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Keywords:

  • degradation;
  • modification states;
  • native vegetation;
  • reconstruction;
  • restoration;
  • state and transition;
  • vegetation condition

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Describing and mapping vegetation
  5. Measurement and classification of vegetation condition
  6. VAST framework
  7. Case studies
  8. Discussion
  9. Conclusions
  10. Acknowledgements
  11. References

Summary  The Vegetation Assets, States and Transitions (VAST) framework classifies vegetation by degree of human modification as a series of states, from intact native vegetation through to total removal. VAST is a simple communication and reporting tool designed to assist in describing and accounting for human-induced modification of vegetation. A benchmark is identified for each vegetation association based on structure, composition and current regenerative capacity. Benchmarks are based on the best understanding of pre-European conditions (sometimes called ‘fully natural’). Relative change in condition from this benchmark is assessed for each site or patch. Three case studies demonstrate use of the diagnostic criteria that underpin VAST. We argue that VAST has potential to provide a consistent framework for monitoring and reporting vegetation modification at a range of scales. Uses of VAST datasets for natural resource planning and management are discussed including a reporting and communication framework for describing the response of vegetation to changes in land use and land management practices, measuring progress toward vegetation targets and describing and mapping vegetation changes and trends.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Describing and mapping vegetation
  5. Measurement and classification of vegetation condition
  6. VAST framework
  7. Case studies
  8. Discussion
  9. Conclusions
  10. Acknowledgements
  11. References

Vegetation, which refers to all plant life in a given area, is extensively managed by technological societies to produce a variety of goods and services (Maltby et al. 1999). Much of Australia's vegetation has undergone significant modification since the commencement of European settlement of Australia about 200 years ago. By 2005 about 62% of the continent has been occupied by agricultural and livestock grazing enterprises, resulting in the extensive change or conversion of forest, woodland, open woodland, shrubland and grassland systems. Intensive agricultural development covers less than eight per cent of the continent (Thackway et al. 2004) and where it occurs has involved the extensive removal and fragmentation of native vegetation. Although the management of this modified vegetation aims primarily to produce food and fibre, retaining native vegetation is increasingly recognized as a way to achieve a wider range of societal goals such as sustaining and securing natural resources benefits including biodiversity, soil and water (Millennium Ecosystem Assessment 2005).

Australian vegetation has been described and mapped using the National Vegetation Information System (NVIS) framework (ESCAVI 2003) at the subformation, association and sub association levels using diagnostic criteria of structure and floristics. Vegetation information, including maps, is used for planning, management and environmental reporting. Vegetation that is managed to deliver a range of ecosystem goods and services may be modified, replaced or removed to meet the needs of human enterprises. These changes in the condition of vegetation can be described and mapped as ‘states’ (Thackway & Lesslie 2005).

Land management decisions that affect the structure, floristics and/or regenerative capacity of vegetation depend on the goals and values and the desired outcomes of management (e.g. habitat for selected species, maximizing water yield, food or fibre production, amelioration of erosion and farm forestry for carbon sequestration) (Maltby et al. 1999). A desired ‘state’ of the vegetation can also be achieved by managing and regulating biophysical conditions including water and nutrient inputs and physical and biological relationships (Trudgill 1977; Maltby et al. 1999) with, for example, the management of fire or grazing pressure.

The Vegetation Assets, States and Transitions (VAST) framework has been developed to assist in describing and mapping vegetation condition. The framework classifies vegetation as a series of states and transitions (sensu Westoby et al. 1989) ranging from an intact native vegetation baseline through to total vegetation removal. The framework:

  • • 
    Describes and accounts for changes in the status and condition of vegetation (note these two parameters may converge in some circumstances)
  • • 
    Makes explicit the links between land management and vegetation modification
  • • 
    Provides a mechanism for describing the consequences of land management on vegetation
  • • 
    Contributes to the analysis of terrestrial ecosystems services provided by vegetation, including comparing alternative land uses

The native vegetation benchmark condition is based on a best estimate of pre-European vegetation conditions (sometimes called ‘fully natural’). The benchmark may be determined from attributes at a single reference site, or an average (or range) of values determined from a set of reference sites (Hnatiuk et al. in press). Reference sites should be precisely located and documented for their benchmark values at specified times. A useful discussion of the benefits and shortcomings of the use of benchmarks is provided in Williams (2004). States and transitions in the framework are defined by artificial partitions in vegetation composition, structure and regenerative capacity resulting from postsettlement land use and land management practices in relation to the identified benchmark condition.

This paper presents and discusses a simple national classification that can accommodate the degree of modification as key criterion for planning vegetation assessments and vegetation policy responses. We demonstrate how vegetation condition datasets can be interpreted into the VAST framework using three case studies. We also discuss the potential to link the National Vegetation Information System (NVIS) framework and the VAST framework to enable consistent national monitoring and reporting on the status and trends of vegetation types, relative to a ‘long undamaged’ benchmark.

Describing and mapping vegetation

  1. Top of page
  2. Abstract
  3. Introduction
  4. Describing and mapping vegetation
  5. Measurement and classification of vegetation condition
  6. VAST framework
  7. Case studies
  8. Discussion
  9. Conclusions
  10. Acknowledgements
  11. References

For natural resource management purposes, vegetation is usually described and classified in terms of its extent, structure (height and spacing) and floristics (taxonomic grouping) (Walker & Hopkins 1990; Hnatiuk et al. in press). At the national level, the NVIS framework is used for describing and compiling data and the information within NVIS contains the agreed national protocol for describing vegetation extent and type (NLWRA 2005).

Without additional information on vegetation modification, or the degree of vegetation change in terms of its state and form of transition against a baseline or reference condition, it is not possible to adequately address links between the resultant levels of management intervention and vegetation structure and floristics on one hand and impacts and trends on natural resources, including biodiversity on the other (McIntyre & Hobbs 1999; Parkes et al. 2003; Gibbons et al. 2004; Hnatiuk et al. in press).

Measurement and classification of vegetation condition

  1. Top of page
  2. Abstract
  3. Introduction
  4. Describing and mapping vegetation
  5. Measurement and classification of vegetation condition
  6. VAST framework
  7. Case studies
  8. Discussion
  9. Conclusions
  10. Acknowledgements
  11. References

To monitor and report on vegetation condition associated with the use of native vegetation it is necessary to survey, describe and map vegetation type and extent. Modelling vegetation dynamics is also of value, as is modelling change through the description of patterns of vegetation use, replacement or removal. Appropriate applications of these three approaches requires an understanding of the response of vegetation to management and the links between natural disturbance regimes (e.g. wildfire, flood, cyclones, pests, diseases and drought) and land management practices which are associated with human use of the vegetation (Trudgill 1977).

Attributes that underpin the NVIS vegetation framework are also diagnostic criteria within the VAST framework, for example structural and floristic attributes. VAST additionally requires information on regenerative capacity of the nominated vegetation association. In order to interpret and classify a site or patch as a VAST state it is necessary to classify and interpret all three diagnostic criteria. An assessment of regenerative capacity requires information about ecosystem resilience (Westman 1986) and the severity and extent of disturbance including soil disturbance, exposure and the loss of biomass/carbon from the site. An understanding of stages of successional interventions and relationships to land management practices is critical to the assessment of the regenerative status of vegetation communities (Connell & Slatyer 1977).

The VAST framework is not a substitute for detailed survey and mapping, modelling and monitoring of native vegetation. Rather the VAST framework is able to translate and compile a wide range of data and information developed from vegetation assessments including survey and mapping, modelling and monitoring. The VAST framework has been developed to utilize existing datasets that are compiled at a range of scales including site, local, regional and national levels; provided these more detailed datasets and expert knowledge are available to inform the VAST diagnostic attributes needed to classify and interpret these datasets into the VAST states.

VAST framework

  1. Top of page
  2. Abstract
  3. Introduction
  4. Describing and mapping vegetation
  5. Measurement and classification of vegetation condition
  6. VAST framework
  7. Case studies
  8. Discussion
  9. Conclusions
  10. Acknowledgements
  11. References

Concepts and principles

Inherent in the VAST framework is the assumption that changes in the state of vegetation modification can be effected through land management practices. Management interventions that are aimed at restoring processes that maintain vegetation communities must be informed by knowledge of the extent and duration of past disturbances, cultural conditions that have shaped the landscape, species availability and species’ resilience and assembly rules (Hobbs & Norton 1996; Lockwood 1997; Society for Ecological Restoration International Science and Policy Working Group 2004). For example, McDougall and Morgan (2005) describe the restoration of a Themeda native grassland in Victoria that was cleared and intensively used for agriculture for about 100 years. Despite considerable effort in restoring and managing the area, supported by 15 years of site-based monitoring, they conclude the area remains largely weedy and will require on-going management and supplemental planting to maintain and expand the native species before the community can be regarded as self-sustaining. In the case study below, we translate information from McDougall and Morgan (2005) into the VAST framework. That example along with other VAST datasets described in Thackway and Lesslie (2005) rely for their interpretation on expert knowledge of human use and modification of native vegetation, the natural resilience of vegetation to disturbance regimes, and the response of vegetation to land use and management practices.

VAST comprises a series of vegetation modification states that are separated by artificial partitions. For vegetation to change to another state it must cross a partition defined in terms of observed changes in, for example, strata, growth form and dominant species. A VAST state can encompass multiple responses of the same vegetation association to human disturbance, for instance multiple age classes and different cover, height and strata. The divisions shown in Figure 1 represent artificial partitions along the continuum. These divisions are used to separate categories of apparent change, rather than changes in ecosystem resilience.

image

Figure 1. Vegetation Assets, States and Transitions with columns representing states and shifts between them defined as transitions.

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Land use choices and management practices can maintain vegetation within a state or change it to another state. For example, native Themeda grassland in southern New South Wales can be managed for conservation of a rare species, grazing of native pastures or conversion to exotic pastures, urban development or water impoundment. Each of these uses corresponds to a VAST state; each state is determined as a result of land use allocation decisions (e.g. converting to urban use) and by land management practice.

Complete removal of vegetation (including its capacity to recover from on-site and nearby propagules) represents an ‘extreme’ state of modification. A decision to reverse the system to its former benchmark condition requires total reconstruction (McDonald 1996, 2000). At the ‘highly modified’ end of the VAST framework, autogenic reversal may be impossible without biotic and abiotic restoration interventions. Buckney and Morrison (1992) and Wilkins et al. (2003) point out that the expected direction of increasing similarity of a reconstructed community toward a reference or benchmark site is probably unrealistic. These examples of two relatively long-term monitoring activities show that despite biotic and abiotic restoration interventions, reconstructed sites tend to maintain their distinctiveness from the desired reference or benchmark site. Although there are examples of reconstruction after high modification of vegetation, such examples are isolated and the restoration process is expensive and in many cases represents a longer-term commitment of resources than other restoration approaches (Society for Ecological Restoration International Science and Policy Working Group 2004).

At the less modified end of the VAST framework, a land manager may succeed in changing a VAST state with lower levels of active intervention (e.g. assisted natural regeneration, McDonald 1996, 2000). Indeed, before any decision is made to invest in the restoration of higher degradation VAST states IV–VI to the benchmark vegetation condition, decision-makers should consider giving priority to investing in the restoration of lower degradation VAST states and building landscape level advantage through three strategic actions proposed by McIntyre and Hobbs (2000). These actions represent in order of least cost: (i) building on the strengths of existing native vegetation; (ii) enhancing remaining native vegetation by filling gaps between remnants; and (iii) rehabilitating degraded areas.

A ‘veil line’ separates native (VAST I–III) from non-native (VAST IV–VI) states (Fig. 1). This disjunction helps partition and organize information, data, priority setting, on-ground investment, monitoring and evaluation and reporting. Figure 1 presents the VAST classification and describes the seven states and the diagnostic criteria used to distinguish them, with examples. VAST states can be mapped if input data and information satisfy the required diagnostic criteria. More information on the ecological concepts and principles that underpin the use and application of the VAST framework are presented in Thackway and Lesslie (2005).

Diagnostic criteria

Three main diagnostic criteria underpin the VAST framework (Fig. 1): floristic composition, vegetation structure and regenerative capacity.

Floristic composition

Change in the floristic composition is defined relative to the benchmark floristics of the nominated vegetation association (i.e. NVIS Level V) which is categorized on the basis of their dominant species in three strata (ESCAVI 2003). The completeness of a component species list will depend partly on the purpose of the survey, the season of sampling, the degree of disturbance and botanical expertise (Hnatiuk et al. in press). For site-based work, it is the list of all species at the site when the site was sampled. The level of detail is determined by the scale of mapping and the purpose of monitoring.

Vegetation structure

Change in the vegetation structure is also defined relative to the benchmark structure of the nominated vegetation association (i.e. NVIS Level V), that is an observed shift in the horizontal and vertical distribution of cover and height of the dominant plants. In the NVIS framework, cover and height is recorded for growth forms of major plants, and is usually repeated for each major layer that is discernible (Hnatiuk et al. in press). Significant changes in the characteristic or dominant growth form, height and cover are usually described for mapping VAST states. The level of attribute detail required is determined by the scale of mapping and the purpose of monitoring.

Regenerative capacity

Change in the regenerative capacity is defined relative to the benchmark growth stages of the nominated vegetation association (i.e. NVIS Level V). Growth stages can be described as recovery, maturing and senescence and are important when assessing the regenerative capacity of the vegetation. When a site is in a recovery phase (and until maturation) its recovery capacity to another disturbance is reduced. Although resprouting capacity may be reinstated by the time of reproductive maturation of the species, reinstatement of buried seed banks will require more time to establish irrespective of community (McDonald 1996). These growth stages are relative to the pre-existing community characteristic of that site (i.e. VAST I in Fig. 1). The growth stage (Hnatiuk et al. in press) of the nominated vegetation association is the phase in the life cycle of the dominant structuring species present at the site and observed or mapped at broader scales using aerial photography or satellite imagery. To map characteristic or dominant growth stage, age class or current regenerative capacity, the level of attribute detail is determined by the scale of mapping and the purpose of monitoring.

Requirements of input datasets

Table 1 shows the relationship between the NVIS and VAST frameworks based on diagnostic structural and floristic attributes. NVIS level V (association) is the preferred level for assessing the state of vegetation communities relative to a ‘long undamaged’ benchmark.

Table 1.  Relationship between the diagnostic criteria (i.e. structural and floristic attributes) required for NVIS and VAST frameworks
NVIS Framework (ESCAVI 2003) Vegetation attributes specified in the NVIS framework field manual (Hnatiuk et al. in press)Vegetation attributes required for VAST (refer to Fig. 1)
Level / NameNameAttributes of the ecologically dominant strata and sub-strataAttributes of the ecologically dominant strata and sub-strata
  1. NB:

  2. 1. VAST requires a benchmark condition for NVIS Level V, i.e. Association.

  3. 2. Additional vegetation attributes depicting regenerative capacity that are required by VAST include age class, growth stage, weeds, basal area, along with ancillary/explanatory attributes, for example, litter, logs, bare ground, land management practices and land use, and disturbance history. The relative abundance of these attributes is used to ascribe a map unit to a VAST state.

I / ClassFormation ClassGrowth form and coverAs for an NVIS Class
II / Structural Formation ClassStructural formationGrowth form, cover and heightAs for an NVIS Structural Formation Class
III / Broad Floristic FormationBroad Generic / Generic Group FormationGrowth form, cover, height and characteristic or broad floristic categoriesAs for an NVIS Broad Floristic Formation
IV / Sub-FormationSub-formationGrowth form, cover, height and characteristic or broad floristic categories in the three strataAs for an NVIS Sub-Formation
V / AssociationFloristic AssociationStructural Formation plus dominant speciesAs for an NVIS Association
VI / Sub-associationAs for Floristic AssociationAs for Floristic AssociationNot applicable

Table 2 describes the data types that may be compiled into VAST states i.e. surveying and mapping, monitoring and modelling, provided these datasets contain diagnostic criteria including structural, floristic and regenerative capacity.

Table 2.  Data types that may be used to derive VAST datasets, i.e. surveying and mapping, monitoring and modelling, provided these input datasets contain diagnostic criteria including structural, floristic and regenerative capacity
Approaches used to create vegetation modification datasetsSources of diagnostic criteria required to create VAST datasets
FloristicStructureRegenerative capacityChange agents (drivers)
Surveying and mapping (e.g. site-based and remotely sensed)Cover and /or frequency of dominant species (sites)Crown or foliage cover Field-based vertical height profile LiDAR vertical height profileObserved growth stage, regrowth, basal area, age class, seed store, vegetation greennessLand management practices, land use and disturbance history, e.g. fire, drought, cyclones
Monitoring (e.g. site-based and remotely sensed)Dominant species at sitesFoliage cover Field-based vertical height profile LiDAR vertical height profileAs for surveying and mappingAs for surveying and mapping
Models (e.g. land management practices, land use and disturbance history are used as independent or explanatory variables)Dominant species at sites and map unitsExpected structural profiles and cover classesExpected growth stage, basal area, regrowth, age class, seed storeAs for surveying and mapping

A decision on whether to collect new vegetation condition data or to translate and compile an existing vegetation condition dataset into the VAST framework must be considered in terms of the costs and benefits and the degree of ‘fit’ between the original dataset and the diagnostic criteria required by VAST. Gaps in diagnostic criteria or spatial coverage of an input dataset may preclude a dataset from being compiled into the VAST framework.

Case studies

  1. Top of page
  2. Abstract
  3. Introduction
  4. Describing and mapping vegetation
  5. Measurement and classification of vegetation condition
  6. VAST framework
  7. Case studies
  8. Discussion
  9. Conclusions
  10. Acknowledgements
  11. References

The three case studies below illustrate implementation of the VAST framework at the site-based and regional levels. The method used to translate and compile each vegetation dataset into the VAST framework involved the authors collaborating with the data custodians to translate the respective input datasets into VAST using the diagnostic criteria contained in the VAST framework. Once the data custodians were familiar with the VAST diagnostic criteria (described above) and the attributes contained in their datasets they, in consultation with the authors, proceeded to translate and compile these datasets into VAST classes. In each case study, the data custodians relied on information about human-induced change to vegetation structure, composition and regenerative capacity resulting from land use and land management practices.

Case study 1 – site level inventory

Sites in Poplar Box (Eucalyptus populnea) woodlands in central Queensland were surveyed as part of a precursor to the National Forest Inventory continental forest monitoring framework (NFI 2003). Detailed site-based vegetation structure, floristics and condition attribute data were collected using an integrated forest monitoring sampling methodology that linked ground plots, satellite data, airborne scanning laser data and medium to large-scale aerial photography (Tickle et al. 2001).

In this case study, the original vegetation surveyors and mappers compared the site-based vegetation structure, floristics and condition attribute data with the diagnostic criteria required for VAST, and translated the sites into VAST states I–III (A. Lee, pers. comm., 2005). The process required an understanding of the impact that land management practices have in modifying the states of Poplar Box woodlands from VAST I to III. Figure 2 presents three sites classified as VAST states I–III, the sites are shown as foliage profiles (method described by Walker & Penridge 1987 and Lee et al. 2004) and as ground photos. Clear differences can be observed between VAST states I, II and III in terms of the number of strata, biomass, foliage cover profiles, top height of the vegetation, the number of species recorded in each stratum, the regeneration of the dominant species and the extent of bare ground.

image

Figure 2. Three sites in the Poplar box woodlands in southeast Queensland classified using VAST states; Note the changes in diagnostic criteria among the sites in VAST I–III.

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Case study 2 – site level monitoring

The Organ Pipes National Park is the focus for a 3-ha long-term grassland restoration project (McDougall & Morgan 2005). The site is located near Melbourne, Victoria. In planning and implementing the Themeda grassland restoration project, McDougall and Morgan used their knowledge of extent and duration of past disturbances, cultural conditions that have shaped the landscape, abiotic influences, species availability and species performance. Between 1989 and 2003, McDougall and Morgan monitored the area at two-yearly intervals.

The following information was interpreted from McDougall and Morgan (2005) and checked with one of that study's authors (K. McDougall, pers. comm., 2005):

  • • 
    In the mid 1850s the site was a natural Themeda grassland, i.e. VAST I
  • • 
    Between 1860 and 1970 the area was used for grazing and cereal cropping, i.e. VAST I to V
  • • 
    In the period 1972–1988 the area was declared a National Park and minimally managed, however, the area was dominated by exotic species associated with crops and pastures, i.e. VAST IV
  • • 
    In 1993 and in 1995 the area was revegetated with Themeda, Danthonia and locally indigenous forbs, i.e. VAST III
  • • 
    Since 1995 the condition of the area declined, partly because of extended drought from 1997 to 2003 (combined with a management burn in 1997) and partly because of the lack of burning since (McDougall & Morgan 2005). In 2003, the area remained largely weedy and requires ongoing management comprising supplemental planting, selective herbicide application and periodic burning to maintain and expand the native species before it can be regarded as self-sustaining. Without ongoing on-ground management, it is likely that the area will change from VAST III to IV.

Case study 3 – regional survey and mapping

The Bogan Gate area of central New South Wales covers 1.6 million ha. Information on vegetation condition was collected by the Department of Infrastructure, Planning and Natural Resources (DIPNR) during detailed site surveys. In mapping the vegetation types, DIPNR used a process of classifying site-based data combined with expert ecological interpretation and relevant Geographic Information System (GIS) data layers to map vegetation across the landscape (DIPNR 2002a,b). The process used to create Figure 3 involved working with the original vegetation surveyors and mappers to synthesize a complex set of site-based vegetation condition data and regional land use mapping. The resultant VAST states were used to re-attribute the mapping units. To ensure vegetation states were accurately assigned the authors consulted with the regional experts. The VAST dataset was revised to reflect that feedback.

image

Figure 3. VAST classification, Bogan Gate, New South Wales.

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Information on vegetation association and modification states may be used to assess the status of native vegetation. Figures 3 and 4 together illustrate the extent of the VAST states and their relationship to the vegetation types present. Hill woodlands of the Bogan Gate area comprise around 75 000 ha, all of which has been classified as VAST I. Grasslands and herbaceous communities comprise around 860 000 ha, most of which (∼610 000 ha) has been converted to VAST V (Fig. 4). Around 240 000 ha of these grassland and herbaceous communities remain as VAST III.

image

Figure 4. Area (hectares) of VAST states for selected vegetation types in Bogan Gate study area, New South Wales.

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Describing and mapping vegetation
  5. Measurement and classification of vegetation condition
  6. VAST framework
  7. Case studies
  8. Discussion
  9. Conclusions
  10. Acknowledgements
  11. References

The three case studies presented here demonstrate translation of vegetation condition datasets into the VAST framework. This flexibility of the VAST framework enables datasets collected and/or developed for different purposes, for example, survey and mapping, modelling and/or monitoring, to be classified (translated and compiled) into the VAST framework. VAST therefore has potential to provide a nationally consistent framework for monitoring and reporting vegetation modification at a range of scales.

As with any classification framework, it is necessary to assess the degree of fit, the gaps and limitations found in classifying complex multi-attribute ecological systems using diagnostic criteria and a continuum of states. This is particularly important when assessing two or more VAST datasets that overlap or abut. In these instances it is vital to understand issues of scale and data resolutions, sampling periods and the different methods used to collect the attribute data and/or to spatially extend or to model the expected modification rates across the landscape.

The case studies demonstrate that the VAST framework provides a simple metric that can be used at a range of scales for classifying and reporting the states and trends in vegetation. Such information is also useful for identifying priorities for investment, informing decision-making on public vegetation policy and for monitoring trend in vegetation condition. In this context, we propose the VAST framework can be readily used as a reporting and communication framework for describing and measuring vegetation targets in natural resource management plans, and for describing vegetation changes and trends.

Reporting and communication framework

In addition to the case studies presented in this paper, the VAST framework has been used to derive a number of interim VAST datasets that were originally created using a variety of different methods and mapping scales, for example, Australia-wide and northwest Victoria (Thackway & Lesslie 2005). Such applications demonstrate the relative ease and flexibility with which data custodians have used the VAST framework. The authors have also found that the VAST framework has been readily understood by decision-makers in the context of developing a scientific underpinning for vegetation policy and program delivery.

Decision-makers who have access to such information can use these products to plan strategically, raise issues of whether land management practices are sustainable, identify areas at risk and set priorities for on-ground investment. For example, at a catchment level, the VAST framework could be used to measure progress toward an aspirational target for restoring native vegetation (Fig. 5). Repeated field-based assessments over time can be used to assess performance relative to a target.

image

Figure 5. Linking VAST to targets and thresholds.

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Describing vegetation changes and trends

VAST information can be used to describe the pathways for sustainable management of native vegetation. These pathways may include positive and negative feedback cycles, and transitions from one VAST state to another, including the replacement, removal or recovery of native vegetation. An example of these pathways includes anecdotal evidence gained by the second author during land use mapping in the southern tablelands of New South Wales. In this case the vegetation is used for the production of wool and meat showed a cycle of pasture management, which is repeated about every 20 years. That cycle begins with:

  • • 
    grazing of native grasslands that are in different states (I to II to III),
  • • 
    which are then converted from native pasture to a crop (III to Va),
  • • 
    conversion from a crop to improved pasture (Va to Vb),
  • • 
    permit improved pasture to convert naturally to native pasture (Vb to IV),
  • • 
    at the end of the cycle it is converted from a native pasture to a crop (IV to Va).

The VAST framework can also be applied to reporting on silviculture practices in native forest management and urban encroachment into native vegetation or land used for cropping. To describe and map vegetation changes and trends it is necessary that appropriate spatial datasets are available (e.g. GIS and satellite imagery combined with field-based sampling). This information can then be used to meet a range of monitoring and evaluation requirements.

Conclusions

  1. Top of page
  2. Abstract
  3. Introduction
  4. Describing and mapping vegetation
  5. Measurement and classification of vegetation condition
  6. VAST framework
  7. Case studies
  8. Discussion
  9. Conclusions
  10. Acknowledgements
  11. References

Values and uses associated with vegetation are not homogeneous across the landscape or within society and also change over time. An assessment and reporting framework that describes and maps these uses and values as states of vegetation condition over time is needed. We have argued that the VAST framework can meet this requirement.

Vegetation management for natural resource management involves monitoring vegetation extent, type and condition and modification states, in relation to management goals. The goals and values for managing vegetation condition requires reviewing and adjusting land management in light of observed changes in condition, new scientific knowledge, changing objectives or community expectations (Thackway et al. 2005).

The VAST framework provides a flexible and repeatable tool for a range of applications to enable land planners and land managers to describe and map vegetation condition across the whole landscape. VAST can be used to describe and map historic, current and/or potential future states of the vegetation at a scale that is relevant to different decision-makers’ needs. Provided the input datasets are available or could be collected, the VAST framework can be used to visualize changes in vegetation condition over time. That information could be used as an input to develop scenarios of future landscapes.

The VAST framework can translate and compile vegetation condition information from a wide range of sources, and therefore it has potential to provide a consistent national approach for assessing the costs and benefits of alternative land and vegetation management practices on the delivery of multiple ecosystem services.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Describing and mapping vegetation
  5. Measurement and classification of vegetation condition
  6. VAST framework
  7. Case studies
  8. Discussion
  9. Conclusions
  10. Acknowledgements
  11. References

The development of the VAST framework was funded by the Natural Heritage Trust and the Bureau of Rural Sciences. Alex Lee prepared Figure 2 and Mijo Gavran prepared Figures 3 and 4. Many people and agencies across Australia contributed to the VAST conceptual framework. Stuart Davey, John Davidson and Mark Parsons provided comments on an earlier draft of this paper.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Describing and mapping vegetation
  5. Measurement and classification of vegetation condition
  6. VAST framework
  7. Case studies
  8. Discussion
  9. Conclusions
  10. Acknowledgements
  11. References
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