The objective of the MioCarb project is to study a remarkable event called Biogenic Bloom and to understand its origin and impact on the carbon cycle. The Biogenic Bloom event is marked by a strong increase in planktonic primary productivity. During this event, the high productivity had an impact on the carbon cycle. However, a decrease in pCO2 is observed in the same time interval as the Biogenic Bloom. However, the causal links between these two events have not been established. To do so, it is necessary to quantify primary productivity at high temporal resolution, on a large geographical scale and to apply a climate modelling approach.
Exploring the changing structure of the oceanic carbonate system and the natural history of atmospheric CO2 using geochemical proxies.
Principal Investigator: Thomas Chalk Participants: Abel Guihou, Matthieu Buisson, Rachel Brown
Our knowledge of carbon dioxide (CO2) concentrations in the atmosphere of the past is fundamental to understanding the Earth’s climate for the past, present and future. Ice cores, the product of an international effort, make it possible to recover air bubbles from ancient atmospheres trapped in the ice. They have provided us with 800,000 years of high-resolution, accurate data, revolutionising our understanding of the Earth system. ForCry, a technique designed by ERC award recipient Thomas Chalk, will enable us to move into a new generation of climate data from the past.
Marine sediments offer the potential to recover high spatial and temporal resolution records of modern and past ocean pH and hence CO2 levels at these times. However, to date, the generation of these data is limited by intensive analytical methods that restrict their high-throughput application and the need to analyse many samples that limit their applicability.
Improvements are needed to answer the fundamental questions:
“Is climate sensitivity correlated with baseline status? ”
The ForCry project will achieve optimal sensitivity of the laser ablation methodology by freezing tiny samples in an ice ‘puck’. This will allow analyses to be carried out with samples about 10 times smaller than conventional methods while maintaining good accuracy. ForCry will explore multiple facets of Earth System science by extending the use of laser ablation methodology to new fossil records, as well as mapping ocean pH change in all four dimensions (spatial and temporal).
Changing CO2 levels will be used to examine the state dependency of climate sensitivity in warm periods of the geological past. ForCry will examine the role of the ocean in fixing and/or regulating past, present and future CO2 at unprecedented resolution.
Aquatic ecosystems are subject to numerous anthropogenic pressures. This calls for the development of innovative ecological diagnostic tools to support robust management measures. Current tools can assess ecological status based on taxonomic characteristics (i.e., species lists) and/or functional traits (i.e., individual phenotypic attributes) of a given group of organisms. However, these approaches often rely on morphological criteria that can be difficult to characterize. In this context, the objective of BIOINDIC-IA is to enhance the biomonitoring of aquatic ecosystems by using artificial intelligence to automatically analyze taxonomy (species) and morphological traits from microscopy images. The project focuses on two model organisms: benthic freshwater diatoms, recognized as bioindicators in the European Water Framework Directive, and marine benthic foraminifera, which are rarely included in ecological assessments despite their acknowledged potential for coastal water biomonitoring.
Coastal marine ecosystems, particularly in tropical areas, are under considerable pressure from climate change and human activities. Water stratification, exacerbated by global warming and increased microbial respiration, is leading to the gradual deoxygenation of sub-surface waters. Not only does this disrupt biogeochemical cycles, it also threatens biodiversity and the fish stocks that are essential to local populations.
The coasts of Senegal are facing a gradual extension of anoxic zones, particularly in coastal regions near mangrove lagoons. The massive input of organic matter by mangroves, combined with the deoxygenation induced by global warming, is profoundly altering biogeochemical balances. These disturbances can lead to a reduction in the quality of fish stocks and have a negative impact on local fishing, a vital sector for the regional economy. Despite the importance of these issues, the mechanisms and evolution of these processes remain largely unknown in this context.
The MANGO project aims to shed light on these complex phenomena by studying changes in oxygen content and nutrient cycles in Senegal’s coastal zones, with particular emphasis on the influence of mangroves.
MANGO’s main objective is to reconstruct the history of oxygen levels over the last century and to unravel the mechanisms responsible for its variations. More specifically, the project aims to understand..:
How has oxygen content changed over the last century along the Senegalese coast?
How much of the observed change is attributed to oceanic changes and how much to changes in the mangroves in the lagoons?
To answer these questions, MANGO is adopting an integrated, multidisciplinary approach:
Fieldwork and sampling Sediment cores and surface sediment samples will be taken from two key sites, located at the mouths of the Mbodiène and Joal-Fadiouth lagoons. These samples will be used to reconstruct oxygen dynamics over a hundred years or so, as a function of local and oceanic variations.
Biogeochemical analyses Precise measurements of oxygen, pH and temperature will be taken in the field. In the laboratory, the study of stable isotopes of carbon (δ13C) and nitrogen (δ15N) will provide robust indicators of the origin and evolution of organic matter, as well as denitrification processes.
Study of benthic foraminifera These micro-organisms, which are sensitive to oxygenation conditions, will be used as bio-indicators to reconstruct the history of environmental variations. A low-cost imaging system (SASHIMI), combined with AI annotation and morphometric analysis tools, will be deployed to automate species identification and quantification.
Sediment modelling By calibrating a sediment model (RADI), the data collected will be integrated to simulate the dynamics of oxygen gradients in sediments. This modelling will make it possible to identify the dominant processes (degradation of organic matter, inputs from mangroves, mineral precipitation) and to predict their future evolution.
The MANGO project aims to provide a better understanding of the biogeochemical processes influencing Senegalese coastal ecosystems. By shedding light on the interaction between mangrove inputs and oceanic conditions, it will contribute to :
Preserving fish stocks and implementing sustainable management strategies.
Building local capacity in quantitative micropalaeontology and environmental modelling.
The development of international scientific collaborations, encouraging North-South and South-South exchanges.
MANGO is also in line with the priorities of the ECLAIRS 2 LMI and is actively involved in the IRD’s initiatives to promote sustainable science and combat the effects of climate change.
The Humboldt Current System off the coast of Peru is an eastern boundary upwelling system, where trade winds push surface waters offshore, allowing cold, nutrient-rich deep waters present to reach the surface. This process fuels high primary production in surface waters, making the region one of the most biologically productive in the world. As a result, its fisheries account for approximately 10% of global fish catches. Despite its importance, the ecosystem’s sensitivity to environmental change—especially events like El Niño—remains poorly understood. Yet, shifts in phytoplankton composition or structure are known to have wide-reaching impacts on the efficiency of the food web. One reason for this knowledge gap is the difficulty of studying the diverse phytoplankton groups together, as their sizes span several orders of magnitude.
DEEP-UP (Deep-Learning Applied to Phytoplankton from the Peruvian Upwelling) aims to study how phytoplankton communities respond to environmental forcing off the coast of Peru. It includes the development of low-cost solutions for automatic image acquisition and image recognition, and a scientific assessment of the spatio-temporal changes affecting the phytoplankton community in this productive ecosystem.
Cyclicité des paléoclimats et de l’évolution du plancton : un test intégré de l’hypothèse climatique – ITCH
PI : Clara Bolton (CEREGE)
Oceanic plankton are sensitive to physical and biochemical changes in the surface ocean, and are key modulators of the ocean carbon cycle via photosynthesis and calcification. Fossil plankton remains exported to the seafloor and preserved in sediments thus hold key clues on both past climate changes as well as associated biological responses and feedbacks. The western equatorial Indian Ocean (WEIO) is a major player in tropical ocean-atmosphere climate dynamics, with far-reaching impacts on global climate patterns. In 2021, the SCRATCH cruise onboard the research vessel Marion Dufresne II collected high-quality, complete sediment cores spanning the Pleistocene (last ~2 million years) from the WEIO, with the aim of resolving past climate variability and volcanic activity in this important region. Here, we propose to study the co-evolution of plankton, coral reefs, and climate over the Pleistocene. We will perform paired paleogenetic, biomarker, and microfossil analyses, as well as reconstruct key paleoceanographic variables to constrain background climate change, in four sediment cores recovered during SCRATCH. Using state-of-the-art methodologies across three partner institutes, we will combine expertise on paleoceanography, organic geochemistry, genetics, and micropaleontology to address the hypothesis that cyclical changes in the morphology of plankton fossils represent genetic evolution, forced by external climate cycles. Anticipated results will (1) provide a comprehensive picture of paleoceanographic evolution of the WEIO, including Indian Ocean Dipole mean state, (2) demonstrate for the first time the relationship between genetic and morphological plankton evolution in multiple groups, and (3) shed light on external (climatic, volcanic) drivers of evolution, plankton community dynamics, and pelagic and neritic marine productivity.
CEREGE – Automate de tri de foraminiferes – Technopole de lenvironnement Arbois-Mediterranee – Aix-en-Provence. François Moura / MAMP
Complex natural materials (sediments & food products), or from industry (waste) need to be sorted for their analysis and recovery. CEREGE has developed with ATG Technologies, a SME specialized in robotics, a microparticle sorting automaton, capable of sorting microorganisms thanks to image recognition based on convolutional neural networks (patent pending, Marchant & al, 2020). This automaton, MicroFossil Sorter (MiSo), the first in the world, is routinely used at CEREGE to image and sort microfossils and waste residues. This automaton is the basis of a second version of the sorter including X-ray detectors [Equipex+ IMAGINE-2, financed]. Nevertheless, the increase in power of microparticle sorting also requires the development of new treatment processes in addition to these new sensors. The objective of the MicroTrEE project is to develop with ATG a new generation of intelligent sorting automatons that will (i) maintain AMU & ATG’s lead in the field by incorporating 3D, parallelizing the processing chains, incorporating ML algorithms to manage each chain and robotize the cleaning of the automaton, but also (ii) develop new applications in environment, paleoenvironments and mining exploration.
