Using Genomics to Inform Management of Tree Populations in a Warming World

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ID: 328799
2026
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Ranked #34 of 49 articles by views in international journal of forestry research

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Abstract
Abstract Tree populations are threatened by a multitude of human activities ranging from deforestation to air pollution. Rapid climate change, including warmer temperatures and increased drought frequency, poses a particular threat by reducing photosynthesis and growth, increasing susceptibility to pests and disease, and intensifying risk of mortality. To maintain healthy forests in the future, resource managers could benefit from practical tools to identify vulnerable populations and select appropriate seed sources for restoration and reforestation. In this paper, we outline four recently developed genomic approaches that can help guide these assessments. First, combining long-term growth data from provenance studies with genetic information makes it possible to identify traits associated with better performance under warmer climates, allowing managers to select climate-adapted planting material. Second, analyzing how genetic variation changes across climate gradients can highlight which tree stands may be most at risk under future conditions. Third, experimental studies on seedlings can identify genes involved in stress responses, improving our ability to predict how different populations will respond to climate change. Fourth, epigenetic markers, which are chemical changes to DNA that can influence gene activity, may provide early indicators of stress that may help identify vulnerable populations and resilient seed sources. As climate change accelerates, these genomic and computational tools offer new opportunities for informed, forward-looking management strategies for forest conservation and restoration.
Reference Key
openalex_W7213306038 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Victoria L. Sork, Ryan Buck, Lily D. Peck
Journal international journal of forestry research
Year 2026
DOI
10.1007/s44392-026-00115-7
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