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  • 1.
    Kleyheeg, Erik
    et al.
    Max Planck Inst Ornithol, Germany.
    Fiedler, Wolfgang
    Max Planck Inst Ornithol, Germany.
    Safi, Kamran
    Max Planck Inst Ornithol, Germany.
    Waldenström, Jonas
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Wikelski, Martin
    Max Planck Inst Ornithol, Germany.
    van Toor, Mariëlle L.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    A Comprehensive Model for the Quantitative Estimation of Seed Dispersal by Migratory Mallards2019In: Frontiers in Ecology and Evolution, E-ISSN 2296-701X, Vol. 7, p. 1-14, article id 40Article in journal (Refereed)
    Abstract [en]

    Long-distance seed dispersal is an important ecosystem service provided by migratory animals. Plants inhabiting discrete habitats, like lakes and wetlands, experience dispersal limitation, and rely heavily on zoochory for their spatial population dynamics. Granivorous waterbirds may disperse viable seeds of wetland plants over long distances during migration. The limited knowledge of waterbird migration has long hampered the evaluation of the importance of waterbirds in seed dispersal, requiring key metrics such as realistic dispersal distances. Using recent GPS tracking of mallards during spring migration, we built a mechanistic seed dispersal model to estimate realistic dispersal distances. Mallards are abundant, partially migratory ducks known to consume seeds of >300 European plant species. Based on the tracking data, we informed a mallard migration simulator to obtain a probabilistic spring migration model for the mallard population wintering at Lake Constance in Southern Germany. We combined the spring migration model with seed retention curves to develop seed dispersal kernels. We also assessed the effects of pre-migratory fasting and the availability of suitable deposition habitats for aquatic and wetland plants. Our results show that mallards at Lake Constance can disperse seeds in the northeastern direction over median distances of 293 and 413 km for seeds with short and long retention times, respectively, assuming a departure immediately after foraging. Pre-migratory fasting strongly affected the dispersal potential, with only 1-7% of ingested seeds left for dispersal after fasting for 12 h. Availability of a suitable deposition habitat was generally <5% along the migratory flyway. The high probability of seed deposition in a freshwater habitat during the first stopover, after the mallards completed the first migratory flight, makes successful dispersal most likely to happen at 204-322 km from Lake Constance. We concluded that the directed long-distance dispersal of plant seeds, realized by mallards on spring migration, may contribute significantly to large scale spatial plant population dynamics, including range expansion in response to shifting temperature and rainfall patterns under global warming. Our dispersal model is the first to incorporate detailed behavior of migratory waterbirds and can be readily adjusted to include other vector species when tracking data are available.

  • 2.
    van Toor, Mariëlle L.
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Avril, Alexis
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    Wu, Guohui
    SAS Inst Inc, USA.
    Holan, Scott H.
    Univ Missouri, USA.
    Waldenström, Jonas
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    As the Duck Flies-Estimating the Dispersal of Low-Pathogenic Avian Influenza Viruses by Migrating Mallards2018In: Frontiers in Ecology and Evolution, E-ISSN 2296-701X, Vol. 6, article id 208Article in journal (Refereed)
    Abstract [en]

    Many pathogens rely on the mobility of their hosts for dispersal. In order to understand and predict how a disease can rapidly sweep across entire continents, illuminating the contributions of host movements to disease spread is pivotal. While elegant proposals have been made to elucidate the spread of human infectious diseases, the direct observation of long-distance dispersal events of animal pathogens is challenging. Pathogens like avian influenza A viruses, causing only short disease in their animal hosts, have proven exceptionally hard to study. Here, we integrate comprehensive data on population and disease dynamics for low-pathogenic avian influenza viruses in one of their main hosts, the mallard, with a novel movement model trained from empirical, high-resolution tracks ofmallardmigrations. This allowed us to simulate individualmallard migrations from a key stopover site in the Baltic Sea for the entire population and link these movements to infection simulations. Using this novel approach, we were able to estimate the dispersal of low-pathogenic avian influenza viruses by migrating mallards throughout several autumn migratory seasons and predicted areas that are at risk of importing these viruses. We found that mallards are competent vectors and on average dispersed viruses over distances of 160 km in just 3 h. Surprisingly, our simulations suggest that such dispersal events are rare even throughout the entire autumn migratory season. Our approach directly combines simulated population-level movements with local infection dynamics and offers a potential converging point for movement and disease ecology.

  • 3.
    van Toor, Mariëlle L.
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science. Max Planck Inst Ornithol, Germany;Univ Konstanz, Germany.
    Kranstauber, Bart
    Univ Zurich, Switzerland.
    Newman, Scott H.
    Food & Agr Org United Nations, Ghana.
    Prosser, Diann J.
    US Geol Survey, USA.
    Takekawa, John Y.
    Suisun Resource Conservat Dist, USA.
    Technitis, Georgios
    Univ Zurich, Switzerland.
    Weibel, Robert
    Univ Zurich, Switzerland.
    Wikelski, Martin
    Max Planck Inst Ornithol, Germany;Univ Konstanz, Germany.
    Safi, Kamran
    Max Planck Inst Ornithol, Germany;Univ Konstanz, Germany.
    Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity2018In: Landscape Ecology, ISSN 0921-2973, E-ISSN 1572-9761, Vol. 33, no 6, p. 879-893Article in journal (Refereed)
    Abstract [en]

    High-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species' potential to link patches or populations are of importance. We introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories' plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range. We used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species' range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature. Simulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corroborating previous findings for this species. We show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting migratory connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.

  • 4.
    van Toor, Mariëlle L.
    et al.
    Linnaeus University, Faculty of Health and Life Sciences, Department of Biology and Environmental Science.
    O'Mara, M. Teague
    Max Planck Inst Ornithol, Germany;Univ Konstanz, Germany.
    Abedi-Lartey, Michael
    Max Planck Inst Ornithol, Germany.
    Wikelski, Martin
    Max Planck Inst Ornithol, Germany.;Univ Konstanz, Germany.
    Fahr, Jakob
    Max Planck Inst Ornithol, Germany;Braunschweig Univ Technol, Germany.
    Dechmann, Dina K. N.
    Max Planck Inst Ornithol, Germany;Univ Konstanz, Germany.
    Linking colony size with quantitative estimates of ecosystem services of African fruit bats2019In: Current Biology, ISSN 0960-9822, E-ISSN 1879-0445, Vol. 29, no 7, p. R237-R238Article in journal (Refereed)
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