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Dispersal Direction (dispersal + direction)
Selected AbstractsDirection of movements in Hungarian Barn Owls (Tyto alba): gene flow and barriersDIVERSITY AND DISTRIBUTIONS, Issue 4 2003Róbert Mátics Abstract. An analysis of dispersal directions of the barn owl showed that all individuals immigrating to Hungary came from W-NW-N. It was shown that immigrating owls breed in Hungary. There is no prevailing direction in emigration from Hungary. The time of fledging does not influence the direction of movement and there is no difference between sexes concerning dispersal direction. The percentages of emigrating owls is greater than that of immigrating ones. These percentages did not differ in relation to most of the analysed countries (Germany, Italy, Switzerland, Poland and countries of the former Yugoslavia and Czechoslovakia) but it differed in relation to Austria. The degree and direction of introgression into and from the transition zone and the recent distribution of the phenotypes are discussed based on the comparative analysis of published European data. These suggest that the subspecies Tyto alba alba and Tyto alba guttata disappear by introgression, to form a phenotypically very variable species. [source] The Application of Geographic Information Systems and Spatial Analysis to Assess Dumped and Subsequently Scattered Human Remains,JOURNAL OF FORENSIC SCIENCES, Issue 3 2006Mary H. Manhein M.A. ABSTRACT: This study utilizes geographic information systems (GIS) and spatial analysis (SA) technology to address the problems associated with prediction of location and effective recovery of dumped and scattered human remains in Louisiana. The goals are to determine if a selective bias exists in Louisiana as to where and when human remains are dumped and to assess whether or not geographically specific patterns exist in the dispersal of human remains. We hypothesized that a positive relationship exists between postmortem interval (PMI) and dispersal distance, and that there are negative relationships between PMI and dispersal direction and between dispersal direction and distance. Our results indicate that, in Louisiana, remains are more often dumped in rural areas away from a structure, and are found within ¼ mile of the nearest road. For Louisiana, no seasonal bias was found in the analysis of when remains are dumped. Furthermore, with the exception of the relationship between PMI and the shortest distance remains were dispersed, no geographically specific patterns were detected in the analyses of dispersal distance, dispersal direction, and PMI. [source] Direction of movements in Hungarian Barn Owls (Tyto alba): gene flow and barriersDIVERSITY AND DISTRIBUTIONS, Issue 4 2003Róbert Mátics Abstract. An analysis of dispersal directions of the barn owl showed that all individuals immigrating to Hungary came from W-NW-N. It was shown that immigrating owls breed in Hungary. There is no prevailing direction in emigration from Hungary. The time of fledging does not influence the direction of movement and there is no difference between sexes concerning dispersal direction. The percentages of emigrating owls is greater than that of immigrating ones. These percentages did not differ in relation to most of the analysed countries (Germany, Italy, Switzerland, Poland and countries of the former Yugoslavia and Czechoslovakia) but it differed in relation to Austria. The degree and direction of introgression into and from the transition zone and the recent distribution of the phenotypes are discussed based on the comparative analysis of published European data. These suggest that the subspecies Tyto alba alba and Tyto alba guttata disappear by introgression, to form a phenotypically very variable species. [source] Building anisotropic sampling schemes for the estimation of anisotropic dispersalANNALS OF APPLIED BIOLOGY, Issue 3 2009S. Soubeyrand Abstract Anisotropy, a structural property of dispersal, is observed in dispersal patterns occurring for a wide range of biological systems. While dispersal models more and more often incorporate anisotropy, the sampling schemes required to collect data for validation usually do not account for the anisotropy of dispersal data. Using a parametric model already published to describe the spatial spread of a plant disease, the wheat yellow rust, we carry out a study aimed at recommending an appropriate sampling scheme for anisotropic data. In a first step, we show with a simulation study that prior knowledge of dispersal anisotropy can be used to improve the sampling scheme. One of the main guidelines to be proposed is the orientation of the sampling grid around the main dispersal directions. In a second step, we propose a sequential sampling procedure (SSP) used to automatically build anisotropic sampling schemes adapted to the actual anisotropy of dispersal. The SSP is applied to simulated and real data. The proposed methodology is expected to be adapted easily to any kind of organisms with wind-borne propagule dispersal because it does not require the inclusion of biological features specific of the considered organism. [source] | ||||||||||