Carbonate compensation depth drives abyssal biogeography in the northeast Pacific

Abyssal seafloor communities cover more than 60% of Earth’s surface. Despite their great size, abyssal plains extend across modest environmental gradients compared to other marine ecosystems. However, little is known about the patterns and processes regulating biodiversity or potentially delimiting biogeographical boundaries at regional scales in the abyss. Improved macroecological understanding of remote abyssal environments is urgent as threats of widespread anthropogenic disturbance grow in the deep ocean. Here, we use a new, basin-scale dataset to show the existence of clear regional zonation in abyssal communities across the 5,000 km span of the Clarion–Clipperton Zone (northeast Pacific), an area targeted for deep-sea mining. We found two pronounced biogeographic provinces, deep and shallow-abyssal, separated by a transition zone between 4,300 and 4,800 m depth. Surprisingly, species richness was maintained across this boundary by phylum-level taxonomic replacements. These regional transitions are probably related to calcium carbonate saturation boundaries as taxa dependent on calcium carbonate structures, such as shelled molluscs, appear restricted to the shallower province. Our results suggest geochemical and climatic forcing on distributions of abyssal populations over large spatial scales and provide a potential paradigm for deep-sea macroecology, opening a new basis for regional-scale biodiversity research and conservation strategies in Earth’s largest biome.


Statistics
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A description of all covariates tested
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For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes Estimates of effect sizes (e.g.Cohen's d, Pearson's r), indicating how they were calculated Our web collection on statistics for biologists contains articles on many of the points above.

Software and code
Policy information about availability of computer code Data collection ArcMap v.6.10 and BIIGLE v.2.0 used for image data handling Data analysis EstimateS ver .9.1 R ver 4.2.1 vegan package ver 2.6-2 AICcmodavg package ver 2.3-1 ggridges package ver 0.5.3 ggplots2 package ver 3.3.6 For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors and reviewers.We strongly encourage code deposition in a community repository (e.g.GitHub).See the Nature Portfolio guidelines for submitting code & software for further information.

nature portfolio | reporting summary
March 2021 dataset): i) imagery collected between 1-4 m above the seabed; ii) well-lit and high resolution (i.e.minimum resolution at 2 m above-seabed: 1280 x 720 px); iii) total seabed survey area imaged per location >2000 square meters; iv) no overlapping frames included; v) scalable stills collected vertically-facing the seabed (for density analysis only); vi) collected in abyssal nodule field habitats within the CCZ Timing and spatial scale Specimen occurrence data were obtained during different deep-sea expeditions conducted between 2010 and 2020 across the 5000 km span of CCZ region

Data exclusions
Taxa living in a closed shell or tube (e.g.most polychaetes) were excluded from analyses as it is not possible to determine whether these are alive in images.Giant seabed foraminifera (Xenophyophores) were also excluded from analysis, for the same reason.

Reproducibility
The original dataset generated and used to run the analyses is provided as as source data files, the software and standard code functions used are all open-sourced, and the taxonomic identification catalogue used to standardize specimen identifications is available on-line.

Randomization
Replicate seabed community samples of fixed size were generated by random selection (without replacement) of specimen occurrences falling within each spatially restricted (i.e. 10 x 10 km patch size) locations.

Blinding
We used BIIGLE 2.0 to blind the location of the images containing each of the specimen occurrences during image re-analysis to minimize potential observer-bias.Several spatially-blind reviews were conducted to the whole dataset to ensure a robust taxonomic alignment between data from different sites, consisting in side-by side visualization of all specimens classified under the same catalogue label using the 'Label Review Grid Overview' tool in BIIGLE 2.0.

Did the study involve field work?
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