Including a spatial predictive process in band recovery models improves inference for Lincoln estimates of animal abundance

Gonnerman, Matthew; Linden, Daniel W.; Shea, Stephanie A.; Sullivan, Kelsey; Kamath, Pauline; Blomberg, Erik

doi:10.1002/ece3.9444

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The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.

i

Including a spatial predictive process in band recovery models improves inference for Lincoln estimates of animal abundance

2022
By Gonnerman, Matthew ; Linden, Daniel W. ; Shea, Stephanie A. ; ...
Source: Ecology and Evolution, 12(10)

[PDF-2.80 MB]

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Details:

Journal Title:

Ecology and Evolution
Personal Author:

Gonnerman, Matthew ; Linden, Daniel W. ; Shea, Stephanie A. ; Sullivan, Kelsey ; Kamath, Pauline ; ... More +

Gonnerman, Matthew ; Linden, Daniel W. ; Shea, Stephanie A. ; Sullivan, Kelsey ; Kamath, Pauline ; Blomberg, Erik Less -
NOAA Program & Office:

NMFS (National Marine Fisheries Service) ; GARF (Greater Atlantic Regional Fisheries)

NMFS (National Marine Fisheries Service) ; GARF (Greater Atlantic Regional Fisheries) Less -
Description:

Abundance estimation is a critical component of conservation planning, particularly for exploited species where managers set regulations to restrict harvest based on current population size. An increasingly common approach for abundance estimation is through integrated population modeling (IPM), which uses multiple data sources in a joint likelihood to estimate abundance and additional demographic parameters. Lincoln estimators are one commonly used IPM component for harvested species,
Keywords:

[+]

Ecology Ecology, Evolution, Behavior And Systematics Nature And Landscape Conservation
Source:

Ecology and Evolution, 12(10)
DOI:

https://doi.org/10.1002/ece3.9444
ISSN:

2045-7758;2045-7758;
Format:

PDF
Publisher:

Wiley
Document Type:

Journal Article
License:

https://creativecommons.org/licenses/by/4.0/
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CC BY
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Library
Main Document Checksum:

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urn:sha256:b42f34248ddf5e37f0e1f73f229ace5fc5c835ac5de511300309548c917406b3
Download URL:

https://repository.library.noaa.gov/view/noaa/53267/noaa_53267_DS1.pdf
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