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Bushland Condition
Monitoring
Nature Conservation Society of SA
Why assess vegetation condition?
• inform decision making- knowledge of vegetation
condition needed at multiple scales for decision
making and prioritisation
• report on outcomes- condition monitoring needed
to report on outcomes from management actions
and investments
• understanding of causal links- improved
understanding needed of causal links between
threats, management actions and vegetation
condition
Trade-offs
expertise
number of sites
data type
technical resources required
magnitude of change detected
huge tiny
time & cost
extravagantshoe
string
absolutely
anyone
trained
expert
subjective
0 ∞
objective
readily
available
IT junkie
Considerations when designing
BCM methodology
Develop a method that:
• provides land managers with feedback relating to the impact of
management action and threats
• can be implemented by NRM practitioners, community members and land
managers, without the need for high level scientific research expertise
• reports on multiple vegetation condition parameters
• allows flexibility to be applied at multiple spatial scales
• requires minimal time, resources and equipment to implement whilst
retaining value of data collected
• is complementary to existing datasets and survey methodology
• has the ability to detect an appropriate degree of difference in vegetation
condition to inform NRM decisions and investment allocation and to report
on the outcomes of investment
BCM methodology
• Uses repeat measures to assess change over time
• Well defined & permanently marked assessment site
• Measurements largely based on 30 x 30m quadrat chosen
to be representative of the bushland area being assessed
• Produces an individual score for each parameter or
indicator
• Parameter scores can be compared to Vegetation
Community Benchmarks
• Provides instant feedback/interpretation of assessment
• Intensive 2 day training is required
• ~2hrs-1/2 day per site
Indicators assessed
1. Plant Species Diversity
2. Weed Abundance and Threat
3. Structural Diversity – Ground Cover & Plant Life
Forms
4. Regeneration
5. Tree & Shrub Health
6. Tree Habitat Features
7. Feral Animals
8. Total Grazing Pressure
9. Fauna Species Diversity
10. Bushland Degradation Risk
Vegetation Community Benchmarks
• Values obtained for each indicator dependent on
both condition and the vegetation type being
assessed
• Vegetation Communities are based on groups of
Vegetation Associations with similar structure and
composition of vegetation
• Comparison of field data to benchmark values for a
particular community type thus allows for expected
variation in indicators as a result of belonging to
that vegetation community
• At the site scale, there is quick feedback of results
that do not require further analysis
Current status
BCM used for biodiversity assessments in:
Upper South East Biodiversity Trading, BushBids (eastern MLR)
Candlebark woodlands (MLR), Bush for Life, On-ground works
assessment (NY NRM region)
Approximately 1500 sites established
375 people trained
Manuals published:
Southern Mt Lofty Ranges
Southern Mt Lofty Ranges Coastal
Northern Agricultural and Yorke Peninsula regions
Eyre Peninsula and SA Murray-Darling Basin manuals published by
Summer 08/09
Existing
SABAT/
BCM sites
Testing the methodology
Trial to gain insights into surveyor consistency as well as the ability of
surveyors to detect differences between different sites.
This would provide an indication of the ability of the BCM method to detect
real change at a site, as compared to change that may be due to the
skill or bias of different observers.
Five different practitioners who had been trained by NCSSA and had been
using the BCMM in field situations independently scored four different
sites that had been marked out within an area of the Waite Reserve in
the Adelaide Hills.
Each site belonged to a similar vegetation association (Eucalyptus
camaldulensis/Eucalyptus leucoxylon woodland) but sites were chosen
to represent different condition classes in the poor to moderate range
Mean species richness scores for five
observers
0
5
10
15
20
1 2 3 4
Site number
SpeciesRichness
AverageScore(+-SD)
Mean structural diversity scores for
five observers
0
2
4
6
8
10
12
1 2 3 4
Site number
StructuralDiversity
PlantLifeForms
score(+-SD)
Power to detect change in tree health
Degree of Change in Tree Health
Number of Trees
Scored
Low (10% change in
tree health)
High (30% change)
10 63% 85%
40 75% 98%
Table 1: Predicted power of tree health data to detect change
(Note that α = β as discussed by Field et al 2007)
Compatibility with state and
transition models
• BCM does not assume a linear model for condition
trajectories (measuring multiple parameters)
• 5 condition classes in 11 indicators allows for 511
possible condition states (approx 50 million)
• Data collected could inform development and
refinement of state and transition models (eg
BushBids predicted versus real response)
Prolonged Domestic Grazing has
led to:
Moderate species diversity,
Moderate weed abundance & threat,
Poor structural diversity, Lack of
regeneration of woody trees &
shrubs, High total grazing pressure
Reduced domestic grazing leads to:
Higher weed abundance and threat
Due to lack of competition:
An increase in grazing feral animals
Other Associated Consequences:
Loss of species diversity
Reduction of structural diversity
Protection from grazing leads to:
Increased species diversity
Lower total grazing pressure
Regeneration of woody perennials
Increased structural diversity
Increased ground cover
Intended application of Bushland Condition Monitoring Tool
Detect condition change over time, investigate causal factors, link to management regime
Comparison of condition information from 2
sites
Value of site based information
• site based data needed to build and support
predictive spatial modeling
• site based data forms a foundation for
expert opinion
• collection of site based data can contribute
to building capacity of land managers and
community
• guides investment decisions
• used to report on outcomes
BCM was not designed to
• provide information relating to the autecology of a
species eg:
• spatial or temporal information on individual
species abundance
• species interactions
BCM provides quantified measure and interpretation
of universally accepted biodiversity surrogates that
allows for valid comparison in these surrogates
spatially or temporally
SABAT/Bushland Condition
Monitoring Database
Species Diversity/
Richness Score
Indicator Rating
Weed Abundance
and Threat Score
Indicator Rating
Structural
Diversity Plant
Life Forms Score
Indicator Rating
Tree and Shrub
Regeneration
Score Indicator
Rating
Total Grazing
Pressure Score
Indicator Rating
Tree Hollow
Score Indicator
Rating
Tree Health -
Dieback Score
Indicator Rating
Tree Health -
Mistletoe Score
Indicator Rating
Tree Habitat
Value Score
Indicator Rating

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Ncssa bcm-vegetation condition monitoring workshop

  • 2. Why assess vegetation condition? • inform decision making- knowledge of vegetation condition needed at multiple scales for decision making and prioritisation • report on outcomes- condition monitoring needed to report on outcomes from management actions and investments • understanding of causal links- improved understanding needed of causal links between threats, management actions and vegetation condition
  • 3. Trade-offs expertise number of sites data type technical resources required magnitude of change detected huge tiny time & cost extravagantshoe string absolutely anyone trained expert subjective 0 ∞ objective readily available IT junkie
  • 4. Considerations when designing BCM methodology Develop a method that: • provides land managers with feedback relating to the impact of management action and threats • can be implemented by NRM practitioners, community members and land managers, without the need for high level scientific research expertise • reports on multiple vegetation condition parameters • allows flexibility to be applied at multiple spatial scales • requires minimal time, resources and equipment to implement whilst retaining value of data collected • is complementary to existing datasets and survey methodology • has the ability to detect an appropriate degree of difference in vegetation condition to inform NRM decisions and investment allocation and to report on the outcomes of investment
  • 5. BCM methodology • Uses repeat measures to assess change over time • Well defined & permanently marked assessment site • Measurements largely based on 30 x 30m quadrat chosen to be representative of the bushland area being assessed • Produces an individual score for each parameter or indicator • Parameter scores can be compared to Vegetation Community Benchmarks • Provides instant feedback/interpretation of assessment • Intensive 2 day training is required • ~2hrs-1/2 day per site
  • 6. Indicators assessed 1. Plant Species Diversity 2. Weed Abundance and Threat 3. Structural Diversity – Ground Cover & Plant Life Forms 4. Regeneration 5. Tree & Shrub Health 6. Tree Habitat Features 7. Feral Animals 8. Total Grazing Pressure 9. Fauna Species Diversity 10. Bushland Degradation Risk
  • 7. Vegetation Community Benchmarks • Values obtained for each indicator dependent on both condition and the vegetation type being assessed • Vegetation Communities are based on groups of Vegetation Associations with similar structure and composition of vegetation • Comparison of field data to benchmark values for a particular community type thus allows for expected variation in indicators as a result of belonging to that vegetation community • At the site scale, there is quick feedback of results that do not require further analysis
  • 8. Current status BCM used for biodiversity assessments in: Upper South East Biodiversity Trading, BushBids (eastern MLR) Candlebark woodlands (MLR), Bush for Life, On-ground works assessment (NY NRM region) Approximately 1500 sites established 375 people trained Manuals published: Southern Mt Lofty Ranges Southern Mt Lofty Ranges Coastal Northern Agricultural and Yorke Peninsula regions Eyre Peninsula and SA Murray-Darling Basin manuals published by Summer 08/09
  • 10. Testing the methodology Trial to gain insights into surveyor consistency as well as the ability of surveyors to detect differences between different sites. This would provide an indication of the ability of the BCM method to detect real change at a site, as compared to change that may be due to the skill or bias of different observers. Five different practitioners who had been trained by NCSSA and had been using the BCMM in field situations independently scored four different sites that had been marked out within an area of the Waite Reserve in the Adelaide Hills. Each site belonged to a similar vegetation association (Eucalyptus camaldulensis/Eucalyptus leucoxylon woodland) but sites were chosen to represent different condition classes in the poor to moderate range
  • 11. Mean species richness scores for five observers 0 5 10 15 20 1 2 3 4 Site number SpeciesRichness AverageScore(+-SD)
  • 12. Mean structural diversity scores for five observers 0 2 4 6 8 10 12 1 2 3 4 Site number StructuralDiversity PlantLifeForms score(+-SD)
  • 13. Power to detect change in tree health Degree of Change in Tree Health Number of Trees Scored Low (10% change in tree health) High (30% change) 10 63% 85% 40 75% 98% Table 1: Predicted power of tree health data to detect change (Note that α = β as discussed by Field et al 2007)
  • 14. Compatibility with state and transition models • BCM does not assume a linear model for condition trajectories (measuring multiple parameters) • 5 condition classes in 11 indicators allows for 511 possible condition states (approx 50 million) • Data collected could inform development and refinement of state and transition models (eg BushBids predicted versus real response)
  • 15. Prolonged Domestic Grazing has led to: Moderate species diversity, Moderate weed abundance & threat, Poor structural diversity, Lack of regeneration of woody trees & shrubs, High total grazing pressure Reduced domestic grazing leads to: Higher weed abundance and threat Due to lack of competition: An increase in grazing feral animals Other Associated Consequences: Loss of species diversity Reduction of structural diversity Protection from grazing leads to: Increased species diversity Lower total grazing pressure Regeneration of woody perennials Increased structural diversity Increased ground cover Intended application of Bushland Condition Monitoring Tool Detect condition change over time, investigate causal factors, link to management regime
  • 16. Comparison of condition information from 2 sites
  • 17. Value of site based information • site based data needed to build and support predictive spatial modeling • site based data forms a foundation for expert opinion • collection of site based data can contribute to building capacity of land managers and community • guides investment decisions • used to report on outcomes
  • 18. BCM was not designed to • provide information relating to the autecology of a species eg: • spatial or temporal information on individual species abundance • species interactions BCM provides quantified measure and interpretation of universally accepted biodiversity surrogates that allows for valid comparison in these surrogates spatially or temporally
  • 21. Weed Abundance and Threat Score Indicator Rating
  • 22. Structural Diversity Plant Life Forms Score Indicator Rating
  • 26. Tree Health - Dieback Score Indicator Rating
  • 27. Tree Health - Mistletoe Score Indicator Rating