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Disentangling the effects of wetland cover and urban development on quality of remaining wetlands

Urban Ecosystems volume 18, pages 663–684 (2015)Cite this article

Abstract

Effective landscape management decisions require knowledge of the relative effects of landscape variables on ecological responses, so that the most important landscape variables can be targeted for management. The relative effects of wetland cover and urbanization on remaining wetland quality are poorly understood because of correlations between these landscape variables. We determined the relative effects of wetland cover and urbanization on wetland quality by selecting a set of focal wetlands in which the percentages of the surrounding landscape in wetland cover and impervious cover were uncorrelated, at multiple spatial scales (extents). Wetland quality was inferred through abundance, taxa richness and taxa composition measures of vegetation and benthic macroinvertebrates. We found that reduced wetland cover was more detrimental than urbanization to remaining wetland quality, at least within the ranges of wetland cover (0 to 10%) and impervious cover (0 to 22%) in our study. In addition, we found that the spatial scale of these effects was large, in an area within 0.8 to 1.8 km of the wetlands. Our results indicate that policies aimed at reducing the impacts of urbanization around remaining wetlands will be only partly successful. Wetland management policies should also include wetland restoration in the landscape. Furthermore, our results indicate that management actions limited to buffer areas within tens of metres of wetlands will be only partly successful, because the influences of wetland cover and impervious cover on wetland quality extend much farther (0.8–1.8 km from wetlands). Policies applied to the whole landscape are needed.

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Acknowledgments

We thank L. Koponen, S. Turney and K. Seguin for their help with the fieldwork, the private landowners for granting us permission to sample on their properties, and all member of the GLEL for their support. We are also grateful to A. Morin, N. Cappuccino, and C. Boutin for their assistance, and to S. Declerck and two anonymous reviewers for helpful comments on a previous draft. This work was supported by a Natural Sciences and Engineering Council of Canada (NSERC) grant to L.F. and scholarship to T.P and an Ontario Graduate Scholarship to T.P.

Compliance with Ethical Standards

This work conforms to the ethical standards of Urban Ecosystems. We have no conflicts of interest and the work did not involve human participants. The species sampled were plants and invertebrates.

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Authors and Affiliations

  1. Department of Biology, Geomatics and Landscape Ecology Research Laboratory (GLEL), Carleton University, 1125 Colonel By Drive, Ottawa, ON, K1S 5B6, Canada

    Theresa Patenaude, Lenore Fahrig & Lenore Fahrig

  2. National Wildlife Research Centre, Environment Canada, Ottawa, Canada

    Adam C. Smith

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  1. Theresa Patenaude
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Correspondence to Lenore Fahrig.

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Appendix

Appendix

Fig. 8
figure 8

Number of sub-quadrat containing each aquatic plant taxon, in decreasing order, summed across all quadrats and sites

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Fig. 9
figure 9

Number of individuals of each benthic invertebrate taxon, in decreasing order, summed across all quadrats and sites

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Fig. 10
figure 10

Correlations (below diagonal), biplots (above diagonal), and variance inflation factors (numbers in parentheses, along diagonal) for all predictors of benthic invertebrate response variables. Wetland cover (wet) and impervious cover (imp) are the two main landscape predictors, the remaining predictors were included in some models to control for potentially confounding local and landscape factors (“a” = area, “per” = perimeter, “da” = date, “tp” = temperature, “pH” = pH, “cond” = conductivity, “ab” = absorption, “dpth” = maximum depth, “ag” = agricultural cover)

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Fig. 11
figure 11

Correlations (below diagonal), biplots (above diagonal), and variance inflation factors (numbers in parentheses, along diagonal) for all predictors of vegetation response variables. Wetland cover (wet) and impervious cover (imp) are the two main landscape predictors, the remaining predictors were included in some models to control for potentially confounding local and landscape factors (“a” = area, “per” = perimeter, “da” = date, “tp” = temperature, “pH” = pH, “cond” = conductivity, “ab” = absorption, “nq” = number of quadrats, “dpth” = maximum depth, “ag” = agricultural cover)

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Fig. 12
figure 12

Coefficients of univariate regressions of the response variables on each of three landscape predictor variables - wetland cover (open circles), impervious cover (black squares), agriculture cover (grey triangles) - at each spatial scale. The “scale of effectS” is the scale at which the absolute value of the coefficient is largest

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Patenaude, T., Smith, A.C. & Fahrig, L. Disentangling the effects of wetland cover and urban development on quality of remaining wetlands. Urban Ecosyst 18, 663–684 (2015). https://doi.org/10.1007/s11252-015-0440-1

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Keywords

  • Landscape composition
  • Habitat loss
  • Wetland loss
  • Multi-scale analysis
  • Urban wetlands
  • Wetland degradation
  • Wetland integrity