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4. NEOTROPICAL ALIEN MAMMALS : a data set of occurrence and abundance of alien mammals in the Neotropics

Author

da Rosa, Clarissa Alves, Ribeiro, Bruno R., Bejarano, Vanesa, Puertas, Fernando Henrique, Bocchiglieri, Adriana, dos Santos Barbosa, Adriana Loeser, Chiarello, Adriano Garcia, Paglia, Adriano Pereira, Pereira, Adriele Aparecida, de Souza Moreira, Adryelle Francisca, de Souza, Agnis Cristiane, Pellegrin, Aiesca, Gatica, Ailin, Medeiro, Akyllan Zoppi, Pereira, Alan Deivid, Braz, Alan Gerhardt, Yanosky, Alberto, Valenzuela, Alejandro Eduardo Jorge, Bertassoni, Alessandra, dos Santos Venturinido Prado, Alessandra, Nava, Alessandra Ferreira Dales, Rocha, Alessandro, Bovo, Alex Augusto Abreu, Bager, Alex, Cravino, Alexandra, dos Santos Pires, Alexandra, Martensen, Alexandre Camargo, Filippini, Alexandre, Percequillo, Alexandre Reis, Vogliotti, Alexandre, Antunes, Alexsander Zamorano, de Oliveira, Aline Cristina Leite, da Silva de Oliveira, Allan Jefferson, Devlin, Allison, de Paula, Almir, Ferreira, Aluane Silva, García-Olaechea, Alvaro, Subalusky, Amanda, Sánchez, Amadeo, de Aquino, Ana Carla Medeiros Morato, Srbek-Araujo, Ana Carolina, Gonçales, Amane Paldês, Araújo, Ana Caroline L., Gozzi, Ana Cecilia, Ochoa, Ana Cecilia, de Oliveira, Ana Cristina Mendes, Lacerda, Ana Cristyna Reis, Francisco, Ana Karina, de Oliveira Paschoal, Ana Maria, Gomes, Ana Paula Nascimento, Potrich, Ana Paula, Olímpio, Ana Priscila Medeiros, Rojas, Ana, Meiga, Ana Yoko Ykeuti, de Almeida Jácomo, Anah Tereza, Calaça, Analice Maria, Feijó, Anderson, Pagoto, Anderson, Miranda, André Borja, Alonso, André Chein, Barreto-Lima, André Felipe, Lanna, Andre, Luza, André Luís, Camilo, André Restel, Tavares, André, Nunes, André Valle, Kindel, Andreas, de Miguel, Andrés, Gatti, Andressa, Nobre, Andrezza Bellotto, da Conceição Campêlo, Anielise, de Albuquerque, Anna Carolina Figueiredo, de la Torre, Antonio, Mangione, Antonio, Pontes, Antonio Rossano Mendes, Fernandes, Arthur Soares, de Almeida Felicio, Artur Luiz, Ferreguetti, Atilla Colombo, Marcili, Arlei, Piratelli, Augusto João, do Nascimento, Ariel Guilherme Santos, dos Santos, Áureo Banhos, Rosa, Beatris Felipe, Cezila, Beatriz Azevedo, de Thoisy, Benoit, Ingberman, Bianca, Köhler, Bianca, Morais, Bianca Cruz, Gómez-Valencia, Bibiana, de Camargo, Bruna Bertagni, Bezerra, Bruna M., Tamasauskas, Bruna, Campos, Bruno A. T. Parahyba, Kubiak, Bruno Busnello, Saranholi, Bruno Henrique, Nakagawa, Bruno K., Leles, Bruno Pereira, Lim, Burton K., Mendes, Calebe Pereira, Islas, Camila Alvez, Aoki, Camila, Devids, Camila Cantagallo, Figueiredo, Camila, de Abreu, Camila Matias Goes, Oliveira, Camila Raquel Silva, Cassano, Camila Righetto, Lugarini, Camile, Caputo, Carin, Gestich, Carla Cristina, Tedesco, Carla Denise, de Vera y Conde, Carla Fabiane, Hegel, Carla Grasiele Zanin, Kasper, Carlos Benhur, De Angelo, Carlos, Grelle, Carlos E. V., Fragoso, Carlos Eduardo, Esbérard, Carlos Eduardo Lustosa, Rocha, Carlos Frederico Duarte, Verona, Carlos Eduardo, Salvador, Carlos Henrique, Vieira, Carlos Leonardo, Abrahão, Carlos Roberto, Brocardo, Carlos Rodrigo, Fieker, Carolline Zatta, Braga, Caryne, Lalinde, Catalina Sánchez, Bueno, Cecília, Ikuta, Cássia Yumi, Luna, Cecília Licarião Barreto, Cestari, Cesar, Del Vechio Koike, Christine, Knogge, Christoph, Anderson, Christopher Brian, Hurtado, Cindy M., de Oliveira, Cintia Ferreira Antunes, Tellaeche, Cintia, Cesário, Clarice Silva, Costa, Claudia Guimarães, Kanda, Claudia Zukeran, Costa, Sebastián Andrés, Seixas, Cristiana Simão, Trinca, Cristiano Trapé, López-Fuerte, Cristina F., da Cunha, Cristina Jaques, Ribas, Cynthia Doutel, Santos, Cyntia Cavalcante, Buscariol, Daiane, Carreira, Daiane, do Nascimento, Daiane Chaves, Carvalho, Danianderson Rodrigues, da Silva Ferraz, Daniel, Galiano, Daniel, Homem, Daniel Henrique, Jesús-Espinosa, Daniel, Bôlla, Daniela A. S., Moreno, Daniele Janina, de Oliveira Moreira, Danielle, Ramos, Danielle Leal, de Amorim, Danilo Angelucci, Barros-Battesti, Darci Moraes, Lopez, David Echeverri, Tavares, Davi Castro, Post, David M., Couto, Dayvid Rodrigues, Patrocínio, Dennis Nogarolli, Carvalho, Diana Letícia Kruger Pacheco, Silva, Diego Afonso, Córdoba, Diego, Queirolo, Diego, Varela, Diego, de Oliveira, Dilmar Alberto Goncalves, Casanova, Diogo Cavenague, de Matos Dias, Douglas, da Silva, Douglas Machado, Barbier, Eder, Rivadeneira, Edgar Federico, Alexandrino, Eduardo, Carrano, Eduardo, Santos, Eduardo Marques, Venticinque, Eduardo Martins, Hernández-Pérez, Edwin, da Fonseca Casazza, Egberto, Anderson, Elizabeth P., da Costa Fraga, Elmary, de Lima, Elson Fernandes, D’Bastiani, Elvira, Vieira, Emerson Monteiro, Guijosa-Guadarrama, Emiliano, González, Enrique M., Maggiorini, Erica Vanessa, de Aguiar, Erick Francisco Silva, Martínez-Nambo, Erik Daniel, Castro, Érika Paula, de la Peña-Cuéllar, Erika, Pedó, Ezequiel, de Melo, Fabiana Cristina S. Alves, Rocha, Fabiana Lopes, Fonseca, Fabiana Luques, Girardi, Fabiane, de Melo, Fabiano Rodrigues, de Oliveira Roque, Fábio, Ferreira, Fabíola Keesen, Peters, Felipe Bortolotto, Fantacini, Felipe Moreli, Pedrosa, Felipe, da Silva, Felipe Pessoa, Vélez-García, Felipe, Abra, Fernanda D., de Azevedo, Fernanda Cavalcanti, da Silva, Fernanda Guedes, Neri, Fernanda Maria, Teixeira, Fernanda Zimmermann, dos Santos Fernandez, Fernando Antonio, Carvalho, Fernando, Passos, Fernandode Camargo, de Castro Jacinavicius, Fernando, Ferreira, Fernando, de Pinho, Fernando Ferreira, Gonçalves, Fernando, Martins, Fernando Ibanez, Lima, Fernando, Contreras-Moreno, Fernando M., Ribeiro, Fernando Silvério, Tortato, Fernando, Patel, Filipe M., Caruso, Flavia, Tirelli, Flávia Pereira, Rodrigues, Flávio Henrique Guimarães, Ubaid, Flávio Kulaif, Palmeira, Francesca Belem Lopes, Neto, Francisco Grotta, Gabriel, Francisco Homem, de Souza, Franco Leandro, da Veiga da Costa, Francys E., de Aguiar, Gabriel Lima, Lemos, Frederico Gemesio, Magezi, Gabriel S., Di Panigai, Gabriel Ferreira Vianna, Hofmann, Gabriel Selbach, Heliodoro, Gabriela, Graviola, Gabriela Rosa, Beca, Gabrielle, de Andrade, Gabrielle Ribeiro, Romero, Germán Jiménez, Duarte, Gabriela Teixeira, Melo, Geruza Leal, Dierings, Geverson Luiz, Sabino-Santos, Gilberto, de Oliveira, Geovana Linhares, Santana, Gindomar Gomes, Ciocheti, Giordano, Zanirato, Gisele Lamberti, Alves, Giselle Bastos, Batista, Graziele Oliveira, Behling, Greici Maia, Ferreira, Guilherme Braga, da Rocha, Guilherme Casoni, Lessa, Gisele, Mourão, Guilherme, Maras, Gustavo A., da Costa Toledo, Gustavo Alves, Gonsioroski, Gustavo, Canale, Gustavo R., Schuchmann, Karl-Ludwig, Sebastião, Harley, do Prado, Helena Alves, de Godoy Bergallo, Helena, Secco, Helio Kinast Cruz, Roig, Henrique Llacer, Rajão, Henrique, Carlos, Henrique Santiago Alberto, de Oliveira B. Duarte, Herbert, Ermenegildo, Hiago, de Jesus Pena, Hilda Fátima, Júnior, Hilton Entringer, Neto, Hipólito Ferreira Paulino, de Macedo Lemos, Hudson, del Castillo, Hugo, Fernandes-Ferreira, Hugo, Banquero, Hugo Ignacio Coitiño, Roesler, Ignacio, Ribeiro, Igor Kintopp, Coelho, Igor Pfeifer, Lima, Ingrid M. S., Bechara, Isabel Muniz, Lermen, Isabel Salgueiro, Méndez, Isac Mella, Schuck, Gabriela, Esperandio, Isadora Beraldi, de Oliveria Silva, Ita, Mourthe, Italo, Oliveira, Igor, Bernardi, Itiberê Piaia, Miller, Jacqueline R., Marinho-Filho, Jader, Zocche, Jairo José, Russell, James Charles, Seibert, Jardel Brandão, Hinojosa, Javier, Vitule, Jean R. S., Thompson, Jeffrey J., Silva, Jean Carlos Ramos, Gouvea, Jéssica Abonízio, Santos, Jean Pierre, de Faria Falcão, Jéssica Caroline, Castro-Prieto, Jessica, Ferreira, Jéssica Paloma, Pincheira-Ulbrich, Jimmy, Nodari, Joana Zorzal, Gebin, João Carlos Zecchini, Giovanelli, João Gabriel Ribeiro, Miranda, João M. D., Souza-Alves, João Pedro, de Almeida Marins, João Rafael Gomes, Costa, Jociel Ferreira, Sponchiado, Jonas, de Souza, Jonathas Linds, Gallo, Jorge Alberto, Cherem, Jorge José, Cordeiro, José Luís Passos, Duarte, José Maurício Barbanti, Dantas, José Oliveira, de Matos, José Roberto, Pires, José Salatiel Rodrigues, Lanfranco, Juan Andrés Martínez, de la Cruz Godoy, Juan Camilo, Rudolf, Juan Carlos, Parrish, Juan Felipe Reátiga, Tellarini, Juan Francisco, Peña-Mondragón, Juan L., Arrabal, Juan Pablo, Reppucci, Juan, Ruiz-Esparza, Juan, Beduschi, Julia, de Faria Oshima, Júlia Emi, Ribeiro, Juliana Fernandes, de Almeida Rocha, Juliana Monteiro, Neto, José Soares Ferreira, dos Santos, Juliana Silveira, Pereira-Ribeiro, Juliane, Zanoni, Juliani Bruna, Bogoni, Juliano André, Ferreira, Juliana Rodrigues, Bicca-Marques, Júlio César, Pacheco, Julio Javier Chacón, de Oliveira Scarascia, Pietro, Guidoni-Martins, Karlo Gregório, Burs, Kathrin, de Barros Ferraz, Katia Maria Paschoaletto Micchi, Pisciotta, Kátia Regina, Von Kossel de Andrade Silva, Katyucha, Juarez, Keila MacFadem, de 1a Cruz-Félix, Keynes, de Morais, Kimberly Danielle Rodrigues, Candelária, Lana Pavão, Fornitano, Larissa, Bailey, Larissa Lynn, Gonçalves, Larissa Oliveira, Fasola, Laura, León, Laura Johanna Nova, de Andrade, Layla Reis, de Oliveira Marques, Leandro, Macedo, Leandro, Moreira, Leandro Santana, Silveira, Leandro, de Carvalho Oliveira, Leonardo, da Silva, Leonardo Henrique, Jerusalinsky, Leandro, La Serra, Leonardo, Costa, Leonardo Marques, Sartorello, Leonardo Rodrigues, Munhoes, Leticia Prado, Oliveira-Silva, Liany Regina B., de Pina, Ligia Ferracine, Bonjorne, Lilian, Rampim, Lilian Elaine, Sales, Lilian P., da Silva, Lucas Gonçalves, Quintilham, Lucas Lacerda Toth, Perillo, Lucas Neves, Rodríguez-Planes, Lucía Inés, Martín, Lucía, Araújo, Luciana Souza, Tiepolo, Liliani Marilia, Silva, Luciana Zago, Loaiza, Lina Marcela García, de Alagão Querido, Luciano Carramaschi, da Silva, Luciano Ferreira, La Sala, Luciano Francisco, Bopp, Luciano Tessare, Hufnagel, Ludmila, de Oliveira, Luiz Flamarion Barbosa, Oliveira-Santos, Luiz Gustavo Rodrigues, Lyra, Luiz Henrique, Guimarães, Luiza Neves, Segura, Luz Fernanda Jimenez, de Sousa, Luziene Conceição, Möcklinghoff, Lydia, Guichón, M. Laura, de la Maza, Javier, Barrios-Garcia, M. Noelia, Talamoni, Sônia A., Severo, Magnus Machado, Martins, Maísa Ziviani Alves, Oliveira, Marcela Alvares, Moraes, Marcela Figuerêdo Duarte, Lima, Marcela Guimarães Moreira, Pinheiro, Marcell Soares, do Carmo Pônzio, Marcella, Guerreiro, Marcello, Cervini, Marcelo, da Silva, Marcelo, Oliveira, Marcelo Juliano Rabelo, Magioli, Marcelo, Passamani, Marcelo, de Almeida, Marcelo Silva, Amaku, Marcos, de Oliveira, Márcio Leite, Tortato, Marcos Adriano, Melo, Marcos Antônio, Coutinho, Marcos E., Santos, Marcos Pérsio Dantas, Vieira, Marcus V., Andrade, Maria Augusta, Barros, Maria Claudene, do Rosario, Maria Cristina Ferreira, dos Santos Domit, Maria Dolores Alves, de Avelar Fernandes, Maria Emília, Iezzi, María Eugenia, do Nascimento, Maria Histele Sousa, Andrade-Núñez, María José, Lorini, Maria Lucia, de Castro Morini, Maria Santina, Nagy-Reis, Mariana B., Landis, Mariana Bueno, Vale, Mariana Moncassim, Xavier, Mariana Sampaio, Kaizer, Mariane C., Baptiste, Maria Piedad, Bergel, Mariano Maudet, Borgnia, Mariela, Barros, Marília A. S., da Silva, Marina Lima, Favarini, Marina Ochoa, Munerato, Marina Sales, Zaluar, Marina Trancoso, Winter, Marina, da Silva, Marina Xavier, Zanin, Marina, Marques, Marinêz Isaac, Haberfeld, Mario Burke, Di Bitetti, Mario S., Galliez, Maron, Alvarez, Martin R., Malerba, Martina, Rivero, Marina, Dias, Mateus Melo, de Oliveira, Mateus Yan, dos Reis, Matheus Gonçalves, Corrêa, Matheus Rocha Jorge, Graipel, Maurício Eduardo, Godoi, Mauricio N., Núñez-Regueiro, Maurício M., Moura, Mauricio Osvaldo, Orsi, Mário Luís, da Silva, Marco Aurélio Galvão, Lopez, Mauro Sanvicente, Benedetti, Maximiliano Augusto, Beltrão, Mayara Guimarães, Camino, Micaela, Faria, Michel Barros, Miretzki, Michel, Luiz, Micheli Ribeiro, Perine, Michell, Monteiro, Miguel Coutinho Moretta, Alves-Eigenheer, Milene, Perilli, Miriam Lucia Lages, da Silva, Mônica Andrade, Marini, Miguel Ângelo, Pereira, Monicque Silva, de Freitas Junior, Mozart Caetano, Cossa, Natalia, Denkiewicz, Natalia Mariana, Tôrres, Natália Mundim, Olifiers, Natalie, de Albuquerque, Natasha Moraes, Canassa, Nathália Fernandes, Detogne, Nathália, Filho, Newton Gurgel, Seoane, Nicolás Fernando, da Rosa Oliveira, Nicole, Megale, Nicoli, Pasqualotto, Nielson, Cáceres, Nilton Carlos, Peroni, Nivaldo, Zanella, Noeli, Pays, Olivier, Arimoro, Omolabake Alhambra Silva, Acevedo-Charry, Orlando, de Almeida Curi, Nelson Henrique, Pinha, Patricia Ribeiro Salgado, Perovic, Pablo, Gonçalves, Pablo Rodrigues, Santos, Paloma Marques, de Goés Brennand, Pamella Gusmão, Rogeri, Patrícia Kerches, Ribeiro, Patrícia Rosas, da Rocha, Patrício Adriano, de Lázari, Patrick Ricardo, Pedreira, Paula Anabel, Pinheiro, Paula Fabiana, Lira, Paula Koeler, Ferreira, Paula Modenesi, Martin, Paula Sanches, de Tarso Zuquim Antas, Paulo, Marinho, Paulo Henrique, Ruffino, Paulo Henrique Peira, Camargo, Paulo Henrique S. A., Filho, Paulo Landgref, Mangini, Paulo Rogério, Farias, Patrick, Cordeiro-Estrela, Pedro, de Faria Peres, Pedro Henrique, Galetti, Pedro Manoel, Ramírez-Bautista, Pedro, de Almeida Maués, Paula Cristina Rodrigues, Renaud, Pierre-Cyril, Sartorello, Ricardo, de Barros, Pollyanna Alves, Lombardi, Pryscilla Moura, Bessa, Rafael, Arroyo-Gerala, Paulina, de Souza, Rafael Cerqueira Castro, Zenni, Rafael D., Peredo, Rafael Flores, Hoogesteijn, Rafael, Loyola, Rafael, Alves, Rafael Souza Cruz, de Paula Rodarte, Raisa Reis, Silva, Ramon Lima, de Oliveira, Ramonna, Beltrão-Mendes, Raone, de Macêdo Alencar, Raony, da Silva, Raquel Costa, Pedroso, Rayssa, Sampaio, Rebeca Ferreira, Ribeiro, Renan Lieto Alves, Pardini, Renata, Bonikowski, Renata Twardowsky Ramalho, Pagotto, Renata Valls, Dias, Ricardo Augusto, Bassini-Silva, Ricardo, Arrais, Ricardo Corassa, Sampaio, Ricardo, de Cassia Bianchi, Rita, Paolino, Roberta Montanheiro, Fusco-Costa, Roberto, Trovati, Roberto Guilherme, Hack, Robson Odeli Espíndola, de Arruda Mauro, Rodiney, de Almeida Nobre, Rodrigo, Gessulli, Rodrigo Delmonte, Pérez, Rodrigo León, Massara, Rodrigo Lima, da Silva, Rodrigo Medina Fróes, de Paula, Rogério Cunha, da Cunha, Rogério Grassetto Teixeira, Costa, Rômulo Theodoro, Marques, Rosane Vera, Morato, Ronaldo Gonçalves, Bovendorp, Ricardo S., da Paixão Dornas, Rubem Augusto, Andrade, Rubia Santana, Siciliano, Salvatore, Guaragni, Samara Arsego, Rolim, Samir Gonçalves, Astete, Samuel, Cavalcanti, Sandra, Hartz, Sandra Maria, Carvalho, Santiago, Cortez, Sara, de Sousa, Saulo Meneses Silvestre, Ballari, Sebastián A., Lima, Saulo Ramos, Cirignoli, Sebastián, García-R, Sebastian, Bazilio, Sérgio, Torres, Sergio Solari, Franco, Silvana Back, Martins, Simone Rebouças, de Bustos, Soledad, Age, Stefani Gabrieli, Ferrari, Stephen Francis, Francisco, Talitha Mayumi, Micheletti, Tatiane, da Silva Godim, Tayanna Medonça, Luiz, Thais Guimaraes, de Freitas, Thales Renato Ochotorena, Rodrigues, Thiago Ferreira, Piovezan, Ubiratan, Barcos, Umberto Cotrim, Onofrio, Valeria Castilho, Martin-Albarracin, Valeria L., Towns, Valeria, Araújo, Valquíria Cabral, Kanaan, Vanessa, Daga, Vanessa Salete, Boere, Vanner, de Araujo, Verônica Parente Gomes, Benitez, Verónica Victoria, Leandro-Silva, Victor, Geraldi, Vilma Clarice, Alberici, Vinicius, Bastazini, Vinícius Augusto Galvão, de Oliveira Gasparotto, Vinícius Peron, Orsini, Vinícius Santana, da Silva, Virgínia Santiago, Bonzi, Viviana Rojas, Pereira, Vinicius José Alves, Layme, Viviane Maria Guedes, da Silva, Victor Hugo Duarte, Tomas, Walfrido Moraes, De Almeida Moreira, Thamy, Martins, Waldney Pereira, de Moraes Pires, Walna Micaelle, Hannibal, Wellington, Dáttilo, Wesley, Mottin, Viviane, Endo, Whaldener, Bercê, William, Carvalho, William Douglas, Magnusson, William, Akkawi, Paula, Di Blanco, Yamil, Amaral, Paulo Roberto, Ramos, Yan Gabriel Celli, Rodríguez-Calderón, Yenifer G., Mendes, Yuri Raia, Ribeiro, Yuri Geraldo Gomes, Campos, Zilca, Galetti, Mauro, and Ribeiro, Milton Cezar

Published
2020

5. NEOTROPICAL XENARTHRANS : a data set of occurrence of xenarthran species in the Neotropics

Author

Santos, Paloma Marques, Bocchiglieri, Adriana, Chiarello, Adriano Garcia, Paglia, Adriano Pereira, Moreira, Adryelle, de Souza, Agnis Cristiane, Abba, Agustin Manuel, Paviolo, Agustin, Gatica, Ailin, Medeiro, Akyllan Zoppi, Costa, Alan Nilo, Gallina, Alberto Gonzalez, Yanosky, Alberto A., Jesus, Alejandro, Bertassoni, Alessandra, Rocha, Alessandro, Bovo, Alex Augusto Abreu, Bager, Alex, Mol, Alexandra Cravino, Martensen, Alexandre Camargo, Faustino, Alexandre Casagrande, Lopes, Alexandre Martins Costa, Percequillo, Alexandre Reis, Vogliotti, Alexandre, Keuroghlian, Alexine, de laColina, María Alicia, Devlin, Allison L., García-Olaechea, Alvaro, Sánchez, Amadeo, Srbek-Araujo, Ana Carolina, Ochoa, Ana Cecilia, Oliveira, Ana Cristina Mendes, Lacerda, Ana Cristyna Reis, Campelo, Ana Kellen Nogueira, de Oliveira Paschoal, Ana Maria, Costa, Ana Raíssa Cunha, Meiga, Ana Yoko Ykeuti, Jesus, Anamélia Souza, Feijó, Anderson, Hirsch, André, da Silva, André Luiz Ferreira, Botelho, André Luis Moura, Regolin, André Luis, Lanna, André Monnerat, Nunes, André Valle, Kindel, Andreas, Moraes, Andreia Magro, Gatti, Andressa, Noss, Andrew J., Nobre, Andrezza Bellotto, Montanarin, Anelise, Deffaci, Ângela Camila, de Albuquerque, Anna Carolina Figueiredo, de Oliveira, Anne Karoline, Mangione, Antonio Marcelo, Pontes, Antonio Rossano Mendes, Bertoldi, Ariane Teixeira, Calouro, Armando Muniz, Desbiez, Arnaud L. J., Fernandes, Arthur, Ferreguetti, Atilla Colombo, da Silva, Maria Augusta Andrade, Zimbres, Barbara, Luciano, Beatriz Fernandes Lima, de Thoisy, Benoit, Niebuhr, Bernardo Brandão S., Papi, Bernardo, Gómez-Valencia, Bibiana, Santos, Bráulio A., Lima, Breno Campelo, Oliveira, Bruna Gomes, Santos, Bruna Silva, Campos, Bruno Augusto Torres Parahyba, Leles, Bruno, de Albuquerque França, Bruno Rodrigo, Lim, Burton, Oliveira, Caetano Troncoso, Cantagallo, Camila, Lara, Camila Clozato, Lima, Camila Silveira, Gestich, Carla Cristina, de Melo-Soares, Carla Danielle, Peres, Carlos A., Kasper, Carlos Benhur, Candia-Gallardo, Carlos, De Angelo, Carlos, Fragoso, Carlos Eduardo, de Freitas, Carlos Henrique, Salvador, Carlos Henrique, Brocardo, Carlos R., Melo, Carolina Depolito, Leuchtenberger, Caroline, Braga, Caryne, Sánchez-Lalinde, Catalina, Bueno, Cecília, Luna, Cecília Licarião, Rojano, Cesar, Hurtado, Cindy Meliza, dos Santos, Cinthya Chiva, Tellaeche, Cintia, Rosa, Clarissa, de Campos, Claudia Bueno, Silva, Cláudia Regina, Kanda, Claudia Zukeran, Jenkins, Clinton N., McDonough, Colleen, Trinca, Cristiano Trapé, da Cunha, Cristina Jaques, Widmer, Cynthia Elisa, Santos, Cyntia, Buscariol, Daiane, Carreira, Daiane Cristina, Carvalho, Danianderson Rodrigues, da Silva Ferraz, Daniel, Casali, Daniel, Thornton, Daniel, Vasconcellos, Daniela Rodrigues, Barcelos, Daniele, Brown, Danielle, Ramos, Daniella Leal, Moreira, Danielle Oliveira, Yogui, Débora Regina, Faria, Deborah, Sana, Denis Alessio, de Mattia, Denise Lidoro, Henz, Denison José, Friedeberg, Diana B, Carvalho, Diana Letícia Kruger Pacheco, Astúa, Diego, Queirolo, Diego, Varela, Diego M., Eaton, Donald P., Dias, Douglas Matos, Rivadeneira, Edgar Federico, Rocha, Ednaldo Cândido, de Abreu-Júnior, Edson Fiedler, Carrano, Eduardo, Santos, Eduardo Marques, Setz, Eleonore Zulnara Freire, Carvalho, Elildo Alves Ribeiro, de Almeida Chiquito, Elisandra, de Matos Cardoso, Elizandra, Mendonça, Eloisa Neves, D’Bastiani, Elvira, Vieira, Emerson M., Ramalho, Emiliano Esterci, Guijosa-Guadarrama, Emiliano, González, Enrique, Maggiorini, Erica Vanessa, Fischer, Erich, Aguiar, Erick Francisco, Castro, Érika Paula, de la Peña-Cuéllar, Erika, de Castro, Ernesto B. Viveiros, Brítez, Evelyn Beatriz, Vanderhoeven, Ezequiel Andres, Pedó, Ezequiel, Rocha, Fabiana Lopes, Girardi, Fabiane, de Oliveira Roque, Fabio, Mazim, Fábio Dias, de Barros, Fabio Monteiro, Martello, Felipe, Fantacini, Felipe Moreli, Pedrosa, Felipe, Peters, Felipe Bortolotto, Abra, Fernanda Delborgo, de Azevedo, Fernanda Cavalcanti, da Silva Santos, Fernanda, da Silva, Fernanda Guedes, Teixeira, Fernanda Zimmermann, Perini, Fernando Araujo, Passos, Fernando C., Carvalho, Fernando, de Azevedo, Fernando Cesar Cascelli, de Pinho, Fernando Ferreira, Gonçalves, Fernando, Lima, Fernando, Contreras-Moreno, Fernando M., Pedroni, Fernando, Tortato, Fernando Rodrigo, Santos, Filipe Pereira Rego, Caruso, Flavia, Tirelli, Flávia Pereira, Miranda, Flávia Regina, Rodrigues, Flávio Henrique Guimarães, Ubaid, Flávio Kulaif, Palmeira, Francesca Belem Lopes, da Silva, Franciane Almeida, Grotta-Neto, Francisco, de Souza, Franco Leandro, Costa, Francys Emanuelle, Pérez-Garduza, Freddy, Delsuc, Frédéric, Lemos, Frederico, Pinto, Fredy Ramirez, Boaglio, Gabriel Ivan, Massocato, Gabriel Fávero, Preuss, Gabriel, Hofmann, Gabriel Selbach, Aguiar, Gabriel Lima, Oliveira, Gabriela Schuck, Duarte, Gabriela Teixeira, Beca, Gabrielle, Giné, Gastón Andrés Fernandez, Batista, Graziele Oliveira, Gil, Guillermo Eduardo, Gonsioroski, Gustavo, Secco, Helio, Medeiros, Hugo Reis, Coelho, Igor Pfeifer, Franceschi, Ingridi Camboim, Bernardi, Itiberê, de la Torre, J. Antonio, Zocche, Jairo José, Seibert, Jardel Brandão, de Faria Falcão, Jéssica Caroline, Dias, Jéssica Helena Mangueira, Nodari, Joana Zorzal, Oliveira, João Alves, Giovanelli, João Gabriel Ribeiro, Favoretti, João Paulo Pandini, Polisar, John, Sponchiado, Jonas, Cherem, Jorge José, Ramírez, José Fernando Moreira, de Toledo, José Julio, Duarte, José Maurício Barbanti, de Matos, Jose Roberto, Arrabal, Juan Pablo, de Faria Oshima, Júlia Emi, Ribeiro, Juliana Fernandes, Bogoni, Juliano André, Pacheco, Julio Javier Chacón, Schuchmann, Karl L., Ferraz, Katia M. P. M. B., dos Santos Everton, Laís, Bailey, Larissa L., Gonçalves, Larissa Oliveira, Cullen, Laury, de Andrade, Layla Reis, Trevelin, Leonardo Carreira, Bonjorne, Lilian, de Almeida Rodrigues, Livia, Leuzinger, Lucas, Perillo, Lucas Neves, Araújo, Luciana Souza, Hufnagel, Ludmila, Ribeiro, Ludmilla Oliveira, Bernardo, Luis Renato Rezende, Oliveira-Santos, Luiz Gustavo Rodrigues, Varzinczak, Luiz Henrique, Borges, Luiz Henrique Medeiros, Guimarães, Luiza Neves, Möcklinghoff, Lydia, Oliveira, Marcela Alvares, Magioli, Marcelo, de Assis Jardim, Márcia Maria, de Oliveira, Márcio Leite, Tortato, Marcos Adriano, Dums, Marcos, Iezzi, Maria Eugenia, Pereira, Maria João Ramos, Jorge, Maria Luísa, de Castro Morini, Maria Santina, Landis, Mariana Bueno, Xavier, Mariana Sampaio, Barros, Marília A. S., da Silva, Marina Lima, Rivero, Marina, Zanin, Marina, Marques, Marinêz Isaac, Alves, Mario Henrique, Di Bitetti, Mario S., Alvarez, Martín R., Graipel, Maurício Eduardo, Godoi, Mauricio Neves, Benedetti, Maximiliano Augusto, Beltrão, Mayara Guimarães, Monteiro, Miguel Coutinho Moretta, de Paula, Milton José, Perilli, Miriam Lucia Lages, da Silva, Murillo Prado, Villar, Nacho, De Albuquerque, Natasha Moraes, Canassa, Nathália F., Filho, Newton Mota, da Rosa Oliveira, Nicole, Pasqualotto, Nielson, Cáceres, Nilton Carlos, Attias, Nina, Favarini, Marina Ochoa, Ribeiro, Otávio Santi, Gonçalves, Pablo Rodrigues, da Rocha, Patrício Adriano, Condé, Paula Alves, Akkawi, Paula, Cruz, Paula, Lira, Paula Koeler, Ferreira, Paula Modenesi, Arroyo-Gerala, Paulina, Hartmann, Paulo Afonso, de Tarso Zuquim Antas, Paulo, Marinho, Paulo Henrique, de Faria Peres, Pedro Henrique, Peña-Mondragón, Juan Luis, Lombardi, Pryscilla Moura, de Souza Laurindo, Rafael, Alves, Rafael Souza Cruz, Grangeiro, Raissa Danielle Praxedes, Silva, Ramon Lima, Beltrão-Mendes, Raone, Bonikowski, Renata Twardowsky Ramalho, Reppucci, Juan, Arrais, Ricardo Corassa, Sampaio, Ricardo, Sartorello, Ricardo, Bovendorp, Ricardo Siqueira, McNab, Roan, Hack, Robson Odeli Espíndola, Magalhães, Rodolfo Assis, Araújo, Rodrigo Costa, de Almeida Nobre, Rodrigo, Pérez, Rodrigo Raúl León, Massara, Rodrigo Lima, de Paula, Rogério Cunha, Anleu, Rony García, Marques, Rosane Vieira, Dornas, Rubem, Rolim, Samir Gonçalves, Cavalcanti, Sandra M. C., Lima, Saulo Ramos, Ballari, Sebastián A., Santamaría, Silvia Benito, Silva, Sofia Marques, Age, Stefani Gabrieli, Godim, Tayana, Sobral-Souza, Thadeu, Maccarini, Thiago Bernardes, Rodrigues, Thiago Ferreira, Piovezan, Ubiratan, da Cunha Tavares, Valéria, Quiroga, Verónica Andrea, Krepschi, Victor Gasperotto, Filho, Vilmar Picinatto, Bastazini, Vinícius Augusto Galvão, de Oliveira Gasparotto, Vinicius Peron, Orsini, Vinicius Santana, Layme, Viviane Maria Guedes, Hannibal, Wellington, Dáttilo, Wesley, de Carvalho, William Douglas, Loughry, William James, Di Blanco, Yamil Edgardo, Núñez-Regueiro, Mauricio M., Giubbina, Marina Furlan, Passamani, Marcelo, de Alagão Querido, Luciano Carramaschi, da Costa Toledo, Gustavo Alvez, Ribeiro, Igor Kintopp, Quintilham, Lucas, de Bustos, Soledad, de la Maza, Javier, Neto, Jorge Ferreira Lima, Von Kossel de Andrade Silva, Katyucha, Sartorello, Leonardo, Rampim, Lilian Elaine, Marás, Gustavo A., Camino, Micaela, Freitas-Junior, Mozart, Perovic, Pablo Gaston, Paolino, Roberta Montanheiro, Ferreira, Scarlat Dalva, Towns, Valeria, Esperandio, Isadora Beraldi, Aximoff, Izar, Beduschi, Júlia, Guenther, Mariana, de Cassia Bianchi, Rita, Keuroghlian-Eaton, Sean, Mendes, Sérgio Lucena, de Fatima Cunha, Lerrane, Cirignoli, Sebastián, Ciocheti, Giordano, do Prado, Helena Alves, Fernandes-Ferreira, Hugo, de Sena, Liana Mara Mendes, Yamane, Marcelo Hideki, Brennand, Pamella G. G, da Silva, Rayana Diniz, Escobar, Santiago, Endo, Whaldener, Hurtado, Rafael Reyna, Gontijo, Nila Rássia Costa, Marsh, Laura K., Severo, Magnus Machado, Pardo, Julia Martinez, Costa, Sebastián Andrés, Melo, Geruza Leal, Santana, Gindomar Gomes, de Miranda Mourão, Guilherme, Gaspari, Gustavo Gabirele, Duarte, Herbert, Cabral, Hugo, da Silva, Leonardo Henrique, Mendonça, Luana, Barbosa, Lucas Lobo, dos Santos, Manuela Vieira, Moraes, Marcela Figuerêdo Duarte, Gordo, Marcelo, Versiani, Natalia Fraguas, Cantero, Nicolás, Pays, Olivier, Guedes, Patrícia Gonçalves, Colas-Rosas, Paul François, Ribeiro, Paulo, Renaud, Pierre-Cyril, Hoogesteijn, Rafael Jan, Ayala, Rodrigo, da Cunha, Rogério Grassetto Teixeira, Schaub, Roxane, Laurito, Sabrina, Betkowski, Samuel Eurich, Cortez, Sara, Silva, Shirley Seixas Pereira, de Oliveira, Tadeu Gomes, Spironello, Wilson Roberto, Gengler, Nicholas, Hidalgo, Mircea Mihart, Juárez, Rugieri, Iglesias, Jesús A, Anacleto, Teresa Cristina, de Souza Fialho, Marcos, Cavicchioli, Guilherme, Beccato, Maria Angélica Barbosa, da Silva, Marcelo, Neto, Omar Correia, Lopes, Karine Galisteo Diemer, Godoy, Leandro Perez, Luiz, Micheli Ribeiro, Rojas Bonzi, Viviana B., Ferreira, Guilherme Braga, Oliveira, Marcelo Juliano Rabelo, Hinojosa, Javier, de Oliveira, Luiz Flamarion Barbosa, Nagy-Reis, Mariana Baldy, Ramirez, Sixto Fernández, Concone, Henrique Villas Boas, Mourthe, Italo, Martínez-Lanfranco, Juan A., Zanoni, Juliani Bruna, Moreira, Tainah Cruz, Guarderas, Zoila Vega, Bazilio, Sérgio, Cervini, Marcelo, Pinheiro, Marcell Soares, Morato, Ronaldo Gonçalves, Peroni, Nivaldo, Trigo, Tatiane Campos, Machado, Ricardo Bomfim, Gaspari, Fernando, Koenemann, Joceleia G., Rudolf, Juan Carlos, Benchimol, Maíra, Vieira, Marcus Vinícius, Retta, Lucía Martínez, Santiago, Pablo Gerardo Fernández, Ciccia, Paula Gonzalez, Estrela, Pedro Cordeiro, Carvalho, Santiago, Esbérard, Carlos Eduardo Lustosa, de la Cruz, Yaribeth Bravata, Castro-Prieto, Jessica, Braga, Ricardo Miranda, Cartes, Jose Luis, Andrade-Núñez, María José, Denkiewicz, Natalia Mariana, Falconi, Nereyda, Pezzuti, Juarez Carlos Brito, del Castillo Cordero, Hugo Fernando, de Sousa, Luziene Conceição, de Gaspari Júnior, Roque Lázaro, Santos-Filho, Manoel, Almeida, Josué Santos, Thompson, Jeffrey J., dos Santos, Juliana Silveira, Pereira-Ribeiro, Juliane, Burs, Kathrin, da Silva, Kena Ferrari Moreira, Velilla, Marianela, da Silva, Marina Xavier, de la Sancha, Noé U., Pinheiro, Paula Fabiana, de Castilho, Pedro Volkmer, Bercê, William, Assis, Julia Camara, Tonetti, Vinicius Rodrigues, Alves-Eigenheer, Milene, Chinem, Simonne, Honda, Laura K., de Godoy Bergallo, Helena, Alberici, Vinicius, Wallace, Robert, Krauer, Juan Manuel Campos, Ribeiro, Milton Cezar, and Galetti, Mauro

Published
2019

6. Process and parameters for laser assisted localised heat treatment in manufacturing applications.

Author

Pereira, Rui Pedro, Peixinho, Nuno, Carneiro, Vítor, Cortez, Sara, Costa, Sérgio Luís, and Blanco, Vítor

Abstract

This paper presents information and results relevant for the development of a laser heat treatment process suitable to improve manufacturing in high strength steel and high strength aluminium alloys. The challenges with manufacturing of such materials include springback effect and localised fracture. The study details heat cycle and their effect in metallurgical state and mechanical properties. Such laser induced heat treatment process is intended to improve the forming behaviour of metal parts in challenging metal forming conditions, in particular for the delay or avoidance of localised fracture. Results for strength, hardness and elongation properties are presented. It was concluded that it is possible to locally modify yield strength and hardness using process duration suitable for industrial applications. Suitable process temperature ranges and target heat cycles were identified. A positive effect of material softening was observed in both hardness and strength properties. However, in some cases a reduction of ductility is apparent which must be considered for targeted industrial applications. The dimension of the heat-affected zone was also considered as design variable for the industrial process development. Preliminary results were obtained in a development forming tool. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Development of Laser Heat Treatment Process for Assisted Forming of Aluminum Alloys.

Author

Peixinho, Nuno, Pereira, Rui, Carneiro, Vitor, Cortez, Sara, Costa, Sergio, and Blanco, Vitor

Subjects
ALUMINUM, HEAT treatment, LASERS, ELONGATION factors (Biochemistry), INDUSTRIAL applications
Abstract

This study presents information regarding the development of a localized laser-induced heat treatment for aluminum alloys. Such a process is intended to improve the forming behavior of aluminum parts in challenging metal-forming conditions. This study details information on material, heat treatment parameters as well as results for strength, hardness, and elongation properties. It was concluded that it is possible to locally modify yield strength and hardness using laser control parameters and process duration suitable for industrial applications. [ABSTRACT FROM AUTHOR]

Published
2024
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8. An Experimental and Numerical Study on Aluminum Alloy Tailor Heat Treated Blanks.

Author

Pereira, Rui, Peixinho, Nuno, Carneiro, Vítor, Soares, Delfim, Cortez, Sara, Costa, Sérgio L., and Blanco, Vítor

Subjects
ALUMINUM forming, STRESS-strain curves, HEATING control, COMPUTER simulation
Abstract

Information is presented on the conceptualization, experimental study, and numerical process simulation of tailor heat treated aluminum alloy blanks. This concept is intended to improve the forming behavior of aluminum parts in challenging conditions. The implementation requires precise control of laser heat treatment parameters within a suitable industrial framework. The study details material properties, heat treatment parameters, and experimental results for the strength and elongation properties of an AA6063-T6 aluminum alloy. Constitutive modeling is applied using the Hocket–Sherby equation, which allowed us to establish a correlation between laser heat treatment maximum temperature and the corresponding material softening degree. Based on the generated flow stress–strain curves, a numerical simulation of a representative case study was performed with Abaqus finite element software highlighting potential improvements of tailor heat treated blanks (THTB). The influence and effectiveness of heat-affected zone (HAZ) dimensions and material softening were analyzed. [ABSTRACT FROM AUTHOR]

Published
2023
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10. Development of an innovative double-chamber syringe for intravenous therapeutics and flushing: Nurses' involvement through a human-centred approach.

Author

Parreira, Pedro, B. Sousa, Liliana, Marques, Inês A., Costa, Paulo, Cortez, Sara, Carneiro, Filipa, Cruz, Arménio, and Salgueiro-Oliveira, Anabela

Subjects
TECHNOLOGY assessment, SYRINGES, NURSES, MEDICAL equipment, MEDICAL technology, DISPOSABLE medical devices, NURSING informatics
Abstract

Background: In nursing practice, flushing the catheters pre and post-drug administration is considered an important clinical procedure to prevent complications, and requires the use of several syringes to comply with international standards of care. We envisioned an innovative double-chamber syringe that enables the filling and administration of both solutions. Following current international recommendations, the development of new medical devices should integrate Health Technology Assessment. The Human-centred design is usually used for that assessment purposes, as a method that actively include end-users in the devices development process. Method: Application of the Human-Centred Design through the involvement of nurses in the initial stages of the device development in order to accomplish the initial stages of Technology Readiness Level. A multi-method approach was used, including literature/guidelines review, focus groups with end-users and expert panels. Results: The involvement of nurses enabled the definition of user requirements and contexts of use, as well as the evaluation of design solutions and prototypes in order to accomplish with usability and ergonomic features of the medical device. Conclusions: Significant contributions were made regarding the final design solution of this innovative double-chamber syringe. [ABSTRACT FROM AUTHOR]

Published
2020
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11. Wildlife Conservation, perceptions of different co-existing cultures

Author

Camino, Micaela, Cortez, Sara, Cerezo, Alexis, and Altrichter Mariana

Subjects
Ciencias Biológicas, Chaco, purl.org/becyt/ford/1 [https], Peasants or Criollos, Local perceptions, purl.org/becyt/ford/1.6 [https], CIENCIAS NATURALES Y EXACTAS, Indigenous, Conservación de la Biodiversidad
Abstract

Different cultures have different relationships with nature, and these relationships have many dimensions which shape people’s perceptions towards nature. Therefore, perceptions may vary between different cultures within the same territories. Understanding each culture´s relationship with the surrounding environment is of extreme importance for the correct allocation of conservation resources, and for the development of efficient conservation actions. In this study, we discuss the perceptions of two different cultures regarding large and mediumsized mammal conservation in an endangered region of Argentina, called the Dry Chaco. These two cultures are peasants, or Criollos, and the indigenous Wichís; we assessed and compared their perceptions on local extinctions, conservation problems, conflicts with wildlife and possible solutions for these issues. We found that although both cultures inhabit the same territory and report local extinctions, their perceptions on which species were locally extinct differed. Another difference was the perceived time-period in which disappearances occurred. We also found that most respondents recognize conservation problems and possible solutions, although these differ between both cultures. Management for conservation of these species should be specific to each culture, and understanding local perspectives allows the inclusion of a broader view of human needs, perceptions and knowledge in conservation programs. Fil: Camino, Micaela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Centro de Ecología Aplicada del Litoral. Universidad Nacional del Nordeste. Centro de Ecología Aplicada del Litoral; Argentina. Universidad de Buenos Aires. Facultad de Arquitectura y Urbanismo. Grupo de Ecología del Paisaje y Medio Ambiente; Argentina Fil: Cortez, Sara. No especifica; Fil: Cerezo, Alexis. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina Fil: Altrichter Mariana. Prescott University; Estados Unidos

Published
2016

13. Optimized FE mesh generation based on medical imaging and on a user-defined spatial refinement gradient. Application to a motion segment

Author

Cortez, Sara Isabel Couto, Claro, José Carlos Pimenta, Alves, J. L., and Universidade do Minho

Subjects
FE mesh generation, Engenharia e Tecnologia::Engenharia Mecânica, Biomechanics, Intervertebral disc
Abstract

In general, the starting point for the 3D geometrical modelling by finite elements of an anatomical structure is the generation of a 3D voxel-based geometrical model, obtained after denoising, smoothing and segmentation of a set of 2D medical images. The accuracy of the FE computation increases if the geometry of model resembles, for instance, the natural smoothness of real anatomical structure. Usually, the lack of detailed data in conventional imaging techniques causes further problems in the IVD finite element mesh generation and analysis. Difficulties arise mainly due to the complexity and the dimension of the IVD constituent structures and the lower resolution of medical imaging. After the 3D voxelized model has been defined, a specific isotropic tetrahedral FE meshing procedure is applied and, generally, a too dense and highly refined FE mesh is obtained. Therefore, it is necessary to decrease its size by diminishing the total number of nodes and elements while maintaining both geometrical accuracy and a physically compatible FE mesh refinement. Generally, after this procedure, the smaller elements are located at the internal and external boundaries, while larger elements are located inside the FE mesh. However, this is not always acceptable. There may be situations where this accuracy may be required simultaneously in structures outside and inside the FE mesh. In a motion segment, the FE mesh should be more refined at the IVD and coarser at the vertebrae (nearly incompressible medium). On the other hand, since the annulus fibrosus (AF) is a stiff ring-shaped structure made up of concentric lamellae [1], an optimized FE mesh should be more refined at the annulus fibrosus than at the nucleus pulposus (NP)The aims of this study are: - to study the impact of medical imaging resolution in the FE mesh accuracy; - to develop a refinement gradient, where in this case the elements should be smaller in the outer annulus (where lamellae are denser and combined) than the ones in the inner annulus (less dense lamellae).

Published
2013

14. Collared peccary (<italic>Pecari tajacu</italic>) behavioral reactions toward a dead member of the herd.

Author

de Kort, Dante, Altrichter, Mariana, Cortez, Sara, and Camino, Micaela

Subjects
COLLARED peccary behavior, ANIMAL social behavior, ANIMAL mortality, COYOTE, ANIMAL herds
Abstract

Abstract: Humans, elephants, chimpanzees, and cetaceans show concern with the death of other members of their species and respond to death in particular ways. Science considers that these species are exceptions and that other mammal species show little or no reaction to the dead bodies of individuals of their species. Collared peccaries (Pecari tajacu; Tayassuidae) are social animals that live in groups of 5–50 individuals maintaining close and complex social relationships. The collared peccary occupies many different environments and it is widely distributed from the south of North America to the north of Argentina. Their behavior is well studied, but we know little about their behavior toward the dead. We directly observed and filmed with a camera trap the reactions of a five‐member herd of collared peccaries to the death of a herd member. We worked on a suburban forested area in the mountains of central Arizona. We found that the herd visited and spent time with the dead body for 10 days after the peccary died. The frequency of the visits declined until the cadaver was consumed by coyotes. Most of the videos showed two individuals visited the dead animal (44%), solitary records were also frequent (39%) and only 4% of the videos recorded three peccaries. Visits were more frequent during the night (64%). Peccaries do react to the death of a herd member by behaving in particular ways. Reactions include pushing at the dead individual, staring at it, biting it, and trying to pick it up by putting their snout under the corpse and pushing it up, and defending it from coyotes, among others. These levels of behavioral complexity for peccaries are beyond those known so far. The behaviors of this herd of peccaries resemble those of humans, cetaceans, chimpanzees, and elephants and show that these groups are not the only ones that react to death. [ABSTRACT FROM AUTHOR]

Published
2018
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15. Relations with wildlife of Wichi and Criollo people of the Dry Chaco, a conservation perspective.

Author

Camino, Micaela, Cortez, Sara, Altrichter, Mariana, and Matteucci, Silvia D.

Subjects
*HUMAN-animal relationships, *WILDLIFE conservation, *MESTIZOS, *ANIMAL diversity, *SUBSISTENCE hunting
Abstract

Indigenous Wichís and mestizos Criollos inhabit a rural, biodiversity rich, area of the Argentinean Dry Chaco. Traditionally, Wichís were nomads and their relations with wildlife were shaped by animistic and shamanic beliefs. Today, Wichís live in stable communities and practice subsistence hunting, gathering and in some cases, fishing. Criollos are mestizos, i.e. a mixture of the first Spanish settlers and different indigenous groups. They arrived during the 20th century from neighbouring Provinces. They practice extensive ranching, hunting and gathering. Our aim was to help develop effective and legitimate actions to conserve wildlife species in this region, focused on Wichís' and Criollos' perceptions of and relations with wildlife. We conducted semistructured interviews (N=105) in rural settlements. We found differences in both groups' hunting techniques, drivers and perceptions on the importance of wild meat for nutrition. However, both groups have a close relation with wildlife, they use wild animals in a variety of ways, including as food resource, medicine and predictors of future events. Wichís and Criollos also relate with wildlife in a spiritual dimension, have animistic and shamanic beliefs and have unique traditional ecological knowledge. Hunters in both communities are breaking traditional hunting norms but conservation measures grounded on these norms have a higher probability of success. Management recommendations include developing programmes focused on (i) conserving thin armadillos; (ii) conserving pregnant and breeding females of all species; (iii) managing dogs to avoid unnecessary killings and on (iv) improving local livelihoods. We also provide recommendations that are specific for each group. [ABSTRACT FROM AUTHOR]

Published
2018
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16. Optimized FE mesh generation procedure based on a user-defined spatial refinement gradient. Application to a motion segment

Author

Cortez, Sara Isabel Couto, Pinheiro, Manuel, Claro, José Carlos Pimenta, Alves, J. L., and Universidade do Minho

Subjects
FEM, Intervertebral segment, Engenharia e Tecnologia::Engenharia Mecânica, Biomechanics, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

Finite Element (FE) meshes are usually highly refined and dense and, consequently, computationally very expensive. Therefore, after the preliminary FE mesh generation, it is necessary to decrease its size by diminishing the total number of nodes and elements while maintaining both geometrical accuracy and a physically-meaningful FE mesh refinement. The aim of this work is to describe an optimized FE mesh simplification procedure based on edge contraction and on a user-defined spatial refinement gradient criterion. The main idea is that, for normal mechanical loadings applied to a motion segment, the vertebrae shall behave almost as an incompressible medium, and only the intervertebral disc (IVD) should undergo relevant strains. In this case, it is acceptable (and desirable) to attain a problem-functional FE mesh, in which the FE mesh should be more refined at the IVD and coarser at vertebrae. On the other hand, an optimized FE mesh should be more refined at the annulus fibrosus than at the nucleus pulposus. In summary, the proposed FE mesh generation and simplification procedure, being based on a user-definable spatial FE mesh refinement gradient, allows the user to define precisely the required refinement and thus to reduce drastically the number of elements in the final FE mesh and consequently to diminish the computation time required for the FE analysis, while keeping the necessary physical meaning on the FE mesh. The aforesaid procedure will be applied to the FE mesh generation (based on [1]) of a motion segment initially characterized by medical imaging.

Published
2012

17. Procedures for finite element mesh generation from medical imaging: application to the intervertebral disc

Author

Cortez, Sara Isabel Couto, Alves, J. L., and Universidade do Minho

Subjects
519.63, 616.7, 616-073
Abstract

Dissertação de mestrado integrado em Engenharia Biomédica, The paramount goal of this ‘half-year’ work is the development of a set of methodologies and procedures for the geometric modelling by a finite element (FE) mesh of the bio-structure of a motion segment (or functional spinal unit), i.e., two vertebrae and an intervertebral disc, from segmented medical images (processed from medical imaging). At an initial stage, a three-dimensional voxel-based geometric model of a goat motion segment was created from magnetic resonance imaging (MRI) data. An imaging processing software (ScanIP/Simplewire) was used for imaging segmentation (identification of different structures and tissues), both in images with lower (normal MRI) and higher (micro-MRI) resolutions. It shall be noticed that some soft-tissues, such as annulus fibrosus or nucleus pulposus, are very hard to isolate and identify given that the interface between them is not clearly defined. At the end of this stage, images with different resolutions allowed to generate different 3D voxel-based geometric models. Thereafter, a procedure for the FE mesh generation from the aforementioned voxelized data should be studied and applied. However, as the original geometry was only approximately known from real medical imaging, it was difficult to objectively quantify the quality of the FE meshing procedure and the accuracy between source geometry and target FE mesh. In order to overcome such difficulties, and due to the lack of quality of the available medical imaging, a “virtualization” procedure was developed to create a set of segmented 2D medical images from a well-defined geometry of a motion segment. The main idea was to create the conditions to quantify the quality and the accuracy of the developed FE meshing procedure, as well to study the effect of imaging resolution. Starting from the virtually generated 2D segmented images, a 3D voxel-based structure was achieved. Given that initial domains are now clearly defined, there is no need for further image processing. Then, a two-step FE mesh generation procedure (generation followed by simplification) allows to create an optimized tetrahedral FE mesh directly from 3D voxelized data. Finally, because the virtualization procedure allowed to know the initial geometry, one is able to objectively quantify the quality and the accuracy of the final simplified tetrahedral FE mesh, and thus to understand and quantify: a) the role of the medical image resolution on the FE geometrical reconstruction, b) the procedure and parameters of the FE mesh generation step, and c) the procedure and parameters of the FE mesh simplification step, and thus to give a clear contribution in the definition of the procedure for the FE mesh generation from medical imaging in case of an intervertebral disc., O objetivo fundamental deste trabalho de seis meses é o desenvolvimento de um conjunto de metodologias e procedimentos para a modelação geométrica, através de uma malha de elementos finitos (EF) de uma bio-estrutura de um motion segment (ou unidade funcional da coluna), ou seja, duas vértebras e um disco intervertebral, a partir de imagens médicas segmentadas (processadas a partir de imagiologia médica). Numa fase inicial, um modelo geométrico tridimensional baseado em voxels de um motion segment de uma cabra foi criado a partir de informação de imagens médicas de ressonância magnética (RM). Um software de processamento de imagem (ScanIp/Simplewire) foi usado para segmentação de imagens (identificação de diferentes estruturas e tecidos), em imagens de menor (RM normal) e maior (micro-RM) resolução. Deve ser referido que alguns tecidos moles, como o anel fibroso e o núcleo pulposo são muito difíceis de isolar e identificar, dado que as fronteiras destes não estão claramente definidas. No final desta etapa, as imagens com diferentes resoluções permitiram gerar diferentes modelos geométricos 3D baseados em voxels. Posteriormente, um procedimento para geração de malha de EF, a partir da informação voxelizada acima mencionada, deveria ser estudado e aplicado. No entanto, como a geometria original era aproximadamente conhecida a partir de imagens médicas reais, foi difícil quantificar objetivamente a qualidade do procedimento de geração de malha de EF e a precisão entre a geometria de origem e a malha de EF de destino. A fim de superar tais dificuldades, e devido à falta de qualidade de imagens médicas disponíveis, um procedimento de “virtualização” foi desenvolvido para criar um conjunto de imagens médicas 2D segmentadas a partir de uma geometria de um motion segment bem conhecida. A principal ideia foi criar as condições para quantificar a qualidade e a precisão do procedimento de geração de malha de EF desenvolvido, bem como estudar o efeito da resolução da imagem médica. A partir das imagens 2D segmentadas, geradas virtualmente, uma estrutura de voxels 3D pode ser conseguida. Dado que os domínios iniciais estão agora claramente definidos, não há necessidade de processamento de imagem adicional. Por conseguinte, um procedimento de geração de malha de EF de duas etapas (geração seguida por simplificação) permite criar uma malha de EF tetraédrica otimizada diretamente a partir de informação 3D voxelizada. Por fim, como o procedimento de virtualização permitiu conhecer a geometria inicial, é possível quantificar objetivamente a qualidade e exatidão da malha de EF tetraédrica final simplificada, e assim, compreender e quantificar: a) o papel da resolução da imagem médica na reconstrução geométrica de EF; b) o procedimento e os parâmetros da etapa de geração de malha de EF; c) o procedimento e os parâmetros da etapa de simplificação de malhas de EF, e assim, dar uma contribuição clara na definição do procedimento para a geração de malha de EF a partir de imagem médica, no caso de um disco intervertebral., European Project : NP Mimetic - Biomimetic Nano-Fiber Based Nucleus Pulposus Regeneration for the Treatment of Degenerative Disc Disease, funded by the European Commission under FP7 (grant NMP3-SL-2010-246351)

Published
2011

20. Using local ecological knowledge to improve large terrestrial mammal surveys, build local capacity and increase conservation opportunities.

Author

Camino, Micaela, Thompson, Jeffrey, Andrade, Laura, Cortez, Sara, Matteucci, Silvia D., and Altrichter, Mariana

Subjects
*LOCAL knowledge, *WILDLIFE monitoring, *MAMMAL conservation, *ENDANGERED species, *PILOT projects, *ZOOLOGICAL surveys, *WILDLIFE conservation
Abstract

Field information is essential for developing conservation actions, but standard methods for surveying wildlife are often inefficient in large, remote areas. Without efficient methods, surveying is difficult or even impossible. Consequently, some of the most threatened species and regions remain un- or under-surveyed, e.g. South American Chaco. Survey methods based on local ecological knowledge (LEK-methods) could be useful for surveying these areas and species. However, LEK-methods may be inaccurate and are rarely evaluated or compared to standard-methods. This is the first large-scale study evaluating the performance of two LEK-methods, and comparing it with the performance of standard-methods, for detecting three species of large terrestrial mammals. We used a locally-based survey (LBS) and interviews as LEK-methods, and transect and camera trapping as standard survey methods. We estimated the probability of detecting each species with each method, of having false-presences and their cost. We also quantitatively analysed the ability of LBS to build local capacity, focusing on conservation, research and working skills. We found that compared to standard-methods, LEK-methods increase detection probabilities of three species while providing accurate information. LBSs are more expensive than interviews but improve local capacities, raising the chances of successful implementation of community-based conservation programmes. Interviews are optimal for rapid assessments and can be useful for wildlife monitoring. Before using LEK-methods, we recommend pilot studies to determine estimators´ variability. Overall, this study shows that LEK-based methods can be efficient and accurate for detecting large mammals in remote areas. Furthermore, LEK-methods can help develop legitimate conservation initiatives. The probability of detecting a species depends on the species characteristics and on the methods used in the survey. For three species with different biological and ecological characteristics -white-lipped, collared or chacoan peccaries (Tayassu pecari, Pecari tajacu and Parachoerus wagneri)-, locally-based surveys provided the highest detection probabilities. The probability of detecting these species with the locally-based survey and interviews to hunters are higher than with standard-methods. The season (rainy/dry) was differentiated when estimating white-lipped peccary's detection probabilities because this factor had a significant effect on estimations. Unlabelled Image • LEK increases efficiency and accuracy of large terrestrial mammal surveys. • Locally-based surveys contribute to build local capacity. • LEK-methods help develop legitimate, successful conservation actions. • Locally-based surveys are better for wildlife monitoring than for rapid assessments. • Interviews are optimal for rapid assessments but respondents must be qualified. [ABSTRACT FROM AUTHOR]

Published
2020
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21. NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics.

Author

Rosa CAD, Ribeiro BR, Bejarano V, Puertas FH, Bocchiglieri A, Barbosa ALDS, Chiarello AG, Paglia AP, Pereira AA, Moreira AFS, Souza AC, Pellegrin A, Gatica A, Medeiro AZ, Pereira AD, Braz AG, Yanosky A, Valenzuela AEJ, Bertassoni A, Prado ADSVD, Nava AFD, Rocha A, Bovo AAA, Bager A, Cravino A, Pires ADS, Martensen AC, Filippini A, Percequillo AR, Vogliotti A, Antunes AZ, Leite de Oliveira AC, da Silva de Oliveira AJ, Devlin A, de Paula A, Ferreira AS, García-Olaechea A, Subalusky A, Sánchez A, de Aquino ACMM, Srbek-Araujo AC, Paldês Gonçales A, Araújo ACL, Gozzi AC, Ochoa AC, Mendes de Oliveira AC, Lacerda ACR, Francisco AK, Paschoal AMO, Gomes APN, Potrich AP, Olímpio APM, Rojas A, Meiga AYY, Jácomo ATA, Calaça AM, Feijó A, Pagoto A, Borja Miranda A, Chein Alonso A, Barreto-Lima AF, Lanna A, Luza AL, Camilo AR, Tavares A, Nunes AV, Kindel A, de Miguel A, Gatti A, Nobre AB, Campêlo ADC, Albuquerque ACF, de la Torre A, Mangione A, Mendes Pontes AR, Fernandes AS, Felicio ALA, Ferreguetti AC, Marcili A, Piratelli AJ, Nascimento AGSD, Banhos Dos Santos Á, Rosa BF, Cezila BA, de Thoisy B, Ingberman B, Köhler B, Morais BC, Gómez-Valencia B, Bertagni de Camargo B, Bezerra BM, Tamasauskas B, Parahyba Campos BAT, Kubiak BB, Saranholi BH, Nakagawa BK, Leles BP, Lim BK, Pereira Mendes C, Islas CA, Aoki C, Cantagallo Devids C, Figueiredo C, Abreu CMG, Silva Oliveira CR, Cassano CR, Lugarini C, Caputo C, Gestich CC, Tedesco CD, Vera Y Conde CF, Hegel CGZ, Kasper CB, De Angelo C, Grelle CEV, Fragoso CE, Esbérard CEL, Rocha CFD, Verona CE, Salvador CH, Vieira CL, Abrahão CR, Brocardo CR, Fieker CZ, Braga C, Sánchez Lalinde C, Bueno C, Ikuta CY, Luna CLB, Cestari C, Del Vechio Koike C, Knogge C, Anderson CB, Hurtado CM, Ferreira Antunes de Oliveira C, Tellaeche C, Cesário CS, Costa CG, Kanda CZ, Costa SA, Seixas CS, Trinca CT, López-Fuerte CF, da Cunha CJ, Doutel Ribas C, Santos CC, Buscariol D, Carreira D, Nascimento DCD, Carvalho DR, Ferraz DDS, Galiano D, Homem DH, Jesús-Espinosa D, Bôlla DAS, Moreno DJ, Moreira DO, Ramos DL, de Amorim DA, Barros-Battesti DM, Lopez DE, Tavares DC, Post DM, Couto DR, Patrocínio DN, Carvalho DLKP, Silva DA, Córdoba D, Queirolo D, Varela D, de Oliveira DAG, Casanova DC, Dias DM, Machado da Silva D, Barbier E, Rivadeneira EF, Alexandrino E, Carrano E, Santos EM, Venticinque EM, Hernández-Pérez E, Casazza EDF, Anderson EP, Fraga EDC, de Lima EF, D'Bastiani E, Vieira EM, Guijosa-Guadarrama E, González EM, Maggiorini EV, Aguiar EFS, Martínez-Nambo ED, Castro ÉP, de la Peña-Cuéllar E, Pedó E, Melo FCSA, Rocha FL, Fonseca FL, Girardi F, Melo FR, Roque FO, Keesen Ferreira F, Peters FB, Moreli Fantacini F, Pedrosa F, Pessoa da Silva F, Vélez-García F, Abra FD, de Azevedo FC, Guedes da Silva F, Neri FM, Teixeira FZ, Fernandez FADS, Carvalho F, Passos FC, Jacinavicius FC, Ferreira F, Pinho FF, Gonçalves F, Ibanez Martins F, Lima F, Contreras-Moreno FM, Ribeiro FS, Tortato F, Patel FM, Caruso F, Tirelli FP, Rodrigues FHG, Ubaid FK, Palmeira FBL, Grotta Neto F, Gabriel FH, de Souza FL, Costa FEDVD, de Aguiar GL, Lemos FG, Magezi GS, Panigai GFVD, Hofmann GS, Heliodoro G, Rosa Graviola G, Beca G, Andrade GR, Jiménez Romero G, Duarte GT, Melo GL, Dierings GL, Sabino-Santos G Jr, de Oliveira GL, Santana GG, Ciocheti G, Zanirato GL, Alves GB, Batista GO, Behling GM, Ferreira GB, da Rocha GC, Lessa G, Mourão G, Maras GA, Toledo GADC, Gonsioroski G, Canale GR, Schuchmann KL, Sebastião H, Alves do Prado H, Bergallo HG, Secco HKC, Roig HL, Rajão H, Carlos HSA, Duarte HOB, Ermenegildo H, Pena HFJ, Entringer Júnior H, Paulino Neto HF, Lemos HM, Del Castillo H, Fernandes-Ferreira H, Coitiño Banquero HI, Roesler I, Ribeiro IK, Coelho IP, Lima IMS, Bechara IM, Lermen IS, Mella Méndez I, Schuck G, Esperandio IB, Silva IO, Mourthe I, Oliveira I, Bernardi IP, Miller JR, Marinho-Filho J, Zocche JJ, Russell JC, Seibert JB, Hinojosa J, Vitule JRS, Thompson JJ, Silva JCR, Gouvea JA, Santos JP, Falcão JCF, Castro-Prieto J, Ferreira JP, Pincheira-Ulbrich J, Nodari JZ, Zecchini Gebin JC, Giovanelli JGR, Miranda JMD, Souza-Alves JP, Marins JRGA, Costa JF, Sponchiado J, de Souza JL, Gallo JA, Cherem JJ, Cordeiro JLP, Duarte JMB, Dantas JO, de Matos JR, Pires JSR, Martínez Lanfranco JA, de la Cruz Godoy JC, Rudolf JC, Parrish JFR, Tellarini JF, Peña-Mondragón JL, Arrabal JP, Reppucci J, Ruiz-Esparza J, Beduschi J, Oshima JEF, Ribeiro JF, Almeida Rocha JM, Ferreira Neto JS, Silveira Dos Santos J, Pereira-Ribeiro J, Zanoni JB, Bogoni JA, Ferreira JR, Bicca-Marques JC, Chacón Pacheco JJ, Scarascia PO, Guidoni-Martins KG, Burs K, Ferraz KMPMB, Pisciotta KR, Silva KVKA, Juarez KM, de la Cruz-Félix K, de Morais KDR, Candelária LP, Fornitano L, Bailey LL, Gonçalves LO, Fasola L, Nova León LJ, de Andrade LR, Marques LO, Macedo L, Moreira LS, Silveira L, Oliveira LC, da Silva LH, Jerusalinsky L, La Serra L, Marques Costa L, Sartorello LR, Munhoes LP, Oliveira-Silva LRB, de Pina LF, Bonjorne L, Rampim LE, Sales LP, Gonçalves da Silva L, Quintilham LLT, Perillo LN, Rodríguez-Planes LI, Martín L, Araújo LS, Tiepolo LM, Zago Silva L, García Loaiza LM, Querido LCA, da Silva LF, La Sala LF, Bopp LT, Hufnagel L, Oliveira LFB, Oliveira-Santos LGR, Lyra LH, Guimarães LN, Jimenez Segura LF, de Sousa LC, Möcklinghoff L, Guichón ML, de la Maza J, Barrios-Garcia MN, Talamoni SA, Severo MM, Martins MZA, Oliveira MA, Figuerêdo Duarte Moraes M, Lima MGM, Soares Pinheiro M, Pônzio MDC, Guerreiro M, Cervini M, da Silva M, Oliveira MJR, Magioli M, Passamani M, Silva de Almeida M, Amaku M, Leite de Oliveira M, Tortato MA, Melo MA, Coutinho ME, Dantas Santos MP, Vieira MV, Andrade MA, Barros MC, Rosario MCFD, Domit MDADS, Fernandes MEA, Iezzi ME, do Nascimento MHS, Andrade-Núñez MJ, Lorini ML, Morini MSC, Nagy-Reis MB, Landis MB, Vale MM, Xavier MS, Kaizer MC, Baptiste MP, Bergel MM, Borgnia M, Barros MAS, Lima da Silva M, Favarini MO, Sales Munerato M, Zaluar MT, Winter M, Xavier da Silva M, Zanin M, Marques MI, Haberfeld MB, Di Bitetti MS, Galliez M, Alvarez MR, Malerba M, Rivero M, Melo Dias M, de Oliveira MY, Dos Reis MG, Corrêa MRJ, Graipel ME, Godoi MN, Núñez-Regueiro MM, Moura MO, Orsi ML, Galvão da Silva MA, Sanvicente Lopez M, Benedetti MA, Beltrão MG, Camino M, Faria MB, Miretzki M, Luiz MR, Perine M, Monteiro MCM, Alves-Eigenheer M, Perilli MLL, da Silva MA, Marini MÂ, Silva Pereira M, de Freitas Junior MC, Cossa N, Denkiewicz NM, Tôrres NM, Olifiers N, de Albuquerque NM, Canassa NF, Detogne N, Gurgel Filho N, Seoane NF, da Rosa Oliveira N, Megale N, Pasqualotto N, Cáceres NC, Peroni N, Zanella N, Pays O, Arimoro OAS, Acevedo-Charry O, de Almeida Curi NH, Pinha PRS, Perovic P, Gonçalves PR, Santos PM, Brennand PGG, Kerches Rogeri P, Rosas Ribeiro P, da Rocha PA, de Lázari PR, Pedreira PA, Pinheiro PF, Lira PK, Ferreira PM, Martin PS, Antas PTZ, Marinho PH, Ruffino PHP, Camargo PHSA, Landgref Filho P, Mangini PR, Farias P, Cordeiro-Estrela P, de Faria Peres PH, Galetti PM Jr, Ramírez-Bautista P, Maués PCRA, Renaud PC, Sartorello R, Barros PA, Lombardi PM, Bessa R, Arroyo-Gerala P, de Souza RCC, Zenni RD, Flores Peredo R, Hoogesteijn R, Loyola R, Alves RSC, Rodarte RRP, Silva RL, de Oliveira R, Beltrão-Mendes R, Alencar RM, da Silva RC, Pedroso R, Sampaio RF, Ribeiro RLA, Pardini R, Twardowsky Ramalho Bonikowski R, Pagotto RV, Dias RA, Bassini-Silva R, Corassa Arrais R, Sampaio R, de Cassia Bianchi R, Paolino RM, Fusco-Costa R, Trovati RG, Espíndola Hack RO, Mauro RA, Nobre RA, Gessulli RD, León Pérez R, Massara RL, Fróes da Silva RM, de Paula RC, da Cunha RGT, Costa RT, Marques RV, Morato RG, Bovendorp RS, Dornas RADP, Andrade RS, Siciliano S, Guaragni SA, Rolim SG, Astete S, Cavalcanti S, Hartz SM, Carvalho S, Cortez S, Silvestre de Sousa SM, Ballari SA, Ramos Lima S, Cirignoli S, García-R S, Bazilio S, Solari Torres S, Back Franco S, Martins SR, de Bustos S, Age SG, Ferrari SF, Francisco TM, Micheletti T, Godim TMDS, Luiz TG, Ochotorena de Freitas TR, Rodrigues TF, Piovezan U, Barcos UC, Onofrio VC, Martin-Albarracin VL, Towns V, Araújo VC, Kanaan V, Daga VS, Boere V, de Araujo VPG, Benitez VV, Leandro-Silva V, Geraldi VC, Alberici V, Bastazini VAG, Gasparotto VPO, Orsini VS, da Silva VS, Rojas Bonzi V, Pereira VJA, Layme VMG, Duarte da Silva VH, Tomas WM, Moreira TA, Martins WP, de Moraes Pires WM, Hannibal W, Dáttilo W, Mottin V, Endo W, Bercê W, Carvalho WD, Magnusson W, Akkawi P, Di Blanco Y, Amaral PR, Ramos YGC, Rodríguez-Calderón YG, Mendes YR, Ribeiro YGG, Campos Z, Galetti M, and Ribeiro MC

Subjects
Animals, Argentina, Biodiversity, Cattle, Chile, Dogs, Florida, Mexico, Introduced Species, Mammals
Abstract

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data., (© 2020 The Authors. Ecology © 2020 The Ecological Society of America.)

Published
2020
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