Urban growth and landscape connectivity threats assessment at Saguaro National Park, Arizona, USA

Ryan Perkl, Laura M. Norman, David Mitchell, Mark Feller, Garrett Smith, Natalie R. Wilson

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Urban and exurban expansion results in habitat and biodiversity loss globally. We hypothesize that a coupled-model approach could connect urban planning for future cities with landscape ecology to consider wildland habitat connectivity. Our work combines urban growth simulations with models of wildlife corridors to examine how species will be impacted by development to test this hypothesis. We leverage a land use change model (SLEUTH) with structural and functional landscape-connectivity modeling techniques to ascertain the spatial extent and locations of connectivity related threats to a national park in southern Arizona, USA, and describe how protected areas might be impacted by urban expansion. Results of projected growth significantly altered structural connectivity (80%) when compared to current (baseline) corridor conditions. Moreover, projected growth impacted functional connectivity differently amongst species, indicating resilience of some species and near-complete displacement of others. We propose that implementing a geospatial-design-based model will allow for a better understanding of the impacts management decisions have on wildlife populations. The application provides the potential to understand both human and environmental impacts of land-system dynamics, critical for long-term sustainability.

Original languageEnglish (US)
Pages (from-to)102-117
Number of pages16
JournalJournal of Land Use Science
Volume13
Issue number1-2
DOIs
StatePublished - Mar 4 2018

Keywords

  • Landscape connectivity modeling
  • SLEUTH
  • Saguaro National Park
  • conservation planning
  • wildlife corridors

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Earth-Surface Processes
  • Management, Monitoring, Policy and Law

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