ArticleScientific reports2026
Monitoring environmental heat on urban green infrastructure in central Italy based on the florence case study.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Urban green infrastructures (GI) are increasingly affected by environmental fluctuations which may impair photosynthetic performance and reduce ecosystem services. This study aimed to assess the health state of urban GI ecosystems in Florence, Italy, from May to October 2023, using different plant species (Arundo donax, Laurus nobilis and Artemisia verlotiorum) as bio-indicators monitored throughout their entire vegetative season. To this end, chlorophyll-a fluorescence (JIP-test), optical leaf traits, and meteorological indicators were integrated. Climate data showed frequent heat stress conditions, with 70–87% of summer days exceeding 30 °C and up to 45% surpassing 35 °C. L. nobilis exhibited the strongest heat sensitivity in July–August, showing a reduction in PIABS, whereas A. donax and A. verlotiorum maintained FV/FM values within optimal ranges (0.75–0.85). Energy fluxes (ABS/RC, TRo/RC, DIo/RC) peaked in summer across species, indicating increased excitation pressure on PSII. Optical traits revealed species-specific strategies: A. donax, showed the highest chlorophyll content, particularly in October (1.1 ru, p < 0.001), while A. verlotiorum accumulated the most flavonols, with peak values in May and August (1.65 ru, p = 0.003), highlighting their photoprotective role under high irradiance and temperature. Linear models confirmed strong associations between heat predictors and variables such as PIABS and FV/FM, supporting their value as indicators of thermal stress. Exploratory heat impact models revealed a clear relationship between environmental temperature and fluorescence-derived parameters, supporting their potential as sensitive indicators of urban thermal stress. These findings provide the basis for developing precision urban heat models for green infrastructures using chlorophyll fluorescence parameters combined with environment-based predictors.
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