Defining 3-dimensional marine provinces with phytoplankton compositions

TL;DR

This paper introduces a novel algorithm, bioprovince, for defining marine biological provinces in three dimensions using phytoplankton composition data, revealing depth-wise and regional ecological patterns.

Contribution

The study develops and applies a new clustering algorithm that incorporates depth into marine province delineation based on phytoplankton compositions, enhancing traditional spatial methods.

Findings

Agreement with Longhurst provinces at the surface level

Revealed finer subdivisions within traditional provinces

Identified significant depth-wise partitions in the Pacific

Abstract

Marine provinces rarely include fine-resolution biological data, and are often defined spatially across only latitude and longitude. Therefore, we aimed to determine how phytoplankton distributions define marine provinces across 3-dimensions (i.e., latitude, longitude, and depth). To do this, we developed a new algorithm called \texttt{bioprovince} which can be applied to compositional biological data. The algorithm first clusters compositional samples to identify spatially coherent groups of samples, then makes flexible province predictions in the broader 3d spatial grid based on environmental similarity. We applied \texttt{bioprovince} to phytoplankton Amplicon Sequencing Variants (ASVs) from five, depth-resolved ocean transects spanning north-south in the Pacific Ocean. In the surface layer of the ocean, our method agreed well with traditional Longhurst provinces. In some cases, the method revealed that with more granular taxonomic resolution afforded by ASVs, traditional Longhurst provinces were divided into smaller zones. Also, one of the major advances of this method is its ability to incorporate a third dimension, depth. Indeed, our analysis found significant depth-wise partitions throughout the Pacific with remarkable agreement in the equatorial region with the base of the euphotic zone. Our algorithm's ability to delineate 3-dimensional bioprovinces will enable scientists to discover new ecological interpretations of marine phytoplankton ecology and biogeography. Furthermore, as compositional biological data inherently exists in three spatial dimensions in nature, bioprovince is broadly applicable beyond marine plankton, offering a more holistic perspective on biological provinces across diverse environments.