An Individual-Based Model for Metapopulations on Patchy Landscapes-Genetics and Demography (IMPL-GD)

  • Jennifer L. Burton
  • Richard F. Lance
  • James D. Westervelt
  • Paul L. Leberg
Part of the Modeling Dynamic Systems book series (MDS)


The model described in this chapter addresses the risk of metapopulation extinction when a habitat parcel is eliminated from a patchy landscape. The authors describe the Individual-Based Model for Metapopulations on Patchy Landscapes-Genetics and Demography (IMPL-GD), an agent-based simulation model developed using NetLogo ( This model is intended to provide a better understanding of how ecological variables such as landscape physical characteristics, population genetic and demographic traits, and network relationships between habitat parcels relate dynamically to metapopulation viability. The IMPL-GD places generic organisms on a landscape that consists of habitable and non-habitable patches, including traversable but non-habitable terrain. The agents, called “whatsits,” were designed to reflect the characteristics of small, solitary animals that defend small, circular territories in the landscape. They are defined in the model by a unique identification number, age, sex, lineage, and other characteristics. The IMPL-GD model enables the user to rapidly execute thousands of simulations in which a random parcel of habitable terrain is eliminated from the landscape after a given number of time steps and the impact on whatsit population viability is recorded. The output from a large number of IMPL-GD simulations can statistically analyzed to identify associations between the independent ecological variables and quantify their relation to the dependent variable of whatsit survival in the form of a conservation utility index.


Habitable Patch Unique Identification Number Small Parcel Patchy Landscape Large Parcel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Brown JH (1984) On the relationship between abundance and distribution of species. Am Nat 124(2):255–297CrossRefGoogle Scholar
  2. Korkeamäki E, Suhonen J (2002) Distribution and habitat specialization of species affect local extinction in dragonfly Odonata populations. Ecography 25(4):459–465CrossRefGoogle Scholar
  3. Munday PL (2004) Habitat loss, resource specialization, and extinction on coral reefs. Glob Chang Biol 10(10):1642–1647CrossRefGoogle Scholar
  4. Owens IPF, Bennett PM (2000) Ecological basis of extinction risk in birds: habitat loss versus human persecution and introduced predators. Proc Natl Acad Sci U S A 97(22):12144CrossRefGoogle Scholar
  5. Reyers B, Fairbanks DHK, Wessels KJ, Van Jaarsveld AS (2002) A multicriteria approach to reserve selection: addressing long-term biodiversity maintenance. Biodivers Conserv 11(5):769–793CrossRefGoogle Scholar
  6. Rothley KD (2006) Finding the tradeoffs between the reserve design and representation. Environ Manage 38(3):327–337CrossRefGoogle Scholar
  7. Wiersma YF, Urban DL (2005) Beta diversity and nature reserve system design in the Yukon, Canada. Conserv Biol 19(4):1262–1272CrossRefGoogle Scholar
  8. Wilensky U (1999) NetLogo. Computer software. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston. Accessed 01/2011
  9. With KA, Crist TO (1995) Critical thresholds in species’ responses to landscape structure. Ecology 76(8):2446–2459CrossRefGoogle Scholar
  10. Wright S (1922) Coefficients of inbreeding and relationship. Am Nat 56:330–338CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Jennifer L. Burton
    • 1
  • Richard F. Lance
    • 2
  • James D. Westervelt
    • 3
  • Paul L. Leberg
    • 4
  1. 1.Department of Natural Resources and Environmental SciencesUniversity of IllinoisUrbanaUSA
  2. 2.Environmental LaboratoryU.S. Army Engineer Research and Development CenterVicksburgUSA
  3. 3.Construction Engineering Research LaboratoryUS Army Engineer Research and Development CenterChampaignUSA
  4. 4.Department of BiologyUniversity of LouisianaLafayetteUSA

Personalised recommendations