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Applications of Urban Growth Models and Wildlife
Habitat Models to Assess Biodiversity Losses

• Christopher B. Cogan
• Alfred Wegener Institute for Polar and Marine
  Research
• Bremerhaven, Germany
• ccogan_at_awi-bremerhaven.de
• Michael D. Jennings
• U.S. Geological Survey, Moscow, Idaho, USA
• jennings_at_uidaho.edu

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Acknowledgements
Research Performed Under Cooperative Agreement
No. 00HQAG0009 as part of the GAP Socioeconomic
Seed Grant Program, managed by Dr. Gary Machlis,
University of Idaho for  USGS Gap Analysis Program
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Outline

• Introduction
• Biodiversity analysis
• Urban growth models
• Methods used
• Case study results
• Discussion modeling urban growth with
  biodiversity

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Biodiversity and Urban Growth

• Biodiversity a collection of indices including
  habitat quality and quantity.
• Habitat loss and fragmentation due to urban
  development are a major concern.
• Urban growth models can help guide landuse
  management for biodiversity goals.

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Methods

• Flow chart for biodiversity sensitivity analysis
  using three urban growth scenarios and two land
  cover models.

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Urban growth forecast using an urban buffer
model. Santa Cruz County, California.
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Urban growth forecast using the Landis model.
Santa Cruz County, California.
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Urban growth forecast based on the Clarke model.
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California Gap Analysis Project (GAP) land cover
polygons in Santa Cruz County, California.
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AMBAG land cover polygons in Santa Cruz County,
California.
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Comparison of three growth scenarios 500 meter
urban buffer, Landis growth model, and Clarke
growth model (area urbanized vs. land cover type).
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Comparison of three growth scenarios in Santa
Cruz County California Habitat loss.
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Biodiversity Analysis Logic
Variations in urban growth patterns are
significant for biodiversity.
Variations in urban growth patterns are not
critical in biodiversity analysis.
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Model error prevents variation in growth pattern
from producing a measurable biodiversity response.
Variation in growth is measurable in terms of
biodiversity.
Urban growth scenarios are constrained into
similar patterns.
Biodiversity data are too coarse to respond to
fine urbanization differences.
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Biodiversity Analysis Logic
Variations in urban growth patterns are
significant for biodiversity.
Variations in urban growth patterns are not
critical in biodiversity analysis.
Model error prevents variation in growth pattern
from producing a measurable biodiversity response.
Variation in growth is measurable in terms of
biodiversity.
Explanation Particular species will always be
impacted perhaps due to their rarity in the
county vs. the ecoregion.
Biodiversity data are too coarse to respond to
fine urbanization differences.
Urban growth scenarios are constrained into
similar patterns.
Explanation Habitat models are too coarse
grained for measurable response to urban change.
Explanation model is working with available data.
Explanation Urban models lack sufficient
realistic variation.
Action Treat these species and habitats as
special cases use the biodiversity model to
evaluate the remaining biodiversity elements.
Action use urban growth scenarios and existing
species habitat data to evaluate biodiversity
impacts.
Action use as is for coarse grain analysis, but
use finer grain habitat data and new WHR models
for detailed analysis.
Action test with different or random growth
scenarios.
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Conclusions

• The Gap data on wildlife habitat relationships
  should maintain a spatial grain which is
  consistent with the grain of the urban growth
  models.
• Finer grain habitat maps are not always better!
• Thematic compatibility with WHR and other models
  may minimize connectivity artifacts.
• Gap maps can help to quantify urban creep

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Cogan, C.B. 2001. A quantitative analysis of
biodiversity for land-use and reserve system
planning. Doctoral dissertation, Department of
Environmental Studies, University of California,
Santa Cruz, USA. Cogan, C.B., and F.W. Davis.
2001. Applications of urban growth models and
wildlife habitat models to assess biodiversity
losses. University of California Santa Barbara
Institute for Computational Earth System Science,
Final Report to U.S. Geological Survey Gap
Analysis Program, Moscow, Idaho, USA. Cogan, C.B.
In press. Biodiversity Predictions Integrating
urban growth models with land cover data and
species habitat information. Gap Analysis
Bulletin No. 10. U.S. Geological Survey, Moscow,
Idaho, USA.
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