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REGENERATION UNDER PARTIAL CUTTING FOR PROGNOSIS BC, MSdk Subzone, CRANBROOK FOREST DISTRICT Badre Tameme Hassani, M.Sc., Valerie LeMay, PhD., RPF, Peter.

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Presentation on theme: "REGENERATION UNDER PARTIAL CUTTING FOR PROGNOSIS BC, MSdk Subzone, CRANBROOK FOREST DISTRICT Badre Tameme Hassani, M.Sc., Valerie LeMay, PhD., RPF, Peter."— Presentation transcript:

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2 REGENERATION UNDER PARTIAL CUTTING FOR PROGNOSIS BC, MSdk Subzone, CRANBROOK FOREST DISTRICT Badre Tameme Hassani, M.Sc., Valerie LeMay, PhD., RPF, Peter Marshall, PhD., RPF and Abdel-Azim Zumrawi, PhD., RPF Presented at the Cranbrook District Office November 6, 2002

3 Background Understanding stand dynamics is necessary to achieve management objectives MoF has adopted Prognosis BC to predict the dynamics of complex stands in the southern interior of BC Prognosis BC is an adaptation of the US Forest Vegetation Simulator (FVS); it forecasts future stand conditions based on the expected growth and mortality of individual trees It can be used to simulate a wide variety of stand management activities, including any form of harvesting Prognosis BC has been calibrated by the MoF, in conjuntion with the Faculty of Forestry at UBC, for use in southeastern BC since 1997

4 It has been calibrated for use in several BEC subzones/variants in the Kamloops, Nelson, and Cariboo Forest Regions Calibration of large tree (height and diameter), live crown ratio, and mortality was done using PSP data Insufficient data limited the capability of the model to predict small tree height growth, regeneration, and to make long-term projections following harvesting Currently, the regeneration portion of Prognosis BC has been disabled; users must supply their own data Regression approaches did not lead to good predictions of regeneration Predicting the regeneration of complex stands in the ICH using imputation approaches proved to work better than regression

5 Objective Predict regeneration under partial cutting using the tabular imputation approach for complex stands in the MSdk subzone

6 Outline Location of the study area Methods Results Conclusions Current and future projects

7 Location of Study Area in BC Continental climate Middle elev. (1100-1650 m) Bounded by IDF (lower elev.) and ESSF (higher) Supports 11 trees species Nelson Forest Region

8 Complex Stands in the MSdk zone Mixed species Uneven-aged Multi-cohort Subalpine fir and hybrid spruce are climax species Extensive presence of lodgepole pine and Douglas-fir

9 Potential Polygons Group (yrs) CCResCCPatchSeed- tree Shelter -wood SelectionMissing* 1 (1-5) 38565302 2 (6-10) 51814 10210 3 (11-15) 1370330111 4 (16-20) 5130590112 5 (21-25) 3420480100 * missing information on the silvicultural system

10 Plot Layout Nested plots Systematically located in selected stands Stands selected to cover the range of:  overstory density  age since disturbance  site preparation  slope percent  aspect  elevation 122 plots from 52 polygons STP (3.99m) LTP (=11.28 m) Regen. P (2.07m) Satel. P (2.07m)

11 Species Groups Species GroupSpecies Shade tolerantCedar, subalpine fir, spruce Shade semi-tolerantDouglas-fir Shade intolerantLarch, lodgepole pine HardwoodAspen, cottonwood, Douglas Maple, willow

12 Tabular Imputation Methods Stand Conditions Basal Area class: Dense: > 5m 2 /ha; Open: =< 5m 2 /ha Site Series class: Dry: 02, 03, and 04 Wet: 01, 05 Time-Since-Disturbance Group (years): Group 1: 1-8 2: 8-16 3: 16-25

13 Tabular Imputation Approach For each stand condition combination: Average number of seedlings per ha by:  height class (1: 15-49.9 cm for shade tolerant species and 30-49.9 cm for shade intolerant species, 2: 50-99.9 cm, 3: 100-129.9 cm, and 4: >130 cm)  and for the 4 species groups (16 regeneration variables) Precision of the tabular imputation models  Standard error of the mean for each cell of in the tables

14 Results Sampling and Regeneration Composition 12 undisturbed, 13 clear-cut plots from 122 plots 69% of the plots were site series 04 Overstory dominated by intolerant species (819 stems/ha)

15 Yrs since Disturbance Yr # plots 0 12 5 6 5-10 41 10-15 15 15-20 22 >20 26 Site Series SS # plot 02 2 03 9 04 84 01 23 05 4 Residual BA (m2/ha) Meth # plot 0 8 1-5 40 5-10 26 10-15 14 15-20 9 20-25 5 25-30 5 30-35 4 35-40 2 >40 9 Silv. System Method # plot CC 13 CC/Res 15 Light shelter 2 Seedtree 42 Selection 23 Shelter/Selec 3 Shelter/ST 1 Shelter 11 Undisturbed 12 Elevation- 100m Elev. # plot <=900 0 9-10 6 10-11 8 11-12 30 12-13 25 13-14 20 14-15 26 15-16 7

16 Site Prep. Method # plot None 81 Burn 41 Aspect Aspect # plot E 19 F 15 N 7 NE 15 NW 16 S 6 SE 17 SW 6 W 21 Slope Position Position # plot Crest 1 Lower 10 Ridge 1 Middle 76 Plateau 18 Terrace 8 Flat 4 Upper 4 Slope Percent Slope # plot 0-10 39 10-20 38 20-30 21 30-40 9 40-50 6 50-60 6 >60 3

17 Diameter Distribution for all residual species combined

18 Regeneration Composition Average regeneration (over 122 plots)= 6023 seedlings/ha Averages of 2168, 1522, 1285, and 1048 seedlings/ha for shade intolerant, hardwood, semi-tolerant, and tolerant species respectively 29 plots had no regeneration (zero)

19 Regeneration by Site Preparation Treatment

20 Regeneration by Time-Since-Disturbance Groups

21 Tabular Imputation Models 12 tables were produced for the disturbed sites; 1 table for undisturbed sites

22 Dense, Dry, first 5 years since disturbance (n=7) SpeciesHeight (cm)All heights 15-49.950-99.9100-129.2>130 Tolerant00000 Semi-tolerant531000 Intolerant849116801062123 Hardwood212531955 2653 All species1592169995510615307

23 Undisturbed Sites (n=12) SpeciesHeight (cm)All heights 15-49.950-99.9100-129.2>130 Tolerant7436200805 Semi-tolerant7432481245571672 Intolerant000124 Hardwood00000 All species14863101246812601

24 SEM- disturbed sites: dense, dry, 5 yrs (n=7) SpeciesHeight (cm)All heights 15-49.950-99.9100-129.2>130 Tolerant00000 Semi-tolerant352000 Intolerant49894301061636 Hardwood1374207389551699 All species5249277389432079

25 SEM- undisturbed sites (n=12) SpeciesHeight (cm)All heights 15-49.950-99.9100-129.2>130 Tolerant4196200461 Semi-tolerant41919083557787 Intolerant000124 Hardwood00000 All species59319383681930

26 Predictions based on three or less plots resulted in very high SEM (reaching 100 % of the mean in most cases) Predictions based on more than 10 plots had lower SEM Lowest SEM values were observed within tables based on more than 20 plots

27 Conclusions Species composition of the overstory was dominated by intolerant species followed by semi-tolerant species Treated sites had more regeneration than undisturbed sites Regeneration present on the disturbed sites were predominately comprised of seral species (intolerant and hardwood species) Regeneration was most abundant between 8 and 16 years after disturbance Shade tolerant and semi-tolerant species dominated undisturbed sites

28 The tabular imputation approach made good use of the available data Tabular imputation models had a simple structure and provided detailed average post-harvest regeneration for different conditions Performance of this technique depends implicitly on the data used for the analysis These models are flexible and can be easily updated as more data become available

29 Acknowledgments This research was funded by Forestry Innovative Investment. In-kind support was provided by the BC Ministry of Forests, Research and Forest Practices Branches, UBC Faculty of Forestry, Tembec Industries, Riverside Forest Products, and Slocan Forest Products

30 Contact and Web Site For more information, you can contact: MoF Research Branch: Dr. Abdel-Azim Zumrawi UBC: Dr. Valerie LeMay and Dr. Peter Marshall Web Site (for contact information and reports): www.forestry.ubc.ca/Prognosis The final report will be available on the web by the end of November 2002

31 Work on progress: Calibration of the Prognosis BC small tree height increment model and development of regeneration imputation models for IDFdm2 in the vicinity of Invermere Planned work: Workshop at UBC to discuss future regeneration modelling approaches (link of regeneration imputation techniques to Prognosis BC ) Make the results accessible for users through the web Consolidate the data collected over the past 5 years in different zones into a single database (corporate database) for use and preservation Current and Future Projects

32 Question for the Audience What other purposes could the data be used for?


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