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1. Global importance of Indigenous Peoples, their lands, and knowledge systems for saving the world’s primates from extinction

Author

Estrada, Alejandro, Garber, Paul A, Gouveia, Sidney, Fernández-Llamazares, Álvaro, Ascensão, Fernando, Fuentes, Agustin, Garnett, Stephen T, Shaffer, Christopher, Bicca-Marques, Júlio, Fa, Julia E, Hockings, Kimberley, Shanee, Sam, Johnson, Steig, Shepard, Glenn H, Shanee, Noga, Golden, Christopher D, Cárdenas-Navarrete, Anaid, Levey, Dallas R, Boonratana, Ramesh, Dobrovolski, Ricardo, Chaudhary, Abhishek, Ratsimbazafy, Jonah, Supriatna, Jatna, Kone, Inza, and Volampeno, Sylviane

Subjects
Life on Land
Abstract

Primates, represented by 521 species, are distributed across 91 countries primarily in the Neotropic, Afrotropic, and Indo-Malayan realms. Primates inhabit a wide range of habitats and play critical roles in sustaining healthy ecosystems that benefit human and nonhuman communities. Approximately 68% of primate species are threatened with extinction because of global pressures to convert their habitats for agricultural production and the extraction of natural resources. Here, we review the scientific literature and conduct a spatial analysis to assess the significance of Indigenous Peoples' lands in safeguarding primate biodiversity. We found that Indigenous Peoples' lands account for 30% of the primate range, and 71% of primate species inhabit these lands. As their range on these lands increases, primate species are less likely to be classified as threatened or have declining populations. Safeguarding Indigenous Peoples' lands, languages, and cultures represents our greatest chance to prevent the extinction of the world's primates.

Published
2022

7. A dataset of acoustic measurements from soundscapes collected worldwide during the COVID-19 pandemic.

Author

Challéat, Samuel, Farrugia, Nicolas, Froidevaux, Jérémy S. P., Gasc, Amandine, Pajusco, Nicolas, Abrahams, Carlos R., Acevedo-Charry, Orlando, Aguiar, Ludmilla M. S., Ahlin, Zachary R., Aiple, Franz, Albert, Cécile H., Alcocer, Irene, Alves, Ana Sofia, Amorim, Francisco, Andrade, Ludmila B., Araújo, Pedro M., Ascensão, Fernando, Aucoin, Serge, Bader, Elias, and Balbuena, Diego

Subjects
COVID-19 pandemic, ACOUSTIC measurements, CITIES & towns, SOUND recordings, ENVIRONMENTAL sciences, METADATA
Abstract

Political responses to the COVID-19 pandemic led to changes in city soundscapes around the globe. From March to October 2020, a consortium of 261 contributors from 35 countries brought together by the Silent Cities project built a unique soundscape recordings collection to report on local acoustic changes in urban areas. We present this collection here, along with metadata including observational descriptions of the local areas from the contributors, open-source environmental data, open-source confinement levels and calculation of acoustic descriptors. We performed a technical validation of the dataset using statistical models run on a subset of manually annotated soundscapes. Results confirmed the large-scale usability of ecoacoustic indices and automatic sound event recognition in the Silent Cities soundscape collection. We expect this dataset to be useful for research in the multidisciplinary field of environmental sciences. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Research gaps in knowledge of the impact of urban growth on biodiversity

Author

McDonald, Robert I., Mansur, Andressa V., Ascensão, Fernando, Colbert, M’lisa, Crossman, Katie, Elmqvist, Thomas, Gonzalez, Andrew, Güneralp, Burak, Haase, Dagmar, Hamann, Maike, Hillel, Oliver, Huang, Kangning, Kahnt, Belinda, Maddox, David, Pacheco, Andrea, Pereira, Henrique M., Seto, Karen C., Simkin, Rohan, Walsh, Brenna, Werner, Alexandra S., and Ziter, Carly

Published
2020
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19. Assessing the Stone Marten’s Patch Occupancy in Fragmented landscapes and its Relation to Road-Killing Occurences

Author

Ascensão, Fernando, Grilo, Clara, and Santos-Reis, Margarida

Subjects
habitat, fragmentation, landscape, road-killing, cork oak
Abstract

Habitat loss and fragmentation is generally considered to be the greatest threat worldwide to the survival of species. Habitat fragmentation is a process generally regarded as comprising three major components: reduction in total area, increase in isolation, and reduction in average size of patches of remnant natural vegetation. Today’s land use practices and road network’s expansion strongly promote habitat fragmentation reducing the habitat availability and its connectivity, which is assumed to strongly influence species occurrence and population survival in fragmented landscapes. Although several studies demonstrated the negative impact of habitat fragmentation, few focused in carnivore species, and particularly in Mediterranean environments. Carnivores’ position in the top of the food webs and their vulnerability to different human activities make this group especially significant in conservation and management actions. Our goal in this study was to assess the influence of human-related variables on the carnivore’s probability of occurrence, according to habitat patch size and isolation, and road network characteristics. Stone marten Martes foina was selected as the model species to investigate the response to cork oak woodland fragmentation, considering that forest dependent species would show a stronger response. Marten species are known to be sensitive to forest fragmentation, although there is some evidence that their response is mainly determined by the level of forest fragmentation and the matrix quality, due to their preference for structurally complex forests to avoid competition and increase den availability. We compared the stone marten response to scent stations located in four large and continuous forest patches (mean 36000 ha, 19 sampling sites) and in 25 smaller and isolated forest patches (mean 2.67 ha, one sampling site). For each sampling site a variable number of scent stations was used (average=11, min=7, max=17) depending on the patch size. Using the software PRESENCE we developed models that best fit stone marten probability of presence. This method parallels a closed-population mark–recapture model with an additional parameter (Phi) that represents the probability of species presence. Also, it enables the introduction of covariate information using a logistic model for Phi. Nine human and road related variables were used to develop models that best fit stone marten probability of occurrence in the smaller and isolated patches. The best models were selected using the Aikaike Information Criteria. Each variable importance was assessed by summing the AIC model weights (w) in which it was included. A data set of eighty stone marten road-kill locations and of eighty points randomly distributed along the sampled roads was used to evaluate if there were significant differences (one factor ANOVA), regarding the models’ most important variables on the road casualties locations. Results suggest that the probability of presence of stone marten in larger and continuous patches was 90%, while for the smaller and isolated patches it decreases to 60%. Nine significant models were retained. Models evidenced that the probability of presence of stone marten in isolated patches is related to cork oak density (+) (w=0.73), distance to nearest patch (-) (w=0.67), distance to nearest large patch (-) (w=0.56), distance to roads with medium/higher traffic volume (+) (w=0.37), and distance to riparian galleries (-) (w=0.12). Moreover, we detected that road kills were also significantly related to higher forest area surrounding the road (F=7.37, d.f.=1, P

Published
2007

20. Spatial patterns of road kills: a case study in Southern Portugal

Author

Ascensão, Fernando and Mira, António

Subjects
collisions, wildlife ecological, vertebrate, road kill, roadkill
Abstract

Roads promote high levels of animal-vehicle collisions and have one of the most visible man-made impacts on wildlife. In Portugal, SW Europe, very few ecological studies have focused on the impacts from roads on vertebrates. Knowledge of the main factors driving the emergence of hotspots of vertebrate mortality is still scarce. A segment of a main road 26-km long was sampled by car at an average speed of 20 km/h every two weeks for two years (54 surveys) between 1995 and 1997, collecting all road-killed specimens found. We defined road sections with high collision rates, or vertebrate-mortality hotspots (VMH), by detecting clusters of animal collision locations. The analysis was conducted by comparing the spatial pattern of road kills with that expected in a random situation. In such a condition, the likelihood of collisions for each road section would show a Poisson distribution. Differences of explanatory variables between hotspots and low-mortality sections were evaluated with the Mann-Whitney U-test. Also, a direct-gradient analysis (Canonical Correspondence Analysis (CCA)) was executed with the mortality rates of the 24 most-killed species and the explanatory variables considered. A total of 2421 vertebrate road-killed specimens were collected, which corresponded to nearly 46 specimens per 0.5 km per year. Eighty non-domestic species were recorded. Several sections were defined as VMH, both for all observations and for each vertebrate class. Results suggested that some road sections should receive particular mitigation actions given that mortality hotspots may arise, particularly sections where montado is the dominant habitat and where stream and other water courses run nearby and parallel to the road.

Published
2005

27. Power line electrocution as an overlooked threat to Lear's Macaw (Anodorhynchus leari).

Author

Biasotto, Larissa D., Pacífico, Erica C., Paschotto, Fernanda R., Filadelfo, Thiago, Couto, Maíla B., Sousa, Antonio Emanuel B. A., Mantovani, Plinio, Silveira, Luis Fábio, Ascensão, Fernando, Tella, José L., and Kindel, Andreas

Subjects
ELECTRIC lines, ELECTROCUTION, MACAWS, ENDANGERED species, BIRD conservation
Abstract

Copyright of Ibis is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2023
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30. Are road-kills representative of wildlife community obtained from atlas data?

Author

Quiles Tundidor, Pablo, Ascensão, Fernando, D'Amico, Marcello, Revilla, Eloy, Barrientos, Rafael, Comunidad de Madrid, Quiles, Pablo [0000-0002-3622-8184], Ascensão, Fernando [0000-0003-1704-0212], D’Amico, Marcello [0000-0002-0573-9184], Revilla, Eloy [0000-0001-5534-5581], Barrientos, Rafael [0000-0002-1677-3214], Repositório da Universidade de Lisboa, Quiles, Pablo, Ascensão, Fernando, D’Amico, Marcello, Revilla, Eloy, and Barrientos, Rafael

Subjects
carnivores, Road ecology, citizen science, Atlas data, wildlife-vehicle collisions, human activities
Abstract

Systematic road-kill surveys are useful to study the impact of roads on wildlife. However, they are time-and budget-consuming, so the use of non-systematic data in road ecology is currently gaining popularity (for instance, by environmental consultants). Some data sources such as atlases (i.e., compilations of species records from a given region), which can include non-systematic and citizen-science data, can entail several intrinsic biases, mostly due to uneven sampling effort and uneven species detectability. Here, we tested this prediction by verifying if data from the Spanish Atlas of Terrestrial Mammals mirror the road-kill patterns obtained from our own systematic roadkill surveys. We focused on the Mediterranean mesocarnivore guild due to its easy identification by citizens involved in atlas-data collection. We tested if the relative abundance of each species, their richness and diversity obtained from Atlas and our systematic surveys were related, using linear models, while controlling for human population and road density (potentially confounding effects). We further compared the patterns of species abundance obtained from both sources. Our results highlight that road-kill patterns do not mirror the Atlas patterns for the three metrics evaluated. This is probably due to survey biases in typical data from wildlife atlases. When analysing species individually, we found that some species are road-killed more (or less) than expected in relation to their abundance in atlas records. These results are probably due to species-specific ecological or behavioural traits such as species morphology or species behaviour when facing the road. We suggest that abundance from atlas data should not be used as a proxy for road-kill rates., PQ and RB were supported by Comunidad de Madrid (2018T1/AMB10374), FA by Fundacão da Ciência e Tecnologia (SFRH/BPD/115968/ 2016), and MD benefited from a Fundacão da Ciência e Tecnologia postdoctoral contract (CEECIND/03798/2017).

Published
2021

31. Silent·Cities

Author

Challéat, Samuel, Farrugia, Nicolas, Gasc, Amandine, Froidevaux, Jeremy, Hatlauf, Jennifer, Dziock, Frank, CHARBONNEAU, Adrien, Linossier, Juliette, Watson, Christopher, Ullrich, Paul, Jůnek, Tomáš, Hulme, Mark, Deoniziak, Krzysztof, Marchais, Guillaume, Gattus, Jean-Christophe, Beason, Richard, López-Baucells, Adrià, Cibulka, Jan, Barbaro, Luc, VIVAT, Agnès, Sandfort, Robin, Médoc, Vincent, da Silva, Luis, Dodgin, Sarah, Briggs, Philip, Linhart, Pavel, Eldridge, Alice, Mueller, Sandra, Gomez, Oscar, BURENS, albane, Puechmaille, Sébastien, Savage, David, Balbuena, Diego, López-Bosch, David, Belshaw, Simon, Cortes, Eliana, Barbier, Eder, Finch, Domhnall, Ceuppens, Ada, Couturier, Clément, Peyronnet, Peyronnet, Vidal Oliveras, Josep, Moreno-Gómez, Felipe, Jones, Steve, Pajusco, Nicolas, Godet, Laurent, Griesberger, Paul, Hintze, Frederico, Thierry, Besche, Ocampo, David, garcia, juan, Belá, Gívan, Bader, Elias, Jégou, Laurent, Bedoya, Daniela, VINET, Olivier, Gilmour, Lia, VRIGNAULT, Jean-Do., Cardoso, Paulo, Sinclair, Peter, Reginster, Jean-Benoît, Abrahams, Carlos, Tarrant, Ian, Acevedo-Charry, Orlando, Colón-Piñeiro, Zuania, Rocha, Ricardo, Tuninetti, Amaro, Victor, Pierre, Scherer-Lorenzen, Michael, Navarro, Carolina, Wearn, Oliver, Quinn, John, Machado, Ricardo, Challéat, Alain, Matheu, Eloisa, Brinkkemper, Joost, Bredewold, Wijnand, Beeston, Amy, Dubset, Chloé, Lauvin, Gregoire, Elliott, David, Davis, Thomas, Quiroga, Nancy, latifi, milad, Amorim, Francisco, Lace, Natalija, Romaine, Luke, Simon, Victoire, Tucker, David, Ferreira, Diogo, Claus, Caroline, Alice, Baudouin, Thompson, Michelle, Newton, Adrian, Durán, Cárol, Schai-Braun, Stéphanie, Clavijo-Bustos, Julián, Nyssen, Pierrette, Korstjens, Amanda, Deans, Sarah, Drolet, Bruno, Marion, PARISOT, Jacobs, Michel, Lizcano, Diego, Townsend, Karina, Canavero, Andrés, Esztl, Karl, Whyte, Damion, Payor, Eve, sebag, mathilde, Habib, Bilal, Reckinger, Georges, Conde, Sofia, Shaw, Taylor, O'Mara, M., Freitas, Bárbara, Montagne, Basile, Lopes, Ricardo, David, PAPAÏX, Villén-Pérez, Sara, Quentin, Rouy, Aucoin, Serge, Garside, Daniel, Ouertani, Marcolin, Fabio, Godart, Louis, Pinto, Nuno, BELTRAN, JUAN, López-Bao, José, Prugh, Laura, Charnaux, Mina, Marques, Carina, PHILIPPE, Magali, Cusack, Peter, Budinski, Ivana, Roos, Andrei, Martin, Tilla, Paiva, Vitor, Sadhukhan, Sougata, Ferreira, Daniel, Duarte, Marina, Pereira, Jorge, Laranjeiras, Thiago, Mackenzie, Michelle, Soto, Juan, Poff, Zach, Cotão, António, Puccherelli, Ignacio, Santos, Ivo, O'Connell, Darren, haupert, sylvain, Aguiar, Ludmilla, Sébastien, LAGUET, Ducruet, Sylvain, PALACINO, JULIAN, Naka, Luciano, Kitson, James, Windsor, Fredric, Beckmann, Christa, Quaglietta, Lorenzo, Templeton, Christopher, Mande, Claude, Elise, Simon, Vega, Kevin, Owren, Jan, Herrera, José, Geoffray, Ferreira, Sonia, Walton, William, Barreiro, Sílvia, Draganoiu, Tudor-Ion, Nunes, João, Villagra, Jose, Carrasco-Rueda, Farah, Segurado, Pedro, de Lacoste, Nathalie, Alves, Flávia, Briglia-Ferreira, Sylvio, Ascensão, Fernando, Poppele, Jonathan, Aiple, Franz, Ross, Samuel, R, PAULA, Rodríguez-González, Patricia, ENGUEHARD, Arthur, Albert, Cécile, Rivera, Vanesa, Levenson, Jacob, Fialas, Penelope, PARIS, Stephane, Bossaert, Mathieu, Khanwilkar, Sarika, Ventrice, Gabriella, Garcia, Fernando, Lavin, Samuel, Buxton, Rachel, Miller, Leah, Ahlin, Zachary, Bates, Henry, Bradley, Ally, Whitten, Hunter, Larrea, Angela, Herzberger, Sierra, Reed, Mimi, Ryser, Alyssa, Foster-Shaner, Lauren, Hallet, Maddy, Buckner, Emily, Todd, Marcela, Ovale, Fenêtre, Hoecherl, Isabelle, WU, Yanchen, Moreno, JoMari, Marques, J., Xie, Selena, Whiteside, Courtney, Martin, Nate, Dickinson, Paul, Araújo, Pedro, Marcaigh, Fionn, Moore, Allen, Patankar, Swaroop, Hodder, Kathy, Marques, Inês, Beltrão-Mendes, Raone, Power, Andrew, Miller, Kirsten, Dentin, Serge, Cerveira, Lara, Evans, Darren, Duarte, Gonçalo, Choksi, Pooja, Lopes, Pedro, Proppe, Darren, Serronha, Ana, Krähenbühl-Künzli, Kim, Llusia, Diego, Lockett, Marty, Puig-Montserrat, Xavier, Bellisario, Kristen, Pijanowski, Bryan, Tattersall, Fran, Branco, Paulo, Biro, Peter, Santos, José, Khalatbari, Leili, Silva, Bruno, de Almeida Scarpelli, Marina, DE ALMEIDA SCARPELLI, MARINA, Boléat, Cathie, Hyland, Emilia, Zina, Vera, Costa, Maria, Friedman, Nicholas, Lankau, Hedwig, Braz, Luís, Sueur, Jerome, BARRIE, LUIS, and GALOP, Didier

Subjects
landscape ecology, SARS-CoV-2, noise pollution, social distancing, deep learning, audioset, urban planning, bioacoustics, ecoacoustics, audio tagging, machine learning, urban ecology, 2019-nCoV, soundscape ecology, environmental geography, urban wildlife
Abstract

A participatory monitoring programme of an exceptional modification of urban soundscapes during Covid-19 containment (Data collection in progress)

Published
2022
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32. Power line electrocution as an overlooked threat to Lear's Macaw ( Anodorhynchus leari )

Author

Biasotto, Larissa D., primary, Pacífico, Erica C., additional, Paschotto, Fernanda R., additional, Filadelfo, Thiago, additional, Couto, Maíla B., additional, Sousa, Antonio Emanuel B. A., additional, Mantovani, Plinio, additional, Silveira, Luis Fábio, additional, Ascensão, Fernando, additional, Tella, José L., additional, and Kindel, Andreas, additional

Published
2022
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35. 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

37. How trade policy can support the climate agenda

Author

Jakob, Michael, primary, Afionis, Stavros, additional, Åhman, Max, additional, Antoci, Angelo, additional, Arens, Marlene, additional, Ascensão, Fernando, additional, van Asselt, Harro, additional, Baumert, Nicolai, additional, Borghesi, Simone, additional, Brunel, Claire, additional, Caron, Justin, additional, Cosbey, Aaron, additional, Droege, Susanne, additional, Evans, Alecia, additional, Iannucci, Gianluca, additional, Jiborn, Magnus, additional, Kander, Astrid, additional, Kulionis, Viktoras, additional, Levinson, Arik, additional, de Melo, Jaime, additional, Moerenhout, Tom, additional, Monti, Alessandro, additional, Panezi, Maria, additional, Quirion, Philippe, additional, Sager, Lutz, additional, Sakai, Marco, additional, Sesmero, Juan, additional, Sodini, Mauro, additional, Solleder, Jean-Marc, additional, Verkuijl, Cleo, additional, Vogl, Valentin, additional, Wenz, Leonie, additional, and Willner, Sven, additional

Published
2022
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39. Native and alien grassland diversity respond differently to environmental and anthropogenic drivers across spatial scales

Author

Bergamin, Rodrigo Scarton, primary, Ascensão, Fernando, additional, Capinha, César, additional, Bastazini, Vinicius Augusto Galvão, additional, Andrade, Bianca Ott, additional, Boldrini, Ilsi Iob, additional, Lezama, Felipe, additional, Altesor, Alice, additional, Perelman, Susana, additional, and Overbeck, Gerhard Ernst, additional

Published
2022
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40. 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

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2022
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