Modelling the spatial population structure and distribution of the queen conch, Aliger gigas, on the Pedro Bank, Jamaica
The estimation of reliable indices of abundance for sedentary stocks requires the incorporation of the underlying spatial population structure, including issues arising from the sampling design and zero inflation. We applied seven spatial interpolation techniques [ordinary kriging (OK), kriging wit...
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| Format: | Article |
| Language: | English |
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Consejo Superior de Investigaciones Científicas
2022-09-01
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| Series: | Scientia Marina |
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| Online Access: | https://scientiamarina.revistas.csic.es/index.php/scientiamarina/article/view/1929 |
| _version_ | 1811183657646292992 |
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| author | Ricardo A. Morris Alvaro Hernández-Flores Alfonso Cuevas-Jimenez |
| author_facet | Ricardo A. Morris Alvaro Hernández-Flores Alfonso Cuevas-Jimenez |
| author_sort | Ricardo A. Morris |
| collection | DOAJ |
| description |
The estimation of reliable indices of abundance for sedentary stocks requires the incorporation of the underlying spatial population structure, including issues arising from the sampling design and zero inflation. We applied seven spatial interpolation techniques [ordinary kriging (OK), kriging with external drift (KED), a negative binomial generalized additive model (NBGAM), NBGAM plus OK (NBGAM+OK), a general additive mixed model (GAMM), GAMM plus OK (GAMM+OK) and a zero-inflated negative binomial model (ZINB) ] to three survey datasets to estimate biomass for the gastropod Aliger gigas on the Pedro Bank Jamaica. The models were evaluated using 10-fold cross-validation diagnostics criteria for choosing the best model. We also compared the best model estimations against two common design methods to assess the consequences of ignoring the spatial structure of the species distribution. GAMM and ZINB were overall the best models but were strongly affected by the sampling design, sample size, the coefficient of variation of the sample and the quality of the available covariates used to model the distribution (geographic location, depth and habitat). More reliable abundance indices can help to improve stock assessments and the development of spatial management using an ecosystem approach.
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| first_indexed | 2024-04-11T09:49:28Z |
| format | Article |
| id | doaj.art-3571305b7ff846cdaa57c319de95ac95 |
| institution | Directory Open Access Journal |
| issn | 0214-8358 1886-8134 |
| language | English |
| last_indexed | 2024-04-11T09:49:28Z |
| publishDate | 2022-09-01 |
| publisher | Consejo Superior de Investigaciones Científicas |
| record_format | Article |
| series | Scientia Marina |
| spelling | doaj.art-3571305b7ff846cdaa57c319de95ac952022-12-22T04:30:50ZengConsejo Superior de Investigaciones CientíficasScientia Marina0214-83581886-81342022-09-0186310.3989/scimar.05269.040Modelling the spatial population structure and distribution of the queen conch, Aliger gigas, on the Pedro Bank, JamaicaRicardo A. Morris0Alvaro Hernández-Flores1Alfonso Cuevas-Jimenez2Universidad Marista de MéridaUniversidad Marista de MéridaUniversidad Marista de Mérida The estimation of reliable indices of abundance for sedentary stocks requires the incorporation of the underlying spatial population structure, including issues arising from the sampling design and zero inflation. We applied seven spatial interpolation techniques [ordinary kriging (OK), kriging with external drift (KED), a negative binomial generalized additive model (NBGAM), NBGAM plus OK (NBGAM+OK), a general additive mixed model (GAMM), GAMM plus OK (GAMM+OK) and a zero-inflated negative binomial model (ZINB) ] to three survey datasets to estimate biomass for the gastropod Aliger gigas on the Pedro Bank Jamaica. The models were evaluated using 10-fold cross-validation diagnostics criteria for choosing the best model. We also compared the best model estimations against two common design methods to assess the consequences of ignoring the spatial structure of the species distribution. GAMM and ZINB were overall the best models but were strongly affected by the sampling design, sample size, the coefficient of variation of the sample and the quality of the available covariates used to model the distribution (geographic location, depth and habitat). More reliable abundance indices can help to improve stock assessments and the development of spatial management using an ecosystem approach. https://scientiamarina.revistas.csic.es/index.php/scientiamarina/article/view/1929spatial analysissedentary specieszero-inflationspecies distribution models |
| spellingShingle | Ricardo A. Morris Alvaro Hernández-Flores Alfonso Cuevas-Jimenez Modelling the spatial population structure and distribution of the queen conch, Aliger gigas, on the Pedro Bank, Jamaica Scientia Marina spatial analysis sedentary species zero-inflation species distribution models |
| title | Modelling the spatial population structure and distribution of the queen conch, Aliger gigas, on the Pedro Bank, Jamaica |
| title_full | Modelling the spatial population structure and distribution of the queen conch, Aliger gigas, on the Pedro Bank, Jamaica |
| title_fullStr | Modelling the spatial population structure and distribution of the queen conch, Aliger gigas, on the Pedro Bank, Jamaica |
| title_full_unstemmed | Modelling the spatial population structure and distribution of the queen conch, Aliger gigas, on the Pedro Bank, Jamaica |
| title_short | Modelling the spatial population structure and distribution of the queen conch, Aliger gigas, on the Pedro Bank, Jamaica |
| title_sort | modelling the spatial population structure and distribution of the queen conch aliger gigas on the pedro bank jamaica |
| topic | spatial analysis sedentary species zero-inflation species distribution models |
| url | https://scientiamarina.revistas.csic.es/index.php/scientiamarina/article/view/1929 |
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