Key Expoitable Results (KERs)

Life history traits influence marine species dispersal and habitat colonization. Medusozoans (jellyfish and siphonophores) exhibit diverse life cycles, evolved from an ancestral cycle alternating between a benthic polyp and a pelagic medusa. Despite their ecological importance, factors shaping medusozoan distribution remain poorly understood. By integrating metabarcoding and environmental data from the Tara Oceans expedition with life history traits, we provide global evidence supporting the longstanding hypothesis that benthic polyp presence/absence is a key factor influencing the distribution and abundance of planktonic medusozoans in the surface ocean. We inferred on a time-calibrated phylogeny of Medusozoa multiple transitions to a fully planktonic (holoplanktonic) life cycle, either through polyp loss, acquisition of drifting polyps, or development of polyps parasitizing pelagic organisms. We could associate each transition with a shift toward offshore habitats and the emergence of globally dominant Operational Taxonomic Units (OTUs), whose abundance far exceeds that of any nonholoplanktonic medusozoans in the planktonic realm. The prevalence of holoplanktonic medusozoans in terms of abundance and diversity is broadly observed in coastal and offshore environments, peaking over greater bathymetric depths in tropical and subtropical regions. We show that holoplanktonic and nonholoplanktonic groups interact with distinct yet compositionally similar planktonic communities. Holoplanktonic OTUs occupy more peripheral positions in a plankton interactome, suggesting greater flexibility in biotic interactions, an adaptive trait in rapidly changing planktonic ecosystems. These findings highlight how life cycle evolution shaped the global distribution of medusozoans and suggest that variations in life history may significantly influence how medusozoans respond to global environmental changes.

Spatial synchrony, the tendency for temporal fluctuations in an ecological variable to be positively associated in different locations, is a widespread and important phenomenon in ecology. Understanding of the nature and mechanisms of synchrony, and how synchrony is changing, has developed rapidly over the past two decades. Many recent developments have taken place through the study of long-term datasets. Here, we review and synthesize some important recent advances in spatial synchrony, with a focus on how long-term data have facilitated new understanding. Longer time series do not just facilitate better testing of existing ideas or more precise statistical results; more importantly, they also frequently make possible the expansion of conceptual paradigms. We discuss several such advances in our understanding of synchrony, how long-term data led to these advances, and how future studies can continue to improve the state of knowledge.

Microfluidic technology can expedite nucleic acid testing by converting the functions of bulky laboratory instruments and protracted bench methodologies into easy-to-use and inexpensive miniaturised systems without compromising speed and reliability. We developed a lab-on-a-chip (LOC) platform that integrates a dimethyl adipimidate (DMA)-based functionalised silica DNA isolation and pre-concentration method with a rapid and real-time loop-mediated isothermal amplification (LAMP) for detecting domoic acid-producing phytoplankton, Pseudo-nitzschia. An optimised design of a lab on a chip extraction module achieved a maximum DNA capture capacity of 61.73 ± 0.98 ng μL−1. The DMA-based method reduced reagent costs per sample by 97% compared to a commercial nucleic acid isolation kit. A subsequent on-chip LAMP process was capable of sensitively quantifying cytochrome P450 homologous to the dabD gene, coding for a component of the domoic acid toxin production pathway, with a limit-of-detection of 10 cells per mL. LAMP-based detection of the target gene was achieved using dry-preserved reagents with a shelf-life of five months without refrigeration. There was no significant difference in assay performance between the preserved LAMP and freshly prepared LAMP mixtures. The total analysis time at the LOD of 10 cells per mL, from sample to result, was achieved within one hour. Our results demonstrate the long-term stability of assay reagents, rapid turnaround, and cost-effectiveness, offering a simple and economical approach to environmental monitoring and environmental bio-hazard diagnostics.

The library provides a shortlist of enzyme candidates obtained from data mining for later experimental characterisation. Enzymes candidates have potential for industrial applications, such as molecular diagnostics and bioremediation, as well as potentially new bioactive compounds that may support the growth of the biotechnological and pharmaceutical industry. Candidate enzymes may also contribute to research towards a better understanding of biodiversity, with applications in environmental and ecological conservation.

The main computational goals of AtlantECO for Advances in Systems Ecology were to develop cutting edge network analysis methods, to define an all-Atlantic interactome and ecological niches, and to provide indicators of ecosystem stability and sensitivity to environmental stressors and drivers. Here, we reviewed the literature for ecological network reconstruction methods from several disciplines (microbiology, ecology, bioinformatics). We built a computational pipeline for the inference of species ecological networks from heterogeneous data types, combining statistical and ecological metrics, as well as probabilistic and machine learning algorithms. Reference databases of known ecological interactions obtained from the literature can be used to benchmark and validate inferred networks. This review of network inference algorithms is accompanied by a computational workflow: AtlantEcoNet (publicly available at: https://gitlab.univ-nantes.fr/mbudinich/atlanteconet), which builds upon existing software by integrating a selection of complementary methods for ecological network inference, analysis, and validation. This workflow was used by AtlantECO to build a plankton ecological network from omics data compiled for the Atlantic Ocean.

The quantitative description of marine systems is constrained by a major issue of scale separation: phytoplankton production processes occur at sub-centimeter scales, while the contribution to the Earth's biogeochemical cycles is expressed at much larger scales, up to the planetary one. In spite of vastly improved computing power and observational capabilities, the modeling approach has remained anchored to an old view that sees the microscales as unable to substantially affect larger ones. The lack of a widespread theoretical appreciation of the interactions between vastly different scales has led to the proliferation of numerical models with uncertain predictive capabilities. In this paper, we use the phenology of phytoplankton blooms as one example of a macroscopic ecosystem feature affected by microscale interactions. We describe two distinct mechanisms that produce patchiness within a productive water column: turbulent entrainment of less-productive water at the base of the mixed layer, and stirring by slow turbulence of a vertical phytoplankton gradient sustained by depth-dependent light availability. In current eddy-diffusive models, patchiness produced in this way is wiped out very rapidly, because the time scales of irreversible mixing largely overlap those of mechanical stirring. We propose a novel Lagrangian modeling framework that allows for the existence of microscale patchiness, even when that is not fully resolved. We show, with a mixture of theoretical arguments and numerical simulations of increasing realism, how the presence of patchiness, in turn, affects larger-scale properties, demonstrating that the timing of phytoplankton blooms and vertical variability of chlorophyll in the oceanic upper layers is determined by the mutual interplay between the stirring, mixing and growing processes.

The ocean hosts a vast diversity of life, from microscopic plankton to large marine mammals, with their distribution shaped by environmental factors and species-specific traits. While ocean currents largely determine the passive transport of plankton, some species can regulate their buoyancy or actively migrate, such as diel vertical migrators (DVM). Larger, more mobile species, like fish and marine mammals, navigate their environment with stronger swimming abilities. Understanding how marine species move and interact with their environment is crucial for predicting ecosystem shifts, especially as climate change alters ocean conditions. This thesis investigates how species traits and environmental factors influence the transport and connectivity of marine organisms using Lagrangian flow modeling. Three case studies explore the dispersal of different marine species: vertically migrating zooplankton, thermally constrained plankton, and cold-stunned Kemp’s ridley turtles. The first study (Chapter 2) examines DVM zooplankton in the Benguela upwelling system, comparing their movement to that of floating and sinking materials such as phytoplankton, nutrients, and biogenic matter. Results show that DVM zooplankton separate more rapidly from other materials, especially during the upwelling season. However, coherent ocean features like eddies and filaments trap different particle types together, potentially increasing interactions between zooplankton, their prey, and pollutants. Chapter 3 applies network theory to Lagrangian modeling to assess minimum time connectivity pathways in the Atlantic Ocean. Passive plankton can theoretically connect all Atlantic locations within three years, but connectivity time increases with depth. When thermal constraints are introduced, connectivity across the basin is reduced, emphasizing the role of environmental preferences in species dispersal. Chapter 4 investigates Kemp’s ridley turtle strandings in the Netherlands, using Lagrangian modeling to trace their drift pathways. Findings suggest that juvenile turtles become cold-stunned in the southern North Sea and experience temperatures below 12°C for up to a month. These results highlight the need for targeted rehabilitation and conservation strategies for this critically endangered species. Together, these studies demonstrate that both species traits and environmental constraints shape marine organism dispersal, influencing ecological interactions and habitat connectivity. As climate change alters ocean temperatures and circulation, species distributions will shift, affecting marine food webs and conservation planning. Future research should refine species-specific behavioral models and integrate dispersal with ecosystem dynamics to better inform marine conservation strategies.

This work combines ecological and macroeconomic approaches to assess the economic costs of climate change impacts on Net Primary Production in the Atlantic Ocean by 2050. The novelty of this study lies in introducing ecological limits in the fishery sector of the Computable General Equilibrium model used for macroeconomic assessment. To control socio-economic and climate uncertainties, we include projections from three CMIP6 climate models under two Shared Socioeconomic Pathways. Our results suggest a substantial economic loss by 2050 in Western African regions higher than 1% of Gross Domestic Product in most of the scenarios. This is the consequence of the impact on Net Primary Production and the strong increase in global fishery prices, which will affect the future economic structure. Economic losses and increases in fish prices are strongly amplified when biophysical constraints on fishery expansion are introduced in the macroeconomic model.

Marine planktonic communities carry out almost half of the net primary production on our planet, keep atmospheric CO2 levels at roughly half of what they would be otherwise, form the base of food webs and produce more than half of the oxygen we breathe. Considering the wealth and economic importance of ecosystem services and climate regulation provided by our oceans fuelled from the very base of its food web, impacts of climate change on marine plankton are still poorly investigated. Within this project we aim to overcome disciplinary boundaries that contribute to impeding exchanges of scientific results between the research community and policy makers. We aim to build an interactive web tool for policy makers to help visualise future projections of climate change impact on global plankton ecosystems as a function of societal decisions. We continue the effort made by the ETH Environmental Physics (UP) Group (Zürich, Switzerland) that has mapped the biogeography of hundreds of plankton species and use this knowledge to define biomes for the surface ocean and identify hotspots of plankton diversity changes under global warming. We aim to include three fully coupled Earth System Models from the Coupled Model Intercomparison Project Phase CMIP5 using three different representative concentration pathways (RCP 2.6, RCP 4.5, RCP 8.5) covering the period from 2012 until 2100. We will translate projections into quantitative global impact metrics targeted at policy makers and characterize ecosystem impacts as a function of carbon emissions and global warming. International decision-makers are informed on potential future changes in global marine plankton and can start addressing challenges to marine conservation.