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Modelling non-Euclideanmovement and landscape connectivity in highly structured ecological networks
Methods in Ecology and Evolution (2014)
  • Chris Sutherland, University of Massachusetts - Amherst
  • Angela Fuller
  • J. Royle
1. Movement is influenced by landscape structure, configuration and geometry, but measuring distance as perceived by animals poses technical and logistical challenges. Instead, movement is typically measured using Euclidean distance, irrespective of location or landscape structure, or is based on arbitrary cost surfaces. A
recently proposed extension of spatial capture-recapture (SCR)models resolves this issue using spatial encounter
histories of individuals to calculate least-cost paths (ecological distance: Ecology, 94, 2013, 287) thereby relaxing
the Euclidean assumption. We evaluate the consequences of not accounting for movement heterogeneity when
estimating abundance in highly structured landscapes, and demonstrate the value of this approach for estimating
biologically realistic space-use patterns and landscape connectivity.
2. We simulated SCR data in a riparian habitat network, using the ecological distance model under a range of scenarios where space-use in and around the landscape was increasingly associated with water (i.e. increasingly less Euclidean). To assess the influence of miscalculating distance on estimates of population size, we compared the results from the ecological and Euclidean distance based models. We then demonstrate that the ecological
distance model can be used to estimate home range geometry when space use is not symmetrical. Finally, we provide
a method for calculating landscape connectivity based on modelled species-landscape interactions generated from capture-recapture data.
3. Using ecological distance always produced unbiased estimates of abundance. Explicitly modelling the strength of the species-landscape interaction provided a direct measure of landscape connectivity and better characterized true home range geometry. Abundance under the Euclidean distance model was increasingly (negatively) biased
as space use was more strongly associated with water and, because home ranges are assumed to be symmetrical, produced poor characterisations of home range geometry and no information about landscape connectivity.
4. The ecological distance SCR model uses spatially indexed capture-recapture data to estimate how activity patterns are influenced by landscape structure. As well as reducing bias in estimates of abundance, this approach provides biologically realistic representations of home range geometry, and direct information about species landscape interactions. The incorporation of both structural (landscape) and functional (movement) components of connectivity provides a direct measure of species-specific landscape connectivity.
  • abundance,
  • animal movement,
  • dendritic ecological network,
  • density,
  • ecological distance,
  • functional connectivity,
  • habitat network,
  • streamdistance,
  • structural connectivity
Publication Date
Winter December 30, 2014
Citation Information
Chris Sutherland, Angela Fuller and J. Royle. "Modelling non-Euclideanmovement and landscape connectivity in highly structured ecological networks" Methods in Ecology and Evolution Vol. 6 Iss. 2 (2014) p. 169 - 177
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