Predicting forest tree leaf phenology under climate change using satellite monitoring and population-based GWAS DOI Creative Commons
Markus Pfenninger, Liam Langan, Barbara Feldmeyer

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Май 4, 2025

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

Язык: Английский

Predicting forest tree leaf phenology under climate change using satellite monitoring and population-based GWAS DOI Creative Commons
Markus Pfenninger, Liam Langan, Barbara Feldmeyer

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Май 4, 2025

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

Язык: Английский

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