Phytosanitary state of Ouled Bechih cork forests in the region of Souk-Ahras, Northeast Algeria

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Phytosanitary state of Ouled Bechih cork forests in the region of Souk-Ahras, Northeast Algeria

Description

Abstract: The cork forests of eastern Algeria know the last few years, serious damage due to many factors. Considering the lack of knowledge about the cork oak forests of high mountains in eastern Algeria, we initiated a study to assess the phytosanitary state of Ouled Bechih cork forests in Souk- Ahras. The study was conducted in 3 different sites (M’Ghassel, Kef-M’kasser and Gliàa) during the years 2010, 2011 and 2012. 40 trees were randomly selected in each site. We have made dendrometric measures to each selected tree, and also did phytosanitary surveys that involve examining the canopy, and the trunk. The different studied descriptors were recorded by classes according their presence on the tree. The calculation of decline index during three seasons indicates a good safe sanitary state, except for site-Kef M’kasser which presents a beginning of decline during 2010 (ID = 1.67). However, we have noted an improvement in the next two years (ID = 1.42 in 2011 and ID = 1.37 in 2012).We also noted traces of xylophagous insects on 26.66% of M’ghassel’s trees in 2010 and the rate increases to 36.66% in 2012. Traces are also present on 5% of Gliaa’s trees in 2010 up to 57.5% in 2012, while on Kef M’kasser’s trees holes are only observed on 2.5% in 2010 and 7.5% in 2012. The percentage of trees with injuries increases during the three years of study; it went from 20% to 50% Gliaa and from 32.5% to 65% in Kef M’kasser, but M’ghassel seems less affected than the others sites (10% in 2010 and 26.66% in 2012). Blackish seeps affect mainly Kef M’kasser’s trees, (45%of the trees in 2010 and 67.5% in 2012), and the biggest crevasses are found on Gliaa’s trees (60% during the three years). The acorns production is abundant and the quality of the cork remains good during the three years of study. All descriptors were compared using a Factorial Correspondence Analysis (FCA) to determine the weight of each factor in the recorded variability.

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