L4 Flashcards
Ecosystem structure refers to:
- The biophysical architecture of an ecosystem
- LAI
- Canopy height
- Vegetation Density
- Clumping
- Affects FaPAR, gas and energy fluxes
Structural traits - Leaf area index
- The total one-sided (or one half of the total all-sided) green leaf per unit ground surface area
- If leaf cover covered all the of ground, LAI = 1
- > 1 = multiple layers of leaves
Why is LAI an important biological parameter?
- It defines the area that interacts with solar radiation and provides the remote sensing signal
- It is the surface responsible for carbon and water exchange with the atmosphere
- The greater the surface size the greater the gas and energy exchange
- Clumping also occurs naturally in vegetation and due to planting in rows etc
Ecosystem function
- The biological , geochemical and physical processes that occur within an ecosystem
- Productivity
- Decomposition
- Energy flows
- Nutrient cycling
Why us understanding ecosystem function important?
- Monitoring variation in ecosystem function is needed to understand how ecosystems respond to anthropogenic environmental variability
Remote sensing and process based models
- Quantifying plant traits that effect structure and function
- The structural, biochemical, physiological and phenological properties of plants regulate the growth and performance or fitness of plants and their ability to propagate or survive in diverse environments
Vegetation indices
- Serve as intermediaries in the assessment of various biochemical or structural traits
- % green cover
- Biomass
- Leaf area index (LAI)
- fAPAR
- Chlorophyll conc
- Land cover classification
- A vegetation index is a simple mathematical formula that gives one value
- Quantitative measure for the amount, structure and condition of vegetation
- Formed from combinations of two to several spectral bands that are added, divided or multiplied…..
Compounds lots of information into one number
Vegetation indices - theoretical basis
- Depends on structure and biochemistry of the leaf
- Green light is reflected back out from surface
- Red and blue light are absorbed for use in photosynthesis
- Strong infrared reflectivity and transmittance depending on interaction surface
- Understanding why wavelengths are absorbed and reflected is a way of quantifying plant traits based on reflection/ absorbtion
- Different amounts of light reflected at each wavelength
- Knowing what wavelengths of light are related to which leaf properties means we can create vegetation indices off a few bands
- 3 Different types of vegetation indices
The three applications of vegetation indices
- Indicators of seasonal and inter annual variations in vegetation (phenology)
- Change detection studies (human/climate)
- Tool for monitoring and mapping vegetation
Healthy vegetation has a high or low NDVI?
High
Bare rock has an NDVI of…?
Nearly 0
Snow produces what NDVI?
Negative
Clouds produce what NDVI…?
Low to negative values
Issues with using NDVI
- Saturates over dense vegetation (then plateaus)
- Want a linear relationship
- Because the red band saturates
- Doesn’t absorb more light
- Less information than original data
- Any factor that unevenly influences the red and NIR reflectance will influence the NDVI, such as atmospheric scattering, soil wetness
- Sensor band characteristics may differ, not standardised across sensors
- NDVI values may vary also according to vegetation species
Enhanced vegetation index
- Accounts for soil background effects
- Reduces both atmosphere and canopy background contamination
- Increased sensitivity at high biomass levels
Amazon vegetation seasonal analyses and land conversion effects on biologic activity
- Many patches
Simple ratio (SR)
- More linear
- Doesn’t saturate, keeps increasing
Biophysical products - LAI
- LAI values and simple ratio measured
- Then make a linear regression
- Statistically can link the two, fitted model can transform LAI to simple ratio
- Vegetation index to biophysical product
- Able to map LAI assuming regression is right and variability has been captured
Absorption features of leaf pigments
- Red and blue have the most absorption
- Each pigment has a different absorption feature
- Don’t see carotenoids until chlorophyll leaves
- Anthocyanin is a photoprotective pigment
- Knowing the location of these absorption features means we can quantify them
There are differences in the relationship between MTCI and chlorophyll content for different functional types
- Crop is much lower than evergreen needleleaf
- Makes a universal equation tricky to map traits using vegetation indices
- Plant functional type dependent
Problems with vegetation indices
- Influence of LAI and Background at the canopy level
- More than just chlorophyll content
Ecosystem function is made up of what type of drivers?
Abiotic drivers and Biotic drivers
Ecosystem function
Abiotic drivers
- Nutrient content
- Light
Biotic drivers
- Disturbance
- These influence biodiversity which effects ecosystem functioning
Integrating of remote sensing and in situ observations, experiments and models as tools to understand biodiversity in the Earth system
Plant traits can be used to:
- Quantify CO2 exchanges with the atmosphere
- Project how terrestrial CO2 exchanges will change in the future
- Need vegetation traits (from RS inputs) and met data
NDVI and physical processes
- NDVI is closely mapped in time to photosynthesis and transpiration
- Key trait driving photosynthesis
- Integrated NDVI values for different functional types for transpiration and photosynthesis
Plant communities with low NDVI had low transpiration and vice versa
Plant communities with low NDVI had … transpiration levels?
Low
Light use efficiency GPP modelling
- Amount of absorbed light is converted into plant productivity
- More light = more productivity
- More light absorbed governed by leaves on the tree
- GPP = PAR X FAPAR X LUE
- Models GPP using remote sensing
- Variations of this are still used based of LUE
Regional light-use efficiency model calculations
- Differences in latitude
What is another optional for modelling GPP?
Process based terrestrial biosphere modelling
Process based terrestrial biosphere modelling
- Other option for modelling GPP
- Data intensive
- Physics based model
- Smaller Parameters have to be inserted eg leaf nitrogen content etc on top of input variables eg LAI, air temp etc
- Different from plant functional types, should not be fixed as these values differ
Process-based terrestrial biosphere modelling P2
- Largest source of variability
- Vcmax: maximum rate of carboxylation (photosynthetic capability)
- Seasonal variation
Environmental drivers of photosynthesis
- Models can examine which drivers (listed below) are limiting or best for photosynthesis and where this is:
- Sunlight
- Temperature
- Water
- Area variation
Temporal variation in plant traits
Seasonal phenology’s can be modelled
- Growing season is longer - Very short at high latitudes - Longer at lower latitudes - Expected metrics can be calculated
Summary
- Analysis of remotely sensed data (ie through vegetation indices) can be used to characterise plant structural, biochemical and physiological traits that combine to give ecosystem structure
- Plant traits play a role in community assembly, characterising the distribution, spatial patterns, and seasonality of traits is crucial for improved prediction of biodiversity change and ecosystem responses to global change
- RS data, combined with models and other meteorological data provides the only means to ecosuystem functioning across large spatial and temporal scales
