Research ArticleECOLOGY

A dynamic ocean management tool to reduce bycatch and support sustainable fisheries

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Science Advances  30 May 2018:
Vol. 4, no. 5, eaar3001
DOI: 10.1126/sciadv.aar3001
  • Fig. 1 Map of tracking and fisheries observer data relative to the PLCA.

    Fisheries observer data are shown as kernel densities, from low (yellow) to high (red) effort. The greatest fishing effort was spatially concentrated in the Southern California Bight. The three tagged species are shown as points, with leatherback turtles migrating from western Pacific breeding grounds to forage in the California Current, blue sharks migrating north-south in the California Current seasonally, and California sea lions remaining within the study area for the duration of our analyses. Inset: The majority of fishing effort (80%) has taken place between August and December throughout the period of the study, with a peak in October.

  • Fig. 2 Habitat suitability predictions for individual species for 1 August 2012 that inform the EcoCast tool, from low (white) to high (blue).

    (A) Swordfish (observer) were predicted to occupy the broadest portion of the California Current. (B) Leatherback turtles (tracking) were predicted to occupy waters offshore of the upwelling front, yet avoiding newly upwelled waters. (C) California sea lions (tracking) occupied cool, nearshore waters with proximity to their haul-out sites. (D) Blue sharks (tracking) were also broadly distributed and avoided the coolest upwelled waters nearshore. (E) Blue sharks (observer) were more closely tied to mesoscale features, incorporating both species distribution and fisheries catchability.

  • Fig. 3 Predicted risk surfaces for bycatch species and integrated EcoCast product for 1 August 2012 and 2015.

    (see movies S1 to S4 for the entire season). Bycatch-only model results for an (A) average year, 2012, in the California Current and (B) an anomalously warm year, 2015, for leatherback turtles, blue sharks, and California sea lions. Integrated EcoCast model predictions for (C) 2012 and (D) 2015 incorporate swordfish in addition to the three aforementioned bycatch species. Values range from −1 (low catch and high bycatch) to 1 (high catch and low bycatch). Risk weightings reflect management concern with leatherbacks and swordfish having the highest, followed by blue sharks, and California sea lions having the lowest (see the Supplementary Materials for details and sensitivity analysis). Risk weightings can be adjusted dependent on management priorities, such as when the fishing season progresses or priorities change.

  • Fig. 4 Comparison of a dynamic ocean management (DOM) approach relative to the existing seasonal PLCA.

    Here, we test two management objectives: a dynamic closure based on a conservative 25% habitat suitability threshold for leatherbacks and a dynamic closure based on the 50% threshold for EcoCast. (A) Nine pixels (dark green, outlined in black) had high turtle bycatch risk for 90 or more days of the 2012 fishing season compared to (B) 79 pixels in the 2015 fishing season. In addition, 86% of the pixels with high turtle bycatch risk for 60 or more days of the season were within the PLCA in 2012 compared to 63% of pixels in 2015. Time series of the ratio of DOM to PLCA area for (C) leatherback protection and (D) integrated EcoCast risk prediction highlight the efficacy of a dynamic approach compared to static protection across contrasting years in the California Current.

  • Table 1 Variable weightings indicating the importance in final boosted regression tree models for tracking and observer data.

    Bathymetry and temperature were reliably the two most important predictors in modeling habitat. Bold numbers highlight the three most important factors for each model. NA, not applicable.

    ObserverTracking
    SwordfishBlue sharkBlue sharkLeatherbackSea lion
    Bottom depth32.947.215.614.649.1
    SST mean18.08.049.334.714.3
    SSHa10.38.24.711.25.4
    Chl-a7.92.711.08.912.2
    y-wind5.73.74.46.11.9
    Lunar phase5.53.5NANANA
    Bottom roughness5.45.54.211.43.0
    SST SD5.36.73.25.12.8
    SSHa SD5.110.24.3NA6.0
    EKE3.94.43.46.15.3

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/4/5/eaar3001/DC1

    Supplementary Methods

    table S1. Species-specific model deviance explained and cross-validation using area under the curve statistics.

    fig. S1. Kernel density plot of fisheries effort and tracking data for leatherback turtles, California sea lions, and blue sharks.

    fig. S2. Sample track with three randomly selected pseudotracks for all three satellite-tracked species.

    fig. S3. Partial response curves from boosted regression trees for sea surface temperature, bathymetry, chl-a, and SSHa across all species models.

    fig. S4. Species-specific predictions with error bounds from boosted regression tree model fitting process.

    fig. S5. Time series of species habitat in a normal (2012) and anomalously warm (2015) year.

    fig. S6. Sensitivity analysis of EcoCast bycatch and integrated risk under varying species weightings to highlight their influence on the final product.

    fig. S7. Operational tool for exploring EcoCast weightings available to managers to assess how varying scenarios change the integrated risk surface.

    movie S1. Animation of daily bycatch predictions for the August to December 2012 fishing season, with red pixels representing high risk and white representing low risk.

    movie S2. Animation of daily bycatch predictions for the August to December 2015 fishing season, with red pixels representing high bycatch risk and white representing low risk.

    movie S3. Animation of daily integrated predictions for the August to December 2012 fishing season, with red pixels representing high bycatch risk and low target catch and with blue pixels representing high target catch and low bycatch risk.

    movie S4. Animation of daily integrated predictions for the August to December 2015 fishing season, with red pixels representing high bycatch risk and low target catch and with blue pixels representing high target catch and low bycatch risk.

  • Supplementary Materials

    This PDF file includes:

    • Supplementary Methods
    • table S1. Species-specific model deviance explained and cross-validation using area under the curve statistics.
    • fig. S1. Kernel density plot of fisheries effort and tracking data for leatherback turtles, California sea lions, and blue sharks.
    • fig. S2. Sample track with three randomly selected pseudotracks for all three satellite-tracked species.
    • fig. S3. Partial response curves from boosted regression trees for sea surface temperature, bathymetry, chl-a, and SSHa across all species models.
    • fig. S4. Species-specific predictions with error bounds from boosted regression tree model fitting process.
    • fig. S5. Time series of species habitat in a normal (2012) and anomalously warm (2015) year.
    • fig. S6. Sensitivity analysis of EcoCast bycatch and integrated risk under varying species weightings to highlight their influence on the final product.
    • fig. S7. Operational tool for exploring EcoCast weightings available to managers to assess how varying scenarios change the integrated risk surface.

    Download PDF

    Other Supplementary Material for this manuscript includes the following:

    • movie S1 (.mp4 format). Animation of daily bycatch predictions for the August to December 2012 fishing season, with red pixels representing high risk and white representing low risk.
    • movie S2 (.mp4 format). Animation of daily bycatch predictions for the August to December 2015 fishing season, with red pixels representing high bycatch risk and white representing low risk.
    • movie S3 (.mp4 format). Animation of daily integrated predictions for the August to December 2015 fishing season, with red pixels representing high bycatch risk and low target catch and with blue pixels representing high target catch and low bycatch risk.
    • movie S4 (.mp4 format). Animation of daily integrated predictions for the August to December 2015 fishing season, with red pixels representing high bycatch risk and low target catch and with blue pixels representing high target catch and low bycatch risk.

    Files in this Data Supplement:

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