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The scale of effect of landscape context varies with the species’ response variable measured

  • Andrew D. Moraga
  • Amanda E. MartinEmail author
  • Lenore Fahrig
Research Article

Abstract

Context

To detect an effect of landscape context on a species’ response, the landscape variables need to be measured within the appropriate distance from the species’ response, i.e. at the scale of effect. However, it is not clear what factors determine the scale of effect.

Objective

Our objective was to test the prediction that the scale of effect should be smallest when the species’ response is fecundity, larger for abundance, and larger still for occurrence.

Methods

We compared the scale of effect of two landscape variables (road density, forest proportion) on the three responses (fecundity, abundance, occurrence) for the wood frog (Lithobates sylvaticus) in eastern Ontario, Canada. We used egg mass surveys of 34 ponds to estimate fecundity (mean eggs/mass), abundance (number of masses), and occurrence (presence/absence of egg masses). We then empirically estimated the scale of effect of each landscape variable on each response.

Results

The scale of effect differed among responses, from 0.2 to 3.0 km radii; however, it did not vary in the predicted order. Furthermore, the order was not consistent between the two landscape variables.

Conclusions

Our results show that the scale of effect of a landscape variable on a given species can differ for different response variables. However, they also suggest that these differences in the scale of effect are not predictable. Thus, the most reliable way to ensure a landscape context study is conducted at the correct spatial extent is to estimate the scale of effect empirically, rather than ‘guesstimating’ the extent a priori.

Keywords

Landscape structure Landscape size Multi-scale model Focal patch Spatial scale Landscape extent 

Notes

Acknowledgements

We thank the private landowners who let us sample their ponds. Erik Pervin and Caitlin Brunton were indispensable field assistants. We thank Joseph Bennett and Jeremy Kerr for helpful comments and suggestions. We also thank the associate editor and two anonymous reviewers for their comments on an earlier version of this paper. This work was supported by a Natural Sciences and Engineering Research Council of Canada Grant to Lenore Fahrig.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standard

All work complied with the Canadian Council on Animal Care requirements for the use of eggs in research (Category of Invasiveness A).

Data availability

The data sets generated during the current study are available in the Mendeley Data repository,  https://doi.org/10.17632/ccw64rpj22.1.

Supplementary material

10980_2019_808_MOESM1_ESM.docx (20 kb)
Supplementary material 1 (DOCX 19 kb)
10980_2019_808_MOESM2_ESM.docx (26 kb)
Supplementary material 2 (DOCX 25 kb)

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Geomatics and Landscape Ecology Research Laboratory, Department of BiologyCarleton UniversityOttawaCanada
  2. 2.School of Environment Resources and SustainabilityUniversity of WaterlooWaterlooCanada
  3. 3.Environment and Climate Change CanadaNational Wildlife Research CentreOttawaCanada

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