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Ecosystems and sustainability in a changing world > L4 > Flashcards

L4 Flashcards

1
Q

Ecosystem structure refers to:

A
  • The biophysical architecture of an ecosystem
    • LAI
    • Canopy height
    • Vegetation Density
    • Clumping
    • Affects FaPAR, gas and energy fluxes
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2
Q

Structural traits - Leaf area index

A
  • 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
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3
Q

Why is LAI an important biological parameter?

A
  • 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
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4
Q

Ecosystem function

A
  • The biological , geochemical and physical processes that occur within an ecosystem
    • Productivity
    • Decomposition
    • Energy flows
    • Nutrient cycling
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5
Q

Why us understanding ecosystem function important?

A
  • Monitoring variation in ecosystem function is needed to understand how ecosystems respond to anthropogenic environmental variability
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6
Q

Remote sensing and process based models

A
  • 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
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7
Q

Vegetation indices

A
  • 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

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8
Q

Vegetation indices - theoretical basis

A
  • 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
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9
Q

The three applications of vegetation indices

A
  • Indicators of seasonal and inter annual variations in vegetation (phenology)
    • Change detection studies (human/climate)
    • Tool for monitoring and mapping vegetation
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10
Q

Healthy vegetation has a high or low NDVI?

A

High

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11
Q

Bare rock has an NDVI of…?

A

Nearly 0

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12
Q

Snow produces what NDVI?

A

Negative

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13
Q

Clouds produce what NDVI…?

A

Low to negative values

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14
Q

Issues with using NDVI

A
  • 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
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15
Q

Enhanced vegetation index

A
  • 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
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16
Q

Simple ratio (SR)

A
  • More linear
    • Doesn’t saturate, keeps increasing
17
Q

Biophysical products - LAI

A
  • 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
18
Q

Absorption features of leaf pigments

A
  • 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
19
Q

There are differences in the relationship between MTCI and chlorophyll content for different functional types

A
  • Crop is much lower than evergreen needleleaf
    • Makes a universal equation tricky to map traits using vegetation indices
    • Plant functional type dependent
20
Q

Problems with vegetation indices

A
  • Influence of LAI and Background at the canopy level
    • More than just chlorophyll content
21
Q

Ecosystem function is made up of what type of drivers?

A

Abiotic drivers and Biotic drivers

22
Q

Ecosystem function

A

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

23
Q

Plant traits can be used to:

A
  • 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
24
Q

NDVI and physical processes

A
  • 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

25
Q

Plant communities with low NDVI had … transpiration levels?

A

Low

26
Q

Light use efficiency GPP modelling

A
  • 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
27
Q

Regional light-use efficiency model calculations

A
  • Differences in latitude
28
Q

What is another optional for modelling GPP?

A

Process based terrestrial biosphere modelling

29
Q

Process based terrestrial biosphere modelling

A
  • 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
30
Q

Process-based terrestrial biosphere modelling P2

A
  • Largest source of variability
    • Vcmax: maximum rate of carboxylation (photosynthetic capability)
    • Seasonal variation
31
Q

Environmental drivers of photosynthesis

A
  • Models can examine which drivers (listed below) are limiting or best for photosynthesis and where this is:
    • Sunlight
    • Temperature
    • Water
    • Area variation
32
Q

Temporal variation in plant traits

A

Seasonal phenology’s can be modelled

- Growing season is longer

- Very short at high latitudes

- Longer at lower latitudes

- Expected metrics can be calculated
33
Q

Summary

A
  • 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

Ecosystems and sustainability in a changing world (21 decks)

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