Year of Award

2014

Document Type

Thesis

Degree Type

Master of Science (MS)

Degree Name

Forestry

Department or School/College

College of Forestry and Conservation

Committee Chair

John Goodburn

Commitee Members

David Affleck, Ray Ford

Keywords

forest landscape models (FLM), SIMPPLLE, U.S. Forest Service Inventory and Analysis (FIA) data

Subject Categories

Forest Management | Other Forestry and Forest Sciences

Abstract

The ability of forest resource managers to understand and anticipate landscape-scale change in composition and structure relies upon an adequate characterization of the current forest composition and structure of various patches (or stands), along with the capacity of forest landscape models (FLMs) to predict patterns of growth, succession, and disturbance at multiple scales over time. Comprehensive vegetation maps, which classify patch polygons or raster cells into forest cover types, can be developed from available inventory data (e.g., FIA Grid) in combination with remotely sensed data, but a simple categorical forest type, even one incorporating average size, may not provide adequate resolution for tracking individual species and age cohorts over time in an FLM. This project, undertaken in Eastern Montana forest types, sought to develop strategies for utilizing extensive inventory data from the U.S. Forest Inventory and Analysis (FIA) program to initialize patch-level vegetation information for use in the landscape disturbance model SIMPPLLE (Chew et al 2004). The information provided to SIMPPLLE, includes not only a forest cover dominance type that crosswalks with the Northern Region’s VMAP labels, but also incorporates further species and size information to the cohort level. By processing FIA data through the stand-level growth model FVS (Forest Vegetation Simulator), tracking of individual cohorts could be summarized to enhance resolution and realism in the SIMPPLLE model. Further, by simulating patch level dynamics within FVS for up to 300 years for representative stands, and segregating growing stock by cohort, it was possible to enhance the complexity of stand development pathways to be used within SIMPPLLE model. Specifically, I enable the tracking of individual cohorts (species and 5” breast-height diameter size class) to be passed on to the SIMPPLLE model, while still allowing for large-scale modeling of disturbances and between-patch interactions, which are the scales of interest within the SIMPPLLE FLM.

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© Copyright 2014 Jacob Muller