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

Strong, James Asa ORCID: https://orcid.org/0000-0001-8603-097X; Johnson, Magnus. 2020 Converting SACFOR data for statistical analysis: validation, demonstration and further possibilities. Marine Biodiversity Records, 13 (1). 10.1186/s41200-020-0184-3

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Official URL: http://dx.doi.org/10.1186/s41200-020-0184-3

Abstract/Summary

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.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1186/s41200-020-0184-3
ISSN:	1755-2672
Date made live:	10 Mar 2020 11:24 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/527214

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1186/s41200-020-0184-3

ISSN:

1755-2672

Date made live:

10 Mar 2020 11:24 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/527214