Improving the precision of the daily egg production method using generalized additive models

D L Borchers, S T Buckland, I G Priede, S Ahmadi

Research output: Contribution to journalArticle

89 Citations (Scopus)

Abstract

Generalized additive models (GAMs) are used to model spatial variation in egg density and increase the precision of biomass estimates from the daily egg production method. Application of GAMs to survey data from the western mackerel (Scomber scombrus) and horse mackerel (Trachurus trachurus) stocks result in a substantial reduction in coefficients of variation of egg abundance. In developing GAM methods for the daily egg production method, we generalize Pennington's method, in which presence-absence is modelled separately from nonzero observations, and use a new form of the bootstrap that accommodates clustered count data without requiring explicit modelling of the form of clustering. In addition to increasing estimation precision, the use of GAMs has several advantages over stratified sample survey methods. To a large degree they allow the data to determine the form of functional dependence of the response on explanatory variables; they accommodate a wide variety of forms of stochastic variation of the response; they provide maps of the predicted density within the survey area; they provide an objective means of interpolating into unsampled areas; and estimation does not assume random sampling with respect to location.

Original languageEnglish
Pages (from-to)2727-2742
Number of pages16
JournalCanadian Journal of Fisheries and Aquatic Sciences
Volume54
Issue number12
DOIs
Publication statusPublished - Dec 1997

Keywords

  • Bering sea
  • environmental-factors
  • Atlantic Mackerel
  • scomber-scombrus L
  • abundance
  • fish
  • biomass

Cite this

Improving the precision of the daily egg production method using generalized additive models. / Borchers, D L ; Buckland, S T ; Priede, I G; Ahmadi, S .

In: Canadian Journal of Fisheries and Aquatic Sciences, Vol. 54, No. 12, 12.1997, p. 2727-2742.

Research output: Contribution to journalArticle

Borchers, D L ; Buckland, S T ; Priede, I G ; Ahmadi, S . / Improving the precision of the daily egg production method using generalized additive models. In: Canadian Journal of Fisheries and Aquatic Sciences. 1997 ; Vol. 54, No. 12. pp. 2727-2742.
@article{34ac5f6d59524eb1bc54012f77412bc5,
title = "Improving the precision of the daily egg production method using generalized additive models",
abstract = "Generalized additive models (GAMs) are used to model spatial variation in egg density and increase the precision of biomass estimates from the daily egg production method. Application of GAMs to survey data from the western mackerel (Scomber scombrus) and horse mackerel (Trachurus trachurus) stocks result in a substantial reduction in coefficients of variation of egg abundance. In developing GAM methods for the daily egg production method, we generalize Pennington's method, in which presence-absence is modelled separately from nonzero observations, and use a new form of the bootstrap that accommodates clustered count data without requiring explicit modelling of the form of clustering. In addition to increasing estimation precision, the use of GAMs has several advantages over stratified sample survey methods. To a large degree they allow the data to determine the form of functional dependence of the response on explanatory variables; they accommodate a wide variety of forms of stochastic variation of the response; they provide maps of the predicted density within the survey area; they provide an objective means of interpolating into unsampled areas; and estimation does not assume random sampling with respect to location.",
keywords = "Bering sea, environmental-factors, Atlantic Mackerel, scomber-scombrus L, abundance, fish, biomass",
author = "Borchers, {D L} and Buckland, {S T} and Priede, {I G} and S Ahmadi",
year = "1997",
month = "12",
doi = "10.1139/f97-134",
language = "English",
volume = "54",
pages = "2727--2742",
journal = "Canadian Journal of Fisheries and Aquatic Sciences",
issn = "0706-652X",
publisher = "CANADIAN SCIENCE PUBLISHING, NRC RESEARCH PRESS",
number = "12",

}

TY - JOUR

T1 - Improving the precision of the daily egg production method using generalized additive models

AU - Borchers, D L

AU - Buckland, S T

AU - Priede, I G

AU - Ahmadi, S

PY - 1997/12

Y1 - 1997/12

N2 - Generalized additive models (GAMs) are used to model spatial variation in egg density and increase the precision of biomass estimates from the daily egg production method. Application of GAMs to survey data from the western mackerel (Scomber scombrus) and horse mackerel (Trachurus trachurus) stocks result in a substantial reduction in coefficients of variation of egg abundance. In developing GAM methods for the daily egg production method, we generalize Pennington's method, in which presence-absence is modelled separately from nonzero observations, and use a new form of the bootstrap that accommodates clustered count data without requiring explicit modelling of the form of clustering. In addition to increasing estimation precision, the use of GAMs has several advantages over stratified sample survey methods. To a large degree they allow the data to determine the form of functional dependence of the response on explanatory variables; they accommodate a wide variety of forms of stochastic variation of the response; they provide maps of the predicted density within the survey area; they provide an objective means of interpolating into unsampled areas; and estimation does not assume random sampling with respect to location.

AB - Generalized additive models (GAMs) are used to model spatial variation in egg density and increase the precision of biomass estimates from the daily egg production method. Application of GAMs to survey data from the western mackerel (Scomber scombrus) and horse mackerel (Trachurus trachurus) stocks result in a substantial reduction in coefficients of variation of egg abundance. In developing GAM methods for the daily egg production method, we generalize Pennington's method, in which presence-absence is modelled separately from nonzero observations, and use a new form of the bootstrap that accommodates clustered count data without requiring explicit modelling of the form of clustering. In addition to increasing estimation precision, the use of GAMs has several advantages over stratified sample survey methods. To a large degree they allow the data to determine the form of functional dependence of the response on explanatory variables; they accommodate a wide variety of forms of stochastic variation of the response; they provide maps of the predicted density within the survey area; they provide an objective means of interpolating into unsampled areas; and estimation does not assume random sampling with respect to location.

KW - Bering sea

KW - environmental-factors

KW - Atlantic Mackerel

KW - scomber-scombrus L

KW - abundance

KW - fish

KW - biomass

U2 - 10.1139/f97-134

DO - 10.1139/f97-134

M3 - Article

VL - 54

SP - 2727

EP - 2742

JO - Canadian Journal of Fisheries and Aquatic Sciences

JF - Canadian Journal of Fisheries and Aquatic Sciences

SN - 0706-652X

IS - 12

ER -