The science behind defensible climate-resilient species selection.
By combining climate envelope modelling, physiological trait data, future climate projections and urban heat island adjustments, Palette generates recommendations that can be understood, scrutinised and defended. Here is a more detailed explanation of the scientific frameworks underpinning the Kew Reach Climate Resilient Tree Tool, including data sources, assessment criteria and scoring methodology.
The scoring methodology
Palette uses a composite methodology informed by leading research in urban forestry, climate resilience and species selection. It is grounded in the work of Martin et al. (2025) and Hirons & Sjoman (2019) bringing together climate suitability modelling and physiological trait analysis to support climate resilient species selection.
Rather than relying solely on historic planting performance or generic species lists, Palette evaluates future climate scenarios alongside key biological characteristics to generate evidence-based recommendations.
The result is a practical suitability score that helps practitioners identify species that are both climate resilient and fit for purpose.
The data behind it
Palette recommendations are informed by multiple scientific datasets and research sources, combining species distribution data, future climate projects, physiological plant traits and local environmental factors.
These inputs include:
Climate envelopes
Climate envelope modelling built on global species distribution and biodiversity datasets
Plant physiology
Drought and heat tolerance traits, including turgor loss point and wood density
Future climate
Future climate projections for UK locations under 2050 and 2090 scenarios
Resilience traits
Species characteristics that shape resilience, establishment and long-term performance on site
Urban heat
Urban heat island adjustments reflecting real growing conditions in towns and cities
Kew evidence
Performance and tolerance data from Kew's botanic collections and screening programmes
By combining these datasets, Palette moves beyond traditional plant selections methods to provide site-specific recommendations grounding in scientific evidence.
Kew-derived vs. Kew-reviewed.
Palette combines data, research and methodologies from multiple sources. Some components are derived directly from Kew research and collections, while others incorporate external datasets and published scientific literature.
All recommendations are generated through a methodology developed with scientific oversight and review, drawing on Kew expertise alongside established external data sources.The detailed methodology, documentation, data provenance and technical caveats are available on request.
