1. What is Bushland Condition Monitoring?
What is it?
A standardized method to measure
1. Health / Condition in bushland
2. Changes in condition over time
What does it comprise?
1. A manual in 3 volumes
2. SABAT database (South Australian Biodiversity Assessment
Tool)
3. 1650 + sites to date across SA

2. What is Bushland Condition?
 healthy
 not fragmented
 functional
 self-sustaining
 not under threat
 providing habitat

3. How does it work?
• 30m x 30m quadrat - uses a quadrat to be representative of a
patch
• 10 Indicators - measures 10-15 aspects of vegetation (Vol. 1) -
converts raw data into indicator scores using simple
calculations (Vol. 1)
• Benchmarks - compares indicator scores against benchmarks,
specific for different vegetation types (Vol. 3)
• Condition Classes - Assigns indicator scores to 1 of 5 condition
classes from Very Poor – Excellent, on the basis of this
comparison

4. Method uses a 30m x 30m quadrat to be REPRESENTATIVE of the patch
But any patch usually comprises areas of
1. Dominant Condition
2. Better Condition
3. Worse Condition
4. Edges
So need to make a decision about which area/s to set up in
Which leads us back to considering the PURPOSE of the monitoring site
Representivity

5. PURPOSE OF MONITORING
3 main reasons for monitoring
1. Performance Monitoring (P)
Looking to see a change due to change in management
(weeding, fencing, grazing control)
2. Resource Condition Monitoring (R)
Looking for a snapshot of condition across a defined area /
vegetation type (random patch selection)
3. Community Engagement (E)
Looking to engage landholders with the ecological and
biodiversity value of their bushland patches

6. REPRESENTIVITY and PURPOSE
in selecting Site Location
• Performance monitoring
o looking for a part that will be affected by
the change in management
o that is most likely to show a change
o  a section in worse condition
• Resource Condition Monitoring
o want to be representative of most
vegetation in the patch
o in section of dominant condition for
the patch
• Community Engagement
o want to show vegetation in its best light
o in area of better condition for the patch
Site Selection Metadata
Whichever is chosen
(Dominant, Better, Worse)
RECORD which it is and
why it was chosen

7. Site Selection Metadata
EXTRAPOLATION CONFIDENCE
• Different management on neighbouring properties
• Ecological gradients – soil, aspect, slope, exposure, etc.
Extrapolation Metadata
• use SA vegetation mapping polygons
• assign extrapolation confidence to nearby patches as
high, moderate, low
• E.g. “the quadrat is representative of (better than
average / dominant/ worse than average) condition in
surrounding patches of to a distance of x km”

8. Monitoring Timing
TIMING
• 5 years
– Recommended maximum interval
between assessments
– Long term trends
• Yearly
– Yearly, medium and long term trends
• Twice a year
– Spring = maximum biomass and
diversity
– Autumn = minumum biomass and
diversity
– Seasonal, yearly, medium and long
term trends
• Re-assessments need to be
made in equivalent seasons
to be comparable

9. What are the BCM Indicators? (Volume 1)
1. Plant Species Diversity
2. Weed Abundance and Threat
3. Structural Diversity (A. ground cover, B. native life forms)
4. Regeneration
5. Tree and Shrub Health (dieback, lerp, mistletoe)
6. Tree Habitat Features (habitat value, hollows, logs)
7. Feral Animals
8. Total Grazing Pressure
9. Fauna Species Diversity
10. Bushland Degradation Risk

10. What are the benchmarks? (Volume 3)
• 10-15 benchmark communities for each NRM region
• Brings together many vegetation associations, sharing similar
characteristics in terms of structure, soils, rainfall, and
understorey species, under a smaller number of major
groupings
• Volume 3 – communities described, in terms of geography,
species, vegetation structure, soils, and benchmarks for the
10 indicators
• E.g. of benchmark table

11. The 10 Indicators – Methods and Scoring
• What is measured and how?
• How is the indicator score calculated?
• How is the condition class assigned?

12. Indicator 1. Plant Species Diversity
METHOD
• All plant species - record all plant species inside
quadrat, including weeds (use later)
• Overhanging plants - plant can be overhanging /
not rooted in quadrat
• Dead Plants - include dead plants if still attached
by roots to ground
• Mistletoe - don’t forget to look for
• Moss and Lichen – not included

13. Indicator 1. Plant Species Diversity
Method
• Start - start with obvious overstorey
and understorey species
• Microbotany - on your knees in a
corner get your eye in for ground
level / small understorey spp.
• Searching - make sure cover all
quadrat - walk around the edges of
quadrat in circular direction then
come back to centre
• Plant Refuges - Check bases of
trees, shrubs and rocks
• Working Names - Use for species
you don’t know “small, fuzzy
lanceloate opposite leaves”
• Collect specimens - Indicate
collected plants with © - press for
future reference
• Taxanomic uncertainty – write
“?” before genus or species name
to show not sure e.g. ?*Trifolium
sp., e.g. Austrostipa ?nodosa

14. Indicator 1. Plant Species Diversity
Method
• Weeds - write “*” in front of plant
name to indicate is weed e.g.
*Plantago lanceolata
Not sure if weed? write (U) next
to name / working name
• In addition, while searching
quadrat for species - take note of
the most abundant weeds, plus
regeneration and grazing of
native species (for later)

15. Indicator 1. Species Diversity
Indicator Score
Calclulation
• Add up the number of native
species
Deriving a Condition Rating
• Compare the score against the
benchmarks in the tables
• Spring species count  multiply
benchmarks x 20%
Some communities are expected to
have less species than others, even in
good condition
• E.g. Good condition for samphire
= 5 species vs heathy forest (24)
• E.g. Good condition in Heathy
forest in Autumn = 24 species
(Spring = 29)

16. Indicator 2. Weed Abundance and Threat
Method
• 5 most abundant - decide which are 5
most abundant inside quadrat
(abundance = % projective cover)
• Estimate %cover (projective cover =
shade caused by a light shining from
directly above, as a proportion of the
whole quadrat)
• Include dead plants - if they are still
attached to ground (e.g. annual
grasses, dried up herbs - not forming
litter yet).

17. Indicator 2. Weed Abundance and Threat
Calculating the Indictor Score
• Cover Ratings - assign %cover for
each species to a cover rating using
table
• Weed Threat Ratings - assign the
weed threat rating for the species
according to the table
• Individual Species Score = cover
rating x threat rating
• Site Score = sum for the 5 species
you have chosen
Deriving a condition rating
• Compare – against the
benchmarks in the table
• Assign – a condition class from
Very Poor to Excellent
Notes
• some vegetation communities are
more susceptible and/or resilient
to weeds than others
• e.g. SMLR 1 Heathy Woodlands:
Poor = 18 or more, while for SMLR
8 Samphire: Poor = 9

18. Indicator 2. Weed Abundance and Threat - Red Alert Weeds
Method
• High Threat Weeds = rating 3, 4, or
5
• Record presence/absence
• in quadrat
• in surrounding bushland patch
• elsewhere on property
• Remember to record as you drive to
site and walk to the bushland
Calculating Indicator Score
• Score for Quadrat = number of
species
• Score for Patch = number of
species (including quadrat)
• Score for Property = number of
species (including patch and
quadrat)
• Not benchmarked

19. Structural Diversity A – Ground Cover
Method
• Estimate %cover of ground cover
components
 Native
 Weed
 Litter
 Rock
 Moss, lichen, microphytic crust
 Bare Ground
• Imagine the mosaic – after quadrat
sawn off with a chainsaw at shoe-
sole height
• Trees and shrubs = cross-section of
stems
• Hanging foliage = resting on the
ground
• Moss and lichen - on rocks as well as
soil (record amount on each)
• Overlap – there may be some
overlap
• hard to tell layers apart
• real overlap e.g. litter on moss,
foliage on weed
• carpet / lino analogy
• accounting for overlap - add up
the total and see if you can
account for the overlap
• Bare Ground – is most important
component for calculating the score

20. Structural Diversity A – Ground Cover
Calculating the Score
• Cover Ratings non-bare components -
convert %cover for non-bare ground
components to a cover rating using
the table
• Sum non-bare cover ratings - for all
the non-bare components
• Cover Rating of Bare Ground - convert
%cover of bare ground to cover rating
using the table
• Site Score = add the sum of non-bare
and bare ratings together
Deriving a Condition Rating
• Compare Site Score – against the
benchmarks using the tables
• Assign a Condition Class - from Very
Poor to Excellent
Notes
• E.g. Coastal dune communities are
expected to have higher bare ground
than sclerophyll forests and
woodlands

21. Indicator3. Structural Diversity B – Native Life-forms
METHOD
• Estimate %cover - in each life-form
category (Volume 1)
• Cover Ratings – assign a cover rating
to each layer using the table
NOTES
• Group native species – in each layer
• Dead Plants – include dead plants if
still attached
• Flower Heads – included in height
• Current Life-form – not what it may
grow into
• “Tussocks” = sedges, rushes and
similar forms - non-grass, perennial,
mostly stiff blades – Juncus, Gahnia,
Dianella, Schoenus spp.
• Woody Herbs – counted as herbs e.g.
Vittadinia spp.
CALCULATING THE INDICATOR SCORE
• Site Score = sum of cover ratings
ASSIGNING A CONDITION CLASS
• Compare – the score against the
benchmarks for the vegetation
community and assign a condition rating
from Very Poor to Excellent
NOTES
• Some plant communities are expected
to have greater diversity of life-forms
than others
• E.g. Samphire: Good = 8
• Heathy Forest: Good = 15

22. Indicator4. Regeneration
METHOD
• Count Seedlings and Juveniles -
inside the quadrat for each native tree
shrub species
• Count Adults – for each species with
seedling or juvenile
• Count Number of height classes - for
each native tree and shrub species
NOTES
• Seedling -
Eucalypts: < 1m
Other tree species: <0.5m
Shrubs: <10cm (use judgement)
• Juvenile – smaller than adult + yet to
flower or fruit
• Very numerous - estimate
CALCULATING THE INDICATOR SCORE
• Site Score = number of native tree and
shrub species with either a seedling or
juvenile present
• Seedling Abundance – assign rating
using table and sum for site
• Juvenile Abundance – as above
ASSIGNING A CONDITION CLASS
• Compare – the score against the
benchmarks for the vegetation
community and assign a condition rating
from Very Poor to Excellent
NOTES
•
•

23. Indicator 5. Tree and Shrub Health
METHOD
• Tree Map - map the 10 nearest trees
to the corner post
• Inside or Outside Quadrat? both
• Measure distance - bearing – species -
number of trunks – girth at breast
height (GBH) (1.35m)
NOTES
• Which trees? – native, adult, from
species comprising the dominant
overstorey layer (tallest layer with
>5% cover)
• doesn’t have to be currently in upper
stratum, as long as is adult
• Alive or Dead (as long as still
attached by roots)
• Dead, snapped off trees - don’t
measure if no trunk at 1.35m (breast
height)
NOTES
• 1 tree or 2 trees? - if trunks touch above
ground = 1 tree

24. Indicator 5. Tree and Shrub Health – 1. Dieback
METHOD
• Estimate %Dieback for each of the 10
trees
• Apply dieback rating to each tree
using the table and diagrams
Dieback
• = % of canopy missing/dead due to ill
health
• View from all sides – to estimate
dieback
• From the tips (not density) imagine
branches have leaves all the way to
ends
• Lower branches – don’t count loss of
leaves on lowest branches
• Epicormic leaves - do count as
dieback
• Long Dead Branches? Judgement call
- dieback or possibly storm damage
CALCULATING THE INDICATOR SCORE
• Site Score = sum of individual dieback
ratings  10
ASSIGNING A CONDITION CLASS
• Compare – the score against the
benchmarks for the vegetation
community and assign a condition rating
from Very Poor to Excellent
NOTES
• Do different communities expect
different levels of dieback?
•
•

25. Indicator 5. Tree and Shrub Health – 2. Lerp Damage
METHOD
• Estimate % of leaves with Lerp
Damage for each of the 10 trees
• Assign Lerp Damage Rating to each
tree using the table and diagrams
Lerp Damage
• Datum = % of leaves with signs of
significant lerp damage (>10% of
individual leaf area?)
• Difficult to distinguish – Lerp may be
difficult to distinguish from other
forms of attack  estimate total % of
leaves with damage from any source.
• Use binoculars – and extrapolate from
a representative clump
• Check upper branches – older leaves
on lower branches have more
accumulated damage
CALCULATING THE INDICATOR SCORE
• Site Score = sum of individual dieback
ratings  10
ASSIGNING A CONDITION CLASS
• Compare – the score against the
benchmarks for the vegetation
community and assign a condition rating
from Very Poor to Excellent
NOTES
• Different species are more or less
susceptible to lerp

26. Indicator 5. Tree and Shrub Health – 3. Mistletoe
METHOD
• Count the number of mistletoe on
each of the 10 trees
• Assign a Mistletoe Rating to each tree
using the table
Mistletoe
• Alive or Dead? Count alive only
• Difficult to distinguish – Mistletoe
mimic their host
• Use binoculars
CALCULATING THE INDICATOR SCORE
• Site Score = sum of individual dieback
ratings  10
DERIVING A CONDITION CLASS
• Compare – the score against the
benchmarks for the vegetation
community and assign a condition rating
from Very Poor to Excellent
NOTES
• Species susceptibility – some species
are more susceptible to mistletoe

27. Indicator 6. Tree Habitat Value A. Tree Habitat Value
3 MEASURES
A. Tree Habitat Value
B. Tree Hollows
C. Fallen Trees and Logs
CALCULATING THE INDICATOR
SCORE
• Individual Tree Score = size
category rating + canopy
health rating + hollows rating
• Site Score = number of trees
with score >5
DERIVING A CONDITION CLASS
• Compare – the score against
the benchmarks for the
vegetation community and
assign a condition rating from
Very Poor to Excellent
NOTES
A. Tree Habitat Value
METHOD
• Measure the Girth
- at breast height (1.35m)
- multistems? – measure largest
- assign a size rating from the
table
• Assign a Canopy Health Rating –
- using the %dieback estimations
already done
• Hollows - search for hollows
and assign a hollow rating to
each tree using the table

28. Indicator 6. Tree Habitat Value B. Tree Hollows
3 MEASURES
A. Tree Habitat Value
B. Tree Hollows
C. Fallen Trees and Logs
CALCULATING THE INDICATOR SCORE
• Site Score = number of trees with a
hollow
DERIVING A CONDITION CLASS
• Compare – the score against the
benchmarks for the vegetation
community and assign a condition
rating from Very Poor to Excellent
NOTES
B. Tree Hollows
Rule of thumb – a hollow is useful
if you can fit your whole thumb
Fissures and Bark – if relatively
stable / permanent
METHOD
Record presence / absence of any
hollows in each of the 10 trees

29. Indicator 6. Tree Habitat Value C. Fallen Trees and Logs
3 MEASURES
A. Tree Habitat Value
B. Tree Hollows
C. Fallen Trees and Logs
CALCULATING THE INDICATOR SCORE
• Site Score = number of logs in the
quadrat
DERIVING A CONDITION CLASS
• Compare – the score against the
benchmarks for the vegetation
community and assign a condition
rating from Very Poor to Excellent
NOTES
• Minimum size criteria - Is the same
minumum size reasonable for mallee
as for woodland species?
C. Fallen Trees and Logs
• Not attached by roots
• Minimum size  10 cm wide at
widest point
• 1 log or 2 – judgement call - if
obviously detached from a larger
limb, count separately
• Weed species – include
METHOD
Record number of logs inside the
quadrat

30. Indicator 7. Feral Animal Abundance
CALCULATING THE INDICATOR SCORE
• Site Score = number of logs in the
quadrat
DERIVING A CONDITION CLASS
• Compare – the score against the
benchmarks for the vegetation
community and assign a condition
rating from Very Poor to Excellent
NOTES
• Minimum size criteria - Is the same
minumum size reasonable for mallee
as for woodland species?
METHOD
Record number of signs inside a 50m
radius of the centre of quadrat
• Vertebrates - include introduced
birds
• Main signs - dung, scratchings, dens
/ burrows, live animal
• Stock animals – include sheep,
goats, deer etc. if not mandated
• Kangaroos / Koalas – make a note,
but record separately

31. Indicator 8. Grazing Pressure
CALCULATING THE INDICATOR SCORE
• Individual Species Score = sum of
grazing ratings for that species
• Site Score = sum of grazing ratings for
all native species
DERIVING A CONDITION CLASS
• Compare – the score against the
benchmarks for the vegetation
community and assign a condition
rating from Very Poor to Excellent
NOTES
• Palatability – useful information can
also be obtained using information on
palatability of species, where known
3 Grazing Intensities - Light – Heavy -
Severe
METHOD
Record number of plants / percentage
of plant population grazed at each
level of intensity for each native
species
Assign a grazing rating – to each
instance of grazing using the table
• Native Species – all native species
including herbs / non woody species
• Total population size – record /
estimate this for the calculations
• Who is grazing? – doesn’t matter
whether native or introduced grazer
• Koala / Cocky grazing on upper
canopy – not included

32. Indicator 9. Fauna Species Diversity
CALCULATING THE INDICATOR SCORE
• Score = number of species
DERIVING A CONDITION CLASS
• Not benchmarked
NOTES
• This information is important to relate
vegetation condition with habitat
function
• Not benchmarked
• Cumulative
METHOD
• Record observations of native
animal species
• Vertebrate species only
• Collect - notes, photos, dung, and
other traces
NOTES
• Important to collect: date, time,
weather, location, behaviour

33. Indicator 10. Bushland Degradation Risk
CALCULATING THE INDICATOR SCORE
• Site Score = sum of ratings for A, B, C
and D
DERIVING A CONDITION CLASS
• Compare – the score against the
benchmarks (common to all
benchmark communities) and assign a
condition rating from Very Poor to
Excellent
NOTES
METHOD
Record information on
A. Size and Nature of Remnant
B. Shape of Remnant
C. Surrounding Land Use
D. Remnancy in Environmental
Association
Assign a ratings to these using the
tables
A. Size and Nature – desktop
• Boundary fences – patches end
at boundary fences
B. Shape – desktop
C. Land Use – field and desktop
D. Remnancy – Nature Maps
• Near edge of EA – use average

34. Visual %Cover Estimation
• Projective Cover = area of shade
caused by a light shining from directly
above, as a proportion of the whole
quadrat
• 2-step process – involves estimating
Extent and Density and then
multiplying them together
• %Extent = the fraction of the quadrat
covered by the sum of polygons
around the perimeters of canopies
• %Density = the fraction of shade
produced by the leaves and branches
within a typical plant canopy polygon
• %Cover = %Extend x %Density
Method %Extent
• Tetris - imagine stacking polygons of
canopies into a corner, tetris-style,
without compression
• Standard Corners – use diagrams of
standard corners of different
fractions of a 30m x 30m quadrat to
decide which corner they would fit
into
• Standard Area Diagrams – use
diagrams of standard areas 5%, 25%,
50% and 75% to estimate the cover
of canopies without compression
Method % density
• Look up (or down) through the
canopy and estimate the fraction of
shade made by the leaves under a
light shining directly from above.
• Revise and Cross-check against other
components etc. until you’re happy

35. Stepwise estimation
> or < 95% ?
> or < 90% ?
> or < 75% ?
> or < 50% ?
> or < 25% ?
> or < 5% ?
> or < 1% ?

36. Cover Diagrams

37. Estimating Cover – Pushing into a
Corner
30 m x 30 m square
1%
5%
10%
25%
50%
3m
3m
7m
7m
10m
10m
30 m
30 m
3 m x 3 m square in a 30 m x 30 m square
0.1%
0.5%
1m 2m
3m
1%
3m
2m
1m
30 cm
30 cm
.01%

38. Cover Calculation Matrix
0% 1% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100%
1% 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1
5% 0 0 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 5 5 5
10% 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10
15% 0 1 2 2 3 4 5 5 6 7 8 8 9 10 11 11 12 13 14 14 15
20% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
25% 0 1 3 4 5 6 8 9 10 11 13 14 15 16 18 19 20 21 23 24 25
30% 0 2 3 5 6 8 9 11 12 14 15 17 18 20 21 23 24 26 27 29 30
35% 0 2 4 5 7 9 11 12 14 16 18 19 21 23 25 26 28 30 32 33 35
40% 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
45% 0 2 5 7 9 11 14 16 18 20 23 25 27 29 32 34 36 38 41 43 45
50% 1 3 5 8 10 13 15 18 20 23 25 28 30 33 35 38 40 43 45 48 50
55% 1 3 6 8 11 14 17 19 22 25 28 30 33 36 39 41 44 47 50 52 55
60% 1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60
65% 1 3 7 10 13 16 20 23 26 29 33 36 39 42 46 49 52 55 59 62 65
70% 1 4 7 11 14 18 21 25 28 32 35 39 42 46 49 53 56 60 63 67 70
75% 1 4 8 11 15 19 23 26 30 34 38 41 45 49 53 56 60 64 68 71 75
80% 1 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80
85% 1 4 9 13 17 21 26 30 34 38 43 47 51 55 60 64 68 72 77 81 85
90% 1 5 9 14 18 23 27 32 36 41 45 50 54 59 63 68 72 77 81 86 90
95% 1 5 10 14 19 24 29 33 38 43 48 52 57 62 67 71 76 81 86 90 95
100% 1 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
PercentofQuadratCoveredbyCanopies
Percent of Canopies covered by leaves and branches

39. E.G. Estimating Canopy Cover
Quadrat Covered by Canopies Outlines
461 m2
461 m2 / 900 m2 = 51%
Canopies Covered by Leaves and
Branches
45%
• Overall Cover
• 45% x 51%
• = 23% = ‘sparse’
Quadrat = 900 m2

40. Step 0 – Assigning a Benchmark Vegetation Community
Notes
 Current vegetation
association – may be
significantly different to the
pre-European state
 Pre-European or other
target – pre-European may
not always be the most
desirable, or practical target
for management
Method
• Current Formation - is it
significantly modified or
relatively unmodified
• Understorey – is it significantly
modified or relatively unmodified
• Volume 3 – use the decision tree
and chapter descriptions to
determine which one is
appropriate

41. 2. Forests and Woodlands with an Open
sclerophyll Shrub Understorey – Benchmark
Scores
Indicator Very Poor Poor Moderate Good Excellent
1. Species Diversity < 6 6 - 12 13 - 20 21 - 30 31+
2. Weed Abundance &
Threat
> 28 19 - 28 13 - 18 8 - 12 < 8
3. Structural Diversity A -
Ground Cover
< 0 0 1 - 2 3 4
3. Structural Diversity B –
Plant Life Forms
< 6 6 - 8 9 - 13 14 - 18 19+
4. Regeneration – Trees 0 1 2 3 4+
4. Regeneration Trees &
Woody Shrubs
0 1 2 - 3 4 - 5 6+
5. Tree Health – Dieback < –4 -4 to –1.1 -1.0 to 0.9 1 to 2.5 > 2.5
5. Tree Health - Lerp -4 to -1.6 -1.5 to 0.4 0.5 to 1.9 2 to 3 > 3
5. Tree Health - Mistletoe < -3 -3 to –2.1 -2 to –0.6 -0.5 to 0.4 > 0.5
6. Tree Habitat Score 0 - 1 2 - 3 4 - 6 7 - 8 9 - 10
6. Tree Hollow Score 0 1 2 - 4 5 - 6 7+
6. Fallen Trees and Logs 0 1 2 3 4+
7. Feral Animal Abundance > 7 5.1 - 7 2.1 - 5 1.1 - 2 0 - 1
7. Feral Animal Frequency < -22 -22 to -16 -15 to –11 -10 to –5 -4 to 0
8. Total Grazing Pressure < -17 -17 to –10 -9 to -5 -4 to -1 0

42. Site Establishment
Equipment
 2 Star Droppers
 aerial photo
 3 x 60m tapes
 camera
 compass
 binoculars
 Dressmakers measuring tape
First Steps
 select site for quadrat
 permanently mark and
photograph
 describe the bushland
patch

43. 1 - Setting up
Quadrat
Size
 30m x 30m
 any configuration of 900m2
Orientation
 NSEW is standard
 corner post (star dropper) – one of northern corners (photo considerations)
 photo post (star dropper) – 10 m from corner looking into middle of quadrat (45o
to one side)
Location
 Representative
 Non-edge
Recording
Non-standard set-up is permissible, all details being carefully recorded

44. Site Naming Convention
e.g. B U R – M C K B – B – 2
• Part 1 _ _ _ = 1st 3 letters of nearest
town or gazzetted locality (e.g. Burra)
• Part 2 _ _ _ _ = 1st 3 letters of
landowner’s surname + landowner’s
first initial (Brian McKeough)
• Part 3 _ = letter A, B, C… assigned to
each separate patch of bushland on a
property (2nd patch with a monitoring
site on this property)
• Part 4 _ = number 1, 2, 3… assigned
to each successive quadrat set up in a
patch (2nd quadrat set up in this
patch)
• Roadside: Part 2 _ _ _ _ = 1st 4
letters of road name
• Reserves: Part 2 _ _ _ _ = 1st 2
letters of reserve name + initials
of park status e.g. CP

45. Step 2 – Setting up Photopoints
METHOD
• Set up quadrat with a view to a good
photo
• Camera-post = cnr stake
• Sighter post = 10m @ 45o (or other
good sightline)
• Record distance and bearing, height
of camera / camera post and sighter
post
• Photo - focus and centre on the site-
board
• Quadrat edges – also take photos
down edges to show orientation of
quadrat for re-assessments
• Re-assessments - similar time of day
= similar light conditions.

46. Step 3 - Bushland Description
Describing the patch / sub-
patch
= the area of which the
quadrat is a representative
sample
1. Vegetation Structure
2. Landscape Description
3. Disturbance History
A. Vegetation Structure
South Australian Vegetation Classification
System  structural formation
Uses:
1. Life form of the tallest layer (e.g.
tree, shrub)
2. Ave. height of the tallest layer
3. % Cover of the tallest layer
METHOD
Dominant stratum - identify the tallest
layer with cover  5%
Average Height – estimate the ave. ht of
plants that belong to this stratum
%Cover – estimate the average %
projective cover in the patch / sub-patch

47. 3 - Bushland Description
A. Vegetation Structure
South Australian Vegetation Classification
System  structural formation
Uses:
1. Life form of the tallest layer (e.g.
tree, shrub)
2. Ave. height of the tallest layer
3. % Cover of the tallest layer
METHOD
Dominant stratum - identify the tallest
layer with cover  5%
Average Height – estimate the ave. ht of
plants that belong to this stratum
%Cover – estimate the average %
projective cover in the patch / sub-patch
Determining the structural formation
Using the combination of 1, 2, and 3 and
the table, assign the patch a vegetation
formation
Notes
• Average %cover in patch maybe
different to %cover in quadrat
• weeds may comprise part of the
dominant stratum
• Benchmark Community – current
formation may not correspond to
assigned Benchmark Community due
to disturbance

48. Vegetation Formations in South Australia
LIFEFORM/
HEIGHTCLASS
PROJECTIVEFOLIAGECOVEROFTALLESTSTRATUM
Dense (70 – 100%) Mid-dense (30 – 70%) Sparse (10 – 30%) Very Sparse (<10%)
Trees> 30m Tall closedforest Tall openforest Tall woodland Tall openwoodland
Trees10– 30m Closedforest Openforest Woodland Openwoodland
Trees5– 10m Lowclosedforest Lowopenforest Lowwoodland Lowopenwoodland
Trees<5m Verylowclosedforest Verylowopenforest Verylowwoodland Verylowopenwoodland
Mallee> 3m Closedmallee Mallee Openmallee Veryopenmallee
Mallee< 3m Closedlowmallee Lowmallee Openlowmallee Veryopenlowmallee
Shrubs> 2m Tall closedshrubland Tall shrubland Tall openshrubland Tall veryopenshrubland
Shrubs1– 2m Closedshrubland Shrubland Openshrubland Veryopenshrubland
Shrubs< 1m Lowclosedshrubland Lowshrubland Lowopenshrubland Lowveryopenshrubland
Grasses Closedgrassland Grassland Opengrassland Veryopengrassland
Sedges Closedsedgeland Sedgeland Opensedgeland Veryopensedgeland

49. Cover Calculation Matrix
0% 1% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100%
1% 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1
5% 0 0 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 5 5 5
10% 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10
15% 0 1 2 2 3 4 5 5 6 7 8 8 9 10 11 11 12 13 14 14 15
20% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
25% 0 1 3 4 5 6 8 9 10 11 13 14 15 16 18 19 20 21 23 24 25
30% 0 2 3 5 6 8 9 11 12 14 15 17 18 20 21 23 24 26 27 29 30
35% 0 2 4 5 7 9 11 12 14 16 18 19 21 23 25 26 28 30 32 33 35
40% 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
45% 0 2 5 7 9 11 14 16 18 20 23 25 27 29 32 34 36 38 41 43 45
50% 1 3 5 8 10 13 15 18 20 23 25 28 30 33 35 38 40 43 45 48 50
55% 1 3 6 8 11 14 17 19 22 25 28 30 33 36 39 41 44 47 50 52 55
60% 1 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60
65% 1 3 7 10 13 16 20 23 26 29 33 36 39 42 46 49 52 55 59 62 65
70% 1 4 7 11 14 18 21 25 28 32 35 39 42 46 49 53 56 60 63 67 70
75% 1 4 8 11 15 19 23 26 30 34 38 41 45 49 53 56 60 64 68 71 75
80% 1 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80
85% 1 4 9 13 17 21 26 30 34 38 43 47 51 55 60 64 68 72 77 81 85
90% 1 5 9 14 18 23 27 32 36 41 45 50 54 59 63 68 72 77 81 86 90
95% 1 5 10 14 19 24 29 33 38 43 48 52 57 62 67 71 76 81 86 90 95
100% 1 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
PercentofQuadratCoveredbyCanopies
Percent of Canopies covered by leaves and branches

50. Part B: Landscape Description
Slope (circle any of the following in the Assessment Area)
Relatively flat land, slope < 50 Moderately steep, slope 50– 200
Steep hillside, slope > 200
Landform (circle any in Assessment Area)
Flat/plain Valley bottom Ridge-top Hill slope Swamp
Creekline River Floodplain Sand dune Inter-dune Swale
Soil type (Tick one)
Mainly Sand Sandy-loam Mainly Loam Clay-loam Mainly
Clay Other: Ironstone
(fine texture, water penetrates rapidly)
(high moisture holding capacity)
Assessment Site Landscape (use the descriptive words above to
describe landscape for each assessment site)
Assessment Site No. 1 On mod –steep slope in scrub, thin sandy loam over ironstone
ridge.
Assessment Site No. 2 In Gully, mainly sandy loam with sparse ironstone.
How does this assessment area vary from other areas of bush?

51. 3. Bushland Description
B. Landscape Description
• Slope
is the ground at head height = 20m away ? slope 5o
is the ground at head height = 5m away ? slope 20o
• Aspect = useful information (which direction would a ball
roll ?)
• Soil
o is it sand, loam, clay, clay-loam ?
o what colour is it ? yellow, brown, red, grey, black ?
o are there rocks ? are they outcropping-like ? or strew-like ?

52. 3. Bushland Description
C. Disturbance History
• Past Land-use
• Current Land Use
• Fire History
• Tree Clearance
• Understorey Clearance