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Using VAST to inform the development
regional environmental accounts
Richard Thackway
Regional Environmental Accounts Technical Workshop, ABS House, Belconnen, ACT
24-25 June, 2013
Outline
• Concepts and definitions
• What is VAST
• VAST-2 methodology
• VAST-2 case studies
• Potential to use VAST for regional accounts
• Where to from here?
• More information
VAST = Vegetation Assets States and Transitions
Land managers affect native veg condition
Process:
Land managers use land management practices (LMP) to
influence ecological function at sites and the landscape by:
• Modifying
• Removing and replacing
• Enhancing
• Restoring
• Maintaining
• Improving
Purpose/s:
To achieve the desired mix of ecosystem services (space & time)
VAST focuses on affects of land management on
plant communities
Soil
Vegetation
Regenerative capacity/ function
Vegetation structure &
Species composition
1. Soil hydrological status
2. Soil physical status
3. Soil chemical status
4. Soil biological status
5. Fire regime
6. Reproductive potential
7. Overstorey structure
8. Understorey structure
9. Overstorey composition
10. Understorey composition
LMP are used to influence
Condition and transformation - VAST
• Change in a plant community (type) due to effects of land
management practices:
– Structure
– Composition
– Regenerative capacity
• Transformation = changes to vegetation condition over time
• Condition and transformation are assessed relative to fully
natural a reference state
Vegetation condition
Occupation
Relaxation
Anthropogenic change
Net impact
Time
1800 1850 1900 1950 2000
Based on Hamilton, Brown & Nolan 2008. FWPA PRO7.1050. pg 18
Land use impacts on biodiversity and Life Cycle Analysis
Reference
Model of ecosystem change i.e. cause & effectChangeinvegetation
indicatorodindex
Vegetation Assets States and Transitions (VAST) framework
VIVIVIIIIII0
Native vegetation
cover
Non-native vegetation
cover
Increasing modification caused by use and management
Transitions = trend
Vegetation
thresholds
Reference for
each veg type
(NVIS)
VAST - A framework for assessing & reporting
vegetation condition
Condition states
Residual or
unmodified
Naturally
bare
Modified Transformed Replaced -
Adventive
Replaced -
managed
Replaced -
removed
Thackway & Lesslie (2008) Environmental
Management, 42, 572-90
Diagnostic attributes of VAST states:
• Vegetation structure
• Species composition
• Regenerative capacity
NVIS
Current datasets are snapshots but not time series
Thackway & Lesslie (2008)
Environmental Management, 42, 572-90
NB: Input dataset biophysical naturalness reclassified using
VAST framework
/ replaced
/ unmodified
VAST 2009
Veg condition derived
from classifying &
mapping effects of land
management practices
Native
VAST-2 System*
Tracking change in vegetation condition
* Thackway 2012 – VAST-2 handbook
Condition
components (3)
[VAST]
Attribute groups
(10)
[LUMIS]
Description of loss or gain relative to pre settlement indicator reference state
(22)
Regenerativecapacity Fire regime 1. Area /size of fire foot prints
2. Number of fire starts
Soil hydrology 3. Soil surface water availability
4. Ground water availability
Soil physical
state
5. Depth of the A horizon
6. Soil structure
Soil nutrient
state
7. Nutrient stress – rundown (deficiency) relative to soil fertility
8. Nutrient stress – excess (toxicity) relative to soil fertility
Soil biological
state
9. Recyclers responsible for maintaining soil porosity and nutrient recycling
10. Surface organic matter, soil crusts
Reproductive
potential
11. Reproductive potential of overstorey structuring species
12. Reproductive potential of understorey structuring species
Vegetation
structure
Overstorey
structure
13. Overstorey top height (mean) of the plant community
14. Overstorey foliage projective cover (mean) of the plant community
15. Overstorey structural diversity (i.e. a diversity of age classes) of the stand
Understorey
structure
16. Understorey top height (mean) of the plant community
17. Understorey ground cover (mean) of the plant community
18. Understorey structural diversity (i.e. a diversity of age classes) of the plant
Species
Composition
Overstorey
composition
19. Densities of overstorey species functional groups
20. Relative number of overstorey species (richness) of indigenous :exotic spp
Understorey
composition
21. Densities of understorey species functional groups
22. Relative number of understorey species (richness) of indigenous :exotic spp
1
3
10
22
Diagnostic
attributes
Vegetation
Transformation
score
Attribute
groups
Vegetation
Structure
(27%)
Overstorey
(3)
Understorey
(3)
Species
Composition
(18%)
(2)
UnderstoreyOverstorey
(2)
Regenerative
Capacity
(55%)
Fire
(2)
Reprod
potent
(2)
Soil
Hydrology
(2)
Biology
(2)
Nutrients
(2)
Structure
(2) Indicators
VAST-2 hierarchy
Step 7
Add the indices for the three components to generate total transformation
index for the ‘transformation site’ for each year of the historical record .
Validate using Expert Knowledge
Step 1a
Use a checklist of 22 indicators to compile
changes in LU & LMP* and plant
community responses over time
Transformation site
Step 1c
Evaluate impacts on the plant community
over time
Step 1b
Evaluate the influence of climate, soil and
landform on the historical record
Step 2
Document responses of 22
indicators over time
Step 4
Document the reference
states for 22 indicators
Step 3a
Literature review to determine the
baseline conditions for 22 indicators
Step 3c
Compile indicator data for 22
indicators for reference site
Step 3b
Evaluate the influence of climate, soil
and landform for the reference site
Reference state/sites
Step 5
Score all 22 indicators for ‘transformation site’ relative to the
‘reference site’. 0 = major change; 1 = no change
Step 6
Derive weighted indices for the three components for the ‘transformation
site’ i.e. regenerative capacity (58%), vegetation structure (27%) and
species composition (18%) by adding predefined indicators
General process for tracking changes
VAST-2 system
* LU Land use
LMP Land management practices
Importance of dynamics
Rainfall assumed to be main driver of system dynamics
• Period 1900 - 2013
• Average seasonal rainfall (summer, autumn, …)
• Rainfall anomaly is calculated above and below the mean
• Two year running trend line fitted
NB: Must calibrate remote sensing to account for dynamics
• e.g ground cover, greenness and foliage projective cover
WA Wheatbelt
BOM rainfall
anomaly
1900-2010
(modelled 5 km
resolution)
Derived from
monthly
modelled
rainfall data
obtained from
http://www.lon
gpaddock.qld.go
v.au/silo/
Rainfall
anomaly
relative to
mean
Case studies VAST-2
Case study 1
• Region:
Credo Station, Great Western Woodlands
(GWW), WA
• Reference state:
Salmon Gum woodland overstorey , saltbush &
bluebush understorey and ground layer
More info: http://www.vasttransformations.com/
Photo: Harry Recher
Salmon Gum reference state
Case study 2
Region:
Taroom Shire, Brigalow Belt South, Qld
Reference state:
Brigalow woodland overstorey , mixed open
shrubland understorey , grassy and forb ground
layer
More info: http://www.vasttransformations.com/
Photo: Griffith University
Brigalow woodland reference state
Wanaringa, Taroom Shire, Qld
VASTclasses
Potential to use VAST-2 to produce whole
landscape regional accounts
Potential to use VAST-2 for
whole landscape accounting
Integrated ecological classification (algorithm)
• Scores and weights
• Enables meaningful simplified reporting over time
Relevant ecological indicators (22)
• Indicators designed to target key national datasets incl. several time series
Historical site-based records a basis for modeling &
validating
• Using GIS and remote sensing
• Reference state
List of VAST-2 indicators (22)
Best source
spatial data
Time series or
modeled
Year/ RS source
1. Area /size of fire foot prints TERN AusCover Time series (RS) >2000 MODIS
2. Number of fire starts TERN AusCover Time series (RS) >2000 MODIS
3. Soil surface water availability CSIRO Modeled epochs NA
4. Ground water availability GA & CSIRO Modeled epochs NA
5. Depth of the A horizon CSIRO Modeled epochs NA
6. Soil structure CSIRO Modeled epochs NA
7. Nutrient stress – rundown (deficiency) relative to soil fertility CSIRO Modeled epochs NA
8. Nutrient stress – excess (toxicity) relative to soil fertility CSIRO Modeled epochs NA
9. Recyclers responsible for maintaining soil porosity and nutrient recycling ?? Modeled epochs NA
10. Surface organic matter, soil crusts CSIRO Modeled epochs NA
11. Reproductive potential of overstorey structuring species CSIRO Modeled epochs NA
12. Reproductive potential of understorey structuring species CSIRO Modeled epochs NA
13. Overstorey top height (mean) of the plant community TERN AusCover Snap shot (RS) 2009 Alos/Landsat/
ICESAT
14. Overstorey foliage projective cover (mean) of the plant community TERN AusCover Time series (RS) 2000-10 Landsat
15. Overstorey structural diversity (i.e. a diversity of age classes) of the stand TERN AusCover Snap shot (RS) 2009 Alos/Landsat/
ICESAT
16. Understorey top height (mean) of the plant community TERN AusCover Snap shot (RS) 2009 Alos/Landsat/
ICESAT
17. Understorey ground cover (mean) of plant community (fractional cover) TERN AusCover Time series (RS) 2000-10 Landsat
18. Understorey structural diversity (i.e. a diversity of age classes) of the plant CSIRO Modeled epochs NA
19. Densities of overstorey species functional groups (biomass) CSIRO Modeled epochs NA
20. Relative number of overstorey species (richness) of indigenous :exotic spp CSIRO Modeled epochs NA
21. Densities of understorey species functional groups (biomass) CSIRO Modeled epochs NA
22. Relative number of understorey species (richness) of indigenous :exotic spp CSIRO Modeled epochs NA
Monitoring Burnt Area and Approximate Day of Burn
VAST-2 indicators 1 & 2
http://data.auscover.org.au/xwiki/bin/view/Product+pages/BurntArea+DoB+MODIS+CDU
0
20
40
60
80
100
1985 1990 1995 2000 2005 2010
Year
FPC
Monitoring Foliage Projective Cover
VAST-2 indicator 14
Source: Tim Danaher
Overstorey height, cover & structural types
VAST-2 indicators 13, 14 & 15
Source: Peter ScarthPolygons based on Landsat FPC (persistent green) and Allos radar backscatter at 25m
Vertical structure from IceSat . Mantuan Downs, Qld
1988 1991 1993
1995
2003 2004
20011999
Monitoring Ground Cover
VAST-2 indicator 17
Source: Tim Danaher
What about info for the other indicators?
• Most info for these indicators are not dynamic e.g.
– Most regenerative capacity indicators will require
models rather than remote sensing
– Most species composition indicators will require expert
elicitation modeling of site data
Conclusions (1)
• VAST is a useful accounting tool for tracking change and
trend in the condition of vegetated landscapes –
– Change is due to use and management
0
1
2
3
4
5
6
7
1750 1800 1850 1900 1950 2000 2050
X, Y Tas Midlands
0
1
2
3
4
5
6
7
1750 1800 1850 1900 1950 2000 2050
X, Y Tas Midlands
0
1
2
3
4
5
6
7
1750 1800 1850 1900 1950 2000 2050
X, Y Tas Midlands
0
1
2
3
4
5
6
7
1750 1800 1850 1900 1950 2000 2050
X, Y Tas Midlands
0
1
2
3
4
5
6
7
1750 1800 1850 1900 1950 2000 2050
X, Y Tas Midlands
0
1
2
3
4
5
6
7
1750 1800 1850 1900 1950 2000 2050
X, Y Tas Midlands
0
2
4
6
1750 1800 1850 1900 1950 2000 2050
X, Y Tas Midlands
0
2
4
6
1750 1800 1850 1900 1950 2000 2050
X, Y Tas Midlands
Potential transformations
We can do this at sites
1962 1983 1986 1997 2004
250 hectare ‘Talaheni’, Murrumbateman, NSW
We can monitor veg condition across small
areas e.g. propertiesVAST states
Reporting condition states ‘Talaheni’
0
50
100
150
200
250
300
1962 1983 1986 1997 2004
Year of VAST assessment
hectares
2
31
32
33
5
6
VAST states
2009
Source: http://app.monitor.abares.gov.au/map.html
Legend
2012
2014
We cannot annualize monitoring of veg
condition whole landscapes
Removed managed
Removed replaced
/unmodified
VAST states
Conclusions (2)
• VAST also has value for:
– Synthesizing information (quantitative and qualitative)
– ‘Telling the story’ of landscape transformation
– Engaging land managers and ecologists as equal players
VAST helps in ‘telling the story’
Residual/ unmodified
Modified
Transformed
Adventive
Replaced and
managed
Replaced /removed
Organ Pipes National Park –
ex cropping paddock
Trajectories of
vegetation status
and VAST classes
reflect choices
and drivers
VAST
classes
More information
http://www.vasttransformations.com/
http://portal.tern.org.au/search
http://aceas-data.science.uq.edu.au/portal/
Acknowledgements
• University of Queensland, Department of Geography Planning and
Environmental Management for ongoing research support
• Many public and private land managers, land management
agencies, consultants and researchers have provided data and information

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Using VAST to inform the development regional environmental accounts

  • 1. Using VAST to inform the development regional environmental accounts Richard Thackway Regional Environmental Accounts Technical Workshop, ABS House, Belconnen, ACT 24-25 June, 2013
  • 2. Outline • Concepts and definitions • What is VAST • VAST-2 methodology • VAST-2 case studies • Potential to use VAST for regional accounts • Where to from here? • More information VAST = Vegetation Assets States and Transitions
  • 3. Land managers affect native veg condition Process: Land managers use land management practices (LMP) to influence ecological function at sites and the landscape by: • Modifying • Removing and replacing • Enhancing • Restoring • Maintaining • Improving Purpose/s: To achieve the desired mix of ecosystem services (space & time)
  • 4. VAST focuses on affects of land management on plant communities Soil Vegetation Regenerative capacity/ function Vegetation structure & Species composition 1. Soil hydrological status 2. Soil physical status 3. Soil chemical status 4. Soil biological status 5. Fire regime 6. Reproductive potential 7. Overstorey structure 8. Understorey structure 9. Overstorey composition 10. Understorey composition LMP are used to influence
  • 5. Condition and transformation - VAST • Change in a plant community (type) due to effects of land management practices: – Structure – Composition – Regenerative capacity • Transformation = changes to vegetation condition over time • Condition and transformation are assessed relative to fully natural a reference state Vegetation condition
  • 6. Occupation Relaxation Anthropogenic change Net impact Time 1800 1850 1900 1950 2000 Based on Hamilton, Brown & Nolan 2008. FWPA PRO7.1050. pg 18 Land use impacts on biodiversity and Life Cycle Analysis Reference Model of ecosystem change i.e. cause & effectChangeinvegetation indicatorodindex
  • 7. Vegetation Assets States and Transitions (VAST) framework VIVIVIIIIII0 Native vegetation cover Non-native vegetation cover Increasing modification caused by use and management Transitions = trend Vegetation thresholds Reference for each veg type (NVIS) VAST - A framework for assessing & reporting vegetation condition Condition states Residual or unmodified Naturally bare Modified Transformed Replaced - Adventive Replaced - managed Replaced - removed Thackway & Lesslie (2008) Environmental Management, 42, 572-90 Diagnostic attributes of VAST states: • Vegetation structure • Species composition • Regenerative capacity NVIS
  • 8. Current datasets are snapshots but not time series Thackway & Lesslie (2008) Environmental Management, 42, 572-90 NB: Input dataset biophysical naturalness reclassified using VAST framework / replaced / unmodified VAST 2009 Veg condition derived from classifying & mapping effects of land management practices Native
  • 9. VAST-2 System* Tracking change in vegetation condition * Thackway 2012 – VAST-2 handbook
  • 10. Condition components (3) [VAST] Attribute groups (10) [LUMIS] Description of loss or gain relative to pre settlement indicator reference state (22) Regenerativecapacity Fire regime 1. Area /size of fire foot prints 2. Number of fire starts Soil hydrology 3. Soil surface water availability 4. Ground water availability Soil physical state 5. Depth of the A horizon 6. Soil structure Soil nutrient state 7. Nutrient stress – rundown (deficiency) relative to soil fertility 8. Nutrient stress – excess (toxicity) relative to soil fertility Soil biological state 9. Recyclers responsible for maintaining soil porosity and nutrient recycling 10. Surface organic matter, soil crusts Reproductive potential 11. Reproductive potential of overstorey structuring species 12. Reproductive potential of understorey structuring species Vegetation structure Overstorey structure 13. Overstorey top height (mean) of the plant community 14. Overstorey foliage projective cover (mean) of the plant community 15. Overstorey structural diversity (i.e. a diversity of age classes) of the stand Understorey structure 16. Understorey top height (mean) of the plant community 17. Understorey ground cover (mean) of the plant community 18. Understorey structural diversity (i.e. a diversity of age classes) of the plant Species Composition Overstorey composition 19. Densities of overstorey species functional groups 20. Relative number of overstorey species (richness) of indigenous :exotic spp Understorey composition 21. Densities of understorey species functional groups 22. Relative number of understorey species (richness) of indigenous :exotic spp
  • 12. Step 7 Add the indices for the three components to generate total transformation index for the ‘transformation site’ for each year of the historical record . Validate using Expert Knowledge Step 1a Use a checklist of 22 indicators to compile changes in LU & LMP* and plant community responses over time Transformation site Step 1c Evaluate impacts on the plant community over time Step 1b Evaluate the influence of climate, soil and landform on the historical record Step 2 Document responses of 22 indicators over time Step 4 Document the reference states for 22 indicators Step 3a Literature review to determine the baseline conditions for 22 indicators Step 3c Compile indicator data for 22 indicators for reference site Step 3b Evaluate the influence of climate, soil and landform for the reference site Reference state/sites Step 5 Score all 22 indicators for ‘transformation site’ relative to the ‘reference site’. 0 = major change; 1 = no change Step 6 Derive weighted indices for the three components for the ‘transformation site’ i.e. regenerative capacity (58%), vegetation structure (27%) and species composition (18%) by adding predefined indicators General process for tracking changes VAST-2 system * LU Land use LMP Land management practices
  • 13. Importance of dynamics Rainfall assumed to be main driver of system dynamics • Period 1900 - 2013 • Average seasonal rainfall (summer, autumn, …) • Rainfall anomaly is calculated above and below the mean • Two year running trend line fitted NB: Must calibrate remote sensing to account for dynamics • e.g ground cover, greenness and foliage projective cover
  • 14. WA Wheatbelt BOM rainfall anomaly 1900-2010 (modelled 5 km resolution) Derived from monthly modelled rainfall data obtained from http://www.lon gpaddock.qld.go v.au/silo/ Rainfall anomaly relative to mean
  • 16. Case study 1 • Region: Credo Station, Great Western Woodlands (GWW), WA • Reference state: Salmon Gum woodland overstorey , saltbush & bluebush understorey and ground layer More info: http://www.vasttransformations.com/
  • 17. Photo: Harry Recher Salmon Gum reference state
  • 18.
  • 19. Case study 2 Region: Taroom Shire, Brigalow Belt South, Qld Reference state: Brigalow woodland overstorey , mixed open shrubland understorey , grassy and forb ground layer More info: http://www.vasttransformations.com/
  • 20. Photo: Griffith University Brigalow woodland reference state
  • 21. Wanaringa, Taroom Shire, Qld VASTclasses
  • 22. Potential to use VAST-2 to produce whole landscape regional accounts
  • 23. Potential to use VAST-2 for whole landscape accounting Integrated ecological classification (algorithm) • Scores and weights • Enables meaningful simplified reporting over time Relevant ecological indicators (22) • Indicators designed to target key national datasets incl. several time series Historical site-based records a basis for modeling & validating • Using GIS and remote sensing • Reference state
  • 24. List of VAST-2 indicators (22) Best source spatial data Time series or modeled Year/ RS source 1. Area /size of fire foot prints TERN AusCover Time series (RS) >2000 MODIS 2. Number of fire starts TERN AusCover Time series (RS) >2000 MODIS 3. Soil surface water availability CSIRO Modeled epochs NA 4. Ground water availability GA & CSIRO Modeled epochs NA 5. Depth of the A horizon CSIRO Modeled epochs NA 6. Soil structure CSIRO Modeled epochs NA 7. Nutrient stress – rundown (deficiency) relative to soil fertility CSIRO Modeled epochs NA 8. Nutrient stress – excess (toxicity) relative to soil fertility CSIRO Modeled epochs NA 9. Recyclers responsible for maintaining soil porosity and nutrient recycling ?? Modeled epochs NA 10. Surface organic matter, soil crusts CSIRO Modeled epochs NA 11. Reproductive potential of overstorey structuring species CSIRO Modeled epochs NA 12. Reproductive potential of understorey structuring species CSIRO Modeled epochs NA 13. Overstorey top height (mean) of the plant community TERN AusCover Snap shot (RS) 2009 Alos/Landsat/ ICESAT 14. Overstorey foliage projective cover (mean) of the plant community TERN AusCover Time series (RS) 2000-10 Landsat 15. Overstorey structural diversity (i.e. a diversity of age classes) of the stand TERN AusCover Snap shot (RS) 2009 Alos/Landsat/ ICESAT 16. Understorey top height (mean) of the plant community TERN AusCover Snap shot (RS) 2009 Alos/Landsat/ ICESAT 17. Understorey ground cover (mean) of plant community (fractional cover) TERN AusCover Time series (RS) 2000-10 Landsat 18. Understorey structural diversity (i.e. a diversity of age classes) of the plant CSIRO Modeled epochs NA 19. Densities of overstorey species functional groups (biomass) CSIRO Modeled epochs NA 20. Relative number of overstorey species (richness) of indigenous :exotic spp CSIRO Modeled epochs NA 21. Densities of understorey species functional groups (biomass) CSIRO Modeled epochs NA 22. Relative number of understorey species (richness) of indigenous :exotic spp CSIRO Modeled epochs NA
  • 25. Monitoring Burnt Area and Approximate Day of Burn VAST-2 indicators 1 & 2 http://data.auscover.org.au/xwiki/bin/view/Product+pages/BurntArea+DoB+MODIS+CDU
  • 26. 0 20 40 60 80 100 1985 1990 1995 2000 2005 2010 Year FPC Monitoring Foliage Projective Cover VAST-2 indicator 14 Source: Tim Danaher
  • 27. Overstorey height, cover & structural types VAST-2 indicators 13, 14 & 15 Source: Peter ScarthPolygons based on Landsat FPC (persistent green) and Allos radar backscatter at 25m Vertical structure from IceSat . Mantuan Downs, Qld
  • 28. 1988 1991 1993 1995 2003 2004 20011999 Monitoring Ground Cover VAST-2 indicator 17 Source: Tim Danaher
  • 29. What about info for the other indicators? • Most info for these indicators are not dynamic e.g. – Most regenerative capacity indicators will require models rather than remote sensing – Most species composition indicators will require expert elicitation modeling of site data
  • 30. Conclusions (1) • VAST is a useful accounting tool for tracking change and trend in the condition of vegetated landscapes – – Change is due to use and management
  • 31. 0 1 2 3 4 5 6 7 1750 1800 1850 1900 1950 2000 2050 X, Y Tas Midlands 0 1 2 3 4 5 6 7 1750 1800 1850 1900 1950 2000 2050 X, Y Tas Midlands 0 1 2 3 4 5 6 7 1750 1800 1850 1900 1950 2000 2050 X, Y Tas Midlands 0 1 2 3 4 5 6 7 1750 1800 1850 1900 1950 2000 2050 X, Y Tas Midlands 0 1 2 3 4 5 6 7 1750 1800 1850 1900 1950 2000 2050 X, Y Tas Midlands 0 1 2 3 4 5 6 7 1750 1800 1850 1900 1950 2000 2050 X, Y Tas Midlands 0 2 4 6 1750 1800 1850 1900 1950 2000 2050 X, Y Tas Midlands 0 2 4 6 1750 1800 1850 1900 1950 2000 2050 X, Y Tas Midlands Potential transformations We can do this at sites
  • 32. 1962 1983 1986 1997 2004 250 hectare ‘Talaheni’, Murrumbateman, NSW We can monitor veg condition across small areas e.g. propertiesVAST states
  • 33. Reporting condition states ‘Talaheni’ 0 50 100 150 200 250 300 1962 1983 1986 1997 2004 Year of VAST assessment hectares 2 31 32 33 5 6 VAST states
  • 34. 2009 Source: http://app.monitor.abares.gov.au/map.html Legend 2012 2014 We cannot annualize monitoring of veg condition whole landscapes Removed managed Removed replaced /unmodified VAST states
  • 35. Conclusions (2) • VAST also has value for: – Synthesizing information (quantitative and qualitative) – ‘Telling the story’ of landscape transformation – Engaging land managers and ecologists as equal players
  • 36. VAST helps in ‘telling the story’ Residual/ unmodified Modified Transformed Adventive Replaced and managed Replaced /removed Organ Pipes National Park – ex cropping paddock Trajectories of vegetation status and VAST classes reflect choices and drivers VAST classes
  • 37. More information http://www.vasttransformations.com/ http://portal.tern.org.au/search http://aceas-data.science.uq.edu.au/portal/ Acknowledgements • University of Queensland, Department of Geography Planning and Environmental Management for ongoing research support • Many public and private land managers, land management agencies, consultants and researchers have provided data and information