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Determination of mean effective shore level to delineate periods of emersion and immersion for intertidal rocky shores

Citation

Ma, Kevin C. K.; Monsinjon, Jonathan R.; Froneman, P. William; McQuaid, Christopher D. (2022), Determination of mean effective shore level to delineate periods of emersion and immersion for intertidal rocky shores, Dryad, Dataset, https://doi.org/10.5061/dryad.h70rxwdmn

Abstract

This dataset contains data described in the paper entitled "Environmental filtering causes increasingly negative effects towards the range limit of an invasive mussel". Data include: the R script to estimate temperature thresholds and calculate effective shore levels (esl_function.R); data files associated with this R script (material.RData); mean effective shore levels determined for the five South African rocky-shore sites where submersible temperature data loggers were installed (esl_overall_results.csv); measurements of mussel shell lengths, level of endolithic infestation, and counts of epibionts on the basibiont mussel Mytilus galloprovincialis (mussel_data.csv); counts of barnacles (Chthamalus dentatus) and mussels (Mytilus galloprovincialis and Perna perna) on emersed rocks using 50 × 50 cm quadrats and counts of mussels (Mytilus galloprovincialis and Perna perna) in mono-layer mixed-species mussel patches using 25 × 25 cm quadrats (quadrat_data.csv); hourly temperatures recorded by submersible temperature data loggers (EnvLogger Version 2.4; precision of ≤ 0.1 ºC and accuracy  of ≤ 0.2 ºC) from September 2019 to September 2020 at the five South African rocky-shore sites (temperature_data.csv); and 2019 and 2020 hourly tidal predictions (courtesy of the South African Navy Hydrographic Office) for the closest maritime port to the sites where the temperature data loggers were installed (tide_data.csv).

Usage Notes

The readme file provides a description of each column in the dataset. NA =  values not available.

Funding

South African Research Chairs Initiative of the Department of Science and Technology and the National Research Foundation, Award: Grant No. 64801