A 2026 study by Ye, Zhengyang from Borealis Harvested Dataverse uses landscape genomics to analyze climate adaptation in the interior spruce hybrid complex. The dataset includes 41,253 SNPs genotyped from 1,692 individuals across 252 natural populations in western Canada. It delineates seed zones and predicts genomic offset to future climate scenarios, validated by common-garden experiments.
Use Cases
- Delineate seed zones for reforestation based on genomic variation and climate relationships described in the study
- Predict genetic offset and maladaptation risks under future climate scenarios using the gradient forest modeling approach
- Validate genomic predictions with fitness-related traits like height and DBH from common-garden experiments mentioned in the description
- Assess population vulnerability and define species boundaries for the interior spruce complex based on adaptive genetic variation
Strengths
- Includes 41,253 SNPs genotyped from 1,692 individuals, providing a substantial genetic marker set
- Covers 252 natural populations across western Canada, offering broad geographic representation
- Predictions validated with fitness measurements from common-garden experiments, linking genomics to phenotypic traits
- Delineated 11 seed zones with 88.2% concordance with previous genetic studies, demonstrating methodological reliability
Limitations
- Column-level documentation is absent; field semantics must be inferred after download
- Row count is unknown, which may limit suitability assessment
- Data may reflect geographic bias inherent to the sampled populations in western Canada
Provenance
- Source
- Borealis Harvested Dataverse
- Collection Method
- Gradient forest modeling applied to SNP data from natural populations and common-garden experiments.
- Freshness
- Last updated 2026-06-13 04:11:13
- Geography
- Western Canada