Mixed forests play an important role in promoting forest functions and services, and showed better resilience to perturbations than monospecific forests. In the Mediterranean Basin they constitute an important share of the total forest area. However, although mixed forests have been described, classified and mapped in most of the Mediterranean regions around the world, in the Mediterranean Basin they remain neglected, with direct negative consequences for forest management and conservation strategies. Our objective is to present a reliable, uniform classification along with a map of the Spanish Mediterranean Mixed Forests (MMF) as a tool for their management and conservation in Spain. The digital Spanish Forest Map was analyzed to identify MMF. The most frequent tree species combinations were identified and their representativeness in terms of the total forest area was analyzed. In addition, to ensure environmental homogeneity in the proposed classification, the arrangement of each tree species combination within the Spanish Mediterranean ecoregions was evaluated using the Pearson Chi-square test. Based on our results, Spanish MMF currently cover 27.07% of the Mediterranean natural forest area. They were divided into 9 main ecological groups and 23 subtypes. The classification of Spanish MMF and the distribution map represent a first step towards recognizing the importance of mixed forests in the vegetation of the Mediterranean Basin. Together they may provide a valuable basis to improve future forest management, monitoring and conservation strategies both at national and European level.
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Citation
Sánchez de Dios R, Velázquez JC, Sainz Ollero H (2019). Classification and mapping of Spanish Mediterranean mixed forests. iForest 12: 480-487. - doi: 10.3832/ifor2817-012
Academic Editor
Luca Salvati
Paper history
Received: Apr 16, 2018
Accepted: Aug 01, 2019
First online: Oct 14, 2019
Publication Date: Oct 31, 2019
Publication Time: 2.47 months
© SISEF - The Italian Society of Silviculture and Forest Ecology 2019
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This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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