adapting a mortality model for southeast interior british columbia
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Adapting a Mortality Model for Southeast Interior British Columbia. By - Temesgen H., V. LeMay, and P.L. Marshall University of British Columbia Forest Resources Management Vancouver, BC, V6T 1Z4 The 2001 Western Mensurationists\' Meeting Klamath Falls, Oregon June 24-26/2001.

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adapting a mortality model for southeast interior british columbia
Adapting a Mortality Model for Southeast Interior British Columbia

By - Temesgen H., V. LeMay, and P.L. Marshall

University of British Columbia

Forest Resources Management

Vancouver, BC, V6T 1Z4

The 2001 Western Mensurationists\' Meeting

Klamath Falls, Oregon

June 24-26/2001

adapting a gy model

BC Biogeoclimatic

Ecosystem

Classification units

US Habitat Types

Adapting a GY model
  • The Northern Idaho prognosis variant (NI) has been adapted to the southeast interior of BC, PrognosisBC
adapting a gy model cont d
Adapting a GY model (cont’d)
  • Different measurement units (metric), basic functions (e.g., volume and taper) and standards
  • Classification of US habitat type to BEC can be subjective
  • Sub-models coefficients and model form may not fit BC data
  • Insufficient ground data for some types of stands
slide4

Adapting a GY model

  • Sub-model components:
  • large tree diameter and height growth
  • small tree diameter and height growth
  • small and large tree crown ratio
  • mortality and regeneration
  • others
background
BACKGROUND
  • Mortality is:
    • an essential attribute of any stand growth projection system
    • frequently expressed as a function of tree size, stand density, individual tree competition, and tree vigor
  • In PrognosisBC, periodic mortality rate is predicted using tree (Ra) and stand based (Rb) mortality functions
background cont d
BACKGROUND (cont’d)
  • Ra is a logistic function of tree size taken in context of stand structure.
  • Rb operates as a convergence on normal basal area stocking and maximum basal area (BAMAX)
  • Rb isbased on the concept that:
    • for each stand, there is a normal stocking density
    • there is a BAMAX that a site can sustain and this maximum varies

by site quality

objectives
Objectives
  • to adapt a mortality model for southeast interior BC
  • to evaluate selected mortality models for conifers and hardwoods in southeast interior BC
methods
METHODS
  • Three approaches of adapting mortality model were assessed, using BC based PSPs:
    • a multiplier function (Model 1)
    • re-fit the same model form by species/zone combination (Model 2)
    • changing variables (Models 3, 4, and 5)
  • PSPs that were re-measured at 5 to 12 years interval and that consistently included all trees > 2.0 cm were included
methods cont d
METHODS(cont’d)
  • For each PSP, individual tree records were coded, as either live or dead at each measurement period, and variables listed in the mortality models were extracted
methods cont d1
METHODS (cont’d)
  • Only species/zone combinations with more than 30 dead trees were selected.
  • To handle the unequal re-measurement periods in the PSP data sets, each model was weighted by the number of years between remeasurement periods.
  • The PSP data set was divided into model (70%) and test data (30%) sets  
  • Observed and predicted number of live and dead trees by species/zone were compared and then a model was selected
results
RESULTS
  • Noticeable differences were found in the % of correctly classified trees among the five models and the species/zone combinations considered in this study
  • Model 5 had lower Akaike Information Criterion (AIC) and Schwartz Criterion (SC) for most species/zone combinations
slide13
Number of observed (N_OBS) and predicted (N_Exp) dead trees by species in the ICH zone, using Model 5 on test data
slide14
Number of observed (N_obs) and predicted (N_Exp) dead trees by diameter class in the ICH zone, using Model 5 on test data
slide16
Number of observed (N_OBS) and predicted (N_Exp) dead trees by species in the IDF zone, using Model 5 on test data
slide17
Number of observed (N_obs) and predicted (N_Exp) dead trees by diameter class in the IDF zone, using Model 5 on test data
for species zone combination with little or no data
For species/zone combination with little or no data
  • substitution by similar species or BEC zone is suggested.

FORUSE

      • Bl in IDF ICH
      • Cw in IDF ICH
      • E in MS ICH
      • Fd in PP IDF
summary
Summary
  • Model 5 predicts mortality of both conifers and hardwoods reasonably well
  • BC based BAMAX values improved the predictive ability of the model
  • Inclusion of eco-physical factors such as slope, aspect, and elevation into the mortality model might increase the predictive ability of the model.
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