Chapter 7

Livestock Production

R.K. Heitschmidt and C.A. Taylor, Jr.






Home Page


Contents

Introduction

Concepts and Terminology

General Principles
        -    Number of Animals
        -    Kinds and Classes of Animals
        -    Spatial Distribution of Animals
        -    Temporal Distribution of Animals

Grazing Systems
        -    Concepts and Terminology
        -    Effects on Livestock Production

Conclusions

List of Figures


Introduction

Level of livestock production on a given site is an integrated measure of energy capture, harvest, and conversion efficiencies (see Chapter 1). The principle factor affecting these efficiencies, and therefore livestock production, is grazing intensity which varies as a function of the:

1. temporal and
2. spatial distribution of various
3. kinds/classes and
4. number of livestock.


The objective of this chapter is to examine the relative effect of each of these four factors on livestock production.

top
Concepts and Terminology

Livestock production is a dynamic process varying as a function of both plant and animal factors. The use of several closely related, often confusing terms is required to conceptualize and/or quantitatively describe the effects of these factors on livestock production (Booysen 1967; Hodgson 1979; Scarnecchia and Kothmann 1982; Soc. Range Manage. 1989). For the purposes of this chapter we use the following specific definitions:

Forage available (FA) is any herbage and/or browse available for grazing.
Forage demand (FD) is the amount of any specified forage required to meet
    the nutrient requirements of an animal over a specified period of time.
Grazing pressure (GP) is the ratio of FD to FA for any specified forage at any instant (i.e., FD/FA).
Stocking density (SD) is the number of specified animals/unit area of land at any instant.
Animal-unit (AU) is any specified combination of animals with a total FD of 12 kg of dry matter/day.
Stocking rate (SR) is the number of animals of a specified class or animal units/unit area of land over a specified period of time (i.e., SD integrated over time).
The fundamental inter-relationships between these variables in a simple I- pasture, 1-herd grazing regime are presented in Figure 7.1. Section A reflects the effect of varying numbers and kinds of animals on SD and SR when SR is defined as number of a specific class of animal species. Section B demonstrates the effect of varying levels of FD on SR when expressed on an AU basis. For example, SR is equal (5 ha/AU/yr) for 1000 ewes or 200 cows if it is assumed the FD substitution ratio is 5. It is quite different, however, if the ratio is otherwise. Section C shows that at equal FD, SR is equal. Section D demonstrates the relative effects of changing levels of FA on GP. Section E demonstrates the effect of preference, which is a relative term describing the discretionary behavior of animals in the selection of various forages (Hodgson 1979), on GP if it is assumed sheep prefer forbs over grass and cattle prefer grass over forbs (see Chapter 2 and Chapter 3).

Figure 7.1

Although the definition of GP used herein differs slightly from traditional definitions (Hodgson 1979; Scarnecchia and Kothmann 1982; Soc. Range Manage. 1989), it is conceptually appropriate because it incorporates the concept of preference at the plant-animal interface. This concept is critical to meeting the objectives of this chapter because of the linkage between the basic principle of grazing management (i.e., control of the intensity of defoliation of individual plants), the four general principles of grazing management as outlined above, and traditional range condition concepts (see Chapter 5).

The concepts used to define and describe range condition have long been the subject of lively debate among range ecologists (Humphrey 1949; Costello 1964; Tainton et al. 1980; Smith 1988a; Wilson 1989; see Chapter 5), particularly with regard to the practical aspects of quantitative assessment and monitoring (Soc. Range Manage. 1983; Westobv et al. 1989). A major issue of concern is the concept that as range condition improves, livestock carrying capacity also improves (see definition of range improvement, Soc. Range Manage. 1989). Although this is an attractive concept because it seems intuitively reasonable and appropriate in certain instances (Danckwerts and Aucamp 1986), it has been shown to be inappropriate in many cases because it is not biologically possible to continually maximize energy capture (i.e., excellent range condition) and harvest and conversion efficiencies simultaneously (see Chapter 1).

In an attempt to avoid having to specifically address the absolute impact of range condition on livestock production throughout this chapter, we specifically define range improvement as any change in quantity and/or quality of available forage that facilitates sustained livestock production. Central to this definition is that optimum range condition in terms of the forage complex, is that which maximizes livestock production/unit area of land on a sustained basis.

top
General Principles

Number of Animals

Determining the proper number of animals to be placed on an area is the principal factor affecting the relative success of any grazing management strategy. This is so because number of animals affects not only individual animal performance but also production/unit area of land (see Chapter 1). Regardless of vegetation complex or the kind or class of animal, number of animals occupying an area over a given period of time (stocking rate) has a profound effect on livestock production because it affects GP directly by virtue of its direct effect on FD and the subsequent effects of FD on FA. For example, at low rates of stocking, individual animal performance is maximized (Fig. 7.2) relative to the quality of forage available because GP is low. However, production/unit area is also necessarily low because number of animals/unit area is low (Fig. 7.3). But as stocking rate is increased (moderate GP), individual animal performance begins to decline because of restrictions imposed on nutrient intake by either quantitative and/or qualitative declines in the forage resource (see Chapter 2). The stocking rate at which this decline begins is commonly referred to as the critical stocking rate (Hart 1978), and any increase in stocking rate beyond this point normally results in a reduction in individual animal performance. Production/unit area, however, continues to increase as stocking rate is increased from low to moderate because of the increase in number of animals (Fig. 7.3). This increase continues to some maximum as stocking rate is increased, but eventually it too decreases as nutrient intake becomes progressively more restrictive.

The stocking rate at which maximum production/unit area is achieved varies as a function of rate of decline in individual animal performance. Most often it is assumed for practical reasons that rate of decline is linear (Hart 1978) because in such cases it can be shown that the stocking rate at which maximum production/unit area is achieved is precisely one-half of the stocking rate at which individual animal performance is zero. In reality, however, the relationship between stocking rate and individual animal performance is probably curvilinear (Peterson et al. 1965; Connolly 1976; Edwards 1981). The reason it is curvilinear is because a linear decline in individual animal performance is only possible if the decline in the net assimilation rate of the individual animals is uniformly linear. This is doubtful particularly in multispecies extensive grazing systems because quantity and quality of available forage (nutrients) are seldom uniformly distributed (vertically and horizontally) over time. As a result, it is doubtful quantity and/or quality of forage consumed (nutrient intake) declines in a linear fashion as stocking rate is increased. Moreover, it is doubtful that the amount of energy expended per animal in search of nutrients (grazing) remains constant as stocking rate increases. The resulting effect is that as stocking rate is increased in extensive rangeland settings, rate of decline in individual animal performance is accelerated (Fig. 7.2).

The stocking rate at which maximum production/unit area is achieved, when individual animal gains-stocking rate responses are assumed to be curvilinear rather than linear, is near that at which individual animal performance is one-half of maximum. In other words, it is near the stocking rate that is halfway between the critical stocking rate and that at which individual animal performance is zero. This is in contrast to an assumed linear response as discussed earlier, wherein maximum production/unit area is achieved at the stocking rate that is precisely one-half of the stocking rate at which individual animal performance is zero. The relative differences in precision of estimates of optimal stocking rates between linear (precise) and curvilinear (near) individual animal-stocking rate response functions occurs because assumed linear responses are easily defined mathematically, whereas curvilinear responses are often undefinable.

But regardless of the precise rate of stocking required to maximize production/unit area, the basic problem in grazing management is that the relationships between rate of stocking and livestock production are extremely complex and highly variable in anv livestock production system because GP varies widely over time and space. This variation is the result primarily of variations in quantity and quality of available forage (nutrients available) over time and space as a result of both managerially uncontrollable variables, which are primarily abiotic, and controllable variables, which are primarily biotic (see Chapter 1). Major abiotic variables are climate and the inherent productivity potential of a site as defined by such factors as soil fertility, slope, and aspect (range site). Thus, quantity and quality of available forage vary seasonally, among years and range sites, and within and among geographical regions (Sims and Singh 1978; Sala et al. 1988) regardless of the relative impact of any biotic factors.

The major biotic factor affecting quantity and quality of available forage is grazing intensity, of which stocking rate is a major determinant. Generally, as stocking rate is increased, quantity of available forage declines on both a short- and long-term basis. On a short-term basis, this decline occurs because rate of forage depletion exceeds rate of accumulation. On a long-term basis, this decline results because of the interaction effects of both abiotic and biotic factors on plant growth (see Chapter 4) and plant successional processes (see Chapter 5). Grazing intensity is a major factor affecting the direction, magnitude, and rate of vegetal change (range trend and condition) in rangeland ecosystems.

Figure 7.2

Figure 7.3

Stocking rate often affects quality of available forage also, but the relative effect varies over time and space depending upon the specific situation. On a short-term basis, overall forage quality often increases as grazing intensity increases because of the removal of low-quality (senesced) forage (Heitschmidt et al. 1987b, 1987c), whereas qualitv of available forage over the long-term varies depending upon the quality of the replacement species resulting from changes in species composition (see Chapter 5).

As a result of the integrated effects of abiotic and biotic factors on quantitv and quality of available forage over time, and because of the relationship between GP and livestock production, the quantitative relationships between stocking rate and livestock production (Figure 7.2 and Figure 7.3) are situation specific in that they vary over time and space. As a result, optimal rates of stocking vary over time and space depending upon season, year, site, and management goals. Although such terms as under- and over-stocking are relative terms that vary as a function of management goals, "proper" stocking can be defined as that which maximizes energy capture, harvest, and conversion efficiencies within a given area on a sustained basis when assumed management goals are oriented towards maximizing livestock production over time. In this sense, under-stocking can be viewed as a tactic that generally enhances efficiency of energy capture and stability of livestock production, whereas over-stocking can be viewed as a tactic that generally reduces stability of livestock production by suppressing energy capture (see Chapter 4 and Chapter 5) and/or energy conversion efficiency (see Chapter 2).

The essence of the effects of stocking rate on livestock production is reflected in Figure 7.2 and Figure 7.3. In both figures, the upper curve reflects the functional relationship between stocking rate and livestock production when nutrient availability/unit area of land is high (low GP), while the lower curve reflects the relationship when nutrient availability/unit area of land is low (high GP). The distance between the two curves reflects the potential effect of varying levels of nutrient availability on livestock production at various rates of stocking. At low rates of stocking, the effects are limited because differences in livestock production are a function of quality of forage. However, potential differences increase dramatically as stocking rate is increased because livestock production is affected by both quantity and quality of forage available. In other words, as forage demand (stocking rate) increases, stability of livestock production decreases. This is reflected by the general increase in the standard deviations of annual means derived from a wide array of stocking rate-livestock production studies as summarized in the margins of Figure 7.2 and Figure 7.3.

Unfortunately, quantity and quality of available forage in dynamic, multi-species rangeland ecosystems often vary more as a function of the highly variable, managerially uncontrollable abiotic factors, as discussed earlier, rather than the managerially controlled biotic factors (Noble 1986; see Chapter 5). As a result, the optimal stocking rates for livestock production in extensive rangeland settings vary widely among seasons, years, and sites, within and among geographical regions (Morley 1966; McCown 1982). This concept is reflected in Figure 7.2 and Figure 7.3 in that the optimal stocking rate for maximizing livestock production when quantity and/or quality of forage available is low, Max 1, is less than the optimal rate when quantity and/or quality of forage available is high, Max 2. It can be concluded also that the probability that frequently occurring abiotic events, such as drought, will become catastrophic, is related to rate of stocking. This is demonstrated in Figure 7.2 and Figure 7.3 in that livestock production at the optimal rate of stocking during periods of reduced forage production, Max 1, would be greater than at the heavier rate of stocking required to maximize production during periods of ample forage production, Max 2. In other words, as rate of stocking increases so does frequency of occurrence of catastrophic events (Noy-Meir and Walker 1986). Thus, proper rates of stocking for sustained livestock production are necessarily moderate in virtually all range livestock production systems.

top
Kinds and Classes of Animals

The concept of GP is related generally only to total forage demand/availability within a given area (Hodgson 1979; Scamecchia and Kothmann 1982). But when forage demand is defined so as to incorporate the concept of preference within the GP function (Figure 7.1, section E), the underlying rationale for mixed animal grazing is easily grasped because:

1. Most grazing lands generally support a combination of forage classes (grasses, forbs, shrubs, and trees); and
2. Dietary preference, nutrient requirements, and foraging abilities vary among kinds and classes of animals (see Chapter 2 and Chapter 3).
Thus, GP varies among forage classes over time and space as a function of the unique assemblage of plants and animals present. By matching the forage demand of various kinds and classes of animals to the forage available, an overall increase in harvest and conversion efficiencies can often be realized, thereby increasing livestock production.

The most common practice employing this strategy is multi-species grazing. The effects of multi-species grazing on livestock production has been the subject of many studies throughout the world (Aucamp et al. 1986). For example, in the Edwards Plateau region of Texas such studies have continued without interruption for the past 38 years (Taylor 1985). Vegetation in this region is a mixture of short and mid-grasses with an abundance of forbs and a moderate overstory of browse. Grazing studies have focused on quantifying the relative effects of various combinations of cattle, sheep, and goats on livestock production. Yearlong grazing treatments stocked at equal rates of total FD include: cattle (100%); sheep (100%); goats (100%); cattle (50%) + goats (50%); and cattle (50%) + goats (25%) + sheep (25%). Results (Fig. 7.4) show that:

1. Production/animal was significantly greater for steers when grazed in combination with sheep and goats than when grazed alone;
2. Production/ewe was significantly greater when sheep were grazed with cattle and goats than when grazed alone; and
3. Production/goat was not affected by species mix.
The results from these studies reflect the relative effects of varying levels of GP on livestock production. Previous research has clearly established that cattle prefer grass, sheep prefer grass and forbs, and goats prefer browse and grass (see Chapter 2). Although forage availability was not measured in these studies, results from diet studies (Taylor 1985) suggest that when cattle were replaced by goats and/or sheep, individual cattle performance increased because FD for the grass component was reduced (lower GP). Likewise, it can be assumed production/ewe increased when some sheep were replaced bv cattle and goats because GP on the forb component declined. Production/goat was presumably unaffected by species mix because rate of stocking was below the critical stocking rate necessary to cause a shift in diet selection from a high-quality browse and grass dominated diet to a lower quality diet. Selection of the proper kinds and classes of animals is also related to environmental and economic constraints. Two examples of variations in kinds and classes of animals relative to these constraints are the preponderance of Bos indicus type cattle in the hot, arid regions of the world and the dominance of growing rather than breeding livestock in regions with an abundance of annual cereal grains.
top
Spatial Distribution of Animals

It is well known that livestock preferentially select various plants and plant parts during the grazing process (see Chapter 2 and Chapter 3). They also preferentially select various assemblages of plant species (plant communities) in which to graze (see Chapter 3). Because the distribution of various plant communities varies spatially as a function of such factors as toposequence, soil type, aspect, and past grazing history (see Chapter 5), GP varies among plant communities depending upon livestock distributional patterns across a landscape relative to the kinds and amounts of forage available.

Common practices utilized to enhance livestock distributional patterns are crossfencing and strategic placement of salt, mineral, and watering facilities. There is also a strong interaction between multi-species grazing and spatial grazing patterns. This interaction effect is related primarily to the spatial distributional pattern of preferred and non-preferred plant communities/forage classes across a landscape, the innate behavioral patterns of various kinds and classes of animals, and the social interaction effects of various animal species that promote the establishment of multiple herds of grazing animals.

Figure 7.4

Studies examining the potential impact of varying livestock distributional patterns on livestock production have been reviewed previously (Squires 1981). More recently, however, the basic effects of cattle distributional patterns on livestock production have been demonstrated by Hart et al. (1988). At nearly equal rates of stocking and GP, they reported that average daily gain (ADG) of yearling heifers in Wyoming in a 518-ha pasture was significantly less than ADG in 24- and 34-ha pastures. Maximum distance to water was 5.4 km in the larger pasture and 1.4 km in the smaller pastures. Herbage utilization, a measure of harvest efficiency, averaged 50% in the smaller pastures and was similar regardless of distance from water. Utilization in the larger pasture averaged 41% and ranged from 60% near water to 25% near the back of the pasture.

top
Temporal Distribution of Animals

Justification for temporal variation in livestock grazing strategies is related primarily to the short- and long-term effects of defoliation on quantity of forage produced (efficiency of energy capture) and consumed (harvest efficiency), and secondarily to the quality of forage produced and consumed (efficiency of conversion). This conclusion is dictated by the first law of thermodynamics (see Chapter 1) because the presence of forage (captured solar energy) is a prerequisite to forage quality determinations. Still, the nutritional aspects of the grazing animal should be considered (Launchbaugh et al. 1978) in light of the effect of temporal variations in quantity and quality of forage available on livestock production.

There is essentially only one mechanism whereby an increase in livestock production can be expected to result as a direct function of temporal adjustment of grazing events, i.e. increased forage quality. Forage quality is seldom directly enhanced by deferment from grazing although it may be indirectly enhanced if deferment induces a desirable qualitative change in species composition (see Chapter 5). This long-term response is in contrast, however, to the potential short-term effect of grazing on forage quality. For example, Heitschmidt et al. (1987b) showed that forage quality [percentage crude protein (CP) and organic matter digestibility (OMD)] in a north Texas grassland increased over the short-term as GP increased. But the increase was the result of a decline in relative amounts of low-quality senesced forage rather than an absolute increase in amounts of high-quality, actively growing forage. This concept is the underlying mechanism justifying the use of such practices as early intensive stocking (EIS). Utilizing EIS tactics, Launchbaugh et al. (1983) showed that in certain instances, cattle production/ha increased approximately 25% over season- long grazing (SLG) when rate of stocking was increased 2-fold and length of grazing season was halved. The apparent reason for this outcome was attributed to the effect of seasonal changes in forage quality on steer conversion efficiency. This conclusion was supported by the ADG of the steers which was nearly equal in both treatments during the duration of the IES treatment (Mav 1-July 15) but declined thereafter in the SLG treatment (May 1-October 1).

It should be noted, however, that the response in this study was mediated through an adjustment in stocking rate in addition to manipulation of the temporal distribution of the grazing season. The strategic timing of the shortened grazing season was selected primarily in consideration of the nutritional aspects of the grazing animal; in short, the aim was to enhance conversion efficiency rather than efficiencv of energy capture. This objective was realized as evidenced by the 25% increase in production/ha with IES, although rate of stocking in both treatments was equal when averaged across the 172-day duration of the SLG treatment. However, it should be noted that the benefits of IES tactics would be difficult to capture in a year-long operation stocked only with breeding animals.

A second example of a management practice designed in consideration of the nutritional needs of grazing livestock is adjustment of breeding seasons (see Chapter 2) in accordance with the cyclic dynamics of forage quality and the cyclic nutritional needs of breeding animals. Because both the nutritional needs of breeding stock and quantity and quality of available forage vary over time, livestock production can be enhanced by proper manipulation of GP over time relative to nutrient demand and nutrient availability. The relative benefits derived from this practice are similar, however, regardless of stocking rate or grazing system because temporal growth patterns of vegetation in most rangeland ecosystems are similar regardless of grazing regime.

top
Grazing Systems

Grazing systems are management tools designed to balance the conflicting relationships between energy capture, harvest, and conversion efficiencies (see Chapter 1). They are designed firstly to enhance livestock production over time by either improving and/or stabilizing the quantity (efficiency of energy capture) and/or quality (efficiency of conversion) of forage produced and/or consumed (efficiency of harvest). Production improves if the benefits of rest or deferment exceed the detrimental impacts of grazing; stabilization results if the benefits of rest exactly equal the detrimental impacts of grazing; while degradation results when the benefits of rest are less than the detrimental impacts of grazing. But regardless of the effects of a grazing system on the vegetation complex, its effects on livestock production vary depending upon its direct effects on GP.

top
Concepts and Terminology

A grazing system is considered "a specialization of grazing management which defines recurring periods of grazing and deferment for 2 or more pastures or management units" (Soc. Range Manage. 1989). For the purposes of this chapter, we limit our discussion to grazing systems stocked year-long. However, the basic ecological concepts and principles presented herein apply equally well to seasonal grazing systems because they too include recurring periods of grazing and deferment. The only difference between year-long and seasonal grazing systems is the tactic utilized to attain desired periods of grazing and deferment (number pastures > number of herds vs. buy/sell seasonally).

As defined earlier, grazing pressure (GP) is the ratio of forage demand (FD) to forage available (FA) at any instant. This is a conceptually convenient definition when considering the effects of GP on livestock production in a I-pasture, 1-herd, continuously grazed treatment. But the conceptual analysis of the functional attributes of grazing systems requires a refinement of this concept because at any instant at least one subdivision of all grazing systems is rested. Thus, GP varies as a function of resource (forage or livestock) or area (individual subdivision or total area) of interest. For example, in a 4-pasture, 1-herd system (Figure 7.5) livestock or subdivision GP will be four-fold greater than forage or total GP because only one fourth of the total forage or area within the fenced boundaries of the system is available to the animals at anv instant. In other words:
 
 

  Livestock GP = forage-demand (FD)


forage available (FA) in grazed subdivisions(s)
  Forage GP = forage-demand


forage present in all subdivisions

In concert with this concept, it can be seen that forage GP will not vary among grazing systems, regardless of number of subdivisions, if total FA and FD are equal whereas livestock GP will vary dramatically depending upon the effect each grazing system has on stock density (Figure 7.5). Appreciation for this concept is paramount for the development of an understanding of the potential impact of various grazing systems on livestock production.

Figure 7.5

top
Effects on Livestock Production

The effects of various year-long grazing systems on livestock production have been reviewed previously by many (Heady 1961; Driscoll 1967; Shiflet and Heady 1971; Herbel 1974; Gammon 1978; Pieper 1980). Although interpretive conclusions vary among these and other reviewers, all tend to agree that the relative benefits derived from any grazing system, in terms of livestock production, vary greatly over time and space thereby making it difficult to make any definitive, universal conclusions concerning relative merits. This is not surprising however, when the varied results are examined within the conceptual framework presented earlier relative to the effect of GP on individual animal performance. For example, it is easy to understand why individual animal performance generally declines, or at least does not improve immediately following the establishment of any grazing system (Wilson et al. 1984), unless rate of stocking is reduced (high livestock GP). Moreover, it is easy to understand why improvement in livestock production is dependent primarily on improvement in quantity and/or quality of forage available and/or consumed over time or space.

Tactics. There are two fundamental management tactics utilized to enhance quantity and/or quality of forage produced over time. These are commonly referred to as:

1. High utilization grazing (HUG); and
2. High performance or high production grazing (HPG) (Booysen and Tainton 1978).
The functional difference between these two tactics is related to the discretionary manner in which they affect the competitive interactions of preferred (high GP) and non-preferred (low GP) plant species. With HUG strategies, all plants are moderately to intensively defoliated during a grazing period, whereas with HPG strategies only the preferred plants are defoliated and then only at light to moderate intensities. Improvement with HUG tactics stems from the discretionary effects moderate to heavy levels of defoliation have on the competitive abilities (see Chapter 4) of the preferred and non-preferred species when both are defoliated. Improvement with HPG tactics stems from the varying effects lenient levels of defoliation have on the competitive abilities of the preferred plants relative to the competitive abilities of the ungrazed, non-preferred plants. The on-going (immediate or short-term) impact of these two tactics on livestock production are quite different because HUG tactics necessarily require livestock consume non-preferred forages whereas HPG tactics require consumption of only preferred forages. As a result, individual animal performance is usually less with HUG than HPG tactics whereas animal production/unit area is greater.

Implementation of a grazing system may also enhance livestock production if additional fencing is required whereby improved livestock distribution patterns are realized. This effect has been demonstrated by Hart et al. (I 988) in Wyoming. At equal rates of stocking, they reported that ADGs of cattle were equal in an 8-pasture, 1-herd rotation system (24 ha/pasture) and a continuously grazed treatment if the continuously . grazed pastures (24 and 34 ha) were small, but were greater in the rotational system when the continuously grazed pasture was large (518 ha).
 

Types of Grazing Systems. Functionally, there are four basic types of grazing systems (Figure 7.6):

1. Deferred rotation (DR);
2. Rest rotation (RR);
3. High intensity-low frequency (HILF); and
4. Short duration (SD).
The functional aspects of each system center around the employment of either HPG or HUG tactics. The major factor affecting such is stocking rate in that high rates of stocking insure HUG tactics are employed rather than HPG regardless of type of system. However, assuming rate of stocking is moderate the general features of each are as follows.

Deferred rotation (DR) systems are multi-pasture, multi-herd systems designed to maintain or improve range condition utilizing HPG tactics. Stock density is moderate, length of graze long, and length of rest moderate. An example of a DR system is the 4-pasture, 3-herd system developed by Merrill (1954) in the southern mixed- grass prairies of the U.S. (Figure 7.6).

Figure 7.6

Rest rotation (RR) systems are either multi-pasture, multi-herd or multi-pasture, single herd. They are designed to maintain or improve range condition utilizing a combination of HPG and HUG tactics. Stock density ranges from moderate (multi- herd) to heavy (single herd); length of graze ranges from short (HPG tactics) to long (HUG tactics), and length of rest from long to short. An example of a RR system is the 3-pasture, 1-herd Santa Rita system developed by Martin (1978) for the and desert grasslands of the southern U.S. (Figure 7.6).

High-intensity, low-frequency (HILF) systems are multi-pasture systems usually stocked with a single herd of livestock (Figure 7.6). They are designed to maintain or improve range condition utilizing HUG tactics. Stock density is high, length of graze moderate, and length of rest long.

Short duration (SD) systems are similar to HILF systems (Figure 7.6) except HPG rather than HUG tactics are employed to maintain or improve range condition. This is achieved by reducing length of graze and rest period while maintaining high stock densities.

Livestock Production. The relative effects of the four types of grazing systems discussed above on livestock production are presented in Figure 7.7. These generalized response curves are based on five important assumptions.

1. Vegetation complex is a multi-species, temporally variable grassland grazed year-long.
2. All systems are implemented using existing pastures.
3. Quantity and quality of available forage (i.e., range condition, our definition) is equal in all systems.
4. Management skill is sufficient to insure that livestock production in the more intensively managed type systems, particularly SD, is not unduly suppressed by improper rotation schedules.
5. There are no kinds or classes of animal by grazing system interaction effects.
Figure 7.7

These assumptions are prerequisites for the development of livestock-stocking rate response curves because of the differential effects that various grazing systems may elicit relative to the four principles of grazing management. A major problem in grazing system research in extensive rangeland settings lies in our inability to effectively employ multi-factor experimental designs to elucidate single-factor effects of a multitude of factors that affect livestock production. For example, livestock production in a 1-herd, multi-paddock RG system may vary as a function of a number of factors including stocking rate, number of paddocks (i.e., stock density), and rate of rotation (i.e.. length of graze/rest periods. Thus to properly evaluate such a system requires at least a twice replicated 3 x 3 factorially designed experiment. Although such studies are desirable, they are often not feasible because of resource limitations relative to land, labor, and capital. Thus, any interpretive summary of the effects of various grazing systems on livestock production, such as that presented in Figure 7.7, must be based on a general understanding of the potential impact that the four types of grazing systems have on livestock GP over time and space.

Assumption # 1 is made to eliminate any confusion that may arise concerning the potential impact of grazing systems on livestock production in tame pasturage and/or seasonal grazing environments. For example, it may be argued that continuous grazing is superior to rotational grazing when the early intensive stocking (EIS) strategy, discussed earlier, is employed on an area of land. However, for the present purposes, we would simply argue that seasonal grazing strategies such as EIS are functionally equivalent to year-long grazing HILF type systems (Le., long graze, long rest).

Assumption #2 is necessary to eliminate the differential impact that various systems may have on livestock production as a result of redistribution of animals from increased subdivisions. This does not mean, however, that grazing systems do not enhance livestock distribution patterns as a result of their effect on stock density, as hypothesized by Kothmann (1980), Savory and Parsons (1980), and Malechek and Dwyer (1983). Certainly, the data of Hart et al. (I 988), as discussed earlier, show stock density does not greatly impact livestock performance when pastures are small. Likewise, studies by Gammon and Roberts (1978), Kirby et al. (1986), and Walker et al. (1989c) tend to support the findings of Hart et al. (1988). Still, there seems little doubt that such would be the case if pastures were extremely large. Unfortunately, we know of no studies that clearly address this hypothesis.

Assumption #3 is necessary to eliminate potential differences in livestock production that may arise over time as a result of a change in quantity and/or quality of forage available (i.e., range condition). As discussed earlier, the potential impact of various grazing systems on range condition, and subsequently on livestock production, is a question that has not been critically addressed (Gammon 1978; Malechek 1984; Hart and Norton 1988; Holechek et al. 1989). We question, however, the value of addressing this issue on a broad scale because desired condition varies depending upon management goals. Moreover, because of regional differences in abiotic conditions and functional differences between grazing systems, no one grazing system is universally the best. Optimal length and sequential scheduling of graze-rest periods vary as a function of the interaction effects of abiotic and biotic factors on plant growth (see Chapter 4) and successional processes (see Chapter 5). Of major importance is the temporal precipitation pattern in a region because the benefits derived from rest or deferment, in terms of range improvement, are greatest during periods of ample rainfall. To improve the probability of encountering favorable growing conditions during a period of deferment, length of rest must be lengthened with increasing aridity. Thus, RR and HILF systems are designed characteristically for regions having extended periods of drought, such as desert grasslands, whereas DR and SD type systems are designed for areas where extended periods of drought are uncommon, such as temperate grasslands. As a result, universal conclusions as to the relative merits of various grazing systems, based on data from a wide array of studies conducted across a broad array of regions, are inappropriate and of little practical value.

Assumption #4 is made to eliminate the impact that varying levels of management skill can have on livestock production in any given system. Certainly, the greater the livestock GP (Figure 7.5) the greater the precision of judgment necessary to attain satisfactory levels of livestock production (Gammon 1978).

Assumption #5 is made because of potential differences among grazing systems in their impact on livestock behavior. For example, there is little doubt that the probability of a grazing system affecting offspring survivability is greater in SD than any other type of system because of interference with the "mothering" process of breeding animals as a result of frequent rotation.

In light of these assumptions and a basic understanding of the potential effects of livestock GP on individual animal performance (HPG and HUG tactics), we believe Figure 7.7 approximates the short-term impacts of DR, RR, HILF, and SD type grazing systems on livestock production at various rates of stocking. We believe generally that critical rates of stocking (Hart 1978) will decrease in direct proportion to the manner in which each system affects livestock GP (DR<RR<HILF) and/or energy expenditures (SD>others). In theory, there is little reason to assume that high livestock GP will decrease individual animal performance in an SD type system if rate of rotation is proper (Assumption #4). However, previous research in SD type systems (Walker and Heitschmidt 1989) has shown that as rate of rotation is accelerated, time spent trailing and distance walked increase, which leads us to believe the lowest critical rate of stocking will most often be in SD type systems.

We also suggest that individual animal performance will be less in DR, RR, and HILF type systems than under continuous grazing, at all rates of stocking in excess of the critical rate. Depicted relative differences between these systems at any given stocking rate are based on how frequently we suspect restrictive performance levels will be encountered as a result of increased livestock GP.

The slower rate of decline in individual animal performance in the SD systems as rate of stocking is increased reflects the potential interaction effect that frequency and/or intensity of encounter of high livestock GP events may have on livestock performance. This hypothesis centers around the assumption that frequent encounters of high livestock GP events of short duration are cumulatively less restrictive to animal performance than infrequent encounters of long duration (see Chapter 2). In other words, how forage is rationed in situations where livestock GP is high can affect individual animal performance. Although we know of no data in direct support of this hypothesis, we believe such is the case based strictly on our personal experiences and observations (Taylor 1989; Heitschmidt et al. 1990).

This generalization does not support, however, the claim that sustainable rates of stocking in SD type systems are well above those under continuous grazing in year- long grazing environments. This matter is currently the subject of lively debate throughout the world (Savory and Parsons 1980; Heitschmidt and Walker 1982; Gammon 1984; Skoviin 1987; Pieper and Heitschmidt 1988; Bryant et al. 1989; Taylor 1989), but the argument has little merit unless it is assumed that SD type grazing systems consistently enhance rate of forage production between grazing events. Although this is an exciting and attractive hypothesis and probably true in certain situations (McNaughton 1978; Detling 1988; Heitschmidt 1990), it is also a well- researched, refuted hypothesis (see Chapter 1) relative to the general effects of grazing on plant growth in multi-species, arid, and semi-arid rangelands (Beisky 1986), and particularly in SD type grazing systems (Heitschmidt et al. 1987a, 1987c).

Based on the above generalization, it is easy to see why the results from various grazing system studies are relevant only when examined within the designed objectives of the study. Universal conclusions as to the relative merits of any particular grazing system are generally of limited value and inappropriate. An understanding of the functional aspects of various grazing systems suggests, however, that perhaps the major benefit derived from the employment of a grazing system is directlv related to the forced use of moderate rates of stocking. Moreover, it seems reasonable to assume that the use of a mix of various grazing systems, in conjunction with continuous grazing, may be more appropriate for achieving management goals rather than the continuous use of any single system strategy (Walker et al. 1986a).

top
Conclusions

Livestock production is an integrated measure of energy capture, harvest, and conversion efficiencies. The principal factor affecting livestock production is grazing pressure (GP), which varies as a function of both abiotic and biotic factors. The principal abiotic factors are climate and the inherent productivity potential of a site. The principal biotic factor is grazing intensity, which varies as a function of the temporal and spatial distribution of various kinds and numbers of grazing animals. Grazing systems are management tools designed to enhance and stabilize livestock production over time. They are designed firstly to enhance efficiency of solar energy capture as evidenced by the universal incorporation of a period of deferment in the design of all grazing systems. The nutritional needs of livestock are necessarily of secondary consideration in the design of all grazing systems, the effects of which are mediated through the use of conservative rates of stocking. Research has shown that the on- going effects of various grazing systems on livestock production vary widely over time and space. As a result, no grazing system has been shown to be universally superior to any other in terms of its ability to enhance livestock production.

 top


 


List of Figures





Figure 7.1    Flow chart depicting relationships among stocking density, stocking rate, forage demand, forage available and grazing pressure as affected by varying numbers and types of animals and amounts of forage in a simple 1-pasture and 1-herd grazing regime.

Figure 7.2    Conceptual model of functional relationship between light, moderate, and heavy stocking rates and production/animal as derived from stocking rate studies by Pieper et al.(1978).

Figure 7.3    Conceptual model of functional relationship between stocking rate and production/unit area.  See Figure 7.2 for details

Figure 7.4    Production / animal of mutton goats, steers, and mutton sheep when grazed year long at a moderate rate of stocking in various combinations.

Figure 7.5    Flow chart depicting relative effects of two grazing systems on stock density and grazing pressure.

Figure 7.6    Conceptual model of sequential schedule of graze-rest periods for deferred rotation, rest rotation, high intensity-low frequency, and short duration type grazing systems.

Figure 7.7    Conceptual model of the theoretical on-going effects of stocking rate on livestock production in continous, deferred rotation, rest rotation, high intensity-low frequency, and short duration type grazing systems.