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Scale, heterogeneity and secondary production intropical rangelandsAndrew Ash , John Gross & Mark Stafford SmithPublished online: 12 Nov 2009.

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African Journal of Range & Forage Science 2004, 21(3): 137–145Printed in South Africa — All rights reserved

Copyright © NISC Pty LtdAFRICAN JOURNAL OF

RANGE & FORAGE SCIENCEISSN 1022–0119

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, Australia2 CSIRO Sustainable Ecosystems, Davies Laboratory, Private Mail Bag, Aitkenvale QLD 4814, Australia3 CSIRO Sustainable Ecosystems, Centre for Arid Zone Research, PO Box 2111, Alice Springs NT 0871, Australia* Corresponding author, e-mail: Andrew.Ash@csiro.au

Received 13 October 2003, accepted 1 September 2004

Tropical rangelands across the world are experiencing land use intensification pressures which are reducing the spatial scale ofgrazing management units. There are implications of a reduction in scale on environmental heterogeneity and its relationship withsecondary production of large herbivores, and on the consequent risks of land degradation. Rangeland managers find it hard toconceptualise these implications and there has been little research to clarify them in the past. This paper will review our currentunderstanding of scale-related effects on livestock production in tropical rangelands and herbivore-plant interactions at patch tolandscape scales. We use published information and results from recent empirical studies in northern Australia and elsewhere toelucidate scale-related effects on secondary production. These results indicate that empirical approaches alone will not provide allthe understanding necessary for better management of extensive grazing lands that are undergoing intensification and that mod-elling approaches are important in helping to understand underlying mechanisms driving observed changes. Such modellingapproaches need to encompass rangeland systems as complex, adaptive systems where socio-economic factors are just as impor-tant as biophysical understanding. We use a conceptual J-curve model to help explain how fragmentation and intensification affectsthe socio-ecological dynamics of arid and semi-arid grazing lands.

Keywords: fragmentation, grazing, intensification, plant–herbivore interactions, rangelands

Spatial scale and complexity play an important role in thefunctioning of socio-ecological systems in rangelands.Compared with many landscapes rangelands are often con-sidered to be rather homogenous, so fragmentation and itsecological implications may not be viewed as importantissues. However, rangelands are diverse, albeit through rel-atively subtle variations and gradients in soil, vegetation andclimate. Any individual landscape element may not appearto be complicated, but these individual elements are linkedand interact with each other through physical and ecologicalprocesses that form a complex ecosystem.

Land use intensification throughout the rangelands isfragmenting landscapes into simpler, discrete units. Theresult is a reduction in the scale of landscape-animal-humaninteractions. There is evidence that this reduction in com-plexity has an impact on ecosystem function and systemresilience (Behnke and Scoones 1993, Ellis and Swift 1988)which may lead to dysfunction in ecological communities,enterprise economics and social structures. This fragmenta-tion can occur regionally, in the form of altered land tenureand/or enterprise size, and within enterprises, particularly incommercial pastoral operations that seek to intensify pro-duction. At the regional scale the fragmentation process canbe 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 qualityresources (waters, grazing, cropping lands, etc). However,at some stage, the history of rangelands in developed coun-tries suggests that this process invariably reverses itself andconsolidation of land begins to occur once more (hence thecurl of the J). This consolidation phase is largely throughpurchase of additional land resources or negotiating long-term agistment (where grazing land is rented for a negotiat-ed period for an agreed number of livestock) arrangements,e.g. in northern Australia approximately 50% of pastoralholdings have more than one property (Bortolussi et al.2004). By this consolidation stage, the higher-value (usuallymost agriculturally prospective) parts of the landscape havebeen excised and the re-consolidation occurs in the residualrangelands or grazing lands. The hypothesis is that thisprocess is indeed part of the same syndrome, and not dis-junct from the descending arm of the ‘J’.

Notwithstanding some naturalistic aversion to develop-ment, it is important to realise that intensification is not nec-essarily bad in terms of net regional welfare — there arewinners and losers but, in most circumstances, it is likelythat net regional productivity can be increased by subdivid-ing the landscape and specialising the use of different land-scape elements. This is indeed the basis on which agricul-tural areas have developed throughout the world. However,

Introduction

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it is a matter of interest to understand these processesbecause we contend that the point in the trajectory at whichsystems are at greatest risk of land degradation may beclose to the bottom of the curve. If this is so, then under-standing where the endpoint of intensification is most likelyto be and facilitating the change to this point as efficiently aspossible may be an important option for managing theprocess of intensification. The factors which drive the trade-offs allowing shifts along the curve are a complex mixture ofthe production and economic benefits of fragmenting thelandscape balanced by the costs of acquiring and retainingownership rights. Once the better lands have been excised,the balance of these factors in the residual rangelandschanges again, triggering the tendency to re-consolidate. Inshort, the challenge is first to identify any marginal caseswhere continued subdivision really is not regionally benefi-cial (the trend being driven by inequitable exploitation orpolitical ideology rather than legitimate net benefits) and, forthose cases where the trend is warranted, minimise the tran-sient degradation risks.

In this paper we wish to focus on the role of spatial scaleon landscape-herbivore interactions in tropical rangelandsand the implications for system productivity and resilience.The initial emphasis will be on biophysical interactions incommercial pastoral enterprises inasmuch as these con-tribute an important parameterisation for the drivers ofchange on the J-curve, but we will then consider briefly howthese interact with the socio-economic drivers and the issueof biophysical scale in rangelands.

Tropical rangelands of northern Australia

In common with rangeland regions throughout the world, thetropical rangelands of northern Australia are characterisedby nutrient limited soils and a highly variable climate that isunsuitable for intensive agriculture. Pastoralism is the domi-nant land use, characterised by large-scale enterprises (10 000–1 000 000ha) which generally rely on low inputsand have low outputs per hectare, and which are subject touncertain markets and variable prices.

The variable climate means that it is difficult for pastoral-ists to match animal numbers to forage supply (O’Reagainand Bushell 1999) and there are episodic forage deficits andassociated concerns about land degradation. Because indi-vidual management units (paddocks) are quite large,uneven utilisation due to landscape heterogeneity and poordistribution of water is common (Ash and Stafford Smith1996).

Increasing costs of production and relatively stableprices have resulted in a cost-price squeeze and the needfor ever-increasing efficiencies in production. This continu-ous cost-price squeeze is forcing many producers to exam-ine ways of increasing productivity and returns and reducingcosts. Most properties are relatively efficient, given their cur-rent scale and resolution of operation, with limited scope todramatically reduce costs, so pastoralists are looking tointensify production to increase returns (Ash and StaffordSmith 2002). Many pastoralists have learnt from pastattempts at increasing productivity that simply increasinganimal numbers using existing infrastructure can lead toshort-term gains, but resource damage and failing econom-ics is the longer-term result (Landsberg et al. 1998). Currentattempts at increasing production are focussed on overcom-ing some of the problems of uneven grazing distribution inlarge paddocks by increasing fencing and water points andreducing paddock size. So while animal numbers areincreased it is assumed that such increases are sustainablebecause of the more even utilisation that smaller paddocksprovide. To avoid potential resource degradation problemsassociated with increasing animal numbers under this inten-sification scenario, increased management inputs arerequired in calculating carrying capacities and better man-aging interannual variability in forage supply.

When making the decision about intensifying infrastruc-ture, reducing paddock size and achieving increased carry-ing capacity, the potential benefits of larger, heterogeneouspaddocks in terms of individual animal performance areoften overlooked. Large, diverse paddocks can provide spa-tial buffering for animals during the dry season and duringdroughts (Scoones 1995) and less diverse, small paddocksmay suffer in productivity if resource rich patches are nolonger accessible (Ash and Stafford Smith 1996, Boone andHobbs 2003). There may also be an impact of intensificationon biodiversity. Increaser species are more abundant nearwater points and grazing sensitive, decreaser species mayonly be found a long way from water where grazing pressureis very light or absent (James et al. 1999). Provision of extrawater points may see further declines in grazing sensitivespecies unless off-reserve conservation areas or formalreserve areas are increased at the same time.

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Figure 1: Hypothesised process of fragmentation and reduction inscale in rangelands

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However, all of these effects are context dependent —for example, grazing impacts on preferred vegetation typesdepend greatly on whether those types are the minority ormajority of the landscape, and whether they are more of lessresilient than other components. To understand the effects ofintensification and a change in scale and heterogeneity onplant-herbivore interactions and its implications for animalproduction and pastoral management, we therefore need tounderstand the critical foraging processes and decisions atall spatial scales. The next section of this paper brieflyreviews plant-animal interactions at various scales in thecontext of management implications.

Spatial scale, plant-herbivore interactions and secondaryproduction

Foraging decisions are made at a range of spatial scalesthat can be organised in a hierarchical manner (Senft et al.1987). These spatial scales range from the bite up to thelandscape unit and each scale can be defined according tocharacteristic behaviours that also involve different timescales (Bailey et al. 1996, Table 1). We now discuss forag-ing behaviour across these spatial scales and the implica-tions of fragmentation on plant-animal interactions.

Plant part and species selectionAt the finest spatial scales, foraging decisions are made onthe basis of plant part (e.g. leaf vs stem) and plant species.In tropical rangelands, which are dominated by tussockperennial grasses, the bulk of the diet is grass though forbsand shrubs can make significant contributions to the diet(Ash et al. 1995). This selection process can lead tochanges in species composition which in turn can havefeedback effects on diet selection and forage quality. Forexample, where the abundance of perennial grasses isreduced by grazing, diet quality can improve if more forbsare made accessible (Ash et al. 1995). However, net primaryproductivity of forages can be reduced in response to over-use at this spatial scale (Ash and McIvor 1998, McIvor et al.1995).

Management does not influence plant-herbivore interac-tions significantly at this scale, except inasmuch as changesof total grazing numbers and distribution resulting from man-

agement changes at the whole paddock scale have an indi-rect effect on specific locations. Fragmentation of land-scapes has relatively little impact on foraging decisions atthis spatial scale.

Patch scale grazingA distinctive feature of tussock dominated grasslands typicalof tropical rangelands is patch grazing (Mott 1987), specifi-cally defined as differentially patterned grazing in otherwisehomogenous vegetation. Because of repeated grazing ofpatches once they are established, patch grazing can leadto localised degradation (Bridge et al. 1983). The formationof patches can have benefits for animal production with theintake and diet quality of animals that have access to shortpatches being higher than that of animals grazing a morehomogenous sward (Houliston et al. 1996, Table 2,Wilmshurst et al. 1995).

Does intensification of pastoral management have animpact on plant-herbivore interactions at the patch scale? Aspastoral management intensifies there is scope for morehigh intensity grazing systems such as cell grazing or shortduration grazing where large numbers of animals are usedto intensively graze a small paddock and the paddock isthen rested for some weeks or months. This has the poten-tial to overcome patch grazing and although there is muchanecdotal evidence that more intensive grazing systemsachieve more uniform grazing distribution, experimental evi-dence has proved elusive (Hart et al. 1993). Fire has beenused successfully to overcome patch grazing in tropical tall-grass communities (Andrew 1986) through a simple burningregime where each half of a paddock is burnt in alternativeyears. Fires tend to reset the system such that animals donot revisit old patches in recently burnt country. Such a fireregime is only practical in more intensively managed land-scapes where there is good control of fire.

Landscape foraging processesIt is foraging decisions in landscapes that will be mostaffected by fragmentation and intensification in pastoralmanagement so it is important that there is a good under-standing of plant–herbivore interactions at this scale andtheir effect on animal production. It is well known that ani-mals use landscapes unevenly, with respect to either dis-

African Journal of Range & Forage Science 2004, 21: 137–145

Table 1: Spatial scale of forage and site selection in rangelands, and potential effects of fragmentation at each scale (modified from Bailey etal. 1996)

Space and time scaleBite: 1–2 seconds

Patch: 1–30 minutes

Feeding site: 1–4 hours

Camp: 1–4 weeks

Seasonal range: monthto years

Selection criteriaNutrient concentration, biomass density, toxins, bite concentrationForage species, forage abundance, topography

Topography, plant community, soil type, forage abun-dance, phenologyWater availability, topography, forage abundance, ther-moregulation, plant phenology, predation, competitionWater availability, forage quality and quantity, ther-moregulation, predation, competition

Effect of fragmentationNone

None to some impact. May limit management options(e.g. burning); may affect patch structure by facilitatingintensive management (e.g. reducing patch structurevia short-term, intensive grazing).None to large. Restrict access to landscape compo-nents, habitats or preferred areas.Potentially large effect if at appropriate scale. Restrictedmovements and access to landscape elements.Almost certainly large. Fragmentation may prohibitmigration, dispersal or transhumance.

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tance to water or herbivore preferences for different vegeta-tion communities (Senft et al. 1983, Lange 1985, StaffordSmith 1988, Pickup and Chewings 1988). It is usually themore fertile parts of the landscape (riparian areas, fertile claysoils) that are the focus of much of the grazing pressure(Scoones 1995, Ash et al. 1995). These key resource areascan buffer animal production by providing greater dietarydiversity or by providing key resources during drought peri-ods. These key resource areas may also be quite resilientand hence be the last part of the landscape to lose produc-tivity (Scoones 1993).

While spatial selection may be able to buffer animal pro-duction it can also promote further degradation if animalsalways focus on the same fertile pockets in the landscape(Pickup and Stafford Smith 1993). Even if these fertile patch-es are more resilient, continual use could eventually lead totheir collapse and a marked decline in animal productionfrom the landscape. If animal density is not controlled byaltering stock numbers in managed pastoral operations or bynatural die-offs with wild herbivores, then key resourcepatches need to be strategically rested so that they do notbecome degraded. Illius and O’Connor (1999) argue thatwhen animals depend on these key resources and they rep-resent only a small portion of the landscape, their populationwill be small, which reduces the risk of degradation. In con-trast, larger areas of key resources can support a large ani-mal population which brings with it a greater risk of degra-dation. Overutilisation of these favoured areas can havenegative feedback effects on forage productivity (Mott et al.1992, Ash and McIvor 1998) and land condition. As morefavoured areas lose productivity and their capacity to sup-port animals, grazing activity is shifted to the next preferredareas and a cycle of sequential degradation across the land-scape may result. This phenomenon is one of the main rea-sons that recommendations on fencing according to landtype have been promoted in commercial rangelands.

Grazing patterns in large, heterogeneous landscapescan have both positive and negative implications for animalproduction. The existence of key resource areas in largelandscape-scale paddocks can help buffer animal productiv-ity during extended dry seasons and droughts (Scoones1995, Illius and O’Connor 1999). Studies of African grazingsystems have consistently identified the importance of large-scale movements to sustaining both domestic and wild her-bivores during droughts (Homewood and Lewis 1987,Walker et al. 1987, Coughenour et al. 1985). Analysis of

mortality patterns has shown that despite a high annual vari-ation in precipitation and plant production, mortality is relat-ed to both animal density and to access to variability in avail-able grazing areas (Homewood and Lewis 1987, Desta andCoppock 2002, Walker et al. 1987). These empirical resultsare supported by recent efforts to simulate broad-scaledynamics of plant-herbivore systems, and they emphasisethe dangers of fragmenting highly variable systems (Illiusand O’Connor 1999, 2000). Anecdotally, pastoralists in blackclay landscapes of northern Australia prefer a mix of heavyclay country and lighter red soils for animal productionbecause of the different forage growth responses to rainfallon these two soils (Ash and Stafford Smith 1996). However,animal performance in large paddocks may suffer wherethere is poor water distribution. Hart et al. (1993) demon-strated this in temperate rangelands where the liveweightgain of cattle grazing a large paddock with water at one endof the paddock was significantly inferior to that of cattle graz-ing smaller paddocks where distance to water was1.0–1.6km.

Clearly, intensification of grazing can have a major effecton plant-herbivore interactions and animal production. Formost pastoral enterprises intensification is not just aboutincreased infrastructure in the form of fences and/or waterpoints to improve grazing distribution, but also usuallyincludes decisions on stocking rate and carrying capacity. Itis therefore important to look at the interaction of spatialscale and stocking rate when considering animal productionin fragmented landscapes. At small spatial scales a lineardecline in animal performance with increasing stocking ratehas been clearly demonstrated in rangelands (Ash andStafford Smith 1996). However, it is unclear whether thisrelationship can be extrapolated to landscape scale pad-docks. If spatial buffering is occurring in heterogeneouspaddocks then the stocking rate–animal performance rela-tionship may not be a linear decline. We hypothesise thatanimal performance per head may decline slowly withincreasing stocking rate until a critical threshold is reached,such as the depletion of key pockets of fertility, which is thenfollowed by a rapid decline in animal performance (Figure 2).There is remarkably little empirical evidence to support thishypothesis. One grazing trial in northern Australia investi-gating stocking rate impacts on animal performance doeshave paddocks that are reasonably large (400–1 200ha) andin this study there has been very little effect of stocking rateon individual animal performance (N MacDonald pers.comm., Figure 3). A cautionary note in interpreting theseresults is that it is a single study and the majority of the yearsin the experimental study were well above average in termsof rainfall and pasture growth. In a smaller grazing trialwhere paddocks were 100ha in size but where there was amixture of soil types the animal production per head at ahigh stocking rate was consistently lower than at a lowerstocking rate (O’Reagain and Bushell 2003). It is not clearwhether this indicates a lack of spatial buffering as the highstocking rate was twice that of the low stocking rate and mayhave represented the two ends of the stocking rate–animalproduction relationship i.e. spatial buffering is most likely tobe evident at intermediate stocking rates. It is clear from ananalysis of a large number of small spatial scale stocking

Ash, Gross and Stafford Smith

Table 2: Effect of mown patches (5 patches per paddock, totalpatch area 16% of paddock) on diet quality, feed intake and forag-ing behaviour of cattle grazing tropical tallgrass pasture atLansdown, near Townsville (Houliston et al. 1996). Mown plots werecut to about 10cm to allow regrowth which simulated a grazed patch

Unmown PatchyDietary nitrogen (%) 1.49 1.59Dietary dry matter digestibility (%) 49.40 52.50Dry matter intake (kg head–1 day–1) 8.50 9.05Grazing time in patches (%) 19.00 28.00

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rate studies in rangelands that there is on average a20–25% decline in animal performance with a doubling instocking rate (Ash and Stafford Smith 1996).

If there is a significant difference in the nature of thesestocking rates–animal performance relationships at differentspatial scales then it is important to take this into account inthe context of landscape intensification. For example, small-er spatially homogenous paddocks may provide the oppor-tunity to increase stock numbers because of better waterdistribution. Hart et al. (1993) found individual animal per-formance may be improved by modifying cattle distributionsto prevent over-utilisation of areas close to water and under-utilisation of areas distant from water. However, there maybe a trade-off in the performance of individual animals if areduction in paddock size is accompanied by a reduction inlandscape and dietary diversity. This context-specific issuehas not been adequately addressed in the rangelands and ithas important implications for rangeland management. Forexample, is it possible to achieve the benefits of more evenutilisation provided by increased water points and also thepotential benefits of increased dietary diversity provided bylarge heterogeneous paddocks by increasing water points inlarge paddocks rather than sub-dividing them? This can alsohave benefits for pastoral management in reducing fencingcosts, which is a major expense in any intensification ofrangeland enterprises.

The effects of scale on plant-herbivore interactions andthe most appropriate management response will be verymuch dependent on how synchronous or asynchronous for-age production and quality is between landscape elements,as well as the resilience or susceptibility to herbivory of dif-ferent vegetation units (Ash and Stafford Smith 1996). Theseinteractions and their management implications can beexpressed in a simple matrix (Table 3) which in effect pro-vides some simple rules of thumb for incorporating into deci-sions on intensification.

To address these issues of how spatial scale and inten-sification (water points, paddock size and heterogeneity) areinteracting with plant-animal relationships, two new fieldstudies in northern Australia have commenced (Hunt et al.2003, Stokes et al. 2004) that should provide empirical datato support or reject the hypotheses raised in this sectionrelating to increasing spatial scale providing dietary diversi-ty and buffering. One study (Hunt et al. 2003) is a formalmanipulative experiment that is examining the interactionbetween spatial scale and animal performance in commer-cial paddocks of a pastoral operation. The study involvessome 40 000ha of land and 5 000 head of cattle. The sec-ond study (Stokes et al. 2004) is looking at variability inlandscape complexity and paddock scale across pastoralproperties in a region to explore relationships between ani-mal diet quality and landscape characteristics.

Given the complexity of plant-animal interactions at thelandscape scale, experimental or experiential evidence mayidentify patterns, but the identification of common patterns,by itself, is unlikely to advance our understanding of theunderlying mechanisms driving the observed changes.Development and application of rangeland systems modelsis thus likely to be a necessary component in the evaluationof conceptual models, as hypotheses, of how these systemsoperate and how various forms of fragmentation and/orintensification will influence their dynamics, including pro-ductivity, resilience, and sustainability. The next section ofthis paper examines how we can use modelling to comple-ment our incomplete process understanding of plant-animalinteractions to address issues of fragmentation and intensi-fication.

Modelling plant-animal interactions in complex land-scapes

An understanding of plant–animal interactions is a key foun-

African Journal of Range & Forage Science 2004, 21: 137–145

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cal savanna environment in northern Australia where paddock sizesranged from 400–1 200ha. Based on unpublished data of NeilMacDonald, Northern Territory Department of Business, Industryand Development, Katherine, NT

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dation for constructing models of rangeland systems thatincorporate spatial heterogeneity and begin to address theissue of fragmentation and how it affects landscape use andanimal productivity. As stated earlier, herbivores respond toheterogeneity at scales from individual bites to major land-scapes components, such as vegetation types, major topo-graphic features, or microclimates (Senft et al. 1983,Coughenour 1991, Bailey et al. 1996), and there are impor-tant feedbacks between consumers and producers at allscales. So has the development of models proceeded farenough to offer any insights into landscape scale plant-ani-mal interactions in relationship to fragmentation? To answerthis question we need to explore model development and itsapplication across all spatial scales.

Most studies of plant-animal dynamics in rangelandshave been at smaller scales, and we now have a firm under-standing of processes that regulate short-term intake rate ofherbivores (Laca et al. 1994, Spalinger and Hobbs 1992,Ungar and Noy-Meir 1988) and experimental data that sup-port process-based models across a broad range of herbi-vore species (Gross et al. 1993). These studies have pro-vided a direct link between the mechanics of feeding and theresponse in intake rate, and this mechanistic link permits thebroad application of these models across plant types, feed-ing habits and body sizes. Insights from the development offine-scale, mechanistic models have been key to under-standing system dynamics of species that are tightly coupledto relatively homogeneous food resources at small spatialscales (e.g. Illius et al. 1995) and for predicting gain func-tions of animals in intensively grazed grasslands (usually intemperate environments). They appear to be far less appli-cable to, for example, tropical systems where there isextreme heterogeneity in the structure, quality and quantityof forages on offer within a paddock or feeding area. In thissituation, trade-offs between quality and intake rate greatlycomplicate diet selection, and our ability to predict eitherintake rate or gain is limited.

The major challenge to extrapolating small-scaleprocesses to the larger scales more relevant to extensive

grazing systems and the issues of fragmentation is the largeeffect of animal behaviour. Mechanistic models can accu-rately predict intake rates of hungry animals over small spa-tial and temporal scales, but selectivity, movement patterns,social interactions, memory, and environmental factorsclearly influence the spatial distribution of herbivores andtheir subsequent use of forages at paddock and landscapescales (Senft et al. 1987, Coughenour 1991, Bailey et al.1996). At the largest scales, both statistical and process-based models have successfully reproduced observed pat-terns of landscape-scale habitat use by domestic and wildherbivores. When animal movements are largely uncon-strained by fences or other barriers, spatial patterns of habi-tat use by herbivores can often be explained using relative-ly simple algorithms based on forage quality, topography,snow depth, or other factors that are, in general, relativelyintuitive (Stafford Smith 1988, Turner et al. 1993, Gross et al.2001). In arid areas, water is clearly the dominant influenceon movements of domestic livestock. The selection of habi-tats by domestic herbivores and large-scale patterns of defo-liation and ecosystem modification can be largely accountedfor by the location of water (Andrew 1988, Hodder and Low1978, James et al. 1999).

At an intermediate scale (500–20 000ha), it has provedto be much more difficult to predict the spatial distribution ofgrazing in many situations. It is essential to understandplant–animal interactions at this scale because it is at thisscale that fragmentation is occurring in many rangelands, atboth enterprise and paddock scales. Regression modelshave provided some insight to factors that can influence thespatial distribution of animals (e.g. Senft et al. 1983), butthese are highly situation-specific and they cannot be easilygeneralised to handle conditions outside the range of theinput data. At one level this would appear to limit the utility ofsimulation models. However, the wisdom of only trying toprecisely manage the spatial distribution of grazing effects,rather than manage for whole-paddock condition, should bequestioned in the highly variable environments typical ofrangeland systems. At the whole-paddock scale, a variety of

Table 3: Relationships between forage production and quality at the landscape scale and likely implications of fragmentation for productionand management (after Ash and Stafford Smith 1996)

Forage growthand quality bet-ween landscapeelementsAsynchronous

Asynchronous

Synchronous

Synchronous

P r e f e r r e dvegetationunits

Resilient

Susceptible

Resilient

Susceptible

Effects of fragmentation

Potential loss of animal productivity because heterogeneitycannot be exploited.Loss of heterogeneity may be deleterious for animal pro-duction but, because parts of the landscape are suscep-tible, subdivision may make it easier to manage degrada-tion risk.Fragmentation has little effect on animal production ormanagement — these landscapes are already likely to besmaller scale in both size of enterprise and paddock size.Fragmentation has little effect on animal production andin fact maybe desirable from a management perspectiveso degradation-prone landscape elements can receivemore focussed management.

Impact on animal production and vegetation

Enhanced animal production, vegetationstable through time.Enhanced animal production but preferredareas at significant risk of degradation.

Little production advantage in trying to exploitdiversity, vegetation stable through time.

Little production advantage in trying to exploitdiversity, preferred areas at risk of degrada-tion.

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models has been usefully applied to guide management(e.g. GRASP (Littleboy and McKeon 1997), SPUR (Foy etal. 1999)).

At larger scales, habitat use and feedbacks betweenvegetation and herbivores have been incorporated into mod-els with a spatial representation of the landscape. Illius andO’Connor (2000) developed a very parsimonious model thatsimply represented the landscape as dry and wet seasonrange, without inferring an explicit spatial structure, andmaking various assumptions about their characteristicswhich mean the model deals only with one of the combina-tions in Table 3. Simulations were designed to address on-going controversy on livestock population controls in semi-arid rangelands, and model results importantly showed howenvironmental degradation could be more likely in systemswith higher environmental variability, in contrast to widelyheld predictions based on more qualitative arguments (Ellisand Swift 1988, Behnke and Scoones 1992). The wide-spread acceptance of a conceptual model of rangeland dis-equilibrium, where degradation is unlikely in highly variablesystems, has had a huge impact on international develop-ment efforts, and model results that refute this hypothesisare important to opening this debate.

Illius and O’Connor’s model epitomised the use of a verysimple model for addressing an important conceptual issue.However, their model is not suitable for simulating any par-ticular location due to its generality and broad assumptions.More detailed models have addressed needs to supportdecisions on paddock or landscape-level management oflarge herbivores. At large spatial scales, simulation modelshave made important contributions to evaluating manage-ment of grazing lands where competition between domesticand wild herbivores is important (Weisburg et al. 2002), andthey have been an integral component of large-scaleresearch in pastoral landscapes (Coughenour et al. 1985).Results from simulation models have supported the hypoth-esis that environmental heterogeneity has important conse-quences for large herbivores (Turner et al. 1993, Boone andHobbs 2003).

Rangeland models have thus far focused on represent-ing the dynamics of the biophysical system, although somemodels have integrated or been linked to relatively simpleeconomic models. If the issue of intensification in arid andsemi-arid landscapes is to be properly understood then it isessential that both biophysical and socio-economic aspectsare considered (cf. Stafford Smith and Reynolds 2002, onrelated issues to do with degradation). The conceptual basisof these models is still in its infancy, although early effortsare promising and new tools provide a means for efficientlyconstructing integrative models (Janssen et al. 2000, Walkerand Abel 2002). To support decisions on important range-land policies and programmes, such as those that promoteor discourage intensification, we need integrated approach-es that provide credible insights to systems dynamics —systems that consist of intricately linked biophysical, socio-economic and institutional components. The J-curve ofFigure 1, to which we now return, represents one conceptu-al example of such linkages.

Other socio-economic factors in the J-curve intensifica-tion trade-off

Trends towards increasing fragmentation depicted by thedownwards component of the J-curve in Figure 1 are gener-ally associated with privatisation in developing nations.However, these trends actually apply in any intensificationprocess and may simply reflect more fencing in developednations (although historically this has also usually beenassociated with the break-up of large properties into smallerunits). Intensification is driven by the balance between thecosts of controlling the smaller or excised units and the ben-efits received from that control. Where the trend is from low-density nomadic pastoralism to greater settlement, fragmen-tation is usually focused initially around water sources andbetter soils for agriculture. It becomes more feasible for indi-viduals to control these resources (Demsetz 1967, Behnke1985) as communal institutions break down, tenure ruleschange to permit privatisation, and the day-to-day costs ofdefending the resource (e.g. fencing and guarding) declineas a result of technology or the availability of labour, or evenchanging levels of public law enforcement. In developednations, greater subdivision has been driven by similar polit-ical imperatives and subsidies, but also by the declining realcosts of fencing and artificial waterpoints for animal control.The desirable extent of subdivision is determined by a bal-ance between the production responses discussed in earliersections, and the economic and social issues touched onhere.

The rising arm of the J-curve is presumed to apply to theresidual grazing lands once the higher value land has beeneffectively excised from the landscape. The reconsolidationof management units is again driven by changing patterns ofcosts and benefits; however, it is usually a phenomenon ofmanagement rather than animal behaviour, in the sense thatindividual holdings are amalgamated, which provides a larg-er area in which to manage animals and production. Quiteoften these amalgamated holdings are spatially separatedby tens to hundreds of kilometres, which means the processof defragmenting landscapes is therefore not throughremoval of fences and increasing the spatial scale of theindividual management unit. Furthermore, although a singleperson may buy up many properties, it is also possible togain greater scale through commercial arrangements suchas agistment, sub-leasing, and many others that can befound among pastoralists in the Australian rangelands. Thusthe tenure system, usually very important on the downwardarm, becomes less important in reconsolidation.

The forces driving ‘consolidation’ are partly economies ofscale, and partly enabling managers to access a greaterdiversity of landscape resources, including even, where theproperties are spatially separated, climatic patterns. In a fewcases, where management is aimed at sustaining wildlifediversity through natural processes rather than achievingmaximal animal production per se, internal fences may actu-ally be removed. In the celebrated commercial game ranchexample of Kruger National Park in South Africa, evenboundary fences were removed when this trend occurred inprivate ranches alongside the park. The detailed process ofconsolidation thus depends in part on the land use purpose,

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but also on the fine-scale landscape processes describedearlier. If the landscape types are such that it is more effi-cient to have small paddocks, then consolidation will simplybe a matter of owning more land. If the landscape process-es (and land use purposes) are such that landscape selec-tion by herbivores is important, then fencing may actually beremoved, as in the example of game ranches, some pastoralneeds and even grouse moors in Scotland. On the otherhand, if the issue is simply that of spreading climatic risk(and animals can be easily trucked between localities), theneven properties at some distance can be combined opera-tionally. In short, that part of consolidation which is driven bymore efficient use of spatial diversity rather than simpleeconomies of scale may be responding to a number of dif-ferent 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 thatdegradation seems most likely to occur. This may be hypoth-esised for degradation relevant to landscape productivitywithin management units or paddocks, but also at a moreregional scale in terms of impacts on public values such asbiodiversity (James et al. 1999). The rationale for theseassertions is that, at the point where the better landscapesare being excised for other uses, the residual rangelandsare most over-fragmented in comparison to the best cost-benefit level of fragmentation. There are inevitable lags inrecognising the over-fragmentation, and the effect of dis-counting the future on human behaviour means that theremay often be undue grazing pressure on the land (StaffordSmith et al. 2000), thus putting the environment particularlyat risk in this most fragmented state. The level of risk differsgreatly between environments with different environmentaland socioeconomic contexts, but will consistently be higherat this point than at other stages in the process.

In summary, it seems conceivable that we could movetowards a complete theory of the trade-offs involved in thisJ-curve of intensification and extensification, which may helpexplain the rate at which a socio-ecological system evolvesthrough the putative changes. The biophysical factors dis-cussed in the earlier part of this paper, together with socioe-conomic drivers, may also determine how likely it is that sub-stantial degradation may occur at different stages in theprocess, and consequently whether policy mechanismsshould seek to take the system evolution through these riskpoints quickly.

Acknowledgements — This paper (like the symposium in which itwas presented) is dedicated to the memory of Dr Jim Ellis, chiefinvestigator and driving force behind the US National ScienceFoundation Biocomplexity project known as SCALE. The authors ofthis paper had many stimulating discussions with Jim Ellis over anumber of years about many of the ideas and hypothesesexpressed in this paper and we are extremely grateful for theencouragement he provided in pursuing these ideas. We all missJim’s intellect, drive and commitment to rangeland ecology, and hisfriendship.

References

Andrew MH 1986. Use of fire for spelling monsoon tallgrass pasturegrazed 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 and McIvor JG 1998. How season of grazing and herbivoreselectivity influence monsoon tallgrass communities of northernAustralia. Journal of Vegetation Science 9: 123–132.

Ash AJ, McIvor JG, Corfield JP and Winter WH 1995. How land con-dition alters plant-animal relationships in Australia’s tropicalrangelands. Agriculture, Ecosystems and Environment 56:77–92.

Ash AJ and Stafford Smith DM 1996. Evaluating stocking rateimpacts in rangelands: animals don’t practice what we preach.Rangelands Journal 18: 216–243.

Ash AJ and Stafford Smith DM 2002. Pastoralism in tropical range-lands: seizing the opportunity to change. Proceedings of the 12th

Biennial Australian Rangeland Conference, Australian RangelandSociety, Kalgoorlie. pp 31–38.

Bailey DW, Gross JE, Laca EA, Rittenhouse LR, Coughenour MB,Swift DM and Simms PL 1996. Mechanisms that result in largeherbivore grazing distribution patterns. Journal of RangeManagement 49: 386–400.

Behnke RH 1985 Open-range management and property rights inpastoral Africa: a case of spontaneous range enclosure in SouthDarfur, Sudan. Pastoral Development Network Paper No. 25b.Overseas Development Institute, London.

Behnke RH and Scoones I 1992. Rethinking range ecology: impli-cations for rangeland management in Africa. World BankEnvironment Working Paper No. 53.

Behnke RH and Scoones I 1993. Rethinking range ecology: impli-cations for rangeland management in Africa. In: RH Behnke, IScoones and C Kerven (eds) Range Ecology at Disequilibrium.Overseas Development Institute, London, UK. pp 1–30.

Boone RB and Hobbs NT 2003. Lines around fragments: effects offencing on large herbivores. VIth International RangelandCongress, Townsville, Australia.

Bortolussi G, McIvor JG, Hodgkinson JJ, Coffey SG and Holmes CR2004. The northern Australian beef industry, a snapshot: 1.Regional enterprise activity and structure. Australian Journal ofExperimental Agriculture 44 (in press).

Bridge BJ, Mott JJ and Hartigan RJ 1983. The formation of degrad-ed 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 inter-actions 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 and Hart TC 1985. Energy extraction and use in anomadic pastoral ecosystem. Science 230: 619–625.

Demsetz H 1967. Toward a theory of property rights. AmericanEconomic Review 57: 347–359.

Desta S and Coppock DL 2002. Cattle population dynamics in thesouthern Ethiopian rangelands, 1980–97. Journal of RangeManagement 55: 439–451.

Ellis JE and Swift DM 1988. Stability of African pastoral ecosystems:alternate paradigms and implications for development. Journal ofRange Management 41: 450–459.

Foy JK, Teague WR and Hanson JD 1999. Evaluation of theupgraded SPUR model (SPUR 2.4). Ecological Modellling 118:149–165.

Gross JE, Kneeland MC, Reed DF and Reich RM 2001. GIS-basedhabitat models for mountain goats. Journal of Mammalogy 83:218–228.

Gross JE, Shipley LA, Hobbs NT, Spalinger DE and Wunder BA1993. Functional response of herbivores in food-concentratedpatches: tests of a mechanistic model. Ecology 74: 778–791.

Hart RH, Bissio J, Samuel MJ and Waggoner JW Jr 1993. Grazingsystems, pasture size, and cattle grazing behavior, distribution

Dow

nloa

ded

by [

Tuf

ts U

nive

rsity

] at

09:

35 1

0 O

ctob

er 2

014

African Journal of Range & Forage Science 2004, 21: 137–145 145

and gains. Journal of Range Management 46: 81–87.Hodder RM and 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 and Lewis J 1987. Impact of drought on pastoral live-stock in Baringo, Kenya 1983–1985. Journal of Applied Ecology24: 615–631.

Houliston FJ, Ash AJ and Mott JJ 1996. The influence of patches onthe intake and grazing behaviour of cattle in tropical rangelands.Proceedings of the 9th Biennial Australian Rangeland Conference,Australian Rangeland Society, Port Augusta. pp 95–96.

Hunt LP, Petty S, Cowley RA, Fisher A, Goody L and MacDonald N2003. Improving grazing distribution, productivity and land condi-tion in extensively grazed landscapes. Proceedings of the VIIth

International Rangeland Congress, Durban, South Africa. pp876–878.

Illius AW, Albon SD, Pemberton JM, Gordon IJ and Clutton-BrockTH 1995. Selection for foraging efficiency during a populationcrash in Soay sheep. Journal of Animal Ecology 64: 481–492.

Illius AW and O’Connor TG 1999. On the relevance of nonequilibri-um concepts to arid and semiarid grazing systems. EcologicalApplications 9: 798–813.

Illius AW and O’Connor TG 2000. Resource heterogeneity andungulate population dynamics. Oikos 89: 283–294.

James CD, Landsberg J and Morton SR 1999. Provision of water-ing 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 and Abel N 2000. An adaptiveagent model for analysing co-evolution of management and poli-cies in a complex rangeland System. Ecological Modelling 131:249–268.

Laca EA, Ungar ED and Demment MW 1994. Mechanisms of han-dling time and intake rate of a large mammalian grazer. AppliedAnimal Behaviour Science 39: 3–19.

Landsberg RG, Ash AJ, Shepherd RK and McKeon GM 1998.Learning from history to survive in the future: management evo-lution on Trafalgar Station, north-east Queensland. TheRangeland Journal 20: 104–118.

Lange RT 1985. Spatial distributions of stocking intensity producedby sheepflocks grazing Australian chenopod shrublands.Transactions of the Royal Society of South Australia 109:167–174.

Littleboy M and McKeon GM 1997. Subroutine GRASP: grass pro-duction model. In: Day KA, McKeon GM and Carter JO (eds)Evaluating the Risks of Pasture and Land Degradation in NativePastures in Queensland. Rural Industries Research andDevelopment Corporation, Final report DAQ-124A. pp 1–69.

McIvor JG, Ash AJ and Cook GD 1995. Land condition in the tropi-cal tallgrass pasture lands. 1. Effects on herbage production. TheRangeland Journal 17: 69–85.

Mott JJ 1987. Patch grazing and degradation in native pastures ofthe tropical savannas in northern Australia. In: Horn FP, HodgsonJ, Mott JJ and Brougham RD (eds) Grazing-lands Research atthe Plant–Animal Interface. Winrock International, Morillton,Arkansas. pp 153–161

Mott JJ, Ludlow MM, Richards JH and Parsons AD 1992. Effects ofmoisture supply in the dry season and subsequent defoliation onpersistence of the savanna grasses Themeda triandra,Heteropogon contortus and Panicum maximum. AustralianJournal of Agricultural Research 43: 241–260.

O’Reagain P and Bushell J 1999. Testing grazing strategies for theseasonally variable tropical savannas. 1. In: Eldridge D andFreudenberger D (eds) People and Rangelands: Building theFuture. Proceedings of the VIth International RangelandCongress, Townsville, Australia. pp 485–486.

O’Reagain PJ and Bushell JJ 2003. Effect of grazing strategy onanimal production in a seasonably variable tropical savanna.Proceedings of the VIIth International Rangeland Congress,Durban, South Africa. pp 913–915.

Pickup G and Chewings VH 1988. Estimating the distribution ofgrazing and patterns of cattle movement in a large arid zone pad-dock. An approach using animal distribution models and Landsatimagery. International Journal of Remote Sensing 9: 1469–1490.

Pickup G and Stafford Smith DM 1993. Problems, prospects andprocedures for assessing the sustainability of pastoral land man-agement in arid Australia. Journal of Biogeography 20: 471–487.

Scoones I 1993. Why are there so many animals? Cattle populationdynamics in the communal areas of Zimbabwe. In: Behnke RH,Scoones I and Kerven C (eds) Range Ecology at Disequilibrium.Overseas Development Institute, London, UK. pp 62–67.

Scoones I 1995. Exploiting heterogeneity — habitat use in cattle indryland Zimbabwe. Journal of Arid Environments 29: 221–237.

Senft RL, Coughenour MB, Bailey DW, Rittenhouse LR, Sala OEand Swift DM 1987. Large herbivore foraging and ecological hier-archies. BioScience 37: 789–799.

Senft RL, Rittenhouse LR and Woodmansee RG 1983. The use ofregression models to predict spatial patterns of cattle behavior.Journal of Range Management 26: 553–557.

Spalinger DE and Hobbs NT 1992. Mechanisms of foraging in mam-malian herbivores: new models of functional response. TheAmerican Naturalist 140: 325–348.

Stafford Smith DM 1988. Modeling: three approaches to predictinghow herbivore impact is distributed in rangelands. New MexicoAgricultural Experiment Station Regular Research Report, LasCruces, NM 628: 1–56.

Stafford Smith DM and Reynolds JF 2002. Desertification: A newparadigm for an old problem. In: Reynolds JF and Stafford SmithDM (eds) Global Desertification: Do Humans Cause Deserts?Dahlem Workshop Report 88, Dahlem University Press, Berlin.pp 403–425.

Stafford Smith M, Morton SR and Ash AJ 2000. Towards sustainablepastoralism in Australia’s rangelands. Australian Journal ofEnvironmental Management 7(4): 190–203.

Stokes CJ, Ash AJ and McAllister RRJ 2004. Fragmentation ofAustralian rangelands: Risk and trade-offs for land management.In: Bastin G, Walsh D and Nicolson S (eds) Proceedings of the13th Biennial Conference of the Australian Rangelands Society,Alice Springs, Australian Rangelands Society. pp 39–48.

Turner MG, Wu Y, Romme WH and Wallace LL 1993. A landscapesimulation model of winter foraging by large ungulates. EcologicalModelling 69: 163–184.

Ungar ED and Noy-Meir I 1988. Herbage intake in relation to avail-ability and sward structure: grazing processes and optimal forag-ing. Journal of Applied Ecology 25: 1045–1062.

Walker BH and Abel N 2002. Resilient rangelands — adaptation incomplex systems. In: Gunderson LH and Holling CS (eds)Panarchy: Understanding Transformations in Human and NaturalSystems. Island Press, Washington. pp 293–313.

Walker BH, Emslie RH, Owen-Smith RN and Scholes RJ 1987. Tocull or not to cull: lessons from a southern African drought.Journal of Applied Ecology 24: 381–401.

Weisberg PJ, Hobbs NT, Ellis JE and Coughenour MB 2002. Anecosystem approach to population management of ungulates.Journal of Environmental Management 65: 181–197.

Wilmshurst JF, Fryxell JM and Hudson RJ 1995. Forage quality andpatch choice by wapiti (Cervus elaphus). Behavioral Ecology 6:209–217.

Dow

nloa

ded

by [

Tuf

ts U

nive

rsity

] at

09:

35 1

0 O

ctob

er 2

014