Relating mammal species richness to landscape patterns across multiple spatial scales

Abstract

Context

Understanding the relationships between spatial pattern, spatial scale and biodiversity can help ecologists to assess the impacts of environmental change and inform management plans. Spatial pattern research has often focussed on the effect of modified landscapes on species diversity. However, few studies have examined species responses to spatial pattern from other sources, including those which vary over time, such as fire.

Objectives

We investigated the effect of composition and configuration for topographic, ecological and disturbance factors on mammal species richness. In addition, we examined whether the magnitude and predictive strength of the relationship with richness varied with spatial scale.

Methods

We sampled ground-dwelling mammals at 187 sites in the Otway Ranges of south-eastern Australia. A gradient modelling approach was used to characterise landscape composition and configuration for each predictor. Relationships with mammal richness were modelled using Bayesian Networks at ten different spatial scales (7–1165 ha).

Results

Composition and configuration were both important to species richness, although the strength and presence of relationships varied across the ten scales. Patterns in NDVI, time since fire, habitat complexity and elevation had the strongest effects on mammal species richness.

Conclusions

Our findings highlight the importance of measuring both the composition and configuration of environmental measures at different spatial scales to assess their effect on species richness. Further, studies focusing on just one environmental measure of spatial pattern or one spatial scale will miss important relationships between environmental variables and species richness.

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Data Availability

The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This study was a part of a long-term fire and biodiversity research project in the Otway Ranges conducted by the Fire Ecology and Biodiversity Research Group at the University of Melbourne. We thank Fiona Christie, Holly Sitters and Alan York for their contributions to the original study design. Additionally, we thank Ellen Rochelmeyer, Julio Najera, Sarah Matthews, Marci Chai, Jenny Huang, Tia Kearney, Matthew Oaten, Louise Falls, Luke Adams, Oakley Germech, Tom Cook, and Tiani Kane for their assistance in the field. We would like to acknowledge the Traditional Owners of the land where this research took place, the Gadubanud and Wadda wurrung peoples. This research was funded by the Victorian Department of Environment, Land, Water and Planning (DELWP), the University of Melbourne, the Holsworth Wildlife Research Endowment and the Ecological Society of Australia. Finally, we would like to thank Sarah McColl-Gausden, Michael Dorph, the anonymous reviewers and Editor for comments that improved this manuscript.

Funding

This research was funded by the Victorian Department of Environment, Land, Water and Planning (DELWP), the University of Melbourne, the Holsworth Wildlife Research Endowment and the Ecological Society of Australia.

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Conceptualization: AD, MS, TP, JDS; Data Curation: AD, MS, JDS; Formal Analysis: AD, TP; Funding Acquisition: AD, MS, JDS; Investigation: AD, MS, JDS; Methodology: AD, MS, TP, JDS; Project administration: AD, MS; Supervision: MS, TP, JDS; Validation: AD; Visualization: AD; Writing—original draft: AD; Writing—review and editing: AD, MS, TP, JDS.

Corresponding author

Correspondence to Annalie Dorph.

Ethics declarations

All field work was conducted in accordance with the National Parks Act (Research Permit Number 10007746) and Forests Act (Scientific Permit Number 00420160819). Faunal surveys were approved by the University of Melbourne Faculty of Science Ethics Committee (Register Number 1513682.1).

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The authors declare that they have no conflict of interest.

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Dorph, A., Swan, M., Di Stefano, J. et al. Relating mammal species richness to landscape patterns across multiple spatial scales. Landscape Ecol 36, 1003–1022 (2021). https://doi.org/10.1007/s10980-021-01208-8

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Keywords

  • Landscape gradient model
  • Bayesian networks
  • Fire ecology
  • Landscape structure
  • Species diversity
  • Spatial pattern