ecology, that aim to infer causal relationships from observational data. We compare our approach to common methods used in ecology, that is, mixed‐effect models, and to analyses that use observations from only one point in time within the growing seasons.We find that mixed models overestimated the effect of biodiversity on productivity by two standard errors as compared to our main models, which find no evidence for a strong positive effect. For the effect of productivity on biodiversity we found a negative effect using mixed models which was highly sensitive to the time at which the data was collected within the growing season. In contrast, our main models found no evidence for an effect. Conventional models overestimated the effects between biodiversity and productivity, likely due to confounding variables.Synthesis. Understanding the biodiversity‐productivity relationships is a focal topic in ecology, but unravelling their reciprocal nature remains challenging. We demonstrate that higher‐resolution longitudinal data along with methods to control for a broader suite of confounding variables can be used to resolve reciprocal relationships. We highlight future data needs and methods that can help us to resolve biodiversity‐productivity relationships, crucial for reconciling a long‐running debate in ecology and ultimately, to understand how biodiversity and ecosystem functioning respond to global change. 
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                            - Award ID(s):
- 2340606
- PAR ID:
- 10575014
- Publisher / Repository:
- British Ecological Society
- Date Published:
- Journal Name:
- Journal of Ecology
- Volume:
- 112
- Issue:
- 10
- ISSN:
- 0022-0477
- Page Range / eLocation ID:
- 2359 to 2373
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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