Tracking the Transformation of Vegetated Landscapes (VAST)

1. Tracking the Transformation of Vegetated Landscapes (VAST) Richard Thackway NSW ECA Conference Fairmont Resort at Leura in the Blue Mountains : 2nd August 2013 Offsets: determination, assessment and management

2. Outline • Concepts and definitions • Overview of VAST framework • Conceptual model for tracking change and trend • VAST-2 system • Case studies • More information

3. 1. Remaining extent of native vegetation 2. Remaining extent of native vegetation types 3. Remaining extent of native vegetation types compared to pre-Euro vegetation types 4. Proportion of remaining native vegetation types in specified condition classes Monitoring and reporting vegetation (maps) Based on: NLWRA 2007 VASTVAST

4. 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

5. VAST = Vegetation States Assets and Transitions NVIS = National Vegetation Information System VIVIVIIIIII0 Native vegetation cover Non-native vegetation cover Increasing vegetation modification Transitions = trend Vegetation thresholds Reference for each veg type (NVIS) VAST - A framework for reporting vegetation condition Condition states Unmodified/ Residual Naturally bare Modified Transformed Replaced - Adventive Replaced - managed Replaced - removed Thackway & Lesslie (2008) Environmental Management, 42, 572-90 Diagnostic attributes of states/ classes : • Vegetation structure • Species composition • Regenerative capacity NVIS

6. Native vegetation extent Dominant structuring plant species indigenous to the locality and spontaneous in occurrence – i.e. a vegetation community described using definitive vegetation types relative to estimated pre1750 states Non-native vegetation extent Dominant structuring plant species indigenous to the locality but cultivated; alien to the locality and cultivated; or alien to the locality and spontaneous VegetationconditionClass (mappingcriteria) UNMODIFIED native vegetation community structure, composition, and regenerative capacity intact – no significant perturbation from land use/land management practice MODIFIED native vegetation community structure, composition and regenerative capacity intact - perturbed by land use/land management practice TRANSFORMED native vegetation community structure, composition and regenerative capacity significantly altered by land use/land management practice REPLACED - ADVENTIVE native vegetation replacement – species alien to the locality and spontaneous in occurrence REPLACED - MANAGED native vegetation replacement with cultivated vegetation REMOVED vegetation removed - alienation to non- vegetated land cover Examples Old growth forests; Native grasslands that have not been grazed; Wildfire in native forests and woodlands of a natural frequency and/or intensity; Native vegetation types managed using sustainable grazing systems; Selective timber harvesting practices; Severely burnt (wildfire) native forests and woodlands not of a natural frequency and/or intensity Intensive native forestry practices; Heavily grazed native grasslands and grassy woodlands; Obvious thinning of trees for pasture production; Weedy native remnant patches; Degraded roadside reserves; Degraded coastal dune systems; Heavily grazed riparian vegetation Severe invasions of introduced weeds; Invasive native woody species found outside their normal range; Isolated native trees/shrubs/grass species in the above examples Forest plantations; Horticulture; Tree cropping; Orchards; Reclaimed mine sites; Environmental and amenity plantings; Improved pastures. (includes heavy thinning of trees for pasture); Cropping; Isolated native trees/ shrubs/ grass species in the above examples Water impoundments; Urban and industrial landscapes; quarries and mines; Transport infrastructure; salt scalded areas Active restoration e.g. Landscape reshaping and hydrological works, soil treatment, revegetation, encouragement of regeneration capacity Rehabilitation & passive restoration e.g. weed removal, re-seeding of understorey, controlled burning, stabilisation of dunes, re-establishment of riparian community flooding regimes Offsets and VAST classes in the short term Offsets

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

8. Replaced and managed (VAST V) Unmodified vegetation (VAST I) Transformed vegetation (VAST III) Adventive (VAST IV) Map of vegetation condition – a snap shot

9. 1. Remaining extent of native vegetation 2. Remaining extent of native vegetation types 3. Remaining extent of native vegetation types compared to pre-Euro vegetation types 4. Proportion of remaining native vegetation types in specified condition classes Tracking change and trend in condition Effects of management action decisions (PAST, PRESENT & FUTURE Resource change and trend reporting VAST-2 VASTVAST

10. Occupation Relaxation Anthropogenic change Net impact years 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. net loss changeinvegetationindicator/s 1800 1825 1850 1900 1925 1950 1975 2000 2025

11. Occupation Relaxation Anthropogenic change Net benefit years Reference Models of ecosystem change i.e. net gain changeinvegetationindicator/s Baseline Management intervention/s 1800 1825 1850 1900 1925 1950 1975 2000 2025

12. 1800 1825 1850 1900 1925 1950 1975 2000 2025 100 80 60 40 20 0 VAST Class Inferred impacts of land use on vegetation condition - ‘potential’ future condition Current land use: Continuous grazing of derived grassland Unmodified/ Residual Replaced - removed Replaced - managed Replaced - Adventive Modified VASTclasses time Transformed ?

13. Why use land management and not land use? 1850s 2000s Increasing intensification Stata: U = upper, M = mid, G = ground RC = Regenerative capacity, VS = Vegetation structure, SC = Species composition % Foliage Cover Height U M G Woodland % Foliage Cover Height U M G Open Woodland % Foliage Cover Height U M G Grassland with scattered trees Cattle grazing native pasture Cattle grazing native pasture Cattle grazing native pasture Land use VAST Class I II III Indicators of vegetation structure

14. VAST III: TransformedVAST I: Unmodified How VAST assesses transitions between states?

15. VAST defines what indicators are effected by management practices: Plant community type Regenerative capacity Vegetation structure Species composition Increasing vegetation modificationReference state

16. 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 : Focus on what the land manager is doing that effect veg condition

17. 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 : Focus on what the land manager is doing that effect veg condition

18. VAST-2 System Tracking change in vegetation condition

19. 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

20. 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

21. 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

22. 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: Rainfall also drives signal in some remote sensing products

23. 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

24. Case studies VAST-2

25. V IV III II I

26. V IV III II I

27. Approaches for accounting for net gains Quantitative accounting ‘Defaults’-based accounting • Rigorous and repeatable measurement at sites • High accuracy and precision • High costs (method development, field-based measurement costs, verification) • High skill levels too complex for citizen science • Potential barrier in high variability / low per-area return activities (e.g. rangelands) • Observations collected at sites over time. +ve & -ve scoring of indicators tied to changes in land management • Relatively accurate and lower precision • Low cost involving a partnership between land managers and ecologists • Attractive for engaging citizen scientists • Attractive for land manager reporting incl. site photos and record keeping • Utilise where appropriate, rigorous and repeatable site-based measurements VAST-2

28. VAST classes Native (based on dominant structuring species = >50 % cover) Non-native (based on dominant structuring species = >50 % cover) Unmodified (100-81) Modified (80-61) Transformed (60-41) Adventive (40-21) Replaced & managed (20-1) Replaced & removed (<1) Fully natural reference e.g. Box gum woodland Short term (~<10 yrs) Medium term (~10-50 yrs) Long term (~>50 yrs) Timerequiredtorecoverfully naturalreference Predicted recovery times for plant community types

29. The role of remote sensing: Health or Condition? • Some remote sensing products can be health measures and NOT condition e.g. – Normalised Difference Vegetation Index (NDVI) – Fractional cover – Leaf Area Index (LAI) • However, some remote sensing products can be used to upscale some condition indicators in VAST-2 e.g. – Lidar to determine Top height of the overstorey – Landsat to determine Foliage projective cover of the overstorey – Radar-based satellites and Lidar to determine Structural diversity derived from – Landsat to determine Ground cover

30. • . • Freehold no grazing • Multiple strata, some emergents • Biomass ~120 t/ha • FPC ~ 52%, Max height ~ 24m • Spp OverS 3-5, MidS 5+, GroundS 5-10 • Regen - good • . • Freehold - grazing • Two strata • Biomass ~68 t/ha • FPC ~ 25%, Max height ~ 17m • Spp OverS 3, MidS 1, GroundS ~1-4 • Regen – Low-Moderate • . • Freehold - heavy grazing - mechanical thinning • Single, low height strata • Biomass ~42 t/ha • FPC ~ 20%, Max height ~ 13m • Spp OverS 3, MidS 0, GroundS ~1-4 • Regen – very low, > % bare ground Site: p143 Site: p142-18 Site: p142-02 Site-based surveys Lidar VAST I - Unmodified VAST II – Modified VAST III – Transformed

31. Compiled by Qld EPA based on the average ground cover disturbance index Desert Uplands, Qld Source: Doug Ward Ground Cover Disturbance Index Landsat 1988-2004

32. Conclusions • Vegetation condition can be changed and can be tracked using indicators of the effects of land management practices • VAST-2 system has value for: – Engaging land managers as citizen scientists – Synthesizing information (quantitative and qualitative) – ‘Telling the story’ of vegetation condition and transformation

33. •More information •http://www.vasttransformations.com/ •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