author = "Banon, Gabriela Paola Ribeiro and Renn{\'o}, Camilo Daleles and 
                         Arraut, Eduardo Moraes and Banon, Gerald Jean Francis and 
                         Villamar{\'{\i}}n, Francisco and Marioni, Boris and Novo, Evlyn 
                         M{\'a}rcia Le{\~a}o de Moraes",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {} and {} and {} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Modelagem dos locais de nidifica{\c{c}}{\~a}o para 
                         conserva{\c{c}}{\~a}o da esp{\'e}cie Melanosuchus niger in 
                         situ: uma abordagem via sensoriamento remoto e Maxent",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "6368--6375",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Conservation of Melanosuchus niger species is commonly based on 
                         protecting nesting sites, where the two most vulnerable life 
                         stages, neonates and reproductive females, remain for a 
                         considerable time. In large areas with difficult access from the 
                         ground, such as the Amazon basin, it is extremely demanding to 
                         identify nests using only field-based methods. Remote sensing can 
                         be an alternative for deriving environmental variables related to 
                         caiman nesting sites. However, only a few studies have been 
                         conducted using this technology for M. niger habitat mapping 
                         within the Amazon basin. Based on previous results and new 
                         hypotheses, we selected the following environmental variables for 
                         predicting nesting site occurrence of M. niger using Maxent: 
                         vertical and horizontal distances from water body at low and high 
                         water seasons, and horizontal distance from forest and non-forest. 
                         Additionally, to predicting occurrence, model outputs allowed for 
                         quantifying the relative contribution of these environmental 
                         variables. Results showed that, on average, females select nesting 
                         sites on the basis of horizontal distance from water body during 
                         the high water season. Predictions reveal that nests are 
                         associated to small water bodies, whose margins are humid owing to 
                         the high water table.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59844",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMCPM",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3PSMCPM",
           targetfile = "59844.pdf",
                 type = "Modelagem espacial",
        urlaccessdate = "02 dez. 2020"