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Coupling fire behaviour modelling and stand characteristics to assess and mitigate fire hazard in a maritime pine landscape in Portugal

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Abstract

Silvicultural models are often developed and applied without due consideration of fire modelling. Yet, this information is important for designing treatment options to lower fire hazard. We used the FlamMap software to assess potential fire behaviour under extreme fire weather conditions within a 10,881-ha maritime pine landscape in central Portugal, the Leiria National Forest. Models describing fire hazard and providing information to assess potential benefits of stand-level fuel treatments were developed based on fire behaviour simulation. These models use as predictors stand variables and may assist forest managers in identifying hazardous areas in pine forests. Models were built from a database comprising 94,207 unique combinations of variables to detect significant fire-landscape interactions between stand-level features and fire behaviour. A set of compatible models that express crown fire likelihood and tree mortality were fitted using logistic regression. Additionally, classification tree analysis was used to model the type of fire, fire suppression difficulty, and tree mortality. The results highlight the potential of this methodology to explain the influences of fuel- and stand-related variables on fire hazard. This approach allowed the identification of straightforward discrimination rules to implement fuel treatments that prevent crown fires, enhancing the effectiveness of fire suppression and thereby reducing fire damage in fire-prone forest stands. Results further allow developing specific hazard-reduction prescriptions based on common forest metrics without resorting to advanced simulation modelling.

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Acknowledgements

This research was supported by several projects funded by the Portuguese Science Foundation: the simulation of fire behaviour in the framework of the Project “Decision support tools for integrating fire and forest management planning” (PTDC/ AGR-CFL/64146/2006) and Project FIRE-ENGINE “Flexible Design of Forest Fire Management Systems” (MIT/FSE/0064/2009), and the fire behaviour models in the frame of SADRI “Models and Decision Support Systems for Addressing Risk and Uncertainty in Forest Planning” (PTDC/AGR-FOR/4526/2012). The study was also partially supported by INTEGRAL “Future Oriented Integrated Management of European Forest Lands” (Collaborative Project No. 282887) which is funded by the European Union Seventh Framework Programme (FP7-PEOPLE-2010-IRSES), and by the SuFoRun project “Models and decision SUpport tools for integrated FOrest policy development under global change and associated Risk and Uncertainty” funded by the European Union’s H2020 research and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 691149. Researcher Jordi Garcia-Gonzalo was supported by a “Ramon y Cajal” research contract from the MINECO (Ref. RYC-2013-14262) and has received funding from CERCA Programme/Generalitat de Catalunya. The authors gratefully acknowledge the Portuguese Science Foundation for funding the Ph.D. scholarship of Brigite Botequim (SFRH/BD/44830/2008).

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Authors and Affiliations

  1. Forest Research Centre, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017, Lisbon, Portugal

    B. Botequim, J. Garcia-Gonzalo, A. Silva & J. G. Borges

  2. Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB), University of Trás–os-Montes e Alto Douro, Quinta de Prados, 5001-801, Vila Real, Portugal

    P. M. Fernandes

  3. Forest Sciences Centre of Catalonia (CTFC), Carretera Sant Llorenç, Km 2, E25280 Solsona (Lleida), Spain

    J. Garcia-Gonzalo

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  1. B. Botequim
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  2. P. M. Fernandes
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  3. J. Garcia-Gonzalo
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  4. A. Silva
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  5. J. G. Borges
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Correspondence to B. Botequim.

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Communicated by Lluís Coll.

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Botequim, B., Fernandes, P.M., Garcia-Gonzalo, J. et al. Coupling fire behaviour modelling and stand characteristics to assess and mitigate fire hazard in a maritime pine landscape in Portugal. Eur J Forest Res 136, 527–542 (2017). https://doi.org/10.1007/s10342-017-1050-7

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