O uso de modelagem para determinar a distribuição de espécies de plantas ameaçadas de extinção na Amazônia brasileira

Abstract

significant way in land use changes, causing loss and degradation of habitats for many species. Allied to this problem, knowledge about the distribution of many species in the Amazon is still very limited. Thus, many species may be compromised, without having a clear idea about their distribution. In this context, it is necessary to expand the knowledge of spatial distribution patterns of species, to compensate for the low degree of knowledge about the distribution. This work aims to generate and compare Spatial Distribution Models of endangered species in the state of Pará, as a new tool to support the collection and conservation of these species. The distribution modeling of the species was carried out using coordinates of species' occurrence records. The presence records (geographic coordinates) were generated by consulting Internet databases, including Tropicos3 - Missouri Botanical Garden (www.mobot.org) and Species Link (www.splink.cria.org.br). In addition to these, geographic coordinates were obtained from the Herbarium of the Museu Paraense Emílio Goeldi. The abiotic data used for spatial modeling were climate and altitude data available in the Worldclim database (www.worldclim.org). The Maxent software version 2.3 was used to generate the models. Spatial distribution maps were generated with the program Arcview 3.3 (ESRI2004) from the models developed in the Maxent programs. Of the 51 species that are on the list of threatened species in the state of Pará. Few have coordinates of occurrence records in the analyzed collections. This is serious, because without this information it is impossible to generate the models of species distribution based on the environmental niche. Another serious point is that the collections consulted are reference collections for the Amazon. However, considering the lack of collection data for the species analyzed, the Species Distribution Models generated for some species can complement the spatial distribution information generated only with data from biological collections, being a fundamental strategy to broaden the distribution of species and draw strategies for their conservation.