The purpose of this study was to map the areal extent and density of submerged aquatic vegetation, principally the seagrasses, Zostera marina and Ruppia maritima, as part of ongoing monitoring for the Barnegat Bay, New Jersey National Estuary Program. We examine the utility of multiscale image segmentation/object-oriented image classification using the eCognition software to map seagrass across our 36,000 ha study area. The multi-scale image segmentation/ object oriented classification approach closely mirrored our conceptual model of the spatial structure of the seagrass habitats and successfully extracted the features of ecological interest. The agreement between the mapped results and the original field reference was 68 percent (Kappa ϭ 56.5 percent) for the four category map and 83 percent (Kappa ϭ 63.1 percent) for the presence/absence map; the agreement between the mapped results and the independent reference data was 71 percent (Kappa ϭ 43.0 percent) for a simple presence/absence map. While the aerial digital camera imagery employed in this study had the advantage of flexible acquisition, suitable image scale, fast processing return time, and comparatively low cost, it had inconsistent radiometric response from image to image. This inconsistency made it difficult to develop a rule-based classification that was universally applicable across the 14 individual image mosaics. However, within the individual scene mosaics, using the eCognition software in a "manual classification" mode provided a flexible and time effective approach to mapping seagrass habitats.

The genus Macrocarpaea (Griseb.) Gilg (Gentianaceae, Helieae) is among the largest woody genera of tropical gentians, with most of its species occurring in the wet mountainous forests of the Andes. Phylogenetic and dispersal-vicariance analyses (DIVA) of 57 of the 105 currently recognized species in the genus, using two data sets from nuclear DNA (ITS and 5S-NTS sequences) and morphology, show a single origin of the Andean species from an ancestral distribution that includes southeastern Brazil. Within the Andes, species divide into two major clades: (1) northern species from the cordilleras of northern Ecuador, Colombia, and Venezuela; and (2) southern species of the Andean Amotape-Huancabamba Zone in Ecuador and Peru, as well as the Andes of central and southern Peru and Bolivia. The Amotape-Huancabamba Zone is supported as the ancestral area for Macrocarpaea within the Andes. There are repeated speciation patterns within the Andes, and three Mesoamerican species derive from the northern clade, as is the single sampled species from the Guayana Shield. The position of the subclade of the three Caribbean species is less certain, but it currently nests among Andean species. An Atlantic coastal Brazilian clade is placed as sister group to all other Macrocarpaea, providing further support for an ancestral refuge in southeastern Brazil for the Helieae. The biogeographic analysis showed that local speciation is more common than long-distance dispersal, and allopatric speciation is more common than sympatric speciation. Using detailed, georeferenced herbarium collection data, patterns in environmental characteristics between clades and sister species were analyzed with Spatial Evolutionary and Ecological Vicariance Analysis (SEEVA), utilizing geographic information system (GIS) and statistical methods. Sister clades and taxa were evaluated for statistical significance in variables such as annual rainfall and temperature, elevation, temperature and rainfall seasonality, geological bedrock age, and soil type to evaluate ecological vicariance between sister groups. The results indicate that there are no general patterns for each variable, but that there are many significant divergences in ecological niches between both larger sister groups and sister species, and ecological niche conservation was also observed when subsequent nodes in the phylogeny were compared.

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 ArcGIS, and were matched with geolocated base layers of eight climatological variables, as well as one each of geological, soil type, elevational and vegetation variables. Sister groups were defined on the basis of the six nested nodes that defined the phylogenetic tree of these two genera. A (0, 1)-scaled divergence index (D) was defined and tested for each of 12 environmental and for each of the six phylogenetic nodes, by means of contingency analyses. We contrast divergence indices of nested clades, allopatric and sympatric sister clades. ResultsThe 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.

No abstract