A dataset on spatial distribution and association patterns of three species from moist semi deciduous forest

Knowledge on the spatial distribution and inter-specific association patterns in tree species is essential in plant ecology to understand ecological mechanisms and dynamic process operating in spatial distribution of a tree population in a plant community. We measured and compiled datasets on three tropical tree species from a moist semi deciduous forest. We used the software Programita to perform univariate and bivariate point pattern analysis by Ripley's L-function. These datasets can be used to inform on possibilities of interaction of these species in forest stands. These datasets can be also used to access the capacity of each tree of Mansonia altissima var. altissima A. Chev. to develop and grow or its exclusion probability within a plant community. Mansonia altissima A. Chev. is a plant species represented by only one-population in a moist semi-deciduous forest in Republic of Benin. Our project aims to understand its ecology for restoration and conservation purposes within its natural habitat as well as other habitats inside of its distribution range.