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Camera trap surveys of Atlantic Forest mammals: A data set for analyses considering imperfect detection (2004–2020)
Ecology ( IF 4.8 ) Pub Date : 2024-04-13 , DOI: 10.1002/ecy.4298
Ingridi Camboim Franceschi 1, 2 , Rubem Augusto da Paixão Dornas 1, 3 , Isabel Salgueiro Lermen 1, 2 , Artur Vicente Pfeifer Coelho 4 , Ademir Henrique Vilas Boas 5 , Adriano Garcia Chiarello 6 , Adriano Pereira Paglia 7 , Agnis Cristiane de Souza 8 , Alana Rafaela Borsekowsky 9 , Alessandro Rocha 10, 11 , Alex Bager 12 , Alexander Zaidan de Souza 13 , Alexandre Martins Costa Lopes 14 , Aloysio Souza de Moura 15 , Aluane Silva Ferreira 16 , Alvaro García‐Olaechea 16, 17 , Ana Cláudia Delciellos 18 , Ana Elisa de Faria Bacellar 19 , Ana Kellen Nogueira Campelo 20, 21 , Ana Maria Oliveira Paschoal 7 , Anderson Claudino Rolim 22 , André Luiz Ferreira da Silva 23, 24 , Andre Monnerat Lanna 25, 26 , André Pereira da Silva 27 , Andresa Guimarães 28 , Ângela Cardoso 29 , Angelica Soligo Cassol 30 , Anna Ludmilla da Costa‐Pinto 31, 32 , Ariel Guilherme Santos do Nascimento 33 , Arthur Soares Fernandes 7 , Aryanne Clyvia 34 , Aureo Banhos dos Santos 35 , Barbara Lima‐Silva 29 , Beatriz de Mello Beisiegel 36, 37 , Beatriz Fernandes Lima Luciano 38, 39 , Bernardo de Faria Leopoldo 40 , Bruna Nunes Krobel 29 , Bruno Busnello Kubiak 41 , Bruno Henrique Saranholi 42 , Bruno Senna Correa 43 , Caio Sant Anna Teixeira 44 , Camila Rezende Ayroza 45 , Camila Righetto Cassano 16 , Camilo Benitez‐Riveros 46, 47 , Carla Cristina Gestich 42 , Carla Denise Tedesco 48 , Carla Gheler‐Costa 49, 50 , Carla Grasiele Zanin Hegel 51 , Carlito da Silva Evangelista Junior 20, 21 , Carlos Eduardo Morando Faria Ferreira 52 , Carlos Eduardo Viveiros Grelle 53, 54 , Carolina Franco Esteves 55 , Caroline da Costa Espinosa 56 , Caroline Leuchtenberger 9 , Catalina Sanchéz‐Lalinde 57, 58 , Cauanne Iglesias Campos Machado 59 , Cecilia Andreazzi 60 , Cecília Bueno 61 , Cecilia Cronemberger de Faria 62, 63 , Claudio Novaes 34 , Cynthia Elisa Widmer 64 , Cyntia Cavalcante Santos 65, 66 , Daniel da Silva Ferraz 34, 52 , Daniel Galiano 67 , Daniela Aparecida Savariz Bôlla 68 , Daniela Behs 8 , Daniele Pereira Rodrigues 69 , Danielle Picão de Melo 27 , Déborah Maria Soares Ramos 70 , Denise Lidório de Mattia 8 , Diego Dias Pavei 8 , Diogo Loretto 71 , Douglas da Silva Huning 48 , Douglas de Matos Dias 72 , Éder Ricardo Paetzhold 73, 74 , Elaine Rios 16 , Eleonore Zulnara Freire Setz 75 , Eliana Cazetta 16 , Emanuel Giovani Cafofo Silva 28 , Emanuelle Pasa 76 , Erica Naomi Saito 2, 77 , Erick Francisco Silva de Aguiar 7 , Érika Paula Castro 12, 78 , Ernesto Bastos Viveiros de Castro 62, 79 , Ezequiel Pedó 2, 80 , Fabiane de Aguiar Pereira 62, 81 , Fábio Bolzan 82, 83 , Fábio de Oliveira Roque 82 , Fábio Dias Mazim 55 , Fábio Henrique Comin 49, 84 , Fábio Maffei 85 , Felipe Bortolotto Peters 55 , Felipe Moreli Fantacini 30, 86 , Felipe Pessoa da Silva 87, 88 , Felipe Santana Machado 15, 88, 89, 90 , Felipe Vélez‐Garcia 57, 58 , Fernanda Stussi Duarte Lage 91 , Fernando Araújo Perini 92 , Fernando Camargo Passos 24 , Fernando Carvalho 38, 39 , Fernando Cesar Cascelli de Azevedo 64 , Fernando Ferreira 93 , Fernando Ferreira de Pinho 94, 95 , Flávia Guimarães Chaves 28 , Flavia Regina Miranda 14, 96 , Flavio Henrique Guimarães Rodrigues 97 , Flávio Kulaif Ubaid 98 , Francisco Homem Gabriel 33, 52 , Franco Leandro de Souza 99 , Fred Victor de Oliveira 92 , Gabriel Cupolillo 5, 100 , Gabriela de Araújo Pires Moreira 7 , Gabriela Mette 101 , Gabriela Teixeira Duarte 7, 94 , Gabrielle Beca 10, 102 , Gilberto Corso 103, 104 , Gilmar Perbiche‐Neves 27 , Glauber Henrique Borges de Oliveira Souto 22, 105 , Glenda Jéssica da Silva Vilarroel 59 , Graziele O. Batista 80, 106 , Guilherme Braga Ferreira 95, 107 , Gustavo Alves da Costa Toledo 108 , Gustavo Senger 9 , Helena de Godoy Bergallo 109 , Hellen Cristina Pinheiro dos Santos 110 , Humberto Angelo Gazola 111 , Isabel Melo 112 , Ismael Verrastro Brack 2, 113 , Iuri Veríssimo 5, 114 , Ivan Réus Viana 8 , Izabela Costa Laurentino 103, 104 , Jaime Luis Diehl 8 , Jairo José Zocche 37, 38 , Jimi Martins‐Silva 115 , João Paulo Gava Just 8 , Jorge José Cherem 116, 117 , Jorge Luiz Nascimento 62 , Jorge Reppold Marinho 118 , José Oliveira Dantas 119 , Jose Roberto de Matos 8 , José Salatiel Rodrigues Pires 120 , Josi Fernanda Cerveira 121, 122 , Juan Ruiz‐Esparza 123 , Juliana Paulo da Silva 28 , Juliano André Bogoni 112 , Karina Theodoro Molina 14, 124 , Karla Dayane de Lima Pereira 125 , Karoline Ceron 37, 112 , Kristel de Vleeschouwer 126 , Laís Lautenschlager 127, 128 , Larissa Bailey 129 , Larissa Fornitano 130, 131 , Lilian Elaine Rampim 132 , Lorena Sforza 46, 47 , Luan Gonçalves Bissa 8 , Luca Mattos Santucci 29 , Lucas Gonçalves da Silva 70 , Lucas Neves Perillo 94, 133 , Lucas Ribeiro Correa 134 , Ludmila Hufnagel 7 , Luis Fernando Alberti 8 , Luis Jose Recalde Mello 135 , Luis Renato Rezende Bernardo 136 , Luiz Gustavo Rodrigues Oliveira‐Santos 99 , Luiza Neves Guimarães 7 , Maíra Benchimol 16 , Manuela Catharina Twardowschy 24, 137 , Marcela Ferreira‐Riveros 46, 47, 138 , Marcelo da Silva 22, 139 , Márcia Maria de Assis Jardim 59, 140 , Marco Aurélio Leite Fontes 15 , Marcos Adriano Tortato 112, 116, 117 , Marcos Tadeu do Nascimento 141 , Margareth Lumy Sekiama 27 , Maria Clara Nascimento‐Costa 92 , Maria Ester Bueno dos Santos 142 , Maria Santina de Castro Morini 20 , Mariana Baldy Nagy‐Reis 143 , Mariane da Cruz Kaizer 34, 144 , Mariano José Ribeiro da Silva Sant'Anna 145, 146 , Marilia Teresinha Hartmann 69 , Marina Ochoa Favarini 55 , Marina Oliveira Olivo 8 , Martín Alejandro Montes 70 , Martin Roberto del Valle Alvaréz 57 , Matheus Feldstein Haddad 30, 147, 148 , Maurício Djalles Costa 149 , Maurício Eduardo Graipel 29, 117 , Mauricio Quoos Konzen 69 , Mauro Galetti 10, 150 , Meyline de Oliveira Souza Almeida 119 , Michel Barros Faria 33, 52 , Micheli Ribeiro Luiz 151 , Michelle Noronha da Matta Baptista 28 , Miguel Ângelo Marini 152 , Milton Cezar Ribeiro 10 , Natalie Olifiers 61 , Natasha Moraes de Albuquerque 153 , Nicolás Cantero 46 , Nivaldo Peroni 106, 120 , Noeli Zanella 48 , Olívia Mendonça‐Furtado 28 , Olivier Pays 66 , Orlando Ednei Ferretti 154 , Oscar Rocha‐Barbosa 155 , Paloma Marques Santos 7, 10 , Patrícia Menegaz de Farias 156, 157 , Patrício Adriano da Rocha 158 , Paul François Colas‐Rosas 159 , Paula Ribeiro‐Souza 160, 161 , Paula Ferracioli 162 , Paulo Afonso Hartmann 69 , Paulo de Tarso Zuquim Antas 163 , Paulo Ribeiro 57, 164, 165 , Paulo Tomasi Sarti 166, 167 , Paulo Ivo Mônico 8 , Pedro Volkmer de Castilho 168 , Peônia Brito de Moraes Pereira 169 , Peter Gransden Crawshaw 170 , Pierre‐Cyril Renaud 66 , Rafael Spilere Romagna 8 , Rafael Turíbio Moraes de Sousa 103, 104 , Raíssa Soares Spagnol 118 , Raone Beltrão‐Mendes 153 , Ravi Fernandes Mariano 15 , Renata Reinoso Rocha 171 , Renata Sousa‐Lima 104, 172 , Renata Valls Pagotto 115 , Rhayssa Terra de Faria 75 , Ricardo Corassa Arrais 173 , Ricardo Moratelli 5 , Ricardo Sartorello 20, 21 , Rita de Cassia Bianchi 131 , Roberto de Carvalho Guimarães 174 , Rodrigo Lima Massara 7 , Romulo Theodoro Costa 130, 131 , Rosane Vera Marques 175 , Ruan Márcio Ruas Nunes 52 , Sandra Maria Hartz 2 , Saulo Meneses Silvestre de Sousa 176 , Saulo Ramos Lima 163 , Sergio Lutz Barbosa 177 , Silvia Neri Godoy 178 , Stephen Francis Ferrari 72, 153 , Talita Guimarães de Araújo‐Piovezan 119 , Talita Laura Góes 160, 179 , Tatiane Campos Trigo 59, 140 , Thales R. O. de Freitas 41 , Thiago Bernardes Maccarini 180 , Thiago Marcial de Castro 8 , Thiago Ribas Bella 181 , Tonny Marques de Oliveira Junior 182 , Uslaine Maciel Cunha 52 , Vanessa Tavares Kanaan 30, 113 , Vera Pfannerstill 183, 184 , Victor Siqueira Pimentel 100, 185 , Vilmar Picinatto Filho 186 , Vinícius Nunes Alves 187 , Viviana Rojas‐Bonzi 47, 188 , Viviane Mottin 37, 38 , Vlamir José Rocha 134 , Andreas Kindel 1, 2 , Igor Pfeifer Coelho 1
Affiliation  

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.

中文翻译:

大西洋森林哺乳动物的相机陷阱调查:考虑不完美检测的分析数据集(2004-2020)

相机陷阱成为大面积观察无数物种的主要方法。相机陷阱的数据集可用于描述模式并监测野生动物的占有率、数量和丰富度,这是气候和土地覆盖快速变化时期保护的重要信息。栖息地丧失和偷猎是造成大西洋森林生物多样性热点地区哺乳动物数量历史性减少的原因,尤其是中型到大型物种。在这里,我们展示了对大西洋森林中型到大型本土哺乳动物(> 1 公斤)进行相机陷阱调查的数据集。我们收集了 2004 年至 2020 年 3046 个地点的 5380 个地面相机陷阱部署的数据,得出 58 个物种的 43,068 条记录。这些数据添加到大西洋森林哺乳动物的现有数据集中,包括处理不完美检测的分析所需的相机操作日期。如果有的话,我们还提供了有关检测的重要预测因素的信息,即相机品牌和型号、诱饵的使用以及相机视域的遮挡,这些信息可以从每个相机位置的示例图片中测量出来。除了应用于研究占用、相对丰度、丰富度和检测背后的模式和机制之外,这里提供的数据集还可用于研究物种的日常活动模式、活动水平和物种之间的时空相互作用。此外,数据可以与其他数据源结合使用,以实现综合人口建模的多种和不断扩展的用途。 R 脚本可用于查看数据集的摘要。我们希望该数据集将用于增进对哺乳动物组合的了解,并为保护大西洋森林提供基于证据的解决方案。数据不受版权限制;使用数据时请引用本文。
更新日期:2024-04-13
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