“Copyright 2009, by the authors of the material, with license for use granted to the Center for Biodiversity and Conservation of the American Museum of Natural History. All rights reserved."

Management of Harvested Wildlife Populations Samuel K. Riffell With modifications by Don White, Jr. Introduction Humans have been harvesting wild populations for the entire extent of human history. In most early human societies, a successful hunt not only fed one’s family, but also brought respect from both family and community (Bolen and Robinson 2002). Although most North Americas and western Europeans today acquire their food that was planted, harvested, and processed by someone else, hunting and harvesting of wild populations will undoubtedly continue. Harvesting wild populations is often controversial, but the ethics of harvesting wild populations is not our primary purpose here. Rather, our objectives are to 1) discuss the reasons for harvesting wild populations, 2) evaluate a variety of common strategies for harvesting, 3) discuss the theoretical foundations for maximum sustainable yield and age- and sex-biased harvests, and 4) understand the effects of harvesting on target and non-target wildlife. Although hunting and harvesting are used almost synonymously in the literature, there can be subtle differences. Hunting usually refers to highly regulated sport hunting. We will define harvest broadly as “removal of animals or plants from a population, usually by humans” (Sinclair et al. 2006). Our definition will include not only regulated hunting, but also a wide variety of human activities that remove individuals from populations—trapping, logging, collection of medicinal plants, collection of animals for the pet trade, subsistence hunting and trapping, commercial harvesting, and illegal take. Reasons for Harvesting There are many reasons for harvesting populations and, most often, they serve some anthropocentric goal. Reasons for participating in hunting range from mere survival in subsistence situations to maintaining a cultural heritage or maintaining a connection with the land and nature. Reasons for harvesting can be summarized in 5 major areas and, in each, the goal of a harvest strategy would be different.

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Nutrition—For many rural populations, especially in developing countries, hunting supplies the primary source of protein in human diets. Subsistence hunting provides substantial nutrients, calories, and protein in 62 countries worldwide (Bennett and Robinson 2000). The anthropocentric goal would be to provide enough sustainable harvest to meet basic nutritional needs.

Economics—Economics can drive harvests in 4 ways. First, for subsistence hunters, the harvest of wild meat represents a source of nutrition that would otherwise have to be purchased (Bennett and Robinson in Robinson and Bennett 2000). Cash money is often scarce in rural communities.

Second, harvests are often conducted with the intent to sell the animals for profit. Such intent can include rural subsistence hunters selling meat for cash, sale to the pet trade, and larger commercial operations. We include both legal and illegal harvest because the ecological effects of both are the same. The goal would be to maximize (or sustain) harvest, and hence profit.

Third, sport hunting produces economic benefits resulting from license sales. Funds from the sale of hunting licenses support game species management programs as well as other programs such as T and E species, nongame, education, and habitat acquisition and management.

Lastly, in 1937, the Federal Aid to the Wildlife Restoration Act (commonly called the Pittman-Robertson Act) placed a federal excise tax on sporting arms and ammunition, with proceeds to be reapportioned to states for wildlife research and restoration.

Recreation—Hunting is often regulated for recreational opportunities, usually in more developed countries. The anthropocentric goal here would be to provide recreational opportunities, although profit can motivate recreational hunting too. With some large mammals and fish, the goal may be to provide “trophy” individuals, rather than a maximum harvest.

Culture—Hunting can be part of a society’s cultural heritage. Hunting can garner respect for the hunter and provider, and produce culturally significant adornments (e.g., feathers) and trophies. In addition, important rituals and celebrations may center on hunting (Bennett and Robinson in Robinson and

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Bennett 2000), with the goal being to ensure a sustainable harvest large enough to provide a reliable harvest for these cultural needs.

Management Tool—Harvests can benefit both humans and ecosystems when they are used as a management tool to preserve populations or to mitigate effects of human activities. Harvests are often an effective way to reduce populations of overabundant wildlife, reduce human-wildlife conflicts, and eradicate invasive and exotic organisms. Sport hunting is commonly referred to as managing with a gun or "trigger management."

For example, historical conversion of land in eastern North America from forest to agricultural land uses has facilitated an increase in Brown-headed cowbirds (Molothrus ater), a nest parasite, which has been shown to contribute to declining populations of some songbirds. For songbirds with small population sizes or limited ranges, removing cowbirds can help sustain populations (Morrison et al. 1999). Similarly, predator removal (i.e., harvesting) has been used to increase breeding success of some waterfowl in some management areas (e.g., Garrettson and Rohwer 2001).

Additionally, non-native, introduced species (exotics) can have profound impacts on native species and ecosystems, such that harvests may be effective over broad areas of habitat. For example, feral hogs (Sus scrofa) can cause great damage to both native ecosystems and agricultural crops, and the only effective means of control currently available is harvest (e.g., Engeman et al. 2007).

The reason for harvesting has profound implications for the particular harvest strategy that should be employed. In sustainable harvesting, the goal is to maintain a positive growth rate so that there is a surplus available to harvest. After harvest, the goal is to sustain a relatively constant population size (r = 0 or λ = 1). Examples include developing sustainable harvesting strategies for wild turkey, black bear, waterfowl, elk, moose, and ruffed grouse.

Sometimes the goal may be to reduce population size. This is often done with invasive or over-abundant wildlife to reduce negative ecological effects, or reduce human-wildlife conflicts. This is wildlife control. An example is the reduction of white-tailed deer, Canada geese, and Snow geese in localized areas well below carrying capacity to reduce crop, garden, and lawn damage.

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A third possible, but less common, goal is to eliminate a population of invasive or exotic species. Here the goal is to harvest unsustainably to eliminate the population. In this case, the goal would be a decreasing population growth rate (r < 0 or λ < 1). Feral hogs in the southeastern U.S. and California provide good examples of elimination management programs.

Principles of Harvesting Wildlife Populations Although we will deal with several general principles of harvesting wildlife populations, it is important to remember that these principles apply to most species and most reasons for harvest. Harvest principles apply to more than just traditional hunted populations, like white-tailed deer, wild turkey, or Bobwhite quail. They also apply to fisheries, invasive species, and plants. In fact, these principles may be applied to almost any situation where individuals are being removed from a wild population. For example, in North America, American ginseng (Panax quinquefolium) is an herbaceous forest plant long thought to possess medicinal qualities. Market demand often results in high levels of harvest from wild ginseng populations. Ginseng has been protected since 1975 under an international treaty known as CITES (Convention on International Trade in Endangered Species of Wild Fauna and Flora), which requires its export to be regulated by the U.S. Fish & Wildlife Service (USFWS). This agency regulates (to some extent) many of the species that are traditionally harvested. The USFWS is mandated to ensure that exported wild ginseng is harvested in a manner that is both legal and not detrimental to the survival of the species. Notice that the phrase “not detrimental to the survival of the species” is simply another way of saying “sustainable.” Although ginseng is a plant, the concepts of population dynamics and harvest management discussed below (i.e., growth rate, carrying capacity, maximum sustainable yield) can be applied just as we would apply these terms and concepts to white-tailed deer, wild turkey, or black bear management.

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Compensatory vs. Additive Mortality Harvest always results in mortality, either through death or through removal from the population (both have identical effects on the population). Compensatory mortality occurs when increased survival, reproduction, or immigration offsets the numerical effects of harvest mortality. Additive mortality occurs when the harvest is additional to (over and above) the normal mortality in the absence of harvest. An example of the potential relationships between hunting mortality rate and realized annual survival is shown in Figure 1. Note that in this population, the background survival rate (i.e., the survival rate in the absence of hunting) is 70%. Hunting is additive when each additional mortality due to hunting decreases survival rate (solid line in Figure 1). Hunting is compensatory when the realized annual survival rate does not change even when hunting mortality takes place (dashed line in Figure 1). Note, however, in our example, hunting is compensatory up to a hunting mortality of 40%. Each hunting mortality over 40% is additive.

Figure 1. Realized annual mortality as a function of hunting mortality rate under compensatory (dashed line) and additive (solid line) conditions.

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These concepts can be expressed as:

St = S0 (1.0 – Ht) Where St is the realized survival rate, S0 is the background survival, and Ht is harvest mortality (1.0 – Ht). For example, assume a harvest mortality of 0.40; the realized survival rate would be: 0.42 = 0.7 (1.0 – 0.4).

To reiterate an important point made earlier, notice that under compensatory mortality (dashed line in Figure 1), the realized survival rate does not change up to a certain threshold of harvest mortality. Up to this point, the population is able to compensate for the harvest mortality (i.e., replace the individuals lost to the harvest) via increased survival of remaining individuals, reduced mortality, or some other population response. Conversely, additive mortality represents additional mortality above and beyond the background mortality. When harvest mortality is additive, it is added to the existing forms of mortality (which are not offset or reduced). There are 2 ways in which mortality can be compensatory. Numerical compensation occurs when some of the individuals harvested are individuals that would have died anyway (see example in Box 1 below). Often there is a surplus of doomed individuals in the population that can be sustainably harvested.

Box 1. Example of Numerical Compensation: Northern Bobwhite quail • Assume a population of 100 bobwhite quail. • Without hunting—

30 quail die annually from natural causes (100 x 0.70 = 70 quail) • With hunting—

30 quail die from hunting (100 x 0.30 = 70 quail) 21 die from natural causes (100 x 0.70 x 0.30 = 21 quail)

• Of the 30 birds harvested, 9 (30 - 21) would have died from natural causes anyway.

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Compensation can also occur when harvest mortality triggers a change in vital rates of the population. This is density-dependent compensation. These changes offset the mortality from harvest. The factors involved are many of the same factors that limit and regulate populations (produce logistic growth patterns) in the absence of harvest. This compensation can occur in several ways: 1. Increased adult survivorship at lower population sizes; 2. Increased juvenile survivorship at lower population sizes; 3. Increased reproductive output at lower population sizes via:

a. Increased litter/clutch sizes, and b. Increased reproduction of yearlings;

4. Increased immigration rates, or “spatial compensation”, from surrounding areas.

Examples of this are common in wild populations (e.g., Sinclair et al. 2006, Mills 2007). In Yellowstone National Park, winter calf mortality is higher when elk populations are high and summer recruitment (new individuals added to the population) is lower (Coughenour and Singer 1996). Thus, reducing the population through harvest could promote increased survival and increased recruitment. Such examples are not limited to wildlife populations. Red maple seedlings have much higher germination rates when seed density is low compared to high seed density (Lambers et al., 2002). Thus, significant seed harvest (e.g., by insect or mammal predators) might be compensated for by higher germination rates. Review of Logistic Population Growth You are already familiar with the exponential and logistic growth equations. The logistic growth equation is a modification of the exponential growth equation in that it includes a density-dependent feedback through a “carrying capacity” term

KN-K that slows population growth at high population densities by acting as a

multiplier to the exponential growth equation:

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.K

N-K rNdtdN

=

Remember, as

KN-K approaches 1, population growth approaches 0 and as the

population size increases,

KN-K gets closer to 0. The relationship between N

and K produces a sigmoid curve (Figure 2). Figure 2. Population size vs. time from the logistic equation. Under logistic growth, the relationship between the realized growth rate and population size is linear (Figure 3). Realized growth rate is the rate at which the population is growing given the effects of carrying capacity (K) at that population

size. As population size (N) nears carrying capacity (K),

KN-K gets increasingly

smaller, so the growth rate is also smaller (Figure 3). This accounts for the density-dependent growth rates of populations that are limited by intrinsic forces like competition for food or space.

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Figure 3. Population size vs. per capita growth rate from the logistic equation. An important aspect of the logistic growth model for harvesting populations is recruitment, or number of new individuals added to the population. Notice the number of individuals added to the population (absolute recruitment) first increases, peaks, and then decreases (Figure 4). Identifying the population size at which recruitment peaks is critical for harvest strategies because this is where the highest number of individuals can be sustainably harvested. This is called the maximum sustainable yield.

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Figure 4. Yield (recruitment) vs. population size from the logistic equation. Maximum Sustainable Yield The top of the recruitment curve (Figure 4) represents that population size at which the maximum sustainable yield (MSY) is possible. The MSY is the largest number of individuals that can be removed sustainably. In this example, the MSY is about 25 individuals and the population size at which this can be accomplished is about 525. This is approximately ½ carrying capacity (K/2). Notice that at population sizes larger than 525, fewer individuals can be sustainably harvested. Why? Refer to the logistic population growth curve in Figure 2. The MSY point corresponds to the inflection point in the logistic curve. Notice the relationship between growth rate and population size: 1. At <K/2, growth rates are high, but the population is small. So, few individuals

are actually added (absolute recruitment is low); 2. At >K/2, the population is large, but the per capita growth rate is small. So,

few individuals are actually added (absolute recruitment is low).

An important principle from this analysis of MSY is that it is impossible to simultaneously maximize both population size and harvest yield. This can be a

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difficult concept to grasp: maintaining a moderate-sized population will permit a greater harvest over time than maintaining larger population sizes. It is also important here to recognize and discuss the assumptions of the logistic model (Rockwood 2006). The assumptions are as follows. 1. Carrying capacity is constant. Unfortunately, this is rarely the case in real

populations. Variation in predator populations, climate, and food resources can all result in a slightly (or not so slightly) different carrying capacity each year.

2. Interaction between N and K is instantaneous (no time lags). The logistic model assumes that populations respond instantly as population size approaches carrying capacity and also to changes in carrying capacity. Most species require some period of time to respond numerically. For example, many large, hoofed mammals breed only once per year and may have long gestation periods. So breeding activity that occurs in response to a particular carrying capacity does not produce a numerical response for several months, at which time the carrying capacity may have changed yet again. This is a greater issue with longer-lived species than with short-lived species.

3. Age structure does not affect growth rate. For many populations, certain ages (i.e., very young ages) have different probabilities of surviving (e.g., often young ages have high mortality) and different fecundities. So, different ratios of these age classes can affect growth rate and recruitment.

4. Growth rate changes linearly with population size. In many cases, there are thresholds that occur rather than strictly linear changes. For instance, juvenile survival may be constant up to some threshold population size when resources become scarce.

These assumptions are important to consider because K/2 is a theoretical point unique to the logistic population model. Other models of density-dependent population growth that account for factors like age structure produce different sigmoid-shaped curves. They are all similar, but produce MSY points at population sizes other than K/2.

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Maximum sustainable yield is rarely the best and safest level of harvest. One reason is that carrying capacity is not always constant. As K fluctuates, so does the MSY harvest and population size. If we do not have accurate data about how K and MSY are fluctuating, the risk of over harvest is very high. Simply relying on MSY can be a dangerous strategy! Thus, MSY harvests should always allow for at least a 25% safety margin (Sinclair et al. 2006). Different Concepts of Carrying Capacity There are several different concepts of carrying capacity (Miller and Wentworth 2000), which are important to understand before we proceed any further. 1. Ecological (K) carrying capacity—this is the definition that one most

commonly associates with the term “carrying capacity”. Ecological carrying capacity (K) is the maximum number of individuals of a given population that the resources of the environment can support. It is represented by the asymptote of the logistic regression curve.

2. I-carrying capacity—this is the population size that yields the maximum sustainable yield (MSY) and that occurs at the inflection point of the logistic curve.

3. Minimum impact carrying capacity—this is the population size that minimizes impact on other wildlife or vegetation (without eliminating the population). This definition includes a distinct value component: what is considered an impact relates to societal (human) objections.

4. Optimum carrying capacity—this is the population size that best satisfies human interests and expectations. Most of the time, populations are managed for optimum yield (or optimum carrying capacity) rather than maximum sustainable yield. This carrying capacity can be anywhere along the curve depending on the human interest to be maximized. When MSY is the goal, then optimum carrying capacity = I-carrying capacity. If the goal to be maximized is population size (say for an endangered or recovering species), then optimum carrying capacity = K-carrying capacity.

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Harvest Strategies Fixed-Quota Harvest Strategy Fixed-quota strategies involve harvesting a constant number of individuals each year (Sinclair et al. 2006). This results in 2 “equilibrium points”, or population sizes at which the quota could be harvested. In Figure 5, the Y-axis represents the number of individuals added to the population (recruitment) at a particular population size (this is the same curve generated in Figure 5). Thus, the terms ‘yield’ and ‘recruitment’ are equivalent, and they both represent possible harvests. Figure 5. Recruitment curve for fixed quota strategy. The lower density point is to be avoided because: 1. more effort is required to harvest than at the higher density; and 2. any reduction in density below the lower point is an over harvest, and could

lead to extinction of the population. If quotas exceed MSY, populations would decline to extinction. Quotas must be established based on knowledge of current carrying capacity. What if that information does not exist? Then the quotas would often lead to over harvesting and possibly extinction. Thus, long-term data (many years) about population

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dynamics help to reduce uncertainty about the true values of both carrying capacity and maximum sustained yield. Fixed-Proportion Harvest Strategy Fixed-proportion strategies harvest a fixed percentage of the population each year (Sinclair et al. 2006). Thus, the actual number of individuals harvested each year will vary as the population size varies (Figure 6). Figure 6. Recruitment curve for fixed proportion harvest strategy. A key advantage of this strategy is that it generates sustained yield even with variation in environmental conditions (carrying capacity). When population sizes are high, a high absolute number of individuals are harvested; however, if population size decreases (perhaps due to a harsh winter), the absolute number of animals decreases, even though the proportion harvested stays the same. Fixed-proportion strategies require accurate estimates about annual recruitment and hunter effort, and population size each year. If this information does not exist, the risk of over harvesting is high.

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Constant-Effort Harvest Strategies Constant-effort strategies indirectly regulate the harvest by regulating hunter effort (Sinclair et al. 2006). The assumption is that hunter effort is related to harvest by the relationship:

H (N) = q EN where: H = Harvest N = Population size q = catchability coefficient E = Hunter effort Effort is usually measured in person-days (or gun-days) or another similar measure. For example, if one hunter covers 1% of the available habitat and ‘captures’ all the individuals encountered, then our catchability coefficient (or efficiency) would be 0.01. We can see that the size of the harvest should increase both with effort and population size. With a large population (N = 1,000), the total harvest given 25 person-days of effort would be:

(0.01) x (25) x (1,000) = 250 animals harvested. Now, assume the population declines because of unfavorable weather conditions (e.g., a drought, an unusually cold, snowy winter) to N = 400:

(0.01) x (25) x (400) = 100 animals harvested. Notice that the number of animals harvested changes in response to a smaller population size, even though hunting effort has not changed. Effort can be controlled through licenses, restricted hunting seasons (limited time period for hunting), and spatial restrictions (see below).

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A key advantage of constant-effort strategies is that there is a built-in safety mechanism. When animal numbers are low, harvest levels drop automatically simply because the harvest becomes more difficult. Quotas are common, but constant effort strategies may be more appropriate in many cases. Despite this, quotas remain popular because the direct link between prescription (quota) and result (harvest) has an intuitive appeal to managers. However, harvesting a constant number of individuals (quotas) is inefficient when there are fluctuations in recruitment or population density. To use quotas safely, harvest quotas must be set low enough to match the lowest predicted density. Or, managers must predict the population size for the upcoming year (to set quotas) using information from monitoring and census efforts. This can be both expensive and uncertain depending on the quality of the monitoring data (see Sinclair et al., 2006 for a detailed discussion). Fixed-Escapement Harvest Strategy In fixed-escapement strategies, animals are harvested only when the population (or recruitment) exceeds some predetermined threshold (Figure 7). Figure 7. Recruitment curve for fixed escapement harvest strategy.

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Thus, conservation, rather than harvest, is the primary goal (Sinclair et al. 2006) because this is, by far, the safest strategy for ensuring the persistence of the population. However, it requires knowledge about annual recruitment and may result in zero harvest in some years. Spatial Harvest Strategy Spatial harvest strategies are an attempt to control effort by restricting hunting in some areas and allowing it in others (McCullough 1996). It is conceptually similar to fixed-escapement strategies, except that the numerical restriction (threshold) is achieved by spatial controls (Figure 8). Hunter effort (and harvest) can be increased by opening additional areas to hunting, allowing hunters access to a larger proportion of the population. Hunter effort can be decreased by restricting access to fewer sections. Figure 8. Hypothetical design of a spatial harvest strategy. The total harvest is controlled by opening and closing grid cells to harvest. One key advantage of spatial harvest strategies is that as long as the unharvested areas contain a viable population, a sustainable harvest is practically guaranteed, even if MSY is occasionally exceeded.

Increasing Harvest Size (H)

= open for harvest

= closed to harvest

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Spatial harvests require little specific information about recruitment, but do require accurate information about harvest, habitat quality, and general population dynamics (e.g., annual rate of increase), especially in unharvested areas. Although many times recognizable divisions of habitat are present, the presence of both biological (natural habitats) and political boundaries may make it difficult to divide management areas into grid systems or other workable management units. Management units may be biological (e.g., physiographic regions, drainages, and watersheds that reflect more or less discrete animal populations), political, (e.g., counties), or a combination (e.g., a grouping of counties that closely match a biological unit). Biological units are typically used in western states where landform and climate produce discrete populations of animals. Intensive studies of seasonal distribution and movement patterns may be necessary in establishing good units. Political units are more typical of eastern states where wildlife populations are more evenly distributed, migrational movements are rare, and habitat and population dynamics are similar. Whatever type of management unit is used the boundaries must be recognizable to hunters. This is particularly important because harvest, the most important measure of human-caused mortality, generally is determined through surveys of hunters. Management unit boundaries easily recognized on maps and in the field facilitate accurate harvest and hunting pressure determinations. The Arkansas Game and Fish Commission employs spatial harvest strategies for white-tailed deer (Figure 9), black bear (Figure 10), elk (Figure 11), wild turkey, alligator, and Canada goose. Roads, highways, and natural features such as rivers are used to designate hunting zones.

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Figure 9. White-tailed deer hunting zones in Arkansas, 2015.

Figure 10. Black bear hunting zones in Arkansas, 2015.

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Figure 11. Elk hunting zones in Arkansas, 2015. Age- and Sex-Specific and Antler-Point Restriction Harvests Age-Specific Harvest Considerations One complicating factor is males and females often have differential survivorship, and different ages make different contributions to the annual recruitment. For example, harvesting an old elk cow that is no longer fecund does not impact the future recruitment into the population. Hunters often preferentially harvest certain age classes. Recreational hunting typically favors mature adults (i.e., the bigger animals). For example, Wright et al. (2006) aged elk killed by wolves and hunters. Wolves took primarily very young and very old individuals. The old individuals had low reproductive values because they had already contributed most of the offspring for their lifespan. Harvesting these animals would not have a large impact on the future recruitment of the population. The very young elk had lower reproductive

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values because many of these would not survive to reproductive age. This is a form of ‘numerical compensation’, which was discussed previously. In contrast, hunters took primarily individuals in the early adult age classes. These individuals had high reproductive values for two reasons. First, they had survived to adulthood and the probability of surviving to reproduce was now high. Second, they were young and had completed very little of their lifetime reproduction. Thus, most of the future recruitment would come from these animals. Sex-Specific Harvest Considerations Sex of the individuals harvested is also an important consideration in harvest strategies. Harvests are often biased toward males for two reasons. First, males typically are larger in many hunted species (especially large mammals) and have the large antlers, tusks, horns, etc. that are the trophies sought by hunters. Second, in some harvested species (those that are polygynous, like lek-breeding birds and many large mammals), one male can fertilize many females. Thus, a population that is skewed toward females can be favorable. It provides for an increased harvest without impacting the reproductive capability of the population. For example, if a population is 80% female, then up to 80% of the population could potentially be bearing offspring. However, populations with sex ratios that are too strongly skewed can cause problems (Mills 2007). 1. There may be too few males to successfully mate all females. And sometimes,

if the number of males drops too low, then females engage in competition for the remaining few males, increasing female mortality and decreasing reproductive output.

2. The few males remaining are often smaller because of selection for “trophy” characteristics. These characteristics may also be the ones that females use to select mates. The remaining small males may, therefore, be less likely to mate.

3. If there are only a few males, these must be protected (not harvested) to

ensure adequate reproduction. However, males are often the most

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“profitable” component of the population to be harvested, because they are the trophies that hunters often value most. A female-skewed sex ratio may thus devalue the population.

Antler-Point Restriction Harvest Considerations Antler-point restrictions (APR) mean that to be legal, a buck must have a minimum number of antler points on 1 side of his rack before being taken. In 1993, Dooley County, GA, became the first place in the US to implement white-tailed deer APR. Following the “Dooley County Experiment,” APR spread steadily through the southeastern US, and more recently into the upper Midwest and the Northeastern US. There are currently (in 2010) 5 states using white-tailed deer APR state-wide. Mississippi was first, instituting a 4-point rule (total points) in 1995. Three years later, in 1998, Arkansas began defining legal bucks as those having at least 3 points on 1 antler (See Box 2 for a description of a legal buck in Arkansas). Pennsylvania was next to implement APR in 2002, limiting hunters to bucks with ≥3 point on 1 antler and ≥4 points on 1 antler in 10 selected counties. In 2005, New Mexico began a 3-point on 1 antler regulation, while Vermont began requiring ≥1 antler with ≥2 points. Many people believe, especially the public, APR are intended to manage for trophy bucks. The primary focus of APR, however, is to protect yearling bucks from harvest, promote the recruitment of more bucks into older age classes, and harvest more does. Although antler restrictions may have some positive impacts, they also may have several drawbacks. One of the most disconcerting is high grading of overall antler quality. The problem is particularly relevant in regions with good soils and habitat where 1.5-year bucks (an age class this harvest strategy is intended to protect from harvest) may grow enough points to be legal. This may mean that bucks with lower quality (i.e., smaller) antlers with less genetic potential for growing larger antlers, survive and breed. Even if these smaller-racked bucks survive and make it into the older age classes, they may still not achieve the antler mass of the genetically superior bucks that were harvested.

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Box 2. What is a legal buck in Arkansas? When counting the number of points, the end of the main beam constitutes one point. Points must be at least 1 inch long to count. The distance from ear-tip to ear-tip on a buck with ears in the alert position is approximately 15 inches. Youth hunters: Youths 6 to 15 years of age may harvest any buck without regard to antler size or points. 3-point rule: A legal buck must have both antlers shorter than 2 inches (button buck) or have three or more points on one side of his rack. The three-point rule applies statewide unless mentioned below. 12-inch inside spread or 15-inch main beam rule: A legal buck on Dr. Lester Sitzes III Bois d’Arc, Harold E. Alexander Spring River, Hope Upland, Lafayette County WMA, McIlroy Madison County, Mike Freeze Wattensaw, Scott Henderson Gulf Mountain, Shirey Bay Rainey Brake and Moro Big Pine Natural Area WMAs must have either: both antlers under 2 inches (button buck), or an inside spread of at least 12 inches, or at least one main beam 15 inches or longer. 15-inch inside spread or 18-inch main beam rule: A legal buck in deer zones 16, 16A and 17 and on Bayou Meto, Buck Island, Cut-Off Creek, Dave Donaldson Black River, Ed Gordon Point Remove, Freddie Black Choctaw Island WMA Deer Research Area East Unit, Henry Gray Hurricane Lake, Rick Evans Grandview Prairie, St. Francis National Forest, Sheffield Nelson Dagmar and Trusten Holder WMAs must have either: both antlers under 2 inches (button buck), or an inside spread of at least 15 inches, or at least one main beam 18 inches or longer. Modified from the Arkansas Game and Fish Commission Hunting Guidebook 2015-16, page 50.

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Second, there exists the potential for an increase in unretreived harvest—some hunters accidentally shoot an illegal buck and let it lay instead of risking a fine. Quantifying unretrieved harvest is difficult. Third, counting antler points may make the hunting experience more stressful and limiting for youngsters and first-time hunters. EXAMPLE: NORTH AMERICAN BIGHORN SHEEP Coltman et al. (2003) described the effect of harvest on bighorn sheep populations. Trophy animals are large males with large, curled horns and these animals are selectively harvested by hunters. They also state that mating success is positively correlated with horn length. Females prefer males with big horns. Coltman et al. (2003) monitored horn length and other measurements in rams from 1971 to 2002 in a population of hunted sheep in Alberta, Canada. Over time, the average weight and horn length of rams declined in response to hunting pressure. The authors succinctly summarize the implications of these findings. “Unrestricted harvesting of trophy [animals] has contributed to a decline in the very traits that determine trophy quality (Coltman et al. 2003).” The genes that confer these traits have been depleted in the population. It is important that wildlife harvesting carefully consider the genetic impacts of harvest. Such impacts are difficult to reverse. It can take many generations to restore genetic traits, if it is possible to do so at all. In this case, a “full curl” restriction was placed on the harvest (tip of the curl extending beyond the tip of the nose) to keep males of high genetic quality in the population until they have had the opportunity to reproduce and sire offspring. This keeps desirable genetic traits in the population.

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EXAMPLE: AFRICAN LIONS Male African lions reach sexual maturity at ≈ 2.5 years of age, and their maximum age in the wild is ≈ 15 years. The mane reaches full size at ≈ 4 years and maximum reproductive success is at about 8 years. Incoming males that replace harvested males do not wait for mothers with dependent offspring to rear their current brood. They kill all cubs when they first take over a pride. Trophy hunting increases these male takeovers and, hence, lowers reproductive output. Whitman et al. (2004) simulated the effect of different hunting strategies on the demographics of the population. These four strategies were to restrict takes to males ≥ 3 yrs, ≥ 4 yrs, ≥ 5 yrs, and ≥ 6 yrs. The number of females quickly went to zero when the restriction was ≥ 3 yrs old, even in the absence of infanticide. This harvest strategy removes males before they reach their reproductive peak. When accounting for infanticide, Whitman et al. (2004) demonstrated that the older the harvest restrictions, the larger the population size. This is because the older restrictions allow each male to get past their reproductive peak and make more of a contribution to recruitment. Younger restrictions result in males being harvested before they have had a chance to reproduce. Interestingly, the total harvest and the number of trophy harvests also increased with the older restrictions. In the case of the lions, male noses darken as they age so it is possible for hunters to assess the age of the males with reasonable accuracy. Whitman et al. (2004) summarize “… Age is a critical variable enabling the persistence of trophy species with extensive paternal care. As long as hunting is restricted to a safe minimum age (and the rule is honestly enforced), there is no risk of setting excessive quotas even in areas where it is impossible to estimate the overall population size. … Thus, … populations can be sustained by following a simple harvest rule, combined with a simple technique for age-assessment” [bold emphasis added]. A critical aspect of both examples is that hunters (i.e., harvesters) are able to reliably estimate age in the field. For bighorn sheep, full horn curl accurately

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reflects age and potential reproductive contribution. In lions, the darkened noses accurately reflect age. If hunters are unable to reliably estimate age based on some characteristic like antler size, then such harvest strategies will not work. For example, this would not work for collecting ginseng (see earlier) because collectors cannot easily or reliably estimate the age of ginseng plants in the field. Example: Potential effects of a 3-antler point regulation on harvested white-tailed deer age composition and antler quality in Arkansas In 1998, the Arkansas Game and Fish Commission implemented a 3-antler point regulation statewide primarily to protect yearling, male white-tailed deer and promote the recruitment of more males (hereafter called bucks) into older age classes. The regulation stipulated that a buck must have both antlers <2 inches in length or have ≥3 points on 1 antler to be legally eligible for harvesting. It was assumed that as more bucks were recruited into older age classes over time, a larger proportion of the buck population would have at least 3 points per antler. Given the use of antler-based selective harvest criteria (ABSHC) in the U.S., managers need information regarding the efficacy, variability, and potentially negative effects of using ABSHC. Therefore, I (DW) am currently quantifying and evaluating the effects of the 3-antler point regulation (hereafter called the 3-point rule) on age composition and cohort antler size of bucks harvested before and after 1998 within 4 physiographic regions in Arkansas: the Ozark Highlands, Ouachita Mountains, West Gulf Coastal Plains, and Mississippi Alluvial Plains (Figure 12). I am also determining whether general antler quality and 4 antler metrics (i.e., number of antler points, inside spread, mean main beam length, and mean beam circumference) changed in the composite harvest after 1998 in these same regions. Some of my preliminary results are presented here.

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Figure. 12. Locations of the West Gulf Coastal Plain, Ozark Mountains (Interior Highlands), Ouachita Mountains, and Mississippi Alluvial Plain physiographic regions in Arkansas. My preliminary data analyses indicate that the age composition of the harvest in all 4 physiographic regions was different during the post-regulation than it was during the pre-regulation period (Figure 13). Fewer yearling (age class 1) bucks were harvested during the post-regulation period than were harvested during the pre-regulation period. Moreover, more 2.5-year old bucks (age class 2) were harvested during the post-regulation period than were harvested during the pre-regulation period. Mean antler quality between physiographic regions was not the same (Figure 14). Mean antler quality in the West Gulf Coastal Plains was significantly lower than the other physiographic regions. Mean antler quality in the Mississippi Alluvial Plains was significantly higher than the other physiographic regions.

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Figure 13. Percentage of 1.5-year (age class 1), 2.5-year (age class 2), and ≥3.5-year (age class 3) male white-tailed deer harvested before (pre-regulation, 1981-1997) and after (post-regulation, 1999-2006) the implementation of a 3-antler point regulation in 1998 within 4 physiographic regions of Arkansas.

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Figure 14. Effects of physiographic region on mean log(Antler Quality Index) and predicted gross Boone and Crocket (B&C) scores for ≥1.5-year old male harvested white-tailed deer in Arkansas, 1981-1997 and 1999-2006. WGCP = West Gulf Coastal Plains, OH = Ozark Highlands, OM = Ouachita Mountains, MAP = Mississippi Alluvial Plains. Mean antler quality values with same letters are not significantly different (Tukey test, P < 0.05). Error bars = 1 SEM. Mean antler quality differed by age class (Figure 15). Mean antler quality for 1.5-year bucks was significantly lower compared to 2.5-year and ≥3.5-year bucks, and mean antler quality for 2.5-year bucks was significantly lower than ≥3.5-year bucks. Mean antler quality for ≥3.5-year bucks was 18 inches (18%) larger than for 2.5-year bucks. Mean antler quality for 2.5-year bucks was 17 inches (21%) larger than for 1.5-year bucks. Mean antler quality between the pre- and post-regulation time periods was not the same (Figure 16). Mean antler quality during the post-regulation time period was significantly lower than during the pre-regulation period (1999-2006). Mean antler quality post-regulation was 2 inches (2.5%) larger than pre-regulation. Whether the 2 inch difference is biologically significant is open to debate.

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Figure 15. Effects of age class on mean log(Antler Quality Index) and predicted gross Boone and Crocket (B&C) scores for male white-tailed deer harvested in Arkansas, 1981-1997 and 1999-2006. Age class 1 = 1.5 years, age class 2 = 2.5 years, and age class 3 = ≥3.5 years. Mean antler quality values with same letters are not significantly different (Tukey test, P < 0.05). Error bars = 1 SEM.

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Figure 16. Effects of time period on mean log(Antler Quality Index) and predicted gross Boone and Crocket (B&C) scores for male white-tailed deer harvested in Arkansas before (pre-regulation, 1981-1997) and after (post-regulation, 1999-2006) the implementation of a state-wide 3-antler point regulation in 1998. Mean antler quality values with same letters are not significantly different (Tukey test, P < 0.05). Error bars = 1 SEM. Effects of Hunting on Wildlife Hunting can have a variety of effects on wildlife, often detrimental, but sometimes beneficial from the population perspective. 1. Mortality impacts—First, and most obvious, is the mortality from hunting that

has been the focus of our evaluation of harvest strategies. Potential impacts of harvest mortality include reduced population size (not always a bad thing if a species is overabundant), reduced population growth rate, and, population extinction.

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2. Disturbance of unharvested animals—Harvesting and/or hunting can alter the behavior of non-hunted animals via the disturbance of harvesting. For example, a flock of ducks will be flushed from a wetland by hunting disturbance. Although most individuals are not harvested, they are forced to abandon a good foraging location. Additionally, they burn valuable calories at a time when they must be reserving energy for migration.

3. Harvesting can also cause animals to shift their activity patterns, use alternate travel routes, and avoid certain habitats or areas . . . sometimes to their detriment.

4. Alter sex ratios—Harvests, as we have seen, can lower or raise reproductive success and alter sex ratios. The examples of bighorn sheep and lions have illustrated how harvests can decrease reproduction. In contrast, fertility of foxes is higher when populations have been reduced by hunting (Weston and Brisbin 2003).

5. Alter genetic structure of population—Harvests can operate as a powerful selective force that alters the genetic structure of a population. See Example: North American Bighorn Sheep above. You should also read Harris et al. (2002) and Festa-Bianchet (2003) for good summaries of the genetic consequences of hunting.

6. Incidental take—One very important, but rarely considered, consequence of harvesting is the impact it can have on non-target wildlife referred to as ‘incidental take’. For example, non-target wildlife, like sea turtles, sand dollars, and crabs are often caught in fishing nets, along with the target species of fish. Although the capture of these organisms may, in fact, be unintentional, it nonetheless results in their harvest.

7. Alteration of predator-prey relationships—Impacts on non-target populations can include removal of predators when predator populations are reduced through harvest. Conversely, species that feed on the harvested population may decrease because of decreased prey availability.

8. Alteration or disturbance of habitat—Alteration or disturbance of habitat effectively impacted all species that use the habitat. This is especially true for

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logging or other plant harvests because plants often provide habitat and food for many other species.

How Humans Select Prey In reality, all the available animals are not targeted by human hunters. Some animals will be included in the hunting set, and some will not. If we assume that animals are randomly distributed and that hunters’ search patterns and encounters with animals are also random, then species will be added to the hunting set according to their value to capture cost ratio (following Stephens and Krebs 1986). In other words, hunters will search for the species that provides the biggest return for the least effort, regardless of how abundant it is. Thus, hunters will not likely invest time capturing species with low value relative to cost, nor will they pass up opportunities to capture a high-value species. For subsistence hunters, this ratio would be the most calories (or size) per effort to capture it. For recreational hunters, the payoff would be large tusks, large size, or some other “trophy” characteristic. Assuming that nothing happens to change the capture cost ratio of a species (i.e., market value and technology remain constant), species will be added or dropped from the hunting set as the density of species of higher rank within the hunting set changes. For example, the average rate of return for high value species will drop over time because it takes more effort to find and capture rare species. Then, lower value species that were ignored will begin to be pursued as the number of high value species declines. Generally, hunters pursue species that have a high value to capture cost ratio. These species will decline with hunting. But, hunters will not necessarily stop hunting high value to capture cost ratio species even if they are rare (Hawkes and O’Connell 1992). Their high value to capture cost ratio induces hunters to attempt to capture them every time they are encountered, regardless of how infrequently. As a result, the depletion or local extinction of high value species is very likely.

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Adaptive Harvest Management Most wildlife management agencies follow some form of adaptive harvest management. Adaptive management is an approach that treats harvest strategies as a form of experiment, where the results of management are measured, compared against objectives and models, and then modified in hopes of improving management. Adaptive management recognizes that there are several sources of uncertainty in any management strategy. The steps to adaptive management are summarized below (following Mills 2007): 1. Objectives for harvest management must be identified; there may be one or

more constraints (i.e., ensure population persistence, provide X number of hunting opportunities, reduce wildlife-human conflict in some areas). Once objectives are identified, then possible harvest strategies (like those we have studied) can be listed.

2. The next step is to develop predictive population models to evaluate the potential outcomes of the different harvest options (see accompanying exercise). These models will be based on the most detailed information possible about environmental factors, demographic rates, etc. Depending on the population being managed, there may be considerable uncertainty about much of the necessary information in these models.

3. The next step is to implement the harvest strategy favored by the population

models. A critical part of adaptive harvest management is to monitor the response of the population to the harvest, because there will be uncertainty about whether or not the chosen strategy is really appropriate.

4. The harvest strategy must be evaluated by comparing how well the predictions from the population model (developed in step #2) fit the monitoring data. In other words, it is important to assess how well the harvest strategy achieved the original objectives.

5. The cycle then repeats. Using the monitoring data, the managing agency (or agencies) reassesses the objectives (#1), updates, and then improves the population models (#2). Hopefully, the result is a more accurate model. The

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updated model is then used to evaluate modified harvest strategies, and the process continues.

CASE STUDY: WILD BIRD TRADE Parrots and other wild tropical birds are popular as pets throughout the world. Although some parrots are bred in captivity (and hence do not impact natural populations or represent a true harvest), most are captured in the wild as adults or nestlings, and thus represent a harvest situation that we can study. One unique aspect of the wild bird trade is that the birds are not lethally harvested. But, because they are removed from the population, the effect on population dynamics is the same as killing them, and, in fact, some 40 – 60% of captured birds do die during handling and transport. From 1991 to 1996, approximately five million birds were traded among countries (Beissinger 2001); however, this does not include the 40-60% mortality suffered during capture and transport, non-export sales, and illegal trade. The total annual harvest of wild birds is probably between 1.6 and 3.2 million. Table 1 lists differences in life history traits between parrots (populations of which are suffering declines from harvesting) and finches (populations of which seem to be doing just fine despite heavy harvest). Table 1. Comparison of life-history traits between parrots and finches. Life History Trait Parrots Finches Clutch size Small Large # of Broods/Season Single Multiple Nest Type Cavity Open Cup Age at 1st Breeding Delayed Intermediate Adult Survivorship High Intermediate

These life-history differences (Table 1) partially account for why finch populations seem to be able to sustain high harvest levels while parrot populations cannot. The effect of each life-history characteristic is described below:

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1. Clutch size and # of broods—Small clutch sizes and fewer broods indicate a lower, inherent reproductive potential. Thus, parrots have less capability to compensate for increased mortality from harvest.

2. Nest sites—Finches can build open cup nests in a variety of habitats, but parrots use a very specific resource (namely, tree cavities), which has a limited availability in forests. This further limits their ability to compensate for harvest mortality.

3. Age at 1st breeding—Because parrots delay breeding, many harvested adults have not yet made their reproductive contribution. Removing adult parrots removes both the individuals and their potential offspring. Harvested adult finches, in contrast, are more likely to have already reproduced.

4. Adult survivorship—High adult survivorship means that little of the parrot harvest is a form of numerical compensation. A greater proportion of the harvested finches would have died from natural causes.

Beissinger et al. (2001) make the suggestion that harvesting nestlings has more potential to be sustainable than harvesting adults. First, survival of nestlings is much lower than survival of adults, meaning that some of the nestling harvest would be numerically compensated. Second, because parrots are cavity-nesters, production of nestlings could potentially be increased by constructing artificial cavities (i.e., nest boxes) if cavities are indeed limiting (rather than predation or food). This nest-box reproduction would be “excess” and thus could be sustainably harvested. From this, we can summarize some characteristics of species that are more amenable to sustainable harvests. 1. Harvest ages with low reproductive value to minimize impact on annual

recruitment.

2. Potential to increase productivity with active management (i.e., adding food plots or nest boxes).

3. High reproductive rates.

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4. Life cycles that are completed within the management area, which facilitates control over all sources of mortality and potentially illegal harvest.

CASE STUDY: BUSHMEAT HARVEST IN TROPICAL FORESTS Hunting in tropical forests differs from the recreational and managed hunting typical of North America and Europe in some key ways. First, the hunting is driven by nutritional needs. In fact, wild meat is the primary source of protein and other vital nutrients for rural and indigenous populations in some 62 countries (Bennett and Robinson in Robinson and Bennett 2000). Second, hunting occurs via “multi-species hunts”, where the hunter traverses wide areas of forest and hunts a variety of animals as they are encountered. Although large mammals make up the majority of bushmeat because they offer the greatest caloric return for effort, subsistence hunting in tropical forests consists of many species of mammals, reptiles, and birds, including hummingbirds ((Bennett and Robinson in Robinson and Bennett 2000). This contrasts with hunting in North America and Europe, where game hunting is tightly regulated and focused on specific “game” species. It is important to consider how much harvest wildlife populations can sustain, not only for the persistence of wildlife species, but also for the health and persistence of the human populations that depend on bushmeat. If these populations are not hunted in a sustainable fashion, then the human hunters will be forced to spend more time and effort in the pursuit of a dwindling resource. We must ask both ‘how much hunting can wildlife populations sustain?’ and ‘how many people can the wildlife populations support with adequate nutrition?’ Robinson and Bennett (Chapter 2 in Robinson and Bennett 2000) estimate that the production of wild game in tropical forests is about 150 kg / km2 / year. Assuming that 65% of wild meat is consumable, this translates into about 97 kilograms of edible meat per square kilometer of forest each year. Further assuming a healthy consumption of meat is 0.25 kg / person / day, the “human carrying capacity” of tropical forests is about 1.0 person / km2. In areas where human populations are below this density, subsistence hunting of animals may be sustainable.

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Unfortunately, in many areas, human populations are above that sustainable level. Consequently, wild animal populations are consistently declining in these areas (See numerous examples in Robinson and Bennett 2000, Bennett et al. 2002). Typically, the larger species decline first because they offer the most nutrition per kill to the hunter and because they are least able to sustain high levels of harvest (see Case Study: Wild Bird Trade above). Several factors can further exacerbate harvest pressures on wild populations in tropical forests. They are as follows. 1. Increasing human populations increase demand for bushmeat.

2. Sedentary agriculture increases human population densities and decreases the

mobility of populations, which can result in an increase in harvest pressure on nearby wild populations.

3. Commercial trade increases demand. Bushmeat harvest can become an important source of cash income, which is often scarce in rural areas. Thus, local hunters hunt both for nutrition and for additional income. Illegal trade and black markets can further increase hunting pressure.

4. Forest fragmentation by roads and logging activities provides access to additional forest habitat to hunters and access to commercial markets. Hunters near logging camps or logging roads not only harvest more bushmeat, but they also sell a greater percentage of their harvest (Bennett et al. 2002).

5. Improved technology (like snares and shotguns vs. traditional blowguns) increases the efficiency of subsistence hunters (Mena et al. in Robinson and Bennett 2000).

Conclusion Populations are a primary concern of conservation biologists who are often faced with recovering endangered populations, reducing populations of pest species, or maintaining populations of harvested species. In every case, the dynamics of populations are an outcome of the complex interactions between births and deaths within a population, and migration between populations. These

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interactions vary dramatically among populations and species. Only by understanding the key processes within populations that regulate their growth, can we manage populations successfully. The accompanying exercise is intended to provide an opportunity for you to delve more deeply into the concepts and their application to population management. Recommended Reading McCullough, D. R. 1996. Spatially structured populations and harvest theory.

Journal of Wildlife Management 60:1-9. Miller, K.V. and J.M. Wentworth. 2000. Modeling Population Dynamics. Pages

100-155 in S. Demarais and P. R. Krausman, editors. Ecology and Management of Large Mammals in North America. Prentice-Hall, Upper Saddle River, New Jersey, USA.

Mills, L.S. 2007. Conservation of Wildlife Populations. Blackwell Publishing, Malden, Massachusetts, USA.

Rockwood, L.L. 2006. Introduction to Population Ecology. Blackwell Publishing, Malden, Massachusetts, USA.

Sinclair, A.R.E., J.M. Fryxell, and G. Caughley. 2006. Wildlife Ecology, Conservation, and Management, Blackwell Publishing, Malden, Massachusetts, USA.

White, G.C. 2000. Modeling Population Dynamics. Pages 84-07 in S. Demarais and P. R. Krausman, editors. Ecology and Management of Large Mammals in North America. Prentice-Hall, Upper Saddle River, New Jersey, USA.

Other Literature Cited Beissinger, S.R. 2001. Trade of live wild birds: potentials, principles and practices

of sustainable use. Pages 182-202 in J.D. Reynolds, G.M. Mace, K.H. Redford, and J.G. Robinson, editors. Conservation of Exploited Species. Cambridge University Press, Cambridge, United Kingdom.

Bennett, E.L. and J.G. Robinson. 2000. Hunting for the snark. Pages 1–12 in Robinson, J.G. and E.L. Bennett, editors. Hunting for sustainability in tropical forests. Columbia University Press, New York, USA.

Bennett, E., H. Eves, J. Robinson, and D. Wilkie. 2002. Why is eating bushmeat a biodiversity crises? Conservation in Practice 3:28-29.

Bolen, E. G., and W. Robinson. 2002. Wildlife ecology and management, 5th edition. Prentice Hall, Upper Saddle River, New Jersey, USA.

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Coltman D.W., P. O'Donoghue, J.T. Jorgenson, J.T. Hogg, C. Strobeck, and M. Festa-Bianchet. 2003. Undesirable evolutionary consequences of trophy hunting. Nature 426:655–658.

Coughenour, E.G. and F.J. Singer. 1996. Elk population processes in Yellowstone National Park under the policy of natural regulation. Ecological Applications 6:573-593.

Engeman, R.M., A. Stevens, J. Allen, J. Dunlap, M. Danial, D. Teague, and B. Constantin. 2007. Feral swine management for conservation of an imperiled wetland habitat: Florida’s vanishing seepage slopes. Biological Conservation 134:440-446.

Festa-Bianchet, M. 2003. Exploitative wildlife management as a selective pressure for life-history evolution of large mammals. Pages 191-207 in M. Festa-Bianchet and M. Apollonio, editors. Animal behavior and wildlife conservation. Island Press, Washington, D.C., USA.

Garrettson P.R., and Rohwer F.C. 2001. Effects of mammalian predator removal on production of upland-nesting ducks in North Dakota. Journal of Wildlife Management 65:398–405.

Harris, R.B., W.A. Wall, and F.W. Allendorf. 2002. Genetic consequences of hunting: what do we know and what should we do? Wildlife Society Bulletin 30:634-643.

Hawkes, K., and J. F. O’Connell. 1992. On optimal foraging models and subsistence transitions. Current Anthropology 33:63–65.

Lambers, J. H.R., J.S. Clark, and B. Beckage. 2002. Density-dependent mortality and the latitudinal gradient in species diversity. Nature 417:732-735.

Morrison, M.L., L.S. Hall, S.K. Robinson, S.I. Rothstein, D.C. Hahn, and T.D. Rich, Eds. 1999. Research and management of the brown-headed cowbird in western landscapes. Studies in Avian Biology, no. 18.

Robinson, J.G., and E.L. Bennett. 2000. Hunting for sustainability in tropical forests. Columbia University Press, New York, USA.

Stephens D.W., and J.R. Krebs. 1986. Foraging theory. Princeton University Press, Princeton, New Jersey, USA.

Weston, J.L. and I.L. Brisbin. 2003. Demographics of a protected population of gray foxes (Urocyon cinereoargenteus) in South Carolina. Journal of Mammalogy 84:996–1005.

Whitman, K., A.M. Starfield, H.S. Quadling, and C. Packer. 2004. Sustainable trophy hunting of African lions. Nature 428:175–178.

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Wright G.J., R.O. Peterson, D.W. Smith, T.O. Lemke. 2006. Selection of northern Yellowstone elk by gray wolves and hunters. Journal of Wildlife Management 70:1070–1078.

Glossary of Important Terms Additive mortality--Harvest mortality that is additional to (above and beyond) the background mortality that occurs in the absence of harvest. Age structure—Composition of a population with regard to age. Bushmeat—Any wild meat taken from tropical forests (which are called the “bush”). Compensatory mortality--Harvest mortality that does not add to the overall mortality rates because of ameliorating effects of increased reproduction, immigration, or reduced mortality from other factors. Competition—Impacts of organisms or species on one another in pursuit of a shared resource(s). Exploitation competition is when one organism or species exploits the resource base more effectively than its competitor. Interference competition is when one species prevents the other species from consuming the resource, such as through territoriality or aggression. Density-dependent—Factors that regulate populations in a manner that changes with population size or density – generally internal and biotic. Density-dependent compensation—Compensation that occurs through increased reproduction or survival in response to harvest mortality. Density-independent—Factors that affect populations regardless of population size or density-- generally external and abiotic. Exponential growth—Also known as geometric growth – populations grow at a constant rate. Rate of change of population number over time will be: dN/dt = ri No. Population size at time t will be: Nt = N0e rt, where N0 is the size of the initial population, e is the base of natural logarithms (2.718), t is time, and r is the

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intrinsic rate of increase. Fecundity—Physical ability to reproduce. Juvenile—Individual that has not yet attained adult characteristics, such as reproductive age, adult size, or adult coloration. Logistic growth—Growth is exponential when resources are unlimited, but slows as population approaches carrying capacity. Numerical compensation—Compensation for harvest mortality in cases where some proportion of the harvested animals would have died from other causes had they remained unharvested. Recruitment—Additional individuals added to a population. Survivorship—Proportion of a cohort that survives to a certain age. Sustainable harvest—Harvest level that can be maintained indefinitely without leading to extinction or unacceptable decline in the population (Mills 2007).