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Cited by 190

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Wildlife Population Assessment: Past Developments and Future Directions

Buckland, S. T., Goudie, I. B. J., Borchers, D. L.·2000·Biometrics

Abstract

Summary.We review the major developments in wildlife population assessment in the past century. Three major areas are considered: mark‐recapture, distance sampling, and harvest models. We speculate on how these fields will develop in the next century. Topics for which we expect to see methodological advances include integration of modeling with Geographic Information Systems, automated survey design algorithms, advances in model‐based inference from sample survey data, a common inferential framework for wildlife population assessment methods, improved methods for estimating population trends, the embedding of biological process models into inference, substantially improved models for conservation management, advanced spatiotemporal models of ecosystems, and greater emphasis on incorporating model selection uncertainty into inference. We discuss the kind of developments that might be anticipated in these topics.

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Crossref · 10.1111/j.0006-341x.2000.00001.x

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Metadata

Authors
Buckland, S. T., Goudie, I. B. J., & Borchers, D. L.
Venue
Biometrics
Published
2000-03
Volume
56
Issue
1
Pages
1-12
ISSN
  • 0006-341X (ISSN-L)
  • 1541-0420
OpenAlex
W2008793508
Cited by
190
References
2
FWCI
9.00
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Wildlife Population Assessment: Past Developments and Future Directions. https://app.cochat.ai/papers/10.1111/j.0006-341x.2000.00001.x
The paper
Buckland, S. T., Goudie, I. B. J., & Borchers, D. L. (2000). Wildlife Population Assessment: Past Developments and Future Directions. Biometrics. https://doi.org/10.1111/j.0006-341x.2000.00001.x

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.