Extensive, Strategic Assessment of Southeast Alaska’s Vegetative Resources Willem van Hees, Bert Mead Pacific Northwest Research Station, Forest Inventory and Analysis, 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 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 distribution

423 1 Microplot: 6.8 ft. radius Subplot: 24.0 ft. radius 120 ft. between subplot centers Field Plot design

Mapped Plot Forest Nonforest

Field Plot (re)measurement schedule initiate annual remeasurement of 1/10 of plots with forested conditions baseline measurement, all vegetated

Also in 2003: Initiate measurement for Forest Health Monitoring

Forest Health Monitoring 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 Owner TotalForest Nonforest NFS Other federal State & local Private All million acres

Woodpile descriptors: Area of timberland/other forest Owner TotalTimberland Other forest All 10,995 4,096 6, thousand acres Other federal Other federal NFS ,423 5,932 State & local Private

Woodpile descriptors: Forest type distribution

Woodpile descriptors: volume/ac on timberland

Woodpile descriptors: growth and mortality on timberland

Woodpile descriptors: Mortality per acre Cubic-foot mortality, per acre, Western redcedar/hemlock forest type

Nonforest vegetation characterization

Nonforest vegetation characterization: shrub & herbaceous types

Nonforest vegetation characterization: area of low shrub

Cooperative Research Centre for Biodiversity & Conservation Schools of Biology & Geography, University of Leeds William Kunin, Steve Carver, Jack Lennon, Simon Corne, Michael Pocock, Naomi van der Velden & Crewenna Dymond Spatial analyses

Research 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 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 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 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 & Management Biology of core & marginal tree populations Testing human impacts on vegetation – – Changes in forest composition after harvest

Core 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: )

Human 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 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 & Mapping Neural net analyses of SEAK data estimating forest characteristics Species maps including marginality index Biodiversity maps (of trees, understory spp)

Neural 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 Type Compared to commercially available post-processed images purchased from Pacific Meridian Resources

Summary comparison (PNN model)

Research 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 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 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