Advanced Distance Sampling

Clicks: 1
ID: 304340
2004
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #1,013 of 1,518 articles by views in Oxford University Press eBooks

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,518 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Abstract 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.
Reference Key
openalex_W204164260 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors S. T. Buckland, David R. Anderson, K P Burnham, Jeffrey L. Laake, David L. Borchers, Len Thomas
Journal Oxford University Press eBooks
Year 2004
DOI
10.1093/oso/9780198507833.001.0001
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.