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Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity

Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity

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VAN TOOR, Mariëlle L., Bart KRANSTAUBER, Scott H. NEWMAN, Diann J. PROSSER, John Y. TAKEKAWA, Georgios TECHNITIS, Robert WEIBEL, Martin WIKELSKI, Kamran SAFI, 2018. Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity. In: Landscape Ecology. 33(6), pp. 879-893. ISSN 0921-2973. eISSN 1572-9761. Available under: doi: 10.1007/s10980-018-0637-9

@article{vanToor2018Integ-43015, title={Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity}, year={2018}, doi={10.1007/s10980-018-0637-9}, number={6}, volume={33}, issn={0921-2973}, journal={Landscape Ecology}, pages={879--893}, author={van Toor, Mariëlle L. and Kranstauber, Bart and Newman, Scott H. and Prosser, Diann J. and Takekawa, John Y. and Technitis, Georgios and Weibel, Robert and Wikelski, Martin and Safi, Kamran} }

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.<br /><br />Objectives<br /><br />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.<br /><br />Methods<br /><br />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.<br /><br />Results<br /><br />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.<br /><br />Conclusions<br /><br />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. van Toor, Mariëlle L. Takekawa, John Y. 2018-08-08T09:11:43Z Weibel, Robert Newman, Scott H. eng Technitis, Georgios Technitis, Georgios Safi, Kamran Wikelski, Martin van Toor, Mariëlle L. Newman, Scott H. Wikelski, Martin 2018-08-08T09:11:43Z Safi, Kamran Kranstauber, Bart Prosser, Diann J. terms-of-use Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity Takekawa, John Y. Prosser, Diann J. 2018 Kranstauber, Bart Weibel, Robert

Dateiabrufe seit 08.08.2018 (Informationen über die Zugriffsstatistik)

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