Use of landscape simulation modeling to quantify resilience for ecological applications

Robert E. Keane, Rachel A. Loehman, Lisa M. Holsinger, Donald A. Falk, Philip Higuera, Sharon M. Hood, Paul F. Hessburg

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


Goals of fostering ecological resilience are increasingly used to guide U.S. public land management in the context of anthropogenic climate change and increasing landscape disturbances. There are, however, few operational means of assessing the resilience of a landscape or ecosystem. We present a method to evaluate resilience using simulation modeling. In this method, we use historical conditions (e.g., in North America, prior to European settlement), quantified using simulation modeling, to provide a comparative reference for contemporary conditions, where substantial departures indicate loss of resilience. Contemporary ecological conditions are compared statistically to the historical time series to create a resilience index, which can be used to prioritize landscapes for treatment and inform possible treatments. However, managing for resilience based on historical conditions is tenuous in the Anthropocene, which is characterized by rapid climate change, extensive human land use, altered disturbance regimes, and exotic species introductions. To account for the future variability of ecosystems resulting from climate and disturbance regime shifts, we augment historical simulations with simulations of ecosystem dynamics under projected climate and land use changes to assess the degree of departure from benchmark historical conditions. We use a mechanistic landscape model (FireBGCv2) applied to a large landscape in western Montana, USA, to illustrate the methods presented in this paper. Spatially explicit ecosystem modeling provides the vehicle to generate the historical and future time series needed to quantify potential resilience conditions associated with past and potential future conditions. Our methods show that given selection of a useful set of metrics, managers could use simulations like ours to evaluate potential future management directions.

Original languageEnglish
Article numbere02414
Issue number9
StatePublished - Sep 2018


  • climate change
  • ecosystem management
  • future ranges of variability (FRV)
  • historical ecology
  • historical range and variation (HRV)
  • land management
  • landscape ecology
  • landscape modeling


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