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Modelling the spatial patterns and interspecific interactions between three chrysomelid beetles defoliating the multipurpose agroforestry tree Sesbania sesban in Africa

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The population dynamics of single species can be understood only in the context of interactions within an ecological community. In this study we used theoretical and empirical models to describe the spatial pattern of the Afrotropical leaf beetles Mesoplatys ochroptera Stål, Exosoma and Ootheca spp. defoliating the agroforestry tree (Sesbania sesban (L.) Merril). We used the Poisson, negative binomial distribution (NBD), Taylor's power law and Iwao's mean crowding models to determine (1) intraspecific spatial patterns and conspecific interactions within a population, (2) interspecific interaction between their populations, and (3) derive a common sampling plan for the three species. The spatial patterns of larvae and adult M. ochroptera were adequately described by the negative binomial, while those of Exosoma and Ootheca fitted the Poisson distribution. Taylor's power law gave very good fit (r 2>0.80) except for Ootheca in Zambia, while Iwao's mean crowding gave poor fit to the spatial pattern of M. ochroptera larvae and Ootheca. The slopes of the variance-mean relationships were significantly greater than unity for adults and larvae of M. ochroptera, indicating aggregated distribution, while those for Exosoma and Ootheca were closer to unity, indicating spatial randomness. The three species showed random association with varying degrees of niche overlap. Therefore, the null hypothesis of spatial independence between the populations of M. ochroptera and Exosoma, and adult M. ochroptera and Ootheca was rejected. Hence, a common sampling plan was developed for estimation of the population densities of the three species at the same time.
    Publication year

    2006

    Authors

    Sileshi G W; Hailu G

    Language

    English

    Keywords

    mesoplatys ochroptera, sesbania sesban, spatial distribution

    Geographic

    Kenya, Malawi, Zambia

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