%0 Journal Article %1 robledoarnuncio2007estimation %A Robledo-Arnuncio, Juan Jose %A García, Cristina %D 2007 %J Molecular Ecology %K dispersal_estimation dispersal_kernel seed_dispersal %N 23 %P 5098-5109 %R https://doi.org/10.1111/j.1365-294X.2007.03427.x %T Estimation of the seed dispersal kernel from exact identification of source plants %U https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-294X.2007.03427.x %V 16 %X Abstract The exact identification of individual seed sources through genetic analysis of seed tissue of maternal origin has recently brought the full analytical potential of parentage analysis to the study of seed dispersal. No specific statistical methodology has been described so far, however, for estimation of the dispersal kernel function from categorical maternity assignment. In this study, we introduce a maximum-likelihood procedure to estimate the seed dispersal kernel from exact identification of seed sources. Using numerical simulations, we show that the proposed method, unlike other approaches, is independent of seed fecundity variation, yielding accurate estimates of the shape and range of the seed dispersal kernel under varied sampling and dispersal conditions. We also demonstrate how an obvious estimator of the dispersal kernel, the maximum-likelihood fit of the observed distribution of dispersal distances to seed traps, can be strongly biased due to the spatial arrangement of seed traps relative to source plants. Finally, we illustrate the use of the proposed method with a previously published empirical example for the animal-dispersed tree species Prunus mahaleb.

@article{robledoarnuncio2007estimation, abstract = {Abstract The exact identification of individual seed sources through genetic analysis of seed tissue of maternal origin has recently brought the full analytical potential of parentage analysis to the study of seed dispersal. No specific statistical methodology has been described so far, however, for estimation of the dispersal kernel function from categorical maternity assignment. In this study, we introduce a maximum-likelihood procedure to estimate the seed dispersal kernel from exact identification of seed sources. Using numerical simulations, we show that the proposed method, unlike other approaches, is independent of seed fecundity variation, yielding accurate estimates of the shape and range of the seed dispersal kernel under varied sampling and dispersal conditions. We also demonstrate how an obvious estimator of the dispersal kernel, the maximum-likelihood fit of the observed distribution of dispersal distances to seed traps, can be strongly biased due to the spatial arrangement of seed traps relative to source plants. Finally, we illustrate the use of the proposed method with a previously published empirical example for the animal-dispersed tree species Prunus mahaleb.}, added-at = {2023-12-30T01:22:48.000+0100}, author = {Robledo-Arnuncio, Juan Jose and García, Cristina}, biburl = {https://www.bibsonomy.org/bibtex/2ad7f9d054199b57f2f7e3f738a9087c1/peter.ralph}, doi = {https://doi.org/10.1111/j.1365-294X.2007.03427.x}, eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-294X.2007.03427.x}, interhash = {68bc5100be06217e6b136c6745366185}, intrahash = {ad7f9d054199b57f2f7e3f738a9087c1}, journal = {Molecular Ecology}, keywords = {dispersal_estimation dispersal_kernel seed_dispersal}, number = 23, pages = {5098-5109}, timestamp = {2023-12-30T01:22:48.000+0100}, title = {Estimation of the seed dispersal kernel from exact identification of source plants}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-294X.2007.03427.x}, volume = 16, year = 2007 }