author = "Costa, Cristina Bestetti and Amaral, Silvana and Valeriano, Dalton 
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Presence-only modeling method for predicting species distribution 
                         and species",
                 year = "2006",
         organization = "Congresso da Sociedade Bot{\^a}nica de S{\~a}o Paulo.",
             keywords = "spatial distribution modeling, OpenModeller, GIS, Coccocypselum.",
             abstract = "Predictive habitat modeling, i.e. the use of a statistical model 
                         to predict the locations of suitable habitat for a given species 
                         has become very popular in recent years. Predictive models 
                         represent an important tool to better understand the factors that 
                         control species distributions. Many of these models have been 
                         developed in temperate areas. However, it is poorly sampled in 
                         tropical regions, where the highest biodiversity areas remain and 
                         models would be of major value. In the best of cases, primary 
                         inventory data exist as georeferenced coordinates from localities 
                         where specimens have been collected. There is rarely data 
                         indicating absence or abundance of species. However, most of the 
                         current modeling approaches need the existence of both presence 
                         and absence data, and many of them are based only on biological 
                         tolerance to climate. The botanical collections are difficult to 
                         use for the assessment of plant diversity, first because they are 
                         geographically biased, favoring more easily accessed areas, and 
                         second because of the taxonomic correctness of the names of the 
                         specimens. The information present at the taxonomic studies, made 
                         always by a specialist during a long period, can carry sufficient 
                         collections to estimate species distributions. Also, the 
                         specialist can guarantee the taxonomic information in the 
                         database. This work presents a contribution of the taxonomic 
                         revision of the neotropical genus Coccocypselum P. Br. (Rubiaceae) 
                         for the species distribution modeling purpose, focusing on 
                         richness pattern and conservation status of the group. Using the 
                         Genetic Algorithm for Rule-Set Prediction (GARP) inside a spatial 
                         distribution modeling library (openModeller) nine brazilian 
                         species of Coccocypselum were modeled. Climate and topographical 
                         data defined the potential niche, and together with the 
                         Coccocypselum data occurrence were manipulated in Terraview, a GIS 
                         database structure. To produce the Coccocypselums species-richness 
                         map for the Brazilian territory all the known locality collections 
                         were used to calculate the most significant sites. The final 
                         modeled distributions were then used to improve the 
                         species-richness map summarizing the contents of modeling process 
                         throughout an analysis of average of occurrences. These modeled 
                         distribution maps for all species evidenced the sites with higher 
                         Coccocypselum richness, compensating the geographically biased 
                         limitations, usually presented in the traditional approach. 
                         Superposing the official conservation unities, the conservation 
                         status of Coccocypselum was discussed. The current approach can be 
                         used to explore the options and demonstrate the role that 
                         botanical collection data can play in building richness and 
                         distribution maps. With additional data, these methods could 
                         contribute to select priority biodiversity sites for possible 
  conference-location = "Piracicaba, S{\~a}o Paulo",
           targetfile = "550.pdf",
        urlaccessdate = "27 jan. 2021"