Eric Valdal, GIS Analyst, EFMPPRalph Wells, Research Analyst, CACB - UBC

OBJECTIVESOBJECTIVES

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.

ApproachesApproaches

• Identify species: Goshawk, CNB, songbirds.

• Develop quantitative methods for habitat models.

• Utilize existing databases for stand structure projections.

• Incorporate natural disturbance in harvest runs.

Quantitative Approaches to Habitat Modeling: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.

SIMFORHabitat

Analysis

Species - Habitat Relationships

Habitat Attributes

Treatments:Harvest ScheduleNatural Disturbance

MapsSummary Data

GIS Processing

MapsTables, Figures

Base Maps

FieldEvaluation

GIS Processing

The Habitat Modeling Niche in theInvermere 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 determinedby the Forest Ecosystem Specialist, MOE Invermere .

A comparison of the habitatimpacts resulting from the two management scenarios.

Habitat Impacts Determination

Peter HolmesInvermere FES, MOE

Habitat Modeling Trends.•Goshawk

•Cavity Nesters•Songbirds

•Maps, Graphs over space and through time.

Local knowledge

Habitat Modeling Inputs I

• Harvest Schedules

• Fire (Alpine)

• Pine Beetle

• DRA

Disturbance

Alpine Fire

Harvest Schedule

Colours representdecade of disturbance.

OperabilityLine

OperabilityLine

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 formSpecies-Habitat Relationships.

(Stand level)

Data to trackHabitat Attributes

over a large area.(Strategic, i.e. LU, District)

• Forest Cover Database

• Cruise Database

• TRIM

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

InventoriedStand Level Attributes

Attributes Modeled

•Very Large Trees•Structure

•CWD•Snags

•Slope•Aspect•Patch Size (GIS)

Assumptions

Goshawk Attributesas inserted into SIMFOR

0

50

100

150

200

250

0 10 30 50 70 110 130 150 180

Years

Ste

ms/

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).

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.

ageclass Fir G Fir M Fir P4 6 0 15 11 9.2 5.06 10.4 10.2 10.47 12.1 6.3 14.38 41.0 34.1 14.89 26.8 43.9 16.6

age class Larch G Larch M Larch P4 0 0 05 10.0 7.0 06 0 0 07 13.5 12.7 08 7.6 7.6 27.39 0 0 0

age class Spruce G Spruce M Spruce P4 0 0 05 10.3 0 14.56 0 3.0 10.27 14.8 0 5.78 28.0 26.2 11.49 41.1 0 23.3

Very Large Tree

Attribute Criteria:50cm. Dbh and greater

Good 20 stems\ha. plusMod. 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 databaseAnalysis

Fir Analysis Units - Stems > 50cm dbh

0

10

20

30

40

50

4 5 6 7 8 9

Age Class

Ste

ms\

ha.

> 5

0cm

. db

h

au1

au2

au3

Larch Analysis Units - Stems > 50cm dbh

0

5

10

15

20

25

30

4 5 6 7 8 9

Age Class

Ste

ms\

ha.

> 5

0cm

db

h

au4

au5

au6

Spruce Analysis Units - Stems > 50cm dbh

0

10

20

30

40

50

4 5 6 7 8 9

Age Class

Ste

ms

> 50

cm d

bh

au7

au8

au9

Stems >=50cm. Dbhper ha.

Stems >=50cm. Dbhper ha.

Stems >=50cm. Dbhper ha.

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)

PremierLake

Layer 1 ageclass Layer 2 ageclass (Vets)

PremierLake

PremierLake

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 andthe overstory is at least 101 yrs.*

PremierLake

Basecase Year 1 Basecase Year 40

Stork Creek

Goshawk Nesting Results

Mapping Spatial and Temporal Differences...

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. 3000

3500

4000

4500

Are

a (h

a)

1 10 20 30 40 50

Harvest Year

Target Patch Size Totals 20-40 ha.

s98>20

base>20

60000

65000

70000

75000

80000

Are

a (

ha)

1 10 20 30 40 50

Harvest Year

Total "Good" Goshawk Nesting Potential

s98 hab

base hab

• 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 - SongbirdsHabitat Association I: Habitat Relationships - Songbirds

Slope-Aspect

ALLSNAGS - MS Burn

0.00

20.00

40.00

60.00

80.00

100.00

120.00

0 10 20 30 40 50

AGE (YRS)

ME

AN

ALL

SN

AG

S

8

1 9 4

ALLSNAGS - MS Harvest

0.00

5.00

10.00

15.00

20.00

0 10 20 30 40 50

AGE (YRS)

ME

AN

AL

L S

NA

GS

25

3

24

16 15

14

2

Habitat Association II: Habitat AttributesHabitat Association II: Habitat Attributes

OCWA - MS: Strategy 98 OCWA - MS: Strategy 98

Year 1 Year 20

Abundance

0

2000

4000

6000

8000

10000

12000

14000

Are

a (h

a)

1 5 10 20 50

Year

OCWA High Abundance

OCWA - MS: Strategy 98 OCWA - MS: Strategy 98

Habitat Supply: Habitat Relationships - CNBHabitat Supply: Habitat Relationships - CNB

Tree species and characteristics important to primary cavity nesting birds.TreeSpecies

DC Dbh (cm) Othercharacteristics

CNB Species Life function

At 1-2 >30 rnsa, hawo, bbwo, nofl, piwo nesting, foragingEp 2-5 >30 broken top,

heart rotrnsa (DC 1-2 foraging), hawo, nofl nesting, foraging

Lw 2-4 >30 broken top,mistletoe

hawo, ttwo, bbwo, nofl, piwo, brcr nesting, foraging

Pl 2-4 >20 ttwo, bbwo, (hawo - foraging only) nesting, foragingFd 3-5 >40 armillaria rbnu

rnsa (DC 1-2), hawo, ttwo, bbwo, piwonestingforaging

Habitat Attributes: Nesting (Year 1):Habitat Attributes: Nesting (Year 1):

HardwoodSource:

Forest Cover Data

% Species fields

Lw potential nesting/foraging

0

10

20

30

40

50

60

0 50 100 150 200

Age

Ste

ms/

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):Habitat Attributes: Nesting (Year 1):

Foraging (Year 1):Foraging (Year 1):

DRA MPB

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 - susceptibilityP - percent susceptible pine BAA - age factorD - density factorL - location factor

Western Larch Nesting/Foraging - Strategy 98:Western Larch Nesting/Foraging - Strategy 98:

0

1000

2000

3000

4000

5000

6000

Are

a (h

a)

natural 1 5 10 20 50

Year

Larch snags >30 stems/ha

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:Last Words I:

Species - Habitat Relationships

Habitat Attributes

Treatments

• research and data synthesis - appropriate for scaling up

• stand level data - scaling issues from cruise to fip; inventorylimitations (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:Last Words II:

Teamwork - biologists, GIS support, planners• setting objectives; getting results

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)

GIS

SIMFOR

DB programming

Scaling Up process

“Scaling up” refers to the processof selecting indicator attributes to represent many related stand levelattributes.

Last Words III:Last Words III:

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 developmentand assistance in model runs