skip to main content

Attention:

The NSF Public Access Repository (NSF-PAR) system and access will be unavailable from 11:00 PM ET on Friday, September 13 until 2:00 AM ET on Saturday, September 14 due to maintenance. We apologize for the inconvenience.


Search for: All records

Creators/Authors contains: "Tonelli, Benjamin A."

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Abstract

    Rare birds known as “accidentals” or “vagrants” have long captivated birdwatchers and puzzled biologists, but the drivers of these rare occurrences remain elusive. Errors in orientation or navigation are considered one potential driver: migratory birds use the Earth’s magnetic field—sensed using specialized magnetoreceptor structures—to traverse long distances over often unfamiliar terrain. Disruption to these magnetoreceptors or to the magnetic field itself could potentially cause errors leading to vagrancy. Using data from 2 million captures of 152 landbird species in North America over 60 years, we demonstrate a strong association between disruption to the Earth’s magnetic field and avian vagrancy during fall migration. Furthermore, we find that increased solar activity—a disruptor of the avian magnetoreceptor—generally counteracts this effect, potentially mitigating misorientation by disabling the ability for birds to use the magnetic field to orient. Our results link a hypothesized cause of misorientation to the phenomenon of avian vagrancy, further demonstrating the importance of magnetoreception among the orientation mechanisms of migratory birds. Geomagnetic disturbance may have important downstream ecological consequences, as vagrants may experience increased mortality rates or facilitate range expansions of avian populations and the organisms they disperse.

     
    more » « less
  2. Abstract

    Rapid advances in the field of movement ecology have led to increasing insight into both the population‐level abundance patterns and individual‐level behaviour of migratory species. Despite this progress, research questions that require scaling individual‐level understanding of the behaviour of migrating organisms to the population level remain difficult to investigate.

    To bridge this gap, we introduce a generalizable framework for training full‐annual cycle individual‐based models of migratory movements by combining information from tracking studies and species occurrence records. Focusing on migratory birds, we call this method: Models of Individual Movement of Avian Species (MIMAS). We implement MIMAS to design individual‐based models of avian migration that are trained using previously published weekly occurrence maps and fit via Approximate Bayesian Computation.

    MIMAS models leverage individual‐ and population‐level information to faithfully represent continental‐scale migration patterns. Models can be trained successfully for species even when little existing individual‐level data is available for parameterization by relying on population‐level information. In contrast to existing mathematical models of migration, MIMAS explicitly represents and estimates behavioural attributes of migrants. MIMAS can additionally be used to simulate movement over consecutive migration seasons, and models can be easily updated or validated as new empirical data on migratory behaviours becomes available.

    MIMAS can be applied to a variety of research questions that require representing individual movement at large scales. We demonstrate three applied uses for MIMAS: estimating population‐specific migratory phenology, predicting the spatial patterns and magnitude of ectoparasite dispersal by migrants, and simulating the spread of a pathogen across the annual cycle of a migrant species. Currently, MIMAS can easily be used to build models for hundreds of migratory landbird species but can also be adapted in the future to build models of other types of migratory animals.

     
    more » « less