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RESEARCH ARTICLE

Predicting the fine fuel moisture content in Dalmatian black pine needle litter

Nera Bakšić A and Darko Bakšić A *
+ Author Affiliations
- Author Affiliations

A Faculty of Forestry and Wood Technology, University of Zagreb, Svetošimunska 23, Zagreb 10002, Croatia.

* Correspondence to: dbaksic@sumfak.hr

International Journal of Wildland Fire 31(7) 708-719 https://doi.org/10.1071/WF21092
Submitted: 28 June 2021  Accepted: 20 May 2022   Published: 17 June 2022

© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF.

Abstract

During the last three decades, there has been an increase in the incidence of severe crown fires affecting black pine forests in the sub-Mediterranean area. The objective of this study was to develop and test a model to predict fine fuel moisture content for Dalmatian black pine (Pinus nigra J.F. Arnold subsp. dalmatica (Vis.) Franco) needle litter. We performed laboratory measurements of equilibrium moisture content and response time of dead black pine needles to modify the hourly fine fuel moisture code (FFMC) model, and we compared the predictive ability of the hourly FFMC model with that of modified model (PnFFMC). Field tests showed that although the hourly FFMC model reproduced trends in moisture content of black pine needles quite well, it consistently overestimated moisture content (mean absolute error 3.9%). The PnFFMC model performed better than the hourly FFMC model and was closer to the line of equivalence (mean absolute error 0.9%). This study indicates that the hourly FFMC can easily be modified by incorporating appropriate species-specific equilibrium moisture content and response time values, leading to more accurate predictions of fine fuel moisture content. The need to use recently fallen needles in fuel moisture modelling for Mediterranean pine species is highlighted.

Keywords: climate change, Dalmatian black pine, dead fine fuel moisture content, equilibrium moisture content, hourly FFMC model, Mediterranean pines, recently fallen needles, response time.


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