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Watershed Planning within a Quantitative Scenario Analysis Framework

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Published on: July 24, 2016

Graph theory as a proxy for spatially explicit population models in conservation planning.

Emily S Minor¹, Dean L Urban

¹Nicholas School of the Environment, Duke University, Durham, North Carolina, USA. eminor@al.umces.edu

Ecological Applications : a Publication of the Ecological Society of America

|October 5, 2007

Summary

Graph theory offers a computationally efficient alternative to spatially explicit population models (SEPMs) for species conservation. It identifies crucial habitat patches for species like the Wood Thrush with similar accuracy and provides additional connectivity insights.

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Area of Science:

Landscape Ecology
Conservation Biology
Computational Ecology

Background:

Spatially explicit population models (SEPMs) are effective for species distribution but are computationally intensive and data-demanding.
Graph theory presents a data-efficient alternative with efficient algorithms, suitable for ecological connectivity and movement studies.

Purpose of the Study:

To compare the performance of graph theory and SEPMs in identifying critical habitat patches for Wood Thrush conservation.
To evaluate graph theory's ability to identify population sources, persistent patches, and dispersal stepping stones.

Main Methods:

Applied both graph theory and SEPMs to identify key habitat patches for Wood Thrush conservation.
Utilized graph theory to specifically identify stepping stone patches crucial for dispersal.

Main Results:

High correlation was observed between patch rankings generated by graph theory and SEPMs.
Graph theory successfully identified population sources, persistent patches, and provided insights into habitat connectivity.

Conclusions:

Graph theory is a suitable and potentially preferable alternative to SEPMs for species conservation in heterogeneous landscapes.
Graph theory provides valuable insights into habitat connectivity, enhancing long-term population persistence strategies.