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- W1574656367 abstract "Conventional distance sampling adopts a mixed approach, using model-based methods for the detection process, and design-based methods to estimate animal abundance in the study region, given estimated probabilities of detection. In recent years, there has been increasing interest in fully model-based methods. Model-based methods are less robust for estimating animal abundance than conventional methods, but offer several advantages: they allow the analyst to explore how animal density varies by habitat or topography; abundance can be estimated for any sub-region of interest; they provide tools for analysing data from designed distance sampling experiments, to assess treatment effects. We develop a common framework for model-based distance sampling, and show how the various model-based methods that have been proposed fit within this framework." @default.
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- W1574656367 date "2015-09-03" @default.
- W1574656367 modified "2023-10-16" @default.
- W1574656367 title "Model-Based Distance Sampling" @default.
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- W1574656367 doi "https://doi.org/10.1007/s13253-015-0220-7" @default.
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