Spatial evolutionary and ecological vicariance analysis (SEEVA), a novel approach to biogeography and speciation research, with an example from Brazilian Gentianaceae
Aim Spatial evolutionary and ecological vicariance analysis (SEEVA) is a simple analytical method that evaluates environmental or ecological divergence associated with evolutionary splits. It integrates evolutionary hypotheses, phylogenetic data, and spatial, temporal, environmental and geographical information to elucidate patterns. Using a phylogeny of Prepusa Mart. and Senaea Taub. (Angiospermae: Gentianaceae), SEEVA is used to describe the radiation and ecological patterns of this basal gentian group across south‐eastern Brazil.
Location Latin America, global.
Methods Environmental data for 151 geolocated botanical collections, associated with specimens from seven species, were compiled with A
Results The level of ecological divergence between sister clades/species, defined in terms of D measures, was substantial for five of six nodes, with 21 of 72 environmental comparisons having D > 0.75. Soil types and geological age of bedrock were strongly divergent only for basal nodes in the phylogeny, by contrast with temperature and precipitation, which exhibited strong divergence at all nodes. There has been strong divergence and progressive occupation of wetter and colder habitats throughout the history of Prepusa. Nodes separating allopatric sister clades exhibited larger niche divergence than did those separating sympatric sister clades.
Main conclusions SEEVA provides a multi‐source, direct analysis method for correlating field collections, phylogenetic hypotheses, species distributions and georeferenced environmental data. Using SEEVA, it was possible to quantify and test the divergence between sister lineages, illustrating both niche conservatism and ecological specialization. SEEVA permits elucidation of historical and ecological vicariance for evolutionary lineages, and is amenable to wide application, taxonomically, geographically and ecologically.
Document Type: Research Article
Affiliations: 1: Department of Ecology, Evolution & Natural Resources, Rutgers University, New Brunswick, NJ 08901-8551, USA 2: Department of Clinical Physiology, Lund University, SE-221 85 Lund, Sweden 3: Center for Remote Sensing & Spatial Analysis, Rutgers University, New Brunswick, NJ 08901-8551, USA
Publication date: October 1, 2011