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Extensive, Strategic Assessment of Extensive, Strategic Assessment of Southeast Alaska’s Vegetative Southeast Alaska’s Vegetative
ResourcesResources
Willem van Hees, Bert MeadWillem van Hees, Bert Mead
Pacific Northwest Research Station, Forest Inventory and Pacific Northwest Research Station, Forest Inventory and Analysis, Anchorage, AKAnalysis, Anchorage, AK
•FIA and R10 – Historic perspective
•Roles of FIA inventory
•Inventory description
•Analysis of inventory data
•FIA and R10 – Historic perspective
•Roles of FIA inventory
•Inventory description
•Analysis of inventory data
•1950’s - 60’s PNW – Alaska Forest survey Unit, Juneau, inventory, some remeasurement
•1970’s PNW, Forest Inventory & Analysis, Juneau, reinventory; FIA/R10 MOU
•1978 PNW FIA moves to Anchorage
•1980’s R10, reinventory
•1995 - 2001 PNW FIA, Anchorage, hex-based sample, annual 1/10 remeasurement
•Roles of FIA inventory
•FIA and R10 – Historic perspective
•Inventory description
•Analysis of inventory data
Strategic scale; spatial nature
• Information base for resource management in landscape/owner context
• Can serve NFS regional planning needs• Independent data set to validate and adjust allowable harvest ratesIndependent data set to validate and adjust allowable harvest rates
• Spatial data to model coverages of derived products unattainable elsewhere.Spatial data to model coverages of derived products unattainable elsewhere.
• Nationally consistent core data and analyses across political, administrative, and land ownerships boundaries. Internal Agency information needs include
• Resource Planning Act (RPA) assessmentsResource Planning Act (RPA) assessments
• Status reports on Criteria and IndicatorsStatus reports on Criteria and Indicators
• Special assessments such as the UN - FAO Forest Resource Assessment.Special assessments such as the UN - FAO Forest Resource Assessment.
•Roles of FIA inventory
•FIA and R10 – Historic perspective
•Inventory description
•Analysis of inventory data
Field Plot distributionField Plot distribution
44
22
33
11
Microplot:Microplot:6.8 ft. radius6.8 ft. radius
Subplot:Subplot:24.0 ft. radius24.0 ft. radius
120 ft. between120 ft. betweensubplot centerssubplot centers
Field Plot designField Plot design
Mapped PlotMapped Plot
44
22
33
11ForestForest
NonforestNonforest
Field Plot (re)measurement scheduleField Plot (re)measurement schedule
20032003 initiate annual remeasurement of 1/10 of plots with forested conditions
1995-2001 1995-2001 baseline measurement, all vegetated
Also in 2003: Initiate measurement for Forest Health Monitoring Also in 2003: Initiate measurement for Forest Health Monitoring
Forest Health MonitoringForest Health Monitoring
5 indicators of forest health:5 indicators of forest health:
• Ozone: Plant ozone injury used to adjust ozone emission standards
• Lichens: Sensitivity to pollutants used as an indicator of changing air quality
• Soil: Evaluation of soil physical and chemical properties, erosion and compaction.
• Vegetation: Assessment of abundance and spatial arrangement of all trees, shrubs, herbs, grasses, ferns for biodiversity changes
• Coarse woody debris: Estimates biomass of coarse woody debris, fine woody debris, duff, litter, slash, and fuelbed depths for carbon sequestration, fire models….
•Roles of FIA inventory
•FIA and R10 – Historic perspective
•Inventory description
•Analysis of inventory data
•Analysis of inventory data –
• Woodpile descriptors
• Nonforest vegetation characterization
• Spatial analyses
•Woodpile descriptors: Area of forest/nonforest
0
1
2
3
4
5
6
7
8
9
10
Forest Nonforest
NFS
Other federal
State & local
Private
Owner Owner Total Total Forest NonforestForest Nonforest
NFS NFS 16.916.9 9.49.4 7.67.6
Other federalOther federal 4.4 4.4 0.60.6 3.83.8
State & localState & local 0.8 0.8 0.40.4 0.40.4
Private Private 0.7 0.7 0.60.6 0.10.1
AllAll 22.9 22.9 11.011.0 11.911.9
----------------------------------million acres------------------million acres------------------
•Woodpile descriptors: Area of timberland/other forest
Owner Owner Total Total Timberland Other forestTimberland Other forest
AllAll 10,995 10,995 4,096 4,096 6,898 6,898
------------------------------------------thousand acres-----------------------thousand acres-----------------------
Other federalOther federal 618 618 6 6 612 612
NFSNFS 9.3559.355 3,423 3,423 5,932 5,932
State & localState & local 390 390 272 272 118 118
PrivatePrivate 632 632 396 396 236 236
0
1,000
2,000
3,000
4,000
5,000
6,000
Timberland Other forest
NFS
Other Federal
State & Local
Private
• Woodpile descriptors: Forest type distribution
•Woodpile descriptors: volume/ac on timberland
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
Ft3
/acr
e
Alaskacedar -hemlock
Lodgepolepine
Mixedconifer
W.hemlock -Sitka spr.
W.redcedar -hemlock
W.hemlock
Sitka spr M.hemlock
Forest type
•Woodpile descriptors: growth and mortality on timberland
0
10000
20000
30000
40000
50000
60000
70000
Th
ou
san
d c
ub
ic f
eet
Alaskacedar -hemlock
Lodgepolepine
Mixedconifer
M. hemlock Sitka spr W. hemlock- sitka spr
W.redcedar -hemlock
W. hemlock
Forest type
GrowthMortality
• Woodpile descriptors: Mortality per acre
Cubic-foot mortality, per acre, Western redcedar/hemlock forest type
20-40
41-60
61-85
•Nonforest vegetation characterization
•Nonforest vegetation characterization: shrub & herbaceous types
0
10
20
30
40
50
60
70
80
thou
sand
acr
es
National Forest State and Local Private
Alder
Alder-w illow
Copperbush
Copperbush-blueberry
Copperbush-salmonberry
Ericaceous
Mixed shrub
Sagebrush-juniper
Salmonberry-blueberry
Sw eetgale
Unknow n
Willow
•Nonforest vegetation characterization: area of low shrub
Cooperative ResearchCooperative Research
Centre for Biodiversity & ConservationCentre for Biodiversity & Conservation
Schools of Biology & Geography, University of Schools of Biology & Geography, University of LeedsLeeds
William Kunin, Steve Carver, Jack Lennon, Simon Corne, Michael Pocock, William Kunin, Steve Carver, Jack Lennon, Simon Corne, Michael Pocock,
Naomi van der Velden & Crewenna DymondNaomi van der Velden & Crewenna Dymond
• Spatial analyses
Research ProgramResearch Program
Development
& testing of New Spatial Analytic Methods
Analysis and mapping of SEAK Forest Data
Basic research in
Macro-ecology
Research in
Forest Biology & Manage-ment
Research ProgramResearch Program
Development
& testing of New Spatial Analytic Methods
Analysis and mapping of SEAK Forest Data
Basic research in
Macro-ecology
Research in
Forest Biology & Manage-ment
Macroecology researchMacroecology research
• Cross-scale analyses of species distributions; extrapolating across scales
• Species-area relationships and their basis in individual species range structure
• Climate & tree spp effects on understory plant spp diversity
Research ProgramResearch Program
Development
& testing of New Spatial Analytic Methods
Analysis and mapping of SEAK Forest Data
Basic research in
Macro-ecology
Research in
Forest Biology & Manage-ment
Forest Biology & ManagementForest Biology & Management
• Biology of core & marginal tree populations
• Testing human impacts on vegetation
– Changes in forest composition after harvest
Core vs. marginal populationsCore vs. marginal populations
• Developed methods for determining the degree of “marginality” of SEAK tree populations
• Results suggest marginal populations become more
specialised in habitat tolerances (Global Ecology & Biogeography 11: 103-114)
Human impacts on vegetationHuman impacts on vegetation
• Analyses of clearcut sites suggest change in forest species composition
• Edge effects of clearcuts difficult to measure (due to position errors)
Research ProgramResearch Program
Development
& testing of New Spatial Analytic Methods
Analysis and mapping of SEAK Forest Data
Basic research in
Macro-ecology
Research in
Forest Biology & Manage-ment
Analysis & MappingAnalysis & Mapping
• Neural net analyses of SEAK data estimating forest characteristics
• Species maps including marginality index
• Biodiversity maps (of trees, understory spp)
Neural Net modelsNeural Net models
• Models trained with SEAK surveys
• Proven potential to outperform commercial LANDSAT image analysis in predicting:– Crown closure– Land cover type– Size/structure
• Application software being developed
Land Cover TypeLand Cover Type
Compared to commercially available post-processed images purchased from Pacific Meridian Resources
Summary comparison Summary comparison (PNN model)(PNN model)
0102030405060708090
100
Crown
cove
r
Crown
cove
r
Stand
size
Stand
size
Land
cove
r
Land
cove
r
PNN approx.
PNN correct
PMR approx.
PMR correct
Research ProgramResearch Program
Development
& testing of New Spatial Analytic Methods
Analysis and mapping of SEAK Forest Data
Basic research in
Macro-ecology
Research in
Forest Biology & Manage-ment
New methods in spatial analysisNew methods in spatial analysis
• Tests of relative effectiveness of various Neural Net models.
• Land cover fragmentation using fractal measures
• Novel methods for testing associations between autocorrelated variables
Future directionsFuture directions
• Neural net analyses could be applied easily to other regions or other issues (e.g. fire risk): a cost-efficient way to generalise from field survey data
• Species interactions at range margins: growth, competition, pathogens