Eric Valdal, GIS Analyst, EFMPP Ralph Wells, Research Analyst, CACB - UBC.
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Transcript of Eric Valdal, GIS Analyst, EFMPP Ralph 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
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
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):
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