1. Eric Valdal, GIS Analyst, EFMPP Ralph Wells, Research Analyst, CACB - UBC

2. OBJECTIVES 1. To evaluate habitat impacts of harvest scenarios in the Invermere EFMPP study area. 2. To evaluate habitat in the Pilot study area. 3. To develop quantitative approaches to habitat analysis for selected species.

3. Approaches Identify species: Goshawk, CNB, songbirds. Develop quantitative methods for habitat models. Utilize existing databases for stand structure projections. Incorporate natural disturbance in harvest runs.

4. Quantitative Approaches to Habitat Modeling: Habitat Supply Modeling To examine the effects of forest harvesting on the availability of habitat attributes. Useful where strong linkages exist between habitat attributes and species (i.e. cavity nesting birds and snags). Habitat Association Modeling Statistical approaches useful where linkages are less clear; can incorporate stand and landscape level information.

5. SIMFOR Habitat Analysis Species - Habitat Relationships Habitat Attributes Treatments: Harvest Schedule Natural Disturbance Maps Summary Data GIS Processing Maps Tables, Figures Base Maps Field Evaluation GIS Processing

6. The Habitat Modeling Niche in the Invermere EFMPP FSSIM Analysis. “Basecase” harvest scenario. Current management. “Strategy 98” harvest scenario. Based on “enhanced” forest management. Desired Management. Harvest Scenarios Habitat Impacts Habitat Impacts determined by the Forest Ecosystem Specialist, MOE Invermere. A comparison of the habitat impacts resulting from the two management scenarios.

7. Habitat Impacts Determination Peter Holmes Invermere FES, MOE Habitat Modeling Trends. Goshawk Cavity Nesters Songbirds Maps, Graphs over space and through time. Local knowledge

8. Habitat Modeling Inputs I Harvest Schedules Fire (Alpine) Pine Beetle DRA Disturbance Alpine Fire Harvest Schedule Colours represent decade of disturbance. Operability Line Operability Line

9. Modeling Inputs II ( Goshawk Nesting Project) Literature Review Utzig and Gaines 1997 Review of existing Goshawk research for attribute selection. Quantitative Nesting Inventory Marlene Machmer refined the Lit. review attribute criteria,by locating and and assessing 16 nest sites. Data from three other nest sites have been added. Data to form Species-Habitat Relationships. (Stand level) Data to track Habitat Attributes over a large area. (Strategic, i.e. LU, District) Forest Cover Database Cruise Database TRIM

10. Scaling Up Attributes (Goshawk Nesting) Very Large Trees Large Trees Crown Closure Canopy Complexity Slope Proximity to Water Source Aspect Large Snags CWD Patch Sizes Inventoried Stand Level Attributes Attributes Modeled Very Large Trees Structure CWD Snags Slope Aspect Patch Size (GIS) Assumptions

11. Goshawk Attributes as inserted into SIMFOR 0 50 100 150 200 250 010305070110130150180 Years Stems/ha Fd good Pl good/med DC 2 - 4 >20cm DBH Slope –static attribute map Aspect –static attribute map Structure –supply curves by AU Very Large Trees (critical) –dynamic attribute maps (projected ages through time, with harvest disturbance considered).

12. Very Large Tree Attribute (Goshawk Nesting) The “Very Large Tree” attribute was addressed in two parts: 1. Single Layer Stands 2. Multiple Layer Stands This attribute was “scaled up” by determining which Age Classes (by Stand [AU]) had a sufficient number of trees >50cm dbh. to “qualify” as a candidate. This was done by analyzing the IFD Cruise database.

13. Very Large Tree Attribute Criteria: 50cm. Dbh and greater Good 20 stems\ha. plus Mod. 10-20 stems\ha. Low. 5-10 stems\ha. Analysis Units were chosen to qualify at the ageclass that they reached 10 stems per ha. Cruise database Analysis Stems >=50cm. Dbh per ha. Stems >=50cm. Dbh per ha. Stems >=50cm. Dbh per ha.

14. Large Tree Attribute - Multi Story Stands Some nests have been discovered in young stands i.e. The Forest Cover Map says Ageclass 4. These stands used for nesting (particularly in the IDF and MS) tend to have large vets which the goshawks are nesting in. This over story tree layer can be mapped with the existing forest cover database. Forest Cover Age classes (rank 1) Premier Lake

15. Layer 1 ageclass Layer 2 ageclass (Vets) Premier Lake Premier Lake

16. Stand Dither by Ageclass and Crown Closure Stands with vertical structure can contribute to the large tree attribute Stands contribute when the understory is at least 61 yrs and the overstory is at least 101 yrs.* Premier Lake

17. Basecase Year 1Basecase Year 40 Stork Creek Goshawk Nesting Results Mapping Spatial and Temporal Differences...

18. Goshawk Nesting Results given assumptions, NOGO nesting habitat is increasing through time. There may be spatial differences in NOGO habitat between the two harvest strategies.

19. Regression models developed in collaboration with Kari Stuart-Smith for selected neo-tropical migrants (MS and ESSF zones). e.g.: ln(ocwa count) = -1.198 - 0.141(LCONOVER) + 0.0085(SHCOVER) – 0.0486 (HEIGHT) + 0.0088 (REGENDEC) – 0.0034(REGENCON) – 0.0066(REGENPL) + 0.202(REGENSP) ln(wiwa count) = -2.776 + 0.0025(ELEV) + 0.0149 (ASPSLO) –0.0096 (ALLSNAGS) – 0.281(MNLAYERS) – 0.050 (HEIGHT) Habitat Association I: Habitat Relationships - Songbirds

20. Slope-Aspect Habitat Association II: Habitat Attributes

21. OCWA - MS: Strategy 98 Year 1 Year 20 Abundance

22. OCWA - MS: Strategy 98

23. Habitat Supply: Habitat Relationships - CNB

24. Habitat Attributes: Nesting (Year 1): Hardwood Source: Forest Cover Data % Species fields

25. Lw potential nesting/foraging 0 10 20 30 40 50 60 050100150200 Age Stems/ha Au 4 Lw G Au 5 Lw M Au 6 Lw P Lw snags (stems/ha) Western Larch - Potential Nesting / Foraging Habitat Attributes: Nesting (Year 1):

26. Foraging (Year 1): DRAMPB

27. DRA model: ITG: Fd, Lw, Pl Code: 8415-15, 8315-15 (AGECLASS,HT_CLASS,STK_CLASS,CROWN_CL_CLASS, AND SITE INDEX) MPB model (Shore and Safranyik): S = P x A x D x L S - susceptibility P - percent susceptible pine BA A - age factor D - density factor L - location factor

28. Western Larch Nesting/Foraging - Strategy 98:

29. 1. Model predictions are hypotheses. test of inventory to project structure test of knowledge about habitat relationships 2. Field verification is an essential next step. 3. Strategic vs. Tactical applications: Quantitative habitat evaluations (Strategic planning - i.e. TSR). ID Patches important for habitat (Tactical - i.e. LU planning). Confidence will improve as models are tested and refined. Last Words I:

30. Species - Habitat Relationships Habitat Attributes Treatments research and data synthesis - appropriate for scaling up stand level data - scaling issues from cruise to fip; inventory limitations (i.e. cwd, understory vegetation). stand structure implications of disturbance (i.e. MPB, DRA). accurate spatial harvest modeling will sometimes be important. cannot ignore natural disturbance. Last Words II: Teamwork - biologists, GIS support, planners setting objectives; getting results

31. Modeling Toolbox GIS –Arc\Info, Pamap SIMFOR –Access relational database setup, maps Generic Database –FoxPro, Access Programming Tools –Perl, SQL Statistical Tools –SAS Relative Time Spent (i.e. Goshawk Modeling) “Scaling up” refers to the process of selecting indicator attributes to represent many related stand level attributes. Last Words III:

32. ACKNOWLEDGMENTS We gratefully acknowledge: Forest Renewal B.C. funding provided by the Invermere Forest District Enhanced Forest Management Pilot Project Greg Anderson for support of the project Russ Hendry for providing the harvest schedules Emile Begin for discussions on MPB and DRA modeling Fred Bunnell for support and helpful comments Arnold Moy and Susan Paczek of CACB for database development and assistance in model runs