Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloNeural Network Analysis to Evaluate Ozone Damage to Vegetation Under Different Climatic Conditions
Anno di pubblicazione2020
Autore/iSavi, Flavia; Nemitz, Eiko; Coyle, Mhairi; Aitkenhead, Matt; Frumau, Kfa; Gerosa, Giacomo; Finco, Angelo; Gruening, Carten; Goded, Ignacio; Loubet, Benjamin; Stella, Patrick; Ruuskanen, Taaina; Weidinger, T.; Horvath, L.; Zenone, Terenzio; Fares, Silvano
Affiliazioni autoriCouncil Agr Res & Econ CREA; Ctr Ecol & Hydrol CEH; James Hutton Inst; Energy Res Ctr Netherlands; Univ Cattolica Sacro Cuore; European Commiss; Univ Paris Saclay; Univ Paris Saclay; Univ Helsinki; Eotvos Lorand Univ; Hungarian Meteorol Serv; Szent Istvan Univ; Univ Exeter; CNR
Autori CNR e affiliazioni
  • inglese
AbstractTropospheric ozone (O-3) is probably the air pollutant most damaging to vegetation. Understanding how plants respond to O(3)pollution under different climate conditions is of central importance for predicting the interactions between climate change, ozone impact and vegetation. This work analyses the effect of O(3)fluxes on net ecosystem productivity (NEP), measured directly at the ecosystem level with the eddy covariance (EC) technique. The relationship was explored with artificial neural networks (ANNs), which were used to model NEP using environmental and phenological variables as inputs in addition to stomatal O(3)uptake in Spring and Summer, when O(3)pollution is expected to be highest. A sensitivity analysis allowed us to isolate the effect of O-3, visualize the shape of the O-3-NEP functional relationship and explore how climatic variables affect NEP response to O-3. This approach has been applied to eleven ecosystems covering a range of climatic areas. The analysis highlighted that O(3)effects over NEP are highly non-linear and site-specific. A significant but small NEP reduction was found during Spring in a Scottish shrubland (-0.67%), in two Italian forests (up to -1.37%) and during Summer in a Californian orange orchard (-1.25%). Although the overall seasonal effect of O(3)on NEP was not found to be negative for the other sites, with episodic O(3)detrimental effect still identified. These episodes were correlated with meteorological variables showing that O(3)damage depends on weather conditions. By identifying O(3)damage under field conditions and the environmental factors influencing to that damage, this work provides an insight into O(3)pollution, climate and weather conditions.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da-
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Pagine totali14
RivistaFrontiers in Forests and Global Change
Attiva dal 2018
Editore: Frontiers Media - [Lausanne]
Paese di pubblicazione: Svizzera
Lingua: inglese
ISSN: 2624-893X
Titolo chiave: Frontiers in Forests and Global Change
Titolo abbreviato: Front. for. glob. change
Numero volume della rivista3
Fascicolo della rivista-
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000556730300001)
Parole chiavenet ecosystem exchange, european forest, stomatal deposition, tropospheric ozone, artificial neural networks, climate change
Link (URL, URI)-
Titolo parallelo-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • IBE — Istituto per la BioEconomia
Moduli/Attività/Sottoprogetti CNR-
Progetti Europei-
Neural Network Analysis to Evaluate Ozone Damage to Vegetation Under Different Climatic Conditions (documento privato )
Tipo documento: application/pdf