Abstract

The viability of wildlife populations in cities is strongly associated to the qualities of urban open spaces and development patterns. Open space systems can serve as armatures to address adverse effects of urbanization on biodiversity. Landscape planners and designers use spatial concepts to translate principles of landscape ecology into working diagrams of land use and land cover to anticipate ecological effects. This paper investigates the consequences of adopting different open space spatial concepts (corridors, patches, and network) in combination with development patterns (compact and dispersed), simulated in eight alternative future scenarios with computer model Envision. Two approaches were used to quantify the effects of the different spatial concepts and urban patterns on Red-legged frog (RLF), Western meadowlark (WML), and Douglas squirrel (DSQ) habitats and populations in an area of urban expansion. First, the amount of habitats was assessed for the initial landscape (ca. 2010) and for the eight future scenarios (year 2060). Second, using the Individual-Based Model (IBM) HexSim, populations of the three species were quantified. All scenarios had increased sums of habitat area, but results showed that differences in open space spatial concepts played a greater role in determining population sizes and were more influential than different development patterns. Network scenarios presented more habitats and the largest populations of RLF. Park and network scenarios showed the most habitats and populations for the WML. No open space and greenway scenarios did not have enough habitats for the WML, but presented the best results for the DSQ. Populations in compact development scenarios showed a small advantage over most dispersed development scenarios. However, in park and network scenarios, dispersed development showed a large influence in the increase of WML population. The study shows that the adopted framework is useful to predict the consequences of landscape plans on wildlife species populations, evaluate trade-offs, and inform planning decisions.

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