Published November 12, 2025 | Version v3

Data and scripts for: The conventional-to-organic yield gap diminishes with increasing crop pollinator dependence

  • 1. INIBIOMA, Bariloche, Argentina

Description

Data and scripts for:  

Nahuel Aizen, Agustin Sáez, Carolina L. Morales, Marcelo A. Aizen; The conventional-to-organic yield gap diminishes with increasing crop pollinator dependence. Proceedings of the Royal Society B 293 (2063): 20252553. https://doi.org/10.1098/rspb.2025.2553

Goal of the study: To conduct a meta-analysis assessing whether the yield gap between conventional and organic agriculture narrows with increasing crop pollinator dependence.

Metadata content: This repository includes the full dataset and R scripts necessary to reproduce all statistical analyses
and figures presented in the manuscript. 


Data

1. dataponisio.csv

This dataset was compiled for the meta-analysis conducted by Ponisio et al. (2015). It includes multiple variables, notably: the study title (column 6), crop name (column 18), and summary statistics—means, standard deviations, and sample sizes (columns 63–68)—used to estimate yield effect sizes under conventional and organic agricultural practices.


2. datagong.csv

This dataset was compiled for the meta-analysis conducted by Gong et al. (2021). It includes several variables, notably: the study title (column 3), crop name (column 21), 
and summary statistics—means, standard deviations, and sample sizes (columns 31–36)—used to estimate yield effect sizes under conventional and organic agricultural systems.


3. data1325.csv

This dataset was compiled based on the authors’ Web of Science search spanning 2013–2025, serving as an update to the dataset originally assembled by Ponisio et al. (2015). It includes several variables, notably: the study title (column 5), crop name (column 9), and summary statistics—means, standard deviations, and sample sizes (columns 16–21)—used to estimate yield effect sizes under conventional and organic agricultural systems.


4. datafull.csv

This dataset represents the collated version obtained after removing duplicate studies across datasets and duplicate records within each individual source. It includes estimates of 1,372 effect sizes—mean effect size and its variance (columns 21–22)—derived from 199 studies spanning 61 crop species.  


5. datafull_pruned.csv

This dataset represents the collated version obtained after applying Lajeunesse’s (2011) method for clustering pseudoreplicated records. The resulting dataset includes estimates of 897 effect sizes—mean effect size and its variance (columns 21–22)—derived from 199 studies encompassing 61 crop species.


6. crops.csv

This file contains information on key crop traits, including: common crop name (column 1), species name (column 2), pollinator dependence (column 3), harvested organ (column 4), growth form (column 5), woodiness (column 6), and the climatic zone of crop origin (column 7).


7.phylo_crop.tre

This file contains the phylogenetic tree used in the analysis, representing lineage relationships among the crop species included in the dataset.

 

Scripts

1. datafull_script

This R script curates and merges the three source datasets, generating datafull.csv and datafull_pruned.csv after applying Lajeunesse’s (2011) method for clustering pseudoreplicated records.


2. yield_gap_dep_analyses_&_figures_script

This R script executes all analyses and generates the figures presented in the paper.

  

References

Ponisio LC, M ’gonigle LK, Mace KC, Palomino J, De Valpine P, Kremen C. 2015 Diversification practices reduce organic to conventional yield gap.
 Proc. R. Soc. B Biol. Sci. 282, 20141396. (doi:10.1098/rspb.2014.1396)

Gong S, Hodgson JA, Tscharntke T, Liu Y, van der Werf W, Batáry P, Knops JMH, Zou Y. 2022 Biodiversity and yield trade-offs for organic farming.
  Ecol. Lett. 25, 1699–1710. (doi:10.1111/ele.14017)

Lajeunesse MJ. 2011 On the meta-analysis of response ratios for studies with correlated and multi-group designs. Ecology 92, 2049–2055. 
  (doi:10.1890/11-0423.1)

Files

crops.csv

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