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1. Thresholds for adding degraded tropical forest to the conservation estate

Author

Ewers, Robert M., Orme, C. David L., Pearse, William D., Zulkifli, Nursyamin, Yvon-Durocher, Genevieve, Yusah, Kalsum M., Yoh, Natalie, Yeo, Darren C. J., Wong, Anna, Williamson, Joseph, Wilkinson, Clare L., Wiederkehr, Fabienne, Webber, Bruce L., Wearn, Oliver R., Wai, Leona, Vollans, Maisie, Twining, Joshua P., Turner, Edgar C., Tobias, Joseph A., Thorley, Jack, Telford, Elizabeth M., Teh, Yit Arn, Tan, Heok Hui, Swinfield, Tom, Svátek, Martin, Struebig, Matthew, Stork, Nigel, Sleutel, Jani, Slade, Eleanor M., Sharp, Adam, Shabrani, Adi, Sethi, Sarab S., Seaman, Dave J. I., Sawang, Anati, Roxby, Gabrielle Briana, Rowcliffe, J. Marcus, Rossiter, Stephen J., Riutta, Terhi, Rahman, Homathevi, Qie, Lan, Psomas, Elizabeth, Prairie, Aaron, Poznansky, Frederica, Pillay, Rajeev, Picinali, Lorenzo, Pianzin, Annabel, Pfeifer, Marion, Parrett, Jonathan M., Noble, Ciar D., Nilus, Reuben, Mustaffa, Nazirah, Mullin, Katherine E., Mitchell, Simon, Mckinlay, Amelia R., Maunsell, Sarah, Matula, Radim, Massam, Michael, Martin, Stephanie, Malhi, Yadvinder, Majalap, Noreen, Maclean, Catherine S., Mackintosh, Emma, Luke, Sarah H., Lewis, Owen T., Layfield, Harry J., Lane-Shaw, Isolde, Kueh, Boon Hee, Kratina, Pavel, Konopik, Oliver, Kitching, Roger, Kinneen, Lois, Kemp, Victoria A., Jotan, Palasiah, Jones, Nick, Jebrail, Evyen W., Hroneš, Michal, Heon, Sui Peng, Hemprich-Bennett, David R., Haysom, Jessica K., Harianja, Martina F., Hardwick, Jane, Gregory, Nichar, Gray, Ryan, Gray, Ross E. J., Granville, Natasha, Gill, Richard, Fraser, Adam, Foster, William A., Folkard-Tapp, Hollie, Fletcher, Robert J., Fikri, Arman Hadi, Fayle, Tom M., Faruk, Aisyah, Eggleton, Paul, Edwards, David P., Drinkwater, Rosie, Dow, Rory A., Döbert, Timm F., Didham, Raphael K., Dickinson, Katharine J. M., Deere, Nicolas J., de Lorm, Tijmen, Dawood, Mahadimenakbar M., Davison, Charles W., Davies, Zoe G., Davies, Richard G., Dančák, Martin, Cusack, Jeremy, Clare, Elizabeth L., Chung, Arthur, Chey, Vun Khen, Chapman, Philip M., Cator, Lauren, Carpenter, Daniel, Carbone, Chris, Calloway, Kerry, Bush, Emma R., Burslem, David F. R. P., Brown, Keiron D., Brooks, Stephen J., Brasington, Ella, Brant, Hayley, Boyle, Michael J. W., Both, Sabine, Blackman, Joshua, Bishop, Tom R., Bicknell, Jake E., Bernard, Henry, Basrur, Saloni, Barclay, Maxwell V. L., Barclay, Holly, Atton, Georgina, Ancrenaz, Marc, Aldridge, David C., Daniel, Olivia Z., Reynolds, Glen, and Banks-Leite, Cristina

Published
2024
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5. Socio-ecological factors shape the distribution of a cultural keystone species in Malaysian Borneo

Author

Kurz, David J., Connor, Thomas, Brodie, Jedediah F., Baking, Esther L., Szeto, Sabrina H., Hearn, Andrew J., Gardner, Penny C., Wearn, Oliver R., Deith, Mairin C. M., Deere, Nicolas J., Ampeng, Ahmad, Bernard, Henry, Goon, Jocelyn, Granados, Alys, Helmy, Olga, Lim, Hong-Ye, Luskin, Matthew Scott, Macdonald, David W., Ross, Joanna, Simpson, Boyd K., Struebig, Matthew J., Mohd-Azlan, Jayasilan, Potts, Matthew D., Goossens, Benoit, and Brashares, Justin S.

Published
2023
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6. Landscape-scale benefits of protected areas for tropical biodiversity

Author

Brodie, Jedediah F., Mohd-Azlan, Jayasilan, Chen, Cheng, Wearn, Oliver R., Deith, Mairin C. M., Ball, James G. C., Slade, Eleanor M., Burslem, David F. R. P., Teoh, Shu Woan, Williams, Peter J., Nguyen, An, Moore, Jonathan H., Goetz, Scott J., Burns, Patrick, Jantz, Patrick, Hakkenberg, Christopher R., Kaszta, Zaneta M., Cushman, Sam, Coomes, David, Helmy, Olga E., Reynolds, Glen, Rodríguez, Jon Paul, Jetz, Walter, and Luskin, Matthew Scott

Published
2023
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7. Author Correction: Landscape-scale benefits of protected areas for tropical biodiversity

Author

Brodie, Jedediah F., Mohd-Azlan, Jayasilan, Chen, Cheng, Wearn, Oliver R., Deith, Mairin C. M., Ball, James G. C., Slade, Eleanor M., Burslem, David F. R. P., Teoh, Shu Woan, Williams, Peter J., Nguyen, An, Moore, Jonathan H., Goetz, Scott J., Burns, Patrick, Jantz, Patrick, Hakkenberg, Christopher R., Kaszta, Zaneta M., Cushman, Sam, Coomes, David, Helmy, Olga E., Reynolds, Glen, Rodríguez, Jon Paul, Jetz, Walter, and Luskin, Matthew Scott

Published
2024
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8. Publisher Correction: Landscape-scale benefits of protected areas for tropical biodiversity

Author

Brodie, Jedediah F., Mohd-Azlan, Jayasilan, Chen, Cheng, Wearn, Oliver R., Deith, Mairin C. M., Ball, James G. C., Slade, Eleanor M., Burslem, David F. R. P., Teoh, Shu Woan, Williams, Peter J., Nguyen, An, Moore, Jonathan H., Goetz, Scott J., Burns, Patrick, Jantz, Patrick, Hakkenberg, Christopher R., Kaszta, Zaneta M., Cushman, Sam, Coomes, David, Helmy, Olga E., Reynolds, Glen, Rodríguez, Jon Paul, Jetz, Walter, and Luskin, Matthew Scott

Published
2024
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10. CamTrapAsia: A dataset of tropical forest vertebrate communities from 239 camera trapping studies

Author

Mendes, Calebe P., primary, Albert, Wido R., additional, Amir, Zachary, additional, Ancrenaz, Marc, additional, Ash, Eric, additional, Azhar, Badrul, additional, Bernard, Henry, additional, Brodie, Jedediah, additional, Bruce, Tom, additional, Carr, Elliot, additional, Clements, Gopalasamy Reuben, additional, Davies, Glyn, additional, Deere, Nicolas J., additional, Dinata, Yoan, additional, Donnelly, Christl A., additional, Duangchantrasiri, Somphot, additional, Fredriksson, Gabriella, additional, Goossens, Benoit, additional, Granados, Alys, additional, Hearn, Andrew, additional, Hon, Jason, additional, Hughes, Tom, additional, Jansen, Patrick, additional, Kawanishi, Kae, additional, Kinnaird, Margaret, additional, Koh, Sharon, additional, Latinne, Alice, additional, Linkie, Matthew, additional, Loi, Federica, additional, Lynam, Anthony J., additional, Meijaard, Erik, additional, Mohd‐Azlan, Jayasilan, additional, Moore, Jonathan H., additional, Nathan, Senthilvel K. S. S., additional, Ngoprasert, Dusit, additional, Novarino, Wilson, additional, Nursamsi, Ilyas, additional, O'Brien, Timothy, additional, Ong, Robert, additional, Payne, John, additional, Priatna, Dolly, additional, Rayan, D. Mark, additional, Reynolds, Glen, additional, Rustam, Rustam, additional, Selvadurai, Sasidhran, additional, Shia, Amanda, additional, Silmi, Muhammad, additional, Sinovas, Pablo, additional, Sribuarod, Kriangsak, additional, Steinmetz, Robert, additional, Struebig, Matthew J., additional, Sukmasuang, Ronglarp, additional, Sunarto, Sunarto, additional, Tarmizi, Tarmizi, additional, Thapa, Arjun, additional, Traeholt, Carl, additional, Wearn, Oliver R., additional, Wibisono, Hariyo B., additional, Wilting, Andreas, additional, Wong, Seth Timothy, additional, Wong, Siew Te, additional, Word, Jettie, additional, Chiok, Wen Xuan, additional, Zainuddin, Zainal Zahari, additional, and Luskin, Matthew Scott, additional

Published
2024
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11. Reasoning About Neural Network Activations: An Application in Spatial Animal Behaviour from Camera Trap Classifications

Author

Evans, Benjamin C., Tucker, Allan, Wearn, Oliver R., Carbone, Chris, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Koprinska, Irena, editor, Kamp, Michael, editor, Appice, Annalisa, editor, Loglisci, Corrado, editor, Antonie, Luiza, editor, Zimmermann, Albrecht, editor, Guidotti, Riccardo, editor, Özgöbek, Özlem, editor, Ribeiro, Rita P., editor, Gavaldà, Ricard, editor, Gama, João, editor, Adilova, Linara, editor, Krishnamurthy, Yamuna, editor, Ferreira, Pedro M., editor, Malerba, Donato, editor, Medeiros, Ibéria, editor, Ceci, Michelangelo, editor, Manco, Giuseppe, editor, Masciari, Elio, editor, Ras, Zbigniew W., editor, Christen, Peter, editor, Ntoutsi, Eirini, editor, Schubert, Erich, editor, Zimek, Arthur, editor, Monreale, Anna, editor, Biecek, Przemyslaw, editor, Rinzivillo, Salvatore, editor, Kille, Benjamin, editor, Lommatzsch, Andreas, editor, and Gulla, Jon Atle, editor

Published
2020
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12. CamTrapAsia : A dataset of tropical forest vertebrate communities from 239 camera trapping studies

Author

Mendes, Calebe P., Albert, Wido R., Amir, Zachary, Ancrenaz, Marc, Ash, Eric, Azhar, Badrul, Bernard, Henry, Brodie, Jedediah, Bruce, Tom, Carr, Elliot, Clements, Gopalasamy Reuben, Davies, Glyn, Deere, Nicolas J., Dinata, Yoan, Donnelly, Christl A., Duangchantrasiri, Somphot, Fredriksson, Gabriella, Goossens, Benoit, Granados, Alys, Hearn, Andrew, Hon, Jason, Hughes, Tom, Jansen, Patrick, Kawanishi, Kae, Kinnaird, Margaret, Koh, Sharon, Latinne, Alice, Linkie, Matthew, Loi, Federica, Lynam, Anthony J., Meijaard, Erik, Mohd-Azlan, Jayasilan, Moore, Jonathan H., Nathan, Senthilvel K.S.S., Ngoprasert, Dusit, Novarino, Wilson, Nursamsi, Ilyas, O'Brien, Timothy, Ong, Robert, Payne, John, Priatna, Dolly, Rayan, Mark, Reynolds, Glen, Rustam, Rustam, Selvadurai, Sasidhran, Shia, Amanda, Silmi, Muhammad, Sinovas, Pablo, Sribuarod, Kriangsak, Steinmetz, Robert, Struebig, Matthew J., Sukmasuang, Ronglarp, Sunarto, Sunarto, Tarmizi, Tarmizi, Thapa, Arjun, Traeholt, Carl, Wearn, Oliver R., Wibisono, Hariyo B., Wilting, Andreas, Wong, Seth Timothy, Wong, Siew Te, Word, Jettie, Chiok, Wen Xuan, Zainuddin, Zainal Zahari, Luskin, Matthew Scott, Mendes, Calebe P., Albert, Wido R., Amir, Zachary, Ancrenaz, Marc, Ash, Eric, Azhar, Badrul, Bernard, Henry, Brodie, Jedediah, Bruce, Tom, Carr, Elliot, Clements, Gopalasamy Reuben, Davies, Glyn, Deere, Nicolas J., Dinata, Yoan, Donnelly, Christl A., Duangchantrasiri, Somphot, Fredriksson, Gabriella, Goossens, Benoit, Granados, Alys, Hearn, Andrew, Hon, Jason, Hughes, Tom, Jansen, Patrick, Kawanishi, Kae, Kinnaird, Margaret, Koh, Sharon, Latinne, Alice, Linkie, Matthew, Loi, Federica, Lynam, Anthony J., Meijaard, Erik, Mohd-Azlan, Jayasilan, Moore, Jonathan H., Nathan, Senthilvel K.S.S., Ngoprasert, Dusit, Novarino, Wilson, Nursamsi, Ilyas, O'Brien, Timothy, Ong, Robert, Payne, John, Priatna, Dolly, Rayan, Mark, Reynolds, Glen, Rustam, Rustam, Selvadurai, Sasidhran, Shia, Amanda, Silmi, Muhammad, Sinovas, Pablo, Sribuarod, Kriangsak, Steinmetz, Robert, Struebig, Matthew J., Sukmasuang, Ronglarp, Sunarto, Sunarto, Tarmizi, Tarmizi, Thapa, Arjun, Traeholt, Carl, Wearn, Oliver R., Wibisono, Hariyo B., Wilting, Andreas, Wong, Seth Timothy, Wong, Siew Te, Word, Jettie, Chiok, Wen Xuan, Zainuddin, Zainal Zahari, and Luskin, Matthew Scott

Abstract

Information on tropical Asian vertebrates has traditionally been sparse, particularly when it comes to cryptic species inhabiting the dense forests of the region. Vertebrate populations are declining globally due to land-use change and hunting, the latter frequently referred as “defaunation.” This is especially true in tropical Asia where there is extensive land-use change and high human densities. Robust monitoring requires that large volumes of vertebrate population data be made available for use by the scientific and applied communities. Camera traps have emerged as an effective, non-invasive, widespread, and common approach to surveying vertebrates in their natural habitats. However, camera-derived datasets remain scattered across a wide array of sources, including published scientific literature, gray literature, and unpublished works, making it challenging for researchers to harness the full potential of cameras for ecology, conservation, and management. In response, we collated and standardized observations from 239 camera trap studies conducted in tropical Asia. There were 278,260 independent records of 371 distinct species, comprising 232 mammals, 132 birds, and seven reptiles. The total trapping effort accumulated in this data paper consisted of 876,606 trap nights, distributed among Indonesia, Singapore, Malaysia, Bhutan, Thailand, Myanmar, Cambodia, Laos, Vietnam, Nepal, and far eastern India. The relatively standardized deployment methods in the region provide a consistent, reliable, and rich count data set relative to other large-scale pressence-only data sets, such as the Global Biodiversity Information Facility (GBIF) or citizen science repositories (e.g., iNaturalist), and is thus most similar to eBird. To facilitate the use of these data, we also provide mammalian species trait information and 13 environmental covariates calculated at three spatial scales around the camera survey centroids (within 10-, 20-, and 30-km buffers). We will update the da

Published
2024

13. AI reflections in 2019

Author

Rich, Alexander S., Rudin, Cynthia, Jacoby, David M. P., Freeman, Robin, Wearn, Oliver R., Shevlin, Henry, Dihal, Kanta, ÓhÉigeartaigh, Seán S., Butcher, James, Lippi, Marco, Palka, Przemyslaw, Torroni, Paolo, Wongvibulsin, Shannon, Begoli, Edmon, Schneider, Gisbert, Cave, Stephen, Sloane, Mona, Moss, Emmanuel, Rahwan, Iyad, Goldberg, Ken, Howard, David, Floridi, Luciano, and Stilgoe, Jack

Published
2020
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14. Estimating animal density using the Space‐to‐Event model and bootstrap resampling with motion‐triggered camera‐trap data.

Author

Lyet, Arnaud, Waller, Scott, Chambert, Thierry, Acevedo, Pelayo, Howe, Eric, Kühl, Hjalmar S., Naidoo, Robin, O'Brien, Timothy, Palencia, Pablo, Soutyrina, Svetlana V., Vicente, Joaquin, Wearn, Oliver R., and Gray, Thomas N. E.

Subjects
ANIMAL tagging, POPULATION density, DENSITY, ZOOARCHAEOLOGY, REGRESSION analysis
Abstract

Over the past few decades, the use of camera‐traps has revolutionized our ability to monitor populations of wild terrestrial mammals. While methods to estimate abundance from individually‐identifiable animals are well‐established, they are mostly restricted to species with clear natural markings or else necessitate invasive and often costly animal tagging campaigns. Estimating abundance or density from unmarked animals remains challenging. Several models recently developed to deal with this issue are promising, but are not widely used by field ecologists. Here, we developed a framework for applying the Space‐To‐Event (STE) model—originally designed to be used with time‐lapse images—on motion‐triggered camera‐trap data. Our approach involves performing bootstrap resampling on the photographic dataset to generate multiple datasets that are then used as input to the STE model. We tested our approach on 29 datasets, including 17 ungulate species from eight sites, in six different countries and various ecosystems. Then, we conducted a regression analysis to evaluate how variations in ecological and sampling conditions across studies affected the bias and precision of our STE density estimates. Our study shows that with a bootstrap resampling approach and information on animal activity and effective detection distances to animals, the STE model can be used to analyze motion‐trigger datasets and provide population density estimates that are similar to those from other methods. We found that measuring the camera viewshed was critical to prevent major negative biases in density estimates. Moreover, using a 1‐s sampling window was important to avoid the positive bias that results from violating the instantaneous‐sampling assumption. We found that precision increased with greater sampling effort and higher density populations. Based on these results, we highlight several issues from past studies that have applied the original timelapse‐based STE to motion‐trigger datasets, issues that our bootstrap resampling approach addresses. We caution that the STE model, whether applied to timelapse or motion‐triggered datasets, relies on strict assumptions. Any violations of these assumptions, such as non‐instantaneous sampling or the application of angle and distance of detection provided by the camera manufacturer, can cause biases in multiple directions that may be difficult to differentiate. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Using global remote camera data of a solitary species complex to evaluate the drivers of group formation.

Author

Twining, Joshua P., Sutherland, Chris, Zalewski, Andrzej, Cove, Michael V., Birks, Johnny, Wearn, Oliver R., Haysom, Jessica, Wereszczuk, Anna, Manzo, Emiliano, Bartolommei, Paola, Mortelliti, Alessio, Evans, Bryn, Gerber, Brian D., McGreevy Jr., Thomas J., Ganoe, Laken S., Masseloux, Juliana, Mayer, Amy E., Wierzbowska, Izabela, Loch, Jan, and Akins, Jocelyn

Subjects
GROUP formation, NATURAL history, CAMERAS, SPECIES, MUSTELIDAE
Abstract

The social system of animals involves a complex interplay between physiology, natural history, and the environment. Long relied upon discrete categorizations of "social" and "solitary" inhibit our capacity to understand species and their interactions with the world around them. Here, we use a globally distributed camera trapping dataset to test the drivers of aggregating into groups in a species complex (martens and relatives, family Mustelidae, Order Carnivora) assumed to be obligately solitary. We use a simple quantification, the probability of being detected in a group, that was applied across our globally derived camera trap dataset. Using a series of binomial generalized mixed-effects models applied to a dataset of 16,483 independent detections across 17 countries on four continents we test explicit hypotheses about potential drivers of group formation. We observe a wide range of probabilities of being detected in groups within the solitary model system, with the probability of aggregating in groups varying by more than an order of magnitude. We demonstrate that a species' context-dependent proclivity toward aggregating in groups is underpinned by a range of resource-related factors, primarily the distribution of resources, with increasing patchiness of resources facilitating group formation, as well as interactions between environmental conditions (resource constancy/winter severity) and physiology (energy storage capabilities). The wide variation in propensities to aggregate with conspecifics observed here highlights how continued failure to recognize complexities in the social behaviors of apparently solitary species limits our understanding not only of the individual species but also the causes and consequences of group formation. [ABSTRACT FROM AUTHOR]

Published
2024
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16. UAV-assisted counts of group size facilitate accurate population surveys of the Critically Endangered cao vit gibbon Nomascus nasutus.

Author

Wearn, Oliver R., Trinh-Dinh, Hoang, Le, Quyet Khac, and Nguyen, Tho Duc

Subjects
*DEMOGRAPHIC surveys, *RHESUS monkeys, *ENDANGERED species, *INFANTS, *MACAQUES
Abstract

Gibbons are often difficult to observe in dense forest habitats using traditional ground-based methods. This makes it challenging to estimate group sizes and, in turn, population sizes. This has proven to be a key constraint on accurate monitoring of the last remaining population of the Critically Endangered cao vit gibbon Nomascus nasutus. However, new technologies are beginning to circumvent the problems associated with traditional methods. We hypothesized that, by using an unoccupied aerial vehicle (UAV) equipped with thermal and standard (RGB) cameras, we could obtain more accurate group size counts than by using ground-based observations, as fewer gibbons would be missed. We tested this during a population survey of the cao vit gibbon, finding that the thermal video footage revealed additional individuals that were not counted by ground-based surveyors. Statistically, there was strong evidence (93% probability) that UAV-derived counts were higher (by 41%) than concurrent ground-based counts. We recorded six primate groups of three species (cao vit gibbon, rhesus macaque Macaca mulatta and Assamese macaque Macaca assamensis), including 24 gibbons across four groups (c. 20% of the global population). The RGB video footage also revealed seven female gibbons, two of which were carrying infants, providing vital group composition data. These data have contributed directly to a more accurate population survey of the species than would have been possible using direct observation only. We anticipate more widespread use of UAVs in the study of gibbons and other threatened species, leading to a more robust evidence base for their conservation. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Estimating animal density using the Space‐to‐Event model and bootstrap resampling with motion‐triggered camera‐trap data

Author

Lyet, Arnaud, primary, Waller, Scott, additional, Chambert, Thierry, additional, Acevedo, Pelayo, additional, Howe, Eric, additional, Kühl, Hjalmar S., additional, Naidoo, Robin, additional, O'Brien, Timothy, additional, Palencia, Pablo, additional, Soutyrina, Svetlana V., additional, Vicente, Joaquin, additional, Wearn, Oliver R., additional, and Gray, Thomas N. E., additional

Published
2023
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28. Estimating animal density for a community of species using information obtained only from camera‐traps

Author

Wearn, Oliver R., Bell, Thomas E. M., Bolitho, Adam, Durrant, James, Haysom, Jessica K., Nijhawan, Sahil, Thorley, Jack, Rowcliffe, J. Marcus, Wearn, Oliver R., Bell, Thomas E. M., Bolitho, Adam, Durrant, James, Haysom, Jessica K., Nijhawan, Sahil, Thorley, Jack, and Rowcliffe, J. Marcus

Abstract

1. Animal density is a fundamental parameter in ecology and conservation, and yet it has remained difficult to measure. For terrestrial mammals and birds, camera-traps have dramatically improved our ability to collect systematic data across a large number of species, but density estimation (except for species with natural marks) is still faced with statistical and logistical hurdles, including the requirement for auxiliary data and large sample sizes, and an inability to incorporate covariates. 2. To fill this gap in the camera-trapper's statistical toolbox, we extended the ex-isting Random Encounter Model (REM) to the multi-species case in a Bayesian framework. This multi-species REM can incorporate covariates and provides pa-rameter estimates for even the rarest species. As input to the model, we used information directly available in the camera-trap data. The model outputs poste-rior distributions for the REM parameters—movement speed, activity level, the effective angle and radius of the camera-trap detection zone, and density—for each species. We applied this model to an existing dataset for 35 species in Borneo, collected across old- growth and logged forest. Here, we added animal position data derived from the image sequences in order to estimate the speed and detection zone parameters. 3. The model revealed a decrease in movement speeds, and therefore day- range, across the species community in logged compared to old- growth forest, whilst activity levels showed no consistent trend. Detection zones were shorter, but of similar width, in logged compared to old- growth forest. Overall, animal density was lower in logged forest, even though most species individually occurred at higher density in logged forest. However, the biomass per unit area was sub-stantially higher in logged compared to old- growth forest, particularly among herbivores and omnivores, likely because of increased resource availability at ground level. We also included body mass as a variable

Published
2022

31. Can CNN‐based species classification generalise across variation in habitat within a camera trap survey?

Author

Norman, Danielle L., Bischoff, Philipp H., Wearn, Oliver R., Ewers, Robert M., Rowcliffe, J. Marcus, Evans, Benjamin, Sethi, Sarab, Chapman, Philip M., and Freeman, Robin

Subjects
HABITATS, IMAGE enhancement (Imaging systems), CONVOLUTIONAL neural networks, ENDANGERED species, CAMERAS, ENVIRONMENTAL monitoring, DIGITAL cameras
Abstract

Camera trap surveys are a popular ecological monitoring tool that produce vast numbers of images making their annotation extremely time‐consuming. Advances in machine learning, in the form of convolutional neural networks, have demonstrated potential for automated image classification, reducing processing time. These networks often have a poor ability to generalise, however, which could impact assessments of species in habitats undergoing change.Here, we (i) compare the performance of three network architectures in identifying species in camera trap images taken from tropical forest of varying disturbance intensities; (ii) explore the impacts of training dataset configuration; (iii) use habitat disturbance categories to investigate network generalisability and (iv) test whether classification performance and generalisability improve when using images cropped to bounding boxes.Overall accuracy (72.8%) was improved by excluding the rarest species and by adding extra training images (76.3% and 82.8%, respectively). Generalisability to new camera locations within a disturbance level was poor (mean F1‐score: 0.32). Performance across unseen habitat disturbance levels was worse (mean F1‐score: 0.27). Training the network on multiple disturbance levels improved generalisability (mean F1‐score on unseen disturbance levels: 0.41). Cropping images to bounding boxes improved overall performance (F1‐score: 0.77 vs. 0.47) and generalisability (mean F1‐score on unseen disturbance levels: 0.73), but at a cost of losing images that contained animals which the detector failed to detect.These results suggest researchers should consider using an object detector before passing images to a classifier, and an improvement in classification might be seen if labelled images from other studies are added to their training data. Composition of training data was shown to be influential, but including rarer classes did not compromise performance on common classes, providing support for the inclusion of rare species to inform conservation efforts. These findings have important implications for use of these methods for long‐term monitoring of habitats undergoing change, as they highlight the potential for misclassifications due to poor generalisability to impact subsequent ecological analyses. These methods therefore need to be considered as dynamic, in that changes to the study site would need to be reflected in the updated training of the network. [ABSTRACT FROM AUTHOR]

Published
2023
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33. SmallSats: a new technological frontier in ecology and conservation?

Author

Curnick, David J., primary, Davies, Alasdair J., additional, Duncan, Clare, additional, Freeman, Robin, additional, Jacoby, David M. P., additional, Shelley, Hugo T. E., additional, Rossi, Cristian, additional, Wearn, Oliver R., additional, Williamson, Michael J., additional, and Pettorelli, Nathalie, additional

Published
2021
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35. Testing a global standard for quantifying species recovery and assessing conservation impact

Author

Grace, Molly K., primary, Akçakaya, H. Resit, additional, Bennett, Elizabeth L., additional, Brooks, Thomas M., additional, Heath, Anna, additional, Hedges, Simon, additional, Hilton‐Taylor, Craig, additional, Hoffmann, Michael, additional, Hochkirch, Axel, additional, Jenkins, Richard, additional, Keith, David A., additional, Long, Barney, additional, Mallon, David P., additional, Meijaard, Erik, additional, Milner‐Gulland, E.J., additional, Rodriguez, Jon Paul, additional, Stephenson, P.J., additional, Stuart, Simon N., additional, Young, Richard P., additional, Acebes, Pablo, additional, Alfaro‐Shigueto, Joanna, additional, Alvarez‐Clare, Silvia, additional, Andriantsimanarilafy, Raphali Rodlis, additional, Arbetman, Marina, additional, Azat, Claudio, additional, Bacchetta, Gianluigi, additional, Badola, Ruchi, additional, Barcelos, Luís M.D., additional, Barreiros, Joao Pedro, additional, Basak, Sayanti, additional, Berger, Danielle J., additional, Bhattacharyya, Sabuj, additional, Bino, Gilad, additional, Borges, Paulo A.V., additional, Boughton, Raoul K., additional, Brockmann, H. Jane, additional, Buckley, Hannah L., additional, Burfield, Ian J., additional, Burton, James, additional, Camacho‐Badani, Teresa, additional, Cano‐Alonso, Luis Santiago, additional, Carmichael, Ruth H., additional, Carrero, Christina, additional, Carroll, John P., additional, Catsadorakis, Giorgos, additional, Chapple, David G., additional, Chapron, Guillaume, additional, Chowdhury, Gawsia Wahidunnessa, additional, Claassens, Louw, additional, Cogoni, Donatella, additional, Constantine, Rochelle, additional, Craig, Christie Anne, additional, Cunningham, Andrew A., additional, Dahal, Nishma, additional, Daltry, Jennifer C., additional, Das, Goura Chandra, additional, Dasgupta, Niladri, additional, Davey, Alexandra, additional, Davies, Katharine, additional, Develey, Pedro, additional, Elangovan, Vanitha, additional, Fairclough, David, additional, Febbraro, Mirko Di, additional, Fenu, Giuseppe, additional, Fernandes, Fernando Moreira, additional, Fernandez, Eduardo Pinheiro, additional, Finucci, Brittany, additional, Földesi, Rita, additional, Foley, Catherine M., additional, Ford, Matthew, additional, Forstner, Michael R.J., additional, García, Néstor, additional, Garcia‐Sandoval, Ricardo, additional, Gardner, Penny C., additional, Garibay‐Orijel, Roberto, additional, Gatan‐Balbas, Marites, additional, Gauto, Irene, additional, Ghazi, Mirza Ghazanfar Ullah, additional, Godfrey, Stephanie S., additional, Gollock, Matthew, additional, González, Benito A., additional, Grant, Tandora D., additional, Gray, Thomas, additional, Gregory, Andrew J., additional, van Grunsven, Roy H.A., additional, Gryzenhout, Marieka, additional, Guernsey, Noelle C., additional, Gupta, Garima, additional, Hagen, Christina, additional, Hagen, Christian A., additional, Hall, Madison B., additional, Hallerman, Eric, additional, Hare, Kelly, additional, Hart, Tom, additional, Hartdegen, Ruston, additional, Harvey‐Brown, Yvette, additional, Hatfield, Richard, additional, Hawke, Tahneal, additional, Hermes, Claudia, additional, Hitchmough, Rod, additional, Hoffmann, Pablo Melo, additional, Howarth, Charlie, additional, Hudson, Michael A., additional, Hussain, Syed Ainul, additional, Huveneers, Charlie, additional, Jacques, Hélène, additional, Jorgensen, Dennis, additional, Katdare, Suyash, additional, Katsis, Lydia K.D., additional, Kaul, Rahul, additional, Kaunda‐Arara, Boaz, additional, Keith‐Diagne, Lucy, additional, Kraus, Daniel T., additional, de Lima, Thales Moreira, additional, Lindeman, Ken, additional, Linsky, Jean, additional, Louis, Edward, additional, Loy, Anna, additional, Lughadha, Eimear Nic, additional, Mangel, Jeffrey C., additional, Marinari, Paul E., additional, Martin, Gabriel M., additional, Martinelli, Gustavo, additional, McGowan, Philip J.K., additional, McInnes, Alistair, additional, Teles Barbosa Mendes, Eduardo, additional, Millard, Michael J., additional, Mirande, Claire, additional, Money, Daniel, additional, Monks, Joanne M., additional, Morales, Carolina Laura, additional, Mumu, Nazia Naoreen, additional, Negrao, Raquel, additional, Nguyen, Anh Ha, additional, Niloy, Md. Nazmul Hasan, additional, Norbury, Grant Leslie, additional, Nordmeyer, Cale, additional, Norris, Darren, additional, O'Brien, Mark, additional, Oda, Gabriela Akemi, additional, Orsenigo, Simone, additional, Outerbridge, Mark Evan, additional, Pasachnik, Stesha, additional, Pérez‐Jiménez, Juan Carlos, additional, Pike, Charlotte, additional, Pilkington, Fred, additional, Plumb, Glenn, additional, Portela, Rita de Cassia Quitete, additional, Prohaska, Ana, additional, Quintana, Manuel G., additional, Rakotondrasoa, Eddie Fanantenana, additional, Ranglack, Dustin H., additional, Rankou, Hassan, additional, Rawat, Ajay Prakash, additional, Reardon, James Thomas, additional, Rheingantz, Marcelo Lopes, additional, Richter, Stephen C., additional, Rivers, Malin C., additional, Rogers, Luke Rollie, additional, da Rosa, Patrícia, additional, Rose, Paul, additional, Royer, Emily, additional, Ryan, Catherine, additional, de Mitcheson, Yvonne J. Sadovy, additional, Salmon, Lily, additional, Salvador, Carlos Henrique, additional, Samways, Michael J., additional, Sanjuan, Tatiana, additional, Souza dos Santos, Amanda, additional, Sasaki, Hiroshi, additional, Schutz, Emmanuel, additional, Scott, Heather Ann, additional, Scott, Robert Michael, additional, Serena, Fabrizio, additional, Sharma, Surya P., additional, Shuey, John A., additional, Silva, Carlos Julio Polo, additional, Simaika, John P., additional, Smith, David R., additional, Spaet, Julia L.Y., additional, Sultana, Shanjida, additional, Talukdar, Bibhab Kumar, additional, Tatayah, Vikash, additional, Thomas, Philip, additional, Tringali, Angela, additional, Trinh‐Dinh, Hoang, additional, Tuboi, Chongpi, additional, Usmani, Aftab Alam, additional, Vasco‐Palacios, Aída M., additional, Vié, Jean‐Christophe, additional, Virens, Evelyn, additional, Walker, Alan, additional, Wallace, Bryan, additional, Waller, Lauren J., additional, Wang, Hongfeng, additional, Wearn, Oliver R., additional, van Weerd, Merlijn, additional, Weigmann, Simon, additional, Willcox, Daniel, additional, Woinarski, John, additional, Yong, Jean W.H., additional, and Young, Stuart, additional

Published
2021
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37. Testing a global standard for quantifying species recovery and assessing conservation impact

Author

Grace, Molly K., Akcakaya, H. Resit, Bennett, Elizabeth L., Brooks, Thomas M., Heath, Anna, Hedges, Simon, Hilton-Taylor, Craig, Hoffmann, Michael, Hochkirch, Axel, Jenkins, Richard, Keith, David A., Long, Barney, Mallon, David P., Meijaard, Erik, Milner-Gulland, E. J., Paul Rodriguez, Jon, Stephenson, P. J., Stuart, Simon N., Young, Richard P., Acebes, Pablo, Alfaro-Shigueto, Joanna, Alvarez-Clare, Silvia, Arbetman, Marina, Azat, Claudio, Bacchetta, Gianluigi, Badola, Ruchi, Barcelos, Luis M. D., Barreiros, Joao Pedro, Basak, Sayanti, Berger, Danielle J., Bhattacharyya, Sabuj, Bino, Gilad, Borges, Paulo A., Boughton, Raoul K., Brockmann, H. Jane, Buckley, Hannah L., Burfield, Ian J., Burton, James, Camacho-Badani, Teresa, Santiago Cano-Alonso, Luis, Carmichael, Ruth H., Carrero, Christina, P Carroll, John, Catsadorakis, Giorgos, Chapple, David G., Chapron, Guillaume, Chowdhury, Gawsia Wahidunnessa, Claassens, Louw, Cogoni, Donatella, Constantine, Rochelle, Craig, Christie Anne, Cunningham, Andrew A., Dahal, Nishma, Daltry, Jennifer C., Das, Goura Chandra, Dasgupta, Niladri, Davey, Alexandra, Davies, Katharine, Develey, Pedro, Elangovan, Vanitha, Fairclough, David, Di Febbraro, Mirko, Fenu, Giuseppe, Fernandes, Fernando Moreira, Fernandez, Eduardo Pinheiro, Finucci, Brittany, Foldesi, Rita, Foley, Catherine M., Ford, Matthew, Forstner, Michael R. J., Garcia-Sandoval, Ricardo, Gardner, Penny C., Garibay-Orijel, Roberto, Gatan-Balbas, Marites, Gauto, Irene, Ghazi, Mirza Ghazanfar Ullah, Godfrey, Stephanie S., Gollock, Matthew, Gonzalez, Benito A., Grant, Tandora D., Gray, Thomas, Gregory, Andrew J., van Grunsven, Roy H. A., Gryzenhout, Marieka, Guernsey, Noelle C., Gupta, Garima, Hagen, Christina, Hagen, Christian A., Hall, Madison B., Hallerman, Eric, Hare, Kelly, Hart, Tom, Hartdegen, Ruston, Harvey-Brown, Yvette, Hatfield, Richard, Hawke, Tahneal, Hermes, Claudia, Hitchmough, Rod, Hoffmann, Pablo Melo, Howarth, Charlie, Hudson, Michael A., Hussain, Syed Ainul, Huveneers, Charlie, Jacques, Helene, Jorgensen, Dennis, Katdare, Suyash, Katsis, Lydia K. D., Kaul, Rahul, Kaunda-Arara, Boaz, Keith-Diagne, Lucy, Kraus, Daniel T., de Lima, Thales Moreira, Lindeman, Ken, Linsky, Jean, Louis, Edward, Loy, Anna, Lughadha, Eimear Nic, Mangel, Jeffrey C., Marinari, Paul E., Martin, Gabriel M., Martinelli, Gustavo, McGowan, Philip J. K., McInnes, Alistair, Mendes, Eduardo Teles Barbosa, Millard, Michael J., Mirande, Claire, Money, Daniel, Monks, Joanne M., Laura Morales, Carolina, Mumu, Nazia Naoreen, Negrao, Raquel, Niloy, Md Nazmul Hasan, Nguyen, Anh Ha, Norbury, Grant Leslie, Nordmeyer, Cale, O'Brien, Mark, Oda, Gabriela Akemi, Orsenigo, Simone, Pasachnik, Stesha, Perez-Jimenez, Juan Carlos, Pike, Charlotte, Pilkington, Fred, Plumb, Glenn, Portela, Rita de Cassia Quitete, Prohaska, Ana, Quintana, Manuel G., Rakotondrasoa, Eddie Fanantenana, Rankou, Hassan, Rawat, Ajay Prakash, Reardon, James Thomas, Rheingantz, Marcelo Lopes, Richter, Stephen C., Rivers, Malin C., da Rosa, Patricia, Rose, Paul, Royer, Emily, Ryan, Catherine, de Mitcheson, Yvonne J. Sadovy, Salmon, Lily, Salvador, Carlos Henrique, Samways, Michael J., Sanjuan, Tatiana, Dos Santos, Amanda Souza, Sasaki, Hiroshi, Schutz, Emmanuel, Scott, Heather Ann, Scott, Robert Michael, Serena, Fabrizio, Sharma, Surya P., Shuey, John A., Silva, Carlos Julio Polo, Simaika, John P., Smith, David R., Spaet, Julia L. Y., Sultana, Shanjida, Talukdar, Bibhab Kumar, Tatayah, Vikash, Thomas, Philip, Tringali, Angela, Tuboi, Chongpi, Hoang, Trinh-Dinh, Usmani, Aftab Alam, Vasco-Palacios, Aida M., Vie, Jean-Christophe, Virens, Jo, Walker, Alan, Wallace, Bryan, Waller, Lauren J., Wang, Hongfeng, Wearn, Oliver R., van Weerd, Merlijn, Weigmann, Simon, Willcox, Daniel, Woinarski, John, Yong, Jean W.H., and Young, Stuart

Subjects
Evolutionary Biology, Ecology, Biological Systematics
Abstract

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a "Green List of Species" (now the IUCN Green Status of Species). A draft Green Status framework for assessing species' progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species' viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species' recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard.

Published
2021

39. Testing a global standard for quantifying species recovery and assessing conservation impact

Author

Grace, Molly K, Akcakaya, H Resit, Bennett, Elizabeth L, Brooks, Thomas M, Heath, Anna, Hedges, Simon, Hilton-Taylor, Craig, Hoffmann, Michael, Hochkirch, Axel, Jenkins, Richard, Keith, David A, Long, Barney, Mallon, David P, Meijaard, Erik, Milner-Gulland, E.J., Rodriguez, Jon Paul, Stephenson, P J, Stuart, Simon N, Young, Richard P, Acebes, Pablo, Alfaro-Shigueto, Joanna, Alvarez-Clare, Silvia, Andriantsimanarilafy, Raphali Rodlis, Arbetman, Marina, Azat, Claudio, Bacchetta, Gianluigi, Badola, Ruchi, Barcelos, Luis M.D., Barreiros, Joao Pedro, Basak, Sayanti, Berger, Danielle J, Bhattacharyya, Sabuj, Bino, Gilad, Borges, Paulo A.V., Boughton, Raoul K, Brockmann, H Jane, Buckley, Hannah L, Burfield, Ian J, Burton, James, Camacho-Badani, Teresa, Cano-Alonso, Luis Santiago, Carmichael, Ruth H, Carrero, Christina, Carroll, John P, Catsadorakis, Giorgos, Chapple, David G, Chapron, Guillaume, Chowdhury, Gawsia Wahidunnessa, Claassens, Louw, Cogoni, Donatella, Constantine, Rochelle, Craig, Christie Anne, Cunningham, Andrew A, Dahal, Nishma, Daltry, Jennifer C, Das, Goura Chandra, Dasgupta, Niladri, Davey, Alexandra, Davies, Katharine, Develey, Pedro, Elangovan, Vanitha, Fairclough, David, Febbraro, Mirko Di, Fenu, Giuseppe, Fernandes, Fernando Moreira, Fernandez, Eduardo Pinheiro, Finucci, Brittany, Foldesi, Rita, Foley, Catherine M, Ford, Matthew, Forstner, Michael R.J., Garcia, Nestor, Garcia-Sandoval, Ricardo, Gardner, Penny C, Garibay-Orijel, Roberto, Gatan-Balbas, Marites, Gauto, Irene, Ullah Ghazi, Mirza Ghazanfar, Godfrey, Stephanie S, Gollock, Matthew, Gonzalez, Benito A, Grant, Tandora D, Gray, Thomas, Gregory, Andrew J, van Grunsven, Roy H.A., Gryzenhout, Marieka, Guernsey, Noelle C, Gupta, Garima, Hagen, Christina, Hagen, Christian A, Hall, Madison B, Hallerman, Eric, Hare, Kelly, Hart, Tom, Hartdegen, Ruston, Harvey-Brown, Yvette, Hatfield, Richard, Hawke, Tahneal, Hermes, Claudia, Hitchmough, Rod, Hoffmann, Pablo Melo, Howarth, Charlie, Hudson, Michael A, Hussain, Syed Ainul, Huveneers, Charlie, Jacques, Helene, Jorgensen, Dennis, Katdare, Suyash, Katsis, Lydia K.D., Kaul, Rahul, Kaundra-Arara, Boaz, Keith-Diagne, Lucy, Kraus, Daniel T, de Lima, Thales Moreira, Lindeman, Ken, Linsky, Jean, Louis, Edward, Jr., Loy, Anna, Lughadha, Eimear Nic, Mangel, Jeffrey C, Marinari, Paul E, Martin, Gabriel M, Martinelli, Gustavo, McGowan, Philip J.K., McInnes, Alistair, Mendes, Eduardo Teles Barbosa, Millard, Michael J, Mirande, Claire, Money, Daniel, Monks, Joanne M, Morales, Carolina Laura, Mumu, Nazia Noareen, Negrao, Raquel, Nguyen, Anh Ha, Niloy, Nazmul Hasan, Md., Norbury, Grant Leslie, Nordmeyer, Cale, Norris, Darren, O'Brien, Mark, Oda, Gabriela Akemi, Orsengio, Simone, Outerbridge, Mark Evan, Pasachnik, Stesha, Perez-Jimenez, Juan Carlos, Pike, Charlotte, Pilkington, Fred, Plumb, Glenn, Quitete Portela, Rita de Cassia, Prohaska, Ana, Quintana, Manuel G, Rakotondrasoa, Eddie Fanantenana, Ranglack, Dustin H, Rankou, Hassan, Rawat, Ajay Prakash, Reardon, James Thomas, Rheingantz, Marcelo Lopes, Richter, Stephen C, Rivers, Malin C, Rogers, Luke Rollie, Rosa, Patricia Da, Rose, Paul, Royer, Emily, Ryan, Catherine, Sadovy de Mitcheson, Yvonne J, Salmon, Lily, Salvador, Carlos Henrique, Samways, Michael J, Sanjuan, Tatiana, Souza dos Santos, Amanda, Sasaki, Hiroshi, Shutz, Emmanuel, Scott, Heather Ann, Scott, Robert Michael, Serena, Fabrizio, Sharma, Surya P, Shuey, John A, Silva, Carlos Julio Polo, Simaika, John P, Smith, David R, Spaet, Julia L.Y., Sultana, Shanjida, Talukdar, Bibhab Kumar, Tatayah, Vikash, Thomas, Philip, Tringali, Angela, Trinh-Dinh, Hoang, Tuboi, Chongpi, Usami, Aftab Alam, Vasco-Palacios, Aida M, Vie, Jean-Christophe, Virens, Jo, Walker, Alan, Wallace, Bryan, Waller, Lauren J, Wang, Hongfeng, Wearn, Oliver R, Weerd, Merlijin van, Weigmann, Simon, Willcox, Daniel, Woinarski, John, Yong, Jean W.H., Young, Stuart, Grace, Molly K, Akcakaya, H Resit, Bennett, Elizabeth L, Brooks, Thomas M, Heath, Anna, Hedges, Simon, Hilton-Taylor, Craig, Hoffmann, Michael, Hochkirch, Axel, Jenkins, Richard, Keith, David A, Long, Barney, Mallon, David P, Meijaard, Erik, Milner-Gulland, E.J., Rodriguez, Jon Paul, Stephenson, P J, Stuart, Simon N, Young, Richard P, Acebes, Pablo, Alfaro-Shigueto, Joanna, Alvarez-Clare, Silvia, Andriantsimanarilafy, Raphali Rodlis, Arbetman, Marina, Azat, Claudio, Bacchetta, Gianluigi, Badola, Ruchi, Barcelos, Luis M.D., Barreiros, Joao Pedro, Basak, Sayanti, Berger, Danielle J, Bhattacharyya, Sabuj, Bino, Gilad, Borges, Paulo A.V., Boughton, Raoul K, Brockmann, H Jane, Buckley, Hannah L, Burfield, Ian J, Burton, James, Camacho-Badani, Teresa, Cano-Alonso, Luis Santiago, Carmichael, Ruth H, Carrero, Christina, Carroll, John P, Catsadorakis, Giorgos, Chapple, David G, Chapron, Guillaume, Chowdhury, Gawsia Wahidunnessa, Claassens, Louw, Cogoni, Donatella, Constantine, Rochelle, Craig, Christie Anne, Cunningham, Andrew A, Dahal, Nishma, Daltry, Jennifer C, Das, Goura Chandra, Dasgupta, Niladri, Davey, Alexandra, Davies, Katharine, Develey, Pedro, Elangovan, Vanitha, Fairclough, David, Febbraro, Mirko Di, Fenu, Giuseppe, Fernandes, Fernando Moreira, Fernandez, Eduardo Pinheiro, Finucci, Brittany, Foldesi, Rita, Foley, Catherine M, Ford, Matthew, Forstner, Michael R.J., Garcia, Nestor, Garcia-Sandoval, Ricardo, Gardner, Penny C, Garibay-Orijel, Roberto, Gatan-Balbas, Marites, Gauto, Irene, Ullah Ghazi, Mirza Ghazanfar, Godfrey, Stephanie S, Gollock, Matthew, Gonzalez, Benito A, Grant, Tandora D, Gray, Thomas, Gregory, Andrew J, van Grunsven, Roy H.A., Gryzenhout, Marieka, Guernsey, Noelle C, Gupta, Garima, Hagen, Christina, Hagen, Christian A, Hall, Madison B, Hallerman, Eric, Hare, Kelly, Hart, Tom, Hartdegen, Ruston, Harvey-Brown, Yvette, Hatfield, Richard, Hawke, Tahneal, Hermes, Claudia, Hitchmough, Rod, Hoffmann, Pablo Melo, Howarth, Charlie, Hudson, Michael A, Hussain, Syed Ainul, Huveneers, Charlie, Jacques, Helene, Jorgensen, Dennis, Katdare, Suyash, Katsis, Lydia K.D., Kaul, Rahul, Kaundra-Arara, Boaz, Keith-Diagne, Lucy, Kraus, Daniel T, de Lima, Thales Moreira, Lindeman, Ken, Linsky, Jean, Louis, Edward, Jr., Loy, Anna, Lughadha, Eimear Nic, Mangel, Jeffrey C, Marinari, Paul E, Martin, Gabriel M, Martinelli, Gustavo, McGowan, Philip J.K., McInnes, Alistair, Mendes, Eduardo Teles Barbosa, Millard, Michael J, Mirande, Claire, Money, Daniel, Monks, Joanne M, Morales, Carolina Laura, Mumu, Nazia Noareen, Negrao, Raquel, Nguyen, Anh Ha, Niloy, Nazmul Hasan, Md., Norbury, Grant Leslie, Nordmeyer, Cale, Norris, Darren, O'Brien, Mark, Oda, Gabriela Akemi, Orsengio, Simone, Outerbridge, Mark Evan, Pasachnik, Stesha, Perez-Jimenez, Juan Carlos, Pike, Charlotte, Pilkington, Fred, Plumb, Glenn, Quitete Portela, Rita de Cassia, Prohaska, Ana, Quintana, Manuel G, Rakotondrasoa, Eddie Fanantenana, Ranglack, Dustin H, Rankou, Hassan, Rawat, Ajay Prakash, Reardon, James Thomas, Rheingantz, Marcelo Lopes, Richter, Stephen C, Rivers, Malin C, Rogers, Luke Rollie, Rosa, Patricia Da, Rose, Paul, Royer, Emily, Ryan, Catherine, Sadovy de Mitcheson, Yvonne J, Salmon, Lily, Salvador, Carlos Henrique, Samways, Michael J, Sanjuan, Tatiana, Souza dos Santos, Amanda, Sasaki, Hiroshi, Shutz, Emmanuel, Scott, Heather Ann, Scott, Robert Michael, Serena, Fabrizio, Sharma, Surya P, Shuey, John A, Silva, Carlos Julio Polo, Simaika, John P, Smith, David R, Spaet, Julia L.Y., Sultana, Shanjida, Talukdar, Bibhab Kumar, Tatayah, Vikash, Thomas, Philip, Tringali, Angela, Trinh-Dinh, Hoang, Tuboi, Chongpi, Usami, Aftab Alam, Vasco-Palacios, Aida M, Vie, Jean-Christophe, Virens, Jo, Walker, Alan, Wallace, Bryan, Waller, Lauren J, Wang, Hongfeng, Wearn, Oliver R, Weerd, Merlijin van, Weigmann, Simon, Willcox, Daniel, Woinarski, John, Yong, Jean W.H., and Young, Stuart

Abstract

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has

Published
2021

40. SmallSats: a new technological frontier in ecology and conservation?

Author

Curnick, David J., Davies, Alasdair J., Duncan, Clare, Freeman, Robin, Jacoby, David M. P., Shelley, Hugo T. E., Rossi, Cristian, Wearn, Oliver R., Williamson, Michael J., Pettorelli, Nathalie, Disney, Mat, and Poursanidis, Dimitris

Subjects
MICROSPACECRAFT, ANIMAL ecology, OPERATING costs, ECOSYSTEM dynamics, ECOLOGICAL disturbances
Abstract

We are in the midst of a revolution in satellite technology, with the rapid development and advancement of small satellites (or SmallSats, i.e., satellites <180 kg). Here, we review the opportunities and challenges that such technology might afford in the field of conservation and ecology. SmallSat constellations may yield higher resolutions than those that are currently available to scientists and practitioners, increasing opportunities to improve environmental‐monitoring and animal‐tracking capabilities. They may cut access costs to end users, by reducing operational costs and bringing increased competition to the existing market. Their greater flexibility and affordability may moreover enable the development of bespoke constellations for specific conservation and ecological applications, and provide greater interoperability with ground‐based sensors, such as tracking devices and camera traps. In addition, SmallSats may serve as cost‐effective research and development platforms for new components and products. Combined, these benefits could significantly improve our ability to monitor threats to the environment as they unfold, while enhancing our understanding of animal ecology and ecosystem dynamics. However, significant hardware and software developments are required before such technology is able to produce, process and handle reliable and cost‐effective data, and the initial research and development costs still represent a major challenge. Further, we argue that much remains to be done to ensure these new data products become accessible, equitable and sustainable. [ABSTRACT FROM AUTHOR]

Published
2022
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41. Extinction filters mediate the global effects of habitat fragmentation on animals

Author

Betts, Matthew G., primary, Wolf, Christopher, additional, Pfeifer, Marion, additional, Banks-Leite, Cristina, additional, Arroyo-Rodríguez, Víctor, additional, Ribeiro, Danilo Bandini, additional, Barlow, Jos, additional, Eigenbrod, Felix, additional, Faria, Deborah, additional, Fletcher, Robert J., additional, Hadley, Adam S., additional, Hawes, Joseph E., additional, Holt, Robert D., additional, Klingbeil, Brian, additional, Kormann, Urs, additional, Lens, Luc, additional, Levi, Taal, additional, Medina-Rangel, Guido F., additional, Melles, Stephanie L., additional, Mezger, Dirk, additional, Morante-Filho, José Carlos, additional, Orme, C. David L., additional, Peres, Carlos A., additional, Phalan, Benjamin T., additional, Pidgeon, Anna, additional, Possingham, Hugh, additional, Ripple, William J., additional, Slade, Eleanor M., additional, Somarriba, Eduardo, additional, Tobias, Joseph A., additional, Tylianakis, Jason M., additional, Urbina-Cardona, J. Nicolás, additional, Valente, Jonathon J., additional, Watling, James I., additional, Wells, Konstans, additional, Wearn, Oliver R., additional, Wood, Eric, additional, Young, Richard, additional, and Ewers, Robert M., additional

Published
2019
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42. Pangolins in global camera trap data: Implications for ecological monitoring

Author

Khwaja, Hannah, Buchan, Claire, Wearn, Oliver R, Bahaa-el-din, Laila, Bantlin, Drew, Bernard, Henry, Bitariho, Robert, Bohm, Torsten, Borah, Jimmy, Brodie, Jedediah, Chutipong, Wanlop, du Preez, Byron, Ebang-Mbele, Alex, Edwards, Sarah, and Orbell, Christopher

Subjects
Detection, Monitoring, Pangolin, Occupancy modelling, Camera trap, Macroecology
Abstract

Despite being heavily exploited, pangolins (Pholidota: Manidae) have been subject to limited research, resulting in a lack of reliable population estimates and standardised survey methods for the eight extant species. Camera trapping represents a unique opportunity for broad-scale collaborative species monitoring due to its largely non-discriminatory nature, which creates considerable volumes of data on a relatively wide range of species. This has the potential to shed light on the ecology of rare, cryptic and understudied taxa, with implications for conservation decision-making. We undertook a global analysis of available pangolin data from camera trapping studies across their range in Africa and Asia. Our aims were (1) to assess the utility of existing camera trapping efforts as a method for monitoring pangolin populations, and (2) to gain insights into the distribution and ecology of pangolins. We analysed data collated from 103 camera trap surveys undertaken across 22 countries that fell within the range of seven of the eight pangolin species, which yielded more than half a million trap nights and 888 pangolin encounters. We ran occupancy analyses on three species (Sunda pangolin Manis javanica, white-bellied pangolin Phataginus tricuspis and giant pangolin Smutsia gigantea). Detection probabilities varied with forest cover and levels of human influence for P. tricuspis, but were low ( < 0.05) for all species. Occupancy was associated with distance from rivers for M. javanica and S. gigantea, elevation for P. tricuspis and S. gigantea, forest cover for P. tricuspis and protected area status for M. javanica and P. tricuspis. We conclude that camera traps are suitable for the detection of pangolins and large-scale assessment of their distributions. However, the trapping effort required to monitor populations at any given study site using existing methods appears prohibitively high. This may change in the future should anticipated technological and methodological advances in camera trapping facilitate greater sampling efforts and/or higher probabilities of detection. In particular, targeted camera placement for pangolins is likely to make pangolin monitoring more feasible with moderate sampling efforts.

Published
2019

44. S3 Appendix - Supplementary discussion from Snap happy: camera traps are an effective sampling tool when compared with alternative methods

Author

Wearn, Oliver R. and Glover-Kapfer, Paul

Subjects
Condensed Matter::Quantum Gases, Quantitative Biology::Tissues and Organs, Computer Science::Computer Vision and Pattern Recognition, Astrophysics::Instrumentation and Methods for Astrophysics, Physics::Atomic Physics
Abstract

Additional discussion of: how camera-trapping compares to hair-trapping and detector dogs; metrics for which camera-trapping was least effective, and study characteristics which had ambiguous or no relationship with camera trap effectiveness.

Published
2019
Full Text
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45. S2 Appendix - Supplementary results from Snap happy: camera traps are an effective sampling tool when compared with alternative methods

Author

Wearn, Oliver R. and Glover-Kapfer, Paul

Subjects
Statistics::Theory, information science, Statistics::Methodology, natural sciences, Astrophysics::Cosmology and Extragalactic Astrophysics, health care quality, access, and evaluation, humanities
Abstract

Bootstrapped median effect sizes and model-averaged parameter estimates, with 95% confidence intervals.

Published
2019
Full Text
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46. Pangolins in global camera trap data:Implications for ecological monitoring

Author

Khwaja, Hannah, Buchan, Claire, Wearn, Oliver R., Bahaa-el-din, Laila, Bantlin, Drew, Bernard, Henry, Bitariho, Robert, Bohm, Torsten, Borah, Jimmy, Brodie, Jedediah, Chutipong, Wanlop, Preez, Byron du, Ebang-Mbele, Alex, Edwards, Sarah, Fairet, Emilie, Frechette, Jackson L., Garside, Adrian, Gibson, Luke, Giordano, Anthony, Veeraswami Gopi, Govindan, Granados, Alys, Gubbi, Sanjay, Harich, Franziska, Haurez, Barbara, Havmøller, Rasmus W., Helmy, Olga, Isbell, Lynne A., Jenks, Kate, Kalle, Riddhika, Kamjing, Anucha, Khamcha, Daphawan, Kiebou-Opepa, Cisquet, Kinnaird, Margaret, Kruger, Caroline, Laudisoit, Anne, Lynam, Antony, Macdonald, Suzanne E., Mathai, John, Sienne, Julia Metsio, Meier, Amelia, Mills, David, Mohd-Azlan, Jayasilan, Nakashima, Yoshihiro, Nash, Helen C., Ngoprasert, Dusit, Nguyen, An, O'Brien, Tim, Olson, David, Orbell, Christopher, Poulsen, John, Ramesh, Tharmalingam, Reeder, Dee Ann, Reyna, Rafael, Rich, Lindsey N., Rode-Margono, Johanna, Rovero, Francesco, Sheil, Douglas, Shirley, Matthew H., Stratford, Ken, Sukumal, Niti, Suwanrat, Saranphat, Tantipisanuh, Naruemon, Tilker, Andrew, Van Berkel, Tim, Van der Weyde, Leanne K., Varney, Matthew, Weise, Florian, Wiesel, Ingrid, Wilting, Andreas, Wong, Seth T., Waterman, Carly, Challender, Daniel W.S., Khwaja, Hannah, Buchan, Claire, Wearn, Oliver R., Bahaa-el-din, Laila, Bantlin, Drew, Bernard, Henry, Bitariho, Robert, Bohm, Torsten, Borah, Jimmy, Brodie, Jedediah, Chutipong, Wanlop, Preez, Byron du, Ebang-Mbele, Alex, Edwards, Sarah, Fairet, Emilie, Frechette, Jackson L., Garside, Adrian, Gibson, Luke, Giordano, Anthony, Veeraswami Gopi, Govindan, Granados, Alys, Gubbi, Sanjay, Harich, Franziska, Haurez, Barbara, Havmøller, Rasmus W., Helmy, Olga, Isbell, Lynne A., Jenks, Kate, Kalle, Riddhika, Kamjing, Anucha, Khamcha, Daphawan, Kiebou-Opepa, Cisquet, Kinnaird, Margaret, Kruger, Caroline, Laudisoit, Anne, Lynam, Antony, Macdonald, Suzanne E., Mathai, John, Sienne, Julia Metsio, Meier, Amelia, Mills, David, Mohd-Azlan, Jayasilan, Nakashima, Yoshihiro, Nash, Helen C., Ngoprasert, Dusit, Nguyen, An, O'Brien, Tim, Olson, David, Orbell, Christopher, Poulsen, John, Ramesh, Tharmalingam, Reeder, Dee Ann, Reyna, Rafael, Rich, Lindsey N., Rode-Margono, Johanna, Rovero, Francesco, Sheil, Douglas, Shirley, Matthew H., Stratford, Ken, Sukumal, Niti, Suwanrat, Saranphat, Tantipisanuh, Naruemon, Tilker, Andrew, Van Berkel, Tim, Van der Weyde, Leanne K., Varney, Matthew, Weise, Florian, Wiesel, Ingrid, Wilting, Andreas, Wong, Seth T., Waterman, Carly, and Challender, Daniel W.S.

Abstract

Despite being heavily exploited, pangolins (Pholidota: Manidae) have been subject to limited research, resulting in a lack of reliable population estimates and standardised survey methods for the eight extant species. Camera trapping represents a unique opportunity for broad-scale collaborative species monitoring due to its largely non-discriminatory nature, which creates considerable volumes of data on a relatively wide range of species. This has the potential to shed light on the ecology of rare, cryptic and understudied taxa, with implications for conservation decision-making. We undertook a global analysis of available pangolin data from camera trapping studies across their range in Africa and Asia. Our aims were (1) to assess the utility of existing camera trapping efforts as a method for monitoring pangolin populations, and (2) to gain insights into the distribution and ecology of pangolins. We analysed data collated from 103 camera trap surveys undertaken across 22 countries that fell within the range of seven of the eight pangolin species, which yielded more than half a million trap nights and 888 pangolin encounters. We ran occupancy analyses on three species (Sunda pangolin Manis javanica, white-bellied pangolin Phataginus tricuspis and giant pangolin Smutsia gigantea). Detection probabilities varied with forest cover and levels of human influence for P. tricuspis, but were low (<0.05) for all species. Occupancy was associated with distance from rivers for M. javanica and S. gigantea, elevation for P. tricuspis and S. gigantea, forest cover for P. tricuspis and protected area status for M. javanica and P. tricuspis. We conclude that camera traps are suitable for the detection of pangolins and large-scale assessment of their distributions. However, the trapping effort required to monitor populations at any given study site using existing methods appears prohibitively high. This may change in the future should anticipated technological and methodologic

Published
2019

47. Pangolins in global camera trap data: Implications for ecological monitoring

Author

Fish and Wildlife Conservation, Khwaja, Hannah, Buchan, Claire, Wearn, Oliver R., Bahaa-el-din, Laila, Bantlin, Drew, Bernard, Henry, Bitariho, Robert, Bohm, Torsten, Borah, Jimmy, Brodie, Jedediah, Chutipong, Wanlop, du Preez, Byron, Ebang-Mbele, Alex, Edwards, Sarah, Fairet, Emilie, Frechette, Jackson L., Garside, Adrian, Gibson, Luke, Giordano, Anthony, Gopi, Govindan Veeraswami, Granados, Alys, Gubbi, Sanjay, Harich, Franziska, Haurez, Barbara, Havmoller, Rasmus W., Helmy, Olga, Isbell, Lynne A., Jenks, Kate, Kalle, Riddhika, Kamjing, Anucha, Khamcha, Daphawan, Kiebou-Opepa, Cisquet, Kinnaird, Margaret, Kruger, Caroline, Laudisoit, Anne, Lynam, Antony, Macdonald, Suzanne E., Mathai, John, Sienne, Julia Metsio, Meier, Amelia, Mills, David, Mohd-Azlan, Jayasilan, Nakashima, Yoshihiro, Nash, Helen C., Ngoprasert, Dusit, Nguyen, An, O'Brien, Timothy J., Olson, David, Orbell, Christopher, Poulsen, John, Ramesh, Tharmalingam, Reeder, DeeAnn, Reyna, Rafael, Rich, Lindsey N., Rode-Margono, Johanna, Rovero, Francesco, Sheil, Douglas, Shirley, Matthew H., Stratford, Ken, Sukumal, Niti, Suwanrat, Saranphat, Tantipisanuh, Naruemon, Tilker, Andrew, Van Berkel, Tim, Van der Weyde, Leanne K., Varney, Matthew, Weise, Florian, Wiesel, Ingrid, Wilting, Andreas, Wong, Seth T., Waterman, Carly, Challender, Daniel W. S., Fish and Wildlife Conservation, Khwaja, Hannah, Buchan, Claire, Wearn, Oliver R., Bahaa-el-din, Laila, Bantlin, Drew, Bernard, Henry, Bitariho, Robert, Bohm, Torsten, Borah, Jimmy, Brodie, Jedediah, Chutipong, Wanlop, du Preez, Byron, Ebang-Mbele, Alex, Edwards, Sarah, Fairet, Emilie, Frechette, Jackson L., Garside, Adrian, Gibson, Luke, Giordano, Anthony, Gopi, Govindan Veeraswami, Granados, Alys, Gubbi, Sanjay, Harich, Franziska, Haurez, Barbara, Havmoller, Rasmus W., Helmy, Olga, Isbell, Lynne A., Jenks, Kate, Kalle, Riddhika, Kamjing, Anucha, Khamcha, Daphawan, Kiebou-Opepa, Cisquet, Kinnaird, Margaret, Kruger, Caroline, Laudisoit, Anne, Lynam, Antony, Macdonald, Suzanne E., Mathai, John, Sienne, Julia Metsio, Meier, Amelia, Mills, David, Mohd-Azlan, Jayasilan, Nakashima, Yoshihiro, Nash, Helen C., Ngoprasert, Dusit, Nguyen, An, O'Brien, Timothy J., Olson, David, Orbell, Christopher, Poulsen, John, Ramesh, Tharmalingam, Reeder, DeeAnn, Reyna, Rafael, Rich, Lindsey N., Rode-Margono, Johanna, Rovero, Francesco, Sheil, Douglas, Shirley, Matthew H., Stratford, Ken, Sukumal, Niti, Suwanrat, Saranphat, Tantipisanuh, Naruemon, Tilker, Andrew, Van Berkel, Tim, Van der Weyde, Leanne K., Varney, Matthew, Weise, Florian, Wiesel, Ingrid, Wilting, Andreas, Wong, Seth T., Waterman, Carly, and Challender, Daniel W. S.

Abstract

Despite being heavily exploited, pangolins (Pholidota: Manidae) have been subject to limited research, resulting in a lack of reliable population estimates and standardised survey methods for the eight extant species. Camera trapping represents a unique opportunity for broad-scale collaborative species monitoring due to its largely nondiscriminatory nature, which creates considerable volumes of data on a relatively wide range of species. This has the potential to shed light on the ecology of rare, cryptic and understudied taxa, with implications for conservation decision-making. We undertook a global analysis of available pangolin data from camera trapping studies across their range in Africa and Asia. Our aims were (1) to assess the utility of existing camera trapping efforts as a method for monitoring pangolin populations, and (2) to gain insights into the distribution and ecology of pangolins. We analysed data collated from 103 camera trap surveys undertaken across 22 countries that fell within the range of seven of the eight pangolin species, which yielded more than half a million trap nights and 888 pangolin encounters. We ran occupancy analyses on three species (Sunda pangolin Manis javanica, white-bellied pangolin Phataginus tricuspis and giant pangolin Smutsia gigantea). Detection probabilities varied with forest cover and levels of human influence for P. tricuspis, but were low (<0.05) for all species. Occupancy was associated with distance from rivers for M. javanica and S. gigantea, elevation for P. tricuspis and S. gigantea, forest cover for P. tricuspis and protected area status for M. javanica and P. tricuspis. We conclude that camera traps are suitable for the detection of pangolins and large-scale assessment of their distributions. However, the trapping effort required to monitor populations at any given study site using existing methods appears prohibitively high. This may change in the future should anticipated technological and methodological adva

Published
2019

49. Prey availability and temporal partitioning modulate felid coexistence in Neotropical forests

Author

Santos, Fernanda, Carbone, Chris, Wearn, Oliver R., Rowcliffe, J.M., Espinosa, Santiago, Moreira, Marcela Guimarães, Ahumada, Jorge A., Gonçalves, André Luis Sousa, Trevelin, Leonardo C., Alvarez-Loayza, Patricia, Spironello, Wilson R., Jansen, Patrick A., Juen, Leandro, Peres, Carlos A., Santos, Fernanda, Carbone, Chris, Wearn, Oliver R., Rowcliffe, J.M., Espinosa, Santiago, Moreira, Marcela Guimarães, Ahumada, Jorge A., Gonçalves, André Luis Sousa, Trevelin, Leonardo C., Alvarez-Loayza, Patricia, Spironello, Wilson R., Jansen, Patrick A., Juen, Leandro, and Peres, Carlos A.

Abstract

Carnivores have long been used as model organisms to examine mechanisms that allow coexistence among ecologically similar species. Interactions between carnivores, including competition and predation, comprise important processes regulating local community structure and diversity. We use data from an intensive camera-trapping monitoring program across eight Neotropical forest sites to describe the patterns of spatiotemporal organization of a guild of five sympatric cat species: jaguar (Panthera onca), puma (Puma concolor), ocelot (Leopardus pardalis), jaguarundi (Herpailurus yagouaroundi) and margay (Leopardus wiedii). For the three largest cat species, we developed multi-stage occupancy models accounting for habitat characteristics (landscape complexity and prey availability) and models accounting for species interactions (occupancy estimates of potential competitor cat species). Patterns of habitat-use were best explained by prey availability, rather than habitat structure or species interactions, with no evidence of negative associations of jaguar on puma and ocelot occupancy or puma on ocelot occupancy. We further explore temporal activity patterns and overlap of all five felid species. We observed a moderate temporal overlap between jaguar, puma and ocelot, with differences in their activity peaks, whereas higher temporal partitioning was observed between jaguarundi and both ocelot and margay. Lastly, we conducted temporal overlap analysis and calculated species activity levels across study sites to explore if shifts in daily activity within species can be explained by varying levels of local competition pressure. Activity patterns of ocelots, jaguarundis and margays were similarly bimodal across sites, but pumas exhibited irregular activity patterns, most likely as a response to jaguar activity. Activity levels were similar among sites and observed differences were unrelated to competition or intraguild killing risk. Our study reveals apparent spatial and temp

Published
2019

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