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Results: 111
Number of items: 111
  • Lisovski, S., van Dijk, J. G. B., Klinkenberg, D., Nolet, B. A., Fouchier, R. A. M., & Klaassen, M. (2018). The roles of migratory and resident birds in local avian influenza infection dynamics. Journal of Applied Ecology, 55(6), 2963-2975. https://doi.org/10.5281/zenodo.1203837
  • Open Access
    Lameris, T. K., Müskens, G. J. D. M., Kölzsch, A., Dokter, A. M., Van der Jeugd, H. P., & Nolet, B. A. (2018). Effects of harness-attached tracking devices on survival, migration, and reproduction in three species of migratory waterfowl. Animal Biotelemetry, 6, Article 7. https://doi.org/10.1186/s40317-018-0153-3
  • Open Access
    Dokter, A. M., Fokkema, W., Ebbinge, B. S., Olff, H., van der Jeugd, H. P., & Nolet, B. A. (2018). Agricultural pastures challenge the attractiveness of natural saltmarsh for a migratory goose. Journal of Applied Ecology, 55(6), 2707-2718. https://doi.org/10.1111/1365-2664.13168
  • Open Access
    Kleyheeg, E., Nolet, B. A., Otero-Ojea, S., & Soons, M. B. (2018). A mechanistic assessment of the relationship between gut morphology and endozoochorous seed dispersal by waterfowl. Ecology and Evolution, 8(22), 10857-10867. https://doi.org/10.1002/ece3.4544
  • Open Access
    Lameris, T. K. (2018). Outflying climate change: Optimal timing of migratory geese breeding in a warming Arctic. [Thesis, fully internal, Universiteit van Amsterdam].
  • De Boer, W. F., Van Krimpen, R. R. D., Stillman, R. A., Gyimesi, A., & Nolet, B. (2017). Data from: Predicting effects of water regime changes on waterbirds: insights from staging swans [Data set]. DRYAD. https://doi.org/10.5061/dryad.76r58
  • Nolet, B. A., Kölzsch, A., Elderenbosch, M., & van Noordwijk, A. J. (2017). Data from: Scaring waterfowl as a management tool: how much more do geese forage after disturbance? [Data set]. DRYAD. https://doi.org/10.5061/dryad.n4m05
  • Kleyheeg, E., Nolet, B., van Dijk, J. G., & Soons, M. B. (2017). Data from: Movement patterns of a keystone waterbird species are highly predictable from landscape configuration [Data set]. Movebank. https://doi.org/10.5441/001/1.p9c4nc97
  • Open Access
    Kleyheeg, E., van Dijk, J. G. B., Tsopoglou-Gkina, D., Woud, T. Y., Boonstra, D. K., Nolet, B. A., & Soons, M. B. (2017). Movement patterns of a keystone waterbird species are highly predictable from landscape configuration. Movement Ecology, 5, Article 2. https://doi.org/10.1186/s40462-016-0092-7
  • Open Access
    Baveco, J. M., Bergjord, A.-K., Bjerke, J. W., Chudzińska, M. E., Pellissier, L., Simonsen, C. E., Madsen, J., Tombre, I. M., & Nolet, B. A. (2017). Combining modelling tools to evaluate a goose management scheme. Ambio, 46(Supplement 2), 210-223. https://doi.org/10.1007/s13280-017-0899-5
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