Potential of a national forest monitoring program to assess change in high latitude ecosystems
Inventorying Alaska’s Forests
Feb. 4, 2014
Anchorage, AK
Tara Barrett
Pacific Northwest Research Station
USDA Forest Service
The bread‐and‐butter FIA
State reports, national reports, owner surveys, mill surveys
FIA: 86 years of being the nation’s forest inventory program Uses of FIA data have diversified
Urban forest
inventory
Fire effects and fuels mapping
Risk assessment for forest pests
Mapping wildlife habitat
Annual FIA
Lichens used by EPA to monitor air quality
Biomass supply for the energy industry
Mapping disturbance
Soil samples used to detect heavy metal deposition from air pollution
Nationally, the diversity of uses has resulted in support from diverse interests
TADIA: Things Are Different in Alaska
• Other U.S. states have all had multiple inventories dating back decades.
• EMAP: Lower 48 states included in the 1990s forest health monitoring program.
• Some states are on their 3rd
annual measurement cycle.
• Nationally: strong and relatively stable support
In Alaska:
 Coastal Alaska inventory was very good: permanent plots at the regular grid, just completed remeasurement. But cancelled for 2014?
 The ~45 million hectares of boreal forest had one aerial survey in the 1960s, with a small field component only in accessible sites.
 Most timberland and commercial forest in the state has been inventoried with a good (air photo & field‐based) system, 1970s & 1980s. We think timberland is about 6% of the boreal forest.
Somewhat understandable: Inventory and monitoring in Alaska is EXPENSIVE
Negative cycle for inventory and monitoring in Alaska
Relatively little data for Alaska
Outdated for most of the state
Not many attributes beyond trees
Fund Alaska inventory last
Cut Alaska inventory first
Find cheap solution for boreal forest
Client perception:
Data is not useful
Products don’t meet our needs
National FIA perception:
Clients in Alaska not vocal
Little political support for Alaska inventory
Only national level need for Alaska data
Positive cycle for inventory and monitoring in Alaska
Ongoing coverage for the entire state
Databases that are publically available and easy to use
Attributes collected are tailored to Alaska’s issues
Sustained and dependable funding for Alaska inventory, entire state included Partners’ perception:
Data is useful
Products meet our needs
National FIA perception:
Clients in Alaska support the program
Alaska is FIA’s global poster child for monitoring in inaccessible regions
What can change the cycle?
1. The 2014 Farm bill: Within 180 days, the Secretary of Agriculture shall revise the plan for FIA to describe the organization, procedures, and funding needed to achieve a fully annualized forest inventory program and include inventory and analysis of interior Alaska.
2. New technology: GPS, LiDAR, other remote sensing
3. New needs: climate change, carbon monitoring, and bioenergy
4. The coastal inventory: first ever good remeasurement is leading to new products and uses of data. (8 EXAMPLES)
5. Working with partners
a. Data and analysis that meets needs
b.
Political support for program
c.
Additional resources (expertise, funding, data‐sharing)
d.
Compatible information systems (tiering, plot designs, definitions)
Major strength of the FIA program: statistically sound sampling design, well‐accepted methods for estimating population attributes and sampling error
A tessellation of hexagons is used to create a spatially balanced sample, with one field plot selected for each hexagon
Field measurements taken on those plots that fall in forest land
Note that FIA sometimes works with partners to also sample nonforest vegetation (e.g., shrubland, tundra, grassland).
Remeasured permanent plots (about 930 permanent sample plots installed 1995–2003 and remeasured 2004–2010) across all lands
2
Eight examples of using the coastal Alaska data for monitoring change
Example #1: change detection in species composition
For monitoring changes in tree species, I looked at three broad ecoregions:
This analysis is part of the USFS/Kenai NWR Climate Change Vulnerability Assessment, a multi‐agency project currently in progress.
Example #1. Results for the Gulf Ecoregion, change in species composition
5
50
4
40
3
30
2
20
1
10
0
0
‐1
‐10
‐2
‐20
‐3
‐30
‐4
‐40
‐5
Decadal net change
Annual mortality and growth (%)
Gulf Ecoregion (unmanaged forest)
Biomass growth, mortality, and net change for major tree species
Annual mortality (%)
Annual growth (%)
Decadal net change (%)
‐50
Error bars denote standard error (68% CI)
Evidence for recent biomass increase is very strong, with the 95% CI of 5–13% increase per decade. P‐values for change are <0.001 for Sitka spruce and biomass overall, 0.002 for paper birch and cottonwood. Leads to …… example #2, a cooperative project between UAA & FIA to analyze tree ring cores to look for relationships between climate and growth.
Example #3: Working with partners (State and Private Forestry, Forest Heath Monitoring, & CalPoly) to figure out why shore pine is decreasing
Pinus contorta sample sites
Shore Pine example #3
Decrease in shore pine found by FIA resulted in a cooperative project with State and Private Forestry plant pathologist Robin Mulvey (Juneau, AK) to do the first baseline survey of insects, diseases, and damages affecting lodgepole pine (shore pine subspecies) in Alaska.
She used the FIA plot design for her randomly selected study plots, but constrained to be within 0.5 miles of roads or trails.
Western gall rust
Lodgepole pine sawfly (1st record for Alaska)
Larval frass and galleries on gall of dying branch
Needle blight
Photos courtesy of Robin Mulvey
7
0.6
6
0.5
5
0.4
4
0.3
3
0.2
2
Dead / Live
Sapling / Live
2200 +
2000 ‐ 2199
1800 ‐ 1999
1600 ‐ 1799
1400 ‐ 1599
1200 ‐ 1399
1000 ‐ 1199
800 ‐ 999
0
600 ‐ 799
0
400 ‐ 599
1
200 ‐ 399
0.1
Ratio of saplings to live trees
0.7
0 ‐ 199
Ratio of dead trees to live trees
Example #4: indirect indication that yellow‐cedar may be “migrating”?
Elevation (ft)
A cooperative project with Paul Hennon, State and Private Forestry. Example #5: projecting change of spruce species in the region
Current distribution of spruce species on inventory plots in the study area, from FIA plots 1995–2008. This analysis is also part of the USFS/Kenai NWR Climate Change Vulnerability Assessment, a multi‐agency project currently in progress.
Results show increased habitat for Sitka spruce on the western Kenai over the next 90 years.
(Note this is being driven by the projected increases in temperature and precipitation in the climate models — some people think the projections are off and the precipitation is not going to be high enough to offset increased evapotranspiration.)
Example #6: First region‐wide assessment of the incidence of hemlock dwarf mistletoe.
Projection of change for western hemlock and hemlock dwarf mistletoe under future climate.
Future Climate Models
We used downscaled GCM composites created by the Scenarios Network for Alaska Planning (SNAP 2011). The composite models were made from the MPI ECHAM5, the GFDL CM2.1, the 324 MIROC 3.2 (medres), the UKMO HADCM3, and the CCCma CGCM3.1 models
which had been chosen based on relatively good performance in a review of GCMs for Alaska and Greenland by Walsh et al. (2008).
PRISM + (GCM_future – GCM_present) = Predicted
Scenarios Network for Alaska Planning [SNAP]. 2011. Alaska climate datasets online. Available from www.snap.uaf.edu/downloads/alaska‐climate‐datasets
Walsh, J.E., Chapman, W.L., Romanovsky, V., Christensen, J.H., and Stendel, M. 2008. Global climate model performance over Alaska and Greenland. J. Clim. 21:6156‐6171.
From: Barrett, T.M.; Latta, G.; Hennon, P.E.; Eskelson, B.N.I.; Temesgen, H. 2012. Host-parasite distributions under changing
climate: Tsuga heterophylla and Arceuthobium tsugense in Alaska. Canadian Journal of Forest Research 42:4: 642–656
Example #7: Carbon and Biomass
Emerging markets for carbon storage?
Required monitoring of carbon for federal lands
National Forest Assessments
Incorporation of carbon consequences into forest management decisions
Biomass (~2× carbon mass for trees) is main metric for bioenergy supply
Results for the Chugach National Forest
Overall, 4.5 percent increase in biomass and carbon in live trees.
Annual sequestration was about 165,000 tons of carbon mass. Increase was about 552 lbs of C per forest acre per year (Doesn’t include the wilderness study areas.)
Results for the Tongass National Forest
No net change in carbon mass in live or dead trees. Total storage is huge — over 650 million metric tons in trees and logs — more than any other national forest in the United States
Unmanaged lands (72 tons per acre):
7 percent logs
13 percent snags
80 percent live trees
Managed lands (45 tons per acre)
38 percent logs
8 percent snags
54 percent live trees
Growth and recruitment was much higher on managed forest (1,608 lbs per acre per year vs 690 lbs per acre per year), natural mortality was much lower (278 lbs per acre per year versus 619 lbs per acre per year).
“Managed”: in this study, the term is used for forest with any evidence of past silvicultural activity or vegetation treatment. Includes some areas with complex structure and old trees as well as former clearcuts.
Basal area (m2ha‐1)
Example # 8: Growth and yield modelling
Mountain hemlock
Basal area (m2ha‐1)
Diameter (cm)
Average predicted and observed stand states at the second inventory for the matrix model and FVS on 293 post‐sample validation plots, with the 95% confidence interval of the observed mean.
Western redcedar
and yellow‐cedar combined
From Peterson, R.; Liang, J.; Barrett, T.M. 2014. Modeling population dynamics and woody biomass in Alaska coastal forest. Forest Science.
Forest inventory & monitoring for interior Alaska:
additional possible uses for FIA data
For more details, see “Potential of a national monitoring program for forests to assess change in high‐latitude ecosystems.” Biological Conservation (2011) 144: 1285–1294. Climate change is complicated, and models have huge uncertainties and limitations. Climate Change
Monitoring provides early information on trends, and can both supply
data to and validate models.
Monitoring of insects and disease impacts on forests
Spruce beetle mortality on the Kenai, 1990s.
2007 Caribou Hills fire on the Kenai Peninsula
Photo taken August 2008
Fire effects
Fire risk
Postfire succession
Mapping species habitat
© Mark Moon
Bobcat (Lynx rufus)
Mapping habitat for bobcats in Oregon/Washington using Gradient Nearest Neighbors imputation; example courtesy of Andy Gray, PNW‐FIA Soils data Nutrients & site productivity
Heavy metal deposition
Understory vegetation and lichen protocols
Invasive
Plants
From UAF Cooperative extension
www.uaf.edu/ces/pests/cnipm/plants/
“Yes we can”
High quality data pertinent to Alaska issues
Good use of data and applications through partnerships and cooperation
Sustained funding
National support of Alaska FIA