Network meta-analysis (NMA) is a method commonly used in medical research that allows for the comparison of multiple interventions in a single, coherent analysis. In this study, we explore how NMA can be applied in ecological studies – specifically, in comparing the effectiveness of multiple interventions in field experiments. Our study aims to provide a general and non-technical introduction of network meta-analysis to ecologists, particularly on key assumptions and methods. Using an example, we demonstrate how NMA can serve as a tool to compare the effectiveness of different interventions used in enhancing crop yield. We conducted a systematic review and extracted data from meta-analytical studies that explored the response of yield to an intervention. Each study structured data as a pairwise comparison between an intervention and a control. Using yield as the measure of effectiveness, we evaluated four interventions – Liming, Straw return, Super Absorbent Polymers, and considered no intervention as the control. All measurements came from field experiments, and we analyzed data from 3733 independent studies that were included in these meta-analytical reviews. The results of our analysis demonstrate the potential of NMA as a valuable statistical method in ecological research, providing more precise comparisons of multiple interventions. However, we emphasize the need for careful consideration of important assumptions such as transitivity and consistency when implementing NMA in ecological studies. This study offers a novel approach to synthesizing ecological data, contributing to improved decision-making in agriculture, ecology, and environmental sciences.

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The implementation of network meta-analysis in Ecology; a case study using crop yield data

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Authors

Maximus Tochukwu Anochirim, Matthew Grainger, Gavin Stewart, Elina Takola 

Abstract

Network meta-analysis (NMA) is a method commonly used in medical research that allows for the comparison of multiple interventions in a single, coherent analysis. In this study, we explore how NMA can be applied in ecological studies – specifically, in comparing the effectiveness of multiple interventions in field experiments. Our study aims to provide a general and non-technical introduction of network meta-analysis to ecologists, particularly on key assumptions and methods. Using an example, we demonstrate how NMA can serve as a tool to compare the effectiveness of different interventions used in enhancing crop yield. We conducted a systematic review and extracted data from meta-analytical studies that explored the response of yield to an intervention. Each study structured data as a pairwise comparison between an intervention and a control. Using yield as the measure of effectiveness, we evaluated four interventions – Liming, Straw return, Super Absorbent Polymers, and considered no intervention as the control. All measurements came from field experiments, and we analyzed data from 3733 independent studies that were included in these meta-analytical reviews. The results of our analysis demonstrate the potential of NMA as a valuable statistical method in ecological research, providing more precise comparisons of multiple interventions. However, we emphasize the need for careful consideration of important assumptions such as transitivity and consistency when implementing NMA in ecological studies. This study offers a novel approach to synthesizing ecological data, contributing to improved decision-making in agriculture, ecology, and environmental sciences.

DOI

https://doi.org/10.32942/X2JH0R

Subjects

Agriculture, Biodiversity, Life Sciences, Natural Resources and Conservation, Natural Resources Management and Policy

Keywords

network meta-analysis, evidence synthesis, systematic review, agriculture, policy, Methodology, multi-treatment analysis, mixed-treatment comparison

Dates

Published: 2025-01-13 11:28

Last Updated: 2025-01-13 20:09

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License

CC BY Attribution 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
None

Data and Code Availability Statement:
Data and code associated with this preprint is publicly available at (https://github.com/Helmholtz-UFZ/network-meta-analysis-using-crop.yield.data)