The shape of the spatial kernel and its implications for biological invasions in patchy environments
2011 (English)In: Proceedings of the Royal Society of London. Biological Sciences, ISSN 0962-8452, E-ISSN 1471-2954, Vol. 278, no 1711, 1564-1571 p.Article in journal (Refereed) Published
Ecological and epidemiological invasions occur in a spatial context. In the study presented we tested how these processes relate to the distance dependence of spread or dispersal between spatial entities such as habitat patches or infective units. The distance dependence was described by a spatial kernel which can be characterized by its shape, quantified by kurtosis, and width, quantified by the kernel variance. We also introduced a method to analyze or generate non randomly distributed infective units or patches as point pattern landscapes. The method is based on Fourier transform and consists of two measures in the spectral representation; Continuity that relates to autocorrelation and Contrast that refers to difference in density of patches, or infective units, in different areas of the landscape. The method was also used to analyze some relevant empirical data where our results are expected to have implications for ecological or epidemiological studies. We analyzed distributions of large old trees (Quercus and Ulmus) as well as the distributions of farms (both cattle and pig) in Sweden. We tested the invasion speed in generated landscapes with different amount of Continuity and Contrast. The results showed that kurtosis, i.e. the kernel shape, was not important for predicting the invasion speed in randomly distributed patches or infective units. However, depending on the assumptions of dispersal, it may be highly important when the distribution of patches or infective units deviates from randomness, in particular when the Contrast is high. We conclude that speed of invasions and spread of diseases depends on its spatial context through the spatial kernel intertwined to the spatial structure. This implies high demands on the empirical data; it requires knowledge of both shape and width of the spatial kernel as well as spatial structure of patches or infective units.
Place, publisher, year, edition, pages
Royal Society , 2011. Vol. 278, no 1711, 1564-1571 p.
Kurtosis, Spread of disease, Point patterns, Spectral density, Dispersal, Invasion
IdentifiersURN: urn:nbn:se:liu:diva-54838DOI: 10.1098/rspb.2010.1902ISI: 000289719100016PubMedID: 20356640OAI: oai:DiVA.org:liu-54838DiVA: diva2:310646