Delimiting Areas of Endemism through Kernel Interpolation
نویسندگان
چکیده
منابع مشابه
Delimiting Areas of Endemism through Kernel Interpolation
We propose a new approach for identification of areas of endemism, the Geographical Interpolation of Endemism (GIE), based on kernel spatial interpolation. This method differs from others in being independent of grid cells. This new approach is based on estimating the overlap between the distribution of species through a kernel interpolation of centroids of species distribution and areas of inf...
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One of the key observations about the distribution of life on Earth is that it is non-random in space and time. Description of these spatio-temporal patterns represents the data of biogeography, and explanation of these spatio-temporal patterns has driven the development of the science of biogeography. Perhaps the concept most associated with the description of distributions is endemism, which ...
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In mathematics, the task of interpolating observed data has a long history. Recently, this task has gained even more attention, also from a statistical point of view, as there are many data situations, where either there is no random error (e.g. computer experiments) or the underlying data generating process is very precise such that a repetition will yield the same numerical result. Here we pr...
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It is often observed that interpolation based on translates of radial basis functions or non-radial kernels is numerically unstable due to exceedingly large condition of the kernel matrix. But if stability is assessed in function space without considering special bases, this paper proves that kernel–based interpolation is stable. Provided that the data are not too wildly scattered, the L2 or L∞...
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ژورنال
عنوان ژورنال: PLOS ONE
سال: 2015
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0116673