Weak reciprocal relationships between productivity and plant biodiversity in managed grasslands

Author:

Andraczek Karl12ORCID,Dee Laura E.3ORCID,Weigelt Alexandra12ORCID,Hinderling Judith4,Prati Daniel4,Le Provost Gaëtane56ORCID,Manning Peter57ORCID,Wirth Christian12ORCID,van der Plas Fons18ORCID

Affiliation:

1. Systematic Botany and Functional Biodiversity University Leipzig Leipzig Germany

2. German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany

3. Department of Ecology and Evolutionary Biology University of Colorado Boulder Colorado USA

4. Institute of Plant Sciences, University of Bern Bern Switzerland

5. Senckenberg Biodiversity and Climate Research Centre (SBIK‐F), Senckenberg Gesellschaft für Naturforschung Frankfurt Germany

6. INRAE, Bordeaux Sciences Agro, ISVV, SAVE Villenave d'Ornon France

7. Department of Biological Sciences University of Bergen Bergen Norway

8. Plant Ecology and Nature Conservation Group Wageningen University Wageningen the Netherlands

Abstract

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.

Funder

Deutsche Forschungsgemeinschaft

Publisher

Wiley

Reference87 articles.

1. Productivity Is a Poor Predictor of Plant Species Richness

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4. Andraczek K.(2023).Data and RCode used in Andraczek et al. “Causal inference methods reveal weak reciprocal relationships between productivity and plant biodiversity in managed grasslands”.Zenodo https://doi.org/10.5281/zenodo.12686128

5. Relationships between species richness and biomass production are context dependent in grasslands differing in land‐use and seed addition;Andraczek K.;Scientific Reports,2023

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