Converting SACFOR data for statistical analysis: Validation, demonstration and further possibilities

Strong, James Asa; Johnson, Magnus

Abstract

© 2020 The Author(s). Background: the context and purpose of the study: Semi-quantitative scales are often used for the rapid assessment of species composition and abundance during time-limited surveys. The semi-quantitative SACFOR abundance scale was developed to support the observation of marine habitats, communities and species and is widely used in the UK. As such, there is now a vast accumulation of SACFOR data. However, there several acknowledged limitations associated with its format that prevent re-analysis. Methods: how the study was performed and statistical tests used: A conversion process is proposed here that allows: (i) the merging of taxa within counts or cover data sub-sets; (ii) observations, based on either counts and cover, to be unified into one matrix; (iii) counts and cover data to have an equal weighting in the final matrix; and (iv) the removal of the influence of body size and growth form from the final values. To achieve this, it is only possible to preserve the ordinal structure of the data set. Results: the main findings: Simulations verified that the SACFOR conversion process (i) converted random cover and counts data whilst maintaining the majority of the ordinal structure and (ii) aligned abundance values regardless of whether it was recorded as a cover or count. A case study is presented, that uses real SACFOR observations, to demonstrate the conversion process and the application of statistical analyses routinely used in ecological assessments. Conclusions: brief summary and potential implications: It is hoped that the SACFOR conversion process proposed here facilitates: (i) the quantitative re-analysis of the burgeoning SACFOR data repository; and (ii) initiates a debate on alternative methods for the conversion of SACFOR data into analysable end products.

Citation

Strong, J. A., & Johnson, M. (2020). Converting SACFOR data for statistical analysis: Validation, demonstration and further possibilities. Marine Biodiversity Records, 13(1), Article 2. https://doi.org/10.1186/s41200-020-0184-3

• Journal Article Type: Article
• Acceptance Date: Jan 6, 2020
• Online Publication Date: Feb 12, 2020
• Publication Date: Feb 12, 2020
• Deposit Date: Apr 1, 2022
• Publicly Available Date: Apr 4, 2022
• Journal: Marine Biodiversity Records
• Electronic ISSN: 1755-2672
• Publisher: Cambridge University Press (CUP)
• Peer Reviewed: Peer Reviewed
• Volume: 13
• Issue: 1
• Article Number: 2
• DOI: https://doi.org/10.1186/s41200-020-0184-3
• Keywords: SACFOR scale; Conversion process; Semi-quantitative data analysis; Marine data reanalysis; Ordinal data; Benthic ecology
• Public URL: https://hull-repository.worktribe.com/output/3525002