Challenges of transferring models of fish abundance between coral reefs

Ana M. M. Sequeira, Camille Mellin, Hector M. Lozano-Montes, Jessica J. Meeuwig, Mathew A. Vanderklift, Michael D. E. Haywood, Russell C. Babcock, M. Julian Caley

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Reliable abundance estimates for species are fundamental in ecology, fisheries, and conservation. Consequently, predictive models able to provide reliable estimates for un- or poorly-surveyed locations would prove a valuable tool for management. Based on commonly used environmental and physical predictors, we developed predictive models of total fish abundance and of abundance by fish family for ten representative taxonomic families for the Great Barrier Reef (GBR) using multiple temporal scenarios. We then tested if models developed for the GBR (reference system) could predict fish abundances at Ningaloo Reef (NR; target system), i.e., if these GBR models could be successfully transferred to NR. Models of abundance by fish family resulted in improved performance (e.g., 44.1 % <R-2 <50.6% for Acanthuridae) compared to total fish abundance (9% <R-2 <18.6%). However, in contrast with previous transferability obtained for similar models for fish species richness from the GBR to NR, transferability for these fish abundance models was poor. When compared with observations of fish abundance collected in NR, our transferability results had low validation scores (R-2 <6%, p > 0.05). High spatio-temporal variability of patterns in fish abundance at the family and population levels in both reef systems likely affected the transferability of these models. Inclusion of additional predictors with potential direct effects on abundance, such as local fishing effort or topographic complexity, may improve transferability of fist local-scale predictors are often not abundance models. However, observations of these available, and might thereby hinder studies on model transferability and its usefulness for conservation planning and management.

Original languageEnglish
Article numbere4566
Number of pages23
JournalPEERJ
Volume6
DOIs
Publication statusPublished - 17 Apr 2018

Cite this

Sequeira, Ana M. M. ; Mellin, Camille ; Lozano-Montes, Hector M. ; Meeuwig, Jessica J. ; Vanderklift, Mathew A. ; Haywood, Michael D. E. ; Babcock, Russell C. ; Caley, M. Julian. / Challenges of transferring models of fish abundance between coral reefs. In: PEERJ. 2018 ; Vol. 6.
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abstract = "Reliable abundance estimates for species are fundamental in ecology, fisheries, and conservation. Consequently, predictive models able to provide reliable estimates for un- or poorly-surveyed locations would prove a valuable tool for management. Based on commonly used environmental and physical predictors, we developed predictive models of total fish abundance and of abundance by fish family for ten representative taxonomic families for the Great Barrier Reef (GBR) using multiple temporal scenarios. We then tested if models developed for the GBR (reference system) could predict fish abundances at Ningaloo Reef (NR; target system), i.e., if these GBR models could be successfully transferred to NR. Models of abundance by fish family resulted in improved performance (e.g., 44.1 {\%} <R-2 <50.6{\%} for Acanthuridae) compared to total fish abundance (9{\%} <R-2 <18.6{\%}). However, in contrast with previous transferability obtained for similar models for fish species richness from the GBR to NR, transferability for these fish abundance models was poor. When compared with observations of fish abundance collected in NR, our transferability results had low validation scores (R-2 <6{\%}, p > 0.05). High spatio-temporal variability of patterns in fish abundance at the family and population levels in both reef systems likely affected the transferability of these models. Inclusion of additional predictors with potential direct effects on abundance, such as local fishing effort or topographic complexity, may improve transferability of fist local-scale predictors are often not abundance models. However, observations of these available, and might thereby hinder studies on model transferability and its usefulness for conservation planning and management.",
keywords = "Great Barrier Reef, Generalized linear mixed-effects modelling, Ningaloo Reef, Species distribution models, Underwater visual counts, SPECIES RICHNESS, COMMUNITY STRUCTURE, HABITAT COMPLEXITY, VARIABILITY, PREDICTORS, DIVERSITY, PATTERNS, REGIONS, BIOMASS",
author = "Sequeira, {Ana M. M.} and Camille Mellin and Lozano-Montes, {Hector M.} and Meeuwig, {Jessica J.} and Vanderklift, {Mathew A.} and Haywood, {Michael D. E.} and Babcock, {Russell C.} and Caley, {M. Julian}",
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Challenges of transferring models of fish abundance between coral reefs. / Sequeira, Ana M. M.; Mellin, Camille; Lozano-Montes, Hector M.; Meeuwig, Jessica J.; Vanderklift, Mathew A.; Haywood, Michael D. E.; Babcock, Russell C.; Caley, M. Julian.

In: PEERJ, Vol. 6, e4566, 17.04.2018.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Challenges of transferring models of fish abundance between coral reefs

AU - Sequeira, Ana M. M.

AU - Mellin, Camille

AU - Lozano-Montes, Hector M.

AU - Meeuwig, Jessica J.

AU - Vanderklift, Mathew A.

AU - Haywood, Michael D. E.

AU - Babcock, Russell C.

AU - Caley, M. Julian

PY - 2018/4/17

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N2 - Reliable abundance estimates for species are fundamental in ecology, fisheries, and conservation. Consequently, predictive models able to provide reliable estimates for un- or poorly-surveyed locations would prove a valuable tool for management. Based on commonly used environmental and physical predictors, we developed predictive models of total fish abundance and of abundance by fish family for ten representative taxonomic families for the Great Barrier Reef (GBR) using multiple temporal scenarios. We then tested if models developed for the GBR (reference system) could predict fish abundances at Ningaloo Reef (NR; target system), i.e., if these GBR models could be successfully transferred to NR. Models of abundance by fish family resulted in improved performance (e.g., 44.1 % <R-2 <50.6% for Acanthuridae) compared to total fish abundance (9% <R-2 <18.6%). However, in contrast with previous transferability obtained for similar models for fish species richness from the GBR to NR, transferability for these fish abundance models was poor. When compared with observations of fish abundance collected in NR, our transferability results had low validation scores (R-2 <6%, p > 0.05). High spatio-temporal variability of patterns in fish abundance at the family and population levels in both reef systems likely affected the transferability of these models. Inclusion of additional predictors with potential direct effects on abundance, such as local fishing effort or topographic complexity, may improve transferability of fist local-scale predictors are often not abundance models. However, observations of these available, and might thereby hinder studies on model transferability and its usefulness for conservation planning and management.

AB - Reliable abundance estimates for species are fundamental in ecology, fisheries, and conservation. Consequently, predictive models able to provide reliable estimates for un- or poorly-surveyed locations would prove a valuable tool for management. Based on commonly used environmental and physical predictors, we developed predictive models of total fish abundance and of abundance by fish family for ten representative taxonomic families for the Great Barrier Reef (GBR) using multiple temporal scenarios. We then tested if models developed for the GBR (reference system) could predict fish abundances at Ningaloo Reef (NR; target system), i.e., if these GBR models could be successfully transferred to NR. Models of abundance by fish family resulted in improved performance (e.g., 44.1 % <R-2 <50.6% for Acanthuridae) compared to total fish abundance (9% <R-2 <18.6%). However, in contrast with previous transferability obtained for similar models for fish species richness from the GBR to NR, transferability for these fish abundance models was poor. When compared with observations of fish abundance collected in NR, our transferability results had low validation scores (R-2 <6%, p > 0.05). High spatio-temporal variability of patterns in fish abundance at the family and population levels in both reef systems likely affected the transferability of these models. Inclusion of additional predictors with potential direct effects on abundance, such as local fishing effort or topographic complexity, may improve transferability of fist local-scale predictors are often not abundance models. However, observations of these available, and might thereby hinder studies on model transferability and its usefulness for conservation planning and management.

KW - Great Barrier Reef

KW - Generalized linear mixed-effects modelling

KW - Ningaloo Reef

KW - Species distribution models

KW - Underwater visual counts

KW - SPECIES RICHNESS

KW - COMMUNITY STRUCTURE

KW - HABITAT COMPLEXITY

KW - VARIABILITY

KW - PREDICTORS

KW - DIVERSITY

KW - PATTERNS

KW - REGIONS

KW - BIOMASS

U2 - 10.7717/peerj.4566

DO - 10.7717/peerj.4566

M3 - Article

VL - 6

JO - PEERJ

JF - PEERJ

SN - 2167-8359

M1 - e4566

ER -