SCALE, HETEROGENEITY AND SECONDARY PRODUCTION
IN TROPICAL RANGELANDS
Andrew Ash1, John Gross2 and Mark Stafford Smith3
1
CSIRO Sustainable Ecosystems, 306 Carmody Rd, St Lucia, QLD 4067, AUSTRALIA
CSIRO Sustainable Ecosystems, Davies Laboratory, Private Mail Bag, Aitkenvale, QLD, 4814
3
CSIRO Sustainable Ecosystems, Centre for Arid Zone Research, PO Box 2111, Alice Springs NT 0871
2
ABSTRACT
Tropical rangelands across the world are experiencing land use intensification pressures which are reducing the spatial
scale of grazing management units. There are implications of a reduction in scale on environmental heterogeneity and
its relationship with secondary production of large herbivores, and on the consequent risks of land degradation.
Rangeland managers find it hard to conceptualise these implications, and there has been little research to clarify them in
the past. This paper will review our current understanding of scale-related effects on livestock production in tropical
rangelands and herbivore-plant interactions at patch to landscape scales. We use published information and results from
recent empirical studies in northern Australia and elsewhere to elucidate scale-related effects on secondary production.
These results indicate that empirical approaches alone will not provide all the understanding necessary for better
management of extensive grazing lands that are undergoing intensification and that modelling approaches are important
in helping to understand underlying mechanisms driving observed changes. Such modelling approaches need to
encompass rangeland systems as complex, adaptive systems where socio-economic factors are just as important as
biophysical understanding. We use a conceptual J-curve model to help explain how fragmentation and intensification
affects the socio-ecological dynamics of arid and semi-arid grazing lands.
INTRODUCTION
Spatial scale and complexity play an important role in the functioning of socio-ecological systems in rangelands.
Compared with many landscapes rangelands are often considered to be rather homogenous so fragmentation and its
ecological implications may not be viewed as important issues. However, rangelands are diverse, albeit through
relatively subtle variations and gradients in soil, vegetation and climate. Any individual landscape element may not
appear to be complicated but these individual elements are linked and interact with each other through physical and
ecological processes that form a complex ecosystem.
Land use intensification throughout the rangelands is fragmenting landscapes into simpler, discrete units. The result is a
reduction in the scale of landscape-animal-human interactions. There is evidence that this reduction in complexity has
an impact on ecosystem function and system resilience (Behnke & Scoones 1993, Ellis & Swift 1988) which may lead
to dysfunction in ecological communities, enterprise economics and social structures. This fragmentation can occur
regionally, in the form of altered land tenure and/or enterprise size, and within enterprises, particularly in commercial
pastoral operations that seek to intensify production. At the regional scale the fragmentation process can be represented
in system dynamics by a J-curve (Figure 1), with the reduction in scale initially focussed on capturing (often but not
necessarily by privatising) the higher quality resources (waters, grazing, cropping lands etc). However, at some stage,
the history of rangelands in developed countries suggests that this process invariably reverses itself and consolidation of
land begins to occur once more (hence the curl of the J). By this stage, the higher-value (usually, most agriculturally
prospective) parts of the landscape have been excised and the re-consolidation occurs in the residual rangelands or
grazing lands. The hypothesis is that this process is indeed part of the same syndrome, and not disjunct from the
descending arm of the ‘J’.
Notwithstanding some naturalistic aversion to development, it is important to realise that intensification is not
necessarily bad in terms of net regional welfare – there are winners and losers but in most circumstances it is likely that
net regional productivity can be increased by subdividing the landscape and specialising the use of different landscape
elements. This is indeed the basis on which agricultural areas have developed throughout the world. However, it is a
matter of interest to understand these processes because we contend that the point in the trajectory at which systems are
at greatest risk of land degradation may be close to the bottom of the curve. If this is so, then understanding where the
endpoint of intensification is most likely to be and facilitating the change to this point as efficiently as possible may be
an important option for managing the process of intensification. The factors which drive the trade-offs allowing shifts
along the curve are a complex mixture of the production and economic benefits of fragmenting the landscape balanced
by the costs of acquiring and retaining ownership rights. Once the better lands have been excised, the balance of these
factors in the residual rangelands changes again, triggering the tendency to re-consolidate. In short, the challenge is
first to identify any marginal cases where continued subdivision really is not regionally beneficial (the trend being
driven by inequitable exploitation or political ideology rather than legitimate net benefits), and, for those cases where
the trend is warranted, minimise the transient degradation risks.
Landscape fragmentation
More fragmented
More intact
land tenure policy
Mainly driven by
commercial arrangements
Unconstrained
nomadic
systems
Privatisation of
‘better’ land as
population
increases
Period of highest
degradation risk
Consolidation of
residual rangelands
Permanent excision
of higher value land
Theorised developmental trajectory over time
(What is the appropriate endpoint in different systems??)
Figure 1. Hypothesised process of fragmentation and reduction in scale in rangelands.
In this paper we wish to focus on the role of spatial scale on landscape-herbivore interactions in tropical rangelands and
the implications for system productivity and resilience. The initial emphasis will be on biophysical interactions in
commercial pastoral enterprises inasmuch as these contribute an important parameterisation for the drivers of change on
the J-curve but we will then consider briefly how these interact with the socio-economic drivers, and the issue of
biophysical scale in rangelands.
TROPICAL RANGELANDS OF NORTHERN AUSTRALIA
In common with rangeland regions throughout the world, the tropical rangelands of northern Australia are characterised
by nutrient limited soils and a highly variable climate that is unsuitable for intensive agriculture. Pastoralism is the
dominant land use, characterised by large-scale enterprises (10,000 to 1,000,000 ha) which generally rely on low inputs
and have low outputs per hectare, and which are subject to uncertain markets and variable prices.
The variable climate means that is difficult for pastoralists to match animal numbers to forage supply (O’Reagain &
Bushell 1999) and there are episodic forage deficits and associated concerns about land degradation. Because individual
management units (paddocks) are quite large, uneven utilisation due to landscape heterogeneity and poor distribution of
water is common (Ash & Stafford Smith 1996), reducing the average utilisation efficiency of primary production per
unit area.
Increasing costs of production and relatively stable prices have resulted in a cost-price squeeze and the need for everincreasing efficiencies in production. This continuous cost-price squeeze is forcing many producers to examine ways of
increasing productivity and returns and reducing costs. Most properties are relatively efficient, given their current scale
and resolution of operation, with limited scope to dramatically reduce costs, so pastoralists are looking to intensify
production to increase returns (Ash & Stafford Smith 2002). Many pastoralists have learnt from past attempts at
increasing productivity that simply increasing animal numbers can lead to short-term gains, but resource damage and
failing economics is the longer-term result (Landsberg et al. 1998). Current attempts at increasing production are
focussed on overcoming some of the problems of uneven grazing distribution in large paddocks by increasing fencing
and water points and reducing paddock size. These developments are undertaken on the assumption that carrying
capacity will be sustainably increased. However, when making these decisions the potential benefits of larger,
heterogeneous paddocks in terms of individual animal performance are often overlooked. Large, diverse paddocks can
provide spatial buffering for animals during the dry season and during droughts (Scoones 1995) and less diverse, small
paddocks may suffer in productivity if resource rich patches are no longer accessible (Ash & Stafford Smith 1996;
Boone & Hobbs 2003). There may also be an impact of intensification on biodiversity. We know that increaser species
are more abundant near water points and that grazing sensitive, decreaser species may only be found a long way from
water where grazing pressure is very light or absent (James, Landsberg and Morton 1999). Provision of extra water
points may see further declines in grazing sensitive species unless off-reserve conservation areas or formal reserve areas
are increased at the same time.
However, all of these effects are context dependent – for example, grazing impacts on preferred vegetation types
depend greatly on whether those types are the minority or majority of the landscape, and whether they are more of less
resilient than other components. To understand the effects of intensification and a change in scale and heterogeneity on
plant-herbivore interactions and its implications for animal production and pastoral management, we therefore need to
understand the critical foraging processes and decisions at all spatial scales. The next section of this paper briefly
reviews plant-animal interactions at various scales in the context of management implications.
SPATIAL SCALE, PLANT-HERBIVORE INTERACTIONS AND SECONDARY
PRODUCTION
Foraging decisions are made at a range of spatial scales that can be organised in a hierarchical manner (Senft et al.
1987). These spatial scales range from the bite up to the landscape and each scale can be defined according to
characteristic behaviours that also involve different time scales (Bailey et al. 1996, Table 1). We now discuss foraging
behaviour across these spatial scales and the implications of fragmentation on plant-animal interactions.
Table 1. Spatial scale of forage and site selection in rangelands, and potential effects of fragmentation at each scale
(modified from Bailey et al. 1996).
Space and time scale
Bite – 1-2 seconds
Patch – 1-30 min
Feeding site – 1-4 hrs
Camp – 1-4 weeks
Seasonal range – month
to years
Selection criteria
Nutrient concentration, biomass density,
toxins, bite concentration
Forage species, forage abundance,
topography
Topography, plant community, soil type,
forage abundance and phenology
Water availability, topography, forage
abundance, thermoregulation, plant
phenology, predation, competition
Water availability, forage quality and
quantity, thermoregulation, predation,
competition
Effect of fragmentation
None
None to some impact. May limit management
options (e.g., burning); may affect patch
structure by facilitating intensive management
(e.g. reducing patch structure via short-term,
intensive grazing)
None to large. Restrict access to landscape
components, habitats, or preferred areas
Potentially large effect if at appropriate scale.
Restricted movements and access to landscape
elements.
Almost certainly large. Fragmentation may
prohibit migration, dispersal, or transhumance
Plant part and species selection
At the finest spatial scales, foraging decisions are made on the basis of plant part (e.g. leaf vs. stem) and plant species.
In tropical rangelands, which are dominated by tussock perennial grasses, the bulk of the diet is grass though forbs and
shrubs can make significant contributions to the diet (Ash et al. 1995). This selection process can lead to changes in
species composition which in turn can have feedback effects on diet selection and forage quality. For example, where
the abundance of perennial grasses is reduced by grazing, diet quality can improve if more forbs are made accessible
(Ash et al. 1995). However, net primary productivity of forages can be reduced in response to overuse at this spatial
scale (Ash & McIvor 1998, McIvor, Ash & Cook 1995).
Management does not influence plant-herbivore interactions significantly at this scale, except inasmuch as changes of
total grazing numbers and distribution resulting from management changes at the whole paddock scale have an indirect
effect on specific locations. Fragmentation of landscapes has relatively little impact on foraging decisions at this spatial
scale.
Patch scale grazing
A distinctive feature of tussock dominated grasslands typical of tropical rangelands is patch grazing (Mott 1987),
specifically defined as differentially patterned grazing in otherwise homogenous vegetation. Because of repeated
grazing of patches once they are established, patch grazing can lead to localised degradation (Bridge, Mott & Hartigan
1983). The formation of patches can have benefits for animal production with the intake and diet quality of animals that
have access to short patches being higher than that of animals grazing a more homogenous sward (Houliston, Ash &
Mott 1996 – Table 2, Wilmshurst, Fryxell & Hudson 1995).
Table 2. Effect of mown patches (5 patches per paddock, total patch area 16% of paddock) on diet quality, feed intake and
foraging behaviour of cattle grazing tropical tallgrass pasture at Lansdown, near Townsville (Houliston et al. 1996). Mown
plots were cut to about 10cm to allow regrowth which simulated a grazed patch.
Dietary nitrogen (%)
Dietary dry matter digestibility (%)
Dry matter intake (kg/head/day)
Grazing time in patches (%)
Unmown
Patchy
1.49
49.4
8.5
19
1.59
52.5
9.5
28
Does intensification of pastoral management have an impact on plant-herbivore interactions at the patch scale? As
pastoral management intensifies there is scope for more high intensity grazing systems such as cell grazing or short
duration grazing where large numbers of animals are used to mob-graze a small paddock and the paddock is then rested
for some weeks or months. Such a grazing system has the potential to overcome patch grazing and although there is
much anecdotal evidence that more intensive grazing systems achieve more uniform grazing distribution, experimental
evidence has proved elusive (Hart et al. 1993). Fire has been used successfully to overcome patch grazing in tropical
tallgrass communities (Andrew 1986) through a simple flip-flop burning regime. Fires tend to reset the system such that
animals do not revisit old patches in recently burnt country. Such a fire regime is only practical in more intensively
managed landscapes where there is good control of fire.
Landscape foraging processes
It is foraging decisions in landscapes that will be most affected by fragmentation and intensification in pastoral
management so it is important that there is a good understanding of plant-herbivore interactions at this scale and their
effect on animal production. It is well known that animals use landscapes unevenly, with respect to either distance to
water or herbivore preferences for different vegetation communities (Senft, Rittenhouse & Woodmansee 1983, Lange
1985, Stafford Smith 1988, Pickup & Chewings 1988). It is usually the more fertile parts of the landscape (riparian
areas, fertile clay soils) that are the focus of much of the grazing pressure (Scoones 1995, Ash et al. 1995). Such spatial
selection can accelerate degradation if animals concentrate their grazing close to water or in more fertile pockets of the
landscape (Pickup & Stafford Smith 1993). Overutilisation of these favoured areas can have negative feedback effects
on forage productivity (Mott et al. 1992, Ash & McIvor 1998) and land condition. As more favoured areas lose
productivity and their capacity to support animals, grazing activity is shifted to the next preferred areas and a cycle of
sequential degradation across the landscape may result. This phenomenon is one of the main reasons that
recommendations on fencing according to land type have been promoted in commercial rangelands.
Grazing patterns in large, heterogeneous landscapes can have both positive and negative implications for animal
production. The existence of key resource areas in large landscape-scale paddocks can help buffer animal productivity
during extended dry seasons and droughts (Scoones 1995, Illius & O’Connor 1999). Studies of African grazing systems
have consistently identified the importance of large-scale movements to sustaining both domestic and wild herbivores
during droughts (Homewood & Lewis 1987; Walker et al. 1987; Coughenour et al. 1985). Analysis of mortality
patterns has shown that despite a high annual variation in precipitation and plant production, mortality is related to both
animal density and to access to variability in available grazing areas (Homewood & Lewis 1987; Desta & Coppock
2002; Walker et al. 1987). These empirical results are supported by recent efforts to simulate broad-scale dynamics of
plant-herbivore systems, and they emphasize the dangers of fragmenting highly variable systems (Illius & O’Connor
1999, 2000). Anecdotally, pastoralists in black clay landscapes of northern Australia prefer a mix of heavy clay country
and lighter red soils for animal production because of the different forage growth responses to rainfall on these two soils
(Ash & Stafford Smith 1996). However, animal performance in large paddocks may suffer where there is poor water
distribution. Hart et al. (1993) demonstrated this in temperate rangelands where the liveweight gain of cattle grazing a
large paddock with water at one end of the paddock was significantly inferior to that of cattle grazing smaller paddocks
where distance to water was 1.0-1.6 km.
Clearly, intensification of grazing can have a major effect on plant-herbivore interactions and animal production. For
most pastoral enterprises intensification is not just about increased infrastructure in the form of fences and/or water
points to improve grazing distribution, but also usually includes decisions on stocking rate and carrying capacity. It is
therefore important to look at the interaction of spatial scale and stocking rate when considering animal production in
fragmented landscapes. At small spatial scales a linear decline in animal performance with increasing stocking rate has
been clearly demonstrated in rangelands (Ash & Stafford Smith 1996). However, it is unclear whether this relationship
Animal production/head
can be extrapolated to landscape scale paddocks. If spatial buffering is occurring in heterogeneous paddocks then the
stocking rate – animal performance relationship may not be a linear decline. We hypothesise that animal performance
per head may decline slowly with increasing stocking rate until a critical threshold is reached, such as the depletion of
key pockets of fertility, which is then followed by a rapid decline in animal performance (Figure 2). There is
remarkably little empirical evidence to support this hypothesis. One grazing trial in northern Australia investigating
stocking rate impacts on animal performance does have paddocks that are reasonably large (400ha – 1200ha) and in this
study there has been very little effect of stocking rate on individual animal performance (N. MacDonald pers. comm.,
Figure 3). This result contrasts with an analysis of a large number of small spatial scale stocking rate studies in
rangelands where there was on average a 20-25% decline in animal performance with a doubling in stocking rate (Ash
& Stafford Smith 1996). However some caution needs to be exercised in inferring the results of the large scale grazing
trial as strongly supporting our hypothesis of stocking rate- animal production relationships in landscape paddocks as it
is a single study and the majority of the years in the experimental study were well above average in terms of rainfall and
pasture growth.
Large, heterogenous
Homogenous
Stocking rate
Figure 2. Hypothesised stocking rate – animal production relationship in relation to scale and landscape complexity.
If there is a significant difference in the nature of these stocking rate – animal performance relationships at different
spatial scales then it is important to take this into account in the context of landscape intensification. For example,
smaller homogenous paddocks may provide the opportunity to increase stock numbers because of better water
distribution. Hart et al. (1993) found individual animal performance may be improved by modifying cattle distributions
to prevent over-utilisation of areas close to water and underutilisation of areas distant from water. However, there may
be a trade-off in the performance of individual animals if a reduction in paddock size is accompanied by a reduction in
landscape and dietary diversity. This context-specific issue has not been adequately addressed in the rangelands and it
has important implications for rangeland management. For example, is it possible to achieve the benefits of more even
utilisation provided by increased water points and also the potential benefits of increased dietary diversity provided by
large heterogeneous paddocks by increasing water points in large paddocks rather than sub-dividing them? This can
also have benefits for pastoral management in reducing fencing costs, which is a major expense in any intensification of
rangeland enterprises.
The effects of scale on plant-herbivore interactions and the most appropriate management response will be very much
dependent on how synchronous or asynchronous forage production and quality is between landscape elements, as well
as the resilience or susceptibility to herbivory of different vegetation units (Ash & Stafford Smith 1996). These
interactions and their management implications can be expressed in a simple matrix (Table 3) which in effect provides
some simple rules of thumb for incorporating into decisions on intensification.
To help answer these questions of landscape diversity, water points and subdivision and their interaction with foraging
behaviour and animal production two new field studies in northern Australia have commenced (Hunt et al. 2003 – this
volume) that should provide empirical data to support or reject the hypotheses raised in this section.
95
170
90
160
85
150
80
140
75
130
70
120
65
110
Reproduction
Annual liveweight gain of
steers (kg)
180
Weaning percentage
100
Steer gain
60
100
7.5
10
15
Stocking rate (head per sq km)
Figure 3. Effect of stocking rate on animal performance in a tropical savanna environment in northern Australia where
paddock sizes ranged from 400 ha to 1200ha. Based on unpublished data of Neil MacDonald, Northern Territory
Department of Business, Industry and Development, Katherine, NT.
Table 3. Relationships between forage production and quality at the landscape scale and likely implications of
fragmentation for production and management (after Ash & Stafford Smith 1996).
Forage growth and
quality between
landscape elements
Asynchronous
Preferred
vegetation units
Impact on animal
production & vegetation
Effects of fragmentation
Resilient
Potential loss of animal productivity
because heterogeneity cannot be exploited
Asynchronous
Susceptible
Enhanced animal
production, vegetation
stable through time
Enhanced animal
production but preferred
areas at significant risk of
degradation
Synchronous
Resilient
Synchronous
Susceptible
Little production
advantage in trying to
exploit diversity,
vegetation stable through
time
Little production
advantage in trying to
exploit diversity,
preferred areas at risk of
degradation
Loss of heterogeneity may be deleterious
for animal production but, because parts of
the landscape are susceptible, subdivision
may make it easier to manage degradation
risk
Fragmentation has little effect on animal
production or management – these
landscapes are already likely to be smaller
scale in both size of enterprise and
paddock size
Fragmentation has little effect on animal
production and in fact maybe desirable
from a management perspective so
degradation-prone landscape elements can
receive more focussed management.
Given the complexity of plant-animal interactions at the landscape scale, experimental or experiential evidence may
identify patterns, but the identification of common patterns, by itself, is unlikely to advance our understanding of the
underlying mechanisms driving the observed changes. Development and application of rangeland systems models is
thus likely to be a necessary component in the evaluation of conceptual models, as hypotheses, of how these systems
operate and how various forms of fragmentation and/or intensification will influence their dynamics, including
productivity, resilience, and sustainability.
MODELLING PLANT-ANIMAL INTERACTIONS IN COMPLEX LANDSCAPES
An understanding of plant-animal interactions is a key foundation for constructing models of rangeland systems that
incorporate spatial heterogeneity. As stated earlier, herbivores respond to heterogeneity at scales from individual bites
to major landscapes components, such as vegetation types, major topographic features, or microclimates (Senft et al.
1988; Coughenour 1991; Bailey et al. 1996), and there are important feedbacks between consumers and producers at all
scales. Given the importance of these interactions, has simulation modelling improved management of grazing
systems?
Most studies of plant-animal dynamics in rangelands have been at smaller scales, and we now have a firm
understanding of processes that regulate short-term intake rate of herbivores (Laca, Ungar & Demment 1994, Spalinger
& Hobbs 1992, Ungar & Noy-Meir 1988)) and experimental data that support process-based models across a broad
range of herbivore species (Gross et al. 1993). These studies have provided a direct link between the mechanics of
feeding and the response in intake rate, and this mechanistic link permits the broad application of these models across
plant types, feeding habits, and body sizes. Insights from the development of fine-scale, mechanistic models have been
key to understanding system dynamics of species that are tightly coupled to relatively homogeneous food resources at
small spatial scales (e.g., Illius et al. 1995) and for predicting gain functions of animals in intensively grazed grasslands
(usually in temperate environments). They appear to be far less applicable to, for example, tropical systems where there
is extreme heterogeneity in the structure, quality and quantity of forages on offer within a paddock or feeding area. In
this situation, tradeoffs between quality and intake rate greatly complicate diet selection, and our ability to predict either
intake rate or gain is limited.
The major challenge to extrapolating small-scale processes to the larger scales more relevant to extensive grazing
systems is the large effect of animal behaviour. Mechanistic models can accurately predict intake rates of hungry
animals over small spatial and temporal scales, but selectivity, movement patterns, social interactions, memory, and
environmental factors clearly influence the spatial distribution of herbivores and their subsequent use of forages at
paddock and landscape scales (Senft et al. 1988; Coughenour 1991; Bailey et al. 1996). At the largest scales, both
statistical and process-based models have successfully reproduced observed patterns of landscape-scale habitat use by
domestic and wild herbivores. When animal movements are largely unconstrained by fences or other barriers, spatial
patterns of habitat use by herbivores can often be explained using relatively simple algorithms based on forage quality,
topography, snow depth, or other factors that are, in general, relatively intuitive (Stafford Smith 1988; Turner et al.
1993; Gross et al. 2001). In arid areas, water is clearly the dominant influence on movements of domestic livestock.
The selection of habitats by domestic herbivores and large-scale patterns of defoliation and ecosystem modification can
be largely accounted for by the location of water (Andrew 1988; Hodder & Low 1978; James et al. 1999).
At an intermediate scale (500-20,000 ha), it has proved to be much more difficult to predict the spatial distribution of
grazing in many situations. It is essential to understand plant-animal interactions at this scale because it is at this scale
that fragmentation is occurring in many rangelands, at both enterprise and paddock scales. Regression models have
provided some insight to factors that can influence the spatial distribution of animals (e.g., Senft et al. 1983), but these
are highly situation-specific and they cannot be easily generalized to handle conditions outside the range of the input
data. At one level this would appear to limit the utility of simulation models. However, the wisdom of only trying to
precisely manage the spatial distribution of grazing effects, rather than manage for whole-paddock condition, should be
questioned in the highly variable environments typical of rangeland systems. At the whole-paddock scale, a variety of
models has been usefully applied to guide management (e.g., GRASP (Littleboy & McKeon 1997), SPUR (Foy et al.
1999)).
At larger scales, habitat use and feedbacks between vegetation and herbivores have been incorporated into models with
a spatial representation of the landscape. Illius & O’Connor (2000) developed a very parsimonious model that simply
represented the landscape as dry and wet season range, without inferring an explicit spatial structure, and making
various assumptions about their characteristics which mean the model deals only with one of the combinations in Table
3. Simulations were designed to address on-going controversy on livestock population controls in semi-arid rangelands,
and model results importantly showed how environmental degradation could be more likely in systems with higher
environmental variability, in contrast to widely held predictions based on more qualitative arguments (Ellis & Swift
1988; Behnke & Scoones 1992). The widespread acceptance of a conceptual model of rangeland disequilibrium, where
degradation is unlikely in highly variable systems, has had a huge impact on international development efforts, and
model results that refute this hypothesis are important to opening this debate.
Illius and O’Connor’s model epitomized the use of a very simple model for addressing an important conceptual issue.
However, their model is not suitable for simulating any particular location due to its generality and broad assumptions.
More detailed models have addressed needs to support decisions on paddock or landscape-level management of large
herbivores. At large spatial scales, simulation models have made important contributions to evaluating management of
grazing lands where competition between domestic and wild herbivores is important (Weisburg et al. 2002), and they
have been an integral component of large-scale research in pastoral landscapes (Coughenour et al. 1985). Results from
simulation models have supported the hypothesis that environmental heterogeneity has important consequences for
large herbivores (Turner et al. 1993; Boone & Hobbs 2003).
Rangeland models have thus far focused on representing the dynamics of the biophysical system, although some models
have integrated or been linked to relatively simple economic models. If the issue of intensification in arid and semi-arid
landscapes is to be properly understood then it is essential that both biophysical and socio-economic aspects are
considered (cf. Stafford Smith & Reynolds 2002, on related issues to do with degradation). In the future, decisions on
policy and high-level management recommendations will be enhanced by support from models that represent rangeland
systems as complex adaptive systems, where both the biophysical system and the institutions (people, policies,
governance structures) are coevolving. The conceptual basis of these models is still in its infancy, although early efforts
are promising and new tools provide a means for efficiently constructing integrative models (Janssen et al. 2000;
Walker & Abel 2002). To support decisions on important rangeland policies and programs, such as those that promote
or discourage intensification, we need a toolkit that provides credible insights to systems dynamics – systems that
consist of intricately linked biophysical, socio-economic and institutional components. The J-curve of Fig.1, to which
we now return, represents one conceptual example of such linkages.
OTHER SOCIO-ECONOMIC FACTORS IN THE J-CURVE INTENSIFICATION TRADEOFF
Trends towards increasing fragmentation depicted by the downwards component of the J-curve in Fig. 1 are generally
associated with privatisation in developing nations. However, these trends actually apply in any intensification process
and may simply reflect more fencing in developed nations (although historically this has also usually been associated
with the break-up of large properties into smaller units). Intensification is driven by the balance between the costs of
controlling the smaller or excised units and the benefits received from that control. Where the trend is from low-density
nomadic pastoralism to greater settlement, fragmentation is usually focused initially around water sources and better
soils for agriculture. It becomes more feasible for individuals to control these resources (Demsetz 1967, Behnke 1985)
as communal institutions break down, tenure rules change to permit privatisation, and the day-to-day costs of defending
the resource (e.g. fencing and guarding) decline as a result of technology or the availability of labour, or even changing
levels of public law enforcement. In developed nations, greater subdivision has been driven by similar political
imperatives and subsidies, but also by the declining real costs of fencing and artificial waterpoints for animal control.
The desirable extent of subdivision is determined by a balance between the production responses discussed in earlier
sections, and the economic and social issues touched on here.
The rising arm of the J-curve is presumed to apply to the residual grazing lands once the higher value land has been
effectively excised from the landscape. Obviously in agriculturally-dominated districts the residue is very small, so this
discussion is of interest primarily where only a small proportion of the landscape is thus excised. Notably, the excised
areas will invariably include critical water resources or the better soils, so their excision is likely to have a significant
effect on the capacity of the remainder of the landscape to produce. The reconsolidation of management units is again
driven by changing patterns of costs and benefits; however, it usually a phenomenon of management rather than animal
behaviour, in the sense that properties are amalgamated, but management is used to control animal movement around
the expanded area rather than the removal of fencing. Furthermore, although a single person may buy up many
properties, it is also possible to gain greater scale through commercial arrangements such as agistment, sub-leasing, and
many others that can be found among pastoralists in the Australian rangelands. Thus the tenure system, usually very
important on the downward arm, becomes less important in reconsolidation.
The forces driving ‘consolidation’ are partly economies of scale, and partly enabling managers to access a greater
diversity of landscape resources, including even, where the properties are spatially separated, climatic patterns. In a few
cases, where management is aimed at sustaining wildlife diversity through natural processes rather than achieving
maximal animal production per se, internal fences may actually be removed. In the celebrated commercial game ranch
example of Kruger National Park in South Africa, even boundary fences were removed when this trend occurred in
private ranches alongside the park. The detailed process of consolidation thus depends in part on the land use purpose,
but also on the fine-scale landscape processes described earlier. If the landscape types are such that it is more efficient
to have small paddocks, then consolidation will simply be a matter of owning more land. If the landscape processes
(and land use purposes) are such that landscape selection by herbivores is important, then fencing may actually be
removed, as in the example of game ranches, some pastoral needs and even grouse moors in Scotland. On the other
hand, if the issue is simply that of spreading climatic risk (and animals can be easily trucked between localities), then
even properties at some distance can be combined operationally. In short, that part of consolidation which is driven by
more efficient use of spatial diversity rather than simple economies of scale may be responding to a number of different
processes, themselves operating at different scales.
Why does any of this matter? In some landscape types, at least, it is around the point of greatest fragmentation that
degradation seems most likely to occur. This may be hypothesised for degradation relevant to landscape productivity
within management units or paddocks, but also at a more regional scale in terms of impacts on public values such as
biodiversity (James et al. 1999). The rationale for these assertions is that, at the point where the better landscapes are
being excised for other uses, the residual rangelands are most over-fragmented in comparison to the best cost-benefit
level of fragmentation. Given the effects of discounting on human behaviour and inevitable lags in recognising the
problems (Stafford Smith et al. 2000), yet the greatest degree of subdivision and grazing pressure on the land, the
environment is most at risk in its most fragmented state. The level of risk differs greatly between environments with
different environmental and socioeconomic contexts, but will consistently be higher at this point than at other stages in
the process.
In summary, it seems conceivable that we could move towards a complete theory of the trade-offs involved in this Jcurve of intensification and extensification, which may help explain the rate at which a socio-ecological system evolves
through the putative changes. The biophysical factors discussed in the earlier part of this paper, together with
socioeconomic drivers, may also determine how likely it is that substantial degradation may occur at different stages in
the process, and consequently whether policy mechanisms should seek to take the system evolution through these risk
points quickly.
ACKNOWLEDGEMENTS
This paper (like the symposium in which it was presented) is dedicated to the memory of Dr Jim Ellis, chief investigator
and driving force behind the US National Science Foundation Biocomplexity project known as SCALE. The authors of
this paper had many stimulating discussions with Jim Ellis over a number of years about many of the ideas and
hypotheses expressed in this paper and we are extremely grateful for the encouragement he provided in pursuing these
ideas. We all miss Jim’s intellect, drive and commitment to rangeland ecology, and his friendship.
REFERENCES
Andrew MH 1986. Use of fire for spelling monsoon tallgrass pasture grazed by cattle. Tropical Grasslands 20: 69-78.
Andrew MH 1988. Grazing impact in relation to watering points. Trends in Ecology and Evolution 3:336-339.
Ash AJ & McIvor JG 1998. How season of grazing and herbivore selectivity influence monsoon tallgrass communities of
northern Australia. Journal of Vegetation Science 9: 123-132.
Ash AJ, McIvor JG, Corfield JP & Winter WH 1995. How land condition alters plant-animal relationships in Australia's
tropical rangelands. Agriculture, Ecosystems and Environment 56:77-92.
Ash AJ & Stafford Smith DM 1996. Evaluating stocking rate impacts in rangelands: animals don't practice what we
preach. Rangelands Journal 18:216-243.
Ash AJ & Stafford Smith DM 2002. Pastoralism in tropical rangelands: seizing the opportunity to change. In:
Proceedings of the 12th Biennial Australian Rangeland Conference (Eds. Sarah Nicholson and David Wilcox) pp. 31-38.
Australian Rangeland Society, Kalgoorlie.
Bailey DW, Gross JE, Laca EA, Rittenhouse LR, Coughenour MB, Swift DM & Simms PL 1996. Mechanisms that
result in large herbivore grazing distribution patterns. Journal of Range Management 49:386-400.
Behnke RH 1985 Open-range management and property rights in pastoral Africa: a case of spontaneous range enclosure
in South Darfur, Sudan. Pastoral Development Network Paper No 25b. London: Overseas Development Institute.
Behnke RH & Scoones I 1992. Rethinking range ecology: implications for rangeland management in Africa. . World
Bank Environment Working Paper No. 53,
Behnke RH & Scoones I 1993. Rethinking range ecology: implications for rangeland management in Africa. In: Range
ecology at disequilibrium, eds.R.H. Behnke, I. Scoones and C. Kerven, pp. 1-30. Overseas Development Institute,
London, UK.
Boone RB & Hobbs NT 2003. Lines around fragments: effects of fencing on large herbivores. VI Intl IRC.
Bridge BJ, Mott JJ & Hartigan RJ 1983. The formation of degraded areas in the dry savanna woodlands of northern
Australia. Australian Journal of Soil Research 21: 91-104.
Coughenour MB 1991. Spatial components of plant-herbivore interactions in pastoral, ranching, and native ungulate
systems. Journal of Range Management 44:530-542.
Coughenour MB, Ellis JE, Swift DM, Coppock DL, Galvin K, McCabe JT & Hart TC 1985. Energy extraction and use
in a nomadic pastoral ecosystem. Science 230:619-625.
Demsetz H 1967 Toward a theory of property rights. American Economic Review 57: 347-359.
Desta S & Coppock DL 2002. Cattle population dynamics in the southern Ethiopian rangelands, 1980-97. Journal of
Range Management 55:439-451.
Ellis JE & Swift DM 1988. Stability of African pastoral ecosystems: alternate paradigms and implications for
development. Journal of Range Management 41:450-459.
Foy JK, Teague WR & Hanson JD 1999. Evaluation of the upgraded SPUR model (SPUR 2.4). Ecological Modellling
118:149-165.
Gross JE, Kneeland MC, Reed DF & Reich RM 2001. GIS-based habitat models for mountain goats. Journal of
Mammalogy 83:218-228.
Gross JE, Shipley LA, Hobbs NT, Spalinger DE & Wunder BA 1993. Functional response of herbivores in foodconcentrated patches: tests of a mechanistic model. Ecology 74:778-791.
Hart RH, Bissio J, Samuel MJ & Waggoner JW Jr 1993. Grazing systems, pasture size, and cattle grazing behavior,
distribution and gains. Journal of Range Management 46:81-87.
Hobbs NT, Gross JE, Shipley LA, Spalinger DE & Wunder BA 2003. Herbivore functional response in hetergeneous
environments: a contest among competing models. Ecology In press:
Hodder RM & Low WA 1978. Grazing distribution of free-ranging cattle at three sites in the Alice Springs District,
central Australia. Australian Rangelands Journal 1:95-105.
Homewood K & Lewis J 1987. Impact of drought on pastoral livestock in Baringo, Kenya 1983-1985. Journal of
Applied Ecology 24:615-631.
Houliston FJ, Ash AJ & Mott JJ 1996. The influence of patches on the intake and grazing behaviour of cattle in tropical
rangelands. In: Proceedings of the 9th Biennial Australian Rangeland Conference (Eds. L.P. Hunt and R. Sinclair) pp. 9596. Australian Rangeland Society, Port Augusta.
Hunt LP, Petty S, Cowley RA, Fisher A, Goody L & MacDonald N 2003. Improving grazing distribution, productivity
and land condition in extensively grazed landscapes. This volume.
Illius AW, Albon SD, Pemberton JM, Gordon IJ & Clutton-Brock TH 1995. Selection for foraging efficiency during a
population crash in Soay sheep. Journal of Animal Ecology 64:481-492.
Illius AW & O'Connor TG 1999. On the relevance of nonequilibrium concepts to arid and semiarid grazing systems.
Ecological Applications 9:798-813.
Illius AW & O'Connor TG 2000. Resource heterogeneity and ungulate population dynamics. Oikos 89:283-294.
James CD, Landsberg J & Morton SR 1999. Provision of watering points in the Australian arid zone: a review of effects
on biota. Journal of Arid Environments 41:87-121.
Janssen MA, Walker BH, Langridge J & Abel N 2000. An adaptive agent model for analysing co-evolution of
management and policies in a complex rangeland System. Ecological Modelling 131:249-268.
Laca EA, Ungar ED & Demment MW 1994. Mechanisms of handling time and intake rate of a large mammalian
grazer. Applied Animal Behaviour Science 39:3-19.
Landsberg RG, Ash AJ, Shepherd RK & McKeon GM 1998. Learning from history to survive in the future: management
evolution on Trafalgar Station, north-east Queensland. The Rangeland Journal 20: 104-118.
Lange RT 1985. Spatial distributions of stocking intensity produced by sheepflocks grazing Australian chenopod
shrublands. Transactions of the Royal Society of South Australia 109: 167-174.
Littleboy M & McKeon GM 1997. Subroutine GRASP: grass production model. In: K. A. Day, G. M. McKeon, and J.
O. Carter eds. Evaluating the risks of pasture and land degradation in native pastures in Queensland. Rural Industries
Research & Development Corporation. Final report DAQ-124A. Pages 1-69.
McIvor JG, Ash AJ & Cook GD 1995. Land condition in the tropical tallgrass pasture lands. 1. Effects on herbage
production. The Rangeland Journal 17: 69-85.
Mott JJ 1987. Patch grazing and degradation in native pastures of the tropical savannas in northern Australia. F. P.
Horn, J. Hodgson, J. J. Mott, and R. W. Brougham, eds. Grazing-lands research at the plant-animal interface. Winrock
International, Morillton, Arkansas.
Mott JJ, Ludlow MM, Richards JH & Parsons AD 1992. Effects of moisture supply in the dry season and subsequent
defoliation on persistence of the savanna grasses Themeda triandra, Heteropogon contortus and Panicum maximum.
Australian Journal of Agricultural Research 43: 241-60.
Noy-Meir I 1975. Stability of grazing systems: an application of predator-prey graphs. Journal of Ecology 63:459-481.
O'Reagain P & Bushell J 1999. Testing grazing strategies for the seasonally variable tropical savannas. 1. Pages 485486 in: D. Eldridge and D. Freudenberger, eds. People and Rangelands: Building the Future. Proceedings of the VI
International Rangeland Congress. VI International Rangeland Congress, Townsville, Australia.
Pickup G & Chewings VH 1988. Estimating the distribution of grazing and patterns of cattle movement in a large arid
zone paddock. An approach using animal distribution models and Landsat imagery. International Journal of Remote
Sensing 9, 1469-1490; 28 ref.
Pickup G & Stafford Smith DM 1993. Problems, prospects and procedures for assessing the sustainability of pastoral
land management in arid Australia . Journal of Biogeography 20:471-487.
Scoones I 1995. Exploiting heterogeneity - habitat use in cattle in dryland Zimbabwe . Journal of Arid Environments
29:221-237.
Senft RL, Coughenour MB, Bailey DW, Rittenhouse LR, Sala OE & Swift DM 1987. Large herbivore foraging and
ecological hierarchies. BioScience 37:789-799.
Senft RL, Rittenhouse LR & Woodmansee RG 1983. The use of regression models to predict spatial patterns of cattle
behavior. Journal of Range Management 26:553-557.
Spalinger DE & Hobbs NT 1992. Mechanisms of foraging in mammalian herbivores: new models of functional
response. The American Naturalist 140:325-348.
Stafford Smith DM 1988. Modeling: three approaches to predicting how herbivore impact is distributed in rangelands.
New Mexico Agricultural Experiment Station Regular Research Report, Las Cruces NM 628:1-56.
Stafford Smith DM & Reynolds JF 2002. Desertification: A new paradigm for an old problem. In: Reynolds, J.F. and
Stafford Smith, D.M. (eds.) Global Desertification: Do Humans Cause Deserts? Dahlem Workshop Report 88,
Berlin: Dahlem University Press. Pp.403-425.
Stafford Smith, M, Morton, SR. & Ash, AJ 2000. Towards sustainable pastoralism in Australia’s rangelands. Australian
Journal of Environmental Management 7(4): 190-203.
Turner MG, Wu Y, Romme WH & Wallace LL 1993. A landscape simulation model of winter foraging by large
ungulates. Ecological Modelling 69:163-184.
Ungar ED & Noy-Meir I 1988. Herbage intake in relation to availability and sward structure: grazing processes and
optimal foraging. J. Applied Ecol. 25:1045-1062.
Walker BH & Abel N 2002. Resilient rangelands - adaptation in complex systems. Pages 293-313 in: L. H. Gunderson
and C. S. Holling, eds. Panarchy: Understanding transformations in human and natural systems. Island Press,
Washington.
Walker BH, Emslie RH, Owen-Smith RN & Scholes RJ 1987. To cull or not to cull: lessons from a southern African
drought. Journal of Applied Ecology 24:381-401.
Weisberg PJ, Hobbs NT, Ellis JE & Coughenour MB 2002. An Ecosystem Approach to Population Management of
Ungulates. Journal of Environmental Management 65:181-197.
Wilmshurst JF, Fryxell JM & Hudson RJ 1995. Forage quality and patch choice by wapiti (Cervus elaphus). Behavioral
Ecology 6:209-217.