A moment's reflection on the nature and distribution of landcover and its potential disturbance across the continent will result in the simple conclusion that not all disturbance factors are everywhere equally important. The most intensive landuses are located in the south of the continent: those in the centre and north of the continent are extensive rather than intensive.
Therefore, to achieve the greatest sensitivity in assessment, it was necessary to stratify the continent into regions based on the importance of one or more disturbance factors. Then, based on this stratification, the quantification stage using satellite image data can be customised to maximise the detection of the landcover disturbance characteristic of that particular landuse type.
The most severe and extensive disturbance to landcover has been, and remains that provided by landuse: the direct result of human activities.
By comparison, the perturbations generated by climate and weather are either so gradual to be imperceptible even over centuries (climate), or rapid but very localised in occurrence (weather - storms, etc.). In contrast, the agents of ancient and modern landuse, fire and mechanical or chemical clearing, are far more influential.
There seems little doubt that Aboriginal Australians significantly disturbed the landcover (and the fauna) of the continent through their use of fire throughout the millennia of their occupation of this continent. They shaped the face of much of Australia in a way that was separable from the very large climatic changes of the last 30, 000 years; see Pyne (1991).
The landcover consequences of an early Dry Season burn in a northern Australian savanna. Fire is a landuse tool with poorly understood long-term consequences for biodiversity; millennia of its application by Aboriginal Australians notwithstanding.
There is no doubt that in the last two centuries European Australians have also changed the landcover of the continent, both extensively and substantially through agricultural and pastoral landuse. Therefore, we primarily stratified the continent by landuse. Because we were interested only in the landcover consequences of landuse, we used a simple two-level stratification.
The first and most important decision was which landcover consequence of landuse is the most significant disturbance for biotic erosion? That we took to be habitat destruction by the clearing of natural vegetation and its replacement by crops and pastures; eg see reviews by Caughley (1994), Noble et al (in preparation), Saunders et al (in preparation).
As a consequence, the principal stratification of the continent was based on the location of clearing; where clearing of native vegetation for replacement with (exotic) crops, pasture and forest vegetation has been and remains the principal disturbance. Within this area of the continent, the impact of landuse on landcover is principally one of replacement. The consequences for the biodiversity that was originally characteristic of the native vegetation are obvious and severe.
Much, but certainly not all, of the biotic erosion of the last two centuries was concentrated in the areas of replacement landuse. It follows then that the continued expansion of this landuse offers the largest threat of accelerating biotic erosion; eg Saunders et al (1994); Hobbs and Saunders (1994).
Urbanisation and mining, like agriculture, are also replacement landuse types. On a continental scale, the direct landuse consequences of mining are trivial and not considered in this study. While urbanisation is perhaps a hundred-fold more extensive than mining, its direct landcover consequences are also not significant on a continental scale. However, the indirect influence of urbanisation on landcover change is substantial. Urban populations are growing and need to be fed and clothed. Urban political values concerning the conservation of biodiversity are also changing.
The dividing lines between the areas of the continent where landcover clearing was the most significant disturbance factor were drawn after searching the satellite image data by eye. Expert interpretation, rather than machine decision, was used because in the detection of the irregular and diffuse boundaries of clearing, the former cannot yet be matched by the latter.
The boundary was finalised by allowing a generous geographic margin beyond the edge of the clearing, approximately 100 km, and aligning it with the national grid of the 1:250,000 scale topographic map sheet series. Using this criterion, the continent was divided roughly into one third and two thirds as in Table 1.
Stratification of the continent by the landcover consequence of landuse. The outermost region (red) encompasses those areas where the principal landcover disturbance threat was clearing for crops, pastures and forests. However, not all of this area was cleared. In the innermost region (green), the principal landcover disturbance results from grazing and burning.
Table 1: The absolute and relative sizes of the two principal strata, the ILZ and the ELZ, used to divide the continent.
km2 %
_____________________________________________________________
Intensive Landuse Zone 2983908 39
Extensive Landuse Zone 4708092 61
_____________________________________________________________
Total 7692000 100
We emphasise that this division was not based on the area actually cleared for agriculture. Rather it was based on the threat of clearing, both actual and potential. Therefore, we have not used the obvious names of cleared and uncleared for fear of generating misunderstanding.
Rather, we have coined the names Extensive Landuse Zone (ELZ) for the central core of the continent and Intensive Landuse Zone (ILZ) for the remaining coastal strips. As defined and illustrated above, the Intensive Landuse Zone is approximately 39% (2, 984, 000 km2) of the continent and contains perhaps more than 90% of the national population. In contrast, the Extensive Landuse Zone is almost twice as large, 4, 708, 000 km2 in size (61%) but carries as little as 5% of the national population.
Not all the ELZ is used on a permanent basis. Within this area of the continent, the most common landuse is extensive pastoralism that in terms of landcover consequences is a harvesting landuse. Like forestry based on native forests and woodlands, it is notionally sustainable where the offtake is small and irregularly patterned in time and space. Nonetheless, most surveys of the impact of extensive pastoralism, past and present, show that considerable landcover change has occurred and because of it, or at least in synergy with the arrival of domestic stock and establishment of feral animals initially released in the ILZ, substantial biotic erosion has occurred also; James et al (In Press), Newsome (1994), Pickard (1994).
Besides extensive pastoralism, there are two other landuses within the Extensive Landuse Zone; Traditional Use and Unused.
These are Aboriginal Australians on Aboriginal land. They are Traditional Owners but this is not Traditional Landuse.
Unused land, or unallocated crown land, most of it in Western Australia, is not completely without the impact of human activity but here it is patchy and episodic.
For the landuses of Traditional and Unused, it was difficult, for understandable reasons, to assess the level of landcover disturbance using satellite data. The partitioning and distribution of finer divisions of landuse within the Intensive and Extensive Landuse Zones is discussed in Adding What Is Known.
A second and independent stratification of the continent was needed by which to aggregate the detected landcover disturbance.
The type of stratification chosen was largely determined by the purpose and scale of the analysis. Possible choices for the basic area unit (strata) could be the (relatively) small area of a farm or a local government area (LGA), or the much larger area of a state, if the purpose of the analysis was landcover management responsibility. However, in this study the principal focus is biodiversity.
Therefore, an ecologically relevant stratification has been used. As argued earlier, with a continental perspective, issues of scale and ecological understanding decide that the most relevant stratification was by landcover types; ie a typology based on vegetation and soil attributes.
The task of deriving a tractable set of consistently defined, landcover types was difficult. Considerable effort was made to evaluate a wide range of alternatives. The final choice was based on two simple and pragmatic reasons. Because the objective of the project was to quantify landcover disturbance, the basic stratification should be on landcover attributes; ie vegetation and soil variables.
Continental datasets of vegetation structural type exist, eg AUSLIG (1990), as does one for soils, Northcote et al (1975). Because attempts to reconcile and integrate these two datasets were unsuccessful, the dataset of Natural Vegetation, AUSLIG (1990), became the source typology for landcover.
It was assumed that considerable climate, soil and topographic information was implicit in this continentally consistent mapping of vegetation at landscape scales. Use of this dataset was not without difficulty and error. Nonetheless, the dataset Natural Vegetation, the vegetation as of 1788, was taken to be the basic ecological divisions of the continent.
Two conditions on the use of the Natural Vegetation dataset were noted. The first was that it was taken to be the truth: the boundaries and descriptions of its 230 categories were not disputed even though they occasionally appeared to be doubtful. The second was that the large number of primary categories of Natural Vegetation was reduced to a smaller set (34) by concentrating on overstorey structural and floristic attributes (height, cover, genus), and ignoring the understorey. Pragmatic reasons required that all overstorey genera other than Eucalyptus and Acacia be pooled, and within these three genera, the tall (T), medium (M), and low (L) height categories also be pooled; Table 2. The nomenclature was derived from that used in AUSLIG (1990).
Table 2: A summary description of the 34 landcover types derived from the original 230 categories of the Natural Vegetation dataset of AUSLIG (1990). The figure in brackets under the Code symbol is the percentage projected foliage cover (pfc).
Number Code Name
_________________________________________________________________________
1 xTML4 Tall, medium and low closed forest: dominant
(70-100) overstorey genus is other than Eucalyptus or Acacia
2 eTML3 Tall, medium and low forest: dominant overstorey
(30-70) genus is Eucalyptus
3 wTML3 Tall, medium and low forest: dominant overstorey
(30-70) genus is Acacia
4 xTML3 Tall, medium and low forest: dominant overstorey
(30-70) genus is other than Eucalyptus or Acacia
5 eM2 Medium open forest: dominant overstorey genus is
(10-30) Eucalyptus
6 wM2 Medium open forest: dominant overstorey genus is
(10-30) Acacia
7 xM2 Medium open forest: dominant overstorey genus is
(10-30) other than Eucalyptus or Acacia
8 eL2 Low open forest: dominant overstorey genus is
(10-30) Eucalyptus
9 wL2 Low open forest: dominant overstorey genus is Acacia
(10-30)
10 xL2 Low open forest: dominant overstorey genus is other
(10-30) than Eucalyptus or Acacia
11 eM1 Medium sparse forest: dominant overstorey genus is
(0-10) Eucalyptus
12 eL1 Low sparse forest: dominant overstorey genus is
(0-10) Eucalyptus
13 wL1 Low sparse forest: dominant overstorey genus is
(0-10) Acacia
14 xL1 Low sparse forest: dominant overstorey genus is other
(0-10) than Eucalyptus or Acacia
15 eS3 Tall shrubland: dominant overstorey genus is
(30-70) Eucalyptus
16 wS3 Tall shrubland: dominant overstorey genus is Acacia
(30-70)
17 xS3 Tall shrubland: dominant overstorey genus is other
(30-70) than Eucalyptus or Acacia
18 eS2 Tall open shrubland: dominant overstorey genus is
(10-30) Eucalyptus
19 wS2 Tall open shrubland: dominant overstorey genus is
(10-30) Acacia
20 xS2 Tall open shrubland: dominant overstorey genus is
(10-30) other than Eucalyptus or Acacia
21 eS1 Tall sparse shrubland: dominant overstorey genus is
(0-10) Eucalyptus
22 wS1 Tall sparse shrubland: dominant overstorey genus is
(0-10) Acacia
23 xS1 Tall sparse shrubland: dominant overstorey genus is
(0-10) other than Eucalyptus or Acacia
24 xZ3 Low shrubland: dominant overstorey genus is other
(30-70) than Eucalyptus or Acacia
25 xZ2 Low open shrubland: dominant overstorey genus is
(10-30) other than Eucalyptus or Acacia
26 wZ1 Low sparse shrubland: dominant overstorey genus is
(0-10) Acacia
27 xH2 Hummock grassland: dominant genus is variable
(10-30)
28 xG4 Closed grassland: dominant genus is variable
(70-100)
29 xG3 Grassland: dominant genus is variable
(30-70)
30 xG2 Open grassland: dominant genus is variable
(10-30)
31 Littoral Littoral complex of variable canopy structure and
composition
32 Lakes Permanent and ephemeral
33 xG1 Sparse open grassland: dominant genus is variable
(0-10)
34 xF1 Sparse open grassland: dominant genus is variable
(0-10)
The areal extent of any one landcover type varies greatly as does its distribution between the ILZ and ELZ; see the next image and Table 3.
The relative size and distribution of the 34 landcover types over the Australian continent and within and between the Intensive and Extensive Landuse Zones.
Within the ILZ, the most extensive landcover type was eM2; the open, medium height (10-30 m) eucalypt forests (or woodlands) which range from tropical to temperate climates. Within the ELZ and the continent as a whole, by far the most extensive landcover type was wS1; the tall, sparse Acacia shrublands that cover much of the arid sandplains; see again the last image.
Table 3: A statistical summary of the 34 landcover types that were the basic ecological strata for this study. The nature and severity of disturbance are determined for each strata within the Intensive and Extensive Landuse Zones. The areas are in km2.
ILZ ELZ Continent
Code Area % Rank Area % Rank Area % Rank
_____|________________________| ______________________| _______________________|
xTML4 44031 1.5 14 1696 0.0 31 45727 0.6 22
eTML3 440494 14.8 2 52799 1.1 16 493293 6.4 5
wTML3 107962 3.6 10 14050 0.3 22 122012 1.6 17
xTML3 19355 0.7 22 2874 0.1 29 22229 0.3 28
eM2 773927 26.0 1 199421 4.2 7 973347 12.7 2
wM2 1021 0.0 30 0 0.0 33 1021 0.0 34
xM2 13971 0.5 23 978 0.0 32 14949 0.2 30
eL2 158227 5.3 5 62251 1.3 13 220478 2.9 10
wL2 147730 5.0 8 58549 1.2 14 206280 2.7 11
xL2 119002 4.0 9 20087 0.4 20 139090 1.8 15
eM1 171560 5.8 4 2473 0.1 30 174033 2.3 12
eL1 149512 5.0 6 768347 16.4 3 917859 12.0 3
wL1 42470 1.4 15 129632 2.8 8 172102 2.2 13
xL1 68333 2.3 12 311320 6.6 4 379654 4.9 6
eS3 19893 0.7 20 0 0.0 33 19893 0.3 29
wS3 34543 1.2 16 8933 0.2 24 43476 0.6 24
xS3 19429 0.7 21 8555 0.2 25 27984 0.4 25
eS2 238537 8.0 3 43146 0.9 18 281683 3.7 9
wS2 26586 0.9 18 778391 16.6 2 804977 10.5 4
xS2 44717 1.5 13 6195 0.1 27 50911 0.7 21
eS1 29443 1.0 17 116866 2.5 9 146309 1.9 14
wS1 21279 0.7 19 1139096 24.2 1 1160375 15.1 1
xS1 5632 0.2 29 53283 1.1 15 58915 0.8 20
xZ3 8103 0.3 26 3625 0.1 28 11728 0.2 33
xZ2 82016 2.8 11 293012 6.2 5 375028 4.9 7
wZ1 724 0.0 31 22990 0.5 19 23714 0.3 27
xH2 170 0.0 32 44725 1.0 17 44895 0.6 23
xG4 6212 0.2 28 7283 0.2 26 13495 0.2 32
xG3 149436 5.0 7 215626 4.6 6 365062 4.8 8
xG2 6515 0.2 27 115842 2.5 10 122357 1.6 16
Littora 11220 0.4 24 16662 0.4 21 27882 0.4 26
Lakes 11220 0.4 24 108681 2.3 11 119901 1.6 18
xG1 0 0.0 33 76848 1.6 12 76848 1.0 19
xF1 0 0.0 33 13966 0.3 23 13966 0.2 31
