Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods |
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Authors: | J Luis Hernandez-Stefanoni Raul Ponce-Hernandez |
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Institution: | (1) Watershed Ecosystems Graduate Program, Trent University, Peterborough, Ontario, Canada;(2) Environmental and Resource Studies Program, Department of Geography, Trent University, Peterborough, Ontario, Canada |
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Abstract: | Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify
high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected
areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this
study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled
in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map
of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions,
kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the
procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries
between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity
over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior
information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators
due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used
as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class
kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the
most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations
of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional
role was found very useful in aiding decisions in conservation planning. |
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Keywords: | biodiversity co-kriging geo-statictics kriging plant diversity remote sensing vegetation indices tropical forest |
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