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Matrix population models as a tool in development of habitat modelsAuthor(s): Gregory D. Hayward; David B. McDonald
Source: In: Duncan, James R.; Johnson, David H.; Nicholls, Thomas H., eds. Biology and conservation of owls of the Northern Hemisphere: 2nd International symposium. Gen. Tech. Rep. NC-190. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 205-212.
Publication Series: General Technical Report (GTR)
Station: North Central Research Station
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DescriptionBuilding sophisticated habitat models for conservation of owls must stem from an understanding of the relative quality of habitats at a variety of geographic and temporal scales. Developing these models requires knowing the relationship between habitat conditions and owl performance. What measure should be used to compare the quality of habitats? Matrix population models represent a powerful tool to aid in designing habitat research. Through sensitivity and elasticity analysis we can identify the demographic transitions most important in determining population growth. Matrix methods also provide a powerful method for assessing individual fitness in varying environmental conditions. Matrix models can help us decide how to: (1) focus field efforts toward measuring the most important demographic parameters, and (2) focus on those habitat characteristics with the greatest effect on population dynamics.
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CitationHayward, Gregory D.; McDonald, David B. 1997. Matrix population models as a tool in development of habitat models. In: Duncan, James R.; Johnson, David H.; Nicholls, Thomas H., eds. Biology and conservation of owls of the Northern Hemisphere: 2nd International symposium. Gen. Tech. Rep. NC-190. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 205-212.
- Analysis of sensitivity and uncertainty in an individual-based model of a threatened wildlife species
- The role and management implications of modeling owl populations and the habitats they occupy
- Optimizing habitat protection using demographic models of population viability.
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