Habitat Supply for Multiple Wildlife: Modeling in MPB-Attacked Landscapes

1. Habitat Supply for Multiple Wildlife in MPB Attacked Landscapes Modeling approach and selected species

2. Goals/Outcomes • Effects of: • Mountain pine beetle • Climate change • Uncertainty • Management paradigms • Conservation of species

3. Challenges • Project was both broad and deep • Extensive • 15 million ha • Multiple wildlife species / variable ecosystems • Intensive • 70% Pl mortality • Habitat quality at 1-ha resolution • Multi-trophic • Range of user expectations

4. Merits/Demerits • Clear goals • Available tools • Experience • Love a good challenge!

5. Background • Selection of modeling approach • Selection of species • General model • Effect of MPB • Effect of Biogeoclimatic • Application • Results

6. Selection of Modeling Approach • Purpose – prediction / explanation • Algorithm structure – mechanistic / correlative • Ecological complexity – multi-trophic / singular • Treatment of time – forecast / static • Resolution (spatial/temporal/functional) – coarse / fine • Type of reasoning – inductive / deductive • Statistical foundation – frequency / probability • Outputs – capability / suitability • Type of result – deterministic / stochastic

7. Common Approaches • Element Distribution • Habitat Supply • Resource Selection Function • Habitat Suitability Index • Wildlife Habitat Rating

8. Chosen Approach • Bayesian-based habitat supply • Spatially referenced probability of occurrence • Sensitive to resource requirements • Not temporally/spatially limited • Explicit uncertainty • Relatively transparent and flexible • Mechanistic, multi-trophic, deductive, and deterministic way to forecast probabilistic explanations about habitat suitability at a relatively fine spatial, temporal, and functional resolution (whew! Never to be quoted please.)

9. Selection of Species • Most adversely affected by MPB and/or management response to MPB • Examples of hunted or trapped species • Closely related species that vary in habitat requirements

10. Criteria for Negatively Affected • CDC, COSEWIC status • Stakeholder interest • Extent of distribution in BC • Key ecological function • Relative dependence on pine • MPB threat on habitat structure • MPB related management threats

11. The 13 Species • Mape • Urar • Rata • Gugu • Spgr • Maam • Lewo • Tahu • Odhe • Lyca • Ceel • Alal • Stgr

12. Life requisite: dens/nests Management lever Life requisite: forage Composite effect: forage usefulness Life requisite: locomotion cost Subnet: Physical/ahabitat barriers Life requisite: thermal cover Composite effect: mortality potential Life requisite: security cover Subnet: Spatial factors General Model Structure Key ecological correlate Key ecological correlate Modifying factor: competition Modifying factor: displacement Key ecological correlate Species Occurrence Key ecological correlate Key ecological correlate Key ecological correlate Key ecological correlate Modifying factor: mortality sources

13. Effect of MPB

14. Biogeoclimatic Effects

15. Model Application Input layers, data management, run sequence

16. Results Spatial results and meta-data

17. Alal Odhe Ceel Rata Maam Gugu Mape Lyca Lewo Stgr Spgr

18. Modeling Results • Mind map • Netica input variable palette • Netica manager • Spatial layers • Input • Output • Meta data

19. Issues: Data Management • MS Access 2 GB limit • Corrupted databases • Adds additional processing steps to compact database or import data to new database • Mid-model spatial processing • Unscripted and done manually • Time intensive • Can introduce error • CPU space • With 3-4 processing areas per machine, space becomes an issue • Data management can introduce error

20. Issues: Missing Data

21. Issues: Caribou Ecotype

22. Issues: VRI • Interpretation • Data management

23. Issues: Background Noise

24. Issues: Other Data • Interpretation • Data management

25. Issues: Responsiveness

26. Scenario 3 Scenario 2 Scenario 1 Yr 10 Yr 0 Predator Prey Yr 20 Issues: Resources Species Habitat Relationships Habitat Supply Models Habitat Supply Management Alternatives Resource Inventory Disturbance Scheduler & Forest Estate Models Disturbance & Succession Inferred Pop’n Response Timber Supply & Landscape Conditions Interpretation

27. Solutions • Research input data / data management • Dump access • Simplify models (but no loss of precision) • Contemplate implications of model structure

28. Alpha- to Beta-level Models …and beyond

29. Why Alpha to Beta • Functional, multi-trophic models by their nature are complex and intricate • Application needs to be simple and uncomplicated

30. The Example of Mountain Caribou • Government wanted models that were transparent and mapped the thoughts of science advisors • Once built, they then wanted models that were easy to implement • Simplification based on sensitivity analyses and node reduction provided a pragmatic result that could be transferred to other modeling platforms

31. Early Winter Range: The Story

32. Early Winter Range: Application

33. Sensitivity Analysis in Netica

34. Other Possible Activities • Correction of errors (input data, scripting) • Adjustment of conditional probabilities • Addition/elimination of KECs • Realignment of relationships • Adjustment of input/output states (number and/or cutpoints) • Trials with “other” less restrictive software • Expert review of results • Verification of results with empirical information

35. Benefits • More reliable/applicable models • Easier and more efficient application • More readily transferred to different platforms