Franceschi Ingridi Camboim, Dornas Rubem Augusto da Paixão, Lermen Isabel Salgueiro, Coelho Artur Vicente Pfeifer, Vilas Boas Ademir Henrique, Chiarello Adriano Garcia, Paglia Adriano Pereira, de Souza Agnis Cristiane, Borsekowsky Alana Rafaela, Rocha Alessandro, Bager Alex, de Souza Alexander Zaidan, Lopes Alexandre Martins Costa, de Moura Aloysio Souza, Ferreira Aluane Silva, García-Olaechea Alvaro, Delciellos Ana Cláudia, Bacellar Ana Elisa de Faria, Campelo Ana Kellen Nogueira, Paschoal Ana Maria Oliveira, Rolim Anderson Claudino, da Silva André Luiz Ferreira, Lanna Andre Monnerat, da Silva André Pereira, Guimarães Andresa, Cardoso Ângela, Cassol Angelica Soligo, da Costa-Pinto Anna Ludmilla, do Nascimento Ariel Guilherme Santos, Fernandes Arthur Soares, Clyvia Aryanne, Santos Aureo Banhos Dos, Lima-Silva Barbara, Beisiegel Beatriz de Mello, Luciano Beatriz Fernandes Lima, Leopoldo Bernardo de Faria, Krobel Bruna Nunes, Kubiak Bruno Busnello, Saranholi Bruno Henrique, Correa Bruno Senna, Sant Anna Teixeira Caio, Ayroza Camila Rezende, Cassano Camila Righetto, Benitez-Riveros Camilo, Gestich Carla Cristina, Tedesco Carla Denise, Gheler-Costa Carla, Hegel Carla Grasiele Zanin, Evangelista Junior Carlito da Silva, Ferreira Carlos Eduardo Morando Faria, Grelle Carlos Eduardo Viveiros, Esteves Carolina Franco, Espinosa Caroline da Costa, Leuchtenberger Caroline, Sanchéz-Lalinde Catalina, Machado Cauanne Iglesias Campos, Andreazzi Cecilia, Bueno Cecília, Cronemberger de Faria Cecilia, Novaes Claudio, Widmer Cynthia Elisa, Santos Cyntia Cavalcante, Ferraz Daniel da Silva, Galiano Daniel, Bôlla Daniela Aparecida Savariz, Behs Daniela, Rodrigues Daniele Pereira, de Melo Danielle Picão, Ramos Déborah Maria Soares, de Mattia Denise Lidório, Pavei Diego Dias, Loretto Diogo, Huning Douglas da Silva, Dias Douglas de Matos, Paetzhold Éder Ricardo, Rios Elaine, Setz Eleonore Zulnara Freire, Cazetta Eliana, Cafofo Silva Emanuel Giovani, Pasa Emanuelle, Saito Erica Naomi, de Aguiar Erick Francisco Silva, Castro Érika Paula, Viveiros de Castro Ernesto Bastos, Pedó Ezequiel, Pereira Fabiane de Aguiar, Bolzan Fábio, Roque Fábio de Oliveira, Mazim Fábio Dias, Comin Fábio Henrique, Maffei Fábio, Peters Felipe Bortolotto, Fantacini Felipe Moreli, da Silva Felipe Pessoa, Machado Felipe Santana, Vélez-Garcia Felipe, Lage Fernanda Stussi Duarte, Perini Fernando Araújo, Passos Fernando Camargo, Carvalho Fernando, de Azevedo Fernando Cesar Cascelli, Ferreira Fernando, de Pinho Fernando Ferreira, Chaves Flávia Guimarães, Miranda Flavia Regina, Rodrigues Flavio Henrique Guimarães, Ubaid Flávio Kulaif, Gabriel Francisco Homem, de Souza Franco Leandro, de Oliveira Fred Victor, Cupolillo Gabriel, Moreira Gabriela de Araújo Pires, Mette Gabriela, Duarte Gabriela Teixeira, Beca Gabrielle, Corso Gilberto, Perbiche-Neves Gilmar, Souto Glauber Henrique Borges de Oliveira, Vilarroel Glenda Jéssica da Silva, Batista Graziele O, Ferreira Guilherme Braga, Toledo Gustavo Alves da Costa, Senger Gustavo, Bergallo Helena de Godoy, Dos Santos Hellen Cristina Pinheiro, Gazola Humberto Angelo, Melo Isabel, Brack Ismael Verrastro, Veríssimo Iuri, Viana Ivan Réus, Laurentino Izabela Costa, Diehl Jaime Luis, Zocche Jairo José, Martins-Silva Jimi, Just João Paulo Gava, Cherem Jorge José, Nascimento Jorge Luiz, Marinho Jorge Reppold, Dantas José Oliveira, de Matos Jose Roberto, Pires José Salatiel Rodrigues, Cerveira Josi Fernanda, Ruiz-Esparza Juan, da Silva Juliana Paulo, Bogoni Juliano André, Molina Karina Theodoro, Pereira Karla Dayane de Lima, Ceron Karoline, de Vleeschouwer Kristel, Lautenschlager Laís, Bailey Larissa, Fornitano Larissa, Rampim Lilian Elaine, Sforza Lorena, Bissa Luan Gonçalves, Santucci Luca Mattos, da Silva Lucas Gonçalves, Perillo Lucas Neves, Correa Lucas Ribeiro, Hufnagel Ludmila, Alberti Luis Fernando, Recalde Mello Luis Jose, Bernardo Luis Renato Rezende, Oliveira-Santos Luiz Gustavo Rodrigues, Guimarães Luiza Neves, Benchimol Maíra, Twardowschy Manuela Catharina, Ferreira-Riveros Marcela, da Silva Marcelo, Jardim Márcia Maria de Assis, Fontes Marco Aurélio Leite, Tortato Marcos Adriano, do Nascimento Marcos Tadeu, Sekiama Margareth Lumy, Nascimento-Costa Maria Clara, Dos Santos Maria Ester Bueno, Morini Maria Santina de Castro, Nagy-Reis Mariana Baldy, Kaizer Mariane da Cruz, Sant'Anna Mariano José Ribeiro da Silva, Hartmann Marilia Teresinha, Favarini Marina Ochoa, Olivo Marina Oliveira, Montes Martín Alejandro, Alvaréz Martin Roberto Del Valle, Haddad Matheus Feldstein, Costa Maurício Djalles, Graipel Maurício Eduardo, Konzen Mauricio Quoos, Galetti Mauro, Almeida Meyline de Oliveira Souza, Faria Michel Barros, Luiz Micheli Ribeiro, Baptista Michelle Noronha da Matta, Marini Miguel Ângelo, Ribeiro Milton Cezar, Olifiers Natalie, de Albuquerque Natasha Moraes, Cantero Nicolás, Peroni Nivaldo, Zanella Noeli, Mendonça-Furtado Olívia, Pays Olivier, Ferretti Orlando Ednei, Rocha-Barbosa Oscar, Santos Paloma Marques, de Farias Patrícia Menegaz, da Rocha Patrício Adriano, Colas-Rosas Paul François, Ribeiro-Souza Paula, Ferracioli Paula, Hartmann Paulo Afonso, Antas Paulo de Tarso Zuquim, Ribeiro Paulo, Tomasi Sarti Paulo, Mônico Paulo Ivo, de Castilho Pedro Volkmer, Pereira Peônia Brito de Moraes, Crawshaw Peter Gransden, Renaud Pierre-Cyril, Romagna Rafael Spilere, de Sousa Rafael Turíbio Moraes, Spagnol Raíssa Soares, Beltrão-Mendes Raone, Mariano Ravi Fernandes, Rocha Renata Reinoso, Sousa-Lima Renata, Pagotto Renata Valls, de Faria Rhayssa Terra, Arrais Ricardo Corassa, Moratelli Ricardo, Sartorello Ricardo, Bianchi Rita de Cassia, Guimarães Roberto de Carvalho, Massara Rodrigo Lima, Costa Romulo Theodoro, Marques Rosane Vera, Nunes Ruan Márcio Ruas, Hartz Sandra Maria, Silvestre de Sousa Saulo Meneses, Lima Saulo Ramos, Barbosa Sergio Lutz, Godoy Silvia Neri, Ferrari Stephen Francis, de Araújo-Piovezan Talita Guimarães, Góes Talita Laura, Trigo Tatiane Campos, de Freitas Thales R O, Maccarini Thiago Bernardes, de Castro Thiago Marcial, Bella Thiago Ribas, de Oliveira Junior Tonny Marques, Cunha Uslaine Maciel, Kanaan Vanessa Tavares, Pfannerstill Vera, Pimentel Victor Siqueira, Picinatto Filho Vilmar, Alves Vinícius Nunes, Rojas-Bonzi Viviana, Mottin Viviane, Rocha Vlamir José, Kindel Andreas, Coelho Igor Pfeifer
Núcleo de Ecologia de Estradas e Ferrovias (NERF), Departamento de Ecologia, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Programa de Pós-Graduação em Ecologia, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Ecology. 2024 May;105(5):e4298. doi: 10.1002/ecy.4298. Epub 2024 Apr 12.
Camera traps became the main observational method of a myriad of species over large areas. Data sets from camera traps can be used to describe the patterns and monitor the occupancy, abundance, and richness of wildlife, essential information for conservation in times of rapid climate and land-cover changes. Habitat loss and poaching are responsible for historical population losses of mammals in the Atlantic Forest biodiversity hotspot, especially for medium to large-sized species. Here we present a data set from camera trap surveys of medium to large-sized native mammals (>1 kg) across the Atlantic Forest. We compiled data from 5380 ground-level camera trap deployments in 3046 locations, from 2004 to 2020, resulting in 43,068 records of 58 species. These data add to existing data sets of mammals in the Atlantic Forest by including dates of camera operation needed for analyses dealing with imperfect detection. We also included, when available, information on important predictors of detection, namely the camera brand and model, use of bait, and obstruction of camera viewshed that can be measured from example pictures at each camera location. Besides its application in studies on the patterns and mechanisms behind occupancy, relative abundance, richness, and detection, the data set presented here can be used to study species' daily activity patterns, activity levels, and spatiotemporal interactions between species. Moreover, data can be used combined with other data sources in the multiple and expanding uses of integrated population modeling. An R script is available to view summaries of the data set. We expect that this data set will be used to advance the knowledge of mammal assemblages and to inform evidence-based solutions for the conservation of the Atlantic Forest. The data are not copyright restricted; please cite this paper when using the data.
相机陷阱已成为大面积监测众多物种的主要观测方法。相机陷阱数据集可用于描述野生动物的分布模式，并监测其占有率、丰度和丰富度，这些信息对于在气候和土地覆盖快速变化时期的保护工作至关重要。栖息地丧失和偷猎是导致大西洋森林生物多样性热点地区哺乳动物历史种群数量减少的原因，尤其是对中大型物种而言。在此，我们展示了一项针对大西洋森林中大型本土哺乳动物（体重>1千克）的相机陷阱调查数据集。我们汇总了2004年至2020年期间在3046个地点进行的5380次地面相机陷阱部署所获得的数据，共得到58个物种的43068条记录。这些数据通过纳入分析不完美检测所需的相机运行日期，补充了大西洋森林现有哺乳动物数据集。我们还在可行的情况下，纳入了有关检测重要预测因子的信息，即相机品牌和型号、诱饵使用情况以及相机视场的遮挡情况，这些可从每个相机位置的示例图片中测量得出。除了应用于研究占有率、相对丰度、丰富度和检测背后的模式和机制外，这里展示的数据集还可用于研究物种的日常活动模式、活动水平以及物种间的时空相互作用。此外，该数据可与其他数据源结合，用于综合种群建模的多种且不断扩展的用途。提供了一个R脚本以查看数据集的摘要。我们期望该数据集将用于增进对哺乳动物群落的了解，并为大西洋森林保护提供基于证据的解决方案。这些数据不受版权限制；使用数据时请引用本文。
