data.daff.gov.audata.daff.gov.au/brs/data/warehouse/pe_brs90000004198/... · Web viewThe full names and codes at four different levels of classification are as follows: Formation

Explanatory notes for theVegetation field handbook, version 2

RJ Hnatiuk, R Thackway and J WalkerOctober 2009

These notes provide greater detail to support:

Hnatiuk RJ, Thackway R and Walker J 2009, ‘Vegetation’, in The National Committee on Soil and Terrain, Australian soil and land survey field handbook (3rd edition), CSIRO Publishing, Melbourne, pp. 73-126.

ISBN 978-1-921192-54-8

Hnatiuk RJ, Thackway R and Walker J 2009, Explanatory notes for the Vegetation field handbook, version 2, Bureau of Rural Sciences, Canberra.

← © Commonwealth of Australia 2009

This work is copyright. Apart from any use as permitted under the Copyright Act 1968, no part may be reproduced by any process without prior written permission from the Commonwealth. Requests and inquiries concerning reproduction and rights should be addressed to the Commonwealth Copyright Administration, Attorney General’s Department, Robert Garran Offices, National Circuit, Barton ACT 2600 or posted at http://www.ag.gov.au/cca.

The Australian Government acting through the Bureau of Rural Sciences has exercised due care and skill in the preparation and compilation of the information and data set out in this publication. Notwithstanding, the Bureau of Rural Sciences, its employees and advisers disclaim all liability, including liability for negligence, for any loss, damage, injury, expense or cost incurred by any person as a result of accessing, using or relying upon any of the information or data set out in this publication to the maximum extent permitted by law.

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Explanatory notes for the Vegetation field handbook, version 2 ii

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Acknowledgments These explanatory notes were developed with the financial support of the National Land and Water Resources Audit, the Bureau of Rural Sciences and CSIRO.

Much of the information in this paper was presented to and discussed at a technical workshop titled ‘Attributes for site-based vegetation survey (Yellow Book) and links to the NVIS framework’, convened at the Australian National University in Canberra on 17–18 February 2005. A shortened version is the ‘Vegetation’ chapter in Australian soil and land survey field handbook (The National Committee on Soil and Terrain 2009). We acknowledge ESCAVI and the Audit Advisory Council for supporting the publication of version 1 of this report as a chapter in the Australian soil and land survey field handbook, version 3, and ESCAVI for its endorsement of the chapter as ‘Guidelines for surveying and classifying Australia’s vegetation’.

We particularly thank Becky Schmidt, who assisted the authors in editing the text of the ‘Vegetation’ chapter in the Australian soil and land survey field handbook, and Christine Atyeo for skilfully restructuring and editing this longer version to match the structure of that chapter.

Explanatory notes for the Vegetation field handbook, version 2 iii

Table of contentsAcknowledgments.......................................................................................................................... iii

Introduction...................................................................................................................................... 1

Who should use these explanatory notes?...................................................................................1

Before field data collection begins................................................................................................1

Attributes.......................................................................................................................................... 5

Site location.................................................................................................................................. 5

Sampling method.......................................................................................................................... 6

Description and classification of vegetation.................................................................................9

Vegetation structure................................................................................................................... 10

Formation class and structural formation....................................................................................12

Coding structural information......................................................................................................12

Adding floristics to the structural formation.................................................................................13

Strata (layers)............................................................................................................................. 15

Example of the standard classification.......................................................................................17

Levels in the standard classification...........................................................................................19

Formation (Level 1)....................................................................................................................19

Structural formation (Level 2).....................................................................................................26

Broad floristic formation (Level 3)...............................................................................................31

Wetlands......................................................................................................................................... 41

Aquatic and wetland types..........................................................................................................42

Rainforest....................................................................................................................................... 44

Tropical and subtropical rainforests............................................................................................44

Tasmanian rainforests................................................................................................................50

Growth stage.................................................................................................................................. 52

Vegetation condition..................................................................................................................... 55

New technology............................................................................................................................. 64

Global positioning systems.........................................................................................................64

LIDAR......................................................................................................................................... 65

Soils................................................................................................................................................ 67

References..................................................................................................................................... 68

Annex 1: Steps in the field survey process.................................................................................72

Annex 2: Forms............................................................................................................................. 74

Annex 3: Schematic profiles of Australian vegetation types.....................................................81

Annex 4: Cover-abundance.............................................................................................................86

Explanatory notes for the Vegetation field handbook, version 2 iv

Table of tablesTable 1: Comparison of structural vegetation classification systems.................................................9

Table 2: Attributes required to define Levels 1, 2 and 3, non-rainforest vegetation.........................11

Table 3: Examples of classification levels........................................................................................12

Table 4: Height classes, codes and names.....................................................................................13

Table 5: Naming floristic associations using species dominance and indicator species in the dominant, mid- and lower strata...............................................................................................14

Table 6: Visual estimation of crown cover class..............................................................................23

Table 7: Converting crown separation ratio to crown cover.............................................................25

Table 8: Glossary of growth forms, structural formations................................................................27

Table 9: Broad floristic formations (Level 3)....................................................................................32

Table 10: Wetland growth forms......................................................................................................41

Table 11: Additional attributes used to classify two special cases of rainforest...............................44

Table 12: Terms for describing leaf size in the tallest stratum of tropical/subtropical rainforest......46

Table 13: Attributes and codes used to classify tropical/subtropical rainforests..............................48

Table 14: Examples to illustrate coding for both the standard and tropical/subtropical rainforest classification............................................................................................................................ 49

Table 15: Distinguishing characteristics of Tasmanian rainforests..................................................51

Table 16: Indicators of growth stage................................................................................................53

Table 17: Condition of woody—particularly tree-dominated—native vegetation in southern Australia. . .56

Table 18: The Vegetation Assets, States and Transitions (VAST) classification.............................57

Table 19: Condition attributes..........................................................................................................58

Table 20: Attributes used in the assessment of wetland condition..................................................60

Table 21: Scoring vegetation using benchmarks.............................................................................60

Table 22: The Braun-Blanquet cover-abundance scale for estimating species quantities........................86

Table of figuresFigure 1: The processes used in vegetation sampling, mapping and classification...........................2

Figure 2: A schematic illustration for tall open forest (tall mid-dense trees), showing several clearly discernible vertical layers of vegetation, or strata....................................................................11

Figure 3: Coding a sample site using the classification: example...........................................................18

Figure 4: The zigzag sampling procedure........................................................................................21

Figure 5: Crown types......................................................................................................................22

Figure 6: Field measurement of foliage cover using a line transect.................................................23

Figure 7: Actual leaf size categories for rainforest trees..................................................................45

Figure 8: Growth stages..................................................................................................................54

Figure 9: Longitudinal profile of air-borne field-plot LIDAR data and its associated vertical profile..66

Explanatory notes for the Vegetation field handbook, version 2 v

IntroductionThe relationship between field sampling for vegetation attributes and the broader work of mapping and classifying vegetation has been documented in Guidelines for surveying soil and land resources (Thackway et al. 2008) (Figure 1). The methods described in this publication relate primarily to the structural (physiognomic) and floristic characteristics of the vegetation (as per Walker and Hopkins 1990), as well as to some ancillary site information. Structural characteristics are those that describe the vertical and horizontal distribution of vegetation in space (i.e. growth form, height, density and layering), while floristics encompass the names of dominant and characteristic plant species as well as comprehensive species lists for particular sites. A good sample-site record also contains a range of non-vegetation information (metadata) essential for the processing and use of vegetation information (see, for example, ESCAVI 2003). The metadata addressed in this source manual are a subset of the full set documented in the Australian Spatial Data Directory.1 The standards in these notes accord with the published views of the Executive Steering Committee for Australian Vegetation Information (ESCAVI) (ESCAVI 2003).

These explanatory notes provide additional detail about the standard methods for sampling, describing, classifying and mapping vegetation in Australia that are published by Hnatiuk, Thackway and Walker (2009), referred to here as the ‘Field Handbook’. The methods have been tested extensively in the field and have a wide range of applications in Australia and elsewhere. As much as possible, they accord with the standards of the National Vegetation Information System (NVIS), but we acknowledge that there are significant new items that will need to be incorporated into the next versions of NVIS. This volume updates an earlier vegetation classification (Walker and Hopkins 1990) to meet the current demands of users operating at a wide range of scales and to take advantage of an improved understanding of floristic and structural characteristics of vegetation and developments in remote sensing and geo-location. It is timely in that it provides a single unified system for classifying vegetation across whole landscapes irrespective of whether they support native, exotic or mixtures of these vegetation types.

Who should use these explanatory notes?These explanatory notes complement the vegetation chapter in the Field Handbook in providing more details for many of the concepts and standards provided in the Field Handbook and also in outlining some issues regarding decisions made about classes and methodology. They provide extra background information for anyone who needs to collect site-based data about vegetation. Potential users include people with interests in vegetation mapping and monitoring, flora, fauna and biodiversity surveys, faunal habitats, biomass and carbon sequestration, fire fuel loads, environmental impact assessment, land-cover change, native and introduced vegetation, the ground-truthing of remotely sensed images of the earth, preparation of land management plans and systems, or foliage and structure profiling.

Before field data collection begins

Checklist prior to going into the fieldAnnex 1 provides a generic checklist of steps to help ensure that surveyors are ready to embark on a field trip.

Purpose of the vegetation surveyIt is important to understand and document the purpose of collecting vegetation data because both the kind and detail of data vary for different purposes. It is impractical to list here all the needs

1<http://asdd.ga.gov.au/asdd/>

Explanatory notes for the Vegetation field handbook, version 2 1

that different users might have for vegetation information; what follows addresses the core needs of those most likely to use this manual.

Figure 1: The processes used in vegetation sampling, mapping and classification

← Note: The elements listed in the highlighted box are the subject of these Explanatory Notes.

← Source: Thackway et al. (2008), adapted from Neldner et al. (2004).


Preliminary MappingDelineation of vegetation polygonsBased on either or a combination of:

Data Analysis

Field Data Collection

Site-based vegetation survey - Sampling and collecting data

i.e. floristic, structural and environmental data

Vegetation polygons

Vegetation associations

Defined by total floristics, or Dominant floristics in each strata e.g. upper strata

Eucalyptus and Casuarina, with or withoutStructure e.g. open forest, with or withoutPosition in the landscape e.g. lower slopes, with or

withoutEnvironmental correlations e.g. sandy soil over

graniteVegetation Mapping and Description

Map units may describe:spatial mix of vegetation types in polygons display labels and coloursenvironmental correlations e.g. landform pattern sandy

soil over granitevalidation of classification and mappingdocumentation of vegetation communities and

dataset/s

Description of vegetation associations

Vegetation communities are described but not mapped

Aerial photo or image interpretation - influenced bylandform element/patternsubstrate (soil and/or

geology)photo-pattern/reflectance

influenced by vegetation and substrate

ecological knowledge

Correlations between independent environmental mapped attributes that share the same vegetation type- influenced byquality and reliability of the

independent environmental mapped attributes

quantity and reliability of the site-based records

Remotely sensed datae.g. aerial photographs and/or satellite imagery

Independent environmental mapse.g. soil, geology, elevation, climate

Survey and planning Stratification - based on either or a combination of:

Qualitative data analysis

Manually assign sites to vegetation communities on the basis of field data and using a variety of floristic, structural and environmental attributes

Quantitative data analysis

Numerical analyses varies with the type of data available (binary or quantitative), may be constrained to woody/ perennial plants only; informed by structural and environmental attributes

ClassificationBased on either or a combination of:

In vegetation mapping, the usual approach has been to locate sites within examples of relatively intact vegetation of what is thought to be mature (or at least not early regeneration) stages of the type. Selecting mature or intact sites has been done because in most circumstances field work cannot be repeated often enough to usefully show the short-term changes in vegetation brought about by disturbances such as those caused by fire, drought, storms, grazing by domestic livestock, and human activities. A map of what is often called ‘potential vegetation’ (e.g. Carnahan 1977) represents what is believed to be the kind of vegetation that a particular set of sites, with similar environments and disturbances, will support at maturity. Even though some intact, mature vegetation sites might themselves be succeeded by a different vegetation type if left undisturbed for long enough, they can qualify for site sampling.

In contrast to the approach just noted, which has been used historically in most vegetation mapping in Australia, an increasing range of users now has interests in successional (seral) stages of vegetation, ranging from the moment of disturbance, through recovery, maturation and senescence, to the next disturbance. In some cases, this process will involve the progressive replacement of the dominant and other species with new species. Samples from successional studies help elucidate vegetation dynamics. Similarly, vegetation samples that are collected in conjunction with a variety of faunal studies may also span different stages in the life cycle of vegetation. These stages are likely to provide differing faunal habitats and need recording in their own right. Studies that involve repeated sampling (i.e. monitoring) might also require that site-based samples include successional stages of vegetation and could use old aerial photos or local knowledge to document past vegetation.

Vegetation data form one of the basic inputs for a variety of environmental modelling programs: habitats, climate change, soil water balances, disturbance impacts, carbon sequestration, fire fuel loads, whole of landscape studies etc. The approach recommended here will provide the basic data for these activities, although project-specific data might also be required.

Vegetation data are also used in the development of numerically-based vegetation classifications, which are used for a great diversity of purposes, such as planning reserve systems, reintroduction of endangered species into native habitat or revegetation of modified landscapes with pre-European vegetation. Surveyers should ensure that the kinds of data needed for such classification work are collected.

Timing of field surveyUntil recently, vegetation field sampling has largely ignored the effects of seasons or longer-period weather factors such as drought on vegetation. Surveys for other biological components of ecosystems, such as fauna, now frequently include planned re-sampling to ensure all such factors are taken into account, and a similar approach should be adopted for vegetation surveys where temporal impacts are known to occur (Neldner et al. 2004). Thus, sampling times should be chosen so that most species expected to occur are likely to be visible (e.g. mid to late-growing season, or across several seasons, or after a drought breaks).

Sample detailThe following factors have a significant influence on the level of detail required in a field survey: the scope of the study (a large area general survey, for example, might

need to record only the dominant species, cover and height of each stratum present; a detailed study might record the height, cover, phenology, dispersion and biomass, etc., of all species present)

whether the data will be used for quantitative floristic analysis (e.g. the production of a floristically-based classification of vegetation types, based on presence-absence or cover-abundance estimates)

the resources available (e.g. people, equipment, time and money)


whether the sample site will be revisited or not (e.g. if it is to be a monitoring or reference site)

whether the sample site is to be fitted into a pre-existing list of vegetation types (e.g. NVIS).

Time required at survey plotThe minimum dataset (see below), which requires the visual estimation of attributes such as mean crown separation, ground stratum foliage cover, height of plants to decide classes, and dominant species, can be collected for a site in only a few minutes and would be sufficient for a broad classification of the vegetation. The core dataset, which provides significantly more information (see below), is used for more detailed studies and offers much more flexibility in data analysis. However, even this should take less than 30 minutes to collect in the field for forest, woodland, shrubland and grassland. It might take longer in some types of rainforest and species-rich shrublands.

Minimum quantitative dataset The minimum dataset necessary to classify non-rainforest vegetation involves the collection of four types of data at each site: 1. dominant growth form (per stratum, if more than one present)2. cover (per stratum, if more than one present)3. height (per stratum, if more than one present) 4. dominant species (per stratum, if more than one present).

While most field workers prefer to design their own field proformas, the proforma shown in Annex 2 is convenient for use in the field. Space is provided to record seven species occuring in the crown of the dominant stratum, second stratum and the third stratum. The ground-layer measurements are taken along a tape measure; additional plant species other than the dominants can be recorded. Space is available to enter median structural data.

Data collected in this proforma can be used to classify vegetation in the field and, in the office, open up a number of possible methods of data analysis. The data collected on the proforma shown in Annex 2 have been used, for example, to generate foliage profiles (Walker and Penridge 1987) using the computer program described by Penridge (1987).

Core dataset for vegetation samplesAnnex 3 shows the core dataset for a vegetation field site. It includes fields for reporting site location and methods used to determine this, recorders’ names, survey date(s), environmental or landscape factors affecting the site, contextual information about disturbance and condition, and floristic and vegetation attributes. Some fields might be irrelevant for some survey regions but have been included for completeness. For example, distance to nearest water is relevant to many vegetation surveys in the drier parts of the continent because of the potential influence of grazing animals on the vegetation and their relationship with access to water, but it might be less relevant to wetter regions. Similarly, evidence of fire and climatic conditions at the time of survey might be relevant to some surveys and not others.

Modifying the proformaIndividual projects may need to modify the core proforma to incorporate project or institution-specific data fields. It is strongly recommended that actual growth forms, heights, crown separation ratios and floristic data be recorded, as these data increase the utility of the survey.


AttributesIn the context of site vegetation survey, attributes are the things that are recorded. They include environmental characteristics of the site and its surroundings, the methods used in the survey, the people doing the survey, the date(s) of the survey, and the characteristics of the vegetation and plants at and near the sample site.

The attributes described below have been grouped according to site location, sampling method, vegetation and plant attributes. A short section on new technology since Walker and Hopkins (1990) is also included. Those attributes that deal with wetlands, the tropical and sub-tropical rainforests of north-eastern and central-eastern Australia, and the cool temperate rainforests of Tasmania are reported separately after the ‘wetlands’ section below.

Site locationLocating a sample site is a multi-stage process. It starts in the office and is progressively refined until the actual location of the site is determined in the field. A first step is to identify the vegetation units that are to be sampled; this is usually done using aerial photographs or maps on the basis of their homogeneity with respect to specified criteria (e.g. landscape position, geological/soil substrate, vegetation structure and age) (Thackway et al. 2008).

The precise fixing of sample plots within the homogeneous area uses a combination of rigorous technique and good judgement. Several factors need to be balanced: The location of the plot should be as free from observer bias as possible. In other

words, plots should not be chosen to include or exclude particular elements of the vegetation units being sampled (moving the edge of the plot, for example, to include desirable or exclude undesirable species or individuals, particular size-classes of trees, understorey species, etc.).

The sample site should be characteristic of the vegetation unit it is meant to represent. Conditions on the ground might have changed since the maps or photographs used in stratifying samples were made, which could mean that the precise location will need to be changed.

The location of the plot should not include elements that are not part of the homogeneous (stratified) unit but which are discovered during an initial examination of a site. Plot boundaries should not: cross into other vegetation units; include age or disturbance areas not meant to be part of the homogeneous unit; or include ecological transition zones (ecotones), unless they explicitly part of the study objectives. Ecotones are usually different from the core areas of vegetation types and, for certain kinds of studies, can be considered ‘types’ in their own right. Under such circumstances, the plot can be relocated using the randomised method described below.

Randomised procedureThe survey team should use the following unbiased procedure to locate the sample plot: Walk from a defined starting point into the sample site to ensure it is well within

the homogeneous unit and away from edge effects. Use a set of random numbers to select the number of paces to walk in a

predetermined compass direction. Record the numbers and the direction so the site can be relocated when necessary. At the location, use that point as one corner of the plot, or one end of the transect

being used as the sampling framework. Examine the area that the plot will cover to ensure it does not include any elements

that are not part of the vegetation unit. If it does, the plot can be shifted slightly to avoid the foreign element, but do not shift to include or exclude elements of the unit being studied; otherwise a new location must be found using the same procedure.


Marking the siteOnce the sample site has been determined it should be permanently marked so that it can be relocated at a later date. The method used to do this needs to be compatible with the needs and uses of the landowners and managers. Options include: marking the location on an aerial photo (pin-prick or measure and record distances

from eastern and southern margins). Record the identification of the aerial photo used. Ensure the photo is adequately archived for future reference

using a global positioning system (GPS) to determine the exact coordinates of the site and recording these for future reference

attaching surveyor’s tape to a tree or stake; this might last several years burying iron or steel pegs (e.g. 5 to10 millimetres diameter by 200 to 300

millimetres long) so that they are not visible and will not pose an injury risk to others using the site, but which can be relocated later using metal detectors.

Issues Correct use of stratified random techniques Avoidance of observer bias Ensuring a homogeneous sample Adequate recording of site location.

Further informationThackway, R, Neldner, J, and Bolton, M 2008, ‘Chapter 7: Vegetation’, in McKenzie, N, Ringrose-Voase, A and Grundy, M (eds.), Australian soil and land survey handbook guidelines for conducting surveys, 2nd edition, CSIRO Publishing, Melbourne.

Walker, J and Penridge, L 1987, FOL-Prof: a Fortran-77 package for the generation of foliage profiles part 1, User manual, Technical memorandum 87/9, Division of Water Resources Research, CSIRO, Canberra.

Sampling method

Plot shapePlot shape is the geometrical shape of the plot. It can be square, rectangular or circular; it can also be point-centred or a transect (i.e. plotless). In general, square plots are preferable, although specific conditions might dictate other shapes: riparian strips, for example, might require narrow plots, and soft herbaceous vegetation that is easily damaged by trampling might be best sampled using a transect.

Characteristics of different plot shapes Square plots are the most commonly used and are relatively easy to set up. Compared with

rectangular plots, they have low edge effects relative to the area of the plot. However, they are more likely than rectangular plots to sustain heavy trampling, which might affect attributes such as cover.

Circular plots have similar characteristics to square ones. They have advantages for certain kinds of measurements, such as basal area, which are determined by sitings from a fixed point (basal area samples are actually made in irregular circular plots, not in plots for which the perimeter of the circle is marked out on the ground). It can be difficult to mark the boundaries of a circular plot where the vegetation is tall.


Rectangular plots, including ‘transect’ plots, allow greater access to the plot with relatively fewer trampling effects compared with square or circular plots. They have relatively larger perimeter to area ratios, however, which increases the risk of edge effects (such as decisions over whether a plant is in or out of the plot). Rectangular plots have advantages in sampling vegetation features that, by nature, are long and narrow in shape, such as riparian habitats.

The zigzag method, outlined in Figure 3, is an example of a plotless method. The line-intercept method (Figure 5) is another.

When using rectangular or transect plots, the orientation of the plot relative to the surrounding environment could become a factor. Decisions on orientation will depend on the purpose of the study or the kinds of analyses intended for the data. Options include:1. Orient the long axis of the plot across any environmental gradient (e.g. slope) that is part of the

homogeneous unit being sampled. This will increase the within-sample variation and facilitate later comparisons with other samples of the type. If the number of samples is determined by statistical or other quantitative analysis, this approach will tend to reduce the number of samples needed compared with the next alternative. It will also produce a conservative result with respect to the recognition of vegetation types: i.e. it tends to aggregate results rather than sub-divide them.

2. Orient the long axis of the plot parallel to within-type environmental gradients (e.g. slope), thus minimising within-sample variation. This process narrows the variation included in the sample but tends to increase the apparent distinctiveness of samples from what might be thought to be a single type, thus tending to increase the number of types recognised in subsequent analyses.

3. Orient the long axis at random, relative to within-type environmental gradients. By taking several samples within the type, the variance because of the included gradient will be incorporated in the aggregated sample of several transects for the location. This approach is similar to 1) above but does not require the explicit recognition of any particular environmental gradient beforehand.

What to record

Record the plot shape. If sampling is plotless, record the particular method used.

Issues Trampling (if likely to have a significant effect, use a narrow rectangular plot or transect rather

than a square or circular plot) Ease of setting up (e.g. circular plots are difficult to establish in tall vegetation) Cost-effectiveness (ease of recording, number of plots relative to the degree of precision

needed).

Further informationMueller-Dombois, D and Ellenberg, H 1974, Aims and methods of vegetation ecology, John Wiley & Sons, New York, United States.

Plot sizePlot size refers to the area covered by the sample plot.

What to recordRecord the dimensions of the plot and the type of plot. If circular, give the radius in metres. If square or rectangular, give the length and width. If point-centred or plot-less, indicate by naming method; if a transect, give the length of the transect.


Plot size should vary with the physical dimensions of the attributes being sampled. The following can be used as a guide: For plants more than 20 metres high, use 900 square metre (30 metres by 30 metres) plots. For plants more than one to less than 20 metres high, use 400 square metres (20 metres by 20

metres) plots. For plants less than one metre high, usually 10 randomly placed plots ranging in size from 25

square metres (five metres by five metres) to four square centimetres (2 centimetres by 2 centimetres).

IssuesPlot size should remain as constant as possible for each vegetation type sampled. Changing the area of a plot might affect some of the statistics for the survey, such as within or between-sample variances. However, it is appropriate to change the shape of a plot (as long as size—i.e. area—is not changed) so that its boundaries do not cross into adjoining vegetation types.

Different sizes of plants are usually sampled better by different sizes of plot. That is, large plants like trees require large plots, while shrubs require smaller plots and herbs and mosses yet smaller plots. The sampling design, therefore, might need to include nested plots (e.g. when sampling multi-layered vegetation, the overstorey might require a larger plot size than the mid-stratum, and the ground stratum might require an even smaller plot size). When undertaking detailed studies in previously unstudied vegetation types, it might be necessary to determine optimal plot size by sampling sets of plots for the attribute(s) in question and plotting the cumulative means of these sets against the cumulative areas, repeating the process until the fluctuation in the mean value is reduced to a negligible size.

If quantitative floristic analyses are planned, species accumulation curves should be determined and optimal plot size deduced from them. To determine the mean sizes of crowns and crown gaps, several transects 50 metres or more in length should be used rather than extra-large plots. In sites dominated by the ground layer (e.g. grasses, low shrubs and mosses), foliage cover and plant height data can be collected in several plots ranging in size from one square metre (for a total of perhaps 50 square metres) to 0.01 square metres (for a total area of 0.5 metres), or transects 1 to 20 metres in length, depending on the size of the plants being measured.

Further information

Kent, M and Coker, P 1992, Vegetation description and analysis: A practical approach, CRC Press, Boca Raton, United States.

Kershaw, K 1966, Quantitative and dynamic ecology, Edward Arnold, London, United Kingdom.

Greig-Smith, P 1983, Quantitative plant ecology: Studies in ecology, 3rd edition, volume 9, Blackwell Scientific, Oxford, United Kingdom.


Description and classification of vegetationIn its most general sense, the term vegetation refers to the total plant cover of the earth (Mueller-Dombois and Ellenberg 1974). It occurs in a wide variety of patterns that involve differences in species mixes, growth forms and spatial attributes such as cover, height and density and reflect changing environmental conditions. At various scales, these patterns constitute plant communities, which can be classified in a hierarchical way from the broadest (formations) to the most detailed (associations and sub-associations).

The NVIS program has suggested a vegetation hierarchy that reflects explicit relationships between vegetation communities at differing scales. Table 1 shows the relationships between the Walker and Hopkins (1990) vegetation classification, the NVIS system (ESCAVI 2003), and the system used in this manual, and the key attributes that need to be measured to classify a vegetation community. Here the first four levels of detail are the main concern, recognising that for most purposes this level of detail will be adequate.

Table 1: Comparison of structural vegetation classification systems

Key attributes This publication NVIS (ESCAVI 2003) Walker and Hopkins

(1990)

Level of detail/name Level/name Name

Life form (woody or non-woody) and cover %

1. Formation I Class Not applicable

Growth form (tree, shrub, grass, oat crop etc.), cover % and height of the dominant stratum and emergents

2. Structural formation(and sub-formation)

II Structural formation Structural formation(see pp. 60–61 in Walker and Hopkins 1990)

Growth form, cover %, height and characteristic species/genera in the dominant stratum

3. Broad floristic formation

III Broad floristic formation

Floristic association – the structural formation plus characteristic species/genera in the dominant stratum (see p. 76 in Walker and Hopkins 1990)

Above plus the dominant genera for each stratum (upper, mid- and ground)

4. Broad floristic sub-formation

IV Broad floristic sub-formation

Structural sub-formation (see p. 74 in Walker and Hopkins 1990)—above plus additional species

Above plus the three dominant or co-dominant species in each stratum

5. Species can be added for sub-strata (see Figure 8)

V Association

Above plus the five dominant or co-dominant species in each stratum

6. Species can be added for sub-strata (see Figure 8)

VI Sub-association


The first attempt at a comprehensive classification of Australian vegetation was made by botanist Ferdinand von Mueller (Mueller 1866) based on broad structure and prominent or interesting species. Ludwig Diels (Diels 1906), a visiting German scientist, produced the next major classification and the continent’s first vegetation map. His system was also structurally-based (cover and height classes and growth form), with floristic dominants defining subunits. Other noteworthy developments in structural classifications of Australian vegetation include: Wood (1930s), Williams (1950s), and Specht (1974); for national vegetation maps: Carnahan (1970s and 1980s); and for site-based vegetation methods: Walker and Hopkins (1984, 1990). Many others have also made substantial contributions to vegetation mapping in Australia. Most systems were based on units defined by structure at the higher levels, with subunits based on the floristic composition of either the canopy dominants or the understorey.

From the earliest days, vegetation units have been related to variation in soils (geology), terrain and climate, and vegetation mosaics were also recognised features. The structurally-based systems enabled vegetation classification in the face of insufficient knowledge about the large and often taxonomically complex Australian flora. They also found wide acceptance because they used easily understood terms such as growth form, cover and height.

The unusually floristically detailed (for Australia) yet extensive studies of vegetation in eastern Victoria by Gullan and others (e.g. Gullan et al. 1981) were an application in Australia of the European school of phytosociology led by Braun-Blanquet and Tuxon. Another, similarly detailed series of studies of forest vegetation in south-western Australia by Havel and Mattiske (1998) was also based on detailed floristic analyses and gave rise to a classification based on understorey strata and characteristic species. Such floristically-based systems, which are in strong contrast to the structurally-based/dominant-species systems of most other classifiers, became possible only after sufficient taxonomic information about regional flora became available.

The balance in the use of floristic information shifted significantly in the last two decades of the 20th century and taxonomic knowledge is now standard in most vegetation studies. Every state and territory has flora handbooks for all or most of their regions (see Floristics) and there is continental cover for a growing proportion of the flora through the Flora of Australia, including lower plants (lichens, mosses, algae and fungi), which is now available online.2 The effect of this increase in floristic information is that vegetation scientists are now expected to include it in their vegetation classifications.

Vegetation structureVegetation structure is the horizontal and vertical distribution of the cover and height of dominant plants, usually recorded for major plants in each discernible layer or stratum (Figure 2). Annex 4 presents a set of schematic illustrations of vegetation structure for a diversity of Australian vegetation types. For convenience, in this manual, the vegetation component of landscapes is divided into classes, which are grouped in a hierarchical system (as shown in Table 1). At the highest levels of the hierarchy, the classes are defined by the way they look—their structure—and, at lower levels, the floristic composition of the dominant plants is used.Table 2 shows the attributes used to define non-rainforest vegetation classes (for rainforest see Rainforest); Table 3 provides examples of the first three levels of detail used here.

2 http://www.deh.gov.au/biodiversity/abrs/online-resources/flora/index.html


Figure 2: A schematic illustration for tall open forest (tall mid-dense trees), showing several clearly discernible vertical layers of vegetation, or strata

← Source: Carnahan (1990, page 11), reproduced with permission from Geosciences Australia.

Table 2:Attributes required to define Levels 1, 2 and 3, non-rainforest vegetation

Rec

ogni

se

Attributes required Level of detail

Dominant stratum

Mid-stratum (if present)

Ground stratum (if present)

Rec

ord

(for

at l

east

thed

omin

ant a

nd g

roun

d st

rata

)

1. Life form (woody or non-woody plant) Formation

(Level 1):record 1–2

Structuralformation(Level 2):record 1–7

Broad floristicformation(Level 3):record 1–8

2. Cover of the dominant stratum (crown separation or foliage cover, Table 7)

3. Crown type (Figure 5)

4. Growth forms in each stratum

5. Height (Table 4) of each stratum

6. Foliage cover of the lower stratum

7. Emergents (if any - cover and height)


8. Species of only the dominant stratum

Formation class and structural formationAt its highest level Level 1, the vegetation classification described here is based on the life form (woody or non-woody) and cover of the species forming the dominant stratum. Where more detailed levels are required include trees, shrubs, and grasses and growth forms as the habit or general appearance of a plant. The classes of vegetation at this high level are called formation classes.

Table 3: Examples of classification levelsLevel Name Notes

Formation class (Level 1)

Mid-dense woody plants Table 6 and life form (woody or non-woody plant)

Structural formation (Level 2)

Very tall mid-dense trees Tables 9 and 10

Broad floristic formation (Level 3)

Very tall mid-dense Eucalyptus trees Tables 9 and 10 and floristics

Broad floristic sub-formation (Level 4)

Very tall mid-dense Eucalyptus trees with tall sparse Eucalyptus tree understorey over dwarf very sparse Eremophila shrubs with a tall sparse Bothriochloa tussock grass ground stratum

Tables 9 and 10 and floristics

Two life forms are used at the level of formation class: woody and non-woody (herbaceous) plants (Table 16). In this context, ‘woody plants’ are plants in which woodiness is achieved by a secondary thickening of the xylem or by other anatomical means (for example, secondary thickening of successive external cambia or of a unidirectional cambium); thus, woody plants include all trees, palms, arborescent cycads, tree ferns, shrubs and woody vines. Herbaceous plants are those that lack or substantially lack woody tissue, including therophytes (i.e. annuals: plants that regenerate more-or-less annually from seed). In this system, all grasses and grass-like plants are defined as herbs, along with forbs.

When the height of the dominant stratum is added to the formation class, the resulting classification unit is called a structural formation (Level 2). The structural formations recognised here are based on those used previously by Walker and Hopkins (1990) but with some differences, particularly the removal of taxonomically based units from the formation classes and structural formations and their inclusion in the next lower level of the vegetation hierarchy (the broad floristic formation and sub-formation). New classes have been added for non-native vegetation and bare surfaces. These changes have allowed a consistent presentation of all units within the hierarchy.

Coding structural informationA shorthand nomenclature for structural formations is desirable for data storage and retrieval, remote sensing marking, and mapping. The code system must be applicable at different levels of detail (see columns 1 and 2 in Table 9).

In circumstances where the broad floristic formations need coding, such as in maps, the following system can be used. Each layer in the vegetation is represented by a group of six characters.


Starting from the left, the first character is for height (see Table 4); the next character for crown separation (crown cover percentage) (see Table 9), and the next four are for growth form (see Table 9), in that order: thus, 7Sw1.0 would represent tall (7) open (S) forest (w1.0). The system is illustrated in greater detail in Figure 6. To ensure compatibility with any existing or future classification, it is strongly recommended that actual height and crown cover percentage (or separation) values be recorded.

Table 4: Height classes, codes and names Height class code

Height (m)

Life form—w(woody plants)

Life form—nw(non-woody plants)

10 >50.01 Giant NA*9 35.01–50 Extremely tall NA8 20.01–35 Very tall NA7 10.01–20 Tall NA6 5.01–10 Medium Giant5 2.01–5.0 Low Extremely tall4 1.01–2 Dwarf Very tall3 0.51–1 Miniature Tall2 0.26–0.5 Micro Medium1 0.05–0.25 Nano Low0 <0.05 NA Dwarf

← * NA, not applicable

← Note: In some cases (e.g. the National Forest Inventory) it is important to distinguish trees from other woody plants. To be considered a tree the woody plant must be taller than 2 metres at maturity.

Recording height classHeight should be recorded as precisely as field methods allow; each life-form (Level 1) or growth-form (Levels 2 to 6) can be assigned to a class during subsequent processing. Height class boundaries are generally fairly arbitrary, especially when considering vegetation across major environmental and climatic gradients or where age is non-uniform.

Adding floristics to the structural formation Species or generic names (i.e. floristics) can be added to the structural formation name. At the highest level, the dominant species in the dominant stratum is used. More species names can be added to distinguish vegetation types that have similar structures and species dominance in the dominant stratum. The species used in the field to tentatively distinguish vegetation types can be modified later on the basis of numerical analysis or to conform to an already compiled vegetation-type list.

The main problem in using the dominant species to qualify the structural formation is that dominance can vary spatially; if two or more species occur in varying amounts in essentially the same vegetation type, for example, a variety of names would be possible. This problem is best resolved after the field survey is completed and various data manipulations tried. One solution is to recognise co-dominants in a stratum and to list each.

Ideally, all species present in the sample site at the time of sampling should be recorded. The completeness of a species list, however, will depend on the purpose of the survey, the season of


sampling, the degree of disturbance and the botanical expertise of the sampler. Those responsible for the survey must ensure that field workers have adequate botanical training and are familiar with the floristics of the survey area. At a minimum, the dominant species of the dominant stratum (and mid and lower strata, if present) should be recorded or the alternatives noted (Table 5). Where sub-strata are absent, the ecologically most important species are recorded. Selecting those species might require a high level of skill; the criteria used to select them should be noted in field records.

Table 5: Naming floristic associations using species dominance and indicator species in the dominant, mid- and lower strata

First species Initially, the most abundant or physically predominant species in the dominant stratum is selected.

Second species If another dominant stratum species is always present and conspicuous (i.e. is a co-dominant), it is selected. In the absence of a second species in the dominant stratum, the most abundant or physically predominant species of the next most conspicuous stratum is selected.

Third species A third species is selected from any stratum, usually a lower stratum, as an indicator species (that is, a species with known environmental preferences or of such abundance that it cannot be ignored), or to distinguish between associations.

Subsequent species In some cases, more species are required to separate associations; the selection is as for the third species.

Species codesA code comprising the first two letters of the genus and the first three letters of the specific name is more convenient in the field than writing names out in full. For the few species with the same code, the last letter is replaced with a number. Some people use four letters for genus and four letters for species, to avoid sequences that might be confusing; others use a ‘pick list’ to record full scientific names.

Examples of floristic codes

EUPOP Eucalyptus populnea (dominant species in dominant stratum)ERMIT Eremophila mitchellii (dominant species in mid-stratum)BODEC Bothriochloa decipiens (dominant species in lower stratum) ERGLA Eremophila glabraERGL2 Eremocitrus glauca

Example of the broad floristic formation naming process

Dominant species in dominant stratum: Eucalyptus populnea (EUPOP)

Mid-stratum dominant: Eremophila mitchellii (ERMIT)

Ground stratum dominant: Bothriochloa decipiens (BODEC)

DOMINANT SPECIES + STRUCTURAL FORMATION = VEGETATION NAME

i.e. Eucalyptus populnea tall trees (coded EUPOP 7Sw1.0)



Strata (layers)A stratum is defined as a visually conspicuous layer, of measurable depth, in a plant community, produced by the occurrence of an aggregation of branches and photosynthetic tissue (when present) (Figure 6). All vegetation has at least one stratum. It might have more than one stratum, or a single stratum might extend from the top of the canopy to near ground level.

What to recordThe height of the top of each stratum should be recorded in metres. This is the median height: i.e. the middle height of the ranked height records, not the height of the tallest plants or the arithmetic mean, especially when there are a few very tall or very short plants making up the top of a stratum or canopy.

When a study requires it, the depth of the stratum should also be recorded. Like the top of the stratum, the height of the bottom of the stratum is the median of ranked records.

IssuesThe recording of layers should not involve the use of predetermined classes: i.e. it should not be based on arbitrary or fixed height classes. The recognition of sub-strata is not a necessary prerequisite for defining plant communities (see Special cases: regrowth below).

Naming strataDominant, or upper, stratum (U): The dominant stratum is the stratum containing the plants with the greatest ecological influence on the vegetation. In most cases, the tallest stratum will also be the dominant stratum (an exception to this is the case of emergents; see below). All vegetation types have a dominant stratum, and there are no mandatory upper or lower height limits.

Ground stratum (G): The ground stratum occurs beneath a taller stratum and is close to the ground. If the ground stratum is also the dominant stratum (e.g. the grass layer in closed grassland) it is recorded as the dominant stratum. There is no mandatory height limit on the ground layer, but it is usually less than 2 metres tall.

Mid-stratum (M): The mid-stratum, if present, is the stratum that occurs between the dominant and lowest or ground strata. When present, it has no preconceived height limits.

Sub-strata: It is sometimes useful to record subdivisions of the three main strata, such as when a major stratum is seen to be composed of two or more elements. The dominant stratum, for example, might consist of a single species that makes up most of the canopy, but its lower limit might be mostly composed of a different species (a co-dominant). In such cases, separate strata do not really exist, but by recognising a sub-stratum it might be possible to clarify a significant aspect of the vegetation (e.g. development stage, species mix, etc.).

Emergents: In some vegetation, the tallest plants are so sparse that they no longer form the dominant or most significant layer. A few Araucaria or Eucalyptus trees, for example, might rise above a closed rainforest canopy, or, in semi-arid regions, widely scattered eucalypts or acacias might rise above lower shrubs or grasses. This tallest stratum can then be classified as an ‘emergent layer’; the dominant layer by which the vegetation will be classified is then, usually, the next-tallest layer (see also later discussion on emergents).

Complex canopies because of regrowth Vegetation that has been disturbed or is still recovering from certain kinds of disturbance can produce complex canopies. Two or more cohorts of canopy species might occur, for example, where the canopy has been reduced but not totally removed by clearing, ringbarking or poisoning.


When of clearly different ages, these cohorts are also likely to differ in height, complicating the task of describing the canopy. This is the case in large areas of grazing land in Queensland.

In such situations, the methods already described for defining dominant stratum and emergents should be applied. The vegetation can be further characterised by recording the age mix of the site (see growth stage, Table 16). The different cohorts should not be amalgamated unless they are too similar in structure to be distinguished consistently. Arbitrary height boundaries should not be used to separate them.


Example of the standard classificationThe first step in a standard classification is identifying the strata. The attributes for each stratum are then measured in the field as described in the previous sections; each level of classification requires the attributes as listed in Table 2. Once these data are gathered, the vegetation type in each stratum can be named and coded as shown in Figure 3. Lower strata can be added in naming and coding following the sequence: upper stratum height/cover/growth form; mid-stratum (or strata) height/cover/growth form; ground stratum height/cover/growth form. For the example shown in Figure 3, a hypothetical site with four strata and emergent trees is used.

The full names and codes at four different levels of classification are as follows:

Formation (Level 1)Name: ‘Mid-dense woody plants’Code: Mw

Structural formation (Level 2)Name: ‘Emergent very tall trees with very tall mid-dense trees’Code: E8w1.0 /8Mw1.0

Broad floristic formation (Level 3)Name: ‘Emergent very tall Angophora trees with very tall mid-dense Eucalyptus trees’Code: E8Angophoraw1.0 /8MEucalyptusw1.0

Broad floristic sub-formation (Level 4)Name: ‘Emergent very tall Angophora trees over very tall mid-dense Eucalyptus trees with tall sparse Eucalyptus tree understorey over dwarf very sparse Eremophila shrubs with a tall sparse Bothriochloa tussock grass ground stratum’Code: E8Angophoraw1.0 /8MEucalyptusw1.0 /7SEucalyptusw1.0 /4VEremophilaw3.0 /3SBothriochloag3.0

Further detail can be added. For example, some vegetation types such as wetlands or rainforests might require additional attributes, or the surveyor might wish to assess the growth stage or condition of the vegetation.

Further information

Australian Land Information Group and Carnahan, J 1990, Atlas of Australian resources: Vegetation, Australian Government Publishing Service, Canberra.

Walker, J and Hopkins, M 1990, ‘Vegetation’, in Gunn, R, Beattie, J, Reid, R, van der Graaff, R (eds), Australian soil and land survey handbook: Guidelines for conducting surveys, Inkata Press, Melbourne.


Figure 3: Coding a sample site using the classification: example

Top height E AStratum name (code) Emergent (E) Dominant stratum (Life forma (code) Woody plants (w) Woody plants (Crown coverb 3% 67%Crown separation ratiob

(name, code)4.0 (emergent, E) 0.1 (mid-dense,

Growth formc (code) Tree (w1.0) Tree (w1.0Heightd (name, code) 28 m (very tall, 8) 21 m (very tall, Descriptionc Emergent very tall trees Very tall mid-dense trees

Genus or species Angophora EucalyptusBroad floristic formation (Level 3) full code E8Angophoraw1.0 8MEucalyptusBroad floristic sub-formation (Level 4) full code E8Angophoraw1.0 8MEucalyptus

← Note: eight classes are shown in Table 4, codes for growth-form types in Table 8


Levels in the standard classification

Formation (Level 1)Formation class is usually the highest level of vegetation classification. Vegetation types at this level are distinguished by their life form (which at this level has two classes: woody and non-woody) and cover. This manual deals with canopy cover, ground cover, and combined cover-abundance estimates.

Life formAt the most general level of classification, formations, there are only two plant life forms: woody and non-woody.

What to recordRecord whether the life form is woody or non-woody (Figure 6). Table 9 presents a full set of formation classes, but not necessarily at the level of detail needed for all types of studies. Trees, shrubs and herbs should be recorded separately, where useful and feasible.

How to collect

Remotely sensed imagery (or knowledge of the species) can often indicate whether a life form is woody or non-woody. This attribute can also be observed directly in the field.

Issues

The treatment of woody plants in this manual represents a major departure from the previous system of structural formations. The tree-shrub dichotomy (used previously) does not apply to all vegetation types. In the relatively dry environments of significant parts of Australia and other continents, there is little ecological gain to be made by attempting to distinguish trees from shrubs at a fundamental level in vegetation classification; in moister regions, on the other hand, the distinction of trees and shrubs is often clear-cut. The system presented here, which involves the measurement of woody plant cover and height, caters for this full range of variation in woody plant form.

Further information

Walker, J and Hopkins, M 1990, Vegetation, in Gunn, R, Beattie, J, Reid, R and van der Graaff, R (eds), Australian soil and land survey handbook: Guidelines for conducting surveys, Inkata Press, Melbourne.

Cover and crown typeCrown cover is the percentage of the total area of a sample site that is covered by a vertical projection of the crown. This is also the generic definition of plant cover.

Crown cover per cent is recommended here as the method for reporting cover for plants more than about 1.5 metre high. The recommended method of measuring it is the crown separation ratio.

Foliage cover is used to estimate ground layer cover. Percentage foliage cover is the percentage of a measured distance covered by the vertical projection of the leaves (and branches, if the life form is woody).

There are several methods for estimating plant cover. Each measures a slightly different aspect of vegetation and is thus subject to different environmental conditions, but each result in a


quantitative estimate that allows the ranking of the relative importance of plant species or vegetation structural components. In addition, to the methods described here relating to describe the standard classification, cover abundance estimates may also be collected (Annex 5)

What to record

For plants taller than about 1.5 to 2 metres, the crown separation ratio (CSR) should be measured and recorded. Table 7 can be used to convert the CSR to either percentage foliage cover or crown cover percentage. For plants less than about 1.5 metre high, plant cover should be estimated using the vertical projection method.

How to collect

In rapid field surveys, it is usually possible to decide the cover class in which a particular stratum fits. However, since primary data, such as actual crown cover percentage, are more valuable than pre-classified data, an accurate method to estimate the crown separation ratio is needed. The zigzag method described below is effective for sampling a relatively large number of trees over a relatively short horizontal distance, while at the same time incorporating the natural variability in crown widths and gaps.

Field estimation of CSR for discrete crownsThe crown separation ratio for discrete crowns is the ratio of the mean distance between crowns relative to the mean crown size. That is:

CSR =

Walker et al. (1988) and Penridge and Walker (1988) discuss the crown separation ratio in detail and outline its limitations. There are three key elements in its field estimation:

1. Sample along a zigzag transect (Figure 4). First establish a transect between points P and Q. Start at a crown near P (A in Figure 4) and determine the next crown that would be encountered when moving towards or across the transect line and in the direction P to Q.

2. For each stratum (irrespective of species), measure crown widths and crown gaps; the mean of 12 measurements is usually sufficient.

3. Where crown-overlap occurs, the crown gap has a negative value; the greater the overlap, the larger the negative value.

Penridge and Walker (1988) showed that:

Crown cover (%) =

where k = 80.6 for samples taken along a zigzag transect (Figure 4). Table 7 gives conversions for a range of cover values.

In some field situations, limitations apply to the use of the crown separation ratio (Penridge and Walker 1988). For example:

CSR should be measured for each stratum separately to avoid situations in which crowns overlap.

Crown shapes should approximate circles or non-extreme ellipses. In cases where crown shapes are so non-circular as to prevent a near-circular equivalent being determined, an alternative method (e.g. line intercept) should be used. For ovoid crowns, the shortest and longest diameters should be averaged.


Zigzag sampling should be used to avoid long distances between trees, which could invalidate the underlying geometric assumptions of the method.

Figure 4: The zigzag sampling procedure

← Note: The method is used for each stratum or layer: e.g. (a) = dominant stratum; (b) = mid-stratum.

Conversion of crown cover percentage to percentage foliage coverThe estimation of crown cover percentage assumes an opaque crown. However, to convert crown to foliage cover, requires the consideration of crown type (i.e. its degree of openness). Crown openness can be estimated by matching the photographs in Figure 5 with actual tree crowns.

Percentage foliage cover = crown cover percentage x crown type

e.g. if CSR = 1.0, percentage crown cover = 20% (Table 7). If crown type = 60%, percentage foliage cover = 20% x 60% = 12%


Figure 5: Crown types← Estimate the openness of individual tree or shrub crowns by matching the crown with a photograph. The rows show similar crown types for different leaf sizes (large to small from left to right). Acacia phyllodes are in the right hand column. Most Australian woody plants are in the range 40 to 70 per cent.

Field estimation of foliage cover in the ground layer The ground layer normally comprises low shrubs, grasses, forbs, rushes, sedges, etc. In this classification method it is necessary to estimate the foliage cover as a vertical projection. For many purposes, a visual estimate will suffice for placing ground cover into a cover class (Table 6). Foliage cover of the ground layer can be estimated accurately using point quadrats or foliar intercepts along transects (Mueller-Dombois and Ellenberg 1974). A rapid field method uses a tape laid out within the sample site (Figure 6); it can be used for vegetation comprising grasses (leaves and inflorescences) or low shrubs (leaves and branches). Whilst looking vertically down onto the tape and foliage (and/or branches), estimate the amount of


foliage and branches intercepted along the tape. This can be expressed as a percentage of the transect length. It is easiest to estimate and record the amount of foliage and branches intercepted per metre of tape and to add these amounts at the completion of the transect.

Figure 6: Field measurement of foliage cover using a line transect

← Note: The length of intercepted foliage is measured along a tape and foliage cover calculated as a percentage of the total length of the transect.

Usually two to four transects are needed per site depending on the spatial variability of the ground cover. In most grassy situations, a 10 metre transect is sufficient, and 20 metres should suffice for small shrubs. The more patchy the ground layer, the greater the total length of transect needed. In environments such as the rangelands where the formation class might require subdivision, it is often useful to collect information about basal area and/or plant density and to recognise a number of cover classes within the ‘<10% foliage cover’ class. The siting of transects should be done independently of the ground layer so the sample is not biased by what the recorder might want to include or exclude from the sample. The starting point and direction of the transect can be fixed in relation to some aspect of the sampling plot, or random numbers can be used.

Issues

There are three commonly used field definitions of percentage plant cover: crown cover, foliage cover and projective foliage cover. These give different values for percentage cover and none is correlated in a simple way with leaf area or leaf area index. If applied consistently, each will provide a useful index for ranking sites and vegetation types, even though they measure or estimate slightly different aspects of the vegetation canopy. Crown cover percentage is the percentage of the sample site within the vertical projection of

the periphery of crowns. In this case, crowns are treated as opaque. Foliage cover percentage (as per Carnahan 1977) is the percentage of the sample site

occupied by the vertical projection of foliage and branches (if woody). Projective foliage cover percentage (as per Specht et al. 1974) is the percentage of the

sample site occupied by the vertical projection of foliage only.

Projective foliage cover percentage is relatively time-consuming to estimate in the field, for plants more than 1.5 metres tall, using point quadrats, optical instruments or photography. Projective foliage cover and foliage cover percentage are also difficult to estimate where lower vegetation blocks the line of sight to the upper strata. Both provide unsatisfactory results in situations that contain either deciduous species or species with vertical or near-vertical leaves.

Crown cover percentage (the method recommended in this manual) has the advantage of being easily estimated both in the field, where line of sight problems are easily overcome by shifting the viewing position, and from large-scale aerial photography, and it appears to be measurable using LIDAR (Lee et al. 2004).


Special cases

In some situations with many overlapping layers it is difficult to measure actual cover values for species or strata. Table 6 and Table 7 show the criteria to assess crown cover classes visually in the field.

Table 6: Visual estimation of crown cover classCode Criteria assessed in

fieldDescribed as Crown

separation ratio

Crown cover %

Foliage cover %

D Crowns touching to overlapping

Closed or dense <0 >80% >70%

M Crowns touching or slightly separated

Mid-dense 0–0.25 50–80% 30–70%

S Crowns clearly separated

Sparse or open 0.25–1 20–50% 10–30%

V Crowns well separated

Very sparse 1–20 0.25–20% 0.2–10%

I Isolated plants: for trees about 100 metres apart, shrubs about 20 m apart

Isolated plants >20 <0.25% <0.20%

L Isolated clumps of 2 to many plants about 200 metres apart

Isolated clumps >20 <0.25% <0.20%

E Emergent Emergents >3 <5% of total crown cover

<3% of total foliage cover

Further information

Carnahan, J 1977, ‘Natural Vegetation’, Atlas of Australian resources, second series, Department of Natural Resources, Canberra.

Lee, A, Lucas, R and Brack, C 2004, Quantifying vertical forest stand structure using small-footprint lidar to assess potential stand dynamics. Proceedings, NATSCAN—Laser scanners for forest and landscape assessment instruments, processing methods and applications, 3–6 October, Freiburg, Germany, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 36(8/W2), pp. 213–217.

Mueller-Dombois, D and Ellenberg, H 1974, Aims and methods of vegetation ecology, John Wiley & Sons, New York, United States.

Penridge, L and Walker, J 1988, ‘The crown-gap ratio (C) and crown cover: derivation and simulation study’, Australian Journal of Ecology, vol. 13, pp. 1090–1120.

Specht, R L 1970, Vegetation in the Australian environment, fourth edition, CSIRO, Melbourne.

Specht, L, Roe, E and Boughton, V (eds) 1974, ‘Conservation of major plant communities in Australia and Papua New Guinea’, Australian Journal of Botany Supplement, No 7.

Walker, J, Crapper, P and Penridge, L 1988, ‘The crown-gap ratio (C) and crown cover: the field study’, Australian Journal of Ecology, vol. 13, pp. 101–108.


Table 7: Converting crown separation ratio to crown coverOverlap Touching Crowns separate

Crown separation ratio

-.01 -.05 -.02 0 .05 0.1 0.15 0.2 0.25 0.3 0.4 0.5 0.6 0.75 1.0 1.25 1.5 2.0 3.0 4.0 8.0 10 15 20 30

Percentage crown cover (%)

100 89 84 81 73 67 60 56 52 48 41 34 31 26 20 16 13 9 5 3 1 0.6 0.3 0.2 0.1


Structural formation (Level 2)Structural formations are the second level of vegetation classification in the hierarchical system. They are distinguished by the addition of height to that of growth form and cover.

What to recordIn each stratum, record growth form, cover class and height of the dominant species. Table 9 presents the full set of structural formations.

How to collectSee life form, cover and height sections under Formation (Level 1).

IssuesCompared with the formation level, at this level the vegetation types can be distinguished to a greater degree, although still relatively coarsely.

Further informationWalker, J and Hopkins, M 1990, ‘Vegetation’, in Gunn, R, Beattie, J, Reid, R, van der Graaff, R (eds) Australian soil and land survey handbook: Guidelines for conducting surveys, Inkata Press, Melbourne.

Growth formLevel 1 accommodates only two life forms (woody plants or non-woody plants). At level 2, ‘growth form’ provides more detail on the life forms of the vegetation under investigation. It is used to describe the form or shape of individual plants (e.g. tree or shrub) and broad floristic land cover types (e.g. native vegetation such as mallee or chenopod shrub, and non-native vegetation such as wheat field or orchard). The glossary (Table 8) (modified from ESCAVI 2003) defines the growth forms for structural formations.

Cover and crown typeAt level 2, cover and crown type are classified according to the process described for level 1 in the section Cover and crown type. See also Table 2.


Table 8:Glossary of growth forms, structural formations

Growth form Code Definition

Algae: fresh or brackish a3.0 A member of the Chlorophyta, Cyanophyta, Phaeophyta or Rhodophyta living in fresh or brackish aquatic environments.

Algae: marine a4.0 A member of the Chlorophyta, Cyanophyta, Phaeophyta or Rhodophyta living in marine environments. May range from thin surface-hugging layers to tall algal forests.

Aquatic higher plants a1.0 (or w)

Dicotyledonous or monocotyledonous plants growing for a significant portion of their life cycle in fresh or brackish water.

(For convenience, this may include woody vegetation such as mangroves, eucalypt, melaleuca or other woody, periodically submerged vegetation, which span saline aquatic environments from brackish to hyper-saline. The code used—a1.0 or w—will depend on the particular emphases of the survey.)

Bare surface b1.0 Soil, rock or water surfaces with less than 0.5 per cent plant cover.

Bryophyte m1.0 A member of the Division Bryophyta: i.e. mosses and liverworts. Mosses are small plants usually with a slender leaf-bearing stem with no true vascular tissue. Liverworts are often moss-like in appearance or consist of a flat, ribbon-like green thallus.

Chenopod shrub w3.2 Single or multi-stemmed, semi-succulent shrub of the family Chenopodiaceae exhibiting drought and salt tolerance.

Cryptogam Refers collectively to lichens and bryophytes.

Fern (excluding tree ferns)

f1.0 A member of the Division Pterophyta: i.e. ferns and fern allies. Characterised by large and usually branched leaves (fronds) and spores in sporangia on the undersides of leaves. Herbaceous and terrestrial to aquatic. Tree ferns are classified with woody plants as they have the same vegetation structure.

Food See herb: planted/cultivated (annual or perennial, food); shrub: planted/cultivated (food) and tree: planted/cultivated (food).

Forb h1.0 Non-graminoid herbaceous plant.

Grass g1.0 Member of the family Poaceae.

Grass: planted/cultivated g4.0 Member of the Poaceae planted or cultivated for specific human uses: e.g. human or other animal food, lawn or other ground cover.

Grass: planted/cultivated (pasture)

g4.1 Member of the Poaceae cultivated or maintained for the production of food for animals, whether harvested or grazed.

Grass: planted/cultivated (cereals)

g4.2 Member of the Poaceae cultivated as food for human consumption (e.g. cereals, sugar cane).

Grass: planted/cultivated (other industrial)

g4.3 Member of Poaceae cultivated or maintained for industrial purposes but not for food: e.g. turf farm for lawns, road batten stabilisation.



Heath or kwongan or wallum shrub

w3.1 Shrub usually less than 2 metres tall, commonly with ericoid leaves (nanophyll, less than 225 square millimetres). Often a member of one of the following families: Epacridaceae, Myrtaceae, Fabaceae and Proteaceae. Commonly occurs on nutrient-poor substrates.

Herb h2.0 Herbaceous or slightly woody, annual or sometimes perennial plant (dicotyledon or monocotyledon).

Herb: planted/cultivated (perennial, non-food)

h2.1 Planted/cultivated perennial herbaceous plant (monocotyledon or dicotyledon); non-food.

Herb: planted/cultivated(annual, non-food)

h2.2 Planted/cultivated annual herbaceous plant (monocotyledon or dicotyledon); non-food.

Herb: planted/cultivated(annual, food)

h2.3 Planted/cultivated annual herbaceous plant (monocotyledon or dicotyledon); food.

Herb: planted/cultivated (perennial, food)

h2.4 Planted/cultivated perennial herbaceous plant (monocotyledon or dicotyledon); food.

Hummock grass g2.0 Coarse xeromorphic grass with a mound-like form, often dead in the middle; genera are Triodia, Plectrachne and Zygochloa.

Lichen l1.0 Composite plant consisting of a fungus living symbiotically with algae or cyanobacteria; without true roots, stems or leaves.

Mallee (tree or shrub) w2.1 Any of the eucalypt trees or shrubs with multiple stems arising from a lignotuber.

Rainforest See Tree: rainforest.

Rush g6.0 Herbaceous, usually perennial, erect monocot that is neither a grass nor a sedge. For the purpose of this manual, rushes include the monocotyledon families Juncaceae, Typhaceae, Liliaceae, Iridaceae, Xyridaceae and the genus Lomandra: i.e. ‘graminoid’ or grass-like genera.

Samphire shrub w3.3 A subdivision of chenopod shrub. Genera (of Tribe Salicornioideae, namely Sarcocornia and Tecticornia) with articulate branches, fleshy stems and reduced flowers within the Chenopodiaceae family; succulent chenopods. Also the genus Suaeda.

Seagrass: marine a2.0 Genera and species of flowering angiosperms of the families Hydrocharitaceae and Potamogetonaceae, forming sparse to dense mats of material at the sub-tidal level and to 30 metres below mean sea level. Occasionally exposed.

Sedge g5.0 Herbaceous, usually perennial, erect plant generally with a tufted habit and of the families Cyperaceae (true sedges) or Restionaceae (node sedges).

Shrub w3.0 Woody plant, multi-stemmed at the base (or within about 200 millimetres from ground level), or, if single-stemmed, less than about 5 metres tall; not always readily distinguishable from small trees.



Shrub: planted/cultivated (food)

w3.4 Shrubs planted in rows for the production of food crops.

Shrub: planted/cultivated (non-food)

w3.5 Shrubs planted in mostly urban/suburban settings such as gardens and along streets, and in nurseries.

Surface crusts c1.0 Assemblages of one or more species of minute plants at or within the surface of soil or rock. May consist of bryophytes, lichens, cyanobacteria, green algae and fungi; in some cases might include very small vascular plants.

Tree w1.0 Woody plant more than 2 metres tall usually with a single stem, or branches well above the base; not always distinguishable from large shrubs.

Tree: rainforest w1.1 There is no widely accepted or universal definition for Australian rainforest. Usually distinguished by their dark green colour and species composition, which contrast with the surrounding grey or reddish-green and often eucalypt-dominated vegetation.

Tree: planted/cultivated (non-food)

w1.2 Trees planted in rows for the intense production of non-food crops.

Tree: planted/cultivated (food)

w1.3 Trees planted in rows for the production of food crops.

Tree: planted/cultivated (landscaping)

w1.4 Trees planted in mostly urban/suburban settings such as gardens and along streets, and in nurseries.

Tussock grass g3.0 Grasses forming discrete but open tufts, usually with distinct individual shoots. These include the common agricultural grasses.

Vine v1.0 Climbing, twining, winding or sprawling plants, usually with a woody stem.

Woody plant (indeterminate tree or shrub)

w2.0 Plants with woody tissue. For the purposes of vegetation classification, also those plants that achieve a growth form similar to that of woody plants (e.g. cycads, palms and tree ferns). Includes both trees and shrubs.

HeightIn the field, actual height measurements should be made, not estimates of height classes. However, plants taller than 10 metres, however, can be categorised within 5 metre class intervals, since finer distinctions are probably not ecologically useful and visually-based methods become increasingly inaccurate as height increases.

What to record

Record the height from the ground to the apex of the plant. Where flower stalks (e.g. grasses, grasstrees) or leaves (e.g. palms, cycads, grass trees and tree ferns) add significantly to plant height and contribute significantly to a ‘stratum’, two measurements of height are recorded: total height from ground level to the top of the highest part of the plant, and height from ground level to the top of the leaves (e.g. Xanthorrhoea johnsonii 2.5 /1.3 metres; Sorghum intrans 1.9 /1.3 metres).


This provides an accurate record of the field situation and allows greater flexibility in analysis. Recorded heights can be converted to height classes (Table 4).

How to collect

For low vegetation, height can be measured using measuring tapes or poles. A variety of tools exist for measuring the height of tall vegetation, including visual sighting instruments such as clinometers, laser or sonic ranging instruments, and LIDAR (see Brack 1998 and Abed and Stephens 2003).

Issues

For tall trees (more than 20 metres), visual sighting methods produce errors caused by the difficulty in determining the highest part of a tree with a rounded and spreading canopy (Alex Lee 2005, pers. comm.).

UNESCO (1973) cautions that, in vegetation studies, ‘height limits are only a generalised guide, not an absolute limit’. In large vegetation units, canopy height often varies significantly across environmental gradients, such as from moist to dry areas and from low to high altitudes; it also varies with the age of the vegetation. Such units should not be subdivided solely on the basis of small changes in height across arbitrary class boundaries. Where anomalies occur along artificial boundaries such as state and territory borders, consensus between specialists is perhaps the best way to decide height class boundaries.

Forestry

In forestry, the common practice is to record the height of the tallest trees (not stratum height as defined here), as it is a good indicator of site quality or potential.

Further information

Brack, C 1999, ‘Forest measurement and modelling’, viewed 20 April 2009, <http://fennerschool-associated.anu.edu.au/mensuration/>.

UNESCO 1973, International classification and mapping of vegetation, United Nations Educational, Scientific and Cultural Organisation, Geneva, Switzerland.

Foliage cover of the lower stratumAt level 2, the foliage cover of the ground stratum is classified according to the process described for level 1 in the section Cover and crown type.

EmergentsSome plants rise above the level of the dominant stratum but, since their total cover is small, they are considered to be emergents rather than a separate stratum. As a guide, plants might be considered emergents if their foliage cover is less than 5 per cent of the crown cover of the dominant stratum (see Figure 3 for a tree-based example). Care is needed, however: the 5% threshold is likely to vary depending on factors such as vegetation type and season, especially if the ground layer is the dominant stratum. In some borderline cases, taller plants can occur above a ground stratum that elsewhere forms the dominant stratum of a well-known vegetation type. In this situation, it would be acceptable to call the tallest stratum emergents where it would be unhelpful to create a new vegetation type solely on the basis of a slightly higher density of the tallest plants.


What to record

The total crown cover percentage, median height and/or maximum height, and the genus (and species if possible) of the emergent layer should be recorded.

How to collect

Height and cover should be measured as described above.

Issues

The definition of emergents varies for different kinds of vegetation, as follows: Where the vegetation is dominated by trees or shrubs and the tallest layer emerges above a

dominant canopy (i.e. cover greater than 5 per cent) and has generally less than 5 per cent total cover, then the tallest trees or shrubs are called emergents. The genus or species of emergents should be recorded, if possible, followed by the word ‘emergents’: e.g. ‘with hoop pine emergents‘, ‘with Araucaria emergents’, ‘with Eucalyptus emergents’.

Where the vegetation is dominated by perennial grasses (e.g. Triodia) and a taller layer of woody plants above it has less than 5 per cent of the Triodia cover, then the taller plants are called emergents and named as per the example above.

Where the vegetation is seasonally or sporadically dominated by annual plants in a mix of perennial plants that form a taller layer, then in most cases the taller perennial layer is the dominant layer: e.g. ‘sparse eucalypt trees with seasonally dominant Sorghum in the understorey’, or ‘sparse acacia trees with periodically dominant annual herbs of Asteraceae and other families’.

For ephemeral wetlands, where the dominant layer is present only periodically and there is no taller woody layer, the ephemeral layer is the dominant layer. It is recorded as ephemeral: e.g. ‘ephemeral mixed herbs’.

Further information

Walker, J and Hopkins, M 1990, ‘Vegetation’, in Gunn, R, Beattie, J, Reid, R, and van der Graaff, R (eds) Australian soil and land survey handbook: Guidelines for conducting surveys, Inkata Press, Melbourne.

Broad floristic formation (Level 3)Broad floristic formations are structural formations that have been subdivided according to the genus or genus group of the dominant stratum. There are 37 growth form classes (Table 9). They reflect major groupings that are of value to both environmental and economic users of vegetation information.

For completeness, bare surfaces are also recognised at this level i.e. b1.0 in Table 9, although technically they do not constitute a vegetation type. Bare ground needs to be explicitly defined with respect to which stratum it is associated with. For example, in a two stratum vegetation type (trees over herbs), there may be 25 per cent cover of bare ground with respect to the herbaceous ground layer, but only 5 per cent with respect to the tree canopy.


Table 9:Broad floristic formations (Level 3) Cover characteristics

Foliage cover % 100–70 70–30 30–10 10–0.2 <0.2 <0.2 <3a

Crown cover % >80 80–50 50–20 20–0.25 <0.25 <0.25 <5a


<0 0–0.25 0.25–1 1–20 >20 >20 >3

Cover code & name

DClosed or dense

MMid-dense

SSparse or open

VVery sparse

IIsolated plants

LIsolated clumps

EEmergents

Growth form codeb

Growth form of dominant stratumc

Height range (m)

Broad floristic formation classesd,e

w1.0 Tree 2–50 Closed X trees Mid-dense X trees Sparse X trees Very sparse X trees

Isolated X trees Isolated clumps of X trees

X trees

w1.1 Tree: rainforest 2–50 Closed X trees Mid-dense X trees Sparse X trees Very sparse X trees


X trees

w1.2 Tree: planted/ cultivated (non-food)

2–50 Closed X trees Mid-dense X trees Sparse X trees Very sparse X trees


X trees

w1.3 Tree: planted/cultivated (food)



X trees

w1.4 Tree: planted/ cultivated (landscaping)



X trees

w2.0 Woody plant (indeterminate tree or shrub)

0.1–10 Closed X woody plants

Mid-dense X woody plants

Sparse X woody plants

Very sparse X woody plants

Isolated X woody plants

Isolated clumps of X woody plants

X woody plants

w2.1 Mallee (tree or shrub)

0.1–30 Closed X mallee Mid-dense X mallee

Sparse X mallee Very sparse X mallee

Isolated X mallee Isolated clumps of X mallee

X mallee

w3.0 Shrub <20 Closed X shrubs Mid-dense X shrubs

Sparse X shrubs Very sparse X shrubs

Isolated X shrubs Isolated clumps of X shrubs

X shrubs

w3.1 Heath or kwongan or wallum shrub

<8 Closed X heath shrubs

Mid-dense X heath shrubs

Sparse X heath shrubs

Very sparse X heath shrubs

Isolated X heath shrubs

Isolated clumps of X heath shrubs

X heath shrubs

w3.2 Chenopod shrub <3 Closed X chenopod shrubs

Mid-dense X chenopod shrubs

Sparse X chenopod shrubs

Very sparse X chenopod shrubs

Isolated X chenopod shrubs

Isolated clumps of X chenopod shrubs

X chenopod shrubs

w3.3 Samphire shrub <3 Closed X samphire shrubs

Mid-dense X samphire shrubs

Sparse X samphire shrubs

Very sparse X samphire shrubs

Isolated X samphire shrubs

Isolated clumps of X samphire shrubs

X samphire shrubs


Cover characteristics

Foliage cover % 100–70 70–30 30–10 10–0.2 <0.2 <0.2 <3a

Crown cover % >80 80–50 50–20 20–0.25 <0.25 <0.25 <5a


<0 0–0.25 0.25–1 1–20 >20 >20 >3

Cover code & name

DClosed or dense

MMid-dense

SSparse or open

VVery sparse

IIsolated plants

LIsolated clumps

EEmergents

Growth form codeb


Height range (m)


w3.4 Shrub: planted/ cultivated (food)

<8 Closed X food shrubs

Mid-dense X food shrubs

Sparse X food shrubs

Very sparse X food shrubs

Isolated X food shrubs

Isolated clumps of X food shrubs

X food shrubs

w3.5 Shrub: planted/ cultivated (non-food)

<10 Closed X industrial shrubs

Mid-dense X industrial shrubs

Sparse X industrial shrubs

Very sparse X industrial shrubs

Isolated X industrial shrubs

Isolated X industrial shrubs

X industrial shrubs

g1.0 Grass 0.01–5 Closed X grasses

Mid-dense X grasses

Sparse X grasses Very sparse X grasses

Isolated X grasses Isolated clumps of X grasses

X grasses

g2.0 Hummock grass <2 Closed X hummock grasses

Mid-dense X hummock grasses

Sparse X hummock grasses

Very sparse X hummock grasses

Isolated X hummock grasses

Isolated clumps of X hummock grasses

X hummock grasses

g3.0 Tussock grass <5 Closed X tussock grasses

Mid-dense X tussock grasses

Sparse X tussock grasses

Very sparse X tussock grasses

Isolated X tussock grasses

Isolated clumps of X tussock grasses

X tussock grasses

g4.0 Grass: planted/ cultivated

<3 Closed X grasses

Mid-dense X grasses



X grasses

g4.1 Grass: planted/ cultivated (pasture)

<4 Closed X pasture

Mid-dense X pasture

Sparse X pasture Very sparse X pasture

Isolated X pasture Isolated clumps of X pasture

X pasture

g4.2 Grass: planted/ cultivated (cereals)

<5 Closed X cereals Mid-dense X cereals

Sparse X cereals Very sparse X cereals

Isolated X cereals Isolated clumps of X cereals

X cereals

g4.3 Grass: planted/ cultivated (other industrial)

<3 Closed X grasses

Mid-dense X grasses



X grasses

g5.0 Sedge <3 Closed X sedges Mid-dense X sedges

Sparse X sedges Very sparse X sedges

Isolated X sedges Isolated clumps of X sedges

X sedges

g6.0 Rush <3 Closed X rushes Mid-dense X rushes

Sparse X rushes Very sparse X rushes

Isolated X rushes Isolated clumps of X rushes

X rushes



Foliage cover % 100–70 70–30 30–10 10–0.2 <0.2 <0.2 <3a

Crown cover % >80 80–50 50–20 20–0.25 <0.25 <0.25 <5a


<0 0–0.25 0.25–1 1–20 >20 >20 >3

Cover code & name

DClosed or dense

MMid-dense

SSparse or open

VVery sparse

IIsolated plants

LIsolated clumps

EEmergents

Growth form codeb


Height range (m)


h1.0 Forb <2 Closed X forbs Mid-dense X forbs Sparse X forbs Very sparse X forbs

Isolated X forbs Isolated clumps of X forbs

X forbs

h2.0 Herb <2 Closed X herbs Mid-dense X herbs Sparse X herbs Very sparse X herbs

Isolated X herbs Isolated clumps of X herbs

X herbs

h2.1 Herb: planted/ cultivated (perennial, non-food)

<2 Closed X herbs Mid-dense X herbs Sparse X herbs Very sparse X herbs


X herbs

h2.2 Herb:planted/ cultivated (annual, non-food)



X herbs

h2.3 Herb: planted/ cultivated (perennial , food)



X herbs

h2.4 Herb: planted/ cultivated (annual, food)


Isolated X herbs Isolated clumps of X herbs)

X herbs

f1.0 Fern (excluding tree ferns)

<2 Closed X ferns Mid-dense X ferns Sparse X ferns Very sparse X ferns

Isolated X ferns Isolated clumps of X ferns

X ferns

m1.0 Bryophyte <2 Closed X bryophytes

Mid-dense X bryophytes

Sparse X bryophytes

Very sparse X bryophytes

Isolated X bryophytes

Isolated clumps of X bryophytes

X bryophytes

l1.0 Lichen <5 Closed X lichens

Mid-dense X lichens

Sparse X lichens Very sparse X lichens

Isolated X lichens Isolated clumps of X lichens

X lichens

c1.0 Surface crusts <0.05 Closed X crusts Mid-dense X crusts

Sparse X crusts Very sparse X crusts

Isolated X crusts Isolated clumps of X crusts

X crusts



Foliage cover % 100–70 70–30 30–10 10–0.2 <0.2 <0.2 <3a

Crown cover % >80 80–50 50–20 20–0.25 <0.25 <0.25 <5a


<0 0–0.25 0.25–1 1–20 >20 >20 >3

Cover code & name

DClosed or dense

MMid-dense

SSparse or open

VVery sparse

IIsolated plants

LIsolated clumps

EEmergents

Growth form codeb


Height range (m)


v1.0 Vine 0.5–30 Closed X vines Mid-dense X vines Sparse X vines Very sparse X vines

Isolated X vines Isolated clumps of X vines

X vines

a1.0 Aquatic higher plants <2 Closed X aquatic

Mid-dense X aquatic

Sparse X aquatic bed

Very sparse X aquatic

Isolated X aquatic Isolated clumps of X aquatic

X aquatic

a2.0 Seagrass:marine

<2 Closed X seagrass

Mid-dense X seagrass

Sparse X seagrass Very sparse X seagrass

Isolated X seagrass Isolated clumps of X seagrass

X seagrass

a3.0 Algae:fresh or brackish

Record thick-ness of layer

Closed X algae Mid-dense X algae Sparse X algae Very sparse X algae

Isolated X algae Isolated clumps of X algae

X algae

a4.0 Algae:marine

<30 Closed X marine algae

Mid-dense X marine algae

Sparse X marine algae

Very sparse X marine algae

Isolated X marine algae

Isolated clumps of X marine algae

X marine algae

b1.0 Bare surface Bare groundf

← Notes:

a For emergents, ‘<3’ means ‘up to 3% of total foliage cover’, and ‘<5’ means ‘up to 5% of total crown cover’.

← b This column is ordered from tallest to shortest vegetation. Cells shaded grey are woody life forms (w) while the unshaded cells are non-woody life forms (nw).

← c See structural formation (Level 2) for definitions of growth forms.

← d For consistency in naming the broad floristic formation classes in this table, two changes to Walker and Hopkins (1990) have occurred: the terms ‘forest’ and ‘woodland’ have been

replaced with ‘trees’, and the suffix ‘land’ has been removed.

← e In each class name, replace the ‘X’ with the taxonomic name of either the dominant genus or genus groups making up the dominant stratum. Not all classes require a separate

taxonomic name (e.g. mid-dense mallee). In other cases the ‘X’ name is optional: e.g. sparse chenopod shrubs versus sparse Atriplex chenopod shrubs or sparse Atriplex shrubs.

← f The classes for bare surface are deliberately not given a name but can be coded.


What to record

The genus or genus group of the dominant stratum should be recorded according to the classes provided in Table 9. The system allows flexibility in the selection of genus or genus group; the Xs in each cell of the table can be replaced with the particular genus/genus-group occurring at the recording site. For example, cell w1.2i is ‘X woodland’, which for a specific site might be ‘Eucalyptus woodland’ or ‘Acacia aneura woodland’. Record the name of the class on the record sheet, since this will provide a useful basis for remembering the site and communicating about it. If necessary, the species name can be refined or corrected after subsequent office work.

Codes have been provided which can be distinguished from previous ones in Walker and Hopkins (1990) by their 4-character form: a lower-case letter followed by a two-digit decimal number. The final digit can be extended to suit particular projects: e.g. ‘shrub: planted cultivated (food) w3.4’ could be extended to ‘w3.4.1 (vine, shiraz)’ or ‘w3.4.2 (vine, riesling)’, etc.

How to collect

Use the relevant sections on growth form, cover and height, and the floristics sections, as a guide to data collection.

Issues

The groupings presented in Table 9 do not represent all possible classes at this level of vegetation classification. Particular projects might require finer resolution or other categories.

The broad floristic formation now includes classes for vegetation dominated by non-native plants and non-vegetation surfaces. Increasingly, land managers are required to integrate their management across all the land for which they are responsible, irrespective of whether it is vegetated with native or non-native plants, or a mixture of the two, or even if it is unvegetated (Thackway 2005). The classification provided here is sufficiently flexible and comprehensive to allow vegetation of any of these types to be sampled, classified and mapped within a single framework.

Special cases

Flushes of annuals: vegetation that is periodically dominated by massive flushes of annual plants following rains, such as in many semi-arid or arid areas of the continent, is classified according to the perennial plants present, but the actual cover and species of annuals should be recorded during the flush.

FloristicsFloristics is the list of plant species found at a sample site.

What to record

The name of each species should be recorded, preferably using the full scientific name. If using ad hoc species names, ensure that appropriate voucher specimens are collected and records are updated later with correct scientific names.

All species (native and non-native) should be recorded unless the project has specifically defined a shortlist of what to include/exclude. The use of standardised plant names improves the ease with which datasets can be combined. Currently, each state and territory maintains its own comprehensive list of plant species. However, in 2004–05, the heads of the major state, territory and national herbaria established a program, known in 2009 as the Australian Plant Census3, to produce a national list of

3 http://www.cpbr.gov.au/chah/apc/index.html.


scientific names, with major synonyms. This census will be used in the development of Australia’s Virtual Herbarium.

The total range of vegetation types for parts of Australia is sufficiently known that, in many instances, field surveyors can obtain comprehensive lists of the species they would expect to find in a region or in specific vegetation types. State and territory environment departments or herbaria may be the source of this information and there might also be local or regional lists. Such lists should be used as part of the field recording proforma, to speed the recording of site floristics and to direct attention to unusual species records requiring detailed notes and possibly voucher specimens or photographs. This list should be prepared as an initial checklist (see sample proforma in Annex 3).

How to collect

Web-based plant species identification tools are increasingly available to assist surveyors to correctly identify plants. Flora of Australia is available online, as is a range of state-level identification tools. Interactive multi-entry digital keys to major plant groups are also available and more can be expected in the future. This means that, in most cases, surveyors should be able to either identify in the field the species they encounter or, for those species they are unsure of, collect adequate vouchers for later identification. In most surveys, voucher specimens should be collected as a matter of course; they can be used to confirm species identities and to help ensure consistency over time in the identification process.

Procedures to help with the floristic component of site-based sampling can be found on the websites of most major herbaria (see web links below). Good field-based floristics surveyors will: ensure that appropriate collecting permits and/or permissions are obtained before collecting.

Each jurisdiction has its own regulations and procedures that must be followed. In many instances, these can be accessed from the website of the relevant authority (e.g. environment departments, national parks agency)

for the various types of plants encountered, know what constitutes an adequate specimen. If required, contact local or state or territory herbaria, or an experienced field collector, for advice. Guidelines are also available from various websites

know what rare flora might be encountered in the survey area. Learn how to identify it and what to do if specimens are discovered during field work (e.g. there might be limits on collecting such material). For rare flora, photographs might suffice as vouchers

in a field note book especially maintained for plant collections, record the basic information of each voucher specimen: collector’s name and unique field number for the specimen; plant name; location where collected (geo-coordinates, distance/direction from known/named geographic feature); date; habitat (soil, vegetation type, other notes that are important); plant height; and phenological state (e.g. whether flowering, fruiting, leafing or dormant, and the colours of key plant parts)

attach a string tag to each specimen, recording the collector’s name/initials and field number. preserve the plants by drying in a plant press designed for the purpose. Some types of plants

(e.g. mosses, lichens, fungi, algae, aquatic plants, succulents, very large plants/leaves) need special treatment

if using field names and numbers for plants, ensure that records are updated when formal identification is complete

ensure appropriate vouchers are collected. Voucher collections can be of two types: one as a reference set for field workers (these specimens can be taken into the field and consists of only snippets of relevant plant parts, or scanned and printed images of such plants, to aid in field identification), and one for depositing in a herbarium, in which case higher collecting and recording standards may apply. Determine the rules and conditions under which voucher specimens can be deposited in an appropriate herbarium and, where possible, arrange to deposit a specimen set there.


Issues

Most vegetation studies in Australia and elsewhere have concentrated on native plant species in their natural habitats. While the methods presented here are particularly suited to such studies, they are equally suitable for use in agricultural and horticultural vegetation (e.g. Payne et al. 1998; Boyland 1974; Walker et al. 1973). The vegetation structures of wheat fields, cotton crops, vineyards and grazing paddocks can all be sampled and reported within the system presented here. The advantage of using a single comprehensive system for recording all vegetation lies in the power of integrating all the vegetation of a landscape, region or continent into a single system, which can then be used for holistic planning, assessment and modelling.

Special cases

Some field workers like to use species codes for their field records, while others prefer to record full scientific names (genus/species/infra-species). This is a matter of either personal preference or institutional practice, and either is acceptable. If in doubt, record the scientific name to the fullest extent possible. The major value of species codes is that they take less space on the recording sheet. Their disadvantage is that they add to the risk of recording error.

Further information

Boyland, D 1974, Vegetation in western arid region land use study part 1, Division of Land Utilisation Technical Bulletin No. 12, Queensland Department of Primary Industry, Brisbane.

Payne, A, Van Vreeswyk, A, Pringle, H, Leighton, K and Hennig, P 1998, An inventory and condition survey of the Sandstone-Yalgoo-Paynes find area, Western Australia, Technical Bulletin No. 90, Agriculture Western Australia, Perth.

Walker, J, Ross, D and Beeston, G 1973, The collection and retrieval of plant ecological data, Woodland Ecology Unit Publication No. 1, CSIRO, Canberra.

Web links to major national, state and territory herbaria and other relevant databases:

Australia’s virtual herbarium (AVH): <http://www.anbg.gov.au/avh/index.html>

Centre for Plant Biodiversity Research on behalf of the Council of Heads of Australian Herbaria (CPBR): <http://www.anbg.gov.au/chah/resources/index.html>

Flora of Australia: <http://www.environment.gov.au/biodiversity/abrs/online-resources/flora/index.html>.

NSW: <http://www.rbgsyd.nsw.gov.au/science/nsw_herbarium>

Qld: <http://www.epa.qld.gov.au/nature_conservation/plants/queensland_herbarium/>

Vic.: <http://www.rbg.vic.gov.au/research_and_conservation/herbarium>

SA: <www.flora.sa.gov.au>

WA: <http://www.dec.wa.gov.au/science-and-research/wa-herbarium/index.html>

Tas.: <http://www.tmag.tas.gov.au/index.aspx?base=1273>

ACT: <www.anbg.gov.au>; <www.anbg.gov.au/cpbr/herbarium/index.html>

NT: <http://www.nt.gov.au/nreta/wildlife/plants/herbarium/index.html>

(Hyperlinks last accessed 20 April 2009.)


Basal areaBasal area is the cross-sectional area of a plant stem, measured at or near ground level. The measure is commonly used by foresters and can be converted to biomass using species related tables. For trees without buttresses or multiple stems, it is usually measured at ‘breast height’ (about 1.2 to 1.4 metres above the ground). For low plants such as tufted/tussocky grasses, basal area is the area of ground covered by the stems/shoots where they emerge from the ground. Basal area is not the same as crown cover.

The basal area of a species is a measure of the dominance of the species at a site. The dominant species is usually the species with the largest basal area.

Basal area also has uses in other applications, such as: in determining relationships with soil erosion potential; in constructing normalised difference vegetation indices when using satellite data; estimating biomass (if equations exist relating basal area to biomass); and in calculating the proportions of trees at different growth stages or with defined defects. Basal area can also be used as an indicator of the potential of a site to grow trees (e.g. a ranking of fertile to infertile sites).What to recordTwo major types of method can be used to measure basal area: (i) measurements of diameter (at breast height or ground level); and (ii) basal area sweeps using a sighting device. 1. Measure either the diameter or circumference of the plant at either ground level or breast height. If

the diameter is measured, the basal area (BA) on an individual plant is calculated according to the following equation:

2

200

DBA

where BA = basal area in square metres, D = diameter in centimetres, and = 3.142.

If the circumference is measured, then basal area is calculated as follows:

000,40

2

CBA

where BA = basal area in square metres, C = circumference in cm and = 3.142.

The basal area of a species = the sum of the basal areas of all individuals of a species in a defined area.

To calculate the basal area for a site, add all individual basal areas.2. Record the number of trees that are ‘in’ (counts 1) or marginal (counts 0.5). Record the sum of

whole and half counts. Record the basal area factor for the instrument being used.

Site basal area (m2/ha) = BAF x count

where: BAF = basal area factor, which is specific to the instrument being used, and ‘count’ is the sum of the number of trees that exceed the sighting image (each counted as ‘1’) plus the number of those that exactly match the sighting image (counted as half each).

How to collect

If measuring basal area for low plants by measuring diameters, a defined area should be marked out (e.g. one square metre and the diameters, by species, of all individuals in the plot should be measured. Measurements will be of the area of the bases of the plants as they come out of the ground, not the extent of their canopies.


The BA sweep involves a 360 degree sweep using a basal wedge or other sighting device. Surveyors should ensure they keep the device over a defined point rather than rotating their bodies over the point, which would mean that the device would trace a circle around the surveyor.

To increase reliability, several non-overlapping samples should be taken. The final value for the site is the median value of the samples.

Basal area prisms can be purchased from commercial suppliers, or sighting devices can be constructed from a variety of materials (see, for example, Abed and Stephens 2003 and Mueller-Dombois and Ellenberg 1974).

Issues

The sighting device should have a basal area factor that allows about five to 10 trees to be counted. More or less than this can result in errors. This means that the surveyor should have access to more than one device; several sweeps using different basal area factor sighting devices might be necessary to determine the device best-suited to the site.

Further information

Mueller-Dombois, D and Ellenberg, H 1974, Aims and methods of vegetation ecology, John Wiley and Sons, New York, United States.

Abed, T and Stephens, N 2003, Tree measurement manual for farm foresters, second edition, Bureau of Rural Sciences, Canberra.


WetlandsThe Ramsar Convention, under its Article 1.1 (Anon. 1994), and Environment Australia (2001) define wetlands as:

Areas of marsh, fen, peatland or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six metres.

Within this broad definition, the wetland classification system identifies 40 wetland types in the following three categories:

marine and coastal zone wetlands inland wetlands human-made wetlands.

What to recordThe type of wetland should be recorded as listed below. The dominant life forms as per Table 10.

How to collectUse site observations, especially at planned times of year or relative to drought/non-drought cycles, aerial photos and maps. Brock and Casanova (2000) provide detailed notes on wetland-specific sampling methods.

IssuesEphemeral and periodic wetlands pose recording issues similar to those for ephemeral annual plants in some inland dryland situations. The speed of temporal changes that affect vegetation structure, cover, height and floristic composition are so great compared with most dryland sites that special sampling programs are required if the essential aspects of wetlands are to be recorded.

If a wetland is ephemeral, intermittent or fluctuating, surveyors who are inexperienced with wetland species might not know, at the time of sampling, the growth form to which the plants they observe belong. In such cases, plants should be recorded as they are seen at the time of sampling and an indication given that the site appears to be a wetland. Any evidence of past changes in water levels should also be recorded.

The method presented here allows aquatic sites to be surveyed to the extent that the major types of wetland will be identified. Many of the attributes needed for the detailed analysis of wetlands are not included.

Table 10: Wetland growth formsCode Type Notes

1 Emergent, permanent Woody or herbaceous, not ephemeral

2 Emergent, ephemeral Herbaceous, ephemeral

3 Floating stems with leaves at the surface but roots in substrate

Herbaceous; leaves at surface

4 Floating mats Herbaceous (predominantly): e.g. grass matts not attached to substrate

5 Fully submerged with roots attached to substrate

Herbaceous, with whole plant below surface (in some cases flowers may be emergent)

6 Fully submerged, floating Unattached plant, submerged e.g. free-floating herbs or algae


Aquatic and wetland typesThe 40 aquatic and wetland types listed here are taken from the Directory of important wetlands in Australia (Commonwealth of Australia 2001). Marine vegetation below 6 metres depth is not covered in this manual.

A: Marine and coastal-zone wetlands

1 Marine waters: permanent shallow waters less than 6 metres deep at low tide; includes sea bays, straits

2 Subtidal aquatic beds: includes kelp beds, seagrasses, tropical marine meadows

3 Coral reefs

4 Rocky marine shores: includes rocky offshore islands, sea cliffs

5 Sand, shingle or pebble beaches: includes sand bars, spits, sandy islets

6 Estuarine waters: permanent waters of estuaries and estuarine systems of deltas

7 Intertidal mud, sand or salt flats

8 Intertidal marshes: includes salt marshes, salt meadows, saltings, raised salt marshes, tidal brackish and freshwater marshes

9 Intertidal forested wetlands: includes mangrove swamps, nipa swamps, tidal freshwater swamp forests

10 Brackish to saline lagoons and marshes with one or more relatively narrow connections with the sea

11 Freshwater lagoons and marshes in the coastal zone

12 Non-tidal freshwater forested wetlands

B: Inland wetlands

13 Permanent rivers and streams: includes waterfalls

14 Seasonal and irregular rivers and streams

15 Inland deltas (permanent)

16 Riverine floodplains: includes river flats, flooded river basins, seasonally flooded grassland, savanna and palm savanna

17 Permanent freshwater lakes (more than 8 hectares): includes large oxbow lakes

18 Seasonal/intermittent freshwater lakes (more than 8 hectares), floodplain lakes

19 Permanent saline/brackish lakes

20 Seasonal/intermittent saline lakes

21 Permanent freshwater ponds (less than 8 hectares), marshes and swamps on inorganic soils; emergent vegetation is waterlogged for at least most of the growing season

22 Seasonal/intermittent freshwater ponds and marshes on inorganic soils: includes billagongs, sloughs, potholes, seasonally flooded meadows, sedge marshes

23 Permanent saline/brackish marshes

24 Seasonal saline marshes

25 Shrub swamps: shrub-dominated freshwater marsh, shrub carr, alder thicket on inorganic soils


26 Freshwater swamp forest: seasonally flooded forest, wooded swamps; on inorganic soils

27 Peatlands: forest, shrub or open bogs

28 Alpine and tundra wetlands: includes alpine meadows, tundra pools, temporary waters from snow melt

29 Freshwater springs, oases and rock pools

30 Geothermal wetlands

31 Inland, subterranean karst wetlands

C: Human-made wetlands

32 Water storage areas: reservoirs, barrages, hydro-electric dams, impoundments (generally more than 8 hectares)

33 Ponds, including farm ponds, stock ponds, small tanks (generally less than 8 hectares)

34 Aquaculture ponds: fish ponds, shrimp ponds

35 Salt exploitation: includes salt pans, salines

36 Excavations: includes gravel pits, borrow pits, mining pools

37 Wastewater treatment: includes sewage farms, settling ponds, oxidation basins

38 Irrigated land and irrigation channels: includes rice fields, canals, ditches

39 Seasonally flooded arable land, farm land

40 Canals

Further informationAnderson, J 1999, Basic decision support system for management of urban streams: Report no. 1, Development of the classification system for urban streams, LWRRDC Occasional paper 8/99, Land and Water Resources Research and Development Corporation, Canberra, available at, <http://www.precisioninfo.com/rivers_org/au/library/nrhp/decn_supp_syst/>.

Brock, M and Casanova, M 2000, Are there plants in your wetland?, Revegetating Wetlands, Land and Water Resources Research and Development Corporation, Canberra, available at, <http://lwa.gov.au/products/PF000026>.

Cowardin, L, Carter, V, Golet, F and LaRoe, E 1979, Classification of wetlands and deepwater Habitats of the United States, US Department of the Interior, Fish and Wildlife Service, Washington, DC, United States, available at, <http://www.npwrc.usgs.gov/resource/wetlands/classwet/index.htm>.

Environment Australia 2001, A directory of important wetlands in Australia, third edition, Environment Australia, Canberra, available at, <http://www.environment.gov.au/water/publications/environmental/wetlands/database/>.

Ramsar Convention on Wetlands 1994, Convention on Wetlands of International Importance especially as Waterfowl Habitat, Text of the Convention (originally agreed 1971, amended 1982 and 1987, published 1994), Ramsar Secretariat, Geneva, Switzerland, available at, <http://www.ramsar.org/key_conv_e.htm>.

Thackway, R 2005, Assessing Vegetation Assets, States and Transitions (VAST), available at, <http://www.daff.gov.au/brs/forest-veg/vast>.

(Hyperlinks last accessed 20 April 2009.)


RainforestPatches of rainforest occur in Australia across the tropical north, along the east coast, and in Tasmania. They tend to have closed, dark-green canopies that are easily distinguished from the generally greyish and reddish-green canopies of surrounding forests.

The ‘dry’ rainforests across the tropical north, as well as the temperate rainforests in south-eastern mainland Australia, are usually classified using standard methods (Table 2). However, because of their structural complexity it may be impractical to classify the wet tropical and subtropical rainforests of Australia using the attributes and methods used for other vegetation types. The structure of the cool temperate rainforests of Tasmania can also be complex. These two varieties of rainforests can be sampled using either the standard classification or methods supplemented with extra structural attributes to fully reflect their additional complexity (Table 11). The rest of this section deals separately with these two special cases.

Table 11: Additional attributes used to classify two special cases of rainforestWet tropical or subtropical rainforest Tasmanian cool temperate rainforest

For dominant stratum only, record:1. Complexity2. Leaf size3. Species4. Indicator growth form5. Crown cover (crown separation) and height6. Emergents (if any)7. Sclerophyll species present

Identify dominant stratum and any other strata present. For at least the dominant stratum and understorey strata, record:

1. Dominant species2. Type of crown3. Height4. Species present (at least the dominants)

Tropical and subtropical rainforestsAustralian tropical rainforests are situated above 18 latitude, while subtropical rainforests occur between approximately 18 and 33 latitudes.

Complexity Depending on their structural complexity, the tropical and subtropical rainforests of eastern Australia are classified as simple, simple–complex or complex: Simple (S): Forests showing most or all of the following properties:

the tendency for one or a few species to dominate the canopy: e.g. coachwood or Antarctic beech a reduced number of structural features: e.g. plant buttresses absent, or most stems

unbuttressed or with star buttresses a tendency for one or two growth forms to be more conspicuous: e.g. understorey layers might

have a conspicuous growth form such as a tree fern layer, ground fern layer, shrub or palm layer the stem diameters of canopy trees are usually uniform in size discrete strata: e.g. a tree fern layer, an understorey tree layer, or shrubs

Simple–complex (coded X): Forests with features of simple and complex forests. Use this category if in doubt or if the vegetation does not possess at least four of the five properties listed for the other categories.

Complex (C): Forests characteristically showing all or most of the following properties: the tallest stratum, excluding emergents, has many species


a large range of structural features: e.g. plant buttresses, spur buttresses, unbuttressed stems, compound leaves, simple leaves, lobed and deeply divided leaves, strap-like leaves

a large range of growth forms, none of which tends to dominate: e.g. trunk bases usually obscured by climbing pandans, palms, ferns and aroids; robust and slender lianes present; complex understorey consisting of shrubs, seedlings of larger trees, palms, gingers, pandans and ferns

the vegetation is not usually arranged into distinguishable, discrete strata the stem diameters of the tallest non-emergent trees are usually uneven in size.

Leaf size Leaf size classes for classifying wet tropical and subtropical rainforests are based on the sizes of the leaves of trees in the tallest stratum. The precise calculation of leaf area is not required.

Record the length and width of a representative sample of canopy leaves (leaves that are exposed to the full sun during their early development, as occurs at the top of the canopy). Figure 7 provides numerical values and a field sheet of actual leaf sizes; precision greater than the classes shown is not required.

Figure 7: Actual leaf size categories for rainforest trees

← Source: Walker and Hopkins (1990) based on Raunkiaer (1934) and Webb (1959)


The forest is described using one of nine terms determined by the proportion of individual trees in the tallest stratum with leaves in each of the leaf size categories (Table 12). Leaf size is assessed by examining leaves from ten 10 adjacent canopy trees in the sample plot. The following rules should be used: Where the average leaf size of a tree appears to be intermediate between size classes (for example

the leaf length of a lanceolate leaf is approximately 75 millimetres), the larger size class should be nominated.

Only leaves that are exposed to the sun should be considered. Because these leaves are usually at the top of a tree, a shotgun or catapult might be needed to collect them. An alternative is to find recently fallen leaves on the ground.

Leaves of palms, aroids and vines should not be considered. The size of the leaflet of a compound leaf should be considered.

This scheme is unable to describe two possible but unlikely combinations of leaf size. If all leaf sizes are represented equally (20 per cent each), the forest should be described as notophyll. If any three size classes are represented equally (e.g. 30 per cent macrophyll, 30 per cent mesophyll and 30 per cent notophyll), the intermediate leaf- size term mesophyll should be selected.

Table 12: Terms for describing leaf size in the tallest stratum of tropical/subtropical rainforest

Term describing leaf size of forest stand

Number of individual trees (maximum 10) with specified leaf sizes

Percentage of individuals in tallest stratum with specified leaf size

1 Macrophyll >5 macro >50% macro

2 Macrophyll–mesophyll 3–5 macro and 1–4 meso

30–50% macro and 10–40% meso

3 Mesophyll >5 meso >50% meso

4 Mesophyll–notophyll 3–5 meso and 1–4 noto

30–50% meso and 10–40% noto

5 Notophyll >5 noto >50% noto

6 Notophyll–microphyll 3–5 noto and 1–4 micro

30–50% noto and 10–40% micro

7 Microphyll >5 micro >50% micro

8 Microphyll–nanophyll 3–5 micro and 1–4 nano

30–50% micro and 10–40% nano

9 Nanophyll >5 nano >50% nano

Species The rainforest type is named after the most abundant species of the dominant stratum using the following system: Mixed (coded M): No one or two species combined make 50 per cent or more of the crown cover

in the tallest stratum. One or two species description (coded S): The one or two species described constitute 50 per cent

or more of the crown cover of the tallest stratum. Common, generic or specific names can be used (e.g. coachwood-crabapple; Ceratopetalum-Schizomeria; Ceratopetalum apetalum-Schizomeria ovata). Use species abbreviations for coding (e.g. CEAPE.SCOVA) except for fan or feather palms, which should not be used as common names because they are used to denote structural


features (see ‘Indicator growth forms’ below). Include sclerophyll species if they constitute 50 per cent or more of the crown cover of the tallest stratum.

Mixed plus one species (coded X): Although no single species, or two species combined, make up 50 per cent of the crown cover of the dominant stratum, one species (the species nominated) is conspicuously abundant. As above, common, generic or specific names can be used except for feather or fan palms (e.g. mixed booyong; mixed Argyrodendron; mixed Argyrodendron trifoliolatum or ARTRI). This floristic term can be used to nominate species of particular indicator value to the user.

Many rainforest species occur in clusters of five or six trees. If species qualifications are used, care should be taken to ensure that the species of the tallest stratum are found over a wide area.

Indicator growth forms Many simple rainforests and some simple–complex and complex rainforests develop strata dominated by particular growth forms. These growth forms are illustrated in Webb et al. (1976). Record the growth form name or code in Table 13 should be recorded as follows: Moss (coded 1): Forests in which mosses and lichens almost completely replace vascular

epiphytes and vines on the trunks and in the crowns. Fern (coded 2): Tree ferns form a dense/closed (80 to 100 per cent crown cover) and discrete

understorey stratum. Fan palm (coded 3): Forests in which fan palms (palms with branches spreading out in a fan

shape, such as Licuala or Livistona) form a dense/closed stratum (80 to 100 per cent crown cover) below the tallest stratum. If they form a closed stratum within the upper stratum, the forest would conform to the third example given in Table 14.

Feather palm (coded 4): Forests in which feather palms (palms, such as coconut palms, with narrow long leaves that appear feather-like from a distance) form a dense/closed (80 to 100 per cent crown cover) understorey stratum.

Vine (coded 5): Forests in which vines or twining or scrambling plants drape at least 60 per cent of the tallest stratum and emergent trees.

None (coded 6): If none of the five growth forms above reaches the required level of dominance nominated, the description should record no dominant indicator growth form.

These terms are inserted before or within the structural formation class: e.g. ‘tall sparse fern forest’ ‘very tall closed fan palm forest’; ‘low closed vine shrubland’; ‘tall closed feather palm forest’.


Table 13: Attributes and codes used to classify tropical/subtropical rainforestsComplexity Core attributes Qualifying attributes

Leaf size of trees in

dominant stratum

Species of trees in

dominant stratum

Indicator growth form

Crown cover and

height

Emergents

Sclerophyll species in dominant stratum

S Simple 1 Macrophyll M Mixed 1 Moss As per Tables 17 and 20

With (species name) emergent

With (or ‘and’) sclerophylls (or species name)

X Simple–complex

2 Macrophyll– mesophyll

S Described by one or two species

2 Fern E or A S

C Complex 3 Mesophyll X Mixed plus one species description

3 Fan palm E Sclerophyll emergents

4 Mesophyll–notophyll

4 Feather palm

A Non- sclerophyll emergents

5 Notophyll 5 Vine

6 Notophyll–microphyll

6 None

7 Microphyll

8 Microphyll–nanophyll

9 Nanophyll


Table 14: Examples to illustrate coding for both the standard and tropical/subtropical rainforest classification

Tropical/subtropical rainforest classification

Standard classification*

Description Code Notes Code(Level 2)

Complex mesophyll mixed tall closed forest C3M6 7Dw1.1

Simple notophyll very tall closed coachwood forest with Lophostemon confertus emergents

S5S6 E for emergents is coded with structure

E8w1.1 /8Dw1.1

Simple notophyll tall closed mixed fan palm forest and Acacia

S5M3S The last S is for sclerophylls in upper stratum

7Dw1.1

Simple notophyll tall closed Schizomeria forest with Syncarpia emergents and eucalypts

S5S6S The last S is for sclerophylls in upper stratum

E7w1.1 /7Dw1.1

Complex mesophyll mixed extremely tall closed black bean forest

C3M6 9Dw1.1

Simple macrophyll-mesophyll low closed Macaranga-Trichospermum forest with Acacia emergents (young secondary forest)

S2S6S The last S is for sclerophylls in upper stratum

E5w1.1 /5Dw1.1

Mixture of Eucalyptus regnans giant very sparse trees above a simple microphyll very tall closed Atherosperma moschatum forest

S7S6 10Vw1.1 /8Dw1.1

← * This is the standard classification as summarised in Example of standard classification section and Figure 3.

← Note: Rainforests may be classified using either this standard classification alone, or using the more specialised tropical/subtropical rainforest classification shown in the first three columns of the table.

Height and crown cover Height and cover classes have been defined previously (see Tables 4 and 6).

Emergents Emergents are plants, usually trees, whose crowns are clearly above the dominant stratum and cover less than 5 per cent of the total crown cover (see Emergents above). Trees that have a crown cover greater than 5 per cent and project above a rainforest are coded and named using the standard classification (see Tables 4, 6, 8 and 9).

Record the genus should be recorded and, if possible, species names of emergents followed by the word ‘emergents’: e.g. ‘with hoop pine emergents’ ‘with Araucaria emergents’ ‘with Eucalyptus emergents’. If no emergents are present, no qualifying character is nominated. Two common categories of emergents are: E: Common sclerophyllous emergents over rainforest include species of Eucalyptus, Corymbia, Acacia,

Syncarpia, Casuarina, Lophostemon and Melaleuca. A: Common non-sclerophyllous rainforest emergents include Agathis, Podocarpus, Araucaria,

Flindersia and Erythrina.

The crown cover of emergents might exceed 5 per cent of the total crown cover, as is occasionally the case for Araucaria emergents above a closed rainforest canopy. These patches should not be classified as separate vegetation types.


Sclerophyll species in dominant stratum Record the presence of any sclerophyllous genera should be recorded. These might include Eucalyptus, Corymbia, Acacia, Syncarpia, Casuarina, Allocasuarina, Lophostemon, Tristaniopsis and Melaleuca. In this rainforest schema, Agathis, Podocarpus and Araucaria are not classed as sclerophyllous.

S If sclerophyllous species (defined above) are present in the dominant stratum, these should be recorded by adding the qualifying term ‘and sclerophylls’. If the sclerophylls can be identified, ‘sclerophyll’ should be replaced by the specific, generic or common name (for example ‘and wattles’). Where sclerophyllous species are 50 per cent of the crown cover of the canopy, this will have been recorded previously and need not be repeated.

Coding tropical/subtropical rainforests Table 13 summarises codes for the tropical/subtropical rainforest classification. Table 14 provides examples.

Tasmanian rainforestsTasmanian rainforests can be sampled using the standard classification presented in the first part of these guidelines. A method widely used in Tasmania, however, classifies rainforest based on the work of Jarman et al. (1991) and Reid et al. (1999). This system uses a combination of floristics and structure that can be coded into the NVIS vegetation hierarchy at Level IV (see Table 3).

The system divides Tasmanian rainforests into two alliances: myrtle-beech and montane. Myrtle-beech rainforest is the most widespread. Although recognised as comprising a continuum, it is divided into three sub-alliances: callidendrous, thamnic and implicate. The characteristics of these four units are presented in Table 15.


Table 15: Distinguishing characteristics of Tasmanian rainforestsTasmanian rainforest

classificationStandard

classification* Alliance Code Sub-alliance Description Code

(Level 2)Myrtle- beech

C Callidendrous Medium to tall forest dominated by Nothofagus cunninghamii and/or Atherosperma moschatum. Trees well formed and widely spaced; understorey open, shady and park-like. Low diversity of woody species, which are sparse and inconspicuous in the understorey of most communities.

6–7Dw1.1

Myrtle- beech

T Thamnic Medium height forest dominated by two to five species, mostly of: Nothofagus cunninghamii, N. gunnii (rarely), Eucryphia lucida, E. milliganii, Atherosperma moschatum, Phyllocladus aspelniifolius, Lagerostrobus franklinii and Athrotaxis selaginoides. Trees well formed; a distinct shrub layer present.

6Mw1.1 /5Mw3.0

Myrtle-beech

I Implicate Low forest with broken uneven canopies. Dominance is usually shared by several species, including Nothofagus cunninghamii, N. gunnii (rarely), Eucryphia lucida, E. milliganii, Phyllocladus aspleniifolius, Athrotaxis selaginoides, Lagerostrobus franklinii, Diselma archeri, Leptospermum nitidum, L. glaucescens, L. scoparium, L. lanigerum, Melaleuca squarrosa and Acacia mucronata. The understorey is tangled and mostly forms a continuous layer from the ground to the canopy; emergents may be present. Species diversity is relatively high for trees and shrubs.

(E) /5Mw1.1 /4Sw3.0

Montane M Low forests dominated by Athrotaxis cupressoides and less commonly by A. selaginoides. The canopy is usually open with widely spaced trees, although dense clumps can occur. The understorey is dominated by low shrubs, grasses or mosses (Sphagnum). Shrub heights range from half to two-thirds the height of the canopy. Woody species diversity is relatively high.

5Sw1.1 /4Mw3.0 /0Dm1.0

← * This is the standard classification as summarised in Examples of standard classification section and Figure 3.

← Note: Rainforests may be classified using either this standard classification alone, or using the more specialised Tasmanian rainforest classification shown in the first four columns of this table.


Growth stageGrowth stage is the life cycle phase the vegetation is in at the time of its sampling; it is generally determined by the life cycle phase of the dominant species at the site. It is an important aspect of any vegetation sample.

What to recordWhere sufficient information is available, assign the vegetation should be assigned to one of the following five categories: early regeneration, advanced regeneration, uneven age, mature phase, senescent phase (Table 16).

In the notes section of the field record sheets, record the features used to make the assessment should be recorded.

Where the vegetation is dominated by trees, the signs of aging are well documented, especially for eucalypts in south-eastern and south-western parts of the continent (Jacobs 1955; Eyre et al. 2000). The form of a tree in profile can be informative about the relative age of the tree. Figure 8 shows growth states for (a) forest trees, (b) woodland trees, and (c) shrubs. Where the vegetation is dominated by woodland, growth stages are similar to those of open forest except that tree- form is shorter and wider. There is little documentation of growth stages in vegetation dominated by shrubs; the development stages depicted by Lange and Purdie (1976) for western myall shown in Figure 8, however, are indicative for shrubs in inland Australia.

How to collect

Information on vegetation can be collected by walking throughout the site and the immediate surrounding area, looking for signs that indicate the history of vegetation development. Use the stages in Table 16 (illustrated in Figure 8) should be used as a guide, although they do not cover all possibilities for all vegetation types.

Issues

Assessing the growth stage of a vegetation type can be difficult in vegetation that is poorly known, so care is needed when recording this attribute. The knowledge base is generally best for forests and woodlands and much poorer for shrublands, grasslands and herblands.

Growth stage is also an attribute of interest when assessing the condition of a vegetation sample. It might not always be possible to separate the effects of increasing age from responses because of stress caused by environmental factors such as pests and diseases or by major land-use change.

Further information

Eyre, T, Kelly, A, Sutcliffe, T, Ward, D, Denham, R, Jermyn, D and Venz, M 2002, Forest condition assessment and implications for biodiversity: Final report, Queensland Department of Natural Resources, Brisbane, available at, <http://pandora.nla.gov.au/pan/26050/20020805-0000/www.ea.gov.au/land/nlwra/condition/brigalow/index.html>.

Jacobs, M 1955, Growth habits of the eucalypts, Forestry and Timber Bureau, Department of the Interior, Commonwealth Government Printer, Canberra.

Lange, R and Purdie, R 1976, ‘Western myall (Acacia sowdenii), its survival prospects and management needs’, Australian Rangelands Journal, vol. 1, pp. 64–69.

Lange, R and Sparrow, A 1992, ‘Growth rates of western myall (Acacia papyrocarpa Benth.) during its main phase of canopy spreading’, Australian Journal of Ecology, vol. 17, pp. 315–320.


Table 16: Indicators of growth stageCode Growth

stageTrees dominant Shrubs dominant Grasses and herbs

dominantCryptogams dominant

(mosses and lichens)1 Early

regenerationDominated by small, juvenile, dense to very sparse regenerating plants, with or without a few older, widely spaced, emergent plants.

Dominated by small, juvenile, dense to very sparse regenerating plants. A few older, widely spaced emergents may be present.

Small and juvenile stages predominate; bare soil or old litter common.

Thin growth of young plants or widely spaced clumps of young plants.

2 Advanced regeneration

Dominated by dense to sparse, well-developed, immature plants. Large emergents may be present with crown cover less than 5 per cent of the total crown cover. If the cover is more than 5 per cent, however, classify as ‘uneven age’. Trees have well-developed stems (poles). Crowns have small branches. The height is below maximum height for the stand type. Apical dominance still apparent in vigorous trees.

Dominated by dense to sparse, well-developed but not mature plants. If large emergent plants are present, they comprise less than 5 per cent crown cover of the dominant stratum; if more than 5 per cent, classify as ‘uneven age’.

Vegetative growth abundant; plants approaching full mature size but reproductive material absent or in early stages only; at average sites, soil surface largely obscured.

Cover of plants high for the site; some reproduction may be evident.

3 Uneven age Mixed size and age classes, usually identified by two or more strata dominated by the same species, but can also include sites with different species regenerating in the understorey of an older canopy.

Mixed size and age classes, usually identified two or more strata dominated by the same species, but can also include sites with different species regenerating in the understorey of an older canopy.

A mixture of mature, perennial and immature annual species present.

A mixture of mature reproductive plants with immature regeneration.

4 Mature Well-spaced mature-sized plants or densely packed plants with crowns touching, with or without emergent senescent plants. Trees at maximum height for the type and conditions. Crown at full lateral development in unlocked stands. No apical dominance.

May have well-spaced mature-sized plants, or have very densely packed plants with crowns touching, with or without emergent senescent plants.

Most plants of reproductive age; depending on vegetation type, reproduction evident, or would be if environmental conditions were appropriate (e.g. water availability).

Swards of plants common; plants of mature physiognomy (clump sizes and forms); reproduction common at appropriate times of year or drought/rain cycle; overall health and vigour high.

5 Senescent Dominated by over-mature plants, particularly in the dominant stratum; evidence of senescence in many plants, some without obvious links to disturbance. Tree crowns show signs of contracting: dead branches and decreased crown diameter and leaf area. Distorted branches and burls may

Dominated by old plants (thick stems and primary branches, crowns either extremely dense with much dead wood or thin and open if species sheds dead branches), particularly in the dominant stratum. Many senescent plants, some without obvious links to disturbance.

In largely annual vegetation, reproduction is complete and plants are dying or mostly dead; in perennial vegetation, plants have lost vigour or are breaking down; large areas

Clear evidence of the degeneration of plants or clumps; dead older parts of plants can be conspicuous.


be common. Dead trees may be present. of soil are exposed. Litter accumulation can be high.


Figure 8: Growth stages

← Note: Numbers underneath refer to the growth stage categories in Table 16.

← Development stages of western myall (Acacia papyrocarpa), redrawn from Lange & Sparrow 1992 (ex Lange and Purdie 1976).

Vegetation condition In the context of this manual, condition is the state of a patch of vegetation at the time of sampling relative to a specified benchmark. A benchmark is a set of attributes with values determined from either a single or a number of reference sites that represent the variability of the vegetation type (Thackway and Lesslie 2008). The reference sites should be precisely located and their benchmark values at known times recorded.

Each unit of vegetation—native, non-native or at different growth stages—should have its own benchmark. For native vegetation, the benchmarks should be based on the best examples representing pre-European conditions (sometimes called ‘fully natural’). For vegetation managed for economic production, benchmarks should be based on reference sites with best-practice, fully ecologically sustainable conditions.

A single site can be assessed from more than one perspective, depending on the focus of the condition assessment. For example: a ‘native vegetation integrity’ perspective would interest a biodiversity manager and should be

compared to with ‘fully natural’ benchmarks a ‘fodder production’ perspective would interest a grazing property manager and should be

compared to with ‘best practice sustainable production’ benchmarks a ‘carbon sequestration’ perspective would interest a climate-change mitigation manager and

should be compared to with ‘optimum sustainable carbon capture/storage’ benchmarks.

Condition assessment is an area of active research and development. The concept of vegetation that is in ‘good’ or ‘poor’ condition is generally well understood. However, taken across the whole of the Australian continent, however, no single set of attributes will measure condition for all land uses (e.g. undisturbed native vegetation compared to with non-native cropland), nor will a single set of attributes apply to all vegetation types (e.g. ash and karri forests versus inland woodlands versus shrublands versus grasslands versus wetlands versus soil crusts).

For the vegetation being sampled, it needs to be determined whether benchmarks or published descriptions of the attributes of such sites exist, or whether expert knowledge is available; potential sources include federal, state and territory environmental protection agencies, and environment, agriculture and forestry departments. If benchmarks exist, standard methods for recording the condition of those vegetation types might also be available from the same sources. Record the benchmark for the site should then be recorded.

Most condition assessment methods have been developed for native biodiversity (Parkes et al. 2003), particularly in forests (e.g. Eyre et al. 2002), wetlands (e.g. Parsons et al. 2002a, b) and rangelands (Smyth et al. 2003), and for production in rangelands (Pickup et al. 2001).4 An interim standard for the assessment of native vegetation condition (Commonwealth of Australia 2004b) has been developed as part of a program by ESCAVI to develop a national approach to this issue.

According to Holmes and Papas (2004b), the Ramsar Convention on Wetlands’ 1999 definition of ecological character (below) can be used as the conceptual basis for indexes of wetland condition:

Ecological character is the sum of the biological, physical, and chemical components of the wetland ecosystem, and their interactions, which maintain the wetland and its products, functions, and attributes. Change in ecological character is the impairment or imbalance in any biological, physical or chemical components of the wetland ecosystem, or in their interactions, which maintain the wetland and its products, functions and attributes.

4 Parkes et al. (2003) extend their indicator method by proposing a method of converting individual, site-based condition values into synthetic whole-site condition indexes. This method is not included here as it relates to the office-based processing of site-based data.

What to recordFor the assessment of woody vegetation, particularly biodiversity condition in native forest in south-eastern Australia, the attributes shown in Table 17 and Table 18 might be suitable.

Table 17: Condition of woody—particularly tree-dominated—native vegetation in southern AustraliaAttribute Notes

Large trees ‘Large’ is relative to benchmark

Tree (canopy) cover ‘Cover’ is relative to benchmark

Understorey (non-tree) strata Quantity and kind of understorey depends on the type of vegetation

Lack of weeds Include consideration of relative impact and invasiveness depending on the weed species and vegetation type

Recruitment The amount of recruitment will vary with vegetation type and position in the growth-stage cycle

Organic litter (fine, medium and coarse woody debris; non-woody debris)

The amount of organic litter present relative to benchmark depends on: the geographic location in

Australia, which affects the kind and rate of organic decomposition

the vegetation type position in the disturbance regime a defined fire frequency.

The biodiversity condition of rangelands has received considerable research attention (Smyth et al. 2003), but national standards for condition assessment are not yet available. Rangeland condition with respect to pastoral production has been assessed for many decades through ground surveys (Holm et al. 1984, Pickup et al. 2001) and methods combining satellite imagery (Landsat TM and multi-spectral scanner resolution) and ground survey to monitor range condition are the current focus of research.

For other vegetation types, and where a wider variety of attributes of the site is required, the list given in Table 19 might be suitable.

Methods are available for assessing wetland condition (e.g. Anderson 1999; Ladson et al. 1999; MDB 2005; NRM 2004; Parsons et al. 2002a, b); Table 20 outlines the basic approach of some of these.

Table 18: The Vegetation Assets, States and Transitions (VAST) classification

Native vegetation extentDominant structuring plant species indigenous to the locality and spontaneous in

occurrence—i.e. a vegetation community described using definitive vegetation types relative to estimated pre-1750 states

Non-native vegetation extentDominant structuring plant species indigenous to the locality but cultivated; alien to the

locality and cultivated; or alien to the locality and spontaneous

Veg

etat

ion

cond

ition

st

ate

(map

ping

crit

eria

)

State 0:NATURALLY BARE

Areas where native vegetation does not naturally persist; recently naturally disturbed areas where native vegetation has been entirely removed. (i.e. open to primary succession)

State I:RESIDUAL

Native vegetation community structure, composition, regenerative capacity intact – no significant perturbation from land use/land management practice

State II:MODIFIED

Native vegetation community structure, composition and regenerative capacity intact - perturbed by land use/land management practice

State III:TRANSFORMED

Native vegetation community structure, composition, regenerative capacity significantly altered by land use/land management practice

State IV:REPLACED - ADVENTIVE

Native vegetation replacement – species alien to the locality and spontaneous in occurrence

State V:REPLACED - MANAGED

Native vegetation replacement with cultivated vegetation

State VI:REMOVED

Vegetation removed – alienation to non-vegetated land cover

Dia

gnos

tic c

rite

ria

Cur

rent

rege

nera

tive

capa

city

(inte

rpre

tativ

e1 )

Complete removal of in-situ regeneration capacity except for ephemerals and lower plants

Natural regenerative capacity unmodified

Natural regeneration capacity persists under past and /or current land management practices

Natural regenerative capacity limited / at risk under past and /or current land use or land management practices. Rehabilitation and restoration possible through modified land management practice

Regeneration potential of native vegetation community has been suppressed and in-situ resilience at least significantly depleted. May still be potential for restoration using assisted natural regeneration approaches

Regeneration potential of native vegetation community likely to be highly depleted by intensive land management. Very limited potential for restoration using assisted natural regeneration approaches

Nil or minimal regeneration potential. Restoration potential dependent on reconstruction approaches

Veg

etat

ion

stru

ctur

e(o

bjec

tive)

Nil or minimal Structural integrity of native vegetation community is very high

Structure is predominantly altered but intact e.g. a layer /strata and/or growth forms and/or age classes removed

Dominant structuring species of native vegetation community significantly altered e.g. layer/strata frequently and repeatedly removed

Dominant structuring species of native vegetation community removed or predominantly cleared or extremely degraded

Dominant structuring species of native vegetation community removed

Vegetation absent or ornamental

Veg

etat

ion

com

posit

ion

(obj

ectiv

e)

Nil or minimal Compositional integrity of native vegetation community is very high

Composition of native vegetation community is altered but intact

Dominant structuring species present - species dominance significantly altered



Vegetation absent or ornamental

Exa

mpl

es

Bare mud; rock; river and beach sand, salt freshwater lakes, rock slides and lava flows

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; 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

Plantations; tree cropping; horticulture; orchards; reclaimed mine sites; environmental and amenity plantings; improved pastures (includes heavy tree thinning 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

58

Increasing vegetation modification from left to right

59


Table 19: Condition attributes*Attribute Recorded observationSite disturbance: % coverDisturbance-observation type

nonelimited clearingcultivationgravel pitcleared within 30 metre quadratcoppice regrowthdrainsearthworksfire breaksfence linesoff-road vehiclespower linesrubbish dumpingremnant vegetation beside roadsideslashingsprayswatering pointsaccess tracksminingloggingBeehivesexotic weedssalinityflooddiebackother/fire/wind/water

Frequency of major disturbances affecting sitecurrent disturbance occurringsingle recent 1 to 10 yearsfew recent 1 to 10 yearsdisturbances all more than 10 yearstype and intensity accelerated erosion

Extent and type surfacecrustingrockslogs


Attribute Recorded observationbrancheslitter (% cover, depth)bare ground

Departure from highest-quality site of the typepristineintactdisturbedvery disturbed

GrazingNilLightmoderateheavycattlehorsesnative herbivorepigsother

Nearest water (km)Fire

year of last fire or evidence of firefire frequency

nilless than 1 yearr1 to 2 years2 to 5 yearsmore than 5 years

Fire intensityno damageminor some/most trees and shrubssome trees/shrubs killedmost trees/shrubs killed

← The above list of attributes are being used by state and territory agencies to record aspects of vegetation and site condition


Table 20: Attributes used in the assessment of wetland conditionBiological indicators Physical chemical indicators

Vegetation extent: % cover of 3 to 5 dominant woody species in

upper and middle layers% herbaceous ground cover% cover aquatic vegetation (submerged,

floating, emergent)% cover exoticsNative regenerationWidth of riparian zone (left and right banks)Longitudinal connectivityExpected species lists for regional community monitoringMacroinvertebratesPhytoplanktonChlorophyll a

pHConductivityTurbidityTransparencyColourDissolved oxygenNutrients

← Adapted from Anderson (1999), NRM (2004), and Commonwealth of Australia (2004a).

How to collectIf a benchmark is available, compare the sample site should be compared with to the benchmark for each condition category (e.g. biodiversity, commercial production, water resource) and rank the site ranked accordingly. Parkes et al. (2003, 2004) describe possible ways of dealing with site and reference site variability.

If no benchmark is available, and the sample is native vegetation, provide a qualitative assessment should be provided using the attributes in Table 17 and Table 18.

IssuesVegetation condition only has meaning relative to an agreed benchmark, which itself is meaningful only in a context of specified management intent. Native vegetation, mixtures of native and non-native vegetation, and substantially non-native vegetation need to be considered separately. Individual sites that support native vegetation, mixtures of native and non-native vegetation, and substantially non-native vegetation can be considered from one or more perspectives, with each perspective requiring a different benchmark. Typically, maximum scores relative to one benchmark will not align with maximum scores relative to a different benchmark (Table 21).

Table 21: Scoring vegetation using benchmarks Type/use Score relative to pre-European

benchmarkScore relative to sustainable production benchmark (grazing cattle)

Remnant native closed to mid-dense trees (forest)

90 20

Grazed sparse trees (woodland)

55 85

Wheat field 5 25


← Note: This example scores three vegetation types based on two different benchmarks. The score in each cell has a potential maximum of 100.

For all vegetation, methods for site-based vegetation condition assessment are evolving. Prior to a survey, surveyors should consult widely to ensure they are using the most reliable available method.

For biodiversity condition, benchmarks are generally taken to be the typical characteristics of sites containing undisturbed, little disturbed or highest-quality representative examples of a native vegetation type. The assessed attributes refer to the status of vegetation structure and floristics and the presence of adequate habitat for a diversity of species (Parkes et al. 2003).

The way in which vegetation dynamics are factored into an assessment (e.g. time-scales of change to floristics, structure or the physical environment) need special attention and methods have not yet been standardised nationally. Examples of natural variability include: differences in mature tree size within a vegetation type because of differences in site productivity, and variation related to growth phases and species behaviour following major disturbances. Moreover, some benchmarked attributes might be absent, even from mature stands of a particular vegetation type (McCarthy et al. 2003). Approaches that attempt to deal with such variability include: using using a different benchmark for each readily definable variant using using a ‘mature’ reference point but annotating early and

senescent stages of the growth cycle to explain condition scores that are less than that of the mature site

using using benchmark values that are derived averages for the values taken from a range of reference sites reflecting the natural variability of the vegetation type.

The optimal values of some attributes that indicate good condition might be less then than the maximum possible values for the attribute. In a stand recovering from clearing, for example, an over-abundance of tree stems/cover (sometimes called ‘locked stands’) might be detrimental to the rate at which the site returns to its ideal reference condition.5

In addition to vegetation, the condition of other site factors, such as soil stability and water resources, should be assessed against the estimated long-term sustainable levels. Excessively high values of any parameter (e.g. very high bumper crops as a result of unsustainable management, or very large numbers of native herbivores) at the expense of long-term ecological stability could infer unsustainable exploitation and a decline in condition.

Although the integrated landscape-scale assessment of biodiversity and production systems is still some way from reality, basic research towards it is under way (e.g. Lindenmeyer et al. 1999).

Further informationAnderson, J 1999, Basic decision support system for management of urban streams: Report no. 1, Development of the classification system for urban streams, LWRRDC Occasional paper 8/99, Land and Water Resources Research and Development Corporation, Canberra, available at, <http://www.precisioninfo.com/rivers_org/au/library/nrhp/decn_supp_syst/>.

Bastin, G 2005, Australian collaborative rangeland information system: Reporting change in the rangelands, National synthesis of reports from pilot regions, available at, <http://www.nlwra.gov.au/Natural_Resource_Topics/Rangelands/index.aspx>.

Commonwealth of Australia 2004, Integrity of inland aquatic ecosystems: Wetland ecosystem condition, Fact sheet, Commonwealth of Australia, Canberra, available at,

5 Nevertheless, the overall role of such stands in the functioning of ecological systems would need to be explored.


<http://www.nrm.gov.au/publications/factsheets/me-indicators/inland-aquatic/pubs/wetland-condition.pdf>.

Commonwealth of Australia 2004b, An interim approach to the native vegetation condition indicator, Fact sheet, Commonwealth of Australia, Canberra, available at, <http://www.nrm.gov.au/publications/factsheets/me-indicators/native-veg/condition.html>.

Eyre, T, Kelly, A, Sutcliffe, T, Ward, D, Denham, R, Jermyn, D and Venz, M 2002, Forest condition assessment and implications for biodiversity: Final report, Queensland Department of Natural Resources, Brisbane, available at <http://pandora.nla.gov.au/pan/26050/20020805-0000/www.ea.gov.au/land/nlwra/condition/brigalow/index.html>.

Holm, A, Burnside, D and Mitchell, A 1987, ‘The development of a system for monitoring trend in range condition in the arid shrublands of Western Australia’, Australian Rangeland Journal, vol. 9, pp.14–20.

Holmes J and Papas P 2004a, Review of wetland assessment methods, version 1.0, Department of Sustainability and Environment, Victoria, available at, <http://www.dse.vic.gov.au/DSE/nrence.nsf/LinkView/3EA5B6AEFB53EE3DCA25708B00145F44522C816829EBF3F7CA25700C00240E63>.

Holmes, J and Papas, P 2004b, Conceptual framework for the development of an index of wetland condition in Victoria, version 1, Department of Sustainability and Environment, Melbourne, available at, <http://www.dse.vic.gov.au/DSE/nrence.nsf/LinkView/3EA5B6AEFB53EE3DCA25708B00145F44522C816829EBF3F7CA25700C00240E63>.

Ladson, A, White, L, Doolan, J, Finlayson, B, Hart, B, Lake, P and Tilleard, J 1999, Development and testing of an index of stream condition for waterway management in Australia, Freshwater Biology, vol. 41, pp. 453–468.

Lindenmayer, D, Cunningham, R and Pope, M 1999, ‘A large-scale ‘experiment’ to examine the effects of landscape context and habitat fragmentation on mammals’, Biological Conservation, vol. 88, pp.387–403.

Murray-Darling Basin Commission 2005, Sustainable rivers audit, available at, http://www.mdbc.gov.au/SRA

McCarthy, M, Parris, K, van der Ree, R, McDonnell, M, Burgman, M, Williams, N, McLean, N, Harper, M, Meyer, R, Hahs, A and Coates, T 2003, ‘The habitat hectares approach to vegetation assessment, An evaluation and suggestions for improvement’, Ecological Management and Restoration, vol. 5, no. 1, pp.24,

http://www.nrm.gov.au/publications/factsheets/me-indicators/inland-aquatic/river-condition.html.

Parkes, D, Newell, G and Cheal, D 2003, ‘Assessing the quality of native vegetation: The ‘habitat hectares’ approach’, Ecological Management and Restoration, vol. 4, no. 1, pp. 29–38.

Parkes, D, Newell, G and Cheal, D 2004, ‘The development and raison d’être of ‘habitat hectares’: A response to McCarthy et al. (2004), Ecological Management and Restoration, vol. 5, no. 1, pp. 28–29.

Parsons, M, Thoms, M and Norris, R 2002a, Australian river assessment system: Review of physical river assessment methods: A biological perspective, Cooperative Research Centre for Freshwater Ecology Monitoring River Health Initiative Technical Report Number 21, Environment Australia, Canberra, available at, <http://www.environment.gov.au/water/publications/environmental/rivers/nrhp/protocol-2.html>.

Ramsar Convention on Wetlands 1994, Convention on qetlands of international importance especially as waterfowl habitat, Text of the Convention (originally agreed 1971, amended 1982


and 1987, published 1994), Ramsar Secretariat, Geneva, Switzerland, available at, <http://www.ramsar.org/key_conv_e.htm>.

Ramsar Convention on Wetlands 1999, Resolution VII.10 on wetland risk assessment at the 7th meeting of the conference of the contracting parties to the convention on wetlands of international importance especially as waterfowl habitat, available at, <http://www.ramsar.org/res/key_res_vii.10e.htm>.

Smyth, A, James, C and Whiteman, G (eds) 2003, Expert technical workshop, Biodiversity monitoring in the rangelands: A way forward, Report to Environment Australia, volume 1, Centre for Arid Zone Research, CSIRO Sustainable Ecosystems, Alice Springs.

Thackway, R and Lesslie, R 2005, Assessing Vegetation Assets, States and Transitions (VAST): Accounting for vegetation condition in the Australian landscape, Bureau of Rural Sciences, Canberra, available at, <http://www.daff.gov.au/brs/forest-veg/vast>.

Thackway, R and Lesslie, R 2008, Describing and mapping human-induced vegetation change in the Australian landscape, Environmental Management, vol. 42, pp. 572–590


New technologyVegetation scientists will continue to devise and adopt new ways of rapidly and cost-effectively collecting data on site and vegetation attributes. Each innovation will improve the efficiency of data collection and is also likely to provide a new perspective on vegetation.

Aerial photographs and satellite imagery in visible and near-infra-red wave bands continue to provide the most commonly used remotely sensed vegetation data, but new remote sensing methods, such as LIDAR (Light Detection And Ranging; see below) and synthetic aperture radar (SAR) have also been shown to be useful for crop production forecasting and forest cover mapping. The role of both in vegetation classification and assessment is likely to increase.

Global positioning systemsA GPS receiver uses the microwave signals from between 24 and 32 Medium Earth Orbit satellites to determine its precise location (i.e. latitude and longitude), speed, direction and time.

What to record

Datum: The Geocentric Datum of Australia 1994 (GDA94) is the preferred standard method to use when recording latitude and longitude from a GPS, although older instruments might use the World Geodetic System 1984 (WGS84); record the system used should be recorded (i.e. GDA94 or WGS84) on the record sheet. Each system uses a slightly different set of corrections that allow for variation in the earth’s shape. If the system is not specified, errors can occur when data are combined with other datasets, such as in GIS mapping projects.If a very high level of accuracy is required from the GPS, the following websites might be useful: http://www.anzlic.org.au/spatial_links.html http://www.icsm.gov.au/ http://www.icsm.gov.au/icsm/gda/index.html http://www.icsm.gov.au/icsm/gda/gdatm/index.html http://www.icsm.gov.au/icsm/gda/faq.html

(Hyperlinks last accessed 20/04/2009.)

The Universal Transmercator Projection (UTM) of datum GDA94 gives coordinates (eastings and northings) in metres from a standard reference point. The UTM projection of the earth is divided into zones that are 6° longitude wide; the Australian continent and its external territories occupy zones 38–58 (zones 49 – to 56 for continental Australia only). Record bBoth the zone and the eastings and northings provided by the GPS receiver need to b e recorded.

How to collect

GPS receivers vary greatly in quality, size, precision and cost, from small, low-cost recreation-quality instruments with a precision of 10 to 100 metres to large, high-cost, survey-quality ones (with a precision of 10 metres or less).

To obtain an accurate position, signals from at least four satellites are needed, which, if the times of satellite positions are unknown, might require several instrument readings. Major GPS manufacturers offer planning software at no cost, which that enables the receivers to take best advantage of satellite positions to optimise readings (Johnson and Barton 2004).

If a high degree of positional precision is required, use a differential GPS receiver; this combines satellite signals with a signal from a known fixed broadcasting location to provide a precision of less than 10 metres. Even higher degrees of positional accuracy can be obtained from high-quality survey instruments using dual-frequency technology.


http://www.icsm.gov.au/icsm/gda/faq.html

http://www.icsm.gov.au/icsm/gda/gdatm/index.html

http://www.icsm.gov.au/icsm/gda/index.html

http://www.icsm.gov.au/

http://www.anzlic.org.au/spatial_links.html

http://en.wikipedia.org/wiki/Geographic_location

http://en.wikipedia.org/wiki/Satellite

http://en.wikipedia.org/wiki/Medium_Earth_Orbit

Issues

Local factors can influence the utility of GPS readings. Rugged terrain or dense forest canopies can reduce accuracy by masking satellite signals. In such circumstances, it might be possible to take readings from nearby locations that are free of obstruction, or to mount a temporary aerial that can receive the required signals.

Further information

Johnson, C and Barton, C 2004, ‘Where in the world are my field plots? Using GPS effectively in environmental field studies’, Frontiers in Ecology and the Environment, vol. 2, no. 9, pp. 475–482.

LIDARLIDAR is an optical remote sensing technology that measures properties of scattered light to find the range and/or other information of a remote target. LIDAR instruments emit pulses of laser light and record the return- times and strengths of the reflected signals. These are processed by software packages to provide data on attributes such as the altitude of the ground surface, plant canopy height, sub-strata height and depth, crown cover, leaf and stem biomass, and clumping and gaps in crowns. In some systems, these can be linked to GIS and digital imagery to enhance subsequent analysis. LIDAR data can be used as a mapping tool or as a method for gathering data to inform mapped units.

How to collect

LIDAR data can be obtained from airborne or satellite platforms or from portable ground-based systems. Various commercially available instruments and software packages are available.

Issues

When using any remotely sensed data, including LIDAR, it is important to have adequate ground controls for biological components. Sample measurements of cover, height, canopy depth and diameter and canopy gaps are needed to calibrate the data produced by LIDAR. Once calibrated, LIDAR data provide much greater area coverage of measured attributes than would be practical using ground measurement only.

Potential uses for LIDAR include large-area mapping of basic vegetation structural attributes, such as cover and height. The three-dimensional measurement and reporting of vegetation structural attributes is potentially useful as a surrogate for biomass distribution (both horizontal and vertical) and in the assessment of habitats created by vegetation (Lee et al. 2004; Lovell et al. 2003; Queija et al. 2004).

Special cases

LIDAR technologies are maturing for some kinds of uses but still developing (albeit rapidly) in others. Commercial packages are available that can measure crown heights and cover. Projects are under way to develop methods for extracting more information from LIDAR; therefore, over time, therefore, LIDAR is likely to become increasingly useful in vegetation survey.

Hyperspectral imagery is being used in a wide range of research projects, either alone or in combination with other remotely sensed data and on-the-ground reference sites. It has been used to map vegetation and environmental attributes on land and in shallow water.


The use of LIDAR in determining the height of strata in vegetation

Airborne scanning LIDAR can be used to generate vertical profiles of foliage density (Lee et al. 2004). However, research is still required, however, to fully understand how these relate to actual ecological strata that can be identified in the field (Lovell et al. 2003).

Two representations of foliage structure from processed LIDAR data are shown below. The first, the left-hand part of Figure 9, shows, in two dimensions, the vertical and horizontal distribution of all foliage elements at the resolution of the data acquired. This is a representation of the vegetation, viewed from the side as if looking into the plot. Two tree clusters with a canopy at approximately 25 metres can be seen clearly, as can an understorey at about 4 to 6 metres height. The continuity of the foliage elements is also clear, from the tops of the dominant trees down through the understorey below them. Thus, two strata can be distinguished.

The second representation of the vertical distribution of foliage density is shown in the right-hand part of Figure 9. The relative amounts of overstorey and understorey in this sample plot were determined by assessing the number of returns per 1 metre height interval; they are depicted in the figure as a percentage of all non-ground returns. The largest percentage values occur where the foliage is most dense and the crowns widest. Strata are separated by relatively low percentage values (troughs in the curve). Two strata can again be distinguished.

Figure 9: Longitudinal profile of air-borne field-plot LIDAR data and its associated vertical profile

← Notes: Left: longitudinal profile of air-borne LiDAR data for a field plot. Right: its associated vertical profile.

← The resolution is 1 m spacing between returns, with a footprint size of 0.10 m, within a 50x50 m field plot from Injune in central Queensland. The vegetation is a Eucalyptus populnea (poplar box) woodland with emergent Angophora.

Further information

Lee, A, Lucas, R and Bracks, C 2004, ‘Quantifying vertical forest stand structure using small footprint lidar to assess potential stand dynamics’, Proceedings, NATSCAN: Laser scanners for forest and landscape assessment instruments, processing methods and applications 3–6 October 2004, Freiburg, Germany, International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 36(8/W2), pp. 213–217.

Lovell, J, Jupp, D, Culvenor, D and Coops, N 2003, ‘Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests’, Canadian Journal of Remote Sensing, vol. 29, no. 5, pp.607–622.

Queija, V, Stoker, J and Kosovich, J 2004, Recent Geological Survey Applications of Lidar, web report, available at, <http://edc.usgs.gov/includes/highlight.pdf>.


http://edc.usgs.gov/includes/highlight.pdf

SoilsBasic information on soils (e.g. Great Soil Group, textures, drainage, colour) usually form part of a vegetation survey. The methods used to collect these data are not covered in this manual but are available in National Committee on Soil and Terrain (2009). Major advances are being made in techniques for the sampling of soil attributes, including soil microorganisms, carbon content and root distributions, often with little disturbance to the soil. Correlating such information on soils with vegetation types could greatly improve understanding of variations in vegetation attributes such as cover, height, species composition and soil dynamics.

Information on soils in Australia is accessible on the internet via the Australian Soil Resources Information System (http://www.anra.gov.au/topics/soils/asris/index.html). A compendium of world soils (Rossiter 2005) can be found at: http://www.itc.nl/~rossiter/research/rsrch_ss_digital.html.

IssuesUntil recently, there has been frustratingly little change in methodologies for soil sampling. Vegetation scientists should keep abreast of changes in soil sampling methods because they are likely to significantly change the way in which soils and vegetation are understood.

Further informationGunn, R, Beattie, J, Reid, R and van der Graaff, R (eds) 1990, Australian soil and land survey handbook: Guidelines for Conducting Surveys, Inkata Press, Melbourne.

Rossiter, D (comp.) 2005, ‘A Compendium of on-line soil survey information: Digital soil geographic databases’, available at <http://www.itc.nl/~rossiter/research/rsrch_ss_digital.html>.


http://www.itc.nl/~rossiter/research/rsrch_ss_digital.html

http://www.itc.nl/~rossiter/research/rsrch_ss_digital.html

http://www.anra.gov.au/topics/soils/asris/index.html

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Annex 1: Steps in the field survey process

Before going to the field Clearly define the aims of the survey. Include the requirements of expected users and those

funding the survey. Consult with those with major interests in the survey or who could be affected by the work or

outcomes of the survey: e.g. funding agencies, landowners, users, other survey groups with interests in the area, herbaria and media. These consultations should aim to gain support, gather existing information, and gather intelligence on sites that could affect site selection or interpretation.

Obtain the necessary permits for access to the site and, should voucher specimens be needed, for collecting.

Office based site-selection processes:– Has the area been surveyed before? If so, are results available and satisfactory for the

current project?– Determine the sampling method. Then, if appropriate:

o obtain geological, environmental, climatic, soil, cadastral and other maps and remote sensing imagery that show attributes relevant to the project

o determine the density of sampling based on the total area being surveyedo stratify sampling area and allocate sites to units.

– Locate potential sample sites on remotely sensed imagery, preferably the most detailed available (e.g. 1:50,000 or 1:25:000 aerial photographs), documenting the closest location a vehicle can reasonably get to the site and the potential route to walk to the site if needed. Program these into GPS receiver, if available.

Prepare field equipment and transport. Prepare sampling teams, ensuring relevant skills (e.g. biological identification, sampling

methods, health and safety).

Near the site Record landmarks such as nearby towns and properties to locate the site and the roads and

directions used to get to the closest place for vehicles. If relevant, mark the take-off point beside the road or track, using plastic tape, but balance the

need for relocation against the potential for attracting the unwelcome attention of others. Record direction(s), distances and route taken from the vehicle to the sampling site. In order to avoid bias in choosing the site, use a random numbers method to locate the actual

location of the sample plot. Reconnoitre the sampling site to see that it meets basic criteria. The situation may have

changed, for example, since aerial photos were taken. Try to keep the site at least 100 metres away from vegetation edges and major intrusions into the site of ‘foreign’ elements such as tracks and rock outcrops. Where the unit being sampled is small or narrow, allowances for this will influence the siting of the sample plot.

At the site Walk around the outside of the site to acquaint yourself with it. Avoid too much traffic within

the area to be sampled so as not to disturb the ground layer before measuring and recording it. Mark out plot boundaries, or, if using plotless sampling, locate the centre or end point. Make general notes about the site (e.g. quality, condition, exceptional aspects). Record the site location (on GPS, aerial photo or map as appropriate). Draw sketch map

showing general features: e.g. vegetation boundaries, tracks, drainage lines, disturbances. Locate sub-plots for plants of small stature using random selection methods wherever possible.


Record and measure the ground layer. Record and measure the canopy, and tall understorey if present, using plots of relevant sizes. Record soil and other environmental information. Collect and label specimens as needed. Make photographic records from standard locations, plus any subsidiary photos, recording

relevant data about the photos on the record sheets. Complete record sheets and re-check to ensure all fields are completed. Ensure that relevant voucher specimens have been collected, labelled and packed. Place permanent marker(s). Unless restricted access has been arranged in advance with the land

custodian/owner, use a system that will allow accurate relocation but that won’t endanger or limit other users of the site.

Check that all equipment has been packed for return to vehicle.


Annex 2: Forms

Field proforma for recording cover and structural characteristics for major species at a field siteSite no: Location: Date:

Dominant stratum CROWN 2nd stratum CROWN 3rd stratum CROWN

Species code Height Width Depth Gap Type Species code Height Width Depth Gap Type Species code Height Width Depth Gap Type

MEDIAN MEDIAN MEDIAN

Additional species:

Sample area : m x m

% grass Height Intercept in cm per m transect

Median values per stratum:

Stratum Height Width Depth Cover% Type* Stratum Height Width Depth Cover% Type* Stratum Height Width Depth Cover% Type

*Crown type (see Figure 5).


Site-based vegetation recording form

1. Site and recorder identification

Survey code: Site no: Permanent plot: Y / N Date:

Site type: 1. Quadrant2. Plotless

Plotless type: Broad floristic formation (Table 9):

Previous sampling date:

Recorder: Site dimensions: Replicate no: Area of vegetation represented by sample site:

Site photo: (Film/media no) Photo no: Location from which photos taken:

Map no: Map name: Map scale: Mapped vegetation unit?

Y / N

AMG zone: Easting: Latitude: Location in plot to which coordinates apply:Northing: Longitude:

Geocode method: Geocode precision:

Tenure type:

Locality:

Air photos (AP):

AP year: AP no: AP run: AP print: Colour AP B&W AP AP scale: 1:

AP of site location, mm from west edge to east: mm AP of site location, mm from south edge to north: mm

Weather conditions: When sampled:

Current & previous season:


2. Landform data

Altitude: m (+above/-below msl)

Altitude method: Altitude source:

Aspect: degrees (o) Aspect method: Compass Map-derived

Estimate – descriptive Other:

Aspect source:

Slope: degrees (0)percent (%)

Slope method: Slope source:

Morphological type:

Landform element: Landform pattern:

Site runoff: Distance to closest water supply:

m Type of water supply:

Permanent Seasonal: Other:

Controlled::

3. Land surface and substrate data

Soils

Observation type: Surface texture: Surface colour:

Great Soil Group: Soil depth: Soil drainage:

Microrelief: Y / N Vertical interval: Horizontal interval:

Gilgai type: Hummock type: Other type:

Litter cover: % Dead wood cover: % Bare ground cover: % Bare rock cover:-not lichen covered:-lichen covered:

%%%

Biological crust: %

Substrate

Observation type Rock type Rock class


4. Site disturbance

Disturbance Observation type Disturbance Observation type

Degree of impact Age (time since disturbance)

Presence / % area affected

Amount Age (time since disturbance)

Stratum affected Degree of impact

Storm damage: Roadwords:

Logging / thinning: Fire:

Ringbarking: Salinity:

Extensive grazing Weeds:

Grazing: type of evidence:

Floods:

Feral digging: Erosion:Water:Wind:

Comment:


5. Vegetation structure

GF L-1 (Growth form)

(Box 1)

GF L-3 Height(m)

Cover % BA m2 (Basal Area)

Species 1 Species 2 Species 3 Species 4 Species 5 Species 6

Height method: Cover method: BA method: BA factor:

DBH sample / BA sweep Y / N

Vegetation strata (Stratum 1 is the highest stratum irrespective of height

Stratum Dominant stratum (√ ) Cover % Height to stratum top: median (m)

Height to stratum top: max (m)

Height of stratum base: median (m)

Crown cover: 1

2

3

Method used for crown cover: Total plot cover %

Notes and profile diagram:


6. Wetland vegetation

Marine and coastal wetland Inland wetland Human-made wetland

Wetland type

Growth-form (Table 12)

Wetland notes:

7. Indicators of vegetation age structure

Code Growth stage Trees Shrubs Grasses & herbs Cryptograms

% crown cover Commonest crown shape

Mean crown openness

% crown cover % crown cover % crown cover

1 Early regeneration

2 Advanced regeneration

3 Uneven age

4 Mature phase

5 Senescent phase


8. Floristics

GF=growth form; St=stratum; Ht=height (m); %C=% crown cover; A=abundance; BA=basal area; C=collection no.; ID is ticked (√) when id is completed.

GF St Ht %C A/BA Species name C ID Herbarium reference no.


Annex 3: Schematic profiles of Australian vegetation types The schematic vegetation profiles developed by AUSLIG (1990, page 11), provide a useful generalised picture of the growth forms and height/cover classes presented in Table 9. The map codes printed in blue used in each structural diagram are those presented on the 1:5 million scale vegetation map in AUSLIG (1990).

Annex 4: Cover-abundance Cover-abundance is a method for estimating the quantity of each species in a vegetation sample that combines, in one scale, estimates of both cover and abundance. For cover values greater than 5 per cent, the scale is a measure of cover (see cover attribute above). For cover values of less than 5 per cent, the scale is a measure of abundance (i.e. the number of individuals in a defined area).

Of the many scales that have been proposed, the Braun-Blanquet cover-abundance scale presented here is used most widely. It is simple and, for most vegetation classification processes, produces robust estimates of cover-abundance. The system is predicated on the view that, in vegetation classification, it is more useful to have many samples of each type, with good estimates of species quantities, than only one or a few samples with a greater measurement precision. The basis for this view is that, since vegetation is often highly variable, it is better to have many samples of this variation than to have only a few precise and time-consuming measures that don’t adequately reflect the diversity of the field situation. On the other hand, if the objectives of the survey are narrowly focused and looking for fine levels of discrimination between samples or sampling times, then actual quantitative measurements might be more appropriate.

What to recordThe Braun-Blanquet cover-abundance scale is shown in Table 22. For each species at the sample site, record the code value that represents it.

Table 22: The Braun-Blanquet cover-abundance scale for estimating species quantitiesCode Description Crown cover percentage

5 Any number of plants covering more than 75 per cent of the sample site

> 75%

4 Any number of plants covering between 50 per cent and 75 per cent of the sample site

50–75%

3 Any number of plants covering25 per cent to 50 per cent of the sample site

25–50%

2 Any number of plants covering from 5 per cent to 25 per cent of the sample site

5–25%

1 Many individuals, but cover less than 5 per cent of the sample site, or scattered with cover up to 5 per cent of the sample site

<5%

+ (‘+’ pronounced ‘cross’) Few individuals, with small cover

Insignificant cover

r Single individual with small cover Insignificant cover

← Note: Modified from Mueller-Dombois & Ellenberg (1974).

How to collect Walk through and around the site several times to become thoroughly acquainted with it. Choose a location where the site can be best seen in its entirety or as close to it as possible. For each species, estimate and record cover-abundance. Start by asking whether a species cover

is greater or less than 50 per cent. If greater, is it greater or less than 75 per cent? If less than 50 per cent, is it greater or less than 25 per cent? If less, is it greater or less than 5 per cent? If less, is there more than one individual?

For the lower cover classes, it can be useful to imagine moving all individuals into one area and comparing that with a reference for the sample site. If the sample site is 400 square metres, for example, 5 per cent of the area would be 20 square metres (4 metres x 5 metres), and 1 per cent would be 4 square metres (2 metres x 2 metres).

To help reduce the errors inherent in the method it is useful to attach the cover-abundance scale to the cover of the field notebook for easy reference.

IssuesAlthough the method provides an absolute value for classes 2 to 5 (i.e. it is a percentage of a defined sample area), the class boundaries are wide and cover is being estimated, not measured. Many studies have shown that different observers, and the same observer at different times, often produce widely differing estimates. To ensure consistency, therefore, it is important to regularly calibrate observers.

Further informationGreig-Smith, P 1983, Quantitative plant ecology; Studies in ecology, volume 9, 3rd edition, Blackwell Scientific, Oxford, United Kingdom.

Mueller-Dombois, D and Ellenberg, H 1974, Aims and methods of vegetation ecology, John Wiley & Sons, New York, United States.

Documents

data.daff.gov.audata.daff.gov.au/brs/data/warehouse/pe_brs90000004198/... · Web viewThe full names and codes at four different levels of classification are as follows: Formation