Population trends in
            <i>Vermivora</i>
            warblers are linked to strong migratory connectivity

Kramer, Gunnar R.; Andersen, David E.; Buehler, David A.; Wood, Petra Bohall; Peterson, Sean M.; Lehman, Justin A.; Aldinger, Kyle R.; Bulluck, Lesley P.; Harding, Sergio R.; Jones, John Anthony; Loegering, John P.; Smalling, Curtis; Vallender, Rachel; Streby, Henry M.

doi:10.1073/pnas.1718985115

Cited by 98 publications

(121 citation statements)

References 71 publications

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“…For Wood Thrush, these results highlight the need to formally evaluate how spatial information on regional threats (e.g., deforestation, fire, drought), during all stages of the life cycle (e.g., breeding, migratory, non‐breeding), correlate with seasonal trends and influence population declines (Kramer et al. ).…”

Section: Discussionmentioning

confidence: 99%

Modeling avian full annual cycle distribution and population trends with citizen science data

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Auer

Johnston

et al. 2020

Ecological Applications

148

176

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Information on species’ distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at landscape scales across range‐wide extents for two main reasons. First, landscape‐scale processes that affect populations vary throughout the year and across species’ ranges, requiring high‐resolution, year‐round data across broad, sometimes hemispheric, spatial extents. Second, while citizen science projects can collect data at these resolutions and extents, using these data requires appropriate analysis to address known sources of bias. Here, we present an analytical framework to address these challenges and generate year‐round, range‐wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush (Hylocichla mustelina), a long‐distance Neotropical migrant and species of conservation concern, using data from the citizen science project eBird. We estimate occurrence and abundance across a range of spatial scales throughout the annual cycle. Additionally, we generate intra‐annual estimates of the range, intra‐annual estimates of the associations between species and characteristics of the landscape, and interannual trends in abundance for breeding and non‐breeding seasons. The range‐wide population trajectories for Wood Thrush show a close correspondence between breeding and non‐breeding seasons with steep declines between 2010 and 2013 followed by shallower rates of decline from 2013 to 2016. The breeding season range‐wide population trajectory based on the independently collected and analyzed North American Breeding Bird Survey data also shows this pattern. The information provided here fills important knowledge gaps for Wood Thrush, especially during the less studied migration and non‐breeding periods. More generally, the modeling framework presented here can be used to accurately capture landscape scale intra‐ and interannual distributional dynamics for broadly distributed, highly mobile species.

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Section: Discussionmentioning

confidence: 99%

Modeling avian full annual cycle distribution and population trends with citizen science data

Fink

Auer

Johnston

et al. 2020

Ecological Applications

148

176

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“…, Kramer et al . ). Population trends seem to be determined partly by non‐breeding factors (Koleček et al .…”

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confidence: 97%

Seasonal climatic niches diverge in migratory birds

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Arcones

Ferrer

et al. 2019

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Migratory birds occupy different geographical areas during breeding and non‐breeding periods, and thus different factors may determine their range limits depending on each season. One such factor is the spatial climatic component of the niche, which is widely used to model species distributions, yet the temporal component is often neglected and is generally assumed to be constant. We tested the hypothesis that the climatic niche is conserved between breeding and non‐breeding areas in 355 bird species migrating through Eurasian–African flyways. For this, we performed niche overlap analyses and compared niche differences between sister or phylogenetically closely related species, as well as linking the differences to migratory distances. For more than 80% of the species, there was no or very little overlap between their breeding and non‐breeding climatic niches. For most closely related species, the degree of overlap of their breeding climatic niches was larger than the overlap observed within each species, but not for their wintering climatic niches, suggesting a phylogenetic conservation of breeding climatic niches. Finally, there was a clear negative relationship between migratory distances and climatic niche overlap within each species. Our results confirmed that the climatic niche of most Eurasian–African migratory species differs between both breeding and non‐breeding ranges, suggesting distinctive seasonal climatic requirements. Given these results and the geographically uneven effects of climate change, the impact of global change is likely to have different effects in each seasonal range. Hence, both breeding and non‐breeding climatic data need to be considered when using species distribution models.

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“…Migratory connectivity is defined as “the movement of individuals between summer and winter populations, including immediate stopover sites” (Webster et al :77). Knowing migratory connectivity is important to understanding the movement of individuals between areas throughout the annual cycle and how these movements influence regional population dynamics (Johnson et al , Taylor and Norris , Taylor and Stutchbury , Kramer et al ). For woodcock, understanding migratory connectivity is important because woodcock populations in most portions of their breeding distribution have experienced population declines since the initiation of a standardized population survey in 1968 (Seamans and Rau ).…”

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confidence: 99%

Migratory connectivity of American woodcock derived using satellite telemetry

et al. 2019

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American woodcock (Scolopax minor; woodcock) migratory connectivity (i.e., association between breeding and wintering areas) is largely unknown, even though current woodcock management is predicated on such associations. Woodcock are currently managed in the Eastern and Central management regions in the United States with the boundary between management regions analogous to the boundary between the Atlantic and Mississippi flyways, based largely on analysis of band returns from hunters. Factors during migration influence survival and fitness, and existing data derived from banding and very high frequency telemetry provide only coarse‐scale information to assess factors influencing woodcock migratory movement patterns and behavior. To assess whether current management‐region boundaries correspond with woodcock migratory connectivity in the Central Management Region and to describe migration patterns with higher resolution than has been previously possible, we deployed satellite transmitters on 73 woodcock (25 adult and 28 juvenile females, and 8 adult and 12 juvenile males) and recorded 87 autumn or spring migration paths from 2014 to 2016. Marked woodcock used 2 primary migrations routes: a Western Route and a Central Route. The Western Route ran north‐south, connecting the breeding and wintering grounds within the Central Management Region. The hourglass‐shaped Central Route connected an area on the wintering grounds reaching from Texas to Florida, to sites throughout northeastern North America in both the Eastern Management Region and Central Management Region and woodcock following this route migrated through the area between the Appalachian Mountains and the Mississippi Alluvial Valley in western Tennessee during autumn and spring. Two of 17 woodcock captured associated with breeding areas in Michigan, Wisconsin, or Minnesota migrated to wintering sites in the Eastern Management Region and 12 marked woodcock captured on wintering areas in Texas and Louisiana migrated to breeding sites in the Eastern Management Region. Woodcock that used the Western Route exhibited high concentrations of stopovers during spring in the Arkansas Ozark Mountains and northern Missouri, and along the Mississippi River on the border between Wisconsin and Minnesota, and autumn concentrations of stopovers in southwestern Iowa, central Missouri, the Arkansas portion of the Ozark Mountains, and around the junction of Texas, Louisiana, Oklahoma, and Arkansas. Woodcock that used the Central Route exhibited high concentrations of stopovers during spring in northern Mississippi through western Tennessee, western Kentucky, and the Missouri Bootheel, and autumn concentrations of stopovers in northern Illinois, southwestern Ohio, and the portions of Kentucky and Tennessee west of the Appalachian Mountains. We suggest that current management of woodcock based on 2 management regions may not be consistent with the apparent lack of strong migratory connectivity we observed. Our results also suggest where management of migration habitat m...

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Population trends in Vermivora warblers are linked to strong migratory connectivity

Cited by 98 publications

References 71 publications

Modeling avian full annual cycle distribution and population trends with citizen science data

Modeling avian full annual cycle distribution and population trends with citizen science data

Seasonal climatic niches diverge in migratory birds

Migratory connectivity of American woodcock derived using satellite telemetry

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