Soil–landscape resource assessment for plantations — a conceptual framework towards an explicit...

Soil±landscape resource assessment for plantations Ð aconceptual framework towards an explicit multi-scale approach

Robin N. Thwaitesa,*, Brian K. Slaterb

aSchool of Land and Food, The University of Queensland, St Lucia, Qld 4072, AustraliabSchool of Natural Resources, Ohio State University, Columbus, OH, USA

Abstract

Soil survey is a major component of forest land resource assessment. Conceptual and operational problems arise from

employing the conventional methods of survey in forest lands, namely: implicit methods of landscape interpretation (lack of

explicit procedures), transfer of data by analogy to unsampled landscapes by inferences which are scale-, and interpreter-

dependent, variability of intuitive surveyor judgement, and poor expression of soil variation within map units. These issues are

being addressed through the forestland resource assessment and modeling study (FRAMS). This study rede®nes the

conceptual process of resource assessment, and applies soil±landscape modeling (developed here as regolith±terrain

modeling) by developing explicit relationships between soil±landscape attributes within a digital, spatial geographic

information system (GIS) framework. Soil survey (advanced here as regolith±terrain modeling) is the science and art of

predicting soil attribute patterns in the 3D landscape. The FRAMS attempts to overcome some scale and procedural issues

related to soil mapping in forest site assessment by adopting a multi-scale and explicit landscape modeling approach. The

conceptual aspects of the method presented here aim to predict the ranges in variation of soil±geomorphic attributes that are

relevant to forest plantation management. Soil±landscape analysis is adapted in this study to encompass regolith±terrain

analysis (i.e. the complete regolith within an understanding of geomorphic systems) employed at three environmental scales:

`hillslope', `catenary', and `landscape'. There is no linear relationship of data resolution and expression of regolith±terrain

attributes between these scales. Each scale is a scale-dependent system linked by an explicit multi-scale method.

When combined with geological and climatic data analysis the resultant model provides an advanced, strati®ed sampling

scheme for subsequent ®eld survey procedures in forestland resource assessment. The ®eld analysis, remote-sensing and

digital terrain model (DTM) analyses are managed in a raster GIS and can then be effectively classi®ed, a posteriori, according

to `fuzzy logic' rules.

In the FRAMS, we investigate the scale effect on both the regolith±terrain parameters and their notional relationships to

forestland management by investigation at ®ner scales: hillslope and catenary scales (in southeast Queensland for planted

native hoop pine (Araucaria cunninghamii)), and at a broader scale: the landscape scale (in north Queensland for native

species reforestation). The study is still in the preliminary stages so the model is not yet fully functional nor have the

components been validated so far. # 2000 Elsevier Science B.V. All rights reserved.

Keywords: Site assessment; Forest ecosystems; Land evaluation; Terrain analysis; Forest soils; Fuzzy logic; Soil±landscape modeling

1. Forestland resource assessment

Lack of soil information at appropriate scales hin-

ders forest management in Australia, not only for

Forest Ecology and Management 138 (2000) 123±138

* Corresponding author. Tel.: �61-7-3365-1689;

fax: �61-7-3365-2965

E-mail address: [email protected] (R.N. Thwaites).

0378-1127/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.

PII: S 0 3 7 8 - 1 1 2 7 ( 0 0 ) 0 0 4 1 6 - 3

management of the current forested lands, but also for

planning (Thwaites, 1997). Soil information is an

essential component of forest site assessment. Forest

site classi®cation can take a variety of forms depend-

ing on the purpose and type of data collected (Grey,

1980). The more complex form integrates biophysical

data to produce a generic classi®cation for several

forest management and planning purposes. Site clas-

si®cation systems for native forest management in

Australia are dominated by a plant ecology bias,

whereas site survey and classi®cation for plantation

forestry tend towards characterization of physical land

qualities, those related to soil, landforms and hydro-

logical factors. This latter bias for plantation forests is

mainly owing to:

1. the ephemeral nature of the vegetation compo-

nents of the assessed ecosystems, which is

dominated by a managed crop;

2. the disturbed nature of the plant ecosystem

because of intensive management influences;

3. the strong expression of physical landscape

character and relevant attributes by pedological

and geomorphological features;

4. the stability of the physical components of the

ecosystem, even under disturbed circumstances.

These criteria are also valid for native forests.

Different purposes for forest land assessments have

spawned distinct philosophical approaches to the pro-

cess. These can be classi®ed into three broad themes

(Thwaites, 1997):

1. Phytocentric Ð plant species and communities

serve as indicators (phytoindicators) of site

properties;

2. Geocentric (or physiographic) Ð soil factors,

topography, parent materials, geomorphic factors,

climate are the site indicators (geoindicators);

3. Integrated Ð combines phytocentric and geo-

centric approaches.

Phytocentric models are valid for tracts of compara-

tively intact native ecosystems vegetation and for

characterization of landscapes for ecological and sil-

vicultural management purposes. They establish con-

ceptual relationships between the biotic and abiotic

components of the ecosystem.

Geocentric models of site classi®cation have been

developed because of disturbances to biotic compo-

nents of ecosystems caused by intensive land use

development and management. These models are

based on concepts of abiotic relationships (often

poorly expressed) with silvicultural requirements to

predict the performance of any site for a speci®c forest

land use. In the absence of detailed information for

any tract, geocentric forestland/site classi®cation is a

valid and sound process because the soil and soil-

in¯uencing processes relate directly to responsible

land resource management and planning.

Integrated systems have been developed with the

intention of holistic assessment of ecosystems as well

as to serve multi-objective land management. This

concept originated with the integrated survey (Chris-

tian and Stewart, 1953) and allied land systems

approaches to the complex land resource survey sys-

tems widely employed today, largely for strategic

planning and land capability and suitability analysis.

Soil survey has developed this century to become

more of an integrated approach in general Ð at the

broad scale. At ®ner scales, and in plantation forestry

(particularly after ®rst rotation), the geocentric

approach applies to conventional soil survey.

Some conceptual problems with conventional soil

survey (expressed by Hewitt, 1993; McKenzie and

Austin, 1993; Slater and Grundy, 1999; Thwaites,

2000a, and others) still linger, e.g. implicit methods

of landscape interpretation which are not recorded or

rationalized (and a corresponding lack of explicit

procedures), transfer of data by analogy to unsampled

landscapes by inferences which are scale-, and inter-

preter-dependent, variability of intuitive surveyor jud-

gement, poor expression of soil variation within map

units, poor ability to validate resultant maps, and a

priori groupings of soil attributes into classes through

implicit criteria.

Technological advances have in¯uenced the more

practical side of land resource assessment. Faith in the

potential use of digital terrain models (DTMs) in

aiding soil±geomorphic forest site classi®cation has

been held for many years (e.g. Grey, 1984; Thwaites,

1988) since their development as altitude matrices in

the late 1970s. Only recently, however, has generally

available computing power allowed the necessary

experimentation with DTMs for forestland resource

assessment (e.g. Gessler et al., 1995; Thwaites, 1995).

The ef®ciency of site surveys, and hence site classi-

®cation, can be increased by using easily identi®able

124 R.N. Thwaites, B.K. Slater / Forest Ecology and Management 138 (2000) 123±138

features in the landscape and applying land-forming

processes.

The traditional implicit and intuitive methodology

of soil survey can be enhanced by de®ning the con-

ceptual process and by developing explicit relation-

ships between soil and geomorphic (later de®ned as

`regolith±terrain') components.

This paper concentrates on the role of explicit

spatial relationships within physical land processes

Ð the soil and geomorphic elements Ð for forest site

assessment, hereafter termed `forestland resource

assessment'. The concepts of the soil±geomorphic

relationships to forestland resource assessment are

presented here through the experience of the continu-

ing forestland resource assessment and modeling

study (FRAMS). As the development of the models

and the subsequent analyses are still underway, the

results of this study and its outputs will be published in

the future.

The objectives of the FRAMS are:

1. To predict the spatial variation in pedogeomorphic

attributes and patterns that are relevant to the

planning and management of plantation forest-

lands; in this study, those attributes relating to soil

water are emphasized as the soil±geomorphic

factor that has a direct relationship to forest

productivity as well as other land management

considerations.

2. To accommodate the sensitivities of changes in

spatial scale that are necessary to address in a

multi-objective land resource assessment; the

systems studied change their character according

to changes in scale and level of investigation

requires a statement of scale and resolution

characteristics.

3. To represent the continua of complex pedogeo-

morphological relationships at particular scales

more realistically by avoiding a priori application

of taxonomic schemes that result in uncertain and

unclear polygon map units; the technique favored

for this study is that of a posteriori expression

through fuzzy rules-based classification.

A problem arises with the temporal variability of

attributes that are being measured. The intention is to

measure or estimate temporally stable (at ®ner time

scales) soil parameters such as water holding capacity

through texture, structure and fabric of the soil, or bulk

density by direct or surrogate means. However, all

characteristics are prone to vary over time, but over

different time scales. The interest is in the spatial

variation of selected attributes rather than their varia-

tion over time. Allen and Hoekstra (1992) argue the

point that all scienti®c modes of ecological investiga-

tion demand that a window of observation be de®ned

on a speci®c time/space scale. Inevitably, certain

phenomena will be consigned to the background while

focusing on the system boundaries, components and

interactions that are central to the study. For the

purposes of this study we are focusing on the spatial

aspects of the soil±landscape systems at various

scales. Whilst cognizant of variation within and

between time scales we have consigned the time-

dependence characteristics of the soil±phenomena

to the background.

1.1. Soil in forestland resource assessment

Soil factors play an important role in assessing

forest site quality and performance. Therefore, soil

classi®cation (i.e. soil description and interpretation)

has been employed by forest managers to characterize

sites in terms of growth performance and other man-

agement properties at the ®ner scale. However, much

of the operational and technological progress in soil

survey has been for agricultural land or for special

developments. In many surveys soils appear to stop at

the forest boundary. Generic soil surveys of lasting

quality have been undertaken only occasionally on the

public forest estate, at a variety of scales. Soil mapping

of private forestland has been variable at best, with

updated comprehensive soil surveys being rare

(Thwaites and Payn, 1997). Forest managers in Aus-

tralia and New Zealand have not prioritized consistent,

routine soil survey and physical site assessment for the

whole of their forest estates. This is largely on con-

siderations of cost, although the cost/bene®t ratio is

favorable (e.g. Turvey, 1984). A survey of forest

managers in Australia and New Zealand indicated

that soil survey procedures are generally ill-under-

stood and that the outcomes from soil survey also

appear to be commonly underestimated and underused

(Thwaites and Payn, 1997).

Much of this poor perception seems to arise from

the generality of information presented in soil survey

reports, the mapping scales used, and their inability to

R.N. Thwaites, B.K. Slater / Forest Ecology and Management 138 (2000) 123±138 125

serve multiple purposes. Survey and mapping of gen-

eric soil types are not necessarily useful for forestry

planning and management. Most soil classi®cation

systems (taxonomies) either are biased towards agri-

cultural requirements or are speci®c to pedological

inventory. A `technical' soil-site survey must be

designed for forestry purposes. This is a task for

specialists with a methodology devised for particular

goals. Even with a broadly applicable technical for-

estry survey approach, the forest managers may not

get what they want. Either the initial terms of refer-

ence (TOR: the agreed requirements for conducting

the survey and the results to be achieved) are inade-

quate or the soil-site assessor cannot provide the

detail the managers require at the scale or in a form

for which they are prepared to pay (Thwaites and

Payn, 1997).

A way around this (besides addressing the issue of

the TOR) is to rethink the types of information that are

acquired as part of a forest soil-site assessment, and to

develop methods for multiple scales with multiple

objectives. The major constraints to achieving this

have been (i) the time and labor costs of the necessary

®eld survey and interpretation of site attributes and

characteristics, the outputs of which could be used at a

variety of scales, and (ii) the unwillingness to quantify

the many attributes and characteristics (again, largely

because of the cost) that are necessary for multi-

objective interpretation.

Forestland assessment methodology normally com-

prises a soil survey to predict potential productivity of

sites to guide site remediation and management. This

is usually perceived as a comparatively simple scheme

that relates speci®cally to the individual management

regime of the forest, and that can be undertaken by

forestry staff who are not necessarily skilled in the

rigorous procedures for soil survey. However, forest

managers and planners now expect more bene®ts out

of the forestland assessment process in the longer

term, and for a wider range of purposes than nutri-

tional management and establishment requirements

(Thwaites and Payn, 1997). This is because of

increased pressures to embrace environmentally sen-

sitive site management for long-term sustainability

and the desire to grasp the opportunities offered by

advances in technology and management methods.

The desirable aim of soil survey information is to

realize effective site-speci®c forest management.

2. Process-based systems and geocentricity

Site survey and classi®cation of forested environ-

ments should integrate, as far as practicable, the

abiotic and biotic components by recognizing ecolo-

gical principles (Grey, 1980). This is not just a descrip-

tive process, as demonstrated in the past by the

widespread use of `land systems' surveys (e.g. Wertz

and Arnold, 1972; Wendt et al., 1975), amongst many

others, but as an expression of landscape±ecosystem

processes. In this way site classi®cation is seen to be

dynamic and relevant to multi-objective forest land

use planning and management.

Bourne (1931) expressed the concept of forest site

as a biophysical, dominantly physiographic, notion of

site regions. He advocated the use of aerial photo-

graphy. European (and especially east European) site

assessment has also favored this concept, both for

native and planted forests, apparently following the

Russian approach of employing the `biogeocoenose'

(Sukachev and Dylis, 1968). The biogeocoenose is a

macro-view of the ecosystem developed in the 1920s

and 1930s. We would now call this a holistic viewpoint

encompassing ecosystem processes, as expressed by

the seminal `Total Site' concept of Hills (1953) in

North America. Site is therefore considered as an

arbitrary subdivision of the landscape, regardless of

scale. It is generally perceived as a natural unit, a

spatial entity which cannot be subdivided without the

loss of an intrinsic characteristic.

The geocentric basis to site assessment, with an

emphasis on the soil and geomorphological compo-

nents, found favor with some agencies in the western

USA with the land systems approach (e.g. Steinbren-

ner, 1965), and for eastern USA hardwoods (Smalley,

1984), as well as some provinces of Canada, e.g. New

Brunswick (Van Groenewoud and Ruitenberg, 1982).

Neither Australia nor New Zealand has had a uni-

®ed approach to forest site assessment. Nor has there

been discussion in the local technical literature about

such a coordinated approach (Thwaites and Payn,

1997). Each state agency responsible for forestry in

Australia has adopted procedures that have suited

local forest types, productivity goals, and expertise.

An emphasis on phytoecological (rather than geoeco-

logical) methods has resulted. This is broadly based on

site index and forest typing, even though the methods

have changed over time (Thwaites, 1997). Some


agencies in Australia have forged the geocentric direc-

tion and have emphasized soil and geomorphic factors

in classi®cations as research tools (e.g. Turner and

Holmes, 1991; Turvey, 1987), but few have been

transferred to successful operational systems. None

are in service in state forestry agencies. The soil-site

factors used by Turner et al. (1990) in a topographical

framework are an example of the type of geocentric

information recorded:

1. parent rock (hard or unconsolidated, from which

the soil is formed),

2. soil profile texture (related to field morphological

description),

3. depth to impeding layer (e.g. rock, densipan or

indurate pan, waterlogging; to an arbitrary max-

imum soil depth),

4. texture of uppermost 10 cm of soil (either intact

A1 horizon or disturbed layer from field morpho-

logical description),

5. condition of the uppermost 10 cm of soil (pedality

and consistence of surface soil when wet or dry),

6. degree of weathering of surficial horizons (pre-

sence and characteristics of an A2 (or E) horizon,

seasonal drainage conditions of the B horizon),

7. nature of subsoil (those morphological character-

istics of the B horizon which affect soil water

permeability).

The systems mentioned above are largely descrip-

tive rather than dynamic, i.e. involving geoecological

processes that operate in the forest landscape. Moss

(1983), amongst others, has shown some of the meth-

odological issues that should be involved in dynamic

forestland assessment procedures. Nonetheless, expli-

cit quanti®cation of landscape attributes is still lack-

ing. Current computing technology and spatial

procedures now readily allow an enhanced quantita-

tive approach (Fig. 1).

3. Scale in forest soil-landscape investigation

From a reductionist perspective, soil and soil±land-

scape attributes can be identi®ed, described and inter-

preted from a regional landscape scale down through

the smallest soil pro®le, or pedon, to microscopic scale

of composition, with the presumption that the sum of

the reduced parts constitute the whole. This iso-

morphic view, zooming in and out to the scale of

interest, is inappropriate in this context because of the

prohibitive data requirements to make spatial state-

ments and since it ignores the discrete scales at which

certain landscape processes operate. Pedogenetic and

geomorphic (i.e. pedogeomorphic) investigations of

soil±landscapes show that pedogeomorphic relation-

ships are rarely linear across scales. Speci®c attributes

are uniquely in¯uenced at particular scales (Slater

et al., 1994).

Scale is often perceived in terms of cartographic

resolution. In this context the distinction between

`scale' and `resolution' can be blurred, especially

when `large' scale refers to detailed resolution. Turner

and Gardner (1985) propose de®nitions for scale-

related phenomena in landscape ecology whereby

the term `®ne scale' represents high resolution of

measurement and smaller dimension of the object

of study, and the term `broad scale' relates to the

coarser resolution of measurement and larger phenom-

ena. These are the terms and contexts that will be used

hereafter.

Arguing on the basis of hierarchy theory, Holling

(1992) presents a hierarchy of scaled structuring

processes. Each of these scales of processes can be

studied individually or in hierarchical form. If the

linkage of scales of study is hierarchical (non-linear)

then a boundary constraint must exist between the

scale of interest and the scales above and below it

(Holling, 1992). This conclusion leads to some indi-

cation of the signi®cance of the scale of study to the

phenomena being studied and to the resolution at

which they may be measured (Meentemeyer and

Box, 1987). Studies must be conducted and presented

at the appropriate process-sensitive scale. As broad-

ness of scale increases, the constraining variables

should become fewer, more apparent and dominant.

With increasing ®neness of scale more variables are

introduced and their relative domination changes.

Many soil classi®cation schemes have formalized

the broad-scale in¯uences (Slater et al., 1994). A

classical example in soil science is the `zonal' model

of pedogenesis popularized by Jenny (1941) whereby

at the global and continental scales, soil patterns

assume `zones' determined by the so-called active

factors of soil formation: climate and vegetation

(themselves highly covariant). The unwitting mistake

has been made subsequently in pedology and soil


survey to apply that broad-scale concept at ®ner

scales; it is only truly relevant at the broad scale, in

which it was conceived. The pedogenesis of so-called

azonal soils can be attributed to phenomena acting at

®ner scales. They are azonal because the zonal idea

does not apply at those scales. At the ®ner landscape

and topographic scales the zonality concept breaks

down but it is not replaced by another scale-appro-

priate concept.

A more acceptable approach would be to seek a

method that uses common indices that do not change

fundamentally across scales, or one that develops

`linking models' that integrate the component models

for each scale (Slater et al., 1994). This is the essence

of a multi-scale approach.

In a soils-based forest site analysis, it is important to

establish the relationships between signi®cant attri-

butes of the pedogeomorphic landscape and the forest

land use. Some attributes studied should maintain their

relevance at multiple scales, others will change

between component models depending on the scale

of investigation. The intensity (or density) of their

Fig. 1. A comparison of approaches to soil survey: the traditional method and the enhanced method that includes predictive digital modeling.


measurement will also change with the resolution

requirements being applied. Digital modeling and

digital terrain analysis provide a ¯exibility of resolu-

tion to match the scale of investigation to synthesize,

organize, and even generate the relevant pedogeo-

morphic attributes. The limitations to using traditional

approaches to soil and site surveys for forestlands

because of scale restriction and resolution of data may

be overcome with these technologies.

Dijkerman (1974) portrays soil as an open system

with many subsystems. He describes a hierarchy that

can be subdivided at increasing levels of organization

to suit the level of pedological investigation. This sort

of open system (from the soil continuum in the macro-

ecosystem to fabric micro-morphology and mineral-

ogy) is often portrayed as a `morphological' system,

hybridizing with a `process±response' system. In land

resource assessment (LRA) we need to capture the

process±response system as much as possible,

although much interpretation and expression

(through soils maps and tables) are in a morphological

model.

The process±response model environment in which

LRA operates is that of the `soil±landscape' Ð a

variously de®ned concept, reviewed by Hall (1983)

and best standardized to that of Huggett (1975) as a

`soil±landscape system'. Thwaites (1995, 2000b) sub-

sequently has taken this concept further by de®ning

the 3D `catenary unit' as the fundamental soil±land-

scape entity. The catenary unit is akin to Huggett's

`valley basin' but with full inclusion of surface and

subsurface pedogeomorphic processes which can be

synthesized through digital terrain modeling.

Hoosbeek and Bryant (1992) introduced three

dimensions to the pedological hierarchy by de®ning

perpendicular axes of `degree of computation' and

`degree of complexity' to our models along a vertical

axis of scale of hierarchy. The relative degree of

computation ranges from `qualitative' to `quantitative'

and the degree of model structure complexity ranges

from `empirical' (or `functional') to `mechanistic'.

These discrete levels of hierarchy are termed `i-

levels'. Bouma and Hoosbeek (1996) added the con-

text of the scale of research approach using i-levels

and took the base i-level to be that of the soil pro®le, or

pedon. This has been adapted for this study so that the

base i-level is the catenary unit to re¯ect the scale

variance being dealt with (Fig. 2a).

Fig. 2. (a) The hierarchies of scale expressed as i-planes. The base level (i) of investigation for this study is the Catenary level. (Adapted from

Bouma, 1996); (b) The chain of research followed in FRAMS with reference to the hierarchy of scale and the variation in the degree of

complexity and degree of computation. Knowledge levels are those presented by Bouma (1996): K1 Ð user expertise, K2 Ð expert

knowledge, K3 Ð generalised holistic models, K4 Ð complex holistic models, K5 Ð complex models for parts of the system studied.


We contend that within a holistic systems approach

these hierarchical levels should be investigated with

methods suitable to the individual level (the ì-level').

Our perspective of the process±response systems will

change depending on the i-level of investigation. From

a holistic ecosystems perspective, soil and soil±land-

scape attributes must be treated within homomorphic

models of appropriate scale. Soil±landscape systems

need to be investigated as systems, and target proper-

ties (e.g. soil attributes) should be dealt with in a

systems context.

4. Explicitness and prediction for forestlandresource assessment

It would be highly desirable for forestland resource

assessment to quantify soil and site attributes for any

location, rather than record interpreted site classes or

derived qualities. The laborious and intensive process

of measuring attributes satisfactorily for extrapolation

to other sites has often precluded the development of

this more desirable approach beyond the experimental

stage. However, through technological advances some

means of measurement are becoming more accessible,

particularly in spatial modeling.

Soil maps and site maps such as those based on

the `land systems' of ècoregions' approaches are

models. They are also hypotheses (Hudson, 1991)

but they are `descriptive', possibly èxplanatory' mod-

els (in Dijkerman's, 1974, terminology). They are not

dynamic, nor are they predictive. The mental models

used to create the soil or site maps are those that we

need to specify, to make explicit, and to bring them

into our assessment and classi®cation procedures

(Hewitt, 1993; Slater and Grundy, 1999; Thwaites,

2000a).

Predictive modeling has been a major area in soil

and land resources survey, but there is little in the

literature to mark this signi®cance. The lack of pre-

dictive models in the soil survey literature (e.g. Dent

and Young, 1981; Gunn et al., 1988; Landon, 1991;

USDA, 1993) and, indeed in its practice, suggest that

soil and site surveyors do not readily appreciate the

role of predictive models in the course of their work.

These predictive models should be the essence of soil

and site survey Ð enhancing the scienti®c aspects of

the discipline.

The predictive modeling process is the key to

expressing and communicating the interpretation of

soil and site in land resource survey. Hewitt (1993)

suggests that predictive models have two roles: First,

making statements about soil or site classes and their

spatial arrangement through `soil±landscapes', or

more usefully, statements about soil properties and

their trends related to landscape features. Second,

`target-property' models (we will use the term àttri-

bute' models) which are predictive models used to

make inferences about technical soil and site qualities

from soil and site observations in the ®eld.

Only recently has interest been shown in making the

extremely complex procedure of predicting soil±land-

scape properties from survey observations more expli-

cit (e.g. McKenzie and Austin, 1993). Explicit

modeling adds quantitative objectivity and repeatabi-

lity into forestland resource survey.

Soil±landscape models are a complex integration of

spatial pedogeomorphic information and processes.

Their use entails a distinct shift from some of the

concepts in conventional soil survey, as a result of the

increased explicitness, quantitativeness, and repeat-

ability, whilst replacing the transfer of interpretation

by analogy with gridded data prediction and by redu-

cing the inherent uncertainty in the traditional

approach (see Table 1). The scale of information

and the resolution of sampling forest sites is markedly

improved with spatial modeling and, with some prior

strati®ed sampling, the accuracy of the information

can be improved in a very short time (see Ryan et al.,

2000). Predictive spatial modeling can optimize the

use of restricted human, ®nancial and time resources.

5. Soil-landscape modeling for forestland resourceassessment

Soil survey is a paradigm-based science (Hudson,

1991) which allows for experimental validation. How-

ever, it usually does not allow for falsi®cation or

replication. Soil survey can be interpreted as the

science of describing and predicting soil attribute

patterns in the 3D landscape. In a strict sense the

output from soil survey, the `theory' of soil pattern, is

more areal than spatial, usually relying on soil pattern

expression by choropleth polygons. Conventional

choropleth soil maps are scale-dependent: they cannot


be used at any other scale. They represent a generality

at a particular level that is only meaningful at that level

(Thwaites, 2000a). To be truly useful and adaptable in

a spatial sense we need to predict earth material

attributes in the 3D landscape and express them in

a more explicit and versatile manner. There are two

main conceptual issues that need to be addressed: the

appropriate analysis and interpretation of earth mate-

rials (soil and regolith), and the appropriate expression

of the earth material attributes.

Most soil survey techniques are based on the con-

ventional pedological concepts that have been engen-

dered by Jenny's (1941) original postulation of the

soil-forming factors. Jenny's assertion that there are

àctive' and `passive' factors of soil formation has led

to implicit interpretations of soil pattern variation to be

dominated by climate (atmospheric) and vegetation

(botanic) relationships. Paton et al. (1995), amongst

others, have asserted that this is a misleading frame-

work and that soil parent materials and topographic

processes exert at least as much in¯uence on soil

formation as the so-called active factors throughout

a range of scales. In erosional, therefore geomorphi-

cally active, landscapes, the in¯uence of parent mate-

rial and topography geomorphic processes generated

by parent material characteristics and hillslope pro-

cesses dominate over the climatic and vegetational

in¯uences. Indeed these latter will be strongly mod-

i®ed by the geomorphological conditions at anything

but the coarse regional and continental scales (Auten,

1945; Carmean, 1975).

For exotic pine plantation forestry, Grey (1983)

found that geomorphic units proved to be of greater

value for site index and mean annual increment (MAI)

prediction than soil classi®cation. Rowe (1971: 3)

provides the reason why a geomorphic approach to

forestland resource surveys works: `̀ . . . geomorphol-

ogy Ð the form and substance of the earth's surface Ð

exerts the fundamental control over all other asso-

ciated phenomena. It is `genetic' in the sense that the

form and substance of the land `makes' the local

climate, . . . selects the appropriate fauna and ¯ora

that can survive there, and shapes the subsequent

development of the soil.'' (original author's emphasis).

Thus Thwaites (1988) makes the statement that at least

up to the `landscape' (or `catchment') scale, soil and

soil materials are `geomorphogenetic', a somewhat

bulky, but accurate, term.

The other aspect of conventional soil, or soil-based,

surveys is that the material described and interpreted is

often contained within or peripheral to the solum

(strictly, the A and B horizons of the soil pro®le).

The characterization and interpretation of the C hor-

izon (a variety of weathered and weathering materials

forming the rest of the regolith) and any underlying

rock is rarely entertained. This may be a legacy of the

dominant agricultural in¯uence in soil survey devel-

opment. Within a forestry and forestland management

Table 1

A comparison between the ideology of the traditional soil survey approach with that of a more explicit, multi-scale, and

pedogeomorphological approach as represented by the FRAMS. The latter is recommended as an improvement of the core land resource

assessment basis and does not represent replacement of it (adapted from Slater et al., 1994, and Thwaites, 1995)

Features Traditional soil survey Pedogeomorphological modeling

Soil±landscape entities Nodal concept (e.g. profiles, pedons, polypedons) Spatial systems (e.g. lateral soil layers,

3D catenary units)

Field observation Soil profile description Soil layer, regolith description; catenary unit definition

Boundary observation Implicitly inferred from surrogate entity distributions Inferred through `fuzzy' expression

Entity classification à priori' generic or regional taxonomic classification

of soils or land types

à posteriori' fuzzy classification of local

pedogeomorphic attributes

Map units Rigidly defined boundaries and units Continuous membership in multiple classes by cell

Attributes Implied as largely homogenous for classified

map units, change at boundaries

Continuous variation

Presentation dimensions Data generalized to 2D 3D model and data structure

Model type Deterministic, empirical Stochastic, more mechanistic

Final scale Standardized published map scales, smaller than

field survey scales

Variable appropriate to local complexity,

and model and user requirements


context the whole regolith (all non-hard rock materials

at the earth surface) is of importance, particularly if

one is investigating the status and dynamics of soil

water and drainage and trees' access to water. Stone

and Kalisz (1991) point out that the extensive root

systems through the regolith of many tree species play

a more important role in the uptake of water and

nutrients than indicated by just their density. They

also suggest that the commonly accepted limitations to

rooting depth (e.g. pans, stone layers, rock, `dry'

substrates) are not necessarily the barrier to root

penetration that they are assumed to be, especially

to sinker roots.

Standard soil survey and classi®cation alone do not

provide the strongest conceptual basis for forestland

classi®cation or multi-purpose forestland manage-

ment. Generic soil taxonomies are not designed for

forest management purposes. They are to help us

organize our information about natural soil bodies

but this restricts their applicability. Therefore, they

can provide only a basis for further, subjective, inter-

pretation, e.g. for `plantability' and erodibility classi-

®cation, as expressed by Foster and Costantini (1991).

Powers et al. (1998) state that for forest soil quality

assessment soil units should be based on stable soil

properties that have strong relationships to forest

productivity, e.g. available soil water capacity and

rooting depth. These stable properties can also be

viewed as soil geomorphic properties, albeit prone

to change by forest soil management. They conclude

that assessment of soil quality indices would have

limited value without an adequate and extensive soil

inventory as a basis. An effective basis is a pedogeo-

morphic approach to soil and site description and

classi®cation, explicitly expressed, which provides a

strong conceptual framework for overall site assess-

ment. At minimum, it provides a preliminary strati®-

cation procedure in cases of landscape complexity for

further, more detailed study.

Surface con®guration is the major physiographic

property that, usually, can be perceived and measured

either in the ®eld or from remote means (e.g. aerial

photography, topographic data). In addition, the model

being developed in this way has not only the potential

to derive salient landform attributes rapidly, but also

the essential perspective of three dimensions.

A DTM provides a 3D analytical component of

forest site assessment and classi®cation. It is an

essential quantitative, repeatable and predictive

model. For the proposed methodological model DTMs

must be used in a soil±landscape systems context with

consideration of process as well as form. Forestland

resource survey can incorporate soil±landscape mod-

eling, at least as an initial framework and stratifying

procedure, to great effect. It has the potential to play a

much greater role in overall forestland site assessment

(Thwaites, 1997). The difference between the model-

ing approach undertaken in the FRAMS project and a

conventional mapping approach is shown in Fig. 1. A

distinction between the two concerns the strategy of

incorporating the ®eld survey and sampling phase, as

well as the type of data that may be collected. Further

distinctions are in the means and method of classi®ca-

tion and presentation of information as output. This

affects the usefulness and ¯exibility of output infor-

mation at the scales at which it can be applied.

Therefore, the systems approach is used here in a

predictive process in a multi-scaled resource assess-

ment. It has an pedogeomorphic framework that

focuses on the explicit interpretation and modeling

of relevant attributes of the whole regolith (subsur-

face) and terrain (surface) system at appropriate

scales: a multi-scale regolith±terrain model.

6. Forestland resource assessment and modelingstudy (FRAMS)

The FRAMS addresses the issue of scale by using a

holistic, systems-oriented approach within the pedo-

geomorphic framework. In the FRAMS, we are

attempting to overcome some of the scale and proce-

dural problems by adopting a multi-scale and explicit

landscape modeling approach that can be implemen-

ted using GIS. Soil±landscape analysis has been

adapted in the study to emphasize `regolith±terrain'

analysis (i.e. emphasizing in¯uences of the complete

regolith within a geomorphological systems frame-

work and using DTMs) employed at nested scales. The

traditional implicit and intuitive methodology of soil

survey is enhanced by ®rst de®ning the conceptual

survey and assessment process, then de®ning the

landscape processes and, consequently developing

explicit relationships between regolith±terrain com-

ponents (e.g. regolith depth, or layer stoniness to slope

gradient and curvature for speci®c lithological types).


The scales of investigation in the FRAMS are the

hillslope (5 m contour interval data for digital terrain

modeling, presented at 1:1000 map scale), the local

`catenary unit' (20 m contour interval data at 1:10 000

map scale), and regional landscape (30 m contour

interval data at 1:50 000 map scale). The ®rst two

are being investigated at Benarkin State Forest in

southeast Queensland (Fig. 3b) in a mixture of hoop

pine (Araucaria cunninghamii Aiton ex D. Don)

plantation with native moist and dry sclerophyll forest

dominated by blackbutt (Eucalyptus pilularis Smith),

Gympie messmate (E. cloeziana F. Muell.) and tallow-

wood (E. microcorys F. Muell.) with some softwood

rainforest elements. The landscape scale investigation

is being carried out in the Atherton Tablelands of

tropical north Queensland (Fig. 3a) as part of site

evaluation for private land reforestation of native

rainforest and wet sclerophyll species (speci®cally

hoop pine, Gympie messmate and Queensland maple

(Flindersia brayleyana F. Muell.), see Thwaites,

2000b).

A central concept inherent within the delineation of

regolith±terrain units is that the attributes characteriz-

ing a regolith±terrain unit can be explained by com-

mon soil and geomorphological (pedogeomorphic)

processes that are not exclusively shared by adjacent

regolith±terrain units.

These different scales of study can use similar

concepts of regolith±terrain investigation but have

to be approached at the relevant resolution. There is

no linear relationship of data resolution and expres-

sion of regolith±terrain attributes between them. Each

is a scale-dependent system. The scale groupings refer

to a range of mapping scales that are appropriate to the

landscape systems being investigated. The area cov-

ered by a particular scale of investigation may vary

owing to the complexity of the landscape and the

complexity of the landscape processes. The `land-

scape' scale is a broad scale which covers differing

geological units and many drainage catchments with

different regolith±terrain systems. It can represent

one major drainage basin or a few smaller ones.

Geological and macro-topographical in¯uences

dominate. It can be likened to the level of `land

province' in the land systems concept (mapping

scale would be around 1:50 000, ranging between

1:25 000 and 1:100 000). The catenary scale refers

to the focus of investigation on hillslope processes

over subcatchments and is therefore more intensive.

Catenary units can be well-de®ned and topographic,

lithological±pedological in¯uences dominate (map-

ping scale would be around 1:10 000, ranging between

1:2000 and 1:25 000). The hillslope scale relates to

small areas (land units) that may be composed of more

than one hillslope or land element. Pedological and

local surface processes dominate (mapping scales

would be around 1:1000, ranging between 1:500

and 1:2000).

Fig. 3. (a) The upper Barron and upper Johnstone Rivers (UB/UJ)

key area in the Atherton Tablelands of north Queensland. (b) The

Benarkin key area in Benarkin State Forest, southeast Queensland.


6.1. The `landscape' (or `regional') scale

In the Atherton Tablelands of tropical north

Queensland the approach to predicting favorable for-

est sites for planting native species has been to

synthesize the regolith±terrain model with climate

and geology data as spatial `surfaces'. Subcatchments,

or groups of catenary units are the basic elements of

interpretation within the upper Barron/upper John-

stone rivers (UB/UJ) key area (Fig. 3a; Thwaites,

2000b). At this scale, and particularly in this region

with a strong, decreasing rainfall gradient east to west,

the climatic factors are convenient for an initial stra-

ti®cation that in¯uences species selection rather than

regolith±terrain patterns. The critical factor is the

amount of potential spring rainfall (`critical rainfall

period') for the rainforest species. The lithological

variations (or `lithotypes') are taken as the next stra-

tum followed by topographical (`slope position') var-

iation before describing some conceptual

understanding of tree performance (Fig. 4).

Potentially favorable forest sites are de®ned

through the use of this `crisp set' conceptual model

and the outcome of digital terrain analysis (slope

length, shape, aspect, insolation receipt, and partial-

contributing area to moisture ¯ow (a `topographic

wetness index' or TWI). This is achieved through

using a rules-based `fuzzy set' classi®cation (see

below). The digital terrain analysis is undertaken on

a 30 m cell resolution digital elevation model (DEM)

from 1:50 000 scale topographic map data. The con-

tour and stream data generated by the DEM were

checked for integrity against the original contour and

stream data to test the reliability of the model as a

Fig. 4. The approach to ultimately defining forestland sites by `fuzzy' classification means in the UB/UJ key area with a `crisp' set hierarchy

of determination (Thwaites, 2000b).


topographic simulation. The data for the conceptual

model vary in scale and resolution (e.g. geology

mapping at 1:100 000 scale, soil mapping at

1:50 000 scale, climate surface generation at 50 m

resolution cell size). The digital terrain analysis (at

30 m resolution) and ®eld analysis enhance the soils

(and regolith) map data through applying soil±geo-

morphic processes to the landscape at a higher resolu-

tion. A 50 m resolution output (nominally at 1:50 000

map scale) from this analysis is deemed legitimate for

the landscape scale although validation has yet to be

undertaken.

6.2. The `catenary' (or `topo') scale

At the `catenary' scale, where catenary units are the

basic elements of investigation within subcatchments,

the components of the regolith±terrain system are

Fig. 5. A set of possible pedotransfer functions illustrating alternative approaches to estimate soil moisture parameters such as hydraulic

conductivity, water retention and soil water deficit: from detailed (TF1±TF4±TF5) to crude (TF6) (adapted from Bouma, 1989).


different from those of the landscape scale. The

investigation is being carried out in the rugged tribu-

tary catchments of the upper Brisbane river in Benar-

kin State Forest in southeast Queensland (Fig. 3b).

Only microclimatic elements such as cold air drainage

and localized frosts have been considered for climatic

analysis here, the in¯uence of which can also be

predicted through use of a DEM. No soil mapping

has been done for this area, so regolith±terrain inves-

tigation is being undertaken as part of the modeling

process. Lithological variation at this scale assumes

importance, as do readily measurable regolith attri-

butes that relate to soil moisture dynamics (soil tex-

ture, structure Ð particularly macro-void pattern, A

horizon depth, bulk density, abundance of coarse

fragments). Other general attributes assume a level

of importance such as pH and presence of texture-

contrast (or `duplex') soil morphology. Certain attri-

butes, which are logistically dif®cult, costly or

impracticable to measure, can be estimated using

surrogate means known as pedotransfer functions

(Bouma and van Lanen, 1989). These predictive rela-

tionships are based on known or empirically-derived

soil relations, such as a function of soil structure,

texture and organic matter for bulk density, as well

as other regolith±terrain attributes which can substi-

tute for hydraulic conductivity and moisture retention

(Fig. 5). Both of these latter attributes are rarely

measured in the course of routine land resource sur-

veys. Ryan et al. (2000) discuss the problems inherent

in applying these pedotransfer functions at inappropri-

ate scales and levels of intensity. At this scale, topo-

graphy dominates soil±geomorphic dynamics, so

DEM derivatives are used speci®cally in the concep-

tual model of site de®nition and in deriving simple

pedotransfer functions for hydraulic conductivity and

soil water status with regolith morphology. The DEM

resolution for this area is 10 m, from 20 m contour

data. Output resolution is at the DEM resolution of

10 m, so site units or `toposites' at this resolution can

be expressed at 1:10 000 mapping scale which corre-

sponds to the standard map scale used by the state

forestry agency.

6.3. The `hillslope' (or `local') scale

The hillslope scale study of Hill 60 is nested within

the catenary scale study area at Benarkin State Forest.

Hill 60 has been topographically surveyed to 5 m

contour resolution from which a 5 m DEM has been

erected. Fine scale topographic derivatives have been

used in conjunction with ®eld data to produce topo-

sites for hoop pine management. In this instance, the

®eld data include bulk density and soil moisture

measurements to aid the digital terrain analysis. These

were not deemed routine measurements for the Caten-

ary scale investigations but are of signi®cance at this

Hillslope scale.

Output resolution is at 5 m cell size which is con-

servatively believed to be suitable for 1:5000 scale

mapping of the predicted toposite classi®cation.

7. Conclusion

FRAMS provides a basis for regolith±terrain map-

ping of forestlands by employing digital terrain ana-

lysis and conceptual soil±geomorphic process

modeling at appropriate scales. The intention is to

predict the variation in pedogeomorphic attributes and

patterns that are relevant to the planning and manage-

ment of plantation forests. In these studies, those

attributes relating to soil water are emphasized. This

digital spatial analysis lends itself to the classi®cation

and presentation of the forest toposite data through

fuzzy rule-set techniques.1 Fuzzy rule classi®cation

re¯ects the reality of regolith±terrain variation more as

a continuum with the expression of class central

concepts and intergrades rather than as crisply de®ned

classes or polygon map units. It also clearly re¯ects

the knowledge system from which the rules were

derived. Instead of classifying natural soil or land

bodies to an a priori scheme, each grid cell is de®ned

by the proportional membership of assigned subsets of

regolith±terrain attributes according to knowledge-

based rules. Thus, it is a classi®cation of selected

attributes rather than a classi®cation of natural soil

bodies. Ryan et al. (2000) use heuristic Bayesian

probability in a similar way for the same purposes.

Therefore, this resource assessment procedure for

forestland not only accommodates the sensitivities

of scale but also attempts to represent the continua

1 See the special issue of Geoderma, Vol. 77, 1997, for

discussions on using of fuzzy logic in soil studies.


of complex pedogeomorphological variations more

closely. We believe that the procedure outlined here

goes further towards the ultimate goal of a dynamic,

process-based, and multi-scale land resource assess-

ment approach.

Acknowledgements

Funding and infrastructural support for this work

has come through the Cooperative Research Centre for

Tropical Rainforest Ecology and Management and the

Enhanced Resource Assessment project of the Depart-

ment of Natural Resources, Queensland. We thank Dr.

David Hammer for valuable comments on an earlier

draft of this paper and Dr. Brendan Mackey for his

helpful insights.

References

Allen, T.F.H., Hoekstra, T.W., 1992. Toward a Unified Ecology.

Columbia University Press, New York, 384 pp.

Auten, J.T., 1945. Prediction of site index for yellow-poplar from

soil and topography. J. Forestry 43, 662±668.

Bouma, J., 1989. Using soil survey for quantitative land evaluation.

Adv. Soil Sci. 9, 177±213.

Bouma, J., 1996. Role of quantitative approaches in soil science

when interacting with stakeholders. In: Soil Science Ð Raising

the Profile. Proceedings of the Australian and New Zealand

National Soils Conference, Vol. 1. University of Melbourne,

ASSSI, Canberra, July 1±4, 1996, pp. 67±72.

Bouma, J., Hoosbeek, M.R., 1996. The contribution and impor-

tance of soil scientists in interdisciplinary studies dealing with

land. In: Wagenet, R.J., Bouma, J. (Eds.), The Role of Soil

Science in Interdisciplinary Research, Soil Science Society of

American Special Publication No. 45, pp. 1±15.

Bouma, J., van Lanen, H.A.J., 1989. Transfer functions and

threshold values: from soil characteristics to land qualities. In:

Beek, K.J., Burrough, P.A., McCormack, D.E. (Eds.), Quanti-

fied Land Evaluation Procedures. Proceedings of the Interna-

tional Workshop, Washington, DC, pp. 106±111.

Bourne, R., 1931. Regional survey and its relation to stock-taking

of the agricultural and forestry resources of the British Empire.

Oxford For. Mem. 13, 16±17.

Carmean, W.H., 1975. Forest site quality evaluation in the United

States. Adv. Agron. 27, 209±258.

Christian, C.S., Stewart, G.A., 1953. General Report on Survey of

the Katherine±Darwin Region, 1946. CSIRO Australian Land

Research Series No. 1, 156 pp.

Dent, D., Young, A., 1981. Soil Survey and Land Evaluation.

Chapman & Hall, London, 278 pp.

Dijkerman, J.C., 1974. Pedology as a science: the role of data,

models and theories in the study of natural soil systems.

Geoderma 11, 73±93.

Foster, P.G., Costantini, A., 1991. Pinus plantation establishment in

Queensland. I. Field surveys for site preparation planning and

site design. Aust. For. 54 (1±2), 75±82.

Gessler, P.E., Moore, I.D., McKenzie, N.J., Ryan, P.J., 1995. Soil±

landscape modelling and spatial prediction of soil attributes.

Int. J. Geogr. Inform. Sys. 4, 421±432.

Grey, D.C., 1980. On the concept of site in forestry. South Afr. For.

J. 113, 81±83.

Grey, D.C., 1983. The geomorphic approach to site delineation in

exotic plantations. South Afr. For. J. 127, 26±30.

Grey, D.C., 1984. Classification of forestry land. South Afr. For. J.

132, 54±57.

Gunn, R.H., Beattie, J.A., Reid, R.E., van de Graaff, R.H.M., 1988.

Australian Soil and Land Survey Handbook: Guidelines for

Conducting Surveys. Inkata Press, Melbourne, 300 pp.

Hall, G.F., 1983. Pedology and geomorphology. In: Wilding, L.P.,

Smeck, N.E., Hall, G.F. (Eds.), Pedogenesis and Soil

Taxonomy I. Concepts and Interactions. Elsevier, Amsterdam,

pp. 117±140.

Hewitt, A.E., 1993. Predictive modelling in soil survey. Soils Fert.

56, 305±314.

Hills, G.A., 1953. The use of site in forest management. For.

Chron. 29, 128±136.

Holling, C.S., 1992. Cross-scale morphology, geometry, and

dynamics of ecosystems. Ecol. Monogr. 62 (4), 447±502.

Hoosbeek, M.R., Bryant, R.B., 1992. Towards the quantitative

modelling of pedogenesis Ð review. Geoderma 55, 183±210.

Hudson, B.D., 1991. The soil survey as a paradigm based science.

Soil Sci. Soc. Am. J. 56, 836±841.

Huggett, R.J., 1975. Soil landscape systems: a model of soil

genesis. Geoderma 13, 1±22.

Jenny, H., 1941. Factors of soil formation. A System of

Quantitative Pedology. McGraw-Hill, New York, 281 pp.

Landon, J.R. (Ed.), 1991. Booker Tropical Soil Manual. Booker-

Tate/Longman, London, 474 pp.

McKenzie, N.J., Austin, M.P., 1993. A quantitative Australian

approach to medium and small scale surveys based on soil

stratigraphy and environmental correlation. Geoderma 57, 329±

355.

Meentemeyer, V., Box, E.O., 1987. Scale effects in landscape

studies. In: Turner, M.G. (Ed.), Landscape Heterogeneity and

Disturbance. Springer, New York, pp. 15±34.

Moss, M.R., 1983. Landscape synthesis, landscape processes, and

land classification, some theoretical and methodological issues.

GeoJournal 7 (2), 145±193.

Paton, T.R., Humphreys, G.S., Mitchell, P.B., 1995. Soils. A New

Global View. UCL Press, London, 213 pp.

Powers, R.F., Tiarks, A.E., Boyle, J.R., 1998. Assessing soil

quality: practicable standards for sustainable forest productivity

in the United States. In: Adams, M., Ramakrishna, K., Davidson,

E.A. (Eds.), The Contribution of Soil Science to the Development

and Implementation of Criteria and Indicators of Sustainable

Forest Management. SSSA Special Publication No. 53, Soil

Science Society of America, Madison, WI, pp. 53±80.

Rowe, J.S., 1971. Why classify forest land? For. Chron. 47 (3), 1±5.


Ryan, P.J., McKenzie, N.J., O'Connell, D.M., Loughhead, A.N.,

Leppert, P.M., Jacquier, D., Ashton, L., 2000. Integrating forest

soils information across scales: spatial prediction of soil properties

under Australian forests. For. Ecol. Manage. 138, 139±157.

Slater, B.K., Grundy, M.J., 1999. Enhanced resource assessment:

integration of innovative technologies by agency soil scientists

in Australia. Paper presented at the Second Approximation

International Conference on Soil Resources, their Inventory,

Analysis and Interpretation in the 21st Century, June 10±12,

1999, Minneapolis, MN, USA.

Slater, B.K., McSweeney, K., Ventura, S.J., Irvin, B.J., McBratney,

A.B., 1994. A spatial framework for integrating soil±landscape

and pedogenic models. In: Bryant, R.B., Arnold, R.W. (Eds.),

Quantitative Modeling of Soil Forming Processes. SSSA

Special Publication No. 39. Soil Science Society of America,

Madison, WI, pp. 169±185.

Smalley, G.W., 1984. Landforms: a practical basis for classifying

forest sites in the Interick Uplands. In: Proceedings of the 12th

Annual Hardwood Symposium. Hardwood Research Council,

Auburn, AL, pp. 92±112.

Steinbrenner, E.C., 1965. The influence of individual soil and

physiographic factors on the site index of Douglas-fir in

western Washington. In: Youngberg, C.T. (Ed.), Forest±Soil

Relationships in North America. Proceedings of the Second

North American Forest Soils conference. Oregon State

University Press, Corvallis.

Sukachev, V.N., Dylis, H., 1968. Fundamentals of Forest

Biogeocoenology. Oliver and Boyd, London, 73 pp. (J.M.

MacLennan, Trans.; Osnovy Lesnoi Biogeotsendogii).

Thwaites, R.N., 1988. An introduction to digital terrain modelling

in forest site analysis Ð an example from the Grabouw±

Lebanon key area. South Afr. For. J. 144, 63±68.

Thwaites, R.N., 1995. Soil landscape modelling for forestry land

resource assessment: technologies and concepts. In: Bren, L.,

Greenwood, C. (Eds.), Applications of New Technologies in

Forestry. Institute of Foresters of Australia, Canberra, pp. 57±4.

Thwaites, R.N., 1997. Revisiting forest site assessment. Changing

requirements necessitate a policy for new approaches. In:

Preparing for the 21st Century. Proceedings of the Fourth

ANZIF Conference. Institute of Foresters of Australia,

Canberra, April 21±24, 1997, pp. 211±217.

Thwaites, R.N., 2000a. From biodiversity to geodiversity and soil

diversity. A spatial understanding of soil in ecological studies

of the forest landscape. J. Trop. For. Sci., in press.

Thwaites, R.N., 2000b. Matching native tree species to sites for

plantations using spatial, predictive terrain analysis. New

Forests, in press.

Thwaites, R.N., Payn, T.W., 1997. Soil information for sustainable

plantations in Australia and New Zealand: a policy necessity.

In: Preparing for the 21st Century. Proceedings of the Fourth

ANZIF Conference. Institute of Foresters of Australia,

Canberra, April 21±24, 1997, pp. 205±210.

Turner, J., Holmes, G.I., 1991. Site classification of Pinus radiata

plantations in the Lithgow district, New South Wales, Australia.

For. Ecol. Mgmt. 12, 253±263.

Turner, J., Thompson, C.H., Turvey, N.D., Hopmans, P., Ryan, P.J.,

1990. A soil technical classification system for Pinus radiata

plantations. I. Development. Aust. J. Soil Res. 28, 797±811.

Turner, M.G., Gardner, R.H., 1985. Quantitative methods in

landscape ecology: an introduction. In: Turner, M.G. (Ed.),

Landscape Heterogeneity and Disturbance. Springer, New

York, pp. 4±14.

Turvey, N.D., 1984. Benefits and costs of soil surveys. In: Grey,

D.C., Schoenau, A.P.G., Schutz, C.J. (Eds.), Proceedings of the

Symposium on Site and Productivity of Fast Growing

Plantations, Vol. 1, Pretoria and Pietermaritzburg, South Africa,

April 30±May 11. SAFRI/IUFRO, Pretoria, pp. 139±146.

Turvey, N.D., 1987. A technical classification for soils of Pinus

plantations: field manual. Bulletin No. 6, School of Forestry,

University of Melbourne, 41 pp.

USDA, 1993. Soil Survey Manual. Agriculture Handbook 18. US

Department of Agriculture, Washington, DC, 437 pp.

Van Groenewoud, H., Ruitenberg, A.A., 1982. A productivity-

oriented forest site classification system for New Brunswick.

Information Report MX 136. Maritimes Forest Research

Centre, Canadian Forestry Service, Fredericton, 9 pp.

Wendt, G.E., Thompson, R.A., Larson, K.W., 1975. Land Systems

Inventory, Boise National Forest. USDA Forest Service,

Intermountain Region, ID, 54 pp.

Wertz, W.A., Arnold, J.F., 1972. Land Systems Inventory. USDA

Forest Service, Intermountain Region, Ogden, UT, 12 pp.


Soil–landscape resource assessment for plantations — a conceptual framework towards an explicit...

Documents

Transcript of Soil–landscape resource assessment for plantations — a conceptual framework towards an explicit...