3

Population Processes

The Bureau of Land Management (BLM) asked the committee to address the following questions as part of the discussion of potential rates of horse and burro population growth: Would free-ranging horse and burro populations self-limit if they were not controlled? If so, what indicators (such as rangeland condition, animal condition, and health) would be present at the point of self-limitation? To address those questions, it is necessary to review the factors that limit population growth in an unmanaged population1 and that determine free-ranging horse and burro population growth and dynamics aside from management removals. Population growth and self-limitation are population processes in the sense that they involve a suite of underlying functions that lead to the result. The underlying functions include changes in natality and survival in response to environmental variables that affect forage availability, such as weather and population density.

The committee was also asked to assess whether there is compensatory reproduction as a result of population-size control, such as fertility control or removal from Herd Management Areas (HMAs). Compensatory reproduction is defined as an increase in reproduction as a direct or indirect consequence of management reductions, including removals and contraception. Indirect responses could include increased fertility, foal survival, or adult survival due to reduced competition for forage.

For self-limitation to occur, it is necessary for population processes to respond to population density (Figure 3-1). That is, population processes—such as population growth rates, age-specific survival rates, natality, and age of bearing first offspring (primiparity)—must be density-dependent. As density increases, population growth rate decreases because of increased competition for resources. Population processes are also altered by density-independent factors, particularly climatic conditions and variations. Natality and mortality can be affected by climatic conditions through direct effects on animals. Climatic conditions also affect resource abundance, for example, through effects on forage production.

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1 Unmanaged populations of horses and burros are not domestic animals, and they are not fed or given veterinary care. Their numbers are not controlled by removals or contraception.



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3 Population Processes T he Bureau of Land Management (BLM) asked the committee to address the following questions as part of the discussion of potential rates of horse and burro population growth: Would free-ranging horse and burro populations self-limit if they were not controlled? If so, what indicators (such as rangeland condition, animal condition, and health) would be present at the point of self-limitation? To address those questions, it is nec- essary to review the factors that limit population growth in an unmanaged population1 and that determine free-ranging horse and burro population growth and dynamics aside from management removals. Population growth and self-limitation are population processes in the sense that they involve a suite of underlying functions that lead to the result. The under­lying functions include changes in natality and survival in response to environmental variables that affect forage availability, such as weather and population density. The committee was also asked to assess whether there is compensatory reproduction as a result of population-size control, such as fertility control or removal from Herd Manage- ment Areas (HMAs). Compensatory reproduction is defined as an increase in reproduction as a direct or indirect consequence of management reductions, including removals and contraception. Indirect responses could include increased fertility, foal survival, or adult survival due to reduced competition for forage. For self-limitation to occur, it is necessary for population processes to respond to popu- lation density (Figure 3-1). That is, population processes—such as population growth rates, age-specific survival rates, natality, and age of bearing first offspring (primiparity)—must be density-dependent. As density increases, population growth rate decreases because of increased competition for resources. Population processes are also altered by density- independent factors, particularly climatic conditions and variations. Natality and mortality can be affected by climatic conditions through direct effects on animals. Climatic condi- tions also affect resource abundance, for example, through effects on forage production. 1  Unmanaged populations of horses and burros are not domestic animals, and they are not fed or given veteri- nary care. Their numbers are not controlled by removals or contraception. 61

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62 USING SCIENCE TO IMPROVE THE BLM WILD HORSE AND BURRO PROGRAM Density Independence r K Density Dependence FIGURE 3-1  Population processes, including density-independent and density-dependent controls. Figure 3-1 NEW Population size can be reduced by predation, and predator abundance is affected by prey abundance. Population growth can also be affected by dispersal, immigration and emigra- tion, and management factors, such as removal of animals from the range and contracep- tion. This chapter examines the changes in population processes of free-ranging equids due to density-dependent, density-independent, predation, and management factors. DENSITY-DEPENDENT FACTORS It is a general principle of ecology that populations do not continue to grow indefi- nitely, but the mechanisms of reduction in growth as densities increase are not always well understood (Flux, 2001). Mechanisms may include competition for resources among members of the same species at high densities (Ginzburg, 1986; Berryman, 2003), complex social behaviors (Wynne-Edwards, 1965), and combinations of physiological responses to social cues (Wolff, 1997). Density dependence can be seen most easily by examining the S-shaped curve of popu- lation size changing over time described by the logistic equation dN/dt = rN([K – N]/K), where dN/dt is the instantaneous rate of change in N, N is the size of the population (num- ber of individuals), r is the intrinsic rate of natural increase, and K is the carrying capacity, that is, the maximum population size that the environment can support as affected by resource abundance. The discrete form of the equation defines the population increment over an interval of time, such as a year, and is expressed as Nt + 1 = Nt + R(Nt[K – Nt]/K), where Nt + 1 is the population size in the next year or generation, Nt is the population size in the current year or generation, R is the maximum rate of increase per year or generation, and K is the carrying capacity. The annual or generational increment can be defined as ∆N = Nt + 1 – Nt.

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POPULATION PROCESSES 63 Early in the growth process there is a period in which population grows without limita- tion because the difference between Nt and K is so large that the density-dependent term ([K – Nt]/K) produces little constraint on ∆N (Figure 3-2A). At the inflection point (point α in Figure 3-2A), ∆N (point β in Figure 3-2A) is maximized, but as Nt approaches K, growth slows; it even becomes negative if Nt is greater than K. The population trajectory represented by the logistic equation, as portrayed in Figure 3-2A, assumes that R and K do not vary over time. If, however, environmental variation is great and harsh conditions periodically reduce R or K independently of density, the importance of density dependence diminishes. If such variations are great enough, the population will rarely experience density dependence. Population sizes that are strongly affected by such density-independent factors show sawtooth-like increases and decreases and do not come to a steady equilibrium with resources. Density indepen- dence is explained further below. Carrying capacity is a concept that has multiple definitions that depend on the situation. For populations of unmanaged large herbivores, carrying capacity is determined by resource availability, primarily food, so it is sometimes called the food-limited or ecological carrying capacity. Food-limited carrying capacity (K in the logistic model) can be determined empiri- cally by letting a population grow until it comes into quasiequilibrium with the resource base. That idea of carrying capacity is different from the idea of carrying capacity discussed in Chapter 7, in which forage supplies are estimated and combined with an appropriate forage utilization level to set an appropriate management level (AML) in an attempt to preserve a thriving natural ecological balance. That is not to say that a population at or near K cannot result in a thriving natural ecological balance. However, the value of K will most likely be higher than the carrying capacity set in the AML process. Similarly, food-limited carrying capacity will be higher than the stocking rate that maximizes animal or vegetation productivity, which Caughley (1979) referred to as economic carrying capacity. For example, the maximum rate of animal production would be attained at point α in Figure 3-2B, which might be the objective if animals were being produced for sale or for hunting. Numerous reviews and meta-analyses have shown that density dependence is com- mon in large herbivore populations (Fowler, 1987; Sinclair, 1989; Gaillard et al., 2000). How density dependence affects individual animals and thus life-history traits varies with the ecological context, and effects are stronger in some age-sex classes than in others (­ onenfant B et al., 2009). Effects of increased population density on reproduction are manifested through reductions in pregnancy, fecundity, twinning rate, number of offspring per female, per- centage of females lactating, and young-to-female ratios and through an increase in age of ­primiparity, depending on the species, population, and environmental context. Survival rate responses to population density are common, but they vary among ungulate populations. Effects of Density on Population Processes Several studies of density dependence have included or focused exclusively on equids. In Kruger National Park, South Africa, adult and juvenile zebra survival rates were ad- versely affected by density and favorably affected by rainfall (Owen-Smith et al., 2005). Similarly, zebra population dynamics in Kenya were best explained by a model of rainfall- mediated density dependence (Georgiadis et al., 2003) that involved fecundity and survival. An unmanaged horse population in Argentina exhibited density-dependent responses. R ­ educed fecundity was the primary response to increased density. Adult female survival was also reduced at higher densities, but to a lesser degree (Scorolli and Lopez Cazorla, ­ 2010). In a feral donkey population in Australia, fecundity was high and not related to

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64 USING SCIENCE TO IMPROVE THE BLM WILD HORSE AND BURRO PROGRAM FIGURE 3-2  (A) Example of logistic population growth, with R = 1.18 and K = 300. Population size N and the annual population increment ∆N are plotted against time. Point α is the inflection point, at which population growth begins to decrease as the population approaches K. The corresponding point β shows that annual population increment is maximal at the inflection point. (B) Plot of annual population increment against population size, in which point α is the population size that maximizes the annual increment.

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POPULATION PROCESSES 65 density; however, ages of males at sexual maturity and juvenile mortality increased at higher densities (Freeland and Choquenot, 1990; Choquenot, 1991; also noted in Bonenfant et al., 2009). Pregnancy rates declined at higher densities in horses in the eastern United States (Kirkpatrick and Turner, 1991). In Nevada, it was not uncommon for 2-year-old mares to foal, in contrast to earlier evidence indicating foaling did not begin until the age of 3 (Berger, 1986; Garrott et al., 1991). Garrott et al. (1991) argued that age at first reproduction is more likely to be earlier when forage is more abundant and when competition for for- age is reduced. Jenkins (2000) analyzed data from the Granite Range and Pryor Mountain horse herds and reported evidence that population growth rate decreased with increasing population. Roelle et al. (2010) confirmed those findings in the Pryor Mountain horse herd. Thus, density dependence appears to take a variety of forms in equids. Responses to density are often age-specific. Gaillard et al. (1998) reviewed evidence related to the conceptual model proposed by Eberhardt (1977) in which density effects on population vital rates (e.g., birth and death rates) would occur first in juvenile survival, then in age at first reproduction, then in reproductive rates of prime-aged (most highly reproduc- tive) adults, and finally in adult survival. They noted that Fowler’s (1987) review supported Eberhardt’s model. The Gaillard et al. review provided further support of the model and reported that survival of prime-aged adults is relatively invariant whereas juvenile survival varies considerably from year to year. They reported that the pattern of high, stable adult survival and variable juvenile survival is observed in a wide variety of environments regard- less of whether mortality is density-dependent or density-independent. They noted that higher annual variation in juvenile survival as compared to adult survival can arise from multiple causes including increased vulnerability to predation, drought, harsh winters, and ­ factors causing low birth weights and early growth rates. In an unmanaged horse population in Argentina that was approaching carrying capacity, fecundity was affected by density and rainfall, but adult, juvenile, and foal survival rates were not (Scorolli and Lopez Cazorla, 2010). Although juvenile survival varies more than adult survival, population growth rate is highly sensitive to variations in adult survival, less sensitive to changes in juvenile survival, and moderately sensitive to changes in fecundity (Gaillard et al., 2000). Possible Effects of Domestication It is possible that domestication has selected for forms of density dependence that are different from those in undomesticated populations. Flux (2001) proposed that the tendency to self-regulate differs between feral and “wild-type” populations. It is believed that domestication of European rabbits by monks for over 600 years has led to feral popula- tions that have been observed at densities of up to 200/ha in Australia and New Zealand (Thompson and King, 1994), whereas “wild” species seldom reach 4/ha. However, it is also likely that introduced rabbit populations in those locations are less affected by preda- tion and disease. Other feral species also reach higher densities than their closest “wild” relatives, such as goats, pigs, cats, and domestic pigeons. Many of those species have been implicated in severely detrimental effects on habitats and native species (Flux, 2001). Genetic history may contribute to the reproductive response of free-ranging equids to resource scarcity. A population of unmanaged horses in the Camargue (France) declined in body condition because of scarce resources, and this led to reduced foal and mare sur- vival without a concurrent decline in fecundity (Grange et al., 2009). The authors pointed out that that pattern is different from the one in wild, nonferal ungulate populations, in which fecundity decreases well before adult survival as resources become more limiting. Other domesticated species, such as cattle, have shown the same pattern as the Camargue

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66 USING SCIENCE TO IMPROVE THE BLM WILD HORSE AND BURRO PROGRAM horses. The authors argued that domestication has selected for reproduction over survival even when resources are scarce. As a result, feral populations are more likely to oscillate strongly, and the tradeoff of decreased adult survival may make them more vulnerable to harsh environmental conditions. Nutritional and Physiological Mechanisms Fowler’s (1987) review indicated that food shortage is the primary factor in density dependence. The mechanisms through which food limitation affects population vital rates are most likely effects of poor nutrition, energy balance, and body condition on reproductive processes and survival rates (e.g., Gaidet and Gaillard, 2008). Poor nutritional status may also impair animal feeding and predator avoidance and increase susceptibility to adverse weather. Feral donkey populations in Australia were regulated by food-limited juvenile mortality, which in turn was related to the nutritional status of lactating females (Choquenot, 1991). In an unmanaged population of horses in the Australian Alps, population growth rate declined as numbers increased because of decreased fecundity and decreased adult and juvenile survival (Dawson and Hone, 2012). Those response variables were related to body condition and available food, and mean body condition correlated positively with forage biomass. In the Pryor Mountains, foal survival rate was positively related to precipitation, and this suggests a link to forage production and availability mediated through the condi- tion of the mares (Roelle et al., 2010). The authors cited several other studies, including Garrott and Taylor’s (1990) study of the horse populations in the Pryor Mountains, whose results suggested that forage availability can affect mare condition and thus foaling rates. In addition to the total quantity of food, the quantity of high-quality food items may be diminished when populations are near carrying capacity. When an Australian donkey population reached carrying capacity, females ingested a diet of low nutritional value, whereas those in a population below carrying capacity were able to ingest a nutrient-rich diet (Freeland and Choquenot, 1990). Low diet quality resulted in low levels of stored n ­ utrients in the females, which impaired their ability to raise offspring. When resources are scarce, females are induced into anestrus as a result of poor body condition (Ginsberg, 1989). Birth sex ratios may be affected because mares in poorer con- dition have more female foals (Cameron et al., 1999). The effect of body condition on sex ratio probably occurs at conception. The age at first reproduction and reproductive rates of 2- to 4-year-old horses are affected by competition for forage, which reduces the amount of forage per individual and thus increases the time needed for individuals to attain sexual maturity (Garrott and Taylor, 1990). Saltz et al. (2006) reported that rainfall during the year before conception and drought conditions during gestation were important determinants of reproductive success in Asiatic wild ass. They focused on rainfall before conception be- cause females in poor condition would not go into estrus. To summarize, the causal pathways underlying density dependence begin with popu- lation size (Figure 3-3). Climatic conditions and spatial accessibility determine the avail- ability of forage for herbivores. Population size affects the amount of forage available per animal: as population size increases, forage per animal declines; this results in reduced forage intake and reduced body condition, which affect survival rates and natality. Behavioral Mechanisms There are two fundamental mechanisms of behavior-mediated density dependence: in- creased dispersal at high densities and changes in social interactions that affect reproduction.

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POPULATION PROCESSES 67 FIGURE 3-3  Nutrition-based mechanisms underlying density dependence and density independence. The role of dispersal in density dependence remains uncertain because there have been few studies (Bonenfant et al., 2009). Duncan (1992) found no evidence of a social mecha- nism that regulates equid populations below levels 3-3 NEW by their food resources. Figure determined However, others have found that increased social stress at high density may contribute to density dependence (Linklater et al., 2004). Tatin et al. (2009) found that reduced space can slow the growth of a population of a Przewalski’s horse herd before forage becomes limit- ing. They suggested that reproduction decreased as a result of mare dispersals to avoid incest (Monard and Duncan, 1996). Where populations are spatially unbounded, dispersal can forestall density-dependent control as long as there are places where populations are small and individuals in crowded locations can disperse (Owen-Smith, 1983; Pulliam, 1988). Such source-sink population complexes where emigration keeps densities low will be common where environ­ ental m forces—ranging from physical factors, such as climate, to biological factors involving p ­ redators—operate over large areas. But where there are boundaries to dispersal, as on n ­ atural islands or habitat islands created by human landscape change, densities can in- crease to a point at which feedback from crowding lowers fecundity and adult and juvenile survival. Crowding changes behavior in many ways among horses and burros. In Nevada, high equid densities were associated with increased incidences of confusion, separation, and desertion of foals by mares at water points in the dry season (Boyd, 1979). Berger (1983b) reported that social instability, specifically high rates of turnover among harem males, ad- versely affect female reproductive success and patterns of age-specific fecundity. He also indicated that increased levels of sexual harassment can lower female body condition and disrupt normal endocrine function. By virtue of their hindgut fermentation system, equids can subsist on low-quality vegetation, and they typically compete by maximizing intake relative to other animals (Rubenstein, 1994). However, when densities increase, individual agonistic interactions increase, and this reduces time available for foraging and thus com- petitive ability. Equid females rely on male protection to increase time spent in feeding, and

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68 USING SCIENCE TO IMPROVE THE BLM WILD HORSE AND BURRO PROGRAM this increases the likelihood that foals will survive to the age of independence (Rubenstein, 1986). Thus, any interference that impinges on a female’s ability to forage can lower body condition and reduce fecundity and survival. Moreover, because band stability increases a female’s long-term reproductive success (Rubenstein and Nuñez, 2009), disturbance that leads to more rapid turnover in the tenure of harem males or increased competition among females that leads to female movements among groups will alter important demographic vital rates. Including Density Dependence in Models Density dependence has been considered in a number of models of ungulate popula- tion dynamics. The trajectory of an unmanaged population of horses in Argentina was successfully modeled by fitting a simple logistic equation with a best-fit intrinsic rate of increase and carrying capacity (Scorolli and Lopez Cazorla, 2010). Georgiadis et al. (2003) developed a model of zebra populations that included density dependence in the form of a ratio of rainfall (as a surrogate of food availability) to density. The inclusion of that density-dependent term improved model accuracy despite the large fraction of variation that was explained by rainfall alone. Rubenstein (2010) modeled Grevy’s and plains zebra populations. Density dependence was solely through age at first reproduction, inasmuch as population growth rate is very sensitive to the number of 3-year-olds reproducing. Overall fecundity was linked to annual rainfall. Density dependence was statistically significant in models of four horse populations (Eberhardt and Breiwick, 2012): Equus ferus caballus in Argentina (Scorolli and Lopez Cazorla, 2010), the Camargue (Grange et al. 2009), and Oregon (Eberhardt et al., 1982) and Equus ferus przewalskii in a fenced area in France (Tatin et al., 2009). Density dependence in the population dynamics of Serengeti wildebeest was modeled by Mduma et al. (1999). Density dependence was most strongly exerted through adult mor- tality, and the primary cause of death was undernutrition. Thus, mortality was ­ odeled as m a function of food per capita, and food supply was modeled as a function of rainfall. The model predicted a period of population growth following a period when population size was reduced below food-limited carrying capacity by rinderpest.2 Projected population d ­ ynamics varied within a wide range as a result of rainfall and food-supply variation, but the projected population nevertheless reached maximal levels because of density-­dependent feedback. Lubow et al. (2002) fitted a series of alternative population projection models to popula- tion data on elk in Rocky Mountain National Park. Logistic regression was used to estimate recruitment (the number of individuals added to a population through births) and survival rates of calves and survival rates of each sex and age segment as functions of population size and seasonal temperatures and precipitation. Because of the effects of population den- sity in the models, populations stabilized at some upper limit, which the authors identified as the carrying capacity. The primary mechanism of density feedback was a nearly linear decline in calf recruitment followed by sharply declining calf survival. An approach to the modeling of time-varying carrying capacity for Yellowstone elk populations was based on temporal variations in food availability (Wallace et al., 1995, 2004; Coughenour and Singer, 1996b). Food availability was affected by spatial heterogene- ity, spatial overlap of elk, and spatially variable food availability. The latter was affected by the distributions of snow depth across the landscape throughout winter, which was affected 2  An often fatal viral disease that affects even-toed ungulates.

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POPULATION PROCESSES 69 by snowfall and temperature, which in turn were related to elevation. The effect of snow depth on forage-intake rate was explicitly represented. An energy-balance model was used to derive temporal changes in elk body condition (fat reserves) on the basis of the balance of energy intake and expenditure. Mean body condition was used to determine the fraction of animals in a normally distributed population that would die because of extremely low body condition—an approach originally developed by Hobbs (1989). A similar idea was extended into actual population-dynamics modeling. A metaphysi- ological modeling approach was developed to represent the effects of energy storage on population dynamics (Getz and Owen-Smith, 1999; Owen-Smith, 2002a,b). Because ani- mals and plants can store energy in body tissues, they have a reserve for use in times of food shortage. The approach links animal energy reserves to population dynamics; the reserves alter population dynamics, for example, through an increase in mortality when there are food shortages in the environment. In an ecosystem modeling approach (Coughenour, 1992, 1999, 2000, 2002; Weisberg et al., 2006), the energy balance of the herbivore population is simulated as an outcome of for- age intake and energy expenditure. The energy balance determines storage (fat) reserves, a measure of body condition. Condition in turn affects survival and fecundity. Forage intake depends on forage-biomass density, which establishes a link between population dynamics and forage. This type of model is explained in greater detail in Chapter 6. Some equid population modelers have avoided considering density dependence and food-limited carrying capacity because populations are limited by other factors. Saltz and Rubenstein (1995) modeled Asiatic wild ass populations with a Leslie matrix, but be- cause the populations were so small relative to the expansive area available, it was unlikely that density dependence was important, so it was not included in the model. Although the WinEquus model that is used by BLM has the capability to consider K (carrying capacity), it is rarely invoked in most BLM applications of the model because populations are always held below food-limited capacity by management removals (see Chapter 6). Gross (2000) ignored food limitations and carrying capacity in his individual-based model of the Pryor Mountain herd. He presumed that horse populations will be managed below food-limited carrying capacity and therefore not allowed to self-regulate. Linklater et al. (2004) also did not attempt to consider density dependence in their model, although it was useful for esti- mating population growth rates below carrying capacity. The assumption that most BLM-managed populations are below food-limited carry- ing capacity and thus unaffected by density dependence appears to be reasonable given that management has heretofore aimed to ensure the prevention of rangeland deteriora- tion, largely interpreted as preventing overuse of the forage and habitat (see Chapter 7). However, an outcome of this situation is that few data or modeling studies have provided information on outcomes of density dependence in horse or burro populations on lands under the purview of BLM. Although density dependence has not been a concern in BLM- managed HMAs and models, it will be necessary to include it in any model that addresses the question posed to the committee regarding self-limitation. DENSITY-INDEPENDENT POPULATION CONTROLS Large herbivore population dynamics are generally influenced by a combination of stochastic environmental variation and population density (Saether, 1997). Unmanaged or minimally managed populations should be expected to fluctuate about some mean tendency in quasiequilibrium, and the degree of fluctuation will depend on the degree of climatic variability. The dynamics of more intensively managed populations can also

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70 USING SCIENCE TO IMPROVE THE BLM WILD HORSE AND BURRO PROGRAM be expected to vary in response to density-independent factors, inasmuch as density-­ independent effects are in play irrespective of whether populations are managed to levels below which density dependence takes effect. Density independence is often incorporated into predictive models of equid popula- tion dynamics. Saltz et al. (2006) applied a Leslie matrix model with demographic and environmental stochasticity to an Asiatic wild ass population in Israel. Annual precipitation during the year before conception, drought conditions during gestation, and population size determined reproductive success. They reported that increased rainfall variability in global climate-change scenarios increased extinction probability by a factor of nearly 10. The widely used WinEquus population model (see Chapter 6) incorporates density inde- pendence as stochastic variation in recruitment and survival. At the other end of the model- complexity spectrum, the ecosystem modeling approach described in Chapter 6 represents density independence by simulating climatically driven variations in forage production and effects of snow cover on forage availability. Effects of Climatic Variability Variable precipitation and winter weather conditions can have marked effects on horse and burro population dynamics. Precipitation affects equids indirectly through its effect on total forage biomass production and the length of time that forage remains green and more highly nutritious (Figure 3-3). Winter weather can act directly on horses and burros through thermal stress, but more often it acts indirectly as snow cover affects forage availability. A stage-structured model of an elk population in Yellowstone that included calf, cow, and bull elk classes modeled recruitment and mortality of each class by using the best equations determined from forward, stepwise multiple regression analyses and using pre- cipitation amounts and elk number as the independent variables (Coughenour and Singer, 1996a). Winter precipitation was a surrogate for snow cover and later forage availability. The model revealed that expected population trajectories should exhibit wide variation in response to this density-independent regulation. Although a population equilibrium could be predicted and could be interpreted as one measure of food-limited carrying capacity, there was considerable variation above and below the equilibrium value. A series of mild winters, for example, could result in population sizes above mean K, and the converse would be true in a series of severe winters. Precipitation appears to have a substantial influence on equid populations. Berger (1986) could find little evidence of density dependence in his data on the Granite Range HMA and suggested that responses to weather variations were overriding and confounding. Roelle et al. (2010) reported that foal survival rate in the Pryor Mountain Wild Horse Range was positively related to precipitation, probably because of the effects of variable forage produc- tion on mare condition. They noted that other investigators had suggested that forage avail- ability can affect foaling rates in this manner (Green and Green, 1977; Nelson, 1978; Berger, 1986; Siniff et al., 1986; Garrott and Taylor, 1990). Horse populations in ­ ustralia possibly A increased by a factor of 4 during good rainfall years in the 1970s (­ erman, 1991), and dry B conditions and more intense management reduced the population by 70 to 80 percent in the central part of the country. A 10- to 20-percent birth rate is probably realistic in poor years, and a 25- to 30-percent birth rate in good years (Berman, 1991). Joubert (1974) observed lower recruitment rates in a zebra population in dry years and a large dieoff during a drought. Owen-Smith et al. (2005) reported that juvenile survival was sensitive to rainfall variability in most of 10 African ungulate species, and there was no evidence of density dependence. Rainfall also affected adult survival in several declining species.

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POPULATION PROCESSES 71 Density-independent mortality was documented by Berger (1983a) in the Granite Range of Nevada. Two horse groups perished as a result of severe winter snowstorms. High-altitude, snow-induced mortality may be common. He concluded that unpredictably heavy snow accumulation is a principal mortality agent in the Granite Range, as it may be elsewhere in the Great Basin. Berger (1983a) referred to the winter of 1977, when an esti- mated 300 horses (50 percent of the population) died in the Buffalo Hills near the Granite Range. Berger (1986) reported a pattern of low mortality in most years but markedly higher mortality in occasional years of bad weather. In Wyoming’s Red Desert, abortions and still- births after a severe winter reduced natality by one-third (Boyd, 1979). Reduction in Equilibrial Tendencies by Density Independence In climatically variable environments, the importance of density-independent pop- ulation dynamics increases. The implication of strong density independence is that, in c ­ limatically variable environments, herbivore populations should not be expected to reach a steady state in which population density is in stable equilibrium with forage production. Climatic variations include severe winters and droughts. When the coefficient of variation of ­ nnual rainfall, and presumably food availability, exceeds 30 percent, population size a is less likely to be determined by mean food-limited carrying capacity (Caughley, 1987; see also the section “Understanding Ecosystem Dynamics” in Chapter 7). Saether (1997) also theorized that lags in the responses of populations to environmental variations, in the absence of predation, will make a stable equilibrium between ungulates and their food ­ esources unlikely. As a result, horse populations may not necessarily decline rapidly r during moderate droughts despite reductions in plant growth, and the grazing pressure, expressed as a percentage offtake, may periodically increase above average values. Ellis and Swift (1988) proposed that plant-herbivore systems in climatically variable environments are unlikely to be equilibrial and that traditional concepts of food-limited carrying capacity have relatively little value in predicting herbivore population sizes and dynamics in such environments. They proposed that a herbivore population in an environ- ment subject to periodic droughts is periodically reduced to a low level independently of density. The population then recovers slowly until the next drought causes another reduc- tion. As a result, the population is kept below food-limited carrying capacity—it is unable to use available food resources fully because of low density. That idea was supported by a model of zebra population dynamics (Georgiadis et al., 2003) that provided realistic predictions for 2 decades (Georgiadis et al., 2007). The model captured the fundamental mechanism of rapid population decline during dry periods and slow increase during wet periods. The greater the variability in rainfall, the greater the proportion of time that the population spends below carrying capacity. The Ellis and Swift (1988) study generated controversy: some interpreted it to sug- gest that plant-herbivore systems would be generally nonequilibrial and herbivore popu- lations would naturally be held below food-limited carrying capacity and thus below sizes that would cause overgrazing and degradation. The conclusions of Ellis and Swift, however, were limited to environments that had a high degree of climatic variability, and the implication was that such systems have nonequilibrial tendencies, not that they are absolutely nonequilibrial. Illius and O’Connor (1999, 2000) showed that herbivore popula- tions in drought-prone environments would be “disequilibrial,” still in quasiequilibrium with critical food supplies during dry periods. Thus, plant resources should appear to be lightly used during wet periods, and on the average a small fraction of plant growth should be used. Illius and O’Connor recognized the importance of key resource areas on the

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82 USING SCIENCE TO IMPROVE THE BLM WILD HORSE AND BURRO PROGRAM Compensatory Reproduction Compensatory reproduction in response to gathers is likely in any population that exhibits density dependence. To the extent that a population is being regulated by food supply, decreased density will provide more forage per individual, increasing body con- dition, reproduction, and survival and thus population growth rate. Choquenot (1991), in a study of feral donkeys in Australia, reported that population growth was regulated by food-related juvenile mortality. Dawson and Hone (2012) advised that compensatory responses in survival, fecundity, and age at first reproduction in the population should be considered in any management program. In particular, they were referring to the fact that their data showed that survival and fecundity were increased and age at first reproduction decreased at lower densities, so it is likely that reductions in density due to culling will have the same effect. The response of population growth rate to increased density must be known in order to predict the degree of compensatory growth that can be expected at a given popula- tion density. If the population size is above the theoretical inflection point of the logistic growth trajectory (point α in Figure 3-2A), reductions will increase the annual population growth increment. However, if the population size is below the theoretical inflection point, reductions will decrease the annual growth increment. Various models of density depen- dence, as discussed above, could be used to predict the degree of compensatory growth resulting from animal removals in relation to the population size and the rate of removal. Gathering has also been shown to have varied indirect effects on reproductive success. In Idaho and Wyoming, foaling success rates were higher among gathered horses than among horses that were not gathered (Hansen and Mosley, 2000). Foaling success rates in Idaho were 29 percent, 31 percent, and 43 percent for mares not gathered, mares gathered and adopted, and mares gathered but released, respectively. In Wyoming, foaling success rates were 29 percent, 42 percent, and 48 percent in those groups. There were no statisti- cally significant differences among groups, however, most likely because samples were small in relation to high variance. Effects of gathers on body condition, lactation status, and pregnancy were not reported. It is important to note that such results, if real, would most likely be attributable to forage limitation and lower body condition among ungathered than among gathered mares. In contrast, in another study, foaling was lower among gathered horses. Pregnant mares that were gathered and removed had substantially lower reproduc- tive success than ungathered mares at one site, and gathered and released mares had less reproductive success than ungathered mares at a second site (Ashley and Holcombe, 2001). The authors speculated that that was a result of loss of fetuses due to the stress of being gathered and handled for a long period. Animals that were removed were transported 246 km to a holding facility, where they were held for 21 days before adoption. A number of miscarriages were observed at the holding facility. Kirkpatrick and Turner (1991) compared a population managed with annual foal r ­ emovals on Chincoteague Island, Virginia, with an unmanaged population on Assateague Island, Maryland. Management-level applications of PZP did not begin on Assateague ­Island until 1994, after the 1989 study (Turner and Kirkpatrick, 2002.) They hypothesized that there would be greater fetal losses in the unmanaged population because of the concurrent physi- ological stresses of lactation and pregnancy (weaning rarely occurs before 1 year and it com- monly occurs at 2 years). They estimated pregnancy and foaling rates of 40 free-ranging mares on Assateague Island and 48 managed mares on Chincoteague Island and found a higher foaling rate in the Chincoteague population because a greater percentage of mares foaled annually (80 percent). The hypothesis of greater fetal loss was not supported: there

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POPULATION PROCESSES 83 was no difference between the two populations. However, pregnancy and foaling rates in the Chincoteague population were nearly double those in the Assateague population. The authors suggested that the greater pregnancy and foaling rates were due to cessation of lactational anestrus and that the cessation of lactation in mares that had their foals removed resulted in these animals going back into estrus. However, the authors provided no evidence that lactating mares were not cycling. Another possible cause of increased pregnancy and foaling in the managed population is reduced energetic demands due to cessation of lacta- tion. In contrast, Wolfe et al. (1989) used plasma progesterone measurement to examine preg- nancy rates in 553 free-­ anging mares. They found no difference in pregnancy rate between r lactating and nonlactating mares. Kirkpatrick and Turner (1991) suggested that the reason that no difference was found was that the method for detecting pregnancy—measurement of plasma progesterone—can be inaccurate. Although the method is widely used for detecting ­ pregnancy in other species, it is not reliable for equids. It is also known that although lacta- tional anestrus does occur, it is very uncommon, and most mares resume cycling 5-9 days after foaling. In summary, it is possible that population management via foal removals may result in increased fecundity, but evidence of a lactational anestrus mechanism is lacking. It is also possible that pregnancy and foaling rates are reduced in lactating mares because of the lower body condition that results from the energetic demands of lactation. Because horse populations on BLM lands are not managed through foal removals, this form of compensa- tory reproduction probably has little relevance. The effects of PZP on population growth, longevity, and body condition were studied over a 10-year period on Assateague Island (Turner and Kirkpatrick, 2002). PZP clearly reduced foaling rates among contracepted animals. However, mortality in mares and foals decreased, and two older age classes appeared (21-25 years and over 25 years), which indicated an increase in longevity. Body-condition scores of nonlactating mares increased substantially but those of lactating mares did not change. The cause of the decrease in foal mortality was unclear, but it could have been due to increased body condition of the mares. Body condition of untreated mares, or of treated mares in which the treatment has lost effec- tiveness, could increase because of reduced competition for forage. In treated mares, contra- ception reduces the energetic costs of reproduction, and this also results in increased body condition and longer life span (Gray and Cameron, 2010). Nuñez et al. (2010) also found that treated mares had better body condition than untreated mares; this could result in an extended breeding season and increased chance of conception in animals that have low PZP antibody levels. Thus, the favorable effects of increases in body condition, longevity, ­ foal survival, and length of breeding season on population growth rate could offset to some extent the adverse effects of contraception on reproduction and population growth rate. That might be termed compensatory population growth; however, it is unlikely that the degree of compensation would be sufficient to overcome the degree to which contraception reduces reproduction and population growth. Effects Related to Ability of Animals to Disperse Ecologically adaptive movement patterns are still exhibited by many extant horse populations. Free-ranging horses in Nevada move from low to high altitudes in spring or early summer after the wave of vegetation green-up, and they move to low elevations in fall (Berger, 1986). However, changes in land ownership and allocations of lands for livestock use may interfere with traditional movement patterns and may preclude the re-establishment of natural movements, ones that presumably exist in truly wild and free- ranging equid populations.

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84 USING SCIENCE TO IMPROVE THE BLM WILD HORSE AND BURRO PROGRAM The importance of movement for coping with drought is illustrated by observations in Namibia (Gasaway et al., 1996). Ungulates, including zebra, maintained near average mortality during severe drought because they could move over large areas and find food reserves in areas not regularly grazed. Low ungulate densities and clumped distribu- tions were responsible for the existence of infrequently used areas that served as drought reserves. Such dry-season food reserves were also important in keeping mortality low in Kruger National Park during a drought in 1982-1983 (Walker et al., 1987). In contrast, popu- lations in two other reserves, which were near their food-limited carrying capacity before the drought, lacked such lightly grazed food reserves and suffered high mortality (Walker et al., 1987, as noted by Gasaway et al., 1996). An important question is the extent to which horse (and cattle) grazing can be managed to compensate for losses in natural movement patterns, which presumably were important determinants of the grazing regimes experienced by plant species that evolved during or before the Pleistocene in the presence of large herbivores. The mix of private, tribal, and public ownership often fragments landscapes that might have been more natural, expan- sive grazing areas. Differences between agency policies may exacerbate the fragmentation. Fencing can interfere with movement to other areas when forage is depleted and cause heavier intensities and frequencies of herbivory than would occur otherwise. Confinement or restrictions on migration or dispersal movements will probably result in a plant-herbivore system that has different dynamics from one that does not have such constraints. In general, the smaller the area that a population is limited to, the greater the potential for a self-regulating system with undesirable qualities, such as population crashes and population oscillations. Spatial constraints can lead to reductions in vegetation cover to lower levels than would be seen otherwise, followed perhaps by vegetation recovery after horse populations decline in response to food shortages. However, there is also an increased likelihood of irreversible shifts in vegetation communities, in accordance with recent theory and observations of alternate stable states, to communities dominated by invasive plant species, by shrubs, or by bare ground with little or no seed bank to support recovery (see the section “Understanding Ecosystem Dynamics” in Chapter 7). In contrast, such generalizations as “confinement will result in range degradation” are also unwarranted. The degree of confinement, the areas that are inaccessible, the availabil- ity and dispersion of water, climate, and vegetation productive potential can all modify the response. Confinement may have little or no consequences or great consequences, depend- ing on those factors. Additional challenges arise from migration and dispersal across HMA boundaries. A designated HMA may constitute the core range of a herd or population, but dispersal movements outside the HMA are possible. Dispersing animals may move onto areas that are subject to conflicting land uses or management objectives. Conversely, movements of animals into an HMA from surrounding areas that are under different management juris- dictions can work at cross purposes to the management objectives of an HMA. Where such cross-jurisdictional movements occur, it is necessary to establish co-operative relationships among adjacent landowners. CONCLUSIONS Large herbivore populations are influenced by density dependence, density- independent factors, and predation. Most large herbivore populations show some degree of density-dependent limitation, particularly when predation is low. Likewise, many wild equid populations exhibit density dependence. Density dependence has operated in some

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POPULATION PROCESSES 85 free-ranging horse and burro populations in the western United States and elsewhere. The primary way that populations self-regulate or self-limit is through increased competition for forage at higher densities, which results in smaller quantities of forage per animal, poorer body condition, and decreased natality and survival rates. Behavioral mechanisms can also contribute to density dependence, particularly increased dispersal, and increased agonistic interactions and decreased band stability may interfere with foraging and repro- ductive success. Clearly, it is possible to incorporate density dependence into models as a population process. Although it has been omitted from some models because populations were believed to be held below food-limited carrying capacity by management or other factors, it was found necessary to include in others when it was an important component of population dynamics, particularly in wild, unmanaged populations of equids. There are basically two approaches to modeling density dependence. One is through the inclusion of a direct effect of density, often in relation to an assumed or derived food-limited carrying capacity (K), which must be empirically determined for the system in question. Although total forage biomass may be estimated through vegetation sampling (see Chapter 7), there is still a need to demonstrate how population variables respond to diminished forage biomass; thus, there is a need for empirical studies. The other approach is through mechanistic model­ing of com- petition for limited forage at higher densities and its effects on survival and reproduction. The first approach is more site-specific, but in either case, there is a need to assign values to parameters based on data from case studies of populations that are ­ llowed to reach levels a at which density dependence takes effect. However, there are few such case studies. The committee suggests that existing situations of self-limited populations be studied or that an experiment be conducted to enhance understanding of such systems. Density-independent variation is also an important consideration. Most equids under BLM purview inhabit arid and semiarid environments characterized by high variability in annual precipitation and thus forage. In some environments, variable snow cover is also an issue. When climatic variation is high, plant-herbivore systems become increasingly disequilibrial. In such environments, density dependence may be relatively weak, and population dynamics may be driven largely by density independence, with resulting large variability in survival and recruitment. Populations may also be driven below any theoreti- cal food-limited carrying capacity that is based on mean forage biomass. Predation can be important in controlling the sizes of some populations of wild equids, but the degree of control is highly variable. In intact equid ecosystems in Africa, zebra populations are probably limited to some extent by predators, but climatically influenced variations are strong in comparison, so it is difficult to establish the effect of predation quantitatively. In some North American free-ranging horse populations, there clearly is predation by mountain lions. However, the degree of limitation has not been established. More problematic is the fact that mountain lion ranges are not widespread throughout the principal habitats of the horses under BLM purview. The limitation of the range is not nec- essarily due to human hunting or extirpation, inasmuch as these habitats may simply be poor habitats for mountain lions. Mountain lions are ambush predators, requiring habitats with broken topography and tree cover, whereas horses tend to use areas that have exten- sive viewsheds. Wolves are cursorial and capable of chasing prey across open, flat topogra- phy. They have a great impact on a few populations on other continents and certain areas in Canada, but their distribution in the western United States has been severely reduced by humans, and very few, if any, free-ranging horse habitats are occupied by wolves. Several case studies have demonstrated the potential outcomes of a self-limited equid population. Equids invariably have some effect on vegetation abundance and composition

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86 USING SCIENCE TO IMPROVE THE BLM WILD HORSE AND BURRO PROGRAM (see Chapter 7). Vegetation cover is usually reduced, and often there are shifts in species composition. There is limited evidence that erosion rates are increased. However, none of the case studies included scientific experimentation that showed that the changed vegeta- tion cannot persist over a long period of time or that complete loss of vegetation cover is inevitable. Case studies have also reported increased competition with other wildlife species and adverse effects on habitats of some species. In some cases, vegetation changes were probably due in part to historical livestock grazing. In other cases, horse population reductions were not shown to reverse vegetation changes. The results of the case studies are consistent with theoretical predictions that when a herbivore population is introduced, vegetation cover will initially change and productiv- ity will often be reduced by herbivory. In some environments, however, moderate levels of herbivory have little effect or even beneficial effects on plant production (see Chapter 7). Vegetation production may decline, but it may stabilize at a lower level as herbivore popu- lations come into quasiequilibrium with the altered vegetation cover. The reduction in plant cover may be great enough to cause accelerated soil erosion, an important indicator of re- duced rangeland health. If erosion reduces soil water-holding capacity and soil fertility, the productive capacity of the vegetation and of the forage base will decline and the resulting feedback effects on equid population growth might reduce grazing pressure and further erosion. Whether unmanaged, quasiequilibrial soil-plant-equid ecosystems can persist over a long term on rangelands administered by BLM is unknown, but there are pertinent exam- ples of unmanaged equids in Africa that have persisted for millennia, in some cases despite weak or no evidence of predator limitation. Feedbacks from the plant-soil system to equid population growth must have enough functionality for long-term ecosystem persistence. Such feedbacks may be disrupted by various human activities. Thus, there is a need to be able to predict equid population responses to decreased forage productivity concurrently with vegetation productivity declines in response to erosion in landscape ecosystems that are affected by human activities, such as habitat fragmentation. The literature clearly demonstrates that density dependence due to food limitation will reduce population growth rates in equids and other large herbivores through reduced f ­ ecundity and survival. The total annual population increment will decline at higher densi- ties (Figure 3-2A). Some of the reduction in annual population increment at high densities will probably be due to reduced fertility, and much of the reduction can also be expected to be due to increased mortality. The literature and the case studies show that although den- sity dependence can regulate population sizes, responses will probably include increased numbers of animals in poor body condition and high numbers of animals dying from starvation. Those may be unacceptable outcomes for some stakeholders, particularly those who perceive that they result from human interference with natural processes of disper- sal, access to key forage resources, or predation. If so, it could be argued that humans are p ­ otentially responsible for the starvation and mortality. The committee was charged with addressing the question of compensatory reproduc- tion in response to population controls. As discussed above, it is quite likely that there would be compensatory increases in recruitment and decreases in mortality in response to lower animal numbers, whether because of removals or contraception, because of de- creased competition for forage, and or because of improved body condition. Mares in better body condition can be expected to have higher fertility rates, and foal survival can also be higher. An increased foaling rate has been observed in one population that was managed through foal removals, but the likelihood of observing that response generally is question- able, and, because horse populations on BLM lands are not managed by foal removals, this possibility is irrelevant in any event. Finally, there is no evidence that contraception

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POPULATION PROCESSES 87 stimulates reproduction through physiological mechanisms. On the contrary, the purpose of contraception is to decrease fertility. A managerially important finding was that free-ranging horse populations are often limited by removals to levels below food-limited carrying capacity, so population growth rate could be increased by the removals through compensatory population growth related to decreased competition for forage. Thus, the number of animals that must be processed through holding facilities is probably increased by management. REFERENCES Andreasen, A. 2012. Predation on Feral Horses by Mountain Lions in Nevada. Presentation to the National Acad- emy of Sciences’ Committee to Review the Bureau of Land Management Wild Horse and Burro Management Program, May 14, Washington, DC. Ashley, M. and D. Holcombe. 2001. Effect of stress induced by gathers and removals on reproductive success of feral horses. Wildlife Society Bulletin 29:248-254. Ashman, D.L., G.C. Christensen, M.L. Hess, G.K. Tsukamoto, and M.S. Wickersham. 1983. The Mountain Lion in Nevada. Reno: Nevada Department of Wildlife. 75 pp. Ballard, W.B., D. Lutz, T.W. Keegan, L.H. Carpenter, and J.C. DeVos, Jr. 2001. Deer-predator relationships: A review of recent North American studies with emphasis on mule and black-tailed deer. Wildlife Society Bulletin 29:99-115. Berger, J. 1983a. Ecology and catastrophic mortality in wild horses: Implications for interpreting fossil assem- blages. Science 220:1403-1404. Berger, J. 1983b. Induced abortion and social factors in wild horses. Nature 303:59-61. Berger, J. 1983c. Predation, sex ratios, and male competition in equids (Mammalia: Persiodactyla). Journal of Z ­ oology (London) 201:205-216. Berger, J. 1986. Wild Horses of the Great Basin: Social Competition and Population Size. Chicago: University of Chicago Press. Berman, D.M. 1991. The Ecology of Feral Horses in Central Australia. Ph.D. dissertation. University of New England, Australia. Berryman, A.A. 2003. On principles, laws and theory in population ecology. Oikos 103:695-701. BLM (Bureau of Land Management). 1984. Herd Management Area Plan Pryor Mountain Wild Horse Range. B ­ illings, MT: U.S. Department of the Interior. Boertje, R.D., M.A. Keech, and T.F. Paragi. 2010. Science and values influencing predator control for Alaska moose management. Journal of Wildlife Management 74:917-928. Bonenfant, C., J.M. Gaillard, T. Coulson, M. Festa-Bianchet, A. Loison, M. Garel, L.E. Loe, P. Blanchard, N. Pettorelli, N. Owen-Smith, J. du Toit, and P. Duncan. 2009. Empirical evidences of density-dependence in populations of large herbivores. Advances in Ecological Research 41:313-357. Boyd, L. 1979. The mare-foal demography of feral horses in Wyoming’s Red Desert. Pp. 185-204 in Proceedings of the Symposium on the Ecology and Behavior of Wild and Feral Equids, R.H. Denniston, ed. Laramie: University of Wyoming. Cameron, E.Z., W.L. Linklater, K.J. Stafford, and C.J. Veltman. 1999. Birth sex ratios relate to mare condition at conception in Kaimanawa horses. Behavioral Ecology 10:472-475. Caughley, G. 1970. Eruption of ungulate populations with emphasis on Himalayan thar in New Zealand. Ecology 51:53-72. Caughley, G. 1976. Wildlife management and the dynamics of ungulate populations. Pp. 183-246 in Applied B ­ iology, Vol. 1, T.H. Coaker, ed. New York: Academic Press. Caughley, G. 1979. What is this thing called carrying capacity? Pp. 2-8 in North American Elk: Ecology, Behaviour and Management, M.S. Boyce and L.D. Hayden-Wing, eds. Laramie: University of Wyoming. Caughley, G. 1987. Ecological relationships. Pp. 158-187 in Kangaroos: Their Ecology and Management in Sheep Rangelands of Australia, G. Caughley, N. Shepard, and J. Short, eds. Cambridge, UK: Cambridge University Press. Choquenot, D. 1991. Density-dependent growth, body condition and demography in feral donkeys: Testing the food hypothesis. Ecology 72:805-813. Coughenour, M.B. 1992. Spatial modeling and landscape characterization of an African pastoral ecosystem: A prototype model and its potential use for monitoring drought. Pp. 787-810 in Ecological Indicators, D.H. McKenzie, D.E. Hyatt, and V.J. McDonald, eds. London and New York: Elsevier Applied Science.

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