1. Vegetation Profile as applied in Interior Alaska
Beth Schulz, PNW-RMA Anchorage
FIA National Vegetation Indicator Advisor

2. The Vegetation Profile
Is more than “understory” veg
Refines how FIA data can characterize forest vegetation in terms of:
Wildlife habitat
Host species for insects and diseases
Wildfire Fuels
Ecological services
Classification
Contributes to other National programs
My objectives: promote understanding that veg profile is more than understory vegetation
AND
Beyond standard reporting tables, provides additional information to characterize forests in terms of multiple reources
Feeds into a number of other national efforts.

3. The VEG Profile is more than understory veg!
Cover by growth habit by layer
Most abundant species
Trees included!

4. What??? More tree data?!?! A different perspective –
For structure, all tally tree cover combined, by layer, “total”
And for species data, each species – combined individuals, by large and small trees, with the layer the most foliage
Capture information about non-tally species
and squished into a single 2 d pancake for a

5. Structure data – cover by growth habit by layer – reveals the importance of shrubs by forest types. Large shrubs over 2 m high are not uncommon. (by forest type)

7. Species data *(regardless of tally tree status)
Species present with ≥3% cover (up to 4 by growth habit)
Large Trees (LT)*
Sapling/Seedling (SD)*
Shrubs (SH)
Forbs (FB) includes herbs, ferns, and fern allies
Grass-like (GR) includes grasses, sedges, rushes
*(regardless of tally tree status)

8. Species Results: 98 plots
Total of 105 species/ genera recorded
Average number species
Per Subplot:
6.1 (range 2-13)
Per Plot:
10.4 (range 3-22)
Most commonly recorded species, growth habit (n plots):
Vaccinium vitis-idaea - SH (71)
Picea mariana SD, LT (67)
Betula neoalaskana SD, LT (66)
Ledum groenlandicum SH (62)
Picea glauca SD, LT (57)
Vaccinium uliginosum SH (37)
Rosa acicularis SH (35)
Alnus viridis ssp. crispa SH (30)
Calamagrostis canadensis GR (27)
Betula nana SH (23)
Geocaulon lividum FB (23)
Photo credit: Mark W. Skinner, hosted by the USDA-NRCS PLANTS Database
Note: the 4 most abundant species per growth habit recorded if cover is 3% or greater. This limits the number of species recorded. Can’t really use to assess species richness.
( If anyone asks - We did a special project on the Tetlin National wildlfe Refuge and did a full census of vascular plants on subplot one, demonstrating the actual number of species present. The average number of species recorded on the full-census subplots was 21 – range )
Mark W. Skinner, hosted by the USDA-NRCS PLANTS Database
Note that the majority of most commonly recorded species where woody – either shrubs, seedlings/saplings, or larger trees

9. Tree species, small and large
Number of plots
Tree species
Small
Large
Both
number of plots 67
Black spruce 66 30 28
Alaska paper birch 58 41 57
White spruce 48 44 32 16
Aspen 13 9 6
Balsam poplar 4 5
Larch
Bebb willow 1 2
Mountain Alder
Scouler’s willow
The Vegetation profile data allows us to collect data on small trees not on the tally tree list. Provides another way to looks at the distribution of trees – not limited to saplings on microplots
Trees in bold on tally tree list, those in italic not on current tally tree list

10. Feeding data to other National programs:
To serve a broader client base, FIA is enhancing its classification options….
Historically, tree species dominance
(SAF cover types ~ FIA Forest Type)
Vegetation-based approach, using FGDC standard
Combination of tree species with physiognomy, biogeography and ecology – USNVC Macrogroup and Group

11. Although some Forest Type ≈ SAF Forest Cover Type ≈ USNVC Alliance
FIA Forest type ≠ USNVC Alliance

12. Because vegetation represents a synthetic surrogate for landscape level processes our objectives include:
Provide uniform federal statistics for vegetation in the U.S.
Encourage partners to use common system when working with federal agencies.

13. Tree abundance = Relative Importance Value (~ Canopy Cover)
Relative importance value by species was calculated for each plot.
RIV= ½ (relative density + relative basal area)
Tree and sapling data were combined into one RIV value per species per plot.
Separating sapling from tree not helpful at macrogroup and group levels.

14. Landfire will develop a key to all USNVC types (forest and non-forest) down to Group level.
How can Landfire benefit from FIA eastern forest Key when building its key?
How can FIA benefit from Landfire key to complete all U.S. forests?

15. Additional data collected will help inform revisions…
Beyond Vegetation Profile
Ground layers
Soils

16. New DWM protocol includes assessment of fuel bed conditions
At the same time we are revising this guide - 6 or 7 black spruce types described, but we only have one FIA Black spruce forest type.

17. Currently using interior AK data to help refine Macrogroups/Groups in Boreal
Forest & Woodland
1.B. Temperate & Boreal Forest & Woodland
1.B.4. Boreal Forest & Woodland
1.B.4.Na. North American Boreal Forest & Woodland
2M156. Alaskan-Yukon North American Boreal Forest
G349. Alaskan-Yukon Boreal Dry Aspen Forest
G579. Alaskan-Yukon Boreal Mesic-Moist White Spruce - Hardwood Forest
G350. Alaskan-Yukon Boreal Mesic-Moist Black Spruce Forest 8
G627. Alaskan-Yukon Boreal Moist White Spruce - Hardwood Forest

18. Vegetation Profile Let’s continue to provide high quality data!
More than understory veg!
Refine descriptions of forest vegetation resources, conditions
National programs depend on FIA data for on-going revisions and development.
Let’s continue to provide high quality data!