Recreational Fish-Finders—An Inexpensive Alternative to Scientific Echo-Sounders for Unravelling the Links between Marine Top Predators and Their Prey
Studies investigating how mobile marine predators respond to their prey are limited due to the challenging nature of the environment. While marine top predators are increasingly easy to study thanks to developments in bio-logging technology, typically there is scant information on the distribution a...
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| Published in: | PloS one Vol. 10; no. 11; p. e0140936 |
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| Language: | English |
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23.11.2015
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| ISSN: | 1932-6203, 1932-6203 |
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| Abstract | Studies investigating how mobile marine predators respond to their prey are limited due to the challenging nature of the environment. While marine top predators are increasingly easy to study thanks to developments in bio-logging technology, typically there is scant information on the distribution and abundance of their prey, largely due to the specialised nature of acquiring this information. We explore the potential of using single-beam recreational fish-finders (RFF) to quantify relative forage fish abundance and draw inferences of the prey distribution at a fine spatial scale. We compared fish school characteristics as inferred from the RFF with that of a calibrated scientific split-beam echo-sounder (SES) by simultaneously operating both systems from the same vessel in Algoa Bay, South Africa. Customized open-source software was developed to extract fish school information from the echo returns of the RFF. For schools insonified by both systems, there was close correspondence between estimates of mean school depth (R2 = 0.98) and school area (R2 = 0.70). Estimates of relative school density (mean volume backscattering strength; Sv) measured by the RFF were negatively biased through saturation of this system given its smaller dynamic range. A correction factor applied to the RFF-derived density estimates improved the comparability between the two systems. Relative abundance estimates using all schools from both systems were congruent at scales from 0.5 km to 18 km with a strong positive linear trend in model fit estimates with increasing scale. Although absolute estimates of fish abundance cannot be derived from these systems, they are effective at describing prey school characteristics and have good potential for mapping forage fish distribution and relative abundance. Using such relatively inexpensive systems could greatly enhance our understanding of predator-prey interactions. |
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| AbstractList | Studies investigating how mobile marine predators respond to their prey are limited due to the challenging nature of the environment. While marine top predators are increasingly easy to study thanks to developments in bio-logging technology, typically there is scant information on the distribution and abundance of their prey, largely due to the specialised nature of acquiring this information. We explore the potential of using single-beam recreational fish-finders (RFF) to quantify relative forage fish abundance and draw inferences of the prey distribution at a fine spatial scale. We compared fish school characteristics as inferred from the RFF with that of a calibrated scientific split-beam echo-sounder (SES) by simultaneously operating both systems from the same vessel in Algoa Bay, South Africa. Customized open-source software was developed to extract fish school information from the echo returns of the RFF. For schools insonified by both systems, there was close correspondence between estimates of mean school depth (R 2 = 0.98) and school area (R 2 = 0.70). Estimates of relative school density (mean volume backscattering strength; S v ) measured by the RFF were negatively biased through saturation of this system given its smaller dynamic range. A correction factor applied to the RFF-derived density estimates improved the comparability between the two systems. Relative abundance estimates using all schools from both systems were congruent at scales from 0.5 km to 18 km with a strong positive linear trend in model fit estimates with increasing scale. Although absolute estimates of fish abundance cannot be derived from these systems, they are effective at describing prey school characteristics and have good potential for mapping forage fish distribution and relative abundance. Using such relatively inexpensive systems could greatly enhance our understanding of predator-prey interactions. Studies investigating how mobile marine predators respond to their prey are limited due to the challenging nature of the environment. While marine top predators are increasingly easy to study thanks to developments in bio-logging technology, typically there is scant information on the distribution and abundance of their prey, largely due to the specialised nature of acquiring this information. We explore the potential of using single-beam recreational fish-finders (RFF) to quantify relative forage fish abundance and draw inferences of the prey distribution at a fine spatial scale. We compared fish school characteristics as inferred from the RFF with that of a calibrated scientific split-beam echo-sounder (SES) by simultaneously operating both systems from the same vessel in Algoa Bay, South Africa. Customized open-source software was developed to extract fish school information from the echo returns of the RFF. For schools insonified by both systems, there was close correspondence between estimates of mean school depth (R2 = 0.98) and school area (R2 = 0.70). Estimates of relative school density (mean volume backscattering strength; Sv) measured by the RFF were negatively biased through saturation of this system given its smaller dynamic range. A correction factor applied to the RFF-derived density estimates improved the comparability between the two systems. Relative abundance estimates using all schools from both systems were congruent at scales from 0.5 km to 18 km with a strong positive linear trend in model fit estimates with increasing scale. Although absolute estimates of fish abundance cannot be derived from these systems, they are effective at describing prey school characteristics and have good potential for mapping forage fish distribution and relative abundance. Using such relatively inexpensive systems could greatly enhance our understanding of predator-prey interactions. Studies investigating how mobile marine predators respond to their prey are limited due to the challenging nature of the environment. While marine top predators are increasingly easy to study thanks to developments in bio-logging technology, typically there is scant information on the distribution and abundance of their prey, largely due to the specialised nature of acquiring this information. We explore the potential of using single-beam recreational fish-finders (RFF) to quantify relative forage fish abundance and draw inferences of the prey distribution at a fine spatial scale. We compared fish school characteristics as inferred from the RFF with that of a calibrated scientific split-beam echo-sounder (SES) by simultaneously operating both systems from the same vessel in Algoa Bay, South Africa. Customized open-source software was developed to extract fish school information from the echo returns of the RFF. For schools insonified by both systems, there was close correspondence between estimates of mean school depth (R2 = 0.98) and school area (R2 = 0.70). Estimates of relative school density (mean volume backscattering strength; Sv) measured by the RFF were negatively biased through saturation of this system given its smaller dynamic range. A correction factor applied to the RFF-derived density estimates improved the comparability between the two systems. Relative abundance estimates using all schools from both systems were congruent at scales from 0.5 km to 18 km with a strong positive linear trend in model fit estimates with increasing scale. Although absolute estimates of fish abundance cannot be derived from these systems, they are effective at describing prey school characteristics and have good potential for mapping forage fish distribution and relative abundance. Using such relatively inexpensive systems could greatly enhance our understanding of predator-prey interactions.Studies investigating how mobile marine predators respond to their prey are limited due to the challenging nature of the environment. While marine top predators are increasingly easy to study thanks to developments in bio-logging technology, typically there is scant information on the distribution and abundance of their prey, largely due to the specialised nature of acquiring this information. We explore the potential of using single-beam recreational fish-finders (RFF) to quantify relative forage fish abundance and draw inferences of the prey distribution at a fine spatial scale. We compared fish school characteristics as inferred from the RFF with that of a calibrated scientific split-beam echo-sounder (SES) by simultaneously operating both systems from the same vessel in Algoa Bay, South Africa. Customized open-source software was developed to extract fish school information from the echo returns of the RFF. For schools insonified by both systems, there was close correspondence between estimates of mean school depth (R2 = 0.98) and school area (R2 = 0.70). Estimates of relative school density (mean volume backscattering strength; Sv) measured by the RFF were negatively biased through saturation of this system given its smaller dynamic range. A correction factor applied to the RFF-derived density estimates improved the comparability between the two systems. Relative abundance estimates using all schools from both systems were congruent at scales from 0.5 km to 18 km with a strong positive linear trend in model fit estimates with increasing scale. Although absolute estimates of fish abundance cannot be derived from these systems, they are effective at describing prey school characteristics and have good potential for mapping forage fish distribution and relative abundance. Using such relatively inexpensive systems could greatly enhance our understanding of predator-prey interactions. Studies investigating how mobile marine predators respond to their prey are limited due to the challenging nature of the environment. While marine top predators are increasingly easy to study thanks to developments in bio-logging technology, typically there is scant information on the distribution and abundance of their prey, largely due to the specialised nature of acquiring this information. We explore the potential of using single-beam recreational fish-finders (RFF) to quantify relative forage fish abundance and draw inferences of the prey distribution at a fine spatial scale. We compared fish school characteristics as inferred from the RFF with that of a calibrated scientific split-beam echo-sounder (SES) by simultaneously operating both systems from the same vessel in Algoa Bay, South Africa. Customized open-source software was developed to extract fish school information from the echo returns of the RFF. For schools insonified by both systems, there was close correspondence between estimates of mean school depth (R.sup.2 = 0.98) and school area (R.sup.2 = 0.70). Estimates of relative school density (mean volume backscattering strength; S.sub.v) measured by the RFF were negatively biased through saturation of this system given its smaller dynamic range. A correction factor applied to the RFF-derived density estimates improved the comparability between the two systems. Relative abundance estimates using all schools from both systems were congruent at scales from 0.5 km to 18 km with a strong positive linear trend in model fit estimates with increasing scale. Although absolute estimates of fish abundance cannot be derived from these systems, they are effective at describing prey school characteristics and have good potential for mapping forage fish distribution and relative abundance. Using such relatively inexpensive systems could greatly enhance our understanding of predator-prey interactions. |
| Audience | Academic |
| Author | Lacerda, Miguel Ryan, Peter G. Merkle, Dagmar Rademan, Johan Edwards, Loyd C. Coetzee, Janet C. Nyengera, Reason Murrell, Ben Khoosal, Arjun McInnes, Alistair M. van der Westhuizen, Jan J Pichegru, Lorien |
| AuthorAffiliation | 1 Percy FitzPatrick Institute, DST/NRF Centre of Excellence, University of Cape Town, Cape Town, South Africa 4 Branch: Fisheries Management, Department of Agriculture, Forestry and Fisheries, Rogge Bay, South Africa 3 Department of Medicine, University of California San Diego, La Jolla, California, United States of America Centre National de la Recherche Scientifique, Centre d'Etudes Biologiques de Chize, FRANCE 2 Computational Biology Group, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa 5 Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa 7 Raggy Charters, Port Elizabeth, South Africa 6 DST/NRF Centre of Excellence at the Percy FitzPatrick Institute of African Ornithology, Department of Zoology, Nelson Mandela Metropolitan University, Port Elizabeth, South Africa |
| AuthorAffiliation_xml | – name: Centre National de la Recherche Scientifique, Centre d'Etudes Biologiques de Chize, FRANCE – name: 4 Branch: Fisheries Management, Department of Agriculture, Forestry and Fisheries, Rogge Bay, South Africa – name: 6 DST/NRF Centre of Excellence at the Percy FitzPatrick Institute of African Ornithology, Department of Zoology, Nelson Mandela Metropolitan University, Port Elizabeth, South Africa – name: 2 Computational Biology Group, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa – name: 3 Department of Medicine, University of California San Diego, La Jolla, California, United States of America – name: 1 Percy FitzPatrick Institute, DST/NRF Centre of Excellence, University of Cape Town, Cape Town, South Africa – name: 7 Raggy Charters, Port Elizabeth, South Africa – name: 5 Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa |
| Author_xml | – sequence: 1 givenname: Alistair M. surname: McInnes fullname: McInnes, Alistair M. – sequence: 2 givenname: Arjun surname: Khoosal fullname: Khoosal, Arjun – sequence: 3 givenname: Ben surname: Murrell fullname: Murrell, Ben – sequence: 4 givenname: Dagmar surname: Merkle fullname: Merkle, Dagmar – sequence: 5 givenname: Miguel surname: Lacerda fullname: Lacerda, Miguel – sequence: 6 givenname: Reason surname: Nyengera fullname: Nyengera, Reason – sequence: 7 givenname: Janet C. surname: Coetzee fullname: Coetzee, Janet C. – sequence: 8 givenname: Loyd C. surname: Edwards fullname: Edwards, Loyd C. – sequence: 9 givenname: Peter G. surname: Ryan fullname: Ryan, Peter G. – sequence: 10 givenname: Johan surname: Rademan fullname: Rademan, Johan – sequence: 11 givenname: Jan J surname: van der Westhuizen fullname: van der Westhuizen, Jan J – sequence: 12 givenname: Lorien surname: Pichegru fullname: Pichegru, Lorien |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26600300$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1371_journal_pone_0217013 crossref_primary_10_1111_1365_2664_13462 crossref_primary_10_3389_fmars_2019_00146 crossref_primary_10_1002_aqc_4091 crossref_primary_10_1038_s41598_017_16569_x crossref_primary_10_1111_ibi_12457 crossref_primary_10_1016_j_jnc_2025_126919 crossref_primary_10_1016_j_marpol_2017_08_013 |
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| ContentType | Journal Article |
| Copyright | COPYRIGHT 2015 Public Library of Science 2015 McInnes et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2015 McInnes et al 2015 McInnes et al |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have the following interests: Co-author Loyd C. Edwards is employed by Raggy Charters. There are no patents, products in development or marketed products to declare. This does not alter their adherence to all the PLOS ONE policies on sharing data and materials. Conceived and designed the experiments: AMM AK BM JCC PGR JR JJV LP. Performed the experiments: AMM DM RN LCE JR JJV LP. Analyzed the data: AMM AK BM ML JCC. Contributed reagents/materials/analysis tools: AK BM DM JCC. Wrote the paper: AMM BM ML JCC PGR LP. Designed software FISH for hydoacoustic quantification: AK BM. |
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| SubjectTerms | Abundance Acoustics Africa Agriculture Analysis Animal behavior Animals Aquatic Organisms - physiology Backscattering Biotelemetry Commercial fishing Data logging Echo sounding Echolocation Echosounders Ecosystems Estimates Fish Fisheries management Fishes - physiology Fishing Fishing (Recreation) Forage Forages Geography Information processing Linear Models Ornithology Predation (Biology) Predator-prey interactions Predators Predatory Behavior - physiology Prey Recreation Relative abundance Remote sensing Scales Schools Software Source code Spheniscus demersus System effectiveness Transducers Zoology |
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| Title | Recreational Fish-Finders—An Inexpensive Alternative to Scientific Echo-Sounders for Unravelling the Links between Marine Top Predators and Their Prey |
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