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Vegetation Structure and Edaphic Factors of Mangrove Forest at Baluran National Park, East Java, Indonesia.
Dissertation Abstract:
The study was conducted at Baluran National Park, East Java, Indonesia from July 1999 to December 1999. Vegetation structure and edaphic factors of mangrove forest covering an area 25 ha at Baluran National Park, East Java, Indonesia, were studied with the aim of explaining the distribution pattern interrelationships between the mangrove vegetation structure and edaphic factors.
Specifically, Principal Component Analysis (PCA) and stepwise multiple regression analysis were used to test the hypothesis that distribution patterns and mangrove vegetation were influenced by soil variables singly or in combination.
All mangrove plant species and soil samples occurring in each 67 randomly located 10 x 10 plots were recorded. The mangrove species with > 10 cm dbh were enumerated in each plot. Horizontal and vertical structure was examined by constructing a profile diagram for a 10 x 50 m transect.
The mangrove forest was comprised of 22 families, 27 genera, and 36 species. The family, which had the greatest number of species was Rhizophoraceae (9 species). Other families were Meliaceae (2 species), Arecaceae (2 species), Aviceniaceae (2 species), Combretaceae (2 species), Malvaceae (2 species), and Sonneratiaceae (2 species). A special finding was that Rhizophora lamarckii is an endangered species to Baluran National Park.
PCA ordination analysis was used to classify 67 plots of mangrove vegetation and soil variable data above to produce a scattergram. The scattergram drawn showed there were two distribution patterns of mangrove vegetation structure, based on the percentage of organic carbon, peat soil and non-peat soil, or mineral soil group.
The first pattern was related to the high percentage of organic carbon, which was 18 percent. This was the peat soil. The second pattern was related to soil texture, especially sand and silt; and this was the non-peat soil group.
Stepwise multiple regression analysis revealed that the first predictor variable for vegetation distribution pattern was organic carbon, and the second was sand and clay.
The vegetation profile showed a patchy distribution, the upper storey at 10 m, formed by groups of tall stems together with scattered large trees, namely: Bruguiera gymnorrhiza and R. apiculata, the latter being the dominant species.
PCA ordination could classify the mangrove vegetation structure into two groups of mangrove forest at Baluran National Park. The clustering of plots was due to the impinging of soil variables especially the percentage of organic carbon and soil texture. The predictor variables identified through the Stepwise Multiple Regression Analysis can be used to predict the distribution patterns of mangrove species in mangrove forests with site characteristics similar to those at Baluran National Park. The findings could be used in decision making for management purposes especially for mangrove rehabilitation or reforestation.
