Oliver Selmoni
Oliver is a Living Planet Fellow at the University of Zurich, where he leads a unit on Landscape and Climate Change Genomics. His work focuses on measuring the impact of global change on biodiversity, so that effective mitigation strategies can be informed. His research combines satellite observation, to assess how habitats are altered by global change, with genetic analysis of species, to uncover how ecosystems respond to these environmental pressures. Oliver trained as a bioinformatician at University of Lausanne, and then earned his PhD at EPFL in collaboration with the French Institute of Research for Development (IRD). His doctoral research examined the adaptive potential of reef-building corals against marine heatwaves. He then developed the Reef Environment Centralized Information System (RECIFS), an open access web-interface to explore global change impacts on coral reefs worldwide. Oliver joined the Carnegie Institution for Science for a postdoc at Johns Hopkins and Stanford Universities, focusing on finding the genes that underlie coral adaptation to warming oceans. Coupling genomic data with climate change scenarios, he produced the first global predictions of genomic vulnerability of coral reefs against climate change. In his current work at UZH, Oliver’s unit investigates the impact of climate change on the genetic diversity of marine and terrestrial ecosystems.
The loss of genetic diversity in marine wildlife is making oceans more vulnerable to climate change. Monitoring this genetic erosion is essential for timely conservation, yet remains highly resource-demanding. The genEOcean project leverages Earth Observation (EO) to efficiently monitor marine genetic diversity and guide rapid conservation action.
Species genetic diversity is a key component of biodiversity that enables ecosystems to adapt to environmental change. Recent studies indicate that the genetic diversity of wild species is at risk and call for improved monitoring. Pionneering approaches now advocate the use EO to facilitate genetic diversity monitoring. While EO cannot directly measure genetic diversity, it can track habitat change over time. Because habitat availability influences the size and distribution of a species’ populations, habitat loss often leads to reduced genetic diversity. Thus, when EO detects habitat decline across multiple populations of a species, it likely signals genetic erosion.
Applying this framework to marine ecosystems is challenging. Marine habitats are highly dynamic in space and time, and cannot be easily captured by a single EO product such as a land-cover time series. Numerous EO-derived datasets describe different aspects of seascapes—such as structure (e.g., depth, distance to coastline), water physics (e.g., temperature, current velocity), biochemistry (e.g., pH, chlorophyll, nutrient concentrations), and anthropogenic pressure—but it remains unclear which of these variables are most relevant for monitoring the genetic diversity of marine taxa.
The genEOcean project will identify the EO-derived seascapes classes that best predict genetic diversity changes across marine taxa. We will compile and harmonize global databases of marine genetic diversity to describe spatial and temporal patterns across species. In parallel, we will process a wide range of EO-derived environmental products to classify the world’s oceans into seascape classes. Machine learning models will then link global patterns of genetic diversity with the temporal dynamics of these seascape classes, identifying those that most effectively explain and predict changes in genetic diversity.
The Genes from Space project is developing an interactive online tool that allows users to monitor genetic diversity of terrestrial species using EO data. The tool offers an intuitive interface that enables non-experts to track habitat change for their species of interest and to identify populations potentially at risk. The genEOcean project will expand this capability to the marine realm, introducing new datasets and functionalities that make the tool applicable to oceanic species and ecosystems.
On a research level, genEOcean advances two major frontiers in earth system science:
1. What is the status of genetic diversity in our oceans?
Existing meta-analyses primarily characterize genetic diversity on land or focus on specific marine taxa (e.g., fish or habitat-forming species). To date, there is no consolidated estimate of the overall trends of genetic diversity in the oceans. We do not yet know whether genetic diversity is declining at a similar pace as in terrestrial ecosystems, which taxa are most affected, or which regions are most vulnerable. In genEOcean, we will address these questions by harmonizing existing global databases on marine genetic diversity to produce the first integrated assessment of genetic diversity in the ocean.
2. Can Earth Observation (EO) predict oceanic genetic diversity?
Numerous studies in seascape genomics have used EO-derived datasets to explain spatial patterns of genetic diversity, but these efforts are typically restricted to single species or regions, limiting their generality. As a result, predictive EO-based models of marine genetic diversity remain elusive. genEOcean will overcome this limitation through a comparative analysis across hundreds of taxa to identify which EO-derived seascape classes are most useful for predicting genetic diversity change across the oceans.
Beyond its scientific innovation, genEOcean, as part of Genes from Space, also addresses a key policy gap:
3. How can we monitor genetic diversity efficiently?
Under the 2022 Global Biodiversity Framework, most countries on Earth committed to establishing monitoring systems to safeguard genetic diversity. However, practitioners still lack operational tools to meet this obligation. Satellite-based observations can play a crucial role in this context. The Genes from Space monitoring tool provides practical guidance for non-EO experts on using EO data to track species genetic diversity, and genEOcean will extend this capability to marine species and ecosystems.
