DOI: 10.25349/d9jk6n
title: Global shark fishing mortality still rising despite widespread regulatory change

description: Over the last two decades, sharks have been increasingly recognized among
 the world’s most threatened wildlife, and hence received
 heightened scientific and regulatory scrutiny. Yet, the effect
 of protective regulations on shark fishing mortality has not been
 evaluated at a global scale. Here we estimate that total fishing
 mortality increased from 76 to 80 million sharks between 2012-2019,
 ~25 million of which were threatened species. Mortality increased
 by 4% in coastal waters but decreased 7% in pelagic fisheries,
 especially across the Atlantic and Western Pacific. By linking fishing
 mortality data to the global regulatory landscape, we show that
 widespread legislation designed to prevent shark finning did not
 reduce mortality, but regional shark fishing or retention bans had
 some success. These analyses combined with expert interviews
 highlight evidence-based solutions to reverse the continued
 overexploitation of sharks.
description: The mortality estimates provided here resulted from the analysis
 of many datasets, both public and private. All datasets used in this
 project are detailed in the attached data Inventory. Please refer to the
 README.md for a brief description of the methods, to the paper
 Supplemental Methods for in-depth methods, and to the associated software
 works for the code used to generate the attached datasets. Each dataset is
 accompanied by a README that provides an overview of the methods used to
 generate the dataset and a description of dataset variables. 
description: Data files can be opened with Microsoft Excel or Numbers. All
 code was run using RStudio: 2022.07.0+548 for MacOS an R version
 4.1.1
description: # Title of Dataset: Global shark fishing mortality still rising despite
 widespread regulatory change --- We estimated spatially explicit global
 shark mortality for all true sharks and Rhinopristiformes from 2012-2019
 at 1x1 degree grids. Total annual mortality was calculated from Regional
 Fisheries Management Organization (RFMO) shark catch (purse seine and
 longlines), coastal shark catch (all gear except purse seine and
 longline), and high seas catch (non-RFMO and unreported RFMO catch). We
 used machine learning to predict RFMO shark catch risk globally using
 self- and observer-reported catch and effort data from RFMOs and a suite
 of environmental parameters. Machine learning allowed us to predict catch
 across areas with otherwise low reporting coverage. Detailed
 reconstructions of shark catch in coastal fisheries and the high seas
 allocated spatially were provided by the Sea Around Us Project. Mortality
 was calculated at the taxa, gear type, year, and grid cell level for both
 RFMO catch and coastal catch using taxa- and gear-specific fate
 information and post-release mortality estimates. Combining spatially
 explicit coastal and RFMO data, total shark fishing mortality (M) was
 calculated in year (y) for each taxa (t) in grid cell (j) as: $M_{y,t,j} =
 R + D_d + ( D_a *M_{pr} )$ where $R$ is retained or landed catch, $D_d$ is
 catch discarded dead, $D_a$ is catch discarded alive, and $M_{pr}$ is the
 post-release mortality rate. All shark catch was assigned to one of four
 fate categories – retained/landed, mortality, discarded dead, or discarded
 alive – with the proportion of catch in each fate category determined
 using the relevant fate dataset (i.e., coastal or RFMO). We calculated
 four sets of fate proportions for coastal catch (with various groupings by
 taxa and gear type) and four sets of fate proportions for RFMO catch.
 Fates were joined to shark catch on a hierarchy of: (i) taxa, gear type,
 (RFMO, year), (ii) taxa (RFMO, year), (iii) gear type (RFMO, year), and
 (iv) total averages (RFMO, year) matching on the highest resolution
 possible for each observation. Mortality was assigned based on fate. All
 catch retained/landed or discarded dead was assigned a mortality of 1.
 Catch discarded alive was assigned a post-release mortality rate using a
 hierarchy of (i) taxa and gear type; (ii) taxa only; (iii) gear class
 only; and (iv) a total average. Please refer to the associated manuscript
 and Supplemental Methods for more information, available
 [here](https://doi.org/10.1126/science.adf8984). ## Description of the
 Data and file structure Data Inventory: The mortality estimates provided
 here resulted from analysis of many datasets both public and private. All
 datasets used in this project are detailed in the attached Data Inventory.
 The `datasets` tab lists all types of data used in the project according
 to the analysis component. Each data type (e.g. RFMO shark catch) is given
 an alphabetic dataset id. A description of the dataset is included and one
 or more associated numeric reference ids. The reference id corresponds to
 each individual piece of data within a dataset and full citations with
 links to download publicly available data are provided in the `references`
 tab. Data that are not publicly available are noted both under ‘Access
 Notes’ in the `datasets` tab and in the `url` of the `references` tab.
 These data must be requested from the appropriate authority. ``` -
 data_inventory.xlxs: an inventory of all the datasets, with references,
 used in the analysis, figures, and tables presented in the associated
 manuscript ``` Please refer to the associated software works for code used
 to generate the output data. Literature review data: The following files
 used in this analysis were compiled through literature review. Please
 refer to each file's README for metadata. ``` - bycatch_fate: data
 collated through literature review on shark fates by species and gear type
 from 1992-2013 - post_release_mortality: data collated through literature
 review on shark post-release mortality rates and ex-vessel mortality rates
 by species and gear type from 1986-2018 ``` Spatial regulations data: The
 following files are spatial representations of shark fishing and finning
 regulations in countries, territories, and RFMOs. Please refer to each
 file's README for metadata. ``` - regulations_by_eez: most current
 shark finning regulation for each country and territory for each maritime
 boundary in Marine Regions v11 - regulations_by_rfmo: most current shark
 finning regulation for four main tuna-RFMOs included in the analysis
 (IATTC, ICCAT, IOTC, WCPFC) ``` Output data: The following files are shark
 mortality calculations and represents a global spatially explicit estimate
 of coastal, high seas, and RFMO shark mortality. Please refer to each
 file's README for metadata. ``` - coastal_shark_mortality_1x1.csv:
 results from the mortality calculation for grid cells within Exclusive
 Economic Zones; estimated shark mortality at 1x1 degree grids by year,
 species, gear type, reporting status, sector, and fate -
 high_seas_shark_mortality_1x1.csv: results from the mortality calculation
 for grid cells within the high seas; estimated shark mortality for
 non-RFMO catch and unreported RFMO catch at 1x1 degree grids by year,
 species, gear type, reporting status, and sector -
 rfmo_shark_mortality_1x1.csv: results from the mortality calculation for
 grid cells within RFMO boundaries; estimated shark mortality at 1x1 degree
 grids by year, species, and gear type ``` The following files are used to
 test for an association between shark mortality and shark fishing and
 finning regulations at the EEZ-level. Please refer to each file's
 README for metadata. ``` - total_mortality_estimate_eez.csv: results from
 the mortality calculation for each Exclusive Economic Zone; estimated
 shark catch and shark mortality by EEZ, year, and gear type -
 eez_predictors_annual.csv: regulations present, total effort, total catch
 of all species, and World Bank Governance Index estimate by EEZ and year
 ``` **Uncertainty disclosure** While the datasets shared here are
 taxonomically and spatially resolved, we caution over interpretation of
 these data at this scale. Please refer to the associated manuscript and
 Supplement Methods Section 5 for discussions of uncertainty surrounding
 shark mortality estimates. ## Sharing/access Information Links to other
 publicly accessible locations of the data: None Was data derived from
 another source? Yes If yes, list source(s): Please refer to the attached
 Data Inventory for a list of all sources