Assessing and reporting resilience of native vegetation using metrics of structure,

composition and function

Richard Thackway

Macquarie University Biology Department Seminar

22 April 2015

Outline

• How the land use modifies native vegetation • Links between management and ecosystem services• VAST-2 methodology

– Detailed chronology of causes and effects – Criteria and indicators of structure, composition and function– Some concepts and definitions– Analytical framework

• Case studies• Lessons • Where to from here• Conclusions and more information

Every vegetated landscape has been effected by land

management practices since European settlement

Reference state:• Grassy woodland

Transformation state:• Modified (VAST II)

Land use: • Aboriginal land

Current management goal:• Establish an

appropriate fire regime

Climate zone:• Tropical

Locality:• Robinson River, NT

2006

Reference state:• Complex Notophyll

Vine Forest

Transformation state:• Transformed (VAST II)

Land use: • Conservation reserve

Current management goal:• Control and remove

weeds

Climate zone:• Sub-tropical

Locality:• Lismore, NSW

200620092009

Reference state:• Grassy woodland

Transformation state:• Adventive (VAST IV)

Land use: • Electricity easement

Current management goal:• Provide open space

Climate zone:• Temperate

Locality:• Canberra, ACT2010

Reference state:• Grassy shrubland

Transformation state:• Transformed (VAST III)

Land use: • Conservation reserve

Current management goal:• Establish 30% ground

cover

Climate zone:• Arid

Locality:• Alice Springs, NT

20062009

Most tools for assessing veg condition only produce a

snapshot and not change over time

VAST = Vegetation Assets States and Transitions NVIS = National Vegetation Information System

VIVIVIIIIII0

Native vegetationcover

Non-native vegetationcover

Increasing modification caused by use and management

Transitions = trend

Vegetation thresholds

Reference for each veg type (NVIS)

VAST - A framework for assessing & reporting native 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 Resilience threshold

Thackway & Lesslie (2008) Environmental Management, 42,

572-90

NB: Input dataset biophysical naturalness reclassified using VAST framework

/ replaced

/ unmodified

VAST 2009

Veg condition derived by classifying &

mapping effects of land management practices

Native

Reporting change in condition

using Vegetation

Types (NVIS/MVG),

and vegetation condition

(VAST)

Source: ABARES 2013

Veg condition

derived fr

om effects

of land m

anagement

practice

s

Veg type (NVIS/MVG)

NVIS: National Vegetation Information SystemMVG: Major Vegetation Groups

VAST

*

* bioregion

To understand landscape transformation we to understand why land managers change the

structure, composition and function of native vegetation

Historic goals of land managers over time

Change in structure, composition & function

Values and decisions matrix:• Social• Economic• Environmental

Intensification

Degradation?

Time

State @ t1

State @ t2

State @ t3

Development

Regulation of hydrological regime Generation of food and fibre Regulation of climate / microclimate Generation of raw materials Recycling of organic matter Creating and regulating habitats Controlling reproduction and dispersal

LMP are used to change ecological function to derive multiple benefits (ecosystem services)

t1 t2 t3

Time

Stat

e @

t1

Stat

e @

t2

Stat

e @

t3

Current & future goals of land managers

Values and decisions matrix:• Social• Economic• Environmental

Extensification

Restoration

State @ t1

Regeneration

State @ t2

State @ t3

Change in structure, composition & function

1925

Occupation

Relaxation

Anthropogenic change

‘Net benefit’

time

1900 2025 1950

Reference

chan

ge in

veg

etati

on in

dica

tor o

r ind

ex

1850 1875 1975 2000

VAST-2 model of transformation of native vegetation

VAST classes

Concepts and definitions

• Resilience = the capacity of an plant community to recover toward a reference state following a change/s in land management

• Change in condition of a plant community (type) is due to effects of land management practices:

– Structure– Composition – Regenerative capacity

• Transformation = changes in vegetation condition over time• Condition, resilience and transformation are assessed relative

to a fully natural Reference state

Vegetation condition

Based on Cannon (1987)

Baseline for assessing resilience:Indigenous peoples first contact with explorers

Based on Cannon (1987), Readers Digest. Plotted using IBRA regions

How do land managers modify structure, composition & function (i.e. resilience) over time?

LMP that focus on soil

LMP that focus on native vegetation

Regenerative capacity/ function

Vegetation structure & Species composition

1. Soil hydrological status2. Soil physical status3. Soil chemical status4. Soil biological status5. Fire regime6. Reproductive potential7. Overstorey structure8. Understorey structure9. Overstorey composition10. Understorey composition

LMP = Land Management Practices

Focussing on 10 key criteria

Common interventions designed to influence structure, composition & function i.e. resilience

Various interventions: Land management practices (LMP) are used to influence ecological building blocks at sites and landscapes by:

• Modifying …• Removing and replacing …• Enhancing …• Restoring …• Maintaining …• Improving …

Various purposes:To achieve the desired mix of ecosystem services (space & time)

VAST-2 is an accounting system for assessing the transformation of native vegetation

Spp compVeg structure

LU = Land Use, LMP = Land Management Practices

VAST Diagnostic attributes

LU & LMPYear

Time

Regen cap

/Function

Aim of VAST-2 at sites and landscapes

Indigenous land management

First explorers

Grazing

Deg

ree

of

resi

lienc

e/co

nditi

on

Logging

Cropping

Site 1

Site 2

Site 3

Time

Reference state

Long term rainfall

Long term disturbance e.g. wildfire, cyclones

Revegetation

VAST classes

Weeds

Ferals

How does VAST-2 use metrics to assess and report

resilience/condition of native vegetation?

Generate total indices for ‘transformation site’ for each year of the historical record. Validate using Expert Knowledge

• Compile and collate effects of land management on criteria (10) and

indicators (22) over time. • Evaluate impacts on the plant

community over time

Transformation site• Compile and collate effects of

land management on criteria (10) and indicators (22)

Reference state/sites

Score all 22 indicators for ‘transformation site’ relative to the ‘reference site’. 0 = major change; 1 = no change

Derive weighted indices for the ‘transformation site’ i.e. regenerative capacity (55%), vegetation structure (27%) and species composition (18%)

by adding predefined indicators

General process for tracking change over time using the VAST-2 system

Approximate year

Source: Year

LU & LMP Source: LU & LMP

Effects of land use and management on criteria and

indicators of vegetation condition

Source: Effects

1800

1840

2015

Establish a chronology of data and information of causes and effects /observed & measured responses

Pre-contact

First contact

Current year

LU = Land Use, LMP = Land Management Practices NB: Accuracy of each observation and measurement is important

Components (3)

Criteria(10)

Description of loss or gain relative to pre settlement indicator reference state (22)

Regenerative

capacity

Fire regime Change in the area /size of fire foot prints

Change in the number of fire starts

Soil hydrology Change in the soil surface water availability

Change in the ground water availability

Soil physical state

Change in the depth of the A horizon

Change in soil structure.

Soil nutrient state

Nutrient stress – rundown (deficiency) relative to soil fertility

Nutrient stress – excess (toxicity) relative to soil fertility

Soil biological state

Change in the recyclers responsible for maintaining soil porosity and nutrient recycling

Change in surface organic matter, soil crusts

Reproductive potential

Change in the reproductive potential of overstorey structuring species

Change in the reproductive potential of understorey structuring species

Vegetation structure

Overstorey structure

Change in the overstorey top height (mean) of the plant community

Change in the overstorey foliage projective cover (mean) of the plant community

Change in the overstorey structural diversity (i.e. a diversity of age classes) of the stand

Understorey structure

Change in the understorey top height (mean) of the plant community

Change in the understorey ground cover (mean) of the plant community

Change in the understorey structural diversity (i.e. a diversity of age classes) of the plant

Species Compositi

on

Overstorey composition

Change in the densities of overstorey species functional groups

Change in no.s of indigenous overstorey species relative to the number of exotic species

Understorey composition

Change in the densities of understorey species functional groups

Change in no.s of indigenous understorey species relative to the number of exotic species

1

3

10

22

Com

pone

nts

(3)

VegetationTransformation

Score (1)

Crite

ria(1

0)

VegetationStructure

(27%)

Overstorey

(3)

Understorey

(3)

SpeciesComposition

(18%)

(2)

UnderstoreyOverstorey

(2)

RegenerativeCapacity

(55%)

Fire

(2)

Reprodpotent

(2)

Soil

Hydrology

(2)

Biology

(2)

Nutrients

(2)

Structure

(2)Indicators

(22)

VAST-2 – benchmark scoring of the effects of use and management of native veg (indicators) over time

Importance of dynamics

Assume rainfall is main driver of natural system dynamics• Period 1900 - 2014• Average seasonal rainfall (summer, autumn, …)• Rainfall anomaly is calculated above and below the mean• Two year running trend line fitted

Seasonal rainfall anomaly (Lat -32.404, Long 152.496)

1901

1904

1907

1910

1913

1916

1919

1922

1925

1928

1931

1934

1937

1940

1943

1946

1949

1952

1955

1958

1961

1964

1967

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

2003

2006

2009

2012

-2-1.5

-1-0.5

00.5

11.5

22.5

Spring

1901

1904

1907

1910

1913

1916

1919

1922

1925

1928

1931

1934

1937

1940

1943

1946

1949

1952

1955

1958

1961

1964

1967

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

2003

2006

2009

2012

-3-2-1012345

Winter

1901

1904

1907

1910

1913

1916

1919

1922

1925

1928

1931

1934

1937

1940

1943

1946

1949

1952

1955

1958

1961

1964

1967

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

2003

2006

2009

2012

-3-2-10123456

Autumn

1901

1904

1907

1910

1913

1916

1919

1922

1925

1928

1931

1934

1937

1940

1943

1946

1949

1952

1955

1958

1961

1964

1967

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

2003

2006

2009

2012

-2-1.5

-1-0.5

00.5

11.5

22.5

3

Summer

Source: BOM

• Network of collaborators• Ecologists, land managers, academics, research scientists,

environmental historians

• Inputs• Reference state • Historical record of land use & Land management practices• Historical record of major natural events e.g. droughts, fires, floods,

cyclones, modelled average rainfall 1900-2014• Observed interactions e.g. rabbits, sheep and drought• Observations and quantitative measures of effects of LMP

• Include written, oral, artistic, photographic, long-term ecological monitoring sites and remote sensing

Resources needed for each site

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

Reliability levels of attribute sources

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

Assumptions

Changes in LU & LMP – result in measurable and predictable changes in structure, floristics

& regen capacity – can be consistently and reliably differentiated from natural events– have or can be adequately and reliably documented over time

Sequential responses in veg structure, floristics & regen capacity can be discovered, unpacked and scored over time

Ratings and weightings are ecologically meaningful

Case studies VAST-2

Coastal Eucalypt Angophora open forest, Myall Lakes, NSW

VAST

clas

ses

Salmon gum woodland, Great Western Woodlands, WA

Chenopod shrubland, Koonamore Station, SA

WanaringaVA

ST cl

asse

s

Brigalow woodland, Taroom Shire, Qld

Can the results and the system be used by decision makers

and land managers to influence future landscapes?

Tran

sfo

rmat

ion

sco

re

Years

1800

2012

Reference

Futures landscape - strategic regeneration, revegetation & restoration

Modified

Transformed

Replaced/ managed

Residual

Replaced/adventive

VAST Classes

1850 19501900 2000 2050 2100 Replaced/ removed

Predictions of mature forest (Bunning’s Enquiry 1974)

Bridge Hill Ridge- post mining restoration

X = 2034Y = 2054Z = 2074

X Y Z

Predictions of mature forest (Bunning’s Enquiry 1974)

Bridge Hill Ridge- post mining restoration

X = 2034Y = 2054Z = 2074

X Y Z

Components (3)

Criteria(10)

Description of loss or gain relative to pre settlement indicator reference state (22)

Regenerative

capacity

Fire regime Change in the area /size of fire foot prints

Change in the number of fire starts

Soil hydrology Change in the soil surface water availability

Change in the ground water availability

Soil physical state

Change in the depth of the A horizon

Change in soil structure.

Soil nutrient state

Nutrient stress – rundown (deficiency) relative to soil fertility

Nutrient stress – excess (toxicity) relative to soil fertility

Soil biological state

Change in the recyclers responsible for maintaining soil porosity and nutrient recycling

Change in surface organic matter, soil crusts

Reproductive potential

Change in the reproductive potential of overstorey structuring species

Change in the reproductive potential of understorey structuring species

Vegetation structure

Overstorey structure

Change in the overstorey top height (mean) of the plant community

Change in the overstorey foliage projective cover (mean) of the plant community

Change in the overstorey structural diversity (i.e. a diversity of age classes) of the stand

Understorey structure

Change in the understorey top height (mean) of the plant community

Change in the understorey ground cover (mean) of the plant community

Change in the understorey structural diversity (i.e. a diversity of age classes) of the plant

Species Compositi

on

Overstorey composition

Change in the densities of overstorey species functional groups

Change in no.s of indigenous overstorey species relative to the number of exotic species

Understorey composition

Change in the densities of understorey species functional groups

Change in no.s of indigenous understorey species relative to the number of exotic species

Lessons site vs. landscape

1. Constrain assessments to soil landscape units because this approximates land manager’s interventions

2. Must account for natural dynamics e.g. flood, fire, cyclone3. Remote sensing is only part of the solution –

a) Some measures of remote sensing e.g. greenness of tree crowns may not be directly related to vegetation condition

4. Tracking outcomes of management interventions using remote sensing a) e.g. environmental plantings and environmental watering requires on-

ground collection of data to calibrate and validate spatial and multi-temporal imagery

b) Only populate criteria and indicators once imagery has been validated

Conclusions

• VAST and VAST-2: Provides an accounting tool for reporting change and trend in the

condition of plant communities Helps with telling the resilience story in landscape transformation Provides a system for synthesizing diverse source and types of

information (quantitative and qualitative) Values equally land managers and ecologists because they both

contribute essential data and information Enables decision-makers to better understand complex ecosystem

transformations such as degradation, restoration and regeneration.

‘Telling the transformation story’

Residual/ unmodified

Modified

Transformed

Adventive

Replaced and managed

Organ Pipes National Park, Vic – ex cropping paddock

Pathways of landscape

transformation reflect choices

and drivers

VAST

cl

asse

s

http://portal.tern.org.au/transformation-of-australias-vegetated-landscapes-cumberland-state-forest-recommissioned-regrowth-forest-nsw

http://aceas-data.science.uq.edu.au/portal/

More info & Acknowledgements

More informationhttp://www.vasttransformations.com/http://portal.tern.org.au/searchhttp://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 assisted in the development of VAST & VAST-2