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Adapting a Mortality Model for Southeast Interior British Columbia

This study aims to adapt a mortality model for conifers and hardwoods in the southeast interior of British Columbia. Various approaches were assessed using BC-based Permanent Sample Plots (PSPs) and variables from these plots were used to evaluate the different models. The results showed that Model 5 had the highest accuracy and predictive ability for most species/zone combinations. Additionally, the inclusion of eco-physical factors like slope, aspect, and elevation could further improve the model's performance.

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Adapting a Mortality Model for Southeast Interior British Columbia

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  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. Objectives • to adapt a mortality model for southeast interior BC • to evaluate selected mortality models for conifers and hardwoods in southeast interior BC

  8. 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

  9. 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

  10. 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

  11. 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

  12. Percent of correctly classified trees in the ICH zone, using test data

  13. Number of observed (N_OBS) and predicted (N_Exp) dead trees by species in the ICH zone, using Model 5 on test data

  14. Number of observed (N_obs) and predicted (N_Exp) dead trees by diameter class in the ICH zone, using Model 5 on test data

  15. Percent of correctly classified trees in the IDF zone, using test data

  16. Number of observed (N_OBS) and predicted (N_Exp) dead trees by species in the IDF zone, using Model 5 on test data

  17. Number of observed (N_obs) and predicted (N_Exp) dead trees by diameter class in the IDF zone, using Model 5 on test data

  18. 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

  19. 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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