Microsoft PowerPoint Portada taller Jaguares

The value known as "mean kinship" (MK) describes the overall degree of 

relatedness of a given individual to the remainder of the captive population. 

Therefore, a wild-caught individual that has not yet bred has a mean kinship of 

O.O, while an individual that has a large number of líiving offspring has a 

relatively higher MK value (up to a theoretical maximum of 1.0). The table above 

indicates those wild-caught individuals that should be given high priority for 

breeding: those animals with a mean kinship value of O.O  and that are relatively 

young adults that will have a higher probability of breeding success. A brief 

analysis of the table indicates that individuals with studbook numbers 48 and 49 

satisfy these criteria. Fortunately, both of these animals are in Guatemala, so this 

will facilitate a successful pairing. These factors are very commonly considered in 

many captive population management plans and can serve as the basis for very 

effective genetic and demographic management of captive populations. 

Finally, it is important to recognize that a total of three litters have come from 

inbred mating. While this is not a particularly high frequency of inbreeding, there 

could be more inbred litters produced in the future as the overall captive population 

becomes more related through the continued skewed genetic representation of wild-

caught individuals. Again, relatively simple computer methods of studbook 

analysis can be used to calculate the current levels of inbreeding among living 

animals and, more importantly, the inbreeding coefficient that can be expected 

from potential mating designed by population managers. 

We hope that this brief summary of the analysis of the captive Mesoamerican 

jaguar population provides a broad summary of the genetic status of the population, 

and demonstrates the valuable and sophisticated tools available for effective 

genetic management of captive populations. Experienced use of these tools can 

provide very valuable guidance for the population manager as mating are designed 

to maximize the amount of genetic variation derived from the wild population. 

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Appendix I: 

Simulation Modeling and Population Viability Analysis 

A model is any simplified representation of a real system. We use models in all 

aspects of our lives, in order to: (1) extract the important trends from complex 

processes, (2) permit comparison among systems, (3) facilitate analysis of causes 

of processes acting on the system, and (4) make predictions about the future. A 

complete description of a natural system, if it were possible, would often decrease 

our understanding relative to that provided by a good model, because there is 

"noise" in the system that is extraneous to the processes we wish to understand. For 

example, the typical representation of the growth of a wildlife population by an 

annual percent growth rate is a simplified mathematical model of the much more 

complex changes in population size. Representing population growth as an annual 

percent change assumes constant exponential growth, ignoring the irregular 

fluctuations as individuals are born or immigrate, and die or emigrate. For many 

purposes, such a simplified model of population growth is very useful, because it 

captures the essential information we might need regarding the average change in 

population size, and it allows us to make predictions about the future size of the 

population. A detailed description of the exact changes in numbers of individuals, 

while a true description of the population, would often be of much less value 

because the essential pattern would be obscured, and it would be difficult or 

impossible to make predictions about the future population size. 

In considerations of the vulnerability of a population to extinction, as is so often 

required for conservation planning and management, the simple model of 

population growth as a constant annual rate of change is inadequate for our needs. 

The fluctuations in population size that are omitted from the standard ecological 

models of population change can cause population extinction, and therefore are 

often the primary focus of concern. In order to understand and predict the 

vulnerability of a wildlife population to extinction, we need to use a model which 

incorporates the processes which cause fluctuations in the population, as well as 

those which control the long-term trends in population size (Shaffer 1981). Many 

processes can cause fluctuations in population size: variation in the environment 

(such as weather, food supplies, and predation), genetic changes in the population 

(such as genetic drift, inbreeding, and response to natural selection), catastrophic 

effects (such as disease epidemics, floods, and droughts), decimation of the 

population or its habitats by humans, the chance results of the probabilistic events 

in the lives of individuals (sex determination, location of mates, breeding success, 

survival), and interactions among these factors (Gilpin and Soulé 1986). 

Models of population dynamics which incorporate causes of fluctuations in 

population size in order to predict probabilities of extinction, and to help identify 

the processes which contribute to a population's vulnerability, are used in 

"Population Viability Analysis" (PVA) (Lacy 1993/4). For the purpose of 

predicting vulnerability to extinction, any and all population processes that impact 

population dynamics can be important. Much analysis of conservation issues is 

conducted by largely intuitive assessments by biologists with experience with the 

system. Assessments by experts can be quite valuable, and are often contrasted 

with "models" used to evaluate population vulnerability to extinction. Such a 

contrast is not valid, however, as any synthesis of facts and understanding of 

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