CSRcalculator: a reproducible framework for understanding plant ecological strategies

Gaskin, Teddy, Crick, Ben, Wright, Manny, Cavanagh, Amanda P, Huber, Katharina ORCID: https://orcid.org/0000-0002-6368-7511, Nikoloski, Zoran and Ferguson, John N. (2026) CSRcalculator: a reproducible framework for understanding plant ecological strategies. Plants, People, Planet. ISSN 2572-2611 (In Press)

PDF (accepted-2026-07-16) - Accepted Version Restricted to Repository staff only until 31 December 2099. Available under License Creative Commons Attribution. Request a copy

Abstract

Societal impact statement: Understanding how plants respond to environmental change is essential for conserving biodiversity and managing ecosystems under climate change. We developed CSRcalculator, an open-source platform that brings together major competitor, stress-tolerator, ruderal (CSR) models to make ecological strategy classification accessible, reproducible, and scalable. The software enables users to rapidly translate plant trait data into standardised ecological strategy classifications through a simple, user-friendly interface, promoting consistent and reproducible analyses across studies. By improving access to the CSR framework and supporting reproducible research, CSRcalculator strengthens ecological monitoring, informs conservation and land management, and enables more robust evidence for environmental policy and practice. Summary: • The competitor, stress-tolerator, ruderal (CSR) theory, first proposed by John Philip Grime, is a useful framework for understanding plant ecological strategies and predicting responses to environmental changes and pressures. However, current tools for assigning CSR strategies are limited to an Excel sheet format and have yet to be integrated into modern computational platforms that enable reproducible research. • We present CSRcalculator (https://github.com/TeddyGaskin/CSRcalculator), an open-source R package and shiny application that calculates CSR scores and assigns strategies based on user-uploaded trait data. CSRcalculator supports CSR assignments according to the three most prominent models: The original soft approach, the global StrateFy, and a morpho-physiological model. • The R package outputs a table including CSR scores, assigned strategies and intermediate traits for the selected model. The shiny application produces this same table alongside an interactive ternary plot to visualise the strategy distribution and an optional summary table describing the overall CSR strategy distribution, using metrics such as, the modal strategy, axis means, standard deviations, and ranges. Group-level analyses calculate the same statistics across user-defined categories. • We demonstrate the utility and reliability of CSRcalculator by validating its outputs against a published dataset and original CSR tools, as well as benchmarking its performance across dataset sizes to confirm it scales efficiently to large datasets.

Item Type:	Article
Additional Information:	All trait data used in this study were sourced from previously published materials (Novakovskiy et al. 2021). An adapted data set from this source is included in the CSRcalculator package (Supporting Dataset S1; Supporting Code S1). The TRY dataset is included in the supporting material (Supporting Dataset S2).
Uncontrolled Keywords:	competitive,csr,plant strategies,ruderal,shiny application,stress-tolerant,universal adaptive strategy theory,sdg 13 - climate action,sdg 15 - life on land ,/dk/atira/pure/sustainabledevelopmentgoals/climate_action
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Computational Biology
Depositing User:	LivePure Connector
Date Deposited:	10 Aug 2026 11:36
Last Modified:	10 Aug 2026 11:36
URI:	https://ueaeprints.uea.ac.uk/id/eprint/104073
DOI:	issn:2572-2611

Actions (login required)

View Item