AN ECONOMIC ANALYSIS OF DEGRADATION IN THE QUEENSLAND MULGA RANGELANDS pot

Ihe @nmic programming model describes a Markov decision process, with stocking rate as the sole land use decision and pasture biomass as the indicator of rangeland condition.. By individ

A thesis submitted for the degree of Master of Agricultural Economics in the

University of Queensland

Department of Agriculture

August, 1991

iii

Abstract

The economic issues involved in arid rangeland degradation have become an increasing focus

in agricultural economics research world-wide The economic and social factors which contribute to degradm'on in Queensland's arid mulga rangelandr are explored in this thesis

Many of the region's problems, including the small property size structure, g r d n g management practices and land tenure have their origins in the historical development of the region These and other factors are idenn3ed using both a regression analysis of cross- sectional d m and a stochastic dynamic programming model of the rangeland

Regressions pelformed on data j?om parallel economic and land condition surveys of

46 graziers in the south-west Queensland mulga rangelandr are used to establish a link between degradation and land utilisation policy Land degradation is shown to be more severe on propem'es with higher stocking rates The importance of property size, financial and domestic cost pressures, land condition and proportion of residual land types in land use decisions are explored D e analysis supports the hypotheses that smaller property sizes and higher interest cost commitments are associated with higher stocking rates As expected, propem'es with a greater proportion ofpoorer quality land types tend to adopt lower stocking rates Kangaroo numbers, an effective regional proxy variable, is positively related to stocking rates indicating the tendency for native grazer populations to be higher on more

productive land types The regression analysis also provides some evidence that incomes are

higher on properties with a greater degree of land degradation

While the cross-sectional regression approach is e m t i v e in idennning some of the economic issues, it has distinct shortcomings Regional biases are diflcult to isolate from the relationships between stocking rates and the various economic factors and much of the variation in stocking rate may in fact be due to regional dzrerences Moreover, the technique does not adequately consider the intertemporal nature of the rangeland resource problem

iv

A stochastic dynamic programming model, amalgamating the cross-sectional swwy data with historical field trial data is developed to address these shortcomings Ihe @nmic programming model describes a Markov decision process, with stocking rate as the sole land use decision and pasture biomass as the indicator of rangeland condition For a given pasture biomass and stocking rate, the transition to a'following stare is described by a probability dism'bution derived porn simulated climaric data By individually varying economic parameters in the model, including property size, wool prices, discount rates and risk, the response in optimal stocking rates and returns can be assessed The dynamic programming model also generates optimal net present values and shadow prices associated with the marginal usage of pasture biomass corresponding to each optimal decision set Pasture condition is imputed from the long-term probability distribution of pasture stares generated by the model

_ The dynamic programming model reveals that the small property size structure in the mulga rangelands, largely a legacy of early land a.inistra.tion policy, is a majorpotential factor in land degradation Graziers with small holdingsjind it economically optimal to stock at higher rates in an e f o n to achieve economies offlock size The costs of degradatr'on incurred by higher stocking strategies are balanced by savings porn more encient management l2e model shows that at the average wool prices assumed, an area of at least 35,000 hectares is required to produce positive net present values at all levels of pasture biomass

I

The effect of wool prices on optimal land use rates reflects the non-linear relationship between wool quality and price, which makes finer wools relatively more attractive during periods of high prices Graziers can gain by opportunistically stocking at higher rates to induce finer wool The so-called lfine wool effect' can be achieved by felling mulga for supplementary feed

The individual grazier's discount rate is expected to vary according to financial circumstances, planning horizon and arn'n.de to risk Sensitivity analysis of the model revealed that optimal stocking rates increased as the grazier's discount rate rose, reflecting

a decreasing concern for resource conservation The amtude of graziers to risk is firther

This thesis reports the original work of the author, except as otherwise stated It has not been submitted previously for a degree at any

university

analysed in a utility-maximising version of the dynamic programming model Quadratic, negative exponential and spliced utility Bnctions are used to convert monetary outcomes to un'lity values Generally, a more risk-averse attitude infers more conservative stocking rates

Apart from examining the importance of propeny size, wool prices and discount rate

in land degradation, the study seeks to validate the use of dynamic programming analysis in policy issues where intertemporal elements are of central importance The problems of dimensionality, data requirements and compurational limits which hamper the efectiveness

of dynamic programming as a decision-making tool are less resmktive of its usefllness in examining policy concern The dynamic programming method has firther potential uses in identBing minimum property sizes for long-tern viability and in the analysis of the response

of land prices to degradation

vii

CONTENTS

ABSTRACT

LIST OF TABLES

- AN INTRODUCTION

1.1 Defining degradation

1.2 Degradation of the mulga rangelands

1.2.1 The degradation cycle

1.2.2 Extent of mulga rangeland degradation

1.3 Theory and analytical issues: A synopsis

A historical perspective Early grazing management

a;,

Closer settlement policy and property size

A market failure approach to land degradation Imperfect market for information and research Divergence between private and social discount rate

Intergenerational equity issues and market failure Financial pressures

Ownership intentions and planning horizon Uncertainty about irreversibility

Property rights and land tenure Land tenure in the mulga rangelands Land market imperfections

Externalities Government policy failure Characteristics of region and production system Drought management and mulga top-feeding Native and feral grazing animals

The effect of stocking rate on wool quality

Summary

LAND DEGRADATION IN THE MULGA RANGELANDS 3 1

3.2 Survey data

3.2.1 Survey methods

3.2.2 Economic data

viii Land condition data

Techniques of analysis

The relationship between stocking rates and degradation

A land degradation variable Analysis

Economic factors influencing stocking rates Identification of economic variables '

Analysis

A two-stage least squares approach Property incomes and stocking rates Analysis of land prices and degradation

Land price analysis for the mulga region Intra-regional comparison

Inter-regional comparison

The mulga rangeland resource and its characteristics

A model of renewable resource use

Maximum sustainable yield

A simple graphical intertemporal model Dynamic optimisation methods

Optimal control theory

Dynamic programming Application of dynamic optimisation methods Review of dynamic optimisation literature

MODEL FOR THE MULGA RANGELANDS

The model framework Determination of state variables Indicators of rangeland productivity Pasture biomass

Basal area

Selected state variables and partitions Determination of decision variables Selected decision variable

The transition matrix Methods for deriving the transition matrix Pasture biomass transition matrix

The stage return function Property sizes

Wool cut per head Wool quality Wool price Stock replacement and values

5.5.5.1 Mortalities

5.5.5.2 Normal replacements

5.5.5.3 Stock adjustment between seasons

5.5.6 Variable production costs

5.5.7 Variable marketing costs

5.5.8 Fixed costs

5.5.9 Discount rates

5.6 An alternative specification - A constrained choice model

INFLUENCES ON OPTIMAL STOCKING RATES

Effects of property size Optimal stocking rates Optimal net present value function Shadow prices

Long-run probabilities of pasture states

Effects of changing model parameters

Wool price variations Wool quality differentials Discount rates

A utility maximising model

Constrained choice model Optimal net present values and shadow prices Sensitivity to property size and discount rate Summary

Wool Price Series Matrix of Stage Return Components Sheep Mortality Rates

Wool Price Sensitivity Analysis The GPDP Computer Package APPENDIX REFERENCES

LIST OF TABLES

Table 3.1 Summary of Economic Data from a Survey of Mulga

Rangeland Graziers, Average per Property

Table 3.2 Summary of Land Condition Data from a Survey of

Mulga Rangeland Graziers, (per cent of total random points)

Table 3.3 OLS Regressions of Land Degradation Variables on Stocking Rate

Table 3.4 Regressions of Economic and Physical Variables on Stocking Rate

Table 3.5 OLS Regressions of Economic and Physical Variables on

Stocking Rates, excluding Residual Land Types

Table 3.6 Land Degradation and Stocking Rate - A Two-Stage

Least Squares Approach

Table 3.7 Significance of Property Size and Land Condition in

Explaining Property Incomes

Table 5.1 Average Pasture Biomass for Land Classes, 1982 Land

Condition Survey

Table 5.2 Pasture Biomass Partitions and Midpoints

Table 5.3 Stocking Rate Decisions and Partitions

Table 5.4 Pasture Biomass Regressions for Deriving the Transition Matrix,

Table 5.5 Economic Characteristics of Property Size Groups

Table 5.6 Wool Cut Per Head for Different Rates of

Pasture Utilisation (Arabella Trial)

Table 5.7 Average Wool Prices for Fibre Diameter, 1973174 to 1989190,

in 1987188 Dollars

Table 5.8 Costs of Mulga Feeding

Table 5.9 Average Saleyard Prices for Young and Aged Wethers

at Dalby (1987188 Dollars)

Table 5.10 Penalty Costs for Stock Adjustment over Time

xi

Table 5.11 Labour and Materials Costs per DSE, 1987188 Dollars

Table 5.12 Variable Production Costs used in Estimating Stage Returns

Table 5.13 Wool Marketing Charges

Table 5.14 Fixed Costs

Table 6.1 Effect of Property Size on Optimal Stocking Rates

Table 6.2 Effect of Property Size on Optimal Net Present

Values at Full Equity

Table 6.3 Effect of Property Size on Optimal Net Present

Values with Average Interest Costs Included

Table 6.4 Effect of Wool Prices on Optimal Stocking Rates

Table 6.5 Effect of Wool Prices on Net Present Values per Hectare

Table 6.6 Effect of Wool Quality Differentials on Optimal

Stocking Rates

Table 6.7 Effect of Discount Rates on Optimal Stocking Rates

Table 6.8 Optimal Stocking Rates using Quadratic &d Negative

Exponential Utility Functions

Table 6.9 Optimal Stocking Rates for a Risk-Averse Grazier at

Four Equity Levels, Spliced Utility Function

Table 6.10 Effect of Property Size on Optimal Stocking Rate ~djukrnents

Table 6.11 Effect of Discount Rate on Optimal Stocking Rate Adjustments

x i i

LIST OF FI

Figure 1.1 Location of the Mulga Rangelands in South-West Queensland 4

Figure 1.2 The Land Degradation Cycle

1.3 Number of Paroo River Flood Heights over Three Metres,

10-year Moving Average, 1926-35 to 1980-89

Annual Average Rainfall, CharleviUe, 10-year Moving Average,

1926-35 to 1980-89

Figure 2.1 Distribution of Property Sizes in the Mulga rangelands

Figure 3.1 Economic and Physical Factors in the Land Degradation Cycle

Figure 3.2 Actual Land Prices in the Eastern and Western Mulga

Rangelands Compared to the Prices Paid Index, 1961-89

Figure 3.3 Actual Land Prices in the Western Mulga Rangelands and

the Blackall District Compared to the Prices Paid Index, 1968-88

Figure 4.1 The Resource Growth - Stock Relationship and Maximum

Sustainable Yield

re 4.2 The Intertemporal Optimum for Renewable Resources

- A Simple Graphical Two-Period Model

Figure 5.2 Annual Wool Prices in Constant 1988 Dollars, by ~ i b r e Diameter 95

Figure 6.2 Equilibrium Probability Distribution of Pasture States

Figure 6.3 Effect of Wool Prices on Shadow Prices

Figure 6.4 Effect of Wool Prices on Equilibrium Probability

Distribution of Pasture Biomass States

Figure 6.5 Effect of Wool Quality Differentials on Shadow

Prices for Pasture Biomass States

Figure 6.6 Effect of Wool Quality Differentials on Equilibrium

Probability Distribution of Pasture Biomass States

X l l l

Figure 6.7 Effect of Discount Rate on Shadow Prices for Pasture

Biomass States

Figure 6.8 Effect of Discount Rate on Equilibrium Probability Distribution

Figure 6.9 Net Present Values for Pasture and Stocking Rate Combinations,

Figure 6.10 Shadow Prices for Combinations of Pasture State

and Stocking Rate, Constrained Choice Model

173

GPDP Output

RUN LOG: DATE 03-17-1991 TIME 15:35:30

PROBLEM NAME > EXP

STOCHASTIC DYNAMIC PROGRAMMING SOLUTION

PROBLEM -EXP - PROBLEM PARAMETERS:

INFINITE NO OF STAGES

RATE OF DISCOUNT (PER CENT) = 5.0000

FOR FEASIBLE INPUT READ, SOME FOLLOW-ON STATES WITH LOW PROBABILITIES WERK IGNORED FOR STAGE 0

REQUIRE LONG-RUN STATE PROBABILITIES - Y(YES) OR N(N0) ) Y

NO DRYMAT

Chapter 1

Degradation of agricultural lands has become a major environmental concern in recent years Globally, mankind has degraded more than 430 million hectares of crop and grazing land (Burch et al., 1987) In Australia's Pastoral Zone, degradation of arid rangelands which support about 25 per cent of the nation's livestock is a major problem (Burch et al., 1987) contend that around 13 per cent of the 432 million hectares under pastoral occupation has become severely degraded In Queensland, a 1975 study found that 53 per cent of the 83 million hectares of arid-zone grazing lands showed some evidence of soil erosion and vegetation degradation, with 10 per cent being severely degraded (Queensland Department

of Environment and Heritage, 1990) This situation was believed to have worsened since that time

Despite awareness among land-users and scientists' understanding of grazing land degradation, the problem has persisted A plethora of historical, economic, environmental and institutional factors have been identified as constraints to land conservation efforts, including land administration and tenure, property size, debt pressures and market information problems These problems have led to a rate of land degradation greater than that which would have naturally occurred before European settlement Policy makers' usual solution has been to treat the symptoms rather than the causes (Quiggin, 1987) Taxation assistance for conservation works is one such example of rnis-directed ameliorative policy measures (Quiggin, 1987)

The economics of rangeland degradation have attracted little attention in the literature This may be due to the low productivity and low value nature of the arid rangelands As costs of regeneration and soil replacement are extremely high relative to land value, degradation of arid lands is generally irreversible Treatment of the cause rather than the symptom is therefore crucial Economic analysis has a major role in determining the causes and the appropriate policies to prevent or slow the process of degradation

The broad objectives of this thesis are:

- to identify the economic and financial constraints in decisions on' land use in

Queensland's mulga rangelands;

- to examine the impact of changes in3economic conditions on optimal land

utilisation rates over time; and

- to explore the potential of dynamic methods in the analysis of policy issues

1.1 Defining demdation

Degradation has been defined as damage to land, water or vegetation resources which impedes long-term grazing productivity and ability to support native animals (Burch et al., 1987; Foran et d., 1990) The damage occurs over a shorter time scale than normal geological processes and is the mult of human intervention (Mills, 1986a) In arid rangelands, degradation describes an irreversible loss of the resource, as distinct from the temporary effects of extreme seasonal variations which charactedsc the system

In economic terms, degradation implies a redistribution of resource use rates from the future to the present with adverse consequences The non-Ricardian or destructible component of the rangeland resource comprises three elements: the conservable flow which must be kept to ensure future productivity, a revolving fund which can economically be replaced by fertilisers, reseeding or other investment, and the initial expendable surplus which can be completely used (Gaffhey, 1965; Van Kooten and Furtan, 1987) Degradation describes the irreversible deterioration over time of the valuable conservable flow resources, such as topsoil in rangelands This may occur due to a failure of usen to distinguish between the conservable flow and revolving fund elements

The evidence of rangeland degradation is a change in species dominance from palatable perennial grasses to woody shrubs, Scalding of soil surfaces by wind and water erosion, and occasional gully erosion Degradation is believed to be a result of heavy

grazing and failure to destock during drought, although competition from native grazing animals and the reduced frequency of natural fire may also play a part

3

Visually, degradation in arid regions removes the uniformity of landscape Native pastures become interspersed increasingly with scalded areas, woody weed infestation and gullying The visible evidence of economic or management influence is the 'fence-line effect' along property boundaries

The mulga rangelands comprise some 19 million hectares in the south-west corner of Queensland (Figure 1.1) The rangelands support a significant pastoral industry accounting for about one quarter of annual wool production in Queensland and one twelfth of the beef herd (Mills, 1989) The main shires with mulga rangeland are Bull00 (30 per cent of shire), Booringa (30 per cent), Murweh (75 per cent), Paroo (65 per cent), Quilpie (75 per cent) and Barcoo (40 per cent) (Reynolds, 1988)

Climatically, the mulga rangelands experience low unreliable rainfall, high evaporation rates and winter frosts Much of the rainfall occurs as isolated heavy falls of little assistance to plant growth Between 1880 and 1989, Charleville's rainfall averaged 486

rnillimetres Rainfall was below this average in 62 of those years, while the lowest recorded annual rainfall was just 175 rnillimetres (Mills, 1989) Seventy per cent of falls occur in the October to March period (Christie and Hughes, 1983) Drought is a dominant feature of the

I

climatic pattern, with some shires being drought-declared for almost half of the past 25 years

(Mills et al., 1989; Mills, 1989)

The mulga rangelands comprise two broad land zones, the soft mulga and the hard mulga, distinguished by rainfall, soil and vegetation characteristics Generally, the hard mulga lies to the west of Charleville and the Warrego River, stretching west of Quilpie, while the soft mulga lies to the east The soft mulga zone consists of flat or gently

undulating plains of red loamy soil supporting tall mulga (Acacia aneura) and valuable perennial grasses The hard mulga zone has a lower average rainfall, a more fragile ecosystem, and is more prone to soil erosion due to shallow soils and low fertility

Figure 1.1 Location of the Mulga Rangelads in South-West Queensland Source: Mills, 1989

shrub cover usually on deep cracking clay soils In the more arid western regions, dunefields and claypans occur with greater frequency

A variety of perennial and ephemeral grasses form the basis of an extensive grazing industry Grazing properties vary in size from under 10,000 hectares to over 200,000 hectares, and typically cany 4,000 to 12,000 sheep and 100 to 300 head of cattle The major source of income is wool, and most properties carry a mixture of merino wethers and breeding ewes The poor breeding capability of the mulga rangelands is reflected in low lambing percentages of 40 to 70 per cent (Sullivan et al., 1986) Stock losses average around 7 per cent per annum (Australian Bureau of Statistics, various issues) Cattle provide

a supplementary income on most properties, and if stocked in smaU numbers, are believed

to have little eifect on overall grazing pressure while absorbing seasonal labour surpluses (Mills, 1989; Sullivan et al., 1986)

Stocking rates range from 0.2 to 0.5 dry sheep equivalents per hectare @SE/ha) A

Lands Department survey in 1983 identified an average carrying capat& on 11 Paroo region properties of 0.28 sheep per hectare (Mills, 1989) Holmes (1986) observed an average stocking rate of 0.47 DSEIha on seven eastern mulga properties over the seven years to

1980 A later economic survey by Passmore (1990) found an average stocking rate of 0.42 DSEIha in the eastern mulga and 0.34 DSE/ha in the western region

1.2.1 The degradation cvcle

Degradation in the mulga rangelands is characterised by a change in species dominance from perennial grasses to woody weeds and by sheet and gully erosion Sheet erosion is of most concern, as the loss of the vital few centimetres of top soil may mean the irreversible loss

of nutrients critical to pasture growth (Miles and Baker, 1988) Bare land areas form a

transitional phase in the degradation process, and if not revegetated or spelled from grazing,

are susceptible to sheet erosion (Miles, 1990)

The complex cycle of degradation in the mulga rangeland is influenced by drought,

the extent of mulga feeding, stock management, native grazefi and fire Figure 1.2

compares the degradation cycle with the natural cycle observed under moderate grazing

conditions

Figure 13 The Land Degradation Cycle

Source: Mills, 1989

The cycle commences with sheet erosion and loss of ground cover caused by drought

or heavy grazing Under continued heavy grazing, soil loss is increased and infdtration

lowered The most palatable grasses are selectively grazed resulting in a loss of ground cover

and a domination by less desirable species In the natural state, woody weeds do not

compete well with native grasses and are controlled by the natural incidence of fire With - f

reduced grass cover, the rangelands are unable to carry a fire The wider distribution of

native grazing animals and feral animals such as pigs and rabbits abets the progress of woody

weed domination The degradation cycle is also reinforced by the availability of mulga as

a drought reserve feed thereby enabling stocking pressure to be maintained Mulga removal

breaks the nutrient cycle of replenishment from the living mulga tree W l s , 1989)

7

The reduced cover leaves the soil vulnerable to sheet and gully erosion which occurs

as a result of reduced plant water uptake and greater water runoff Sheet erosion and the

,- corresponding loss of nutrients reduces the potential for bare areas to be regenerated, particularly if stocking pressure is maintained As Miles (3990) states, the relatively infertile

soils of the mdga contain around 90 per cent of their vital nutrients in the top 3 centimetres

of a 10 centimetre soil profile, and 75 per cent in the top 2 centimetres Using pot trials Miles (1990) was able to show that a 1 centimetre soil loss resulted in a 64 per cent fall in plant productivity as measured by total plant matter, while a 3 centimetre loss caused an 84

per cent decline

The cycle of degradation is believed to occur in discrete stages of stability or steady states The woody weed stage represents one such stable state Despite the loss of palatable grasses and a change in species dominance, woody weeds can help with topsoil retention and provide litter for the soil The extent of woody weeds is considered a reliable indicator of land condition (Mills et al., 1989) While they indicate the early stages of degradation, a large infestation is required to have an effect on total property productivity (Mills et al.,

1989) With careful management, woody weed affected areas may still be able to support perennial grasses (Miles, 1990)

A state of severe erosion with complete loss of the valuable topsoil implies

irreversible damage If only one tenth of a mulga site is affected by sheet erosion, productivity (perennial pasture biomass) is likely to be halved (MI.LIS et al., 1989) With lower pasture biomass, response to rainfall is considerably reduced

Extent of mulga rangeland de~radation

Potential degradation problems in the mulga rangelands were fist noted in a survey by

Skinner and Kelsey in 1964 They reported evidence of sheet erosion and increased run-off

in the western mulga rangelands and concluded that deterioration had occurred during the previous 20 to 30 years

The Western Arid Region Land Use Studies (WARLUS), undertaken in the 1960s and

1970s by the Queensland Department of Primary Industries, also identified degradation in

the mulga rangelands These surveys of geology, soils, vegetation and hydrology found that

while most of the area was in a productive condition, the early stages of degradation were

evident

It was left to Mills (1986b), in a land use study of 8.7 million hectares of mulga, to

reveal the extent of the problem His study found that 29 per cent of the surveyed area

showed symptoms of sheet erosion while 20 per cent had substantial woody weed cover

A land condition survey of 70 properties in the western mulga by Mills er al (1989)

supported these findings Properties were rated on a six-point scale from 'very poor' to

'very good', based on woody weed cover, sheet erosion and quantity of pasture The results

showed that half of the properties fell into the 'poor' and 'very poor' categories Woody

weeds were a problem on 51 properties representing 44 per cent of the total area, while

erosion was severe on 32 properties representing 9 per cent of the total area The properties

concerned were experiencing substantially reduced productivity

Miles (1990) used the level of radio-active isotope Caesium-137 remaining in the soil

from nuclear tests of the 1950s to measure the extent of soil loss In Miles' research, the

soil loss on woody weed affected areas, bare land and severely eroded areas were each

compared with soil loss from land with a good cover of perennial grasses and mulga

Woody weed affected lands lost 2 centimetres more soil than non-degraded lands over the

30-year period The soil loss was 2 to 3 centimetres greater on bare land, whereas in

severely eroded areas a loss of 5 centimetres of topsoil was recorded for the 30-year period

Miles showed that this soil was not redeposited but entirely removed from the system I

Further symptoms of degradation are reduced infiltration and greater water run-off

An increase in the number of flows of the Paroo River, the catchment of which lies almost

wholly within the western mulga rangelands, is evidence of greater run-off This occumed

despite relatively constant rainfall patterns (Mdes, 1990) Ten-year moving averages of the

number of annual Paroo River flood heights over 3 metres and Charleville rainfall for the

corresponding period are shown in Figures 1.3 and 1.4

0 ! l l l l l l r l l l l l , l l l l l l l l l l l l l l l l l l l l l l l l l l 1 1 1 1 1 1 1 1 1 1 ( 1 1 , ,

1835 1939 1949 1947 1 H 1955 1959 1- lW7 1@7l 1976 1979 1

F i Year, 10-year Moving Average

Figure 1.3 Number of Paroo River Flood Heights over Three Metres, 10-year Moving

Average, 1926-35 to 198 1-90

2 9 I I I I 1 , 1 I I I I I I I I I I I 1 I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I l I I I I I I I

1936 1939 1943 1947 1851 1955 1959 1863 1987 1971 1875 1979 1983 1887

Final Year, 10-year Moving Average

Figure 1.4 Annual Average Rainfall, Charleville, 10-year Moving Average, 1926-35 to

1981-90

Source: Bureau of Meteorology

10 The extent of soil loss for different levels of ground cover was examined by Miles and Johnston (1990) using four 1-hectare experimental catchments Predominantly bare areas, that is those with less than 20 per cent cover, realised soil losses 10 times those of areas with 40 per cent cover Infiltration losses amounting to an average of 40 per cent of

annual rainfall occurred where ground cover was under 20 per cent, equivalent to a loss in pasture biomass production of 400 kg/ha With a cover of over 40 per cent, the infiltration loss was only 10 per cent (Miles and Johnston, 1990)

1.3 Theorv and analvtical issues: A svnomig

The evolution of the mulga rangeland degradation problem can be attributed to numerous historial, environmental, physical and economic factors The theory of market failure is often used by economists to explain resource use rates above the social optimum Specific

sources of market failure relevant to the mulga rangelands include imperfect markets for information, divergence between private and social discount rates, property rights and land tenure, and land market imperfections An analysis of market failure arguments and those relevant to the mulga rangelands follows in Chapter 2, together with a historical perspective

on the degradation problem

The role of stocking rate in land degradation is analysed using cross-sectional economic and land condition data in Chapter 3 Regression tec&pes are used to idenhfy the significance ofeeonomic influences including property size and interest cost pressures on stocking rates Correlations between land condition and net incomes are also evaluated In

a separate exercise, a time-series of land price data is used to examine the performance of mulga rangeland prices over a 30-year period

Although the survey data reveal the correlations between economic factors, stocking rates and degradation, regional and climatic differences between properties are difficult to isolate Further, rangeland degradation is a dynamic process influenced by management and economic variables over time The problems of interpreting results of the static positive analysis using cross-sectional data may be avoided using dynamic methods One major

shortcoming of the static approach is that it does not incorporate the cost of lost future productivity The static optimal stocking rate, for example, at best incorporates a subjective judgement on the effects of utilisation on the pasture resource over time Graziers select a stocking rate based on a subjective balance between current and future use Dynamic

I , _ models, however, include the 'user cost' of current resource use, the foregone future

' resource rents, as an additional cost in the production function The concept of user cost,

, the conceptualisation of dynamic models by optimal control theory, and their solution by

J , dynamic programming are all discussed in Chapter 4

?$ Dynamic models are best adapted to normative problems By selecting a typical property in each size stratum and assuming profit maximisation, regional and other differences can be isolated in determum

g optimal rangeland use rates By varying economic parameters in turn, the effects on optimal stocking rates are observed A disadvantage of the dynamic approach is the data and computer memory requirement Cross-sectional survey

data are augmented with limited field trial and historical data to construct wool yield and price functions for a stochastic dynamic programming model The development of the model -

is outlined in Chapter 5 and the results are reported in Chapter 6

The normative dynamic programming approach eliminates the regional biases affecting the cross-sectional regression analysis The impacts of property size, price variations, wool

quality differentials and discount rate on optimal stocking rates are assessed A utility maximising model is used to explore the effect of risk aversion on optimal stocking rates over time Chapter 6 also gives details of a dynamic programming model incorporating previous stocking rate as an additional state variable with a constraint on possible following states This constrained choice model enables the derivation of user costs for sub-optimal combinations of pasture biomass and stocking rate

Chapter 7 summarises the significant economic issues in mulga rangeland degradation

in the context of the sustainability debate The usefulness of dynamic optimisation techniques

in identifymg the focus of rangeland policy is discussed

Chapter 2

%'r The degradation of rangeland from the pristine state through stable states of woody weed

;s infestation to eventual irreversible sheet erosion was attributed in Chapter 1 to grazing management In particular, the lack of flexibility in drought management and the availability

of mulga as a supplement fadltate the progressive deterioration in range condition In recent

times, the gamut of economic, institutional, environmental and social factors which determine

grazing management

This chapter identifies and discusses the importance of these factors The emphasis

is on the market failure approach, commonly used by economists in the discussion of land degradation issues (Kirby and Blyth, 1987; Wills, 1987; Rose and CO;, 1991) While many factors in mulga rangeland degradation may fall into the category of market failure, others are best described as government policy failure, or merely characteristics of the rangeland production system Moreover, many of the problems of land degradation have their origins

in the historical development of the region and early grazing management A review of the historical background to degradation is therefore a logical starting point

2.1 A historical ~erspectivq

2.1.1

The Queensland mulga rangelands were first settled in the 1 8 6 0 ~ ~ and by the 1870s, most of

the better grazing land had been claimed Due to an over-optimistic assessment of the

grazing capability of the rangeland, many of the smaller landholders soon encountered

financial difficulties Their problems were exacerbated by dingoes, isolation, drought and

the financial mash of 1893 which culminated in the demise of the small landholder class in

the years up to 1900 (Gasteen, 1986) Originally, grazing was concentrated along

watercourses and graziers practised a virtual nomadic existence The fist tapping of artesian

water in the 1890s allowed: stock to be grazed away from the main watercourses and

contributed to a boom in stock numbers By the late 1 8 9 0 ~ ~ stock numbers reached a peak

and many large stations carried over 100,000 sheep @avidson, 1981) The peak in stock

numbers was closely followed by the severe drought of the early 1900s which caused severe

degradation and turned stock routes into wasteland (Gasteen, 1986)

The frequency of drought and other problems which thwarted early settlers resulted

in a dominance by large pastoral companies By the outbreak of the Great War these large

pastoral companies jointly occupied around 50 per cent of pastoral leases Following the

war, the government was pressured to break up the huge pastoral'holdiings, thus commencing

the era of closer settlement This policy of subdivision continued through to the 1950s

(Gasteen, 1986)

Early grazing management followed a European approach of continuous heavy grazing

I

unsuited to fragile arid environments (Gasteen, 1986; Davidson, 1981) The result was a

gradual change from the relatively open grasslands to the existing dominance of woody

species including mulga Land degradation was most severe in the western zone where the

open downs were more amenable to stock management, and along frontage country where

stock concentrations were heaviest The eastern mulga with its dense scrub was in better

condition, being less developed and stocked mainly with cattle (Gasteen, 1986) Even with

15 development and improved watering, the peak stock numbers reached in the late 1890s were not matched until the 1950s, when a wool price boom encouraged expansion (Mills, 1982)

Another example of the poor understanding of the rangeland system was the damage caused by introduced species such as rabbits and foxes Nonetheless, awareness has

, improved with time Fisher and Krutilla (1974) refer to an improvement in 'future expectations as determined by past realisations'

2.1.2 Closer settlement mlicy and propertv size

Davidson (1981) states that the 'history of land settlement in Australia is a repetitious cycle

of the failure of small-scale fanning' The attempts by early land administrators to introduce small-scale farming to the mulga rangelands have been a major factor in land degradation

Closer settlement involved the resumption and subdivision of large properties and the reallocation of land by ballot to family farmers The aims were to encourage land development, improve wealth distribution and to improve regional economies by increasing population (Young et al., 1984) In the post-war era, a further aim was to assist returned soldiers to re-integrate Regrettably, the closer settlement policies failed to recognise the limitations of both the land and the new settlers It resulted in a uniformity of property sizes

despite the need for diversity to accommodate the different management styles and land types (Young et al , 1984) Most importantly, the legacy of closer settlement is a domination of small properties in the pastoral zone To achieve cost efficiencies in flack management, these graziers have had to adopt higher stocking rates than those on larger properties (Young

et al., 1984) Young's (1980) study of western New South Wales graziers observed that stocking rates were higher and land was in poorer condition on smaller holdings

In recognition of the implications of closer settlement for land utilisation and degradation the fragmentation of pastoral blocks ceased in the 1960s, and since then, many property amalgamations have occurred The number of holdings in the Paroo and Murweh shires declined from 476 in 1966 to 366 in 1988 (Australian Bureau of Statistics, various)

16

The distribution of property sizes in the mulga rangelands as at 1988 is illustrated in Figure 2.1 The average property size was 32,900 hectares, though the distribution was positively skewed with 71 per cent being smaller than this average Some 24 per cent of properties were smaller than 15,000 hectares

Property Size (thousand hectares) Figure 2.1 Distribution of Property Sizes in the Mulga Rangelands

Source: Queensland Department of Primary Industries

Although the smaller properties are expected to be the most severely degraded, there

is limited evidence of this to date Mills et al (1989) compared land condition on the seven largest properties in their survey of 70 properties (71,510 hectare average) with the seven smallest properties (10,894 hectare average) They found little difference in eroded areas

or woody weeds, but mulga cover was significantly lower on smaller properties This may have indicated a greater use of mulga topfeed on smaller properties The apparent absence

of correlation between property size and degradation may be due to the dominance of regional and rainfall differences in explaining variations The larger properties are generally

in the west and receive lower average rainfall This research demonstrated the difficulty in attaching empirical estimates on the impact of property size on degradation due to regional diversity

in

: Previous research has identified minimum property sizes or flock sizes for viable

1s

; mulga properties Childs (1974) showed that a minimum flock of 7,600 sheep was required

3f to maintain a positive cash flow on Paroo properties during the dry seasons 1967-70 This

equated to an area of 60,000 hectares, compared to the western mulga average of 37,000

maintained for 9 years out of 10, a property size of 67,000 hectares was required More

;: recent suggestions are for a minimum flock size of 8,500 DSEs (Wanego Graziers

I: Association, 1988) Graziers appear to also recognise the property size problem Further

2.2 A market failure approach to land de~radation

: - I The preceding historical background illustrates that the degradation problem largely grew out

of ignorance and the poor understanding of the fragility of the rangeland and its carrying capacity Government objectives of regional development rather than conservation in the intervening years gave the region its current property size structure with further implications for degradation However, the market failure or imperfections approach provides a useful framework for identifying other factors relevant to the degradation issue

The existence of land degradation does not necessarily imply an economic problem (Kirby and Blyth, 1987) A problem only exists if the actual rate of land degradation diverges from the optimal rate preferred by society, and it may well be optimal to deplete

or degrade the resource entirely (Quiggin, 1986) The optimal rate of land degradation is the rate which rnaximises the net social benefit, a rate which may be higher or lower than

the actual rate (Kirby and Blyth, 1987)

Economists use the theory of market failure or market imperfections to explain this divergence between optimal and actual rates of degradation Market failures describe an interference or breakdown in the operation of the competitive economy towards a Pareto-

optimal resource allocation, (Quiggin, 1986; Randall, 1983) and are often used as a case for government intervention By analysing the factors thought to contribute to degradation, it may be determined whether the actual rate of degradation lies at, above or below the optimal rate For instance, if it can be shown that market fkilures exist in the land market, or that external costs are not incorporated in the decision making process, then it may be concluded -

that land use is above the optimal rate With such causes identified, policy measures can be devised to reduce actual rates of degradation by treating the cause rather than the symptom However, the identification of failures in the market is insufficient justification for government intervention The expected net social benefits from intervention must exceed social costs in a benefit-cost analysis (Chisholm, 1987a; Edwards, 1987)

Sources of market failure include externalities, divergences between private and social

discount rates, imperfect markets for information, absence of markets for existence and option values, problems with tenure and distorted market prices (Quiggin, 1986; Kirby and Blyth, 1987; Wills, 1987) These sources and their relevance to the mulga rangeland environment are reviewed in the following sections

2.2.1 Imperfect market for information and research

Perfect market operations require perfeft knowledge Information deficiencies can lead to

I

divergences between private and optimal rates of land use The non-excludable nature of the provision of technical and research information means that graziers have little incentive to conduct their own research into solutions to degradation Usually, no market exists for the transfer of information and free riders cannot be excluded (Wills, 1987) In any case, the cost and resource commitments required for research may be beyond the capability of the individual land user Economies of scale in research projects may only be achieved if all

land users cooperate or if the government intervenes (Chisholm, 198%)

The experience of government intervention provides further evidence of imperfect information Soil conservation research and extension have received active consideration only since the 1940s, while the economic aspects of land degradation are a very recent issue

.?I (Chisholm, 198%) A lack of knowledge of the physical tolerance of the mulga rangelands led to exploitive early grazing practices, to the misguided policies of early land administration and closer settlement, and to current graziers' approaches to drought management

2.2.2 Divergence betwee

r'

1 *_ The discount rate provides a measure of the relative value of economic resources between

'5 consumption, due to impatience or time preference Similarly, current investment is

" *

2;- + preferred to future investment due to the opportunity value or earnings potential of current

i - ' z resource use A high discount rate gives a greater weight to present cash flows than to future

i ones and the present value of all future cash flows declines as the discount rate rises The

L , , relative value or price of present versw future consumption clearly influences the decision

i - of present versus future resource use With renewable resources, the rate of discount

influences the rate of harvest Generally, a high discount rate used by the grazier implies

a higher rate of utilisation and potential land degradation

2.2.2.1 Intergenerational ea-uihr issues and market failure

One of the basic elements of the market failure approach is the apparen't divergence between social and private rates of discount The rate of discount which defines society's choice between present and future income is usually lower than the individual's rate of discount for

a number of reasons Firstly, for reasons of myopia or selfishness, the current generation

is expected to show inadequate concern for future generations However, this intergenerational equity argument was challenged by Kirby and Blyth (1987) Mechanisms

of intergenerational transfer such as bequests demonstrate the concern of the current generation for at least the next one or two generations Moreover, productivity gains, technological change, economies of scale and product substitution may enable future generations to be richer and enjoy higher living standards than the current generation A

lower discount rate would therefore mean a redistribution from the poorer current generation

to richer future generations Another criticism of the myopia view is that any discount rate adjustment would be subjective

Secondly, although the current generation may be concerned for future generations,

an under-investment in conservation is likely to occur due to a type of free-riding behaviour

by individuals According to Marglin (1963), provision for future generations is viewd by current generations as a public good Hence, the total resources left unused or undegraded for fbture generations by individuals acting alone would be less than the total that individuals

- would collectively desire (Chisholm, 1987b) Individual discount rates would be higher than that expressed collectively by the population as a group Kirby and Blyth again state that this argument provides only arbitrary guidance for estimating a social discount rate Krutilla

(1967) noted that since the social discount rate as measured by society's rate of time preference was directly related to market rikes of interest, a lower discount rate would stimulate investment and potentially result in further exploitation of resources and environmental damage Lower discount rates may also interfere with interest rate policy

As Kirby and Blyth note, the myopia and intergenerational market failure arguments provide limited justification for using discount rates other than the private (or market) rate

of discount Quiggin (1987) highlighted the difficulties in comparing the estimated private discount rate with the social rate of time preference After inflation, credit rationing, and

risk considerations, Quiggin estimated a pre-tax real discount rate for farm investment of around 5 per cent The real discount rate is essentially the market interest rate less the expected rate of inflation (Chisholm, 1987b) Qulggin's estimate compares with real rates

of time preference ranging from 0 to 10 per cent and more The problem lies in the absence

of an agreed value for the social time preference rate

Although the unquantifiable divergence between social and private rates may explain

the process of degradation in general, it does not explain the different rates of degradation between individual properties Hence, the divergences in individual discount rates and the sources of these divergences are a further problem in land degradation The chief elements

in private discount rate sensitivity are interest costs, ownership intentions, planning horizon

2 1

y and security of land tenure The interpretation of these factors in a discount rate may depend

on the individual grazier's risk attitude and the nature of the investment (Rose and Cox,

;ie 1991) Usually, society tends to be risk-neutral and rural producers are risk averse (Young,

$ small Young (1980) argues that if the premium was less than 2 or 3 per cent and credit

, market imperfections were not in evidence, the graziers' management strategies and those

f preferred by society would not diverge A proportion of rnulga graziers, however, may be

r

6 risk-preferrers given the type of environment in which they choose to operate (Francisco and

*Anderson, 1972) A risk-preferring attitude would produce a greater premium on discount

3:

F+ rate Moreover, risk attitudes change according to circumstances Graziers may become risk-preferring when they receive small or negative incomes and more conservative when incomes are high (Francisco and Anderson, 1972) Clearly, the pressure of debt is likely to significantly influence risk attitudes

2,-

-: 2.2.2.2 Financial ~ressures

A grazier's financial status is likely to be a major determinant of his discount rate and therefore stocking policy The need to meet periodic payments required by lenders constrains management options Young et al (1984) hypothesise that heavy grazing and degradation

I

are more likely on properties with high debt levels While the debt-free grazier is able to reduce stock numbers during drought, the indebted grazier is forced to maintain stocking rates at the risk of degradation Meppem and Johnston (1990) refer to the need to meet short-term financial objectives as a factor in grazing policy No research has yet been conducted linking indebtedness and degradation in the mulga rangelands

A further source of financial pressure arises from the isolation and distance problems

of living in the mulga rangelands Additional expenses in education, travel and communications burden financial resources and restrict management options (Warrego Grazier's Association, 1988) Many graziers purchase city housing for their children, while others are forced to sell and move closer to schooling facilities

Fluctuations in livestock and wool markets will also affect stocking decisions In

good seasons and with high p-rices, graziers opportunistically increase stock numbers to rnaximise return per sheep or per hectare (Young et d., 1984) The simultaneous occmence

of drought and low product prices may exacerbate the impact of opportunism on land condition by forcing gfazim to retain stock -

2.2.2.3 owners hi^ intentions and ~ l a n n i n ~ horizon

Ownership intentions and planning horizons are related factors which might be expected to influence land use A grazier intending to sell before retirement may be more exploitive in his approach than a grazier intending to bequeath the property to his children Graziers with

a longer planning horizon may be expected to have a lower discount rate However, this outcome rests on the expectation that land values will not be affected by degradation If the land market operates efficiently, a short planning horizon and a corresponding overuse of resources will be reflected in land prices, the residual value of the capital asset which is included in the discounted present value of rents (Gardner and Barrows, 1985) The planning horizon issue therefore relates to the problem of imperfect information in the land market

2.2.3 Uncertaintv about irreversibilitv

Irreversibility refers to the possibility that the selected current &source use precludes some future use The uncertainty associated with irreversible resource use decisions is reflected

in a value placed by society on the option to preserve the resource for future use This option value is the value society would be willing to pay to retain the mulga rangelands, a cost of risk-bearing or insurance (Chisholm, 1987b; Fisher and Krutilla, 1974) If a future use yielding higher returns could not be found, there would be no option value

In the latter case there may still remain an 'existence' value, an amount society is willing to pay for the knowledge alone that land remains undegraded (Chisholm, 1987b)

The source of market failure is that no market exists for the expression of option and existence values

, , Attempts to estimate option and existence values have been made using simulated

' f

market information Problems with estimating such values include methods of payment,

' consistency between expressed and actual willingness-to-pay, and potentially negative values

6 (Quiggin 1986; Chisholm, 198%) Such problems in measurement limit the usefulness of

$bption and existence values It can be further argued that preferences for such values are

SX In the case of the mulga rangelands, no estimate has been made of society's option

?Or existence values, possibly due to the region's remoteness and its low productivity

i However, Foran et al (1990) suggest that positive option and existence values for rangelands

;iAhave a basis in the tourism industry, with the attraction of space, natural landscape and

F

?

I - cultural heritage under threat from degradation Thus the option value may be related to the aesthetic values as well as the productive value of future alternative uses

2.2.4 Property r i ~ h t s and land tenuR

The economic theory of property rights concentrates heavily on the comparison between open access and private ownership In the Australian context, the issues relate mainly to the two main forms of land title, leasehold and freehold Uncertainty about length and security of tenure, rewards and penalties, and lack of compensation for land value at end of lease are the main concerns with leasehold tenure in terms of land degradation Adverse consequences

could be minirnised if lease terms are long and lease covenants can be used to monitor the lessee's behaviour (Quiggin, 1987)

Freehold tenure involves risks of degradation if the highest bidder is over-optimistic about carrying capacity, and especially where new settlement is taking place (Quiggin, 1987) Another risk with freehold tenure is that if applied on a large scale, it is difficult to reacquire for national parks or to revert to leasehold tenure (Young, 1987)