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6. R2d2 Drives Selfish Sweeps in the House Mouse.

Author

Didion, John, Morgan, Andrew, Yadgary, Liran, Bell, Timothy, McMullan, Rachel, Ortiz de Solorzano, Lydia, Britton-Davidian, Janice, Bult, Carol, Campbell, Karl, Castiglia, Riccardo, Ching, Yung-Hao, Chunco, Amanda, Crowley, James, Chesler, Elissa, Förster, Daniel, French, John, Gabriel, Sofia, Gatti, Daniel, Garland, Theodore, Giagia-Athanasopoulou, Eva, Giménez, Mabel, Grize, Sofia, Gündüz, İslam, Holmes, Andrew, Hauffe, Heidi, Herman, Jeremy, Holt, James, Hua, Kunjie, Jolley, Wesley, Lindholm, Anna, López-Fuster, María, Mitsainas, George, da Luz Mathias, Maria, McMillan, Leonard, Ramalhinho, Maria, Rehermann, Barbara, Rosshart, Stephan, Searle, Jeremy, Shiao, Meng-Shin, Solano, Emanuela, Svenson, Karen, Thomas-Laemont, Patricia, Threadgill, David, Ventura, Jacint, Weinstock, George, Pomp, Daniel, Churchill, Gary, and Pardo-Manuel de Villena, Fernando

Subjects
House Mouse., Meiotic Drive, R2d2, Selective Sweep, Selfish Genes, Adaptation, Physiological, Alleles, Animals, Biological Evolution, DNA Copy Number Variations, Evolution, Molecular, Female, Genetic Variation, Genetics, Population, Male, Mice, Models, Genetic, Mutation, Nuclear Proteins, RNA-Binding Proteins, Repetitive Sequences, Nucleic Acid, Selection, Genetic
Abstract

A selective sweep is the result of strong positive selection driving newly occurring or standing genetic variants to fixation, and can dramatically alter the pattern and distribution of allelic diversity in a population. Population-level sequencing data have enabled discoveries of selective sweeps associated with genes involved in recent adaptations in many species. In contrast, much debate but little evidence addresses whether selfish genes are capable of fixation-thereby leaving signatures identical to classical selective sweeps-despite being neutral or deleterious to organismal fitness. We previously described R2d2, a large copy-number variant that causes nonrandom segregation of mouse Chromosome 2 in females due to meiotic drive. Here we show population-genetic data consistent with a selfish sweep driven by alleles of R2d2 with high copy number (R2d2(HC)) in natural populations. We replicate this finding in multiple closed breeding populations from six outbred backgrounds segregating for R2d2 alleles. We find that R2d2(HC) rapidly increases in frequency, and in most cases becomes fixed in significantly fewer generations than can be explained by genetic drift. R2d2(HC) is also associated with significantly reduced litter sizes in heterozygous mothers, making it a true selfish allele. Our data provide direct evidence of populations actively undergoing selfish sweeps, and demonstrate that meiotic drive can rapidly alter the genomic landscape in favor of mutations with neutral or even negative effects on overall Darwinian fitness. Further study will reveal the incidence of selfish sweeps, and will elucidate the relative contributions of selfish genes, adaptation and genetic drift to evolution.

Published
2016

9. Phylogeny and adaptation shape the teeth of insular mice

Author

Ledevin, Ronan, Chevret, Pascale, Ganem, Guila, Britton-Davidian, Janice, Hardouin, Emilie A., Chapuis, Jean-Louis, Pisanu, Benoit, da Luz Mathias, Maria, Schlager, Stefan, Auffray, Jean-Christophe, and Renaud, Sabrina

Published
2016

10. Large-scale grid-based detection in occupancy surveys of a threatened small mammal: A comparison of two non-invasive methods

Author

Oliveira, Alexandra, primary, Medinas, Denis, additional, Craveiro, João, additional, Milhinhas, Catarina, additional, Sabino-Marques, Helena, additional, Mendes, Tiago, additional, Spadoni, Giulia, additional, Oliveira, André, additional, Guilherme Sousa, Luís, additional, Tapisso, Joaquim T., additional, Santos, Sara, additional, Lopes-Fernandes, Margarida, additional, da Luz Mathias, Maria, additional, Mira, António, additional, and Pita, Ricardo, additional

Published
2023
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11. MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Author

Grilo, Clara, Afonso, Beatriz C., Afonso, Filipe, Alexandre, Marta, Aliácar, Sara, Almeida, Ana, Alonso, Ivan Prego, Álvares, Francisco, Alves, Paulo, Alves, Paulo Célio, Alves, Pedro, Duarte, Beatriz, Duro, Virginia, Encarnação, Cláudia, Eufrázio, Sofia, Fael, António, Falé, João Salvador, Faria, Sandra, Fernandes, C, Fernandes, Margarida, Lopes, Susana, Rosalino, L. M., Costa, Gonçalo Ferrão, Ferreira, Clara, Ferreira, Diogo F., Ferreira, Eduardo, Ferreira, Joaquim Pedro, Ferreira, João, Ferreira, Diana, Fonseca, Carlos, Fontes, Inês, Fragoso, Ricardo, Rosário, Inês T., López-Baucells, Adrià, Franco, Claudia, Freitas, Tamira, Gabriel, Sofia I., Gibb, Rory, Gil, Patricia, Gomes, Carla Patricia Jorge, Horta, Pedro, Gomes, Pedro, Gomes, Verónica, Rossa, Mariana, Grilo, Ana Filipa, Amado, Anabela, Guedes, Américo, Guilherme, Filipa, Gutiérrez, Iván, Harper, Henry, Herrera, José M., Hipólito, Dário, Infante, Samuel, Jesus, José, Russo, Danilo, Loureiro, Armando, Loureiro, Filipa, Lourenço, Rui, Lourenço, Sofia, Lucas, Paula, Magalhães, Ana, Maldonado, Cristina, Marcolin, Fabio, Marques, Sara, Marques, J. Tiago, Sá, Pedro, Amendoeira, Vitor, Marques, Carina, Marques, Paulo, Marrecas, Pedro Caetano, Martins, Frederico, Martins, Raquel, Mascarenhas, Miguel, Mata, Vanessa A., Mateus, Ana Rita, Matos, Milene, Sabino‐Marques, Helena, Medinas, Denis, Amorim, Francisco, Mendes, Tiago, Mendes, Gabriel, Mestre, Frederico, Milhinhas, Catarina, Mira, António, Monarca, Rita I., Monteiro, Norberto, Monteiro, Barbara, Salgueiro, Vânia, Monterroso, Pedro, Nakamura, Mónia, Silva Aparício, Guilherme, Negrões, Nuno, Nóbrega, Eva K., Nóvoa, Miguel, Nunes, Manuel, Nunes, Nuno Jardim, Oliveira, Flávio, Oliveira, José Miguel, Santos, Helena, M. Palmeirim, Jorge, Pargana, João, Paula, Anabela, Araújo, Ricardo, Paupério, Joana, Pedroso, Nuno M., Pereira, Guilherme, Pereira, Pedro F., Pereira, José, Pereira, Maria João Ramos, Santos, Joana, Petrucci-Fonseca, Francisco, Pimenta, Miguel, Pinto, Sara, Pinto, Nuno, Ascensão, Fernando, Pires, Rosa, Pita, Ricardo, Pontes, Carlos, Quaresma, Marisa, Queirós, João, Barbosa, A. Márcia, Queirós, Luís, Rainho, Ana, Graça Ramalhinho, Maria, Ramalho, Patrícia, Raposeira, Helena, Augusto, Margarida, Rasteiro, Francisco, Rebelo, Hugo, Regala, Frederico Tátá, Reto, Dyana, Jones, Kate E., Ribeiro, Sérgio Bruno, Rio‐Maior, Helena, Rocha, Ricardo, Rocha, Rita Gomes, Rodrigues, Luísa, Román, Jacinto, Bandeira, Victor, Roque, Sara, Santos, João P. V., Santos, Nuno, Santos, Sara, Santos, Carlos Pedro, Santos-Reis, Margarida, Serronha, Ana, Sierra, Pablo, Silva, Bruno, Silva, Carla S. G. M., Silva, Clara, Laborde, Marina I., Barbosa, Soraia, Silva, Diogo, Silva, Luís P., Silva, Ricardo, Silva, Carmen, Silva Júnior, Flavio Manoel Rodrigues, Sousa, Pedro, Sousa‐Guedes, Diana, Spadoni, Giulia, Tapisso, Joaquim T., Oliveira, Luís Lamas, Teixeira, Daniela, Barbosa, Sérgio, Teixeira, Sérgio, Teixeira, Nuno, Torres, Rita T., Travassos, Paulo, Vale‐Gonçalves, Hélia, Cidraes‐Vieira, Nuno, Merten, Sophie, Luz Mathias, Maria, Leitão, Inês, Barreiro, Silvia, Barros, Paulo, Barros, Tânia, Barros, Filomena, Pinto Basto, Mafalda, Bernardino, Joana, Bicho, Sara, Biedma, Luis Eduardo, Borges, Marta, Braz, Luis, Lemos, Rita, Brito, José Carlos, Brito, Tiago, Cabral, João Alexandre, Calzada, Javier, Camarinha, Cláudia, Carapuço, Mafalda, Cardoso, Paulo, Carmo, Mário, Carrapato, Carlos, Silva Carrilho, Maílis, Lima, Cátia, Carvalho, Diogo Filipe T. C. S., Carvalho, Filipe, Carvalho, João, Castro, Diana, Castro, Guilherme, Castro, Joana, Castro, Luis Roma, Catry, Filipe Xavier, Cerveira, Ana M., Cid, André, Linck, Paloma, Clarke, Rafael, Conde, Conceição, Conde, José, Costa, Jorge, Costa, Mafalda, Costa, Pedro, Costa, Cristina, Couto, André Pedro, Craveiro, João, Dias, Marta, Lopes, Hugo, Dias, Sofia, and Repositório da Universidade de Lisboa

Abstract

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.

Published
2022

14. MAMMALS IN PORTUGAL: A data set of terrestrial, volant, and marine mammal occurrences in Portugal

Author

Grilo, Clara, primary, Afonso, Beatriz C., additional, Afonso, Filipe, additional, Alexandre, Marta, additional, Aliácar, Sara, additional, Almeida, Ana, additional, Alonso, Ivan Prego, additional, Álvares, Francisco, additional, Alves, Paulo, additional, Alves, Paulo Célio, additional, Alves, Pedro, additional, Amado, Anabela, additional, Amendoeira, Vitor, additional, Amorim, Francisco, additional, da Silva Aparício, Guilherme, additional, Araújo, Ricardo, additional, Ascensão, Fernando, additional, Augusto, Margarida, additional, Bandeira, Victor, additional, Barbosa, A. Márcia, additional, Barbosa, Soraia, additional, Barbosa, Sérgio, additional, Barreiro, Silvia, additional, Barros, Paulo, additional, Barros, Tânia, additional, Barros, Filomena, additional, Basto, Mafalda, additional, Bernardino, Joana, additional, Bicho, Sara, additional, Biedma, Luis Eduardo, additional, Borges, Marta, additional, Braz, Luis, additional, Brito, José Carlos, additional, Brito, Tiago, additional, Cabral, João Alexandre, additional, Calzada, Javier, additional, Camarinha, Cláudia, additional, Carapuço, Mafalda, additional, Cardoso, Paulo, additional, Carmo, Mário, additional, Carrapato, Carlos, additional, da Silva Carrilho, Maílis, additional, Carvalho, Diogo Filipe T. C. S., additional, Carvalho, Filipe, additional, Carvalho, João, additional, Castro, Diana, additional, Castro, Guilherme, additional, Castro, Joana, additional, Castro, Luis Roma, additional, Catry, Filipe Xavier, additional, Cerveira, Ana M., additional, Cid, André, additional, Clarke, Rafael, additional, Conde, Conceição, additional, Conde, José, additional, Costa, Jorge, additional, Costa, Mafalda, additional, Costa, Pedro, additional, Costa, Cristina, additional, do Couto, André Pedro, additional, Craveiro, João, additional, Dias, Marta, additional, Dias, Sofia, additional, Duarte, Beatriz, additional, Duro, Virginia, additional, Encarnação, Cláudia, additional, Eufrázio, Sofia, additional, Fael, António, additional, Falé, João Salvador, additional, Faria, Sandra, additional, Fernandes, Carlos, additional, Fernandes, Margarida, additional, da Costa, Gonçalo Ferrão, additional, Ferreira, Clara, additional, Ferreira, Diogo F., additional, Ferreira, Eduardo, additional, Ferreira, Joaquim Pedro, additional, Ferreira, João, additional, Ferreira, Diana, additional, Fonseca, Carlos, additional, Fontes, Inês, additional, Fragoso, Ricardo, additional, Franco, Claudia, additional, Freitas, Tamira, additional, Gabriel, Sofia I., additional, Gibb, Rory, additional, Gil, Patricia, additional, Gomes, Carla Patricia Jorge, additional, Horta, Pedro, additional, Gomes, Pedro, additional, Gomes, Verónica, additional, Grilo, Filipa, additional, Guedes, Américo, additional, Guilherme, Filipa, additional, Gutiérrez, Iván, additional, Harper, Henry, additional, Herrera, José M., additional, Hipólito, Dário, additional, Infante, Samuel, additional, Jesus, José, additional, Jones, Kate E., additional, Laborde, Marina I., additional, de Oliveira, Luís Lamas, additional, Leitão, Inês, additional, Lemos, Rita, additional, Lima, Cátia, additional, Linck, Paloma, additional, Lopes, Hugo, additional, Lopes, Susana, additional, López‐Baucells, Adrià, additional, Loureiro, Armando, additional, Loureiro, Filipa, additional, Lourenço, Rui, additional, Lourenço, Sofia, additional, Lucas, Paula, additional, Magalhães, Ana, additional, Maldonado, Cristina, additional, Marcolin, Fabio, additional, Marques, Sara, additional, Marques, J. Tiago, additional, Marques, Carina, additional, Marques, Paulo, additional, Marrecas, Pedro Caetano, additional, Martins, Frederico, additional, Martins, Raquel, additional, Mascarenhas, Miguel, additional, Mata, Vanessa A., additional, Mateus, Ana Rita, additional, Matos, Milene, additional, Medinas, Denis, additional, Mendes, Tiago, additional, Mendes, Gabriel, additional, Mestre, Frederico, additional, Milhinhas, Catarina, additional, Mira, António, additional, Monarca, Rita I., additional, Monteiro, Norberto, additional, Monteiro, Barbara, additional, Monterroso, Pedro, additional, Nakamura, Mónia, additional, Negrões, Nuno, additional, Nóbrega, Eva K., additional, Nóvoa, Miguel, additional, Nunes, Manuel, additional, Nunes, Nuno Jardim, additional, Oliveira, Flávio, additional, Oliveira, José Miguel, additional, Palmeirim, Jorge M., additional, Pargana, João, additional, Paula, Anabela, additional, Paupério, Joana, additional, Pedroso, Nuno M., additional, Pereira, Guilherme, additional, Pereira, Pedro F., additional, Pereira, José, additional, Pereira, Maria João Ramos, additional, Petrucci‐Fonseca, Francisco, additional, Pimenta, Miguel, additional, Pinto, Sara, additional, Pinto, Nuno, additional, Pires, Rosa, additional, Pita, Ricardo, additional, Pontes, Carlos, additional, Quaresma, Marisa, additional, Queirós, João, additional, Queirós, Luís, additional, Rainho, Ana, additional, da Graça Ramalhinho, Maria, additional, Ramalho, Patrícia, additional, Raposeira, Helena, additional, Rasteiro, Francisco, additional, Rebelo, Hugo, additional, Regala, Frederico Tátá, additional, Reto, Dyana, additional, Ribeiro, Sérgio Bruno, additional, Rio‐Maior, Helena, additional, Rocha, Ricardo, additional, Rocha, Rita Gomes, additional, Rodrigues, Luísa, additional, Román, Jacinto, additional, Roque, Sara, additional, Rosalino, Luís Miguel, additional, do Rosário, Inês T., additional, Rossa, Mariana, additional, Russo, Danilo, additional, Sá, Pedro, additional, Sabino‐Marques, Helena, additional, Salgueiro, Vânia, additional, Santos, Helena, additional, Santos, Joana, additional, Santos, João P. V., additional, Santos, Nuno, additional, Santos, Sara, additional, Santos, Carlos Pedro, additional, Santos‐Reis, Margarida, additional, Serronha, Ana, additional, Sierra, Pablo, additional, Silva, Bruno, additional, Silva, Carla S. G. M., additional, Silva, Clara, additional, Silva, Diogo, additional, da Silva, Luís P., additional, Silva, Ricardo, additional, Silva, Carmen, additional, da Silva Júnior, Flavio Manoel Rodrigues, additional, Sousa, Pedro, additional, Sousa‐Guedes, Diana, additional, Spadoni, Giulia, additional, Tapisso, Joaquim T., additional, Teixeira, Daniela, additional, Teixeira, Sérgio, additional, Teixeira, Nuno, additional, Torres, Rita T., additional, Travassos, Paulo, additional, Vale‐Gonçalves, Hélia, additional, Cidraes‐Vieira, Nuno, additional, von Merten, Sophie, additional, and da Luz Mathias, Maria, additional

Published
2022
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16. Supplementary material 4 from: Ascensão F, D'Amico M, Martins RC, Rebelo R, Barbosa AM, Bencatel J, Barrientos R, Abellán P, Tella JL, Cardador L, Anadón JD, Carrete M, Murgui E, Fernandes P, Santos SM, Mira A, da Luz Mathias M, Tiago P, Casabella E, Reino L, Paulo OS, Pereira HM, Capinha C (2021) Distribution of alien tetrapods in the Iberian Peninsula. NeoBiota 64: 1-21. https://doi.org/10.3897/neobiota.64.55597

Author

Ascensão, Fernando, primary, D'Amico, Marcello, additional, Martins, Ricardo C., additional, Rebelo, Rui, additional, Barbosa, A. Márcia, additional, Bencatel, Joana, additional, Barrientos, Rafael, additional, Abellán, Pedro, additional, Tella, José L., additional, Cardador, Laura, additional, Anadón, José D., additional, Carrete, Martina, additional, Murgui, Enrique, additional, Fernandes, Pedro, additional, Santos, Sara M., additional, Mira, António, additional, da Luz Mathias, Maria, additional, Tiago, Patrícia, additional, Casabella, Eduardo, additional, Reino, Luís, additional, Paulo, Octávio S., additional, Pereira, Henrique M., additional, and Capinha, César, additional

Published
2021
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17. Distribution of alien tetrapods in the Iberian Peninsula

Author

Ascensão, Fernando, primary, D'Amico, Marcello, additional, Martins, Ricardo C., additional, Rebelo, Rui, additional, Barbosa, A. Márcia, additional, Bencatel, Joana, additional, Barrientos, Rafael, additional, Abellán, Pedro, additional, Tella, José L., additional, Cardador, Laura, additional, Anadón, José D., additional, Carrete, Martina, additional, Murgui, Enrique, additional, Fernandes, Pedro, additional, Santos, Sara M., additional, Mira, António, additional, da Luz Mathias, Maria, additional, Tiago, Patrícia, additional, Casabella, Eduardo, additional, Reino, Luís, additional, Paulo, Octávio S., additional, Pereira, Henrique M., additional, and Capinha, César, additional

Published
2021
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18. Supplementary material 1 from: Ascensão F, D'Amico M, Martins RC, Rebelo R, Barbosa AM, Bencatel J, Barrientos R, Abellán P, Tella JL, Cardador L, Anadón JD, Carrete M, Murgui E, Fernandes P, Santos SM, Mira A, da Luz Mathias M, Tiago P, Casabella E, Reino L, Paulo OS, Pereira HM, Capinha C (2021) Distribution of alien tetrapods in the Iberian Peninsula. NeoBiota 64: 1-21. https://doi.org/10.3897/neobiota.64.55597

Author

Ascensão, Fernando, primary, D'Amico, Marcello, additional, Martins, Ricardo C., additional, Rebelo, Rui, additional, Barbosa, A. Márcia, additional, Bencatel, Joana, additional, Barrientos, Rafael, additional, Abellán, Pedro, additional, Tella, José L., additional, Cardador, Laura, additional, Anadón, José D., additional, Carrete, Martina, additional, Murgui, Enrique, additional, Fernandes, Pedro, additional, Santos, Sara M., additional, Mira, António, additional, da Luz Mathias, Maria, additional, Tiago, Patrícia, additional, Casabella, Eduardo, additional, Reino, Luís, additional, Paulo, Octávio S., additional, Pereira, Henrique M., additional, and Capinha, César, additional

Published
2021
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19. Supplementary material 2 from: Ascensão F, D'Amico M, Martins RC, Rebelo R, Barbosa AM, Bencatel J, Barrientos R, Abellán P, Tella JL, Cardador L, Anadón JD, Carrete M, Murgui E, Fernandes P, Santos SM, Mira A, da Luz Mathias M, Tiago P, Casabella E, Reino L, Paulo OS, Pereira HM, Capinha C (2021) Distribution of alien tetrapods in the Iberian Peninsula. NeoBiota 64: 1-21. https://doi.org/10.3897/neobiota.64.55597

Author

Ascensão, Fernando, primary, D'Amico, Marcello, additional, Martins, Ricardo C., additional, Rebelo, Rui, additional, Barbosa, A. Márcia, additional, Bencatel, Joana, additional, Barrientos, Rafael, additional, Abellán, Pedro, additional, Tella, José L., additional, Cardador, Laura, additional, Anadón, José D., additional, Carrete, Martina, additional, Murgui, Enrique, additional, Fernandes, Pedro, additional, Santos, Sara M., additional, Mira, António, additional, da Luz Mathias, Maria, additional, Tiago, Patrícia, additional, Casabella, Eduardo, additional, Reino, Luís, additional, Paulo, Octávio S., additional, Pereira, Henrique M., additional, and Capinha, César, additional

Published
2021
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20. Supplementary material 3 from: Ascensão F, D'Amico M, Martins RC, Rebelo R, Barbosa AM, Bencatel J, Barrientos R, Abellán P, Tella JL, Cardador L, Anadón JD, Carrete M, Murgui E, Fernandes P, Santos SM, Mira A, da Luz Mathias M, Tiago P, Casabella E, Reino L, Paulo OS, Pereira HM, Capinha C (2021) Distribution of alien tetrapods in the Iberian Peninsula. NeoBiota 64: 1-21. https://doi.org/10.3897/neobiota.64.55597

Author

Ascensão, Fernando, primary, D'Amico, Marcello, additional, Martins, Ricardo C., additional, Rebelo, Rui, additional, Barbosa, A. Márcia, additional, Bencatel, Joana, additional, Barrientos, Rafael, additional, Abellán, Pedro, additional, Tella, José L., additional, Cardador, Laura, additional, Anadón, José D., additional, Carrete, Martina, additional, Murgui, Enrique, additional, Fernandes, Pedro, additional, Santos, Sara M., additional, Mira, António, additional, da Luz Mathias, Maria, additional, Tiago, Patrícia, additional, Casabella, Eduardo, additional, Reino, Luís, additional, Paulo, Octávio S., additional, Pereira, Henrique M., additional, and Capinha, César, additional

Published
2021
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21. Multimarker approach to assess the exposure of the wild rodent Calomys laucha to a simulated crude oil spill

Author

de Almeida, Krissia Aparecida, primary, Garcia, Edariane Menestrino, additional, Penteado, Julia Oliveira, additional, Tavella, Ronan Adler, additional, Fernandes, Caroline Lopes Feijo, additional, Ramires, Paula Florencio, additional, Ramires Júnior, Osmar Vieira, additional, Muccillo-Baisch, Ana Luíza, additional, da Luz Mathias, Maria, additional, Dias, Deodália, additional, and da Siva Júnior, Flavio Manoel Rodrigues, additional

Published
2020
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24. Sharing the Decision Process Framework to Identify Well-supported Records of Mammal Speciesoccurrence in Mozambique.

Author

Neves, Isabel Queirós, da Luz Mathias, Maria, and Bastos-Silveira, Cristiane

Subjects
BIODIVERSITY conservation, DECISION making, MAMMALS
Abstract

Conservation research and policies tend to be significantly restricted wherever relevant data on biodiversity is sparse, scattered or non-curated. Thus, the usefulness of occurrence data, for the study of biodiversity, depends not only on the availability but also on data quality. Notwithstanding the increase in the global availability of primary biodiversity data, they have numerous shortfalls, from incomplete or partially erroneous documentation to spatial and temporal biases (Hortal et al. 2015, Aubry et al. 2017). Also, many non-digitized specimen collections, scientific publications and grey literature are locked as printed or digital publications. We integrated existing knowledge, from dispersed sources of biodiversity data, namely Global Biodiversity Information Facility (GBIF), natural history collections, wildlife survey reports, species checklist and other scientific literature. This procedure allowed an update of Mozambique's checklist of terrestrial mammals (Neves et al. 2018). Despite the potential from digital data to overcome gaps of knowledge, a relevant constraint on creating or updating species checklist is the dificulty to access spatially-disperse collections and examine every specimens upon which occurrences are based. To partly overcome this impediment, we developed a species selection process for specimen data from GBIF and museums (Fig. 1). The aim was to categorise the species detected in more than one data source as species with the well-supported occurrence. In addition to the number of collectors, we also accounted for the number of records collected and presented in Smithers and Tello (1976), the last checklist produced for Mozambique' mammals. A species-occurrence record was considered well-supported and included into the species checklist when was: 1. independently recorded by different collectors or 2. recorded by a single collector but listed in Smithers and Tello (1976). An additional list was produced which contained species with questionable occurrence in the country. Species entered this "questionable occurrence" list when they were: 1. not listed in Smithers and Tello (1976), and a single record supported its presence in the country; 2. not listed in Smithers and Tello (1976) and multiple records exist, but were all cited by a single author; or 3. registered with a single record in Smithers and Tello (1976). We compiled more than 17000 records, resulting in a total of 217 species (14 orders, 39 families and 133 genera) with supported occurrence in Mozambique and 23 species with questionable reported occurrence (Table 1). The proposed approach for species selection can be adapted and function as a powerful tool to update species checklists of countries facing similar lack of knowledge regarding their biodiversity. The capacity to pinpointing species and specimens in need of occurrence and taxonomic re-evaluation is of great value to optimise collection's study and to boost collaboration between curators and researchers. Lastly, considering that most records integrated are from European and North American institutions, this work would significantly improve with the integration of data from African institutions. Therefore, an effort should be made to make these essential collections accessible online. [ABSTRACT FROM AUTHOR]

Published
2019
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25. R2d2 drives selfish sweeps in the house mouse

Author

Didion, John P, Morgan, Andrew P, Yadgary, Liran, Bell, Timothy A, McMullan, Rachel C, de Solorzano, Lydia Ortiz, Britton-Davidian, Janice, Bult, Carol J, Campbell, Karl J, Castiglia, Riccardo, Ching, Yung-Hao, Chunco, Amanda J, Crowley, James J, Chesler, Elissa J, Förster, Daniel W, French, John E, Gabriel, Sofia I, Gatti, Daniel M, Garland, Theodore, Giagia-Athanasopoulou, Eva B, Giménez, Mabel D, Grize, Sofia A, Günduz, Islam, Holmes, Andrew, Hauffe, Heidi C, Herman, Jeremy S, Holt, James M, Hua, Kunjie, Jolley, Wesley J, Lindholm, Anna K, Lopez-Fuster, Maria J, Mitsainas, George, da Luz Mathias, Maria, McMillan, Leonard, da Graca Morgado Ramalhinho, Maria, Rehermann, Barbara, Rosshart, Stephan P, Searle, Jeremy B, Shiao, Meng-Shin, Solano, Emanuela, Svenson, Karen L, Thomas-Laemont, Patricia, Threadgill, David W, Ventura, Jacint, Weinstock, George M, Pomp, Daniel, Churchill, Gary A, de Villena, Fernando Pardo-Manuel, Didion, John P, Morgan, Andrew P, Yadgary, Liran, Bell, Timothy A, McMullan, Rachel C, de Solorzano, Lydia Ortiz, Britton-Davidian, Janice, Bult, Carol J, Campbell, Karl J, Castiglia, Riccardo, Ching, Yung-Hao, Chunco, Amanda J, Crowley, James J, Chesler, Elissa J, Förster, Daniel W, French, John E, Gabriel, Sofia I, Gatti, Daniel M, Garland, Theodore, Giagia-Athanasopoulou, Eva B, Giménez, Mabel D, Grize, Sofia A, Günduz, Islam, Holmes, Andrew, Hauffe, Heidi C, Herman, Jeremy S, Holt, James M, Hua, Kunjie, Jolley, Wesley J, Lindholm, Anna K, Lopez-Fuster, Maria J, Mitsainas, George, da Luz Mathias, Maria, McMillan, Leonard, da Graca Morgado Ramalhinho, Maria, Rehermann, Barbara, Rosshart, Stephan P, Searle, Jeremy B, Shiao, Meng-Shin, Solano, Emanuela, Svenson, Karen L, Thomas-Laemont, Patricia, Threadgill, David W, Ventura, Jacint, Weinstock, George M, Pomp, Daniel, Churchill, Gary A, and de Villena, Fernando Pardo-Manuel

Abstract

A selective sweep is the result of strong positive selection driving newly occurring or standing genetic variants to fixation, and can dramatically alter the pattern and distribution of allelic diversity in a population. Population-level sequencing data have enabled discoveries of selective sweeps associated with genes involved in recent adaptations in many species. In contrast, much debate but little evidence addresses whether “selfish” genes are capable of fixation – thereby leaving signatures identical to classical selective sweeps – despite being neutral or deleterious to organismal fitness. We previously described R2d2, a large copy-number variant that causes non-random segregation of mouse Chromosome 2 in females due to meiotic drive. Here we show population-genetic data consistent with a selfish sweep driven by alleles of R2d2 with high copy number (R2d2HC) in natural populations. We replicate this finding in multiple closed breeding populations from six outbred backgrounds segregating for R2d2 alleles. We find that R2d2HC rapidly increases in frequency, and in most cases becomes fixed in significantly fewer generations than can be explained by genetic drift. R2d2HC is also associated with significantly reduced litter sizes in heterozygous mothers, making it a true selfish allele. Our data provide direct evidence of populations actively undergoing selfish sweeps, and demonstrate that meiotic drive can rapidly alter the genomic landscape in favor of mutations with neutral or even negative effects on overall Darwinian fitness. Further study will reveal the incidence of selfish sweeps, and will elucidate the relative contributions of selfish genes, adaptation and genetic drift to evolution.

Published
2016

26. R2d2Drives Selfish Sweeps in the House Mouse

Author

Didion, John P., primary, Morgan, Andrew P., additional, Yadgary, Liran, additional, Bell, Timothy A., additional, McMullan, Rachel C., additional, Ortiz de Solorzano, Lydia, additional, Britton-Davidian, Janice, additional, Bult, Carol J., additional, Campbell, Karl J., additional, Castiglia, Riccardo, additional, Ching, Yung-Hao, additional, Chunco, Amanda J., additional, Crowley, James J., additional, Chesler, Elissa J., additional, Förster, Daniel W., additional, French, John E., additional, Gabriel, Sofia I., additional, Gatti, Daniel M., additional, Garland, Theodore, additional, Giagia-Athanasopoulou, Eva B., additional, Giménez, Mabel D., additional, Grize, Sofia A., additional, Gündüz, İslam, additional, Holmes, Andrew, additional, Hauffe, Heidi C., additional, Herman, Jeremy S., additional, Holt, James M., additional, Hua, Kunjie, additional, Jolley, Wesley J., additional, Lindholm, Anna K., additional, López-Fuster, María J., additional, Mitsainas, George, additional, da Luz Mathias, Maria, additional, McMillan, Leonard, additional, Ramalhinho, Maria da Graça Morgado, additional, Rehermann, Barbara, additional, Rosshart, Stephan P., additional, Searle, Jeremy B., additional, Shiao, Meng-Shin, additional, Solano, Emanuela, additional, Svenson, Karen L., additional, Thomas-Laemont, Patricia, additional, Threadgill, David W., additional, Ventura, Jacint, additional, Weinstock, George M., additional, Pomp, Daniel, additional, Churchill, Gary A., additional, and Pardo-Manuel de Villena, Fernando, additional

Published
2016
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28. Mapping the Impact of Digitisation for Poorly Documented Countries: Mozambique as a case study.

Author

Neves, Isabel Queirós, da Luz Mathias, Maria, and Bastos-Silveira, Cristiane

Subjects
INFORMATION sharing, NATURAL history catalogs & collections, MAMMALS
Abstract

Despite the rise of the global availability of biodiversity data by digitisation, essential regions of the world remain poorly documented (Peterson et al. 2015). Research-neglected regions that lack quality information, are mainly the species-rich and developing nations (Gaikwad and Chavan 2006). Mozambique is an African country without a wide-ranging knowledge regarding its fauna's diversity and distribution (Neves et al. 2018). Undeniably, this country's knowledge gaps constitute a significant impediment for the improvement of effective conservation measures. Primary species occurrence data across dispersed data sources can be a cost-effective resource for boosting knowledge about a country's biodiversity. Aiming to aggregate a comprehensive dataset of Mozambique's terrestrial mammals, we compiled primary species occurrence data from dispersed data sources. The produced dataset not only gathered digitalised accessible knowledge (DAK) from the Global Biodiversity Information Facility (GBIF) and natural history collections, but also retrieved and digitalised species occurrence data enclosed in grey and scientific literature. Particularly for poorly documented countries, filling data gaps are crucial for new and broad insights for biodiversity research and preservation. Thus, quantification of the effects of data digitisation and mobilisation goes beyond the specific goals of organisations, institutions or data-sharing resources. The impact of data digitisation should be disseminated, not only by the number of publications and times data are accessed (Nelson and Ellis 2018), but also by the actual achievements in regions covered by DAK. To highlight the impact of further data digitisation in a poorly documented country, we examine the effective gain of further digitisation and data cleaning on the terrestrial mammals from Mozambique. We demonstrate the increase in the overall knowledge, not merely in terms of number of species, number of records, and country's coverage, but from the production of outputs with potential value for data-driven conservation research and planning. More than 17000 records were compiled. The digitisation of data in literature as well as data cleaning and quality improvements resulted in a substantial increase in the amount of DAK, which acknowledges Mozambique's high species diversity (Fig. 1). The digitisation and data mobilisation hereby described allowed for the update of the country's terrestrial mammals checklist (Neves et al. 2018). The final dataset also expands the knowledge of the most poorly documented provinces, allowing generation of a data-driven proposal of priority areas to survey (in review). Also, an assessment of Mozambique's conservation network effectiveness for mammal protection was performed, and additional relevant areas were suggested (in prep.). The dataset compiled is an important "stepping stone" towards an enhanced knowledge of Mozambique's fauna. Biodiversity conservation and management in developing countries rich in natural resources, which often must deal with a lack of internal capacity for applied research and conservation actions, are challenges. Considering that digitisation and mobilisation of biodiversity data are resourceful processes for improving knowledge collaborative work between institutions of those countries and international data-provider communities could, in the short term, successfully improve the information baseline to support decision-making in future conservation and management actions. [ABSTRACT FROM AUTHOR]

Published
2019
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29. MAMMALS IN PORTUGAL: A data set of terrestrial, volant, and marine mammal occurrences in Portugal

Author

Clara Grilo, Beatriz C. Afonso, Filipe Afonso, Marta Alexandre, Sara Aliácar, Ana Almeida, Ivan Prego Alonso, Francisco Álvares, Paulo Alves, Paulo Célio Alves, Pedro Alves, Anabela Amado, Vitor Amendoeira, Francisco Amorim, Guilherme Silva Aparício, Ricardo Araújo, Fernando Ascensão, Margarida Augusto, Victor Bandeira, A. Márcia Barbosa, Soraia Barbosa, Sérgio Barbosa, Silvia Barreiro, Paulo Barros, Tânia Barros, Filomena Barros, Mafalda Basto, Joana Bernardino, Sara Bicho, Luis Eduardo Biedma, Marta Borges, Luis Braz, José Carlos Brito, Tiago Brito, João Alexandre Cabral, Javier Calzada, Cláudia Camarinha, Mafalda Carapuço, Paulo Cardoso, Mário Carmo, Carlos Carrapato, Maílis Silva Carrilho, Diogo Filipe T. C. S. Carvalho, Filipe Carvalho, João Carvalho, Diana Castro, Guilherme Castro, Joana Castro, Luis Roma Castro, Filipe Xavier Catry, Ana M. Cerveira, André Cid, Rafael Clarke, Conceição Conde, José Conde, Jorge Costa, Mafalda Costa, Pedro Costa, Cristina Costa, André Pedro Couto, João Craveiro, Marta Dias, Sofia Dias, Beatriz Duarte, Virginia Duro, Cláudia Encarnação, Sofia Eufrázio, António Fael, João Salvador Falé, Sandra Faria, Carlos Fernandes, Margarida Fernandes, Gonçalo Ferrão Costa, Clara Ferreira, Diogo F. Ferreira, Eduardo Ferreira, Joaquim Pedro Ferreira, João Ferreira, Diana Ferreira, Carlos Fonseca, Inês Fontes, Ricardo Fragoso, Claudia Franco, Tamira Freitas, Sofia I. Gabriel, Rory Gibb, Patricia Gil, Carla Patricia Jorge Gomes, Pedro Horta, Pedro Gomes, Verónica Gomes, Filipa Grilo, Américo Guedes, Filipa Guilherme, Iván Gutiérrez, Henry Harper, José M. Herrera, Dário Hipólito, Samuel Infante, José Jesus, Kate E. Jones, Marina I. Laborde, Luís Lamas Oliveira, Inês Leitão, Rita Lemos, Cátia Lima, Paloma Linck, Hugo Lopes, Susana Lopes, Adrià López‐Baucells, Armando Loureiro, Filipa Loureiro, Rui Lourenço, Sofia Lourenço, Paula Lucas, Ana Magalhães, Cristina Maldonado, Fabio Marcolin, Sara Marques, J. Tiago Marques, Carina Marques, Paulo Marques, Pedro Caetano Marrecas, Frederico Martins, Raquel Martins, Miguel Mascarenhas, Vanessa A. Mata, Ana Rita Mateus, Milene Matos, Denis Medinas, Tiago Mendes, Gabriel Mendes, Frederico Mestre, Catarina Milhinhas, António Mira, Rita I. Monarca, Norberto Monteiro, Barbara Monteiro, Pedro Monterroso, Mónia Nakamura, Nuno Negrões, Eva K. Nóbrega, Miguel Nóvoa, Manuel Nunes, Nuno Jardim Nunes, Flávio Oliveira, José Miguel Oliveira, Jorge M. Palmeirim, João Pargana, Anabela Paula, Joana Paupério, Nuno M. Pedroso, Guilherme Pereira, Pedro F. Pereira, José Pereira, Maria João Ramos Pereira, Francisco Petrucci‐Fonseca, Miguel Pimenta, Sara Pinto, Nuno Pinto, Rosa Pires, Ricardo Pita, Carlos Pontes, Marisa Quaresma, João Queirós, Luís Queirós, Ana Rainho, Maria Graça Ramalhinho, Patrícia Ramalho, Helena Raposeira, Francisco Rasteiro, Hugo Rebelo, Frederico Tátá Regala, Dyana Reto, Sérgio Bruno Ribeiro, Helena Rio‐Maior, Ricardo Rocha, Rita Gomes Rocha, Luísa Rodrigues, Jacinto Román, Sara Roque, Luís Miguel Rosalino, Inês T. Rosário, Mariana Rossa, Danilo Russo, Pedro Sá, Helena Sabino‐Marques, Vânia Salgueiro, Helena Santos, Joana Santos, João P. V. Santos, Nuno Santos, Sara Santos, Carlos Pedro Santos, Margarida Santos‐Reis, Ana Serronha, Pablo Sierra, Bruno Silva, Carla S. G. M. Silva, Clara Silva, Diogo Silva, Luís P. Silva, Ricardo Silva, Carmen Silva, Flavio Manoel Rodrigues Silva Júnior, Pedro Sousa, Diana Sousa‐Guedes, Giulia Spadoni, Joaquim T. Tapisso, Daniela Teixeira, Sérgio Teixeira, Nuno Teixeira, Rita T. Torres, Paulo Travassos, Hélia Vale‐Gonçalves, Nuno Cidraes‐Vieira, Sophie Merten, Maria Luz Mathias, Grilo, Clara, Afonso, Beatriz C, Afonso, Filipe, Alexandre, Marta, Aliácar, Sara, Almeida, Ana, Alonso, Ivan Prego, Álvares, Francisco, Alves, Paulo, Alves, Paulo Célio, Alves, Pedro, Amado, Anabela, Amendoeira, Vitor, Amorim, Francisco, da Silva Aparício, Guilherme, Araújo, Ricardo, Ascensão, Fernando, Augusto, Margarida, Bandeira, Victor, Barbosa, A Márcia, Barbosa, Soraia, Barbosa, Sérgio, Barreiro, Silvia, Barros, Paulo, Barros, Tânia, Barros, Filomena, Basto, Mafalda, Bernardino, Joana, Bicho, Sara, Biedma, Luis Eduardo, Borges, Marta, Braz, Lui, Brito, José Carlo, Brito, Tiago, Cabral, João Alexandre, Calzada, Javier, Camarinha, Cláudia, Carapuço, Mafalda, Cardoso, Paulo, Carmo, Mário, Carrapato, Carlo, da Silva Carrilho, Maíli, Carvalho, Diogo Filipe T C S, Carvalho, Filipe, Carvalho, João, Castro, Diana, Castro, Guilherme, Castro, Joana, Castro, Luis Roma, Catry, Filipe Xavier, Cerveira, Ana M, Cid, André, Clarke, Rafael, Conde, Conceição, Conde, José, Costa, Jorge, Costa, Mafalda, Costa, Pedro, Costa, Cristina, do Couto, André Pedro, Craveiro, João, Dias, Marta, Dias, Sofia, Duarte, Beatriz, Duro, Virginia, Encarnação, Cláudia, Eufrázio, Sofia, Fael, António, Falé, João Salvador, Faria, Sandra, Fernandes, Carlo, Fernandes, Margarida, da Costa, Gonçalo Ferrão, Ferreira, Clara, Ferreira, Diogo F, Ferreira, Eduardo, Ferreira, Joaquim Pedro, Ferreira, João, Ferreira, Diana, Fonseca, Carlo, Fontes, Inê, Fragoso, Ricardo, Franco, Claudia, Freitas, Tamira, Gabriel, Sofia I, Gibb, Rory, Gil, Patricia, Gomes, Carla Patricia Jorge, Horta, Pedro, Gomes, Pedro, Gomes, Verónica, Grilo, Filipa, Guedes, Américo, Guilherme, Filipa, Gutiérrez, Iván, Harper, Henry, Herrera, José M, Hipólito, Dário, Infante, Samuel, Jesus, José, Jones, Kate E, Laborde, Marina I, de Oliveira, Luís Lama, Leitão, Inê, Lemos, Rita, Lima, Cátia, Linck, Paloma, Lopes, Hugo, Lopes, Susana, López-Baucells, Adrià, Loureiro, Armando, Loureiro, Filipa, Lourenço, Rui, Lourenço, Sofia, Lucas, Paula, Magalhães, Ana, Maldonado, Cristina, Marcolin, Fabio, Marques, Sara, Marques, J Tiago, Marques, Carina, Marques, Paulo, Marrecas, Pedro Caetano, Martins, Frederico, Martins, Raquel, Mascarenhas, Miguel, Mata, Vanessa A, Mateus, Ana Rita, Matos, Milene, Medinas, Deni, Mendes, Tiago, Mendes, Gabriel, Mestre, Frederico, Milhinhas, Catarina, Mira, António, Monarca, Rita I, Monteiro, Norberto, Monteiro, Barbara, Monterroso, Pedro, Nakamura, Mónia, Negrões, Nuno, Nóbrega, Eva K, Nóvoa, Miguel, Nunes, Manuel, Nunes, Nuno Jardim, Oliveira, Flávio, Oliveira, José Miguel, Palmeirim, Jorge M, Pargana, João, Paula, Anabela, Paupério, Joana, Pedroso, Nuno M, Pereira, Guilherme, Pereira, Pedro F, Pereira, José, Pereira, Maria João Ramo, Petrucci-Fonseca, Francisco, Pimenta, Miguel, Pinto, Sara, Pinto, Nuno, Pires, Rosa, Pita, Ricardo, Pontes, Carlo, Quaresma, Marisa, Queirós, João, Queirós, Luí, Rainho, Ana, da Graça Ramalhinho, Maria, Ramalho, Patrícia, Raposeira, Helena, Rasteiro, Francisco, Rebelo, Hugo, Regala, Frederico Tátá, Reto, Dyana, Ribeiro, Sérgio Bruno, Rio-Maior, Helena, Rocha, Ricardo, Rocha, Rita Gome, Rodrigues, Luísa, Román, Jacinto, Roque, Sara, Rosalino, Luís Miguel, do Rosário, Inês T, Rossa, Mariana, Russo, Danilo, Sá, Pedro, Sabino-Marques, Helena, Salgueiro, Vânia, Santos, Helena, Santos, Joana, Santos, João P V, Santos, Nuno, Santos, Sara, Santos, Carlos Pedro, Santos-Reis, Margarida, Serronha, Ana, Sierra, Pablo, Silva, Bruno, Silva, Carla S G M, Silva, Clara, Silva, Diogo, da Silva, Luís P, Silva, Ricardo, Silva, Carmen, da Silva Júnior, Flavio Manoel Rodrigue, Sousa, Pedro, Sousa-Guedes, Diana, Spadoni, Giulia, Tapisso, Joaquim T, Teixeira, Daniela, Teixeira, Sérgio, Teixeira, Nuno, Torres, Rita T, Travassos, Paulo, Vale-Gonçalves, Hélia, Cidraes-Vieira, Nuno, von Merten, Sophie, and da Luz Mathias, Maria

Subjects
1873-2021, Mammals, EuropeIberian Peninsula, Portugal, Animal, Climate Change, Carnivora, Eulipotyphla, Rodentia, Rabbit, Lagomorpha, Mammal, Europe, Rodentiaspecies distribution, Chiroptera, Animals, species distribution, Rabbits, Cetartiodactyla, Ecology, Evolution, Behavior and Systematics, Ecosystem, Iberian Peninsula
Abstract

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n=31,573) has the highest number of records followed by Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496), Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n=12,159], Monachus monachus [n=1,512], and Lynx pardinus [n=197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications.

Published
2021

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