# Population Ecology at Work: Managing Game Populations

By: Michael Stokes, Ph.D © 2012 Nature Education
Citation: Stokes, M. (2012) Population Ecology at Work: Managing Game Populations. Nature Education Knowledge 3(10):5
Game managers apply ecological models to regulate harvest of economically important species.

## Population Growth

For species that are managed for harvest, the manager must have an intimate knowledge of the species and its environment. An important part of this expert knowledge is a fundamental understanding of the dynamics of each managed population. Population dynamics refers to changes in the numbers of individuals in populations over time. The essential processes that determine the dynamics of a population are the vital rates, or births and deaths (as well as immigration and emigration). Recruitment refers to immigration and births, or the number of individuals added to the population in a given time. There are many models that describe population growth, be it positive or negative, that result from these internal processes. The most relevant basic population growth model for understanding the various approaches to harvesting is called the logistic growth model. This is most commonly shown in differential form as: dN/dt = rN((K – N)/K), where dN/dt (e.g., the rate of change in population size, N, at a given moment in time, t) is a function of the current size of the population (N) and the intrinsic or instantaneous rate of change (r). The resulting product is then multiplied by a term that includes carrying capacity, K. The carrying capacity is the number of individuals the environment can support indefinitely, given fluctuations in resources in the environment. In this equation, if K is much larger than N, the population can grow quickly. If K is smaller than N, the population will shrink. If K=N, the population will remain the same over time. Figure 1 illustrates a density plot of a population that changes based on this equation. It shows a population that grows rapidly, with growth slowing as resources become limited, until the population stabilizes at K. The equation shown produces an asymptotic approach to constant population size represented by K; however, in nature, a variety of factors such as extreme weather events, changing resource availability and other disturbances cause populations to fluctuate around K. Any model in which the rate of growth is a function of the number of individuals, as in the logistic growth model, rather than independent of population density, is said to be a density-dependent model. Nearly all models upon which game harvesting practices are based are density-dependent models.

## Sustained Harvest Management

Harvest management involves determining how harvesting impacts population growth, composition and density, then setting harvest goals and practices accordingly. Many harvest management approaches are based on an extension of single-species, density-dependent, population-dynamics models, such as the logistic growth model, to two-species models, especially predator-prey models. A common goal of harvest management is to allow the predator (humans) to take as many prey items (the game) as possible from a population without putting that population in danger. To reach this goal, it's important to realize that the best approach is usually not to maintain the game population at the highest possible density, but rather at a sustainable N at which the rate of growth of the population is greatest. This N is often substantially less than K, indeed is half of K in the basic logistic growth model, and allows the maximum rate of harvest, referred to as maximum sustainable yield (MSY). In an economic context, where hunters pay for animals or for access to hunting opportunities with a reasonable chance of success (both typical of large game hunting operations), MSY may be an important management goal. However, MSY is but one goal of game management and can actually be a dangerous approach to managing populations if lack of knowledge of chronological or spatial variation in recruitment, or carrying capacity, or the inability to accurately estimate N can lead to over or under-harvesting

If MSY is a management goal, there are various strategies a game manager can employ to attempt to regulate the rate of harvest. These include fixed or constant quota harvesting, fixed or constant effort harvesting, fixed proportion harvesting, and fixed escapement harvesting. Fixed quota management occurs when a predetermined, fixed number of animals is harvested from a population. Essentially, this is the number of animals that represent the difference between K and the N that represents population size at which MSY is possible. Given variation in r, N and K, this can lead to catastrophic overharvesting and is considered very risky. Fixed effort harvesting is safer. The game manager specifies the level of effort (for example the number of hunters or length of a hunting season), rather than the number of animals to be harvested. If N is low, harvesting success will be low and vice versa, so this becomes a self-regulating system.

Fixed proportion harvesting specifies a percentage of N that can be harvested, rather than a specific number of animals. As long as N is known, this has a similar effect to fixed effort harvesting. Fixed escapement harvesting is the safest approach, as it specifies not the number of animals to be harvested, but the number of animals to remain unharvested, ensuring safety of the population, especially when variation in r, N or K is large, or when these variables cannot be measured with confidence.

However, in modern, ecologically-based wildlife management, MSY is rarely the goal (Figure 2). Rather, especially in the case of very rare or non-game species, management goals may include conservation, maintenance of ecosystem function, elimination of non-native species, or aesthetics. When managing very small populations or very high-value species, other harvesting approaches may be necessary. For example, a recent approach to harvest management is adaptive harvest management or AHM. This strategy is based on a constant flow of information about the managed population and its environment. This data stream is used to continually update harvesting limit or effort, even within a single harvest season. Unfortunately, data of this quality are not available in most situations; however, AHM has been in use in waterfowl management in the U.S. since the mid 1990s, and is used in commercial fisheries.

Implementation of these management techniques requires careful observation of the managed population. For example, the manager may find that animals of a certain age have a relatively high expectation of survival or reproduction. In that case, those animals should be protected, limiting harvest to older or younger individuals. Alternatively, if older or larger animals have a naturally high rate of mortality, then targeting those classes for harvesting will have a relatively lower impact on the population. This is the concept of compensatory mortality — that is, animals removed by harvesters would likely have died of other causes. Thus harvesting is a compensatory mortality factor. If harvesting reduces the number of animals by an amount greater than natural mortality, this excess reduction is called additive mortality.

Application of population-dynamics models to harvesting may be an effective approach to game management. However, proper management requires an in-depth knowledge of the ecology of the species and/or populations under management. Ecologically safe harvest management may require adjustment by age and stage of individuals harvested, and by environmental conditions at time of harvest.

### Glossary

Population dynamics changes in the numbers of individuals in populations over time.

Vital rates births and deaths (as well as immigration and emigration).

Recruitment immigration and births, or the number of individuals added to the population in a given time.

Logistic growth model. The most relevant of the very basic population growth models for understanding the various approaches to harvesting. This is most commonly shown in differential form as: dN/dt = rN((K – N)/K), where dN/dt (e.g., the rate of change in population size, N, at a given moment in time, t) is a function of the current size of the population (N) and the intrinsic or instantaneous rate of change (r).

Carrying capacity (K) is the number of individuals the environment can support indefinitely, given fluctuations in resources in the environment.

Maximum sustainable yield (MSY). A common goal of harvest management is to allow the predator (humans) to take as many prey items (the game) as possible from a population without putting that population in danger. To reach this goal, it's important to realize that the best approach is usually not to maintain the game population at the highest possible density, but rather at a sustainable N at which the rate of growth of the population is greatest. This N is often substantially less than K, indeed is half of K in the basic logistic growth model, and allows the maximum rate of harvest. MSY may be an important management goal. However, MSY is but one goal of game management and can actually be a dangerous approach to managing populations if lack of knowledge of chronological or spatial variation in recruitment, or carrying capacity, or the inability to accurately estimate N can lead to over or under-harvesting.

Fixed quota management occurs when a predetermined, fixed number of animals is harvested from a population. Essentially, this is the number of animals that represent the difference between K and the N that represents population size at which MSY is possible. Given variation in r, N and K, this can lead to catastrophic overharvesting and is considered very risky.

Fixed effort harvesting is safer than fixed quota management. The game manager specifies the level of effort (for example the number of hunters or length of a hunting season), rather than the number of animals to be harvested. If N is low, harvesting success will be low and vice versa, so this becomes a self-regulating system.

Fixed proportion harvesting specifies a proportion of N that can be harvested, rather than a specific number of animals. As long as N is known, this has a similar effect to fixed effort harvesting.

Fixed escapement harvesting is the safest approach of harvest management, as it specifies not the number of animals to be harvested, but the number of animals to remain unharvested, ensuring safety of the population, especially when variation in r, N or K is large, or when these variables cannot be measured with confidence.

Adaptive harvest management (AHM), A recent approach to harvest management, this strategy is based on a constant flow of information about the managed population and its environment.

Begon, M., Townsend, C. R., & Harper, J. L. Ecology: From Individuals to Ecosystems. 4th ed. Oxford, UK: Blackwell Publishing Ltd., 2006.

Bolen, E. G. & Robinson, W. L. Wildlife Ecology and Management, 5th ed. Upper Saddle River, NJ: Prentice Hall, 2003.

CITES Secretariat. Official website of the Convention on International Trade in Endangered Species of Wild Fauna and Flora. (link)

Ntiamoa-Baidu, Y. Wildlife and Food Security in Africa. New York, NY: Food and Agriculture Organization of the United Nations, 1997. (link)

Sibly, R. M. et al. Wildlife population growth rates. Cambridge, UK: Cambridge University Press, 2003.

Sinclair, A. R. E., Fryxell, J. M. & Caughley,G. Wildlife Ecology: Conservation and Management, 2nd ed. Hoboken, NJ: Wiley-Blackwell, 2006.

U.S. Department of the Interior, Fish and Wildlife Service, and U.S. Department of Commerce, U.S. Census Bureau. 2006 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation, 2006. (link)

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