V. 81 N. 2s (2026): Atti della Conferenza Foreste vetuste e antichi alberi: un tesoro di natura, vita e cultura. Firenze 1 ottobre 2025 / Vallombrosa 2-3 ottobre 2025
Articoli Scientifici

Caratterizzazione dei gradienti di maturità e vetustà nelle foreste italiane: un approccio integrato tra telerilevamento e inventari forestali

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  • Costanza Borghi,
  • Francesco Solano,
  • Giovanni D'Amico,
  • Titomanlio Pepe,
  • Mattia Niccoli,
  • Elia Vangi,
  • Francesco Parisi,
  • Davide Travaglini,
  • Giuseppe Modica,
  • Giancarlo Papitto,
  • Gianluca Piovesan,
  • Gherardo Chirici
Costanza Borghi
Department of Agriculture, Food, Environment and Forestry, University of Florence; via San Bonaventura 13 - 50145 Firenze, Italy.
Francesco Solano
Department of Agriculture and Forest Sciences, University of Tuscia, via San Camillo de Lellis s/n, 01100 Viterbo, Italy
Giovanni D'Amico
Department of Agriculture, Food, Environment and Forestry, University of Florence; via San Bonaventura 13 - 50145 Firenze, Italy.
Titomanlio Pepe
Department of Ecological and Biological Sciences, University of Tuscia; largo dell’Università s/n, 01100 Viterbo, Italy
Mattia Niccoli
Department of Agriculture, Food, Environment and Forestry, University of Florence; via San Bonaventura 13 - 50145 Firenze, Italy.
Elia Vangi
Department of Agriculture, Food, Environment and Forestry, University of Florence; via San Bonaventura 13 - 50145 Firenze, Italy.
Francesco Parisi
Department of Biosciences and Territory, University of Molise; contrada Fonte Lappone - 86090 Pesche (IS), Italy. Institute of Technologies and Environmental Intelligence (CNR-ITIAm), National Research Council of Italy, strada provinciale 35d, n. 9 - 00010 Montelibretti (RM), Italy.
Davide Travaglini
Department of Agriculture, Food, Environment and Forestry, University of Florence; via San Bonaventura 13 - 50145 Firenze, Italy.
Giuseppe Modica
Dipartimento di Scienze Veterinarie, Università degli Studi di Messina; viale G. Palatucci s/n - 98168 Messina, Italy.
Giancarlo Papitto
Arma dei Carabinieri, Comando Unità Forestali Ambientali Agroalimentari, Via. G. Carducci 5, Rome, 00187, Italy
Gianluca Piovesan
Department of Ecological and Biological Sciences, University of Tuscia, Largo dell’Università s/n, 01100 Viterbo, Italy
Gherardo Chirici
Department of Agriculture, Food, Environment and Forestry, University of Florence; via San Bonaventura 13 - 50145 Firenze, Italy.
DOI: https://doi.org/10.36253/ifm-1250

Pubblicato 2026-10-06

Parole chiave

  • forestry,
  • machine learning,
  • structural complexity,
  • explainable artificial intelligence,
  • Natural Restoration Law

Come citare

Borghi, C., Solano, F., D’Amico, G., Pepe, T., Niccoli, M., Vangi, E., Parisi, F., Travaglini, D., Modica, G., Papitto, G., Piovesan, G., & Chirici, G. (2026). Caratterizzazione dei gradienti di maturità e vetustà nelle foreste italiane: un approccio integrato tra telerilevamento e inventari forestali. L’Italia Forestale E Montana, 81(2s), 118–139. https://doi.org/10.36253/ifm-1250

Copyright (c) 2026 Costanza Borghi, Francesco Solano, Giovanni D'Amico, Titomanlio Pepe, Mattia Niccoli, Elia Vangi, Francesco Parisi, Davide Travaglini, Giuseppe Modica, Giancarlo Papitto, Gianluca Piovesan, Gherardo Chirici

Creative Commons License

Questo lavoro è fornito con la licenza Creative Commons Attribuzione - Non commerciale 4.0 Internazionale.

Abstract

Mature and Old-Growth-like Forests (MOGF) are critical for biodiversity conservation and climate regulation, yet they remain rare and fragmented across Europe. This study aims to ecologically validate a high-resolution (30 m) predictive map of MOGF probability across Italy by integrating it with independent ground-based data from the 2015 National Forest Inventory (INFC2015). Utilizing a multi-source approach, we analyzed 6993 inventory sampling plots across diverse forest types and environmental gradients. Statistical analysis confirmed that higher MOGF probabilities strongly correlate with indicators of advanced stand development, including older age classes (> 120 years), multilayered vertical structures, and high canopy cover (> 80%). MOGF probability is also significantly higher within strictly protected areas (e.g., National Park Zone A) and topographically remote sites characterized by high altitudes and steep slopes. Quantitative correlations also link MOGF probability to an increase in above-ground biomass and deadwood. While the study successfully validates the spatial patterns of forest maturity, limitations include the current lack of national-scale 3D LiDAR data for deadwood modeling and the lack of microhabitat indicators in the INFC2015. However, the anticipated inclusion of these metrics in future national frameworks will further refine the monitoring of these ecosystems.

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