1. Comparing ORGANON & SPS Using the Bakuzis Matrix Growth Model Users Group December 15, 2005 Dave Hamlin

2. The Bakuzis Matrix Egolfs Bakuzis U. Minnesota Synecological Coordinates Named by Rolfe Leary North Central Station, St. Paul. (retired)

3. The Bakuzis Matrix A framework for examining models In the context of biological ‘laws’ Useful for side-by-side comparisons Leary, R.A. 1997. Testing models of unthinned red pine plantations using a modified Bakuzis matrix of stand properties. Ecological Modelling 98 (1997) 35-46

4. Full Matrix Plots Stand Parameters against Time and Each Other by Site Quality

5. Full Matrix AgeStemsHeightBasal Area Mean DBH Volume Increment Age StemsSukachev Effect Spacing Percent Reineke’s Rule Height Site Curves Ht-DBH SI Class Basal AreaStocking Guide Framework Mean DBH Volume Site Curves Yield – Density Effect Eichorn's Rule Volume Increment Yield ClassAssman’s Density Langsaeter’s Hypothesis Italics identify relationships involving increment and thinning

6. Simplified Matrix AgeMean DBH HeightStemsBasal Area Volume Mean DBH Height Site Curves Ht-DBH Site Class StemsSukachev Effect Reineke’s Rule Spacing Percent Basal Area Stocking Guide Volume Site Class Eichorn’s Rule Yield-Density Effect Leary’s Triangular Form Italics indicate cells from which relationships can be derived.

7. Interpreting Cells Sukachev Effect ‘stands on good sites self-thin faster than stands on poor sites.’ Reineke’s Rule sd = a(dbh) b b is approximately -1.6 b is independent of site quality a reflects stockability of the site

8. Interpreting Cells Percent Spacing Stands self-thin when their mean inter-tree distance approaches 10% to 20% of height. Eichorn’s Rule Relationship between volume and height is independent of site.

9. Models SPS 4.1H January 1999 ORGANON SMC Beta, April 2005.

10. Stand Projected 100% DF 400 TPA at age 15 SI 65, 105, 145 (merchandised with the same functions)

11. Observations AGE relationships make sense Sukachev as expected Reineke as expected Eichorn looks good (except SI 65)

12. Observations AGE relationships make sense Sukachev as expected Reineke shows a bit of SI effect Eichorn looks good

13. Observations Identical HT-Age Mortality Very Different QDBH-TOPHT differ CVTS-Age Similar Has value implications

14. Compare TPA Observations ORGANON - Little SI effect in Reineke SPS 4.1 – Some SI Effect

15. Compare QDBH & TopHT Observations ORGANON taller for a given QDBH. Expected, given denser stands.

16. Thoughts Mortality model drives much of the difference between SPS and ORGANON Both models conform reasonably well to ‘law like’ expectations. It is interesting that CVTS is as similar as it is, given differences in TPA. What are the value implications?

17. Questions?