The effects of wind and fuel stores on stopover departure behavior across a migratory barrier

Dossman, Bryant C.; Mitchell, Greg W.; Norris, D. Ryan; Taylor, Philip D.; Guglielmo, Christopher G.; Matthews, Stephen N.; Rodewald, Paul G.

doi:10.1093/beheco/arv189

Cited by 57 publications

(81 citation statements)

References 56 publications

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“…This wealth of data has led to comprehensive and diverse applications in the study of breeding and postbreeding dispersal, stopover and migration behavior, and overwintering ecology. For example, detection data from Motus collaborators have been used to estimate stopover duration (Dossman et al 2016, Mann et al 2017, Neima 2017, activity level, e.g., onset of diel activity, stopover versus active migration (Crysler et al 2016;Morbey et al, unpublished data), regional and site fidelity during migratory stopover (Mann et al 2017, Neima 2017, precise departure and arrival times , Dossman et al 2016, Müller et al 2016), departure and flight orientation , Crysler et al 2016, Kishkinev et al 2016, Neima 2017, flight distance, time, and therefore flight speed (Woodworth et al 2014, 2015, Brown and Taylor 2015, Crysler et al 2016, Falconer et al 2016, colony attendance patterns (Loring 2016), and types of movements, e.g., migratory, relocation (Woodworth et al 2014, 2015, Crysler et al 2016). …”

Section: Current Usesmentioning

confidence: 99%

“…The ability to estimate these parameters has led to advancements in our understanding of the movement behavior of small animals, including the spatial and temporal scale of migratory stopover , Mann et al 2017, Neima 2017, the influence of ecological barriers on movement behaviour , Crysler 2016, Dossman et al 2016, postfledging dispersal movements (Brown andTaylor 2015, Crysler 2015), migratory connectivity (McKellar et al 2015), the proximate mechanisms of orientation and navigation (Kishkinev et al 2016), and effects of availability of roosting habitat on duration of stay (Mann et al 2017). We have also gained understanding of how movements are influenced by intrinsic and extrinsic factors, including age (Brown and Taylor 2015, Crysler et al 2016, Dossman et al 2016, Kennedy et al 2016, sex (Falconer et al 2016), physiological condition (Dossman et al 2016, Eikenaar et al 2017, habitat (Woodworth et al 2014), and weather , Dossman et al 2016, Loring 2016, Neima 2017.…”

Section: Current Usesmentioning

confidence: 99%

“…We have also gained understanding of how movements are influenced by intrinsic and extrinsic factors, including age (Brown and Taylor 2015, Crysler et al 2016, Dossman et al 2016, Kennedy et al 2016, sex (Falconer et al 2016), physiological condition (Dossman et al 2016, Eikenaar et al 2017, habitat (Woodworth et al 2014), and weather , Dossman et al 2016, Loring 2016, Neima 2017.…”

Section: Current Usesmentioning

confidence: 99%

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The Motus Wildlife Tracking System: a collaborative research network to enhance the understanding of wildlife movement

Taylor¹,

Crewe²,

Mackenzie³

et al. 2017

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ABSTRACT. We describe a new collaborative network, the Motus Wildlife Tracking System (Motus; https://motus.org), which is an international network of researchers using coordinated automated radio-telemetry arrays to study movements of small flying organisms including birds, bats, and insects, at local, regional, and hemispheric scales. Radio-telemetry has been a cornerstone of tracking studies for over 50 years, and because of current limitations of geographic positioning systems (GPS) and satellite transmitters, has remained the primary means to track movements of small animals with high temporal and spatial precision. Automated receivers, along with recent miniaturization and digital coding of tags, have further improved the utility of radio-telemetry by allowing many individuals to be tracked continuously and simultaneously across broad landscapes. Motus is novel among automated arrays in that collaborators employ a single radio frequency across receiving stations over a broad geographic scale, allowing individuals to be detected at sites maintained by others. Motus also coordinates, disseminates, and archives detections and associated metadata in a central repository. Combined with the ability to track many individuals simultaneously, Motus has expanded the scope and spatial scale of research questions that can be addressed using radio-telemetry from local to regional and even hemispheric scales. Since its inception in 2012, more than 9000 individuals of over 87 species of birds, bats, and insects have been tracked, resulting in more than 250 million detections. This rich and comprehensive dataset includes detections of individuals during all phases of the annual cycle (breeding, migration, and nonbreeding), and at a variety of spatial scales, resulting in novel insights into the movement behavior of small flying animals. The value of the Motus network will grow as spatial coverage of stations and number of partners and collaborators increases. With continued expansion and support, Motus can provide a framework for global collaboration, and a coordinated approach to solving some of the most complex problems in movement biology and ecology.Le Système de suivi de la faune Motus : un réseau de recherche collaboratif visant à mieux comprendre le déplacement des animaux RÉSUMÉ. Le Système de suivi de la faune Motus (Motus; https://motus.org), un nouveau réseau collaboratif de chercheurs internationaux, repose sur un ensemble coordonné de stations automatisées de radiotélémétrie pour étudier le déplacement de petits organismes volant, comme les oiseaux, les chauves-souris et les insectes, aux échelles locales et régionales, et à celle de l'hémisphère. Pierre angulaire pour les études de suivi depuis plus de 50 ans, la radiotélémétrie est encore le principal moyen de suivre le déplacement de petits animaux avec une grande précision temporelle et spatiale, en raison des limites que présentent les émetteurs basés sur le système de positionnement géographique (GPS) ou satellite. Des stations réceptrices automatisées,...

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Section: Current Usesmentioning

confidence: 99%

Section: Current Usesmentioning

confidence: 99%

Section: Current Usesmentioning

confidence: 99%

See 1 more Smart Citation

The Motus Wildlife Tracking System: a collaborative research network to enhance the understanding of wildlife movement

Taylor¹,

Crewe²,

Mackenzie³

et al. 2017

ACE

Self Cite

245

289

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“…, Dossman et al. ). Field‐based studies conducted at the individual level are particularly useful for understanding such responses to environmental cues and for linking physiology and behavior.…”

mentioning

confidence: 99%

“…, Dossman et al. , Müller et al. ), and determining factors that influence the duration of migratory stopovers (Dossman et al.…”

mentioning

confidence: 99%

Detection range of songbirds using a stopover site by automated radio‐telemetry

et al. 2019

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A major uncertainty in automated radio‐telemetry studies of small birds is the detection range of receiving antennas. We compared simultaneous daytime detections (± 30 s) by automated and manual radio‐telemetry to assess detection probability and the proportion of transmissions detected for birds on migratory stopover as a function of distance, foraging guild (Black‐throated Blue Warblers, Setophaga caerulescens, and Yellow‐rumped Warblers, Dendroica coronata coronata, represented mid‐canopy foliage gleaners and White‐throated Sparrows, Zonotrichia albicollis, represented a ground forager), habitat type, meteorological variables, tower antenna number (1–4), and the position of a bird relative to the receiving antenna's bearing (offset angle). Our study was conducted at a migratory stopover site in southern Ontario, Canada. Most detections were in dense to sparse forest, and all individuals were within 1.03 km of the automated receiving station. Daily detection probability was near 100% for both foraging guilds. However, within 30 s before and after a manual radio‐telemetry location was made, detection probability and the proportion of transmissions detected by automated radio‐telemetry declined with distance, was higher for warblers than sparrows, and was lowest for 90° offset angles. Our results suggest that when research goals do not require detections with high temporal frequency, e.g., estimation of departure date or daily departure probability, our study design had an effective detection range of at least 1 km. However, where temporal precision is required, e.g., to investigate movements and changes in activity levels during stopover, detection range was ~300 m for ground‐foraging sparrows and 600 m for mid‐canopy foraging warblers, which is much lower than the presumed detection range of antennas under optimal conditions (15 km). This corresponds to a spatial area of coverage for forest‐dwelling birds of ~0.3–1.1 km2. Our results suggest that to optimally configure an automated radio‐telemetry array at the regional scale, investigators should carefully consider detection range and its underlying covariates, including species type, the habitat matrix, and the orientation of antennas relative to preferred habitat.

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The urge to breed early: Similar responses to environmental conditions in short‐ and long‐distance migrants during spring migration

Rüppel

Hüppop

Schmaljohann

et al. 2023

Ecology and Evolution

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Birds migrating different distances experience different temporal, energetic, physiological, and physical constraints throughout migration, which is reflected in their migration strategy. Consequently, we predict different behavioral decisions to similar environmental cues between short-and long-distance migrants, which has been documented for autumn migration. Here, we focus on the question whether tradeoff decisions regarding departure, routing, and landing when alternating between migratory endurance flights and stopovers also differ during spring migration. As early arrivals at the breeding grounds should be ultimately favored regardless of migration distance, selection may favor more similar behavioral decisions in spring than in autumn. We radio-tagged short-and long-distance migratory songbirds at stopover sites along the German North Sea coast during spring and automatically tracked their migratory behavior using a large-scale network of receiver stations. Once departed, birds could either cross the sea or detour along the coast. We corrected for spatially biased detection data, using a hierarchical multistate model to assess how birds respond to variation in environmental conditions in their day-to-day departure decisions and route selection. The day-to-day departure probability was higher in long-distance migrants independently of the routing decision. Irrespective of migration distance, all species more likely departed under light winds and rainless conditions, while the influence of air pressure change and relative humidity was species-specific. By accounting for detection probabilities, we estimated that about half of all individuals of each species crossed the sea but did not find differences between short-and longdistance migrants. Offshore flights were more likely when winds blew offshore and began earlier within the night compared with onshore flights. Our results suggest that selection more similarly affects birds of different migration distances in spring than in autumn. These findings put the focus toward how ultimate mechanisms may shape departure and routing decisions differently between migration seasons.

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The effects of wind and fuel stores on stopover departure behavior across a migratory barrier

Cited by 57 publications

References 56 publications

The Motus Wildlife Tracking System: a collaborative research network to enhance the understanding of wildlife movement

The Motus Wildlife Tracking System: a collaborative research network to enhance the understanding of wildlife movement

Detection range of songbirds using a stopover site by automated radio‐telemetry

The urge to breed early: Similar responses to environmental conditions in short‐ and long‐distance migrants during spring migration

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