1. STAND STRUCTURE CLASSIFICATION A Cumulative Distribution Approach to Stand Structure Classification Craig Farnden and Ian S. Moss Western Mensurationists’ Meeting July 2, 2003

2. STAND STRUCTURE CLASSIFICATION Why Classify? It helps us to organize our observations of complex systems and to learn from those observations It facilitates communication between individuals: a given class label infers a set of attributes that are commonly understood

3. STAND STRUCTURE CLASSIFICATION Implicit Assumptions Recognized that: Stand structure is a continuum There are few if any obvious breaks upon which to base classes Perceptions of what stands should look like can seriously skew a classification (“textbook” stand structures)

4. STAND STRUCTURE CLASSIFICATION Design Criteria Units must be internally consistent Units must be readily recognizable Sufficient number of units to facilitate interpretations Classification must be definitive

5. STAND STRUCTURE CLASSIFICATION Design Criteria Classification attributes should be easy to measure or assess for general applicability System should be open to improvement or refinement through sub-division and/or re-fitting Separable with respect to diameter distributions and species composition

6. STAND STRUCTURE CLASSIFICATION The Cumulative Distribution Approach to Classification Current classification built on 424 sample plots Uses mathematical algorithm to find stands with similar structures Pattern recognition based on two cumulative frequency distributions: –Basal area (m 2 /ha) –Trees/ha

7. STAND STRUCTURE CLASSIFICATION The Cumulative Distribution Approach to Classification 0 5 10 15 20 25 30 35 40 01020304050607080 Tree DBH (cm) Basal Area (m 2 /ha)

8. STAND STRUCTURE CLASSIFICATION The Cumulative Distribution Approach to Classification 0 500 1000 1500 2000 2500 3000 3500 4000 051015202530 Tree DBH (cm) Trees/ha

9. STAND STRUCTURE CLASSIFICATION 0 25 50 75 100 051015202530 Tree DBH (cm) Trees/ha Percentile Methodology…

10. STAND STRUCTURE CLASSIFICATION 0 25 50 75 100 051015202530 Tree DBH (cm) Trees/ha Percentile Methodology…

11. STAND STRUCTURE CLASSIFICATION Methodology… T= ∑distance between all pairs WG ij = ∑within group pairs BG ij = T - WG ij

12. STAND STRUCTURE CLASSIFICATION Methodology… For each possible move, calculate: New WG ij ∆BG i R ij = Wg ij/ ∆Bg i Find Rmin ij

13. STAND STRUCTURE CLASSIFICATION Results

14. STAND STRUCTURE CLASSIFICATION Results

15. STAND STRUCTURE CLASSIFICATION Results - Reference Distributions C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 C17 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 0510152025 Tree DBH (cm) Trees/ha

16. STAND STRUCTURE CLASSIFICATION Results - Reference Distributions 0 10 20 30 40 50 60 0102030405060708090100 Tree DBH (cm) C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 C17 Basal Area (m2/ha)

17. STAND STRUCTURE CLASSIFICATION Classifying Stands Plot cumulative distributions and compare to reference distributions

18. STAND STRUCTURE CLASSIFICATION Classifying Stands

19. STAND STRUCTURE CLASSIFICATION Classifying Stands Use computer software (planned) Use keys in field guide Plot cumulative distributions and compare to reference distributions

20. STAND STRUCTURE CLASSIFICATION Classifying Stands 17 16 15 12 13 15 14 B 40 >19.5 AND B 20 >27.5 B 25 >37 OR B 80 >8 B 60 >5 AND B 10 <35 B 10 <32.5 B 0 >30 OR B 15 >26 B 10 >19 OR B 20 >16 B 35 >12 B 0 >34 B 40 >18 Y Y Y Y Y Y Y Y Y N N N N N N N N N KEY "A"

21. STAND STRUCTURE CLASSIFICATION Classifying Stands Tree DBH (cm) Basal Area (m2/ha)

22. STAND STRUCTURE CLASSIFICATION Classifying Stands Use Air Photo Interpretation Plot cumulative distributions and compare to reference distributions Use computer software (planned) Use keys in field guide

23. STAND STRUCTURE CLASSIFICATION Classifying Stands Class 14 Class 15Class 17

24. STAND STRUCTURE CLASSIFICATION Plot cumulative distributions and compare to reference distributions Use computer software (planned) Use keys in field guide Use Air Photo Interpretation Classifying Stands Recognize through familiarity

25. STAND STRUCTURE CLASSIFICATION Classifying Stands

26. STAND STRUCTURE CLASSIFICATION Classifying Stands 4 6 2 12 16

27. STAND STRUCTURE CLASSIFICATION Classifying Stands 14 16

28. STAND STRUCTURE CLASSIFICATION Unresolved Issues Number and distribution of classes Use of discrete point samples versus composite samples Class hierarchy –Species –Spatial distribution and complex –Small tree frequency

29. STAND STRUCTURE CLASSIFICATION Conclusions System has great potential –Enhanced resource interpretations –Enhanced treelist imputation –Enhanced broad scale prescriptive abilities Appears to be robust and defensible Should be exportable with minimal modifications New and untested - guinea pigs required

30. STAND STRUCTURE CLASSIFICATION Documentation Field guide and poster Lignum Limited web site: www.lignum.com go to publications

31. STAND STRUCTURE CLASSIFICATION Acknowledgements This project was undertaken as part of the Lignum Ltd. IFPA Funding for this project was provided by Forestry Innovation Investment (FII), a forestry investment mechanism of the Gov’t of BC, and Forest Renewal BC