Computer and remote-sensing infrastructure to enhance large-scale testing of individual-based forest models

Herman H. Shugart, Gregory P. Asner, Rico Fischer, Andreas Huth, Nikolai Knapp, Thuy Le Toan, Jacquelyn K. Shuman

Research output: Contribution to journalReview article

40 Scopus citations

Abstract

Global environmental change necessitates increased predictive capacity; for forests, recent advances in technology provide the response to this challenge. "Next-generation" remote-sensing instruments can measure forest biogeochemistry and structural change, and individual-based models can predict the fates of vast numbers of simulated trees, all growing and competing according to their ecological attributes in altered environments across large areas. Application of these models at continental scales is now feasible using current computing power. The results obtained from individual-based models are testable against remotely sensed data, and so can be used to predict changes in forests at plot, landscape, and regional scales. This model-data comparison allows the detailed prediction, observation, and testing of forest ecosystem changes at very large scales and under novel environmental conditions, a capability that is greatly needed in this time of potentially massive ecological change.

Original languageEnglish (US)
Pages (from-to)503-511
Number of pages9
JournalFrontiers in Ecology and the Environment
Volume13
Issue number9
DOIs
StatePublished - Nov 2015
Externally publishedYes

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology

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