Data from: Predicting the distribution of Mesophotic coral ecosystems in the Chagos Archipelago
Data files
Mar 17, 2025 version files 419.06 KB
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Data_for_modelling.xlsx
417.01 KB
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README.md
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Abstract
To support conservation efforts, accurate mapping of marine organism community’ distribution has become more critical than ever before. While previous mapping endeavours have primarily focused on easily accessible shallow-water habitats, there remains limited knowledge about the ecosystems lying beyond SCUBA diving depths, such as mesophotic coral ecosystems (MCEs, ~30-150 m). MCEs are important habitats from an ecological and conservation perspective, yet little is known about the environmental factors that shape these ecosystems and their distribution, particularly in the Indian Ocean region. The goals of this study are to 1) predict the spatial distribution and extent of distinct benthic communities and MCEs in the Chagos Archipelago, central Indian Ocean, 2) test the effectiveness of a range of environmental and topography derived variables to predict the location of MCEs around Egmont Atoll and the Archipelago, and 3) independently validate the models produced. In addition, we compared the MCEs predicted extent in the Archipelago for the models derived from high-resolution multibeam and low-resolution GEBCO bathymetry data. Using maximum entropy modelling, all models resulted in excellent (>0.9) performances, for AUC and threshold-dependent metrics, predicting extensive and previously undocumented MCEs across the entire Archipelago, with however, differences in the predicted extent between the high- and low-resolution models. Independent validation resulted in fair (>0.7 AUC) and poor (>0.6 AUC) performances for the high-resolution and low-resolution models, respectively. Photosynthetically Active Radiation (PAR), temperature, chlorophyll-a and topographically derived variables were identified as the most influential predictors. In conclusion, this study provides the first prediction of the distribution of MCEs and their distinct benthic communities in the Archipelago. It highlights their significance in terms of potential extent and response to various environmental factors, supporting decision making for prioritising future survey sites to study MCEs across the Archipelago and targeting ecologically important areas for conservation.
Description of the data and file structure
Dataset “Data_for_modelling” for the Maxent model used in the manuscript entitled “Predicting the distribution of Mesophotic Coral Ecosystems in the central Indian Ocean”
Files and variables
File: Data_for_modelling.xlsx
Description: Data for modelling
- each sheet is for a cluster
Variables
Environmental parameters of each cluster identified with a Hierarchical clustering with a similarity profile (SIMPROF) permutational test (1-6) and a mesophotic coral ecosystems (MCEs) cluster.
Grid_code: presence (1), absence (0)
POINT_X; POINT_Y: latitude and longitude in Good Homolosine Ocean
Transect_names: transect code given: e.g. 23110: site 2, transect 3, depth zone 110-120m.
Bathy: bathymetry in meters
BBPI; FBPI: broad- fine-scale bathymetry position index
Chla: chlorophyll a in milligram/m3
PAR: photosynthetically active radiation in μmol photons.m2.s1
Sal: salinity in PSU
Rugosity: or ruggedness, obtained from mutlibeam data
Slope: slope, obtained from multibeam data
Temp_min, mean, max: temperature minimal, average and maximal over 4 years, in degrees Celsius
Temp_delta: difference in temperature between the minimum and maximum, in degrees Celsius
For further information, please read the detailed “methods” section of the main manuscript or visit the supplementary information of the manuscript.
You can additionally contact clara.diaz@plymouth.ac.uk / clara.diaz97466@gmail.com
Code/software
R was used to generate this dataset. Please see the methods section of the manuscript for more information.
Access information
Other publicly accessible locations of the data:
Data was derived from the following sources:
- please see the Methods section of the manuscript