2015-10-082015-10-082011-01-18LANDEIRO, Victor L.; MAGNUSSON, William E.; MELO, Adriano S.; ESPIRITO-SANTO, Helder M. V.; BINI, Luis M. Spatial eigenfunction analyses in stream networks: do watercourse and overland distances produce different results?. Freshwater Biology, v. 56, p. 1184-1192, Jun. 2011. Disponível em: <http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2427.2010.02563.x/epdf>.http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2427.2010.02563.x/epdfhttp://repositorio.bc.ufg.br/handle/ri/11109v. 56, p. 1184-1192, jun. 2011.1. The use of spatial variables is a common procedure in ecological studies. The technique is based on the definition of a connectivity ⁄distance matrix that conceptually defines the dispersal of organisms. The shortest distance between two points is a straight line. Despite the fact that a straight line may not represent the easiest dispersal path for many kinds of organisms, straight-line distances are often used to detect patterns. We argue that other types of connectivity ⁄distance matrices will better represent dispersal paths, such as the watercourse distance for aquatic organisms (e.g. fish, shrimps). 2. We used empirical and simulated community data to evaluate the usefulness of spatial variables generated from watercourse and overland (straight-line) distances. 3. Spatial variables based on watercourse distances captured patterns that straight-line distances did not, and provided better representations of the spatial patterns generated by dispersal along a dendritic network.engAcesso AbertoCommunityDispersalOverlandStream networksWatercourseArtigo10.1111/j.1365-2427.2010.02563.x