Air pollution and climate change remain critical environmental challenges, particularly in urban areas, where conventional monitoring networks are often too sparse to capture fine-scale exposure gradients due to their high operational costs. Epiphytic lichen biomonitoring provides a valuable complementary approach, as these organisms are sensitive to both air pollutants and climate conditions. Despite the existence of a standardized European protocol, large-scale implementation is hindered by the absence of a robust interpretative framework and incomplete knowledge of species-specific responses to pollutants and climate variables. This study initiated the development of a standardized interpretative framework for European lichen biomonitoring data by identifying a core set of indicator species with clear responses to major air pollutants and climate variables. To achieve this, we compiled and harmonized raw lichen data from 58 studies that applied the European protocol and modeled the response of 43 lichen species to dominant air pollutants (NH3, NOx, and SO2) and climate variables (mean air temperature, mean relative humidity, and temperature seasonality). While confirming established trends, our models allowed us to decouple species responses to reduced (NH3) vs. oxidized (NOx) nitrogen compounds, a distinction rarely achievable in local studies due to insufficient contrast in pollutant gradients. We also provided actionable recommendations to enhance comparability, such as prioritizing widespread, well-studied tree species and standardizing lichen taxa groupings. Our study established a foundation for a harmonized European interpretative framework by identifying low-bias, ecologically meaningful indicator species. Future efforts should focus on translating sensitivity classifications into actionable air quality indices and refining regional-scale assessments.

Towards a New Interpretative Framework for Air Quality and Climate Biomonitoring With Lichens: A Meta‐Analysis of Surveys Using the European Protocol

Castello, Miris;Giordani, Paolo;Loppi, Stefano;Martellos, Stefano;Nimis, Pier Luigi;Paoli, Luca;
2025-01-01

Abstract

Air pollution and climate change remain critical environmental challenges, particularly in urban areas, where conventional monitoring networks are often too sparse to capture fine-scale exposure gradients due to their high operational costs. Epiphytic lichen biomonitoring provides a valuable complementary approach, as these organisms are sensitive to both air pollutants and climate conditions. Despite the existence of a standardized European protocol, large-scale implementation is hindered by the absence of a robust interpretative framework and incomplete knowledge of species-specific responses to pollutants and climate variables. This study initiated the development of a standardized interpretative framework for European lichen biomonitoring data by identifying a core set of indicator species with clear responses to major air pollutants and climate variables. To achieve this, we compiled and harmonized raw lichen data from 58 studies that applied the European protocol and modeled the response of 43 lichen species to dominant air pollutants (NH3, NOx, and SO2) and climate variables (mean air temperature, mean relative humidity, and temperature seasonality). While confirming established trends, our models allowed us to decouple species responses to reduced (NH3) vs. oxidized (NOx) nitrogen compounds, a distinction rarely achievable in local studies due to insufficient contrast in pollutant gradients. We also provided actionable recommendations to enhance comparability, such as prioritizing widespread, well-studied tree species and standardizing lichen taxa groupings. Our study established a foundation for a harmonized European interpretative framework by identifying low-bias, ecologically meaningful indicator species. Future efforts should focus on translating sensitivity classifications into actionable air quality indices and refining regional-scale assessments.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3123260
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