Advanced Distance Sampling: Estimating abundance of biological populationsS. T. Buckland, D. R Anderson, K. P. Burnham, J. L. Laake, D. L. Borchers, L. Thomas This advanced text focuses on the uses of distance sampling to estimate the density and abundance of biological populations. It addresses new methodologies, new technologies and recent developments in statistical theory and is the follow up companion to Introduction to Distance Sampling (OUP, 2001). In this text, a general theoretical basis is established for methods of estimating animal abundance from sightings surveys, and a wide range of approaches to analysis of sightings data is explored. These approaches include: modelling animal detectability as a function of covariates, where the effects of habitat, observer, weather, etc. on detectability can be assessed; estimating animal density as a function of location, allowing for example animal density to be related to habitat and other locational covariates; estimating change over time in populations, a necessary aspect of any monitoring programme; estimation when detection of animals on the line or at the point is uncertain, as often occurs for marine populations, or when the survey region has dense cover; survey design and automated design algorithms, allowing rapid generation of sound survey designs using geographic information systems; adaptive distance sampling methods, which concentrate survey effort in areas of high animal density; passive distance sampling methods, which extend the application of distance sampling to species that cannot be readily detected in sightings surveys, but can be trapped; and testing of methods by simulation, so that performance of the approach in varying circumstances can be assessed. Authored by a leading team this text is aimed at professionals in government and environment agencies, statisticians, biologists, wildlife managers, conservation biologists and ecologists, as well as graduate students, studying the density and abundance of biological populations. |
Contents
| 1 | |
| 6 | |
3 Covariate models for the detection function | 31 |
4 Spatial distance sampling models | 48 |
5 Temporal inferences from distance sampling surveys | 71 |
6 Methods for incomplete detection at distance zero | 108 |
7 Design of distance sampling surveys and Geographic Information Systems | 190 |
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Common terms and phrases
abundance estimates adaptive analysis approach assumed assumption availability bias Borchers Buckland capture histories centreline Chapter component confidence interval consider covariates coverage probability covered region density estimate design-based detection function detection probability distance data distance sampling distance sampling methods distance sampling surveys distribution effort encounter rate estimated detection estimates of abundance example full likelihood given grid half-normal harbour porpoise hazard-rate inference Laake likelihood function line length line transect sampling line transect surveys linear mark-recapture mean cluster measurement error minke whale model-based number of animals object density observer parameter perpendicular distance plot point independence point transect sampling Poisson Poisson distribution Poisson process population Pr{w probability of detection q-q plot random recaptures search strips Section simple random sample simulation survey design survey region systematic sample tees tion transect lines trapping line transect trend estimate values variables whales zero zigzag sampler