Biodiversity and allergenic risks: Modeling the impact of climate change and extreme events on the distribution and phenology of allergenic plants

The One Health approach recognises that environmental changes directly affect human well-being, highlighting the close link between human health and the health of ecosystems. Airborne pollen is a striking example of how biodiversity and climate interact to influence public health. It affects up to 40% of adults in Europe (D’Amato et al., 2007) and this trend is expected to worsen with climate change. However, current risk assessments often overlook biodiversity dynamics, the ecology of species, and their physiological features (functional traits). Traditional monitoring focuses on a few genera and rarely identifies pollen at the species level, limiting its ecological and medical relevance. Furthermore, most predictive models ignore how future plant distributions and species-level dynamics will affect pollen dispersion (Wozniak & Steiner, 2017; Zhang & Steiner, 2022).

This project aims to fill these gaps by combining species-specific distribution forecasts, plants functional traits, and ecological strategies. By linking airborne pollen patterns to ecological processes and climate change, we seek to improve allergy risk prediction and develop a complete framework that connects biodiversity, functional traits and public health outcomes, deepening our understanding of the ecological strategies that drive allergenic pollen production.

H1 — Allergenic plants exhibit distinct ecological strategies.

Species that produce allergenic pollen differ functionally and ecologically from non-allergenic species. Their specific combinations of traits (e.g. phenology, dispersal mode and life strategy) may define the ecological strategies associated with a higher allergenic potential.

H2 — Trait-informed species distribution models (SDMs) improve allergenic risk prediction.

By modelling the future distributions of allergenic species at species level and incorporating functional traits into SDMs, we can provide climate models with more realistic inputs and produce finer, more reliable forecasts of future pollen emissions.

H3 — Biodiversity can mitigate allergenic risk (Dilution Effect Hypothesis).

High local biodiversity could mitigate human exposure to and sensitisation to allergenic pollen by diluting dominant allergenic taxa within more diverse plant communities.

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