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Data from: A review of seascape complexity indices and their performance in coral and rocky reefs

Citation

Lazarus, Mai; Belmaker, Jonathan (2020), Data from: A review of seascape complexity indices and their performance in coral and rocky reefs, Dryad, Dataset, https://doi.org/10.5061/dryad.4tmpg4f8g

Abstract

Seascape complexity is an important driver of ecological processes in marine systems. Today, high resolution, multiscale bathymetric data is being collected due to rapid advances in marine technologies and image processing, drastically improving the detailed mapping of the physical structure of the seascape. However, these data are rarely synthesized to create comprehensive complexity estimates, and complexity is still mostly measured using a small set of simple indices. The aims of this study are to: (1) review existing seascape complexity indices and propose innovative indices designed to capture the marine organism perspective, (2) quantify the interrelationships among these complexity indices; (3) test the performance of these indices in explaining fish assemblage structure; and (4) provide R code to easily reproduce the indices. Seascape bottom topography for this study was quantified using digital depth recordings along transects in Mediterranean subtropical rocky reefs and Red Sea tropical coral reefs. These were used to generate complexity indices that were then compared to visually surveyed fish assemblages. We found that several common indices captured similar complexity facets, while an innovative family of structural diversity indices, representing the diversity of physical elements, captured distinct complexity facets not represented by existing indices. No single index was consistently superior; however, vertical relief was consistently included as a top predictor of fish assemblage structure. Interestingly, the most commonly used index, rugosity, was a poor predictor. We suggest a new, distinct set of structural diversity indices that may explain considerable variation in fish assemblages. The results suggest that several indices may need to be combined to capture the full influence of complexity on marine diversity and caution against the use of a single ‘universal’ index. While bathymetric data is increasingly being collected at high resolutions and increasing scales, synthesizing this data requires the use of appropriate complexity indices. The guidelines and recommendations presented here, along with the supplemental R code, will facilitate progress towards a more complete representation of different complexity facets.

Methods

Each transect was conducted by a single or two observers. For each transect, species richness ('max_richness'), species abundance ('max_abundance') and species biomass ('max_biomass', calculated using literature-based species-specific conversion factors) were calculated using the maximum values observed by one of the surveyors. Shannon diversity ('shannon') was claculated as the mean between two observers. Sampling sites were randomly chosen in areas with continuous hard substrate cover.

Bottom profiles were created using a digital depth water level data logger (by 'Onset') (accompanied by visual fish censuses). From these bottom profiles 21 complexity indices were calculated (columns M to AH) along with the mean depth along the transect ('mean_depth' variable).

Usage Notes

This dataset includes all the information used for analyses in the manuscript "A review of seascape complexity indices and their performance in coral and rocky reefs":

1. The file 'data_for_publication' includes fish community structure data per sampling unit along with structural complexity indices calculated per sampling unit. The file includes data from both the Mediterranean Sea and the Red Sea ('coast' variable). Data from the Mediterranean were collected between 2015-2017 and includes 183 transects conducted in four locations ('location' variable), within marine reserves and in their surroundings ('reserve' variable). Data from the Red Sea were collected along the Israeli coast of the Gulf of Aqaba between 2018-2019 and includes 60 transects conducted in five locations ('location variable). An identifier variable for each transect ('transect_id') is composed of the sampling point ('sampling_point'), trasect letter/number (within the Red Sea, due to longer protocol duration, sampling points are identical to transects letters), sampling site ('location'), year ('year'), sampling season and name of first observer and of second observer. 

2. The file 'copmlexity_papers' summarizes the information we used for a mini-review about the use of complexity indices to date. This information includes the author of the paper ('Author', if one or two authors, all are specificed, if more than two authors, the first auther is specified), paper title ('Paper title'), year of publication ('Year'). Columns D-I specify the amount of indices used in each publication, and which ones used the rugosity index or its derivatives.