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“But I can’t preregister my research”: Improving the reproducibility and transparency of ecology and conservation with adaptive preregistration for model-based research
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Abstract
1. Preregistration is an open-science practice which aims to improve research transparency and mitigate questionable research practices, like cherry-picking results. It helps protect against cognitive biases, like hindsight bias, that can influence how study outcomes are interpreted. There has been little uptake of preregistration in ecology and conservation, arguably because existing pre-registration templates focus on null-hypothesis significance testing whereas ecology and conservation often rely on different types of statistical modelling. 2. We argue that preregistration in model-based research in ecology and conservation is both possible and beneficial, using templates adapted for domain-specific methodologies. We applied a user-centred design approach to translate the concept of preregistration into model-based research practice for ecology and conservation. 3. To better align the internal logic of preregistration with the iterative and non-linear process of ecological modelling, we propose, test and evaluate a methodology for ‘adaptive preregistration’, using a case study of modelling managed water releases (“environmental flows modelling”) in regulated rivers for maintaining riparian vegetation condition in Victoria, Australia. 4. This research provides a template and methodology for implementing adaptive preregistration of ecological models. Although we focus on ecology and conservation in this paper, the concept of adaptive preregistration, and the templates developed here, could be applied to model-based research in other scientific disciplines within science more broadly. Modelers in ecology and conservation need no longer cry “but I can’t preregister my research.”
DOI
https://doi.org/10.32942/X2GW66
Subjects
Ecology and Evolutionary Biology, Research Methods in Life Sciences
Keywords
adaptive preregistration, ecological modelling, environmental flows modelling, good modelling practice, metascience, preregistration, open science, transparency
Dates
Published: 2025-08-19 02:03
Last Updated: 2025-08-19 02:03
License
CC-By Attribution-NonCommercial-NoDerivatives 4.0 International
Additional Metadata
Language:
English
Data and Code Availability Statement:
Case study data and code are available at https://github.com/egouldo/VEFMAP_VEG_Stage6 and will be made available following double-blind peer-review. Our preregistration template is available as a quarto template extension at https://github.com/egouldo/EcoConsModPreReg and our user guide to adaptive preregistration is located at https://egouldo.github.io/EcoConsPreReg/
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