Depth and latitudinal diversity gradients in seamount benthic communities of the South Atlantic ...
Aim Although latitudinal and bathymetric species diversity gradients in the deep sea have been identified and investigated, studies have rarely considered these gradients across seamount and oceanic island ecosystems. This study aimed to identify whether the current understanding of latitudinal and...
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| Format: | Dataset |
| Language: | English |
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Dryad
2020
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| Online Access: | https://dx.doi.org/10.5061/dryad.b5mkkwhbw https://datadryad.org/stash/dataset/doi:10.5061/dryad.b5mkkwhbw |
| Summary: | Aim Although latitudinal and bathymetric species diversity gradients in the deep sea have been identified and investigated, studies have rarely considered these gradients across seamount and oceanic island ecosystems. This study aimed to identify whether the current understanding of latitudinal and bathymetric gradients in α-diversity (species richness) apply to South Atlantic seamount ecosystems, as well as ascertaining whether identifiable trends were present in seamount β-diversity along a bathymetric gradient. Location The South Atlantic Ocean. Time period 2013-2019 Major taxa studied Benthic communities. Methods Drop camera images from 39 transects, collected between 250 m and 950 m, were used to characterise species richness from within the Exclusive Economic Zones of Ascension Island, Saint Helena and Tristan da Cunha, spanning 8°S to 40°S. We subsequently applied linear modelling to test possible environmental drivers across latitudinal and bathymetric ranges (see transect metadata for variables). An ... : Drop camera images from 39 transects, collected between 250 m and 950 m, were used to characterise species richness from within the Exclusive Economic Zones of Ascension Island, Saint Helena and Tristan da Cunha, spanning 8°S to 40°S. Environmnetal data derived from high-resolution multibeam bathyemtry were used to identify possible environmental drivers across latitudinal and bathymetric ranges (see transect metadata for variables). ... |
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