DOI: 10.5061/dryad.rn8pk0ph6
title: Sponge diversity patterns in the shallow and mesophotic reefs of the Northern Red Sea row data

description: Accumulating data regarding the increasingly degraded coral reefs
 worldwide have directed focus to the unique mesophotic coral ecosystem
 (MCE) as a potential refuge for shallow-water endangered species. Sponges
 play a crucial role in coral-reef functioning but are often overlooked in
 benthic surveys. This knowledge gap is especially true for the Red Sea,
 where data on sponge abundance, coverage and species composition are
 scarce. Moreover, no study to date has examined Red Sea mesophotic
 sponges. Here we compared sponge diversity metrics between the shallow and
 mesophotic reefs in the Gulf of Aqaba, Northern Red Sea. We also examined
 the role of biotic and abiotic parameters in determining sponge spatial
 variability. Sponge diversity metrics significantly varied with increasing
 depth and between sites. Sponge species composition also significantly
 differed between depth and sites. However, while no significant evidence
 supported a sponge bottom-up control, the findings indicated that local
 factors, such as site characters and biotic interactions, might play
 essential roles in determining sponge diversity and community composition.
 The sponges’ spatial differences found in this study highlight the
 importance of considering variability in benthic communities and the
 factors controlling this, when designing management tools for coral reefs,
 particularly for the Northern Red Sea.
description: Data was collected during
 suryes at the shallow (5, 10, 20 m) and mesophotic (50, 60, 70 m) reef at
 the Gulf of Aqaba/Eilat northern Red Sea at two sites the IUI and OJ.
 At each site and depth the
 quantitative survey comprised three transects of 3.5
 m<sup>2</sup> each (total 10.5<sup>2 </sup>per
 site*depth). Each transect was created from 25-30 photo-quadrats,
 processed using ImageJ [40] to create image collections of equal size
 (~70X50
 cm). The MCE survey was conducted from the R/V Sam
 Rothberg using a Remotely Operated Vehicle (ROV ECA-Robotics H800)
 equipped with FHD camera, four video lights (4000 lumens) and two parallel
 laser beams for scale (7.5 cm apart). A similar methodology was performed
 at the
 shallow reefs, using SCUBA
 diving, with photo-quadrats taken ~1 m above the reef using a CANON G12/16
 camera mounted on a tray with two video lights (3500 lumens) and two
 parallel laser beams for scale. At both habitats, additional close-up pictures
 of the surveyed area (in each photo-quadrat) were taken in order to
 facilitate identification of the living organisms on the
 substrate. For sponge
 coverage calculation, 100 sampling points were overlaid on each image
 (50x70 cm) in a stratified random manner using CoralNet online software.
 Benthos components beneath each point were classified into one of three
 categories: sponge, coral or algae, and each component’s coverage was
 calculated in relation to the others (relative abundance). To assess
 sponge diversity at each site/depth (e.g., richness, abundance, Shannon,
 evenness), the sponge
 species were counted and identified in each image to the lowest possible
 taxonomic level. Where feasible, sponge species were collected during the
 survey, facilitating identification in the photo-quadrats. However, when
 taxonomic identification and/or sampling were not possible, sponges were
 defined according to their morphology and referred to as
 "morphospecies". Finally, the average sponge diversity per site
 or depth was calculated based on the averaged values per transect.
 Seawater was sampled adjacent to the
 reef (&lt;50 cm) at 50 and 5 m depth at the two survey sites, using
 horizontal 12 L Niskin bottle (Fig. S1). Samples were collected during
 winter (Nov 2018-Mar 2019) and summer (Jun-Sep) of 2019 and processed for:
 Total Organic Carbon (TOC), Particulate Organic Carbon (POC) and inorganic
 nutrients (NOx<sup>-</sup>, SiO<sub>2</sub>,
 PO<sub>4</sub><sup>3-</sup>), and
 fluorescence-activated cell-sorting (FACS) was used to sort the
 cells.
description: All statistical analyses and
 data visualizations were performed with RStudio 2021.09.0+351
 R version 4.1.0 and Excel (MS Office).