1. Site Productivity and Land Classification
Lecture 13:
Forest Ecology 550

2. Objectives Discuss indirect ways to measure site productivity
Briefly discuss land classification
Introduce ecosystem process models
What role can remote sensing play in estimating forest species composition, structure, and function.

3. Site Productivity Definition
Sites potential to produce one or more natural resources
Sustainable
Manage for multiple resources

4. Site Productivity: indirect measurement approaches
1) Site index: Forest measurement to measure site quality
Based on height of the dominant and co-dominant trees based on some standard age
Age depends on location and stand type
Typically 50 years but..

5. Forest Productivity: Site Index Curve
Anamorphic curves

6. Site index curves: Pros/cons
Easy and inexpensive
Height growth is less sensitive than basal area growth to stocking density.
Cons
very site dependent (soils, topography, aspect)
Differs among species
Requires trees growing on the site
Cannot capture dynamic nature of tree growth and global change

7. Site Productivity: indirect measurement approaches
2) Overstory tree species
Each species occupies its own niche
Black spruce image from:

8. Site Productivity: indirect measurement approaches
2) Overstory tree species
Each species occupies its own niche
Advantages
Allows you to make quick assumptions about a given area
Disadvantages
Challenging for species that are able to exist in a wide range of climates

9. Site Productivity: Indirect measurement approaches
3) understory species
Definition: use of understory species to make classifications of site
Advantages:
More sensitive to micro-climate differences
Indicator species
Disadvantages
What about disturbance
Indicator species: have such a small ecological niche that their presence or absence can mean different things.
Marsh marigold: fen indicator species

10. Site Productivity: Indirect measurement approaches
3) understory species
Other examples:
Ephemerals often have a narrow ecological niche

11. Site Productivity: Indirect measurement approaches
4) Ecological Site Classification
Primary means is through Habitat Typing
Identified by distinct understory plant assemblages
natural vegetation to identify ecologically equivalent landscape units
growth
natural resource use potential

12. Soil usually sand to loamy sand. At least two species
present:low sweet blueberry, wintergreen,
sweet fern, pipsissewa, cow wheat, witch hazel, maple-leaf
viburnum, pointed leaf tick treefoil
witch hazel, maple-leaf
viburnum, pointed
leaf tick treefoil
Species on right rare
or absent blueberry,
wintergreen
or absent
At least 2 present
honeysuckle, twisted
stalk, partridgeberry,
yellow beadlilly, shield
fern, ironwood
Sum of the coverage >
2x’s the sum of species
In right box
trailing arbutus, bear
berry, reindeer moss
hazelnut, false
Soloman’s seal,
barren strawberry
AQVib
PMV
QAE
AQV

13. Examples of WI Habitat Types
Epigaea:
Vaccinium angustifolium
Maianthemum canadense:
Viburnum acerfolium (maple-leaf viburnum):
Osmorihza:
coptis_goldenthread:

14. Examples of WI Habitat Types
Maianthemum
Coptis
Sweet anise/osmorhiza

15. Habitat Types: Comparisons in WI
Litterfall C and N generally increase from low quality to high quality habitat type
For more general information about specific habitat types please feel free to check the website listed below.

16. Habitat Types Advantages Disadvantages Fairly detailed
Qualitative formulae
Disadvantages
May take some time to identify the factors in the stand

17. Site Productivity: Indirect Measurement Approaches
5) Environmental Relationships/factors
Simple relationships between one of more variable and tree growth.
from E.C. Steinbrenner Forest soil productivity relationships. In Forest Soils of the Douglas-fir Region).

18. Environmental relationships/factors cont..
from E.C. Steinbrenner Forest soil productivity relationships.
In Forest Soils of the Douglas-fir Region).

19. Environmental relationships/factors cont..
ANPP
Leaf biomass

20. Site Productivity: Indirect Measurement Approaches
6) Ecosystem Process Models
based on biophysical and ecological principles
every physiological process model has some level of empiricism

21. PPT evaporation LAI transpiration LAI Soil water Soil water outflow
General Outline for the conceptual framework of biome-BGC
PPT
evaporation
LAI
transpiration
LAI
Soil water
photosynthesis
Soil water
outflow
respiration

22. Remember our radiation lecture?
We can see in this figure that red is strongly absorbed by vegetation and infra red is strongly reflected.

23. Site Productivity: Indirect Measurement Approaches
7) Remote Sensing
Common Vegetation indices derived from radiation reflectance measured using satellites
Simple ratio = (near infra-red(NIR)/red (R) wavelength)
Normalized Difference Vegetation Index
(NDVI)= (NIR - R)/(NIR + R)

24. Site Productivity: Indirect Measurement Approaches
7) Remote Sensing
Normalized Difference Vegetation Index
(NDVI)= (NIR - R)/(NIR + R)
See Tom’s book about this a bit more.

25. Remote Sensing: Global Classification of Vegetation

26. Predicted versus Measured LAI
What does ETM mean on this slide presentation?
Corn LAI= *CCIca R2=0.63
Soy LAI= *CCIsa R2=0.27
ETM+ predictions of Aug. LAI
Corn LAI= *CCIcj R2=0.61
Soy LAI= *CCIsj R2=0.58
ETM+ predictions of July LAI

27. RMSE=9.09 Slope=0.98 RMSE=1.19 Intercept=1.46 Slope=1.00 R=0.84
1:1
1:1
Canonical indices
ETM+ March, June
Canonical indices
ETM+ March, June

28. Generally how do you get the remote sensed values?

29. Modis GPP project GPP (gC m-2 d-1) = PAR * fAPAR * g Where:
PAR = from climate model
fAPAR = from MODIS reflectances
g ( gC MJ-1) = GPP / APAR
MODIS g from lookup table
Spatial Resolution is 1 km
Temporal Res. is 8-day mean

31. Remote Sensing Disturbance
- Disturbances are an important component of any forest ecosystem
- Disturbances have no effect on the C budget if the system is in
steady state
Fire frequency and extent has
increased 270% in recent decades
In Saskatchewan and Manitoba 98
1995
1989 81
50 km

32. Fire scar profiles taken from 2003 NDVI seasonal data.
Hudson Bay
2003 NDVI 3-date Composite
max leaf area
Fire date
leaf expansion
NDVI: normalized difference vegetation index. NDVI=(near infrared-vis)/ (near infrared + Vis)
snowmelt
2003 fire
Fire scar profiles taken from 2003 NDVI seasonal data.
Selected burn areas shown in image on the right.
2002 MODIS Image Manitoba-Saskatchewan