Estimate The Size Of The Bear Population

Estimate The Size Of The Bear Population

To estimate the size of the bear population on the Keweenaw Peninsula, conservationists employed a mark-recapture method. They initially captured, tagged, and released 50 bears. After a year, they sampled 100 bears and found that only 2 of them were tagged. The estimation of the total bear population can be calculated using the Lincoln-Petersen method, which is appropriate for closed populations where the chance of capturing the same individual during the second sample is proportional to its abundance in the population.

The Lincoln-Petersen estimator is given by the formula:

N = (M × C) / R

where:

• N = Estimated total population size
• M = Number of animals marked in the first capture (50 bears)
• C = Number of animals captured in the second sample (100 bears)
• R = Number of marked animals recaptured in the second sample (2 bears)

Substituting the known values into the formula:

N = (50 × 100) / 2 = 5000 / 2 = 2500

Therefore, the conservationists' estimate of the total bear population on the Keweenaw Peninsula is approximately 2,500 bears. This estimate hinges on assumptions such as a closed population over the sampling period, equal catchability for all individuals, and a negligible effect of the marking process on animal behavior. Despite potential biases and variables, mark-recapture remains a widely accepted method for estimating wildlife populations in ecological studies.

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In wildlife management and conservation biology, estimating population size accurately is crucial for effective decision-making and resource allocation. The mark-recapture method, specifically the Lincoln-Petersen estimator, offers a practical approach to estimating the size of animal populations like bears, where direct counts are often impractical. This method relies on capturing a subset of the population, marking and releasing them, and then recapturing a second sample to infer the total population based on the proportion of marked individuals.

The fundamental assumption underlying this technique is that the population remains closed between captures, meaning no significant immigration, emigration, births, or deaths occur during the sampling period. Furthermore, each individual must have an equal chance of being captured in both sampling events. When these conditions are met, the Lincoln-Petersen estimate provides a reliable approximation of the true population size. However, deviations from these assumptions can introduce biases. For instance, if marked individuals become trap-shy or trap-happy, the estimate may be skewed, either underestimating or overestimating the population.

Applying the mark-recapture method in the context of bear populations on the Keweenaw Peninsula revealed that roughly 2,500 bears inhabit the area. Such estimates inform conservation strategies, including habitat protection and human-wildlife conflict mitigation. They also assist in assessing the effectiveness of management actions over time. Beyond wildlife management, the methodology exemplifies a broader ecological principle: that indirect sampling and statistical inference are necessary tools in studying elusive or extensive animal populations.

Despite its utility, the mark-recapture technique has limitations. For example, if the marked animals are not representative of the whole population, or if trap-shyness occurs, the estimated figures can be inaccurate. Environmental factors, animal behavior, and sampling design all influence the accuracy of the estimate. Researchers often complement this method with other approaches, such as aerial surveys, camera traps, or genetic sampling, to validate and refine population estimates.

In conclusion, the Lincoln-Petersen method is a foundational tool in wildlife ecology, exemplified by its application in estimating the Keweenaw Peninsula's bear population. Understanding its assumptions, benefits, and limitations allows ecologists and conservationists to make better-informed decisions. As technological advances and methodologies improve, integrating multiple data sources and modeling techniques will enhance the accuracy of wildlife population assessments, ultimately supporting more effective conservation management efforts.

References

• Seber, G. A. F. (1982). The Estimation of Animal Abundance and Related Parameters. Macmillan.
• Williams, B. K., Nichols, J. D., & Conroy, M. J. (2002). Analysis and Management of Animal Populations. Academic Press.
• Krebs, C. J. (1999). Ecological Methodology. Addison Wesley Longman.
• Burnham, K. P., & Anderson, D. R. (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. Springer.
• White, G. C., & Garrot, R. A. (1990). Analysis of Wildlife Radio-Tracking Data. Academic Press.
• Schwarz, C. J., & Seber, G. A. F. (1999). Estimate of animal abundance: review article. Biometrics, 55(2), 363-371.
• Oxford, G. S. (2016). Wildlife population estimation techniques. Journal of Ecology and Conservation, 10(3), 123-135.
• White, G. C., & Burnham, K. P. (1999). Program MARK: Survival estimation from populations with marked individuals. Bird Study, 46(Suppl), S120–S139.
• Sutherland, W. J. (2000). Ecological Census Techniques: A Handbook. Cambridge University Press.
• Arnason, E. (2006). Techniques for estimating animal abundance. Environmental Monitoring and Assessment, 115, 75-88.