The presentation by Richard Thackway discusses tracking changes in land use and vegetation condition, emphasizing the importance of land management practices on biodiversity and ecological functions. It presents the VAST-2 methodology, case studies, and frameworks for assessing vegetation condition and transformation over time, highlighting the diverse land uses in Australia and their impacts. Finally, it outlines future directions for scaling up monitoring and engaging land managers to improve ecological outcomes.

1. Tracking change in land use and
vegetation condition
Richard Thackway
Presentation to Department of Agriculture, Fisheries and Forestry, Canberra
22 May 2013

2. Outline
• Concepts and definitions
• Current status of national data and information
• VAST-2 methodology
• Case studies
• Lessons
• Where to from here?
• More information

3. Regulation ofhydrologicalregime
Generation offood and fibre
Regulation ofclimate / microclimate
Generation ofraw materials
Recyclingoforganic matter
Creating and regulatinghabitats
Controllingreproductionand dispersal
Changing ecological function to derive multiple benefits (ecosystem services)

4. Models of ecosystem change i.e. cause & effect
Source: Adamson and Fox (1982)
Time
Changeinvegetationindicator
Settlement
10000
Reference

5. 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
Models of ecosystem change i.e. cause & effect
Changeinvegetationindicator

6. The big questions for tracking change
IF
land management practices are the CAUSE of observed and
measured EFFECTS* i.e. changes in veg condition over time
THEN
• How can we make sense over time of
– Land use change?
– The plethora and diversity of LMPs?
– The effects of these LMP on veg?
* Noting interactions with climatic drivers i.e. natural dynamics

7. Present land use type & extent
Source: DAFF 2008

8. Present land use
Source: DAFF 2008
1. Dryland livestock grazing (58%)
2. Minimal use (15%)
3. Other protected areas including indigenous use (13%)
4. Nature conservation (6.9%)
5. Dryland agriculture (3.1%)
6. Timber production (2.0%)
7. Water (1.8%)
8. Irrigated agriculture (0.4%)
9. Intensive uses (0.3%)

9. Regional changes in land use over time
Source: ABARES 2010
• Mainly intensification of agricultural production
• Some conversion to conservation and minimal use

10. Present land use
1. Dryland livestock grazing (58%)
2. Minimal use (15%)
3. Other protected areas including indigenous use (13%)
4. Nature conservation (6.9%)
5. Dryland agriculture (3.1%)
6. Timber production (2.0%)
7. Water (1.8%)
8. Irrigated agriculture (0.4%)
9. Intensive uses (0.3%)
Source: DAFF 2008
These 5 land uses utilise native veg ~90%
of area of Australia – BUT what are their
effects on native vegetation condition?

11. Present vegetation type & extent
Source: DAFF 2008

12. Present vegetation
1. Shrublands and heathlands (37%)
2. Grasslands & minimally modified pastures (33%)
3. Forests and woodlands (19%)
4. Annual crops and highly modified pastures (9%)
5. Other non-native vegetation (1.7%)
6. Plantations (0.2%) and
7. Horticultural trees and shrubs (0.1%).
Source: DAFF 2008

13. Present vegetation
1. Shrublands and heathlands (37%)
2. Grasslands & minimally modified pastures (34%)
3. Forests and woodlands (19%)
4. Annual crops and highly modified pastures (8%)
5. Plantations (0.2%) and
6. Horticultural trees and shrubs (0.1%).
Source: DAFF 2008
These 3 native veg types cover ~90% of
area of Australia – BUT how can we assess
change and trend in condition?

14. Snapshots of gross change in extent of native
veg types
Pre-European
Present or
extantMVG and NVIS
Source: SEWPAC
Conversion from native to non-
native and non-vegetated due
to land use change

15. Reporting change
in condition using
Veg type
(NVIS/MVG)
Pre-European and
Present vegetation
Source: ABARES 2013
Veg type
Naracoorte
Coastal Plain
bioregion
NVIS: National Vegetation Information System
MVG: Major Vegetation Groups
Region: Naracoorte Coastal Plain

16. Drivers for information on changes in
vegetation condition?
Public and private interests
• NRM & Forest policy and program design e.g. biodiversity and
sustainability
• Assessing resource condition e.g. degradation and resilence
• Monitoring and reporting and improvement e.g. SoE & SOFR,
environmental accounting
Wider community interests
• Educators, researchers, students …

17. What is condition and transformation?
• 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 can be assessed relative to fully
natural a reference state
Vegetation condition

18. 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 compiling & 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

19. Vegetation condition – a snapshot
Thackway & Lesslie (2008)
Environmental Management, 42, 572-90
NB: Input dataset biophysical naturalness reclassified using
VAST framework
/ replaced
/ unmodified

20. Reporting
change in
condition
using veg
type
(NVIS/MVG),
and
vegetation
condition
(VAST)
Source: ABARES 2013
Veg type
Veg type
NVIS: National Vegetation Information System
MVG: Major Vegetation Groups

21. The big questions for tracking change
IF
land management practices are the CAUSE of observed and
measured EFFECTS* i.e. changes in veg condition over time
THEN
• How can we make sense over time of
– Land use change?
– The plethora and diversity of LMPs?
– The effects of these LMP on veg?
* Noting interactions with climatic drivers i.e. natural dynamics

22. VAST framework = Effects
• VAST classifies and orders the magnitude and intensity of LMP
• VAST gives clues re how to classify targets for action into core set of
vegetation condition indicators that affected by LMPs
LUMIS framework = Cause
• LUMIS classifies all LMP into focal themes:
– Vegetation/plants, soil, landform, water, animal, air
• LUMIS classifies all vegetation-related LMPs into five objectives:
1. Establish and rehabilitate
2. Improve and maintain growth and condition
3. Harvest plant products and remove waste and weeds
4. Monitor health, vitality and condition
5. No activity or interventions
Links between VAST and LUMIS
LUMIS = Land Use and Management Information System

23. TARGET of
action
Purpose of ACTIVITY
eg. establish, maintain, remove,
protect, monitor
Management PRACTICE category
Specific ACTION by manager
METHOD used to undertake the activity
eg. select, control, handle, legislate, sample
Business,
Infrastructure
Vegetation/
plants, animals,
soil, water, air
Level 5
Level 4
Level 3
Level 2
Level 1
Source: ACLUMP ABARES (Land Use and Information Management System (LUMIS) 2010
Making sense of land management practices

24. Focus on what the land manager is doing
that effect veg condition
TARGET of action
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
Soil
Vegetation
LUMIS
PURPOSE of activity is to

25. Focus on what the land manager is doing
Soil
Vegetation
Regenerative capacity/
function / processes - VAST
Vegetation structure &
Species composition - VAST
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
LUMIS
PURPOSE of activity is to

26. Define goal
/target or
purpose
Do it
Assess the
situation and
context
Recognise an
opportunity /
problem
Choose a
method/
practice
Change and
trend are not
acceptable
Direction of
change and
trend is
acceptable
Sources of
information
Citizen science
Making sense of land manager activities

27. 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
Models of ecosystem change i.e. cause & effect
Changeinvegetationindicator

28. Aim of VAST-2
Indigenous
land
management
First
explorers
Grazing
Degreeof
modification
Logging
Cropping
Site 1
Site 2
Site 3
Time
Reference state
Long
term
rainfall
Long term
disturbance
e.g. wildfire,
cyclones
Revegetation
VAST
classes
Cell /pulse grazing

29. VAST-2 System
Tracking change in vegetation condition

30. Condition
components (3)
[VAST]
Attribute groups
(10)
[LUMIS]
Description of loss or gain relative to pre settlement indicator reference state
(22)
Regenerativecapacity
Fire regime Area /size of fire foot prints
Number of fire starts
Soil hydrology Soil surface water availability
Ground water availability
Soil physical
state
Depth of the A horizon
Soil structure
Soil nutrient
state
Nutrient stress – rundown (deficiency) relative to soil fertility
Nutrient stress – excess (toxicity) relative to soil fertility
Soil biological
state
Recyclers responsible for maintaining soil porosity and nutrient recycling
Surface organic matter, soil crusts
Reproductive
potential
Reproductive potential of overstorey structuring species
Reproductive potential of understorey structuring species
Vegetation
structure
Overstorey
structure
Overstorey top height (mean) of the plant community
Overstorey foliage projective cover (mean) of the plant community
Overstorey structural diversity (i.e. a diversity of age classes) of the stand
Understorey
structure
Understorey top height (mean) of the plant community
Understorey ground cover (mean) of the plant community
Understorey structural diversity (i.e. a diversity of age classes) of the plant
Species
Composition
Overstorey
composition
Densities of overstorey species functional groups
Relative number of overstorey species (richness) of indigenous to exotic species
Understorey
composition
Densities of understorey species functional groups
Relative number of understorey species (richness) of indigenous to exotic species

31. 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

32. 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

33. • Network of collaborators
• Ecologists, academics, land managers, environmental historians,
educators
• Inputs
• Reference state
• Land use
• Land management practices
• Natural events e.g. droughts, fires, floods, cyclones, average rainfall
1900-2013 etc
• Observed interactions e.g. rabbits, sheep and drought
• Observations and quantitative measures of effects of management
practices:
• Include written, oral, artistic, photographic, survey plots and remote sensing
Resources needed to compile and analyse
an historical record for each site

34. 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

35. 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

36. Method: VAST-2
LU = Land Use, LMP = Land Management Practices
Effects on indicators of VAST
diagnostic attributes
Time
Cause

37. Filling in the gaps in effects at the site level
Quadrat or pixel
Land unit
Land system
Sub-bioregion
Bioregion
Certainty
levels
Coarse
Fine
Low
Low
Medium
Medium
High
Sources of
information
Granularity of
information

38. Certainty level standards used to
compile historic record
Certainty
level
standards
Spatial precision
(Scale)
Temporal precision
(Year of observation)
Attribute accuracy
(Land use, land
management practices,
effects on condition)
HIGH
"Definite”
Reliable direct
quantitative data.
Code: 1
Reliable direct
quantitative data.
Code: 4
Reliable direct
quantitative data.
Code: 7
MEDIUM
"Probable
"
Direct (with
qualifications) or strong
indirect data.
Code: 2
Direct (with
qualifications) or strong
indirect data.
Code: 5
Direct (with
qualifications) or strong
indirect data.
Code: 8
LOW
"Possible"
Limited qualitative and
possibly contradictory
observations. More
data needed.
Code: 3
Limited qualitative and
possibly contradictory
observations. More
data needed.
Code: 6
Limited qualitative and
possibly contradictory
observations. More
data needed.
Code: 9

39. Year Source
Year and
reliability
LU & LMP Source:
LU & LMP
Reliability
of LMP
sources and
spatial
accuracy
Effects of use and land
management practices on
structure, composition
and function
Source
Effects
Reliability
of effects
and spatial
accuracy
1800
1840
2013
Pre-contact
First contact
Current year
LU = Land Use, LMP = Land Management Practices
Results: VAST-2 historical record

40. Case studies VAST-2

41. Case studies 1 and 2
• Region:
Credo Station, Great Western Woodlands (GWW), WA
• Reference state:
Salmon Gum woodland overstorey , saltbush and
bluebush understorey and ground layer

42. Photo: Harry Recher
Salmon Gum reference state

45. Case studies 3 and 4
Region:
Taroom Shire, Brigalow Belt South, Qld
Reference state:
Brigalow woodland overstorey , mixed open
shrubland understorey , grassy and forb ground layer

46. Photo: Griffith University
Brigalow woodland reference state

47. Potters Flat, Taroom Shire, Qld

48. Wanaringa, Taroom Shire, Qld

49. VAST/VAST-2 is a useful tool for:
• Understanding and reporting the effects of agricultural and
forest management practices on native vegetation
• Evaluating a site’s potential to be restored under different
social-ecological conditions e.g. 20% forest canopy cover
• Assisting land managers understand relationships between:
– natural dynamic cycles, degrees of disturbance/change, management
interventions and changes in ecological function that underpin
ecosystem services

50. Potential effects of land use change and
management at paired sites
Observed / measured
change due to land
management
Observed / measured
change due to other
causes including natural
processes
VAST-2transformationindex
100
80
60
40
20
0
time now time n +
Production forestry continues unchanged
Change from production forestry to conservation
Reference

51. Where to next?
• More sites
• Scaling up to the landscape scale
• Modelling the transformation of landscapes
– Historical
– Current
– Future

52. Sources of information to populate indicators
View 3D imagery
Potential to derive information on tree
heights, tree crown size and depth,
strata, regeneration

53. Scaling up from sites to landscape levels
Static layers
•first contact by European explorers
•slope & relief derived from 30m DEM
•aspect classes derived from 30m DEM
•weathering layer
•digital atlas of soils+
•pre-European vegetation types (NVIS)
Time series response variables
•rainfall anomaly (post 1900)
•state-wide & national land tenure
•Remote sensing (FPC, fire, bare ground)*
•native veg (tree) layers*
•state-wide & national land use
• sheep DSE
• cattle DSE
• cropping
• urban areas
• Plantations
• nature conservation reserves
• indigenous protected areas
•Infrastructure
• railways
• roads
•fire regime (fire area & No. fire starts)*
•other
TERN AusCover*
TERN Soils+

54. Conclusions
• Vegetation condition is dynamic and can be tracked
• Plant communities are not static nor irreparable
• Vegetated landscapes can be altered, maintained in a modified
state, restored ... as management preferences change
• As a national system VAST-2 has value for:
– Engaging land managers as citizen scientists
– Synthesizing information (quantitative and qualitative)
– Examining interactions between natural dynamics /disturbance and
land management
– ‘Telling the story’ of vegetation condition and transformation

55. More information
http://www.vasttransformations.com/
Acknowledgements
• University of Queensland, Department of Geography Planning and Environmental
Management for ongoing research support
• TERN ACEAS funded my sabbatical fellowship at the University of Queensland,
Brisbane in 2010-11
• CSIRO Ecosystems Sciences for hosting me as a visiting research scientist, Canberra
in 2010-11
• Many public and private land managers, land management agencies, consultants
and researchers have provided data and information