Effects of inconsistent reporting, regulation changes and market demand on abundance indices of sharks caught by pelagic longliners off southern Africa

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Biodiversity and Conservation

Main article text

 

Introduction

Materials and Methods

Study area

Data and assumptions

Data analysis

Results

Nominal trends in fishing effort, landings and shark species composition

CPUE standardization

Discussion

Conclusion

Supplemental Information

The R-coding used for the main analyses for the paper

DOI: 10.7717/peerj.5726/supp-1

An overview of the total number of hooks set, blue and shortfin mako shark catch numbers reported by month, year, region fished, and fleet (local and foreign pelagic longline fishing vessels)

DOI: 10.7717/peerj.5726/supp-2

Final models selected to determine blue shark and shortfin mako CPUE for longline vessels from 2000–2015 for the West area

Included are the estimate, standard error, and p-values for each coefficient of the model. The variables Year, Month and Observer were included as fixed effects in the models. Vessel was the only random effect. The explanatory variables (1—Vessel) + Year + Month + Fleet + Observer consistently provided the lowest BIC for all the models.

DOI: 10.7717/peerj.5726/supp-3

Final models selected to determine blue shark and shortfin mako CPUE for longline vessels from 2000–2015 for the Southwest area

Included are the estimate, standard error, and p-values for each coefficient of the model. The variables Year, Month and Observer were included as fixed effects in the models. Vessel was the only random effect. The explanatory variables (1—Vessel) + Year + Month + Fleet + Observer consistently provided the lowest BIC for all the models.

DOI: 10.7717/peerj.5726/supp-4

Final models selected to determine blue shark and shortfin mako CPUE for longline vessels from 2000–2015 for the South area

Included are the estimate, standard error, and p-values for each coefficient of the model. The variables Year, Month and Observer were included as fixed effects in the models. Vessel was the only random effect. The explanatory variables (1—Vessel) + Year + Month + Fleet + Observer consistently provided the lowest BIC for all the models.

DOI: 10.7717/peerj.5726/supp-5

Final models selected to determine blue shark and shortfin mako CPUE for longline vessels from 2000–2015 for the East area

Included are the estimate, standard error, and p-values for each year for each model. The variables Year, Month and Observer were included as fixed effects in the models. Vessel was the only random effect. The explanatory variables (1—Vessel) + Year + Month + Observer consistently provided the lowest BIC for all the models.

DOI: 10.7717/peerj.5726/supp-6

Additional Information and Declarations

Competing Interests

The authors declare there are no competing interests.

Author Contributions

Gareth L. Jordaan and Johan C. Groeneveld conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.

Jorge Santos conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.

Data Availability

The following information was supplied regarding data availability:

The logbook data provides active fishing positions and the catches of sharks made at each, and cannot be made available in the public domain. Scientists that are interested in using the raw data for bona fide research must apply directly to the Chief Director: Fisheries Research and Development at the Department of Agriculture, Forestry and Fisheries (DAFF) in Cape Town, South Africa (email to kimp@daff.gov.za). After permission is granted by DAFF (on a case by case basis), data files can be made available.

Funding

This work was funded by National Research Foundation (NRF) incentive fund (grant number 96309) to Johan Groeneveld, as well as through a college bursary provided by the University of KwaZulu Natal (UKZN). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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