Biology subjects

Eberhardt, L.

Publications and source records attributed to Eberhardt, L..

5 recordsLinked to original sources

bioRxiv2026

Standing Genomic Variation inferred by popGWAS Predicts Seedling Drought Survival Experiment in Fagus sylvatica

Intensifying drought regimes across Central Europe, driven by global climate change, pose an increasing threat to forest regeneration, with the seedling stage representing the primary demographic bottleneck for long-lived tree species such as Fagus sylvatica. While intraspecific phenotypic variation in drought resistance among beech seedlings has been documented, the genomic basis of this variation remains poorly understood. Existing provenance trial approaches capture broad-sense heritability but lack the resolution to identify specific causal loci. To address this gap, we conducted a controlled soil drought experiment with Fagus sylvatica seedlings and applied a population-level genome-wide association study (GWAS), and leveraged individual survival length as a direct fitness proxy. We detected substantial variation in survival duration (10-40 days) among populations, with corresponding allele frequency differences at candidate loci whose functional annotations partially reflect known responses to environmental stress. Notably, seedlings sourced from an official seed bank consistently underperformed relative to wild-collected material, suggesting that current seed sourcing practices may inadvertently deplete adaptive genetic diversity. Our results demonstrate that standing genomic variation in natural Fagus sylvatica populations predicts differential seedling drought survival, and that the species retains substantial genetic potential to cope with prolonged spring drought when natural genetic diversity is preserved. These findings have direct implications for assisted migration strategies and seed sourcing guidelines under projected climate scenarios.

evolutionary biology↗

bioRxiv2026

Climate change intensifies rapid genomic selection beyond the ancestral niche of Fagus sylvatica

As climate change accelerates, the persistence of long-lived organisms increasingly depends on their capacity to adapt in situ. While phenotypic plasticity provides an immediate buffer, it remains uncertain whether forest trees can evolve rapidly enough to track shifting climatic niches. Here, we investigate the adaptive potential of European beech (Fagus sylvatica L.), a keystone temperate species, by leveraging different growth classes as a quasi-time-series. This approach allows us to compare growth classes established under the relatively stable climate of the early 20th century against those regenerating under contemporary warming (+1.1{degrees}C global mean temperature increase). Integrating pool-seq data from three growth classes across 43 sites in Germany with satellite-derived environmental stress indicators, we characterised past, current and projected future climate-driven selection. We detected rapid, genome-wide selective sweeps between the oldest and youngest growth classes, particularly in sites already exceeding their historical climatic niche (defined as the 95% confidence interval of pre-warming conditions). Notably, selection signatures have shifted over time: while older classes show signatures related to biotic interactions, younger cohorts exhibit intense selection on genes managing abiotic heat and drought stress. In the warmest regions, we estimated exceptionally high selection coefficients (s{approx}2), suggesting intense selection where beech trees exceed their ancestral niche. In older growth classes, distance and geology account for genetic differences between populations but in young growth classes climate is the primary factor, highlighting the importance of climate change. However, predictive modelling reveals a critical threshold to this resilience. While adaptive potential appears sufficient to maintain population persistence under low-emission scenarios (SSP1-2.6), high-emission trajectories (SSP5-8.5) are projected to rapidly outpace the species evolutionary capacity. These findings demonstrate that while trees can undergo remarkably rapid genomic shifts, the sheer velocity of unmitigated climate change threatens to exceed the fundamental limits of forest adaptation.

evolutionary biology↗

bioRxiv2025

Pervasive and dynamic release of Cryptic Genetic Variation in Chironomus riparius: Rethinking adaptation in fluctuating environments

The interplay between phenotypic plasticity and cryptic genetic variation (CGV) is crucial for understanding adaptation, yet the prevailing paradigm suggests CGV is primarily exposed under novel or extreme conditions. By examining gene expression responses along a natural temperature gradient in Chironomus riparius, we challenged this view. We found that the vast majority of expressed genes (63%) exhibit dynamic CGV, where interindividual expression variability scales continuously with distance from the selectively optimal temperature, a pattern also observed in higher-level traits like mutation rate and ROS levels. Genes with lower overall expression levels were less temperature-regulated, and thermal reaction norm shapes varied with gene function. Unexpectedly, thermally plastic genes were more pleiotropic, often acting as hub genes, while CGV in gene expression was associated with lower pleiotropy. This pattern, and the observed strong recurrent selection on plastic genes with CGV, aligns with C. ripariuss adaptation to its highly fluctuating environment through selective tracking. We propose that this continuous, dynamic release of genetic variation is a necessary and inherent outcome of the polygenic nature of traits. This model fundamentally reshapes our understanding of adaptation, implying that populations can gradually and continuously adapt without requiring harsh conditions to expose hidden diversity. This leads to smoother adaptive landscapes, enhancing rapid adaptation and facilitating evolutionary innovation in the face of ongoing environmental change.

evolutionary biology↗

bioRxiv2025

Predicting forest tree leaf phenology under climate change using satellite monitoring and population-based GWAS

Leaf phenology, a critical determinant of plant fitness and ecosystem function, is undergoing rapid shifts due to climate change, yet its complex genetic and environmental drivers remain incompletely understood. Understanding the genetic basis of phenological adaptation is crucial for forecasting forest responses to a changing climate. Here, we integrate multi-year satellite-derived phenology from 46 Fagus sylvatica (European beech) populations across Germany with a population-based genome-wide association study to dissect the environmental and genetic drivers of leaf-out day (LOD) and leaf shedding day (LSD). We show that environmental factors, particularly temperature forcing and water availability, are the primary drivers of LOD variation, while LSD is influenced by a more complex suite of climatic cues. Our genomic analysis identifies candidate genes associated with LOD and LSD, primarily linked to circadian rhythms and dormancy pathways, respectively. Furthermore, genomic prediction models incorporating these loci accurately reconstruct past phenological dynamics, providing a powerful framework to forecast forest vulnerability and adaptation to future climate change.

evolutionary biology↗

bioRxiv2024

Transcriptomics predicts Artificial Light at Night's (ALAN) impact on fitness: nightly illumination alters gene expression pattern and negatively affects fitness components in the midge Chironomus riparius (Diptera:Chironomidae)

The emission of artificial light at night (ALAN) is rapidly increasing worldwide. Yet, evidence for its detrimental effects on various species is accumulating. While the effects of ALAN on phenotypic traits have been widely investigated, effects on the molecular level are less well understood. Here we aimed to integrate the effects of ALAN at the transcriptomic and the phenotypic level. We tested these effects on Chironomus riparius, a multivoltine, holometabolous midge with high ecological relevance for which genomic resources are available. We performed life-cycle experiments in which we exposed midges to constant light and control conditions for one generation. We observed higher EmT50 and reduced fertility under ALAN. From the observed decline in population size due to the reduced fertility, we predicted the population size to decline to 1% after 200 days. The transcriptomic analysis revealed expression changes of genes related to circadian rhythmicity, moulting, catabolism and oxidative stress. From the transcriptomic analysis we hypothesised that under ALAN, oxidative stress is increased, and that moulting begins earlier. We were able to confirm both hypotheses in two posthoc experiments, showing that transcriptomics are a powerful tool in predicting physiological outcomes before they are even observable.

molecular biology↗