Articles
Navigating the future: unveiling the resilience of trees in evolving UK climates
Article number
1429_9
Pages
77 – 84
Language
English
Abstract
As the UK undergoes dynamic shifts in climate patterns marked by increased warmth, precipitation, and sunlight, understanding the adaptability of tree populations becomes imperative.
This study examines the long-term implications of climate change on arboreal landscapes, botanical gardens, and urban greenery.
By employing climate modelling and species occurrence data, we predict the future suitability of tree species for various environments.
Our findings highlight significant shifts towards warmer and drier conditions, particularly in urban settings.
This research enhances our understanding of tree resilience and provides a practical framework for sustainable urban and landscape planning amidst climate change.
Specifically, we focus on five common species (Betula pendula, Prunus padus, Quercus robur, Tilia cordata, Tilia platyphyllos) within the living collection of the Royal Botanic Gardens Kew, which are also prevalent in wider landscapes.
This study examines the long-term implications of climate change on arboreal landscapes, botanical gardens, and urban greenery.
By employing climate modelling and species occurrence data, we predict the future suitability of tree species for various environments.
Our findings highlight significant shifts towards warmer and drier conditions, particularly in urban settings.
This research enhances our understanding of tree resilience and provides a practical framework for sustainable urban and landscape planning amidst climate change.
Specifically, we focus on five common species (Betula pendula, Prunus padus, Quercus robur, Tilia cordata, Tilia platyphyllos) within the living collection of the Royal Botanic Gardens Kew, which are also prevalent in wider landscapes.
Authors
K.W.E. Martin, H. Sjöman
Keywords
tree species selection, urban heat mitigation, climatic adaptation, horticultural traits, seed sourcing for urban landscapes, species suitability modelling
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