Biology subjects

El Hourany, R.

Publications and source records attributed to El Hourany, R..

4 recordsLinked to original sources

bioRxiv2026

Satellite-gene abundance fusion reveals global hotspots of ocean ecosystem services

The Ocean sustains planetary health through climate regulation, biodiversity, and essential ecosystem services. Plankton underpins these processes by driving primary production, sustaining food webs, and mediating carbon sequestration. Yet the spatial organization of plankton-based ecosystem services remains poorly understood. The High Seas Treaty and the 30% Ocean protection target by 2030 create an urgent need for science-based guidance for global ocean governance. Here, we aim to identify key planktonic areas associated with functional diversity, net primary productivity, and carbon export globally. We used machine learning to integrate omics-derived plankton functions and satellite observations with diversity metric and ecosystem services. Leveraging metagenomic data, we identified molecular functions strongly linked to ecosystem functioning and project their global distributions across seasons. We reveal putative hotspots of functional diversity, net primary productivity, and carbon export. Our analysis pinpoints areas where all three indicators converge synchronously, predominantly along oceanographic structures such as polar fronts and principal current systems. By relying on satellite data as core input, our approach captures the temporal variability of these hotspots, providing a global, dynamic protocol for projections of plankton-based ecosystem services. These findings establish a foundation for developing integrative conservation tools based on ecosystem functioning and inform adaptive management under climate change.

ecology↗

bioRxiv2026

Hyperspectral ocean color encodes global eukaryotic phytoplankton community structure

Phytoplankton community composition (PCC) impacts global ocean change across scales. Combining the taxonomic resolution of in situ methods with the spatiotemporal coverage of satellite ocean color remains a major challenge. Phytoplankton pigments link PCC to ocean color; past work has demonstrated that 4-6 pigment-based groups can be reconstructed from hyperspectral remote sensing reflectance (Rrs({lambda})). Alternately, metabarcoding approaches reveal thousands of taxa to the species level, but the links between optics and genes are less clear. Here, we compiled a global, coincident dataset of hyperspectral Rrs({lambda}), pigments, and 18S rRNA gene sequences. We used a bio-optical model to produce the relative contributions of 13 eukaryotic phytoplankton classes identified by metabarcoding with high confidence in most cases. Model coefficients were highly spectrally correlated between genes and pigments, revealing the strong PCC signal within Rrs({lambda}). This proof-of-concept study establishes a foundation for detecting eukaryotic PCC beyond pigments in the PACE era.

ecology↗

bioRxiv2025

Genomics-based quantitative biogeography of marine plankton

Marine plankton are key drivers of ocean productivity and global carbon cycling, yet their quantitative biogeography remains poorly characterized. Environmental genomic datasets are inherently compositional, restricting analyses to relative abundances and limiting their integration into ecological and biogeochemical models. Here we combine DNA mass measurements, filtered seawater volumes, and metagenomic relative abundances to generate absolute estimates of cell concentrations and carbon biomass of plankton across the global ocean. Leveraging thousands of samples, this approach provides quantitative estimates for hundreds of eukaryotic and thousands of prokaryotic environmental genomes, unveiling ecological associations not captured by compositional data. Using the psbO marker gene, we reconstruct quantitative biogeographies of photosynthetic lineages and, through global-scale modeling, project their distributions to generate quantitative maps of phytoplankton communities across the worlds ocean. By bridging genomic data with biogeochemical metrics, this study provides novel resources for integrating plankton at genomic resolution into next-generation biogeochemical models.

genomics↗

bioRxiv2022

Global observation of plankton communities from space

Satellite remote sensing from space is a powerful way to monitor the global dynamics of marine plankton. Previous research has focused on developing models to predict the size or taxonomic groups of phytoplankton. Here we present an approach to identify representative communities from a global plankton network that included both zooplankton and phytoplankton and using global satellite observations to predict their biogeography. Six representative plankton communities were identified from a global co-occurrence network inferred using a novel rDNA 18S V4 planetary-scale eukaryotic metabarcoding dataset. Machine learning techniques were then applied to train a model that predicted these representative communities from satellite data. The model showed an overall 67% accuracy in the prediction of the representative communities. The prediction based on 17 satellite-derived parameters showed better performance than based only on temperature and/or the concentration of chlorophyll a. The trained model allowed to predict the global spatiotemporal distribution of communities over 19-years. Our model exhibited strong seasonal changes in the community compositions in the subarctic-subtropical boundary regions, which were consistent with previous field observations. This network-oriented approach can easily be extended to more comprehensive models including prokaryotes as well as viruses.

ecology↗