Corals from the Gulf of Aqaba (northern Red Sea) are resilient to high temperatures and therefore this region is regarded as globally important for reef conservation. However, long-term dynamics of coral reef assemblages from the Gulf of Aqaba remain largely understudied. In this study, we analysed the change in benthic, fish and invertebrate assemblages of reefs around Dahab (South Sinai, Egypt) between 2009 and 2019. We also studied the individual trajectories of coral reef benthic categories, key invertebrate and fish species and their relationship. As site emerged as the main factor explaining the variability in coral reef communities, we identified three clusters of sites with similar assemblages. Both benthic, fish and invertebrate assemblages changed considerably at the three site clusters between 2009 and 2019. We found significant increases in fleshy macroalgae (~ 6 to 15%) and cyanobacterial mats (~ 6 to 12%) in all site clusters. Although not observing a significant reduction of hard coral cover, both macroalgae mat cover and cyanobacterial mat cover were significantly negatively related to hard coral cover and hard coral disease. Soft coral cover (mainly corals from the Xeniidae family) decreased significantly in two of the site clusters, their cover being negatively related to macroalgal and cyanobacterial cover. Significant declines in grazer urchins were observed at all site clusters, and a strong negative relationship was found with macroalgae and cyanobacterial mats cover, suggesting urchin decline as one of the main drivers behind algal increases. Different site clusters had different fish trajectories (butterflyfish, parrotfish, surgeonfish and predators), with only damselfish densities significantly decreasing at all sites. A significant decrease in damselfish densities was related to increases in cyanobacterial mats. These findings suggest that if macroalgae and cyanobacteria continue to increase, Dahab coral reefs could undergo degradation, and therefore, more studies are needed to elucidate the drivers behind these algal increases.

Many coastal ecosystems, such as coral reefs and seagrass meadows, currently experience overgrowth by fleshy algae due to the interplay of local and global stressors. This is usually accompanied by strong decreases in habitat complexity and biodiversity. Recently, persistent, mat-forming fleshy red algae, previously described for the Black Sea and several Atlantic locations, have also been observed in the Mediterranean. These several centimetre high mats may displace seagrass meadows and invertebrate communities, potentially causing a substantial loss of associated biodiversity. We show that the sessile invertebrate biodiversity in these red algae mats is high and exceeds that of neighbouring seagrass meadows. Comparative biodiversity indices were similar to or higher than those recently described for calcifying green algae habitats and biodiversity hotspots like coral reefs or mangrove forests. Our findings suggest that fleshy red algae mats can act as alternative habitats and temporary sessile invertebrate biodiversity reservoirs in times of environmental change.

In order to assess and compare sample completeness and alpha diversity of samples, Chao et al. (2020) proposed a 4-step-workflow. It is based on their extensive earlier works (e.g., Chao et al. 2014) which make use of the now widely accepted concept of Hill numbers, also known as effective number of equally abundant species qD (Hill 1973, Chao et al. 2014). Here, q denotes the diversity order of a Hill number and determines its sensitivity to species’ relative abundances or frequencies (in case of incidence data, i.e., species presence /absence). Hill numbers based on higher values of q put more emphasis on more commonly occurring species. In their publication, Chao et al. (2020) mention the online tool iNEXT4steps which supposedly offers users to complete the workflow via a web-based application. This tool is an extended and updated version of the earlier iNEXT online tool and R package (Hsieh et al. 2016). Unfortunately, the link provided in the paper does not lead to the new application. We therefore got in touch with the authors and they provided us with a link to the trial version of the iNEXT4steps online tool (see link in section 2 of the protocol). We here present a detailed workflow combining the new iNEXT4steps online tool with the existing iNEXT R package to assess and compare sample completeness, diversity and evenness between habitats as presented. This allows researchers to obtain results and figures as presented in Chao et al. (2020). References: Chao, A., Gotelli, N.J., Hsieh, T.C., Sander, E.L., Ma, K.H., Colwell, R.K. and Ellison, A.M. (2014), Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies. Ecological Monographs, 84: 45-67. https://doi.org/10.1890/13-0133.1 Chao, A, Kubota, Y, Zelený, D, et al. Quantifying sample completeness and comparing diversities among assemblages. Ecological Research. 2020; 35: 292– 314. https://doi.org/10.1111/1440-1703.12102 Hill, M.O. (1973), Diversity and Evenness: A Unifying Notation and Its Consequences. Ecology, 54: 427-432. https://doi.org/10.2307/1934352 Hsieh, T.C., Ma, K.H. and Chao, A. (2016), iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods Ecol Evol, 7: 1451-1456. https://doi.org/10.1111/2041-210X.12613 We further used Microsoft Excel, R (R Core Team 2020) and RStudio (RStudio Team 2020) and the packages ggplot2 (Wickham 2009) and ggpubr (Kassambara 2020). Microsoft Corporation. (2018). Microsoft Excel. Retrieved from https://office.microsoft.com/excel R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. RStudio Team (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/. Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis.Springer-Verlag New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org Kassambara A (2020): ggpubr. https://rpkgs.datanovia.com/ggpubr.

In order to assess and compare sample completeness and alpha diversity of samples, Chao et al. (2020) proposed a 4-step-workflow. It is based on their extensive earlier works (e.g., Chao et al. 2014) which make use of the now widely accepted concept of Hill numbers, also known as effective number of equally abundant species q D (Hill 1973, Chao et al. 2014. Here, q denotes the diversity order of a Hill number and determines its sensitivity to species' relative abundances or frequencies (in case of incidence data, i.e., species presence /absence). Hill numbers based on higher values of q put more emphasis on more commonly occurring species.In their publication, Chao et al. (2020) mention the online tool iNEXT4steps which supposedly offers users to complete the workflow via a web-based application. This tool is an extended and updated version of the earlier iNEXT online tool and R package (Hsieh et al. 2016). Unfortunately, the link provided in the paper does not lead to the new application. We therefore got in touch with the authors and they provided us with a link to the trial version of the iNEXT4steps online tool (see link in section 2 of the protocol).We here present a detailed workflow combining the new iNEXT4steps online tool with the existing iNEXT R package to assess and compare sample completeness, diversity and evenness between habitats as presented. This allows researchers to obtain results and figures as presented in Chao et al. (2020).