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Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity

van Toor, Mariëlle L. (author)
Linnéuniversitetet,Institutionen för biologi och miljö (BOM),Max Planck Inst Ornithol, Germany;Univ Konstanz, Germany
Kranstauber, Bart (author)
Univ Zurich, Switzerland
Newman, Scott H. (author)
Food & Agr Org United Nations, Ghana
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Prosser, Diann J. (author)
US Geol Survey, USA
Takekawa, John Y. (author)
Suisun Resource Conservat Dist, USA
Technitis, Georgios (author)
Univ Zurich, Switzerland
Weibel, Robert (author)
Univ Zurich, Switzerland
Wikelski, Martin (author)
Max Planck Inst Ornithol, Germany;Univ Konstanz, Germany
Safi, Kamran (author)
Max Planck Inst Ornithol, Germany;Univ Konstanz, Germany
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 (creator_code:org_t)
2018-04-26
2018
English.
In: Landscape Ecology. - : Springer. - 0921-2973 .- 1572-9761. ; 33:6, s. 879-893
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • 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.

Subject headings

NATURVETENSKAP  -- Biologi -- Ekologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Ecology (hsv//eng)

Keyword

Anser indicus
Bar-headed goose
Empirical random trajectory generator
Migratory connectivity
Movement model
Stepping-stone migration model
Ecology
Ekologi

Publication and Content Type

ref (subject category)
art (subject category)

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