Pub Date : 2023-11-25DOI: 10.1093/ornithology/ukad051
João Marcos Guimarães Capurucho, Lukas J Musher, Alexander Lees, Marco A Rego, Glaucia Del-Rio, Alexandre Aleixo, Vanessa E Luzuriaga-Aveiga, Mateus Ferreira, Camila C Ribas, Gregory Thom
Our understanding of Amazonian biogeography is quickly increasing, catalyzed by the growing use of genomic datasets, improved knowledge of species distributions, and the accumulation of new data on the geological and climatic history of the region. The high number of species in Amazonia and their intricate patterns of geographic distribution triggered the development of many diversification hypotheses that shaped historical biogeography as a discipline. Here, we present a historical overview of avian biogeographic studies in Amazonia, their recent advances, outstanding questions, and future directions. We focus on how new approaches have led to novel understandings of the distribution patterns and diversification processes that underpin avian diversity. We show how genomic tools are being used to establish new hypotheses about the drivers of diversification and highlight the importance of recent studies of birds in previously overlooked environments, such as floodplains and open vegetation enclaves. We emphasize the importance of gene flow, species traits, and habitat affinities in studying diversification processes to fully acknowledge the complexity of Amazonian ecosystems and their history. We then discuss the current gaps in Amazonian taxonomic and biogeographic knowledge, with a focus on the issues that we believe hinder our understanding of the field. Amazonia has been facing increasing levels of forest loss due to agricultural expansion, infrastructure development, mining, climate change, and illegal activities catalyzed by weak governance. To halt biodiversity loss, it is crucial to increase our knowledge of the natural history and biogeography of Amazonian species. We suggest increasing incentives for research and training at institutions based in the region, as well as the establishment of partnerships with governments, local communities, NGOs, and international institutions to bring diverse communities together to address crucial questions.
{"title":"Amazonian avian biogeography: Broadscale patterns, microevolutionary processes, and habitat-specific models revealed by multidisciplinary approaches","authors":"João Marcos Guimarães Capurucho, Lukas J Musher, Alexander Lees, Marco A Rego, Glaucia Del-Rio, Alexandre Aleixo, Vanessa E Luzuriaga-Aveiga, Mateus Ferreira, Camila C Ribas, Gregory Thom","doi":"10.1093/ornithology/ukad051","DOIUrl":"https://doi.org/10.1093/ornithology/ukad051","url":null,"abstract":"Our understanding of Amazonian biogeography is quickly increasing, catalyzed by the growing use of genomic datasets, improved knowledge of species distributions, and the accumulation of new data on the geological and climatic history of the region. The high number of species in Amazonia and their intricate patterns of geographic distribution triggered the development of many diversification hypotheses that shaped historical biogeography as a discipline. Here, we present a historical overview of avian biogeographic studies in Amazonia, their recent advances, outstanding questions, and future directions. We focus on how new approaches have led to novel understandings of the distribution patterns and diversification processes that underpin avian diversity. We show how genomic tools are being used to establish new hypotheses about the drivers of diversification and highlight the importance of recent studies of birds in previously overlooked environments, such as floodplains and open vegetation enclaves. We emphasize the importance of gene flow, species traits, and habitat affinities in studying diversification processes to fully acknowledge the complexity of Amazonian ecosystems and their history. We then discuss the current gaps in Amazonian taxonomic and biogeographic knowledge, with a focus on the issues that we believe hinder our understanding of the field. Amazonia has been facing increasing levels of forest loss due to agricultural expansion, infrastructure development, mining, climate change, and illegal activities catalyzed by weak governance. To halt biodiversity loss, it is crucial to increase our knowledge of the natural history and biogeography of Amazonian species. We suggest increasing incentives for research and training at institutions based in the region, as well as the establishment of partnerships with governments, local communities, NGOs, and international institutions to bring diverse communities together to address crucial questions.","PeriodicalId":501265,"journal":{"name":"The Auk","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138520992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-15DOI: 10.1093/ornithology/ukad056
Elliott M Ress, Andrew Farnsworth, Sara R Morris, Michael Lanzone, Benjamin M Van Doren
Flight calls are short vocalizations frequently associated with migratory behavior that may maintain group structure, signal individual identity, and facilitate intra- and interspecific communication. In this study, Magnolia Warbler (Setophaga magnolia) flight call characteristics varied significantly by season and recording location, but not age or sex, and an individual’s flight calls were significantly more similar to one another than to calls of other individuals. To determine if flight calls encode traits of the signaling individual during migration, we analyzed acoustic characteristics of the calls from the nocturnally migrating Magnolia Warbler. Specifically, we analyzed calls recorded from temporarily captured birds across the northeastern United States, including Appledore Island in Maine, Braddock Bay Bird Observatory in New York, and Powdermill Avian Research Center in Pennsylvania to quantify variation attributable to individual identity, sex, age, seasonality, and recording location. Overall, our findings suggest that Magnolia Warbler flight calls may show meaningful individual variation and exhibit previously undescribed spatiotemporal variation, providing a basis for future research.
{"title":"Magnolia Warbler flight calls demonstrate individuality and variation by season and recording location","authors":"Elliott M Ress, Andrew Farnsworth, Sara R Morris, Michael Lanzone, Benjamin M Van Doren","doi":"10.1093/ornithology/ukad056","DOIUrl":"https://doi.org/10.1093/ornithology/ukad056","url":null,"abstract":"Flight calls are short vocalizations frequently associated with migratory behavior that may maintain group structure, signal individual identity, and facilitate intra- and interspecific communication. In this study, Magnolia Warbler (Setophaga magnolia) flight call characteristics varied significantly by season and recording location, but not age or sex, and an individual’s flight calls were significantly more similar to one another than to calls of other individuals. To determine if flight calls encode traits of the signaling individual during migration, we analyzed acoustic characteristics of the calls from the nocturnally migrating Magnolia Warbler. Specifically, we analyzed calls recorded from temporarily captured birds across the northeastern United States, including Appledore Island in Maine, Braddock Bay Bird Observatory in New York, and Powdermill Avian Research Center in Pennsylvania to quantify variation attributable to individual identity, sex, age, seasonality, and recording location. Overall, our findings suggest that Magnolia Warbler flight calls may show meaningful individual variation and exhibit previously undescribed spatiotemporal variation, providing a basis for future research.","PeriodicalId":501265,"journal":{"name":"The Auk","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138520993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-21DOI: 10.1093/ornithology/ukad035
Wesley M Hochachka, Viviana Ruiz Gutierrez, Alison Johnston
An occupancy model makes use of data that are structured as sets of repeated visits to each of many sites, in order estimate the actual probability of occupancy (i.e., proportion of occupied sites) after correcting for imperfect detection using the information contained in the sets of repeated observations. We explore the conditions under which preexisting, volunteer-collected data from the citizen science project eBird can be used for fitting occupancy models. Because the majority of eBird’s data are not collected in the form of repeated observations at individual locations, we explore two ways in which the single-visit records could be used in occupancy models. First, we assess the potential for space-for-time substitution: aggregating single-visit records from different locations within a region into pseudo-repeat visits. On average, eBird’s observers did not make their observations at locations that were representative of the habitat in the surrounding area, which would lead to biased estimates of occupancy probabilities when using space-for-time substitution. Thus, the use of space-for-time substitution is not always appropriate. Second, we explored the utility of including data from single-visit records to supplement sets of repeated-visit data. In a simulation study we found that inclusion of single-visit records increased the precision of occupancy estimates, but only when detection probabilities are high. When detection probability was low, the addition of single-visit records exacerbated biases in estimates of occupancy probability. We conclude that subsets of data from eBird, and likely from similar projects, can be used for occupancy modeling either using space-for-time substation or supplementing repeated-visit data with data from single-visit records. The appropriateness of either alternative will depend on the goals of a study and on the probabilities of detection and occupancy of the species of interest.
{"title":"Considerations for fitting occupancy models to data from eBird and similar volunteer-collected data","authors":"Wesley M Hochachka, Viviana Ruiz Gutierrez, Alison Johnston","doi":"10.1093/ornithology/ukad035","DOIUrl":"https://doi.org/10.1093/ornithology/ukad035","url":null,"abstract":"An occupancy model makes use of data that are structured as sets of repeated visits to each of many sites, in order estimate the actual probability of occupancy (i.e., proportion of occupied sites) after correcting for imperfect detection using the information contained in the sets of repeated observations. We explore the conditions under which preexisting, volunteer-collected data from the citizen science project eBird can be used for fitting occupancy models. Because the majority of eBird’s data are not collected in the form of repeated observations at individual locations, we explore two ways in which the single-visit records could be used in occupancy models. First, we assess the potential for space-for-time substitution: aggregating single-visit records from different locations within a region into pseudo-repeat visits. On average, eBird’s observers did not make their observations at locations that were representative of the habitat in the surrounding area, which would lead to biased estimates of occupancy probabilities when using space-for-time substitution. Thus, the use of space-for-time substitution is not always appropriate. Second, we explored the utility of including data from single-visit records to supplement sets of repeated-visit data. In a simulation study we found that inclusion of single-visit records increased the precision of occupancy estimates, but only when detection probabilities are high. When detection probability was low, the addition of single-visit records exacerbated biases in estimates of occupancy probability. We conclude that subsets of data from eBird, and likely from similar projects, can be used for occupancy modeling either using space-for-time substation or supplementing repeated-visit data with data from single-visit records. The appropriateness of either alternative will depend on the goals of a study and on the probabilities of detection and occupancy of the species of interest.","PeriodicalId":501265,"journal":{"name":"The Auk","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138526354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-15DOI: 10.1093/ornithology/ukac011
Leesia C Marshall
{"title":"100 Years Ago in the American Ornithologists’ Union","authors":"Leesia C Marshall","doi":"10.1093/ornithology/ukac011","DOIUrl":"https://doi.org/10.1093/ornithology/ukac011","url":null,"abstract":"","PeriodicalId":501265,"journal":{"name":"The Auk","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138526353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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