Nils Linek

Max Planck Institute of Animal Behavior

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Martin Wikelski

University of Konstanz

Jesko Partecke

Max Planck Institute of Animal Behavior

Tamara Volkmer

Max Planck Institute of Animal Behavior

Dina K. N. Dechmann

University of Konstanz

Timm A. Wild

Max Planck Institute of Animal Behavior

Wolfgang Fiedler

Max Planck Institute of Animal Behavior

Nina Richter

Max Planck Institute of Animal Behavior

Pauli Viljoen

South African National Parks

Louis van Schalkwyk

University of Pretoria

J. Ryan Shipley

Swiss Federal Institute for Forest, Snow and Landscape Research

Cooperative Institutions

Max Planck Institute of Animal Behavior

Max Planck Institute for Ornithology

University of Konstanz

Max Planck Society

Russian Academy of Sciences

Yale University

Lomonosov Moscow State University

University of Cyprus

University of Copenhagen

University of Groningen

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A partial migrant relies upon a range-wide cue set but uses population-specific weighting for migratory timing

Movement Ecology (2021)

Nils Linek Paweł Brzęk Phillip Gienapp M. Teague O’Mara Ivan Pokrovsky

Many birds species range over vast geographic regions and migrate seasonally between their breeding and overwintering sites. Deciding when to depart for migration is one of the most consequential life-history decisions an individual may make. However, it is still not fully understood which environmental cues are used to time the onset of migration and to what extent their relative importance differs across a range of migratory strategies. We focus on departure decisions of a songbird, the Eurasian blackbird Turdus merula, in which selected Russian and Polish populations are full migrants which travel relatively long-distances, whereas Finnish and German populations exhibit partial migration with shorter migration distances.We used telemetry data from the four populations (610 individuals) to determine which environmental cues individuals from each population use to initiate their autumn migration.When departing, individuals in all populations selected nights with high atmospheric pressure and minimal cloud cover. Fully migratory populations departed earlier in autumn, at longer day length, at higher ambient temperatures, and during nights with higher relative atmospheric pressure and more supportive winds than partial migrants; however, they did not depart in higher synchrony. Thus, while all studied populations used the same environmental cues, they used population-specific and locally tuned thresholds to determine the day of departure.Our data support the idea that migratory timing is controlled by general, species-wide mechanisms, but fine-tuned thresholds in response to local conditions.

Animal ecology

Songbird

Bird migration

Overwintering

10.1186/s40462-021-00298-y

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Citations (12)

A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network

Research Square (Research Square) (2022)

Timm A. Wild Louis van Schalkwyk Pauli Viljoen Georg Heine Nina Richter

Abstract Bio-telemetry from small tags attached to animals is one of the principal methods for studying the ecology and behaviour of wildlife. The field has constantly evolved over the last 80 years as technological improvement enabled a diversity of sensors to be integrated into the tags (e.g., GPS, accelerometers, etc.). However, retrieving data from tags on free-ranging animals remains a challenge since satellite and GSM networks are relatively expensive and or power hungry. Recently a new class of low-power communication networks have been developed and deployed worldwide to connect the internet of things (IoT). Here, we evaluated one of these, the Sigfox IoT network, for the potential as a real-time multi-sensor data retrieval and tag commanding system for studying fauna across a diversity of species and ecosystems. We tracked 312 individuals across 30 species (from 25 g bats to 3 t elephants) with seven different device concepts, resulting in more than 177,742 successful transmissions. We found a maximum line of sight communication distance of 280 km (on a flying cape vulture [ Gyps coprotheres ]), which sets a new documented record for animal-borne digital data transmission using terrestrial infrastructure. The average transmission success rate amounted to 68.3% (SD 22.1) on flying species and 54.1% (SD 27.4) on terrestrial species. In addition to GPS data, we also collected and transmitted data products from accelerometers, barometers, and thermometers. Further, we assessed the performance of Sigfox Atlas Native, a low-power method for positional estimates based on radio signal strengths and found a median accuracy of 12.89 km (MAD 5.17) on animals. We found that robust real-time communication (median message delay of 1.49 s), the extremely small size of the tags (starting at 1.28 g without GPS), and the low power demands (as low as 5.8 µAh per transmitted byte) unlock new possibilities for ecological data collection and global animal observation.

GSM

10.21203/rs.3.rs-2272694/v1

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Citations (2)

A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network

Animal Biotelemetry (2023)

Timm A. Wild Louis van Schalkwyk Pauli Viljoen Georg Heine Nina Richter

GSM

10.1186/s40317-023-00326-1

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Citations (22)

Biological Earth observation with animal sensors

Trends in Ecology & Evolution (2022)

Walter Jetz Grigori Tertitski Roland Kays Uschi Mueller Martin Wikelski

Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmental change.

Earth observation

Human animal

Biological motion

Tracking (education)

Animal Behavior

Animal health

10.1016/j.tree.2021.11.011

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Citations (80)

Time synchronisation for millisecond-precision on bio-loggers

Movement Ecology (2024)

Timm A. Wild Georg Wilbs Dina K. N. Dechmann Jenna E. Kohles Nils Linek

Abstract Time-synchronised data streams from bio-loggers are becoming increasingly important for analysing and interpreting intricate animal behaviour including split-second decision making, group dynamics, and collective responses to environmental conditions. With the increased use of AI-based approaches for behaviour classification, time synchronisation between recording systems is becoming an essential challenge. Current solutions in bio-logging rely on manually removing time errors during post processing, which is complex and typically does not achieve sub-second timing accuracies. We first introduce an error model to quantify time errors, then optimise three wireless methods for automated onboard time (re)synchronisation on bio-loggers (GPS, WiFi, proximity messages). The methods can be combined as required and, when coupled with a state-of-the-art real time clock, facilitate accurate time annotations for all types of bio-logging data without need for post processing. We analyse time accuracy of our optimised methods in stationary tests and in a case study on 99 Egyptian fruit bats ( Rousettus aegyptiacus ). Based on the results, we offer recommendations for projects that require high time synchrony. During stationary tests, our low power synchronisation methods achieved median time accuracies of 2.72 / 0.43 ms (GPS / WiFi), compared to UTC time, and relative median time accuracies of 5 ms between tags (wireless proximity messages). In our case study with bats, we achieved a median relative time accuracy of 40 ms between tags throughout the entire 10-day duration of tag deployment. Using only one automated resynchronisation per day, permanent UTC time accuracies of ≤ 185 ms can be guaranteed in 95% of cases over a wide temperature range between 0 and 50 °C. Accurate timekeeping required a minimal battery capacity, operating in the nano- to microwatt range. Time measurements on bio-loggers, similar to other forms of sensor-derived data, are prone to errors and so far received little scientific attention. Our combinable methods offer a means to quantify time errors and autonomously correct them at the source (i.e., on bio-loggers). This approach facilitates sub-second comparisons of simultaneously recorded time series data across multiple individuals and off-animal devices such as cameras or weather stations. Through automated resynchronisations on bio-loggers, long-term sub-second accurate timestamps become feasible, even for life-time studies on animals. We contend that our methods have potential to greatly enhance the quality of ecological data, thereby improving scientific conclusions.

Animal ecology

Data logger

Millisecond

Biotelemetry

10.1186/s40462-024-00512-7

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Citations (0)

New frontiers in bird migration research

Current Biology (2022)

Andrea Flack Ellen O. Aikens Andrea Kölzsch Elham Nourani Katherine R. S. Snell

Bird migration

10.1016/j.cub.2022.08.028

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Citations (51)

A songbird adjusts its heart rate and body temperature in response to season and fluctuating daily conditions

Philosophical Transactions of the Royal Society B Biological Sciences (2021)

Nils Linek Tamara Volkmer J. Ryan Shipley Cornelia W. Twining Daniel Zúñiga

In a seasonal world, organisms are continuously adjusting physiological processes relative to local environmental conditions. Owing to their limited heat and fat storage capacities, small animals, such as songbirds, must rapidly modulate their metabolism in response to weather extremes and changing seasons to ensure survival. As a consequence of previous technical limitations, most of our existing knowledge about how animals respond to changing environmental conditions comes from laboratory studies or field studies over short temporal scales. Here, we expanded beyond previous studies by outfitting 71 free-ranging Eurasian blackbirds ( Turdus merula ) with novel heart rate and body temperature loggers coupled with radio transmitters, and followed individuals in the wild from autumn to spring. Across seasons, blackbirds thermoconformed at night, i.e. their body temperature decreased with decreasing ambient temperature, but not so during daytime. By contrast, during all seasons blackbirds increased their heart rate when ambient temperatures became colder. However, the temperature setpoint at which heart rate was increased differed between seasons and between day and night. In our study, blackbirds showed an overall seasonal reduction in mean heart rate of 108 beats min −1 (21%) as well as a 1.2°C decrease in nighttime body temperature. Episodes of hypometabolism during cold periods likely allow the birds to save energy and, thus, help offset the increased energetic costs during the winter when also confronted with lower resource availability. Our data highlight that, similar to larger non-hibernating mammals and birds, small passerine birds such as Eurasian blackbirds not only adjust their heart rate and body temperature on daily timescales, but also exhibit pronounced seasonal changes in both that are modulated by local environmental conditions such as temperature. This article is part of the theme issue ‘Measuring physiology in free-living animals (Part I)’.

Songbird

Homeothermy

10.1098/rstb.2020.0213

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Citations (17)

Migratory lifestyle carries no added overall energy cost in a partial migratory songbird

Nature Ecology & Evolution (2024)

Nils Linek Scott W. Yanco Tamara Volkmer Daniel Zúñiga Martin Wikelski

Songbird

Energy budget

Energy cost

Endotherm

Doubly labeled water

Bird migration

10.1038/s41559-024-02545-y

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Citations (3)

Time synchronisation for millisecond-precision on bio-loggers

Research Square (Research Square) (2024)

Timm A. Wild Georg Wilbs Dina K. N. Dechmann Jenna E. Kohles Nils Linek

Abstract Time-synchronised data streams from bio-loggers are becoming increasingly important for analysing and interpreting intricate animal behaviour including split-second decision making, group dynamics, and collective responses to environmental conditions. With the increased use of AI-based approaches for behaviour classification, time synchronisation between recording systems is becoming an essential challenge. Current solutions in bio-logging rely on manually removing time errors during post processing, which is complex and typically does not achieve sub-second timing accuracies. We first introduce an error model to quantify time errors, then optimise three wireless methods for automated onboard time (re)synchronisation on bio-loggers (GPS, WiFi, proximity messages). The methods can be combined as required and, when coupled with a state-of-the-art real time clock, facilitate accurate time annotations for all types of bio-logging data without need for post processing. We analyse time accuracy of our optimised methods in stationary tests and in a case study on 99 Egyptian fruit bats (Rousettus aegyptiacus). Based on the results, we offer recommendations for projects that require high time synchrony. In our case study with bats, we achieved a median relative time accuracy of 40 ms between tags throughout the entire 10-day duration of tag deployment. During stationary tests, our low power synchronisation methods achieved median time accuracies of 2.72 / 0.43 ms (GPS / WiFi), compared to UTC time, and relative median time accuracies of 5 ms between tags (wireless proximity messages). Using only one automated resynchronisation per day, permanent UTC time accuracies of ≤ 185 ms can be guaranteed in 95% of cases over a wide temperature range between 0 to 50°C. Accurate timekeeping required a minimal battery capacity, operating in the nano- to microwatt range. Time measurements on bio-loggers, similar to other forms of sensor-derived data, are prone to errors and so far received little scientific attention. Our combinable methods offer a means to quantify time errors and autonomously correct them at the source (i.e., on bio-loggers). This approach facilitates sub-second comparisons of simultaneously recorded time series data across multiple individuals and off-animal devices such as cameras or weather stations. Through automated resynchronisations on bio-loggers, long-term sub-second accurate timestamps become feasible, even for life-time studies on animals. We contend that our methods have potential to greatly enhance the quality of ecological data, thereby improving scientific conclusions.

Millisecond

10.21203/rs.3.rs-4494865/v1

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Citations (0)