Static landscape features predict uplift locations for soaring birds across Europe

Soaring flight is a remarkable adaptation to reduce movement costs by taking advantage of atmospheric uplifts. The movement pattern of soaring birds is shaped by the spatial and temporal availability and intensity of uplifts, which result from an interaction of local weather conditions with the underlying landscape structure. We used soaring flight locations and vertical speeds of an obligate soaring species, the white stork (Ciconia ciconia), as proxies for uplift availability and intensity. We then tested if static landscape features such as topography and land cover, instead of the commonly used weather information, could predict and map the occurrence and intensity of uplifts across Europe. We found that storks encountering fewer uplifts along their routes, as determined by static landscape features, suffered higher energy expenditures, approximated by their overall body dynamic acceleration. This result validates the use of static features as uplift predictors and suggests the existence of a direct link between energy expenditure and static landscape structure, thus far largely unquantified for flying animals. Our uplift availability map represents a computationally efficient proxy of the distribution of movement costs for soaring birds across the world's landscapes. It thus provides a base to explore the effects of changes in the landscape structure on the energy expenditure of soaring birds, identify low-cost movement corridors and ultimately inform the planning of anthropogenic developments.

Subject (DDC)

570 Biosciences, Biology

Keywords

habitat suitability, movement ecology, random forest, species distribution model, anthropogenic infrastructure, energy landscape

Cite This

ISO 690

SCACCO, Martina, Andrea FLACK, Olivier DURIEZ, Martin WIKELSKI, Kamran SAFI, 2019. Static landscape features predict uplift locations for soaring birds across Europe. In: Royal Society Open Science. 6(1), 181440. eISSN 2054-5703. Available under: doi: 10.1098/rsos.181440

BibTex

@article{Scacco2019-01Stati-44671,
  year={2019},
  doi={10.1098/rsos.181440},
  title={Static landscape features predict uplift locations for soaring birds across Europe},
  number={1},
  volume={6},
  journal={Royal Society Open Science},
  author={Scacco, Martina and Flack, Andrea and Duriez, Olivier and Wikelski, Martin and Safi, Kamran},
  note={Article Number: 181440}
}

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    <dcterms:abstract xml:lang="eng">Soaring flight is a remarkable adaptation to reduce movement costs by taking advantage of atmospheric uplifts. The movement pattern of soaring birds is shaped by the spatial and temporal availability and intensity of uplifts, which result from an interaction of local weather conditions with the underlying landscape structure. We used soaring flight locations and vertical speeds of an obligate soaring species, the white stork (Ciconia ciconia), as proxies for uplift availability and intensity. We then tested if static landscape features such as topography and land cover, instead of the commonly used weather information, could predict and map the occurrence and intensity of uplifts across Europe. We found that storks encountering fewer uplifts along their routes, as determined by static landscape features, suffered higher energy expenditures, approximated by their overall body dynamic acceleration. This result validates the use of static features as uplift predictors and suggests the existence of a direct link between energy expenditure and static landscape structure, thus far largely unquantified for flying animals. Our uplift availability map represents a computationally efficient proxy of the distribution of movement costs for soaring birds across the world's landscapes. It thus provides a base to explore the effects of changes in the landscape structure on the energy expenditure of soaring birds, identify low-cost movement corridors and ultimately inform the planning of anthropogenic developments.</dcterms:abstract>
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Bibliography of Konstanz

Yes

Refereed

Yes