Presentation on theme: "Site Productivity and Land Classification Lecture 13: Forest Ecology 550."— Presentation transcript:
Site Productivity and Land Classification Lecture 13: Forest Ecology 550
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.
Site Productivity Definition – Sites potential to produce one or more natural resources – Sustainable – Manage for multiple resources
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..
Forest Productivity: Site Index Curve
Site index curves: Pros/cons Pros – 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
Site Productivity: indirect measurement approaches 2) Overstory tree species – Each species occupies its own niche
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
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
Site Productivity: Indirect measurement approaches 3) understory species – Other examples: Ephemerals often have a narrow ecological niche
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
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 Species on right rare or absent At least 2 present honeysuckle, twisted stalk, partridgeberry, yellow beadlilly, shield fern, ironwood Sum of the coverage > 2xs the sum of species In right box trailing arbutus, bear berry, reindeer moss hazelnut, false Solomans seal, barren strawberry AQVib PMV QAE AQV
Examples of WI Habitat Types
Maianthemum Sweet anise/osmorhiza Coptis
Habitat Types: Comparisons in WI Litterfall C and N generally increase from low quality to high quality habitat type
Habitat Types Advantages – Fairly detailed – Qualitative formulae Disadvantages – May take some time to identify the factors in the stand
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).
Environmental relationships/factors cont.. – from E.C. Steinbrenner Forest soil productivity relationships. – In Forest Soils of the Douglas-fir Region).
Site Productivity: Indirect Measurement Approaches 6) Ecosystem Process Models – based on biophysical and ecological principles – every physiological process model has some level of empiricism
PPT LAI evaporation Soil water outflow transpiration photosynthesis respiration LAI General Outline for the conceptual framework of biome-BGC
Remember our radiation lecture?
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)
Site Productivity: Indirect Measurement Approaches 7) Remote Sensing – Normalized Difference Vegetation Index (NDVI)= (NIR - R)/(NIR + R)
Remote Sensing: Global Classification of Vegetation
Predicted versus Measured LAI Corn LAI= *CCI cj R 2 =0.61 Soy LAI= *CCI sj R 2 =0.58 ETM+ predictions of July LAI Corn LAI= *CCI ca R 2 =0.63 Soy LAI= *CCI sa R 2 =0.27 ETM+ predictions of Aug. LAI
RMSE=9.09 Slope=0.98 Intercept=1.46 R=0.84 1:1 Canonical indices ETM+ March, June RMSE=1.19 Slope=1.00 Intercept=0.10 R=0.74 Canonical indices ETM+ March, June
Generally how do you get the remote sensed values?
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
Remote Sensing Disturbance km - 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
2002 MODIS Image Manitoba-Saskatchewan 2003 NDVI 3-date Composite Fire scar profiles taken from 2003 NDVI seasonal data. Selected burn areas shown in image on the right. snowmelt leaf expansion 2003 fire max leaf area Fire date Hudson Bay