Cape York Peninsula Land Use Strategy
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Cape York Peninsula Land Use Strategy
Abrahams, H., Mulvaney, M., Glasco, D., & Bugg, A.
Office of the Co-ordinator General of Queensland
Australian Heritage Commission, March 1995
The National Wilderness Inventory (NWI) is an environmental data base and a set of modelling procedures which are designed to assist in the planning and management of remote and natural lands in Australia. The NWI is compiled and maintained by the Australian Heritage Commission and is accessible through the Environmental Resources Information Network.
The inventory is designed to assess wilderness quality across the Australian landscape. It is a decision-making tool which supports purposes such as monitoring wilderness loss, delineating wilderness areas, defining management options and predicting the effects of development on wilderness values.
The NWI has, to date, made a major contribution to wilderness planning and management in many parts of Australia. For instance, the wilderness assessment process required under wilderness legislation in South Australia is underpinned by the NWI data base and wilderness analysis procedures. The results of the Victorian component of the NWI were utilised as the starting point for a Victorian Land Conservation Council investigation of wilderness in that state. NWI procedures for wilderness identification and assessment have also been incorporated into the management planning process for the Wet Tropics World Heritage Area. The NWI also forms a key part of the process for implementing the wilderness reserves component of the National Forests Strategy.
The program is designed to measure variation in wilderness quality in the landscape using consistent and objectively measurable criteria. The data base that is produced may then be used in an entirely flexible way to assist in determining which areas meet specified criteria for wilderness, which will be suitable for wilderness management and which should be considered for inclusion in a wilderness protection system.
A2.1 PRINCIPLES OF THE SURVEY METHODOLOGY
The evaluation of wilderness in the NWI is based on the concept of wilderness as part of a continuum of remote and natural conditions which vary in intensity from pristine to urban.
The wilderness inventory procedure is implemented by measuring variation in wilderness quality across the landscape using four wilderness quality 'indicators' that represent the two essential attributes of wilderness; remoteness and naturalness. These derive from the definition of wilderness quality as the extent to which a location is remote from and undisturbed by the influence of modern technological society. These indicators are:
Remoteness from - how remote a site is from places of Settlement permanent human occupation; Remoteness from - how remote a site is from established Access access routes; Apparent - the degree to which a site is free from Naturalness permanent structures associated with modern technological society; Biophysical - the degree to which a site is free from Naturalness biophysical disturbances caused by the influence of modern technological society.
Numeric values are calculated for each of the indicators for areas with an essentially natural cover and by standardising and combining these values a simple estimation of total wilderness quality, a total wilderness quality index, may be produced.
A2.2 STRUCTURE OF THE INVENTORY
A2.2.1 The Primary Data Base
A wide range of geographical information is required for the calculation of wilderness indicator values. This is the primary data base for the NWI.
The primary data base for Remoteness from Access includes all classes of road and vehicle tracks, railways, aircraft landing grounds and cleared area boundaries. The Remoteness from Settlement primary data base includes permanently occupied buildings and built up areas. The Apparent Naturalness primary data base includes all structures, including those mentioned previously. The primary data base for Biophysical Naturalness includes a variety of information relating to land use.
The degree of confidence which may be placed in final wilderness evaluations depends particularly on the accuracy and precision of the primary data. This raises issues in so far as change is ubiquitous in the Australian landscape and information about access, settlement and land use is often poorly recorded and lacking in currency. Even the most recently available information may be inaccurate and out of date. Field verification may be possible in situations where there are serious doubts as to the validity of information and where accuracy and precision is important. However, the expense of these activities is generally prohibitive. The NWI, in base-line surveys, has placed heavy reliance on pre-existing, documented primary data sources.
A2.2.1 The Wilderness Data Base
GIS modelling techniques are applied to the primary data base to produce a secondary data base; the wilderness data base. This data base is constructed by establishing a grid of sampling points across all areas selected for inclusion in the survey. A range of measurements are calculated for each sampling point which are then processed to produce values for each of the four wilderness quality indicators. These indicator values are, in turn, processed to produce a total wilderness quality index.
The wilderness data base consists of all measurements used to derive wilderness indicator values, the wilderness indicator values themselves, and the final wilderness quality index. Together, these attributes form a powerful and comprehensive data base which can be used for addressing a wide range of planning requirements for remote and natural lands.
A2.3. WILDERNESS QUALITY ASSESSMENT
A2.3.1 Remoteness from Settlement
A value for Remoteness from Settlement is based on the calculation of distance from each grid point to the nearest settlement feature. This measure of remoteness does not take into account the features of local terrain. (Terrain is a factor affecting many aspects of wilderness assessment and this will be introduced into NWI wilderness survey procedures in future).
Four grades of permanent occupation are defined, according to the degree of settlement they represent. A total Remoteness from Settlement value is derived by assigning a weight to each grade of settlement to reflect its considered level of influence on remoteness. This weighting factor is then used to standardise distance measures between the different settlement grades. This, in effect, converts all settlement locations to a major settlement equivalent. The nearest standardised distance for each grid point is then recorded. In this way the final indicator value reflects the greater influence of, for example, a small town compared with a single station or farmhouse in reducing remoteness values. The weighting factor applied to each grade of settlement in base-line NWI surveys is presented in Table A2.1.
TABLE A2.1 Settlement Features
Settlement Weighting Grade Descriptor Factor* Major Built-up areas and commercial and/or service 1.00 location with 100 permanent residents or more Intermediate Commercial and/or service location with more 0.80 than ten but less than 100 permanent residents Minor Commercial and/or service location with ten 0.74 permanent residents or less Residential Residential location only 0.66
* major settlement equivalent
A2.3.2 Remoteness from Access
Values for Remoteness from Access are derived by measuring distance to access features. Four grades of access are defined, according to the level of access provided and the degree of use received.
Weighting is applied in the same manner to the Remoteness from Settlement indicator to standardise all access features to high grade equivalence. The final indicator value therefore reflects the greater influence of, for example, a highway compared with that of a four-wheel drive track. The weighting factor applied to each grade of access in the base-line NWI survey is presented in Table A2.2.
TABLE A2.2 Access Features
Access Weighting Grade Descriptor Factor* High Major two-wheel drive roads: generally sealed or 1.00 at least surfaced to ensure regular and continuous public use Medium Minor roads: generally unsurfaced, or, if 0.71 surfaced, then irregularly used and maintained. Also included are constructed and maintained airstrips and operating railways Low Vehicle tracks (usually four-wheel drive) 0.33 Very Low Established but unconstructed vehicle access 0.20 routes (e.g. beach access) and cleared lines; established walking tracks; cleared land
* high grade access equivalent
A2.3.3 Apparent Naturalness
The Apparent Naturalness indicator is designed to account for the apparent impact that structures and disturbances have on wilderness quality. Relevant structures include: buildings, yards, bridges, bores, windmills, pipelines, fence-lines etc. Values for this indicator in base-line NWI surveys are obtained simply by calculating distance to the nearest defined structure.
Three grades of artefacts are defined, according to their scale and permanence. Weighting is applied for Apparent Naturalness in the same manner to the previous indicators, so that all structures are standardised to major equivalence. The weighting factor applied to each grade of structure in base-line NWI surveys is presented in Table A2.3.
TABLE A2.3 Apparent Naturalness Structures
Structure Weighting Grade Descriptor Factor* Major Intrusive infrastructure (including medium and 0.71 high grade access routes) and cleared land boundaries Medium Small-scale infrastructure (including four-wheel 0.40 drive tracks) Minor Minor structures 0.16
* major structure equivalent
A2.3.4 Biophysical Naturalness
The Biophysical Naturalness Indicator is a measure of ecosystem integrity, determined through an indirect assessment of intensity of landuse as a proxy for ecosystem integrity. For Cape York Peninsula, the Biophysical Naturalness coverage has been developed using five-data sets available from the Natural Resources Assessment Program (NRAP) reports. These were considered to provide the best systematic indication of current biophysical naturalness across the Peninsula. Additionally, the coding was consistent with that used across Australia by the National Wilderness Inventory (NWI). Information incorporated from the CYPLUS NRAP and Land Use Assessment Program (LUP) data sets has been selected to ensure that the best indication of existing (rather than potential) Biophysical Naturalness has been derived.
The flow chart used to derive the Biophysical Naturalness layer is at Table A2.4 with an explanation following.
The data sets incorporated in deriving the Biophysical Naturalness layer were:
Although a CYPLUS Land Use Program (LUP) addressing weeds and feral animals was available the data-sets were insufficiently systematic for inclusion in the derivation of the Biophysical Naturalness layer. Although it was hoped to include weed and feral animal information for CYPLUS, this has not been possible elsewhere in Australia either.
The NWI analysis was undertaken by the AHC using ArcInfo Version 6.1.1. The data-sets used in determining Biophysical Naturalness have been provided by Queensland Land Information Section (QLIS) from the CYPLUS GIS.
The flow chart illustrated shows how the data-sets have been combined to achieve an indication of Biophysical Naturalness on a scale of 0 - 5 (lowest to highest), and is consistent with that indicator used in the NWI elsewhere. In the determination of the Biophysical Naturalness coverage, categories within the original data-sets were chosen to be consistent with the NWI. These coverages were then combined using the 'Union' command to create one coverage with the attributes as attached.
A2.4 THE PROCESS FOR DELINEATING BIOPHYSICAL NATURALNESS COVERAGE.
A2.4.1 Vegetation Class - Neldner, Clarkson Vegetation Mapping
In the Neldner, Clarkson Vegetation Coverage (1994) , each vegetation class has a code. A number of classes directly indicate Biophysical Naturalness irrespective of other factors, for example:
These were directly calculated to Biophysical Naturalness codes (BN) of 0, 0 and 1 respectively
For all the other vegetation classes it is considered that land use, grazing intensity and soil characteristics will contribute to the Biophysical Naturalness. Land use, Tenure, Grazing and Soil degradability are incorporated in the analyses as on the flow diagram.
A2.4.2 LUSE - Land use coding from the Biggs & Philip Soils Coverage.
A field for current land use was incorporated in the Biggs & Philip (1994) soils mapping. In a similar fashion to the vegetation coverage, there were land use categories that indicate Biophysical Naturalness irrespective of other factors, and these categories were able to be directly given a Biophysical Naturalness code consistent with that used elsewhere across Australia as follows:
Where landuse is coded a 'No Effective Disturbance' or 'Disturbance only by Hoofed Animals' then consideration of tenure, grazing rate, and soil degradability was incorporated on the flow diagram.
LUSE was incorporated as follows;
Biggs & Description BN Code Philips LUSE Code 0 No effective disturbance Consider other parameters 1 No effective disturbance other Consider other than by hoofed animals. parameters 2 Limited Clearing 2 3 Extensive Clearing 1 4 Complete Clearing, Pasture 0 5 Complete Clearing Pasture Stage 0 6 Cultivation Rainfed 0 7 Cultivation Irrigated 0 8 Highly Disturbed 0
A2.4.3 Tenure - Determined from the Qld Dept of Lands DCBD coverage. (Qld Lands 1994)
The tenure codes were reclassified for this analysis according to the attached table (Table A2.2). Some categories were considered to provide a direct indication of Biophysical Naturalness irrespective of other consideration while in other tenure categories Biophysical Naturalness coding was calculated as follows for those instances:
For tenures other than above, ie some form of leases, freehold or Aboriginal tenure, assume that grazing has occurred and the impact is related to the soil degradability and potential grazing rate.
Biophysical Naturalness for the later two categories was determined incorporating the following information.
A2.4.4 Grazing Rate: From Cotter Pastoral Industry Mapping of Country Types.
Cotter (1994) identified the potential grazing rate for the country types mapped as an indication of suitability for cattle harvesting. These classes were themselves derived from the Neldner, Clarkson Vegetation coverage (1994). These rates were grouped into nine categories that equated with the probability of grazing density. These nine categories of grazing suitability have been further grouped into five to give an indication of long term grazing impact .
'Average' grazing rate as follows:
Grazing Rate Five Group Code Nine Group Code
> 175 hectares per beast Impact Insignificant (8,9)
145 - 175 hectares per beast Impact Minimal (7)
60 - 145 hectares per beast Impact Very Light (6)
30 - 60 hectares per beast Impact Light (4,5)
< 30 hectares per beast Impact Moderate (1,2,3).
These categories have been considered in association with the Soil Degradability as it was considered that grazing rate alone would not provide a direct indicator of Biophysical Naturalness. The flow chart graphically illustrates the connections.
A2.4.5 Soil Degradability: From the Biggs & Philip Soils Mapping
This information was used to strengthen the relationship between intensity of landuse to ecosystem integrity. Biggs and Philip (1994) identified three categories as indicators of Soil Degradation potential. When used in relation with the grazing rate information described above, an indication of existing disturbance can be achieved. For example stable soils only capable of maintaining a low grazing rate were considered to be of higher Biophysical Naturalness than areas of higher grazing density on very unstable soils. Soil Degradation potentials as mapped by Biggs and Philip are as follows:
1 Stable soils - low potential for degradation.
2 Unstable Soils - moderate potential for degradation.
3 Very unstable Soils - susceptible to degradation.
0 No soils information - low potential for degradation.
The category 0 exists where there are slight differences in the extent of GIS coverages and the Vegetation, Tenure etc coverages extend beyond the soils coverage. These small peripheral and coastal areas and consequently considered of low potential for degradation by grazing.
A2.4.6 Bores: From Queensland Department of Primary Industries Ground Water Coverage (QDPI 1994)
The presence of both grazing cattle and feral or pest species, is strongly influenced by availability of water. The Cotter Country Types effectively address the availability of surface water across the Peninsula. The ground water coverage of bores was used to provide additional information regarding water sources to enable grazing impact to be modelled accordingly. Only the location of water supply bores was considered. Biophysical Naturalness for areas within a ten kilometre radius of the bores, the approximate distance from a bore that cattle will range if the bore is the only supply of water. A Code = 100 for areas <10km from a bore compared with Code = 0 for those areas >10km from bores.
A2.4.7 Calculation of Biophysical Naturalness
The attributes described above were combined following a logical decision tree (Table A1.1) to derive the overall Biophysical Naturalness Indicator. The National Wilderness Inventory scale use of 0 - 5 ensures a consistent indication of Biophysical Naturalness across Australia. While undertaking the calculation of Biophysical Naturalness, frequent checks were made of the number of polygons affected to ensure the analysis was discrete as anticipated. The distribution of the quality of Biophysical Naturalness across Cape York Peninsula is shown at Figure 3.1, in the main body of this report.
A2.6 TOTAL WILDERNESS QUALITY
A total wilderness quality index may be produced by performing operations on wilderness indicator measurements. Key operations include standardising, deriving class values for the distance-based indicator measurements and combining indicator class values.
Base-line NWI surveys express variation in wilderness quality in terms of a standardised classed scale. Class values for Remoteness from Access, Remoteness from Settlement, and Apparent Naturalness are assigned according to the standard functions shown in Figure 4. Each of these distance-based indicators are represented by continuous data, so that there is no defined upper limit to class values. This is not the case for Biophysical Naturalness which is categorical data, having a built-in five level standard. Biophysical Naturalness indicator class values may be included in a total wilderness quality assessment on a comparably weighted basis by setting a maximum class limit at five for the distance-based indicators. The class five level for each of the distance-based indicators is shown in Figure A2.1.
FIGURE A2.1 Wilderness Indicator Classification
* Measurements are weighted and expressed in terms of distance from: high grade access equivalent, major settlement equivalent and major structure equivalent.
A total wilderness quality estimate may be produced by combining indicator class values. The standard process is additive, resulting in a total wilderness quality scale ranging from minimum to maximum indicator class value combinations. This procedure rests on the assumption that each indicator contributes independently and equally to total wilderness quality.
The additive process may also incorporate procedures which ensure wilderness quality assessments meet specific requirements. For instance, minimum thresholds for each indicator may be applied to ensure the exclusion of areas which do not meet minimum levels of remoteness and naturalness.