Environmentally Driven Seasonal Forecasts of Pacific Hake Distribution
Changing ecosystem conditions present a challenge for the monitoring and management of living marine resources, where decisions often require lead-times of weeks to months. Consistent improvement in the skill of regional ocean models to predict physical ocean states at seasonal time scales provides...
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2020-10-01
|
| Series: | Frontiers in Marine Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fmars.2020.578490/full |
| _version_ | 1818137116037611520 |
|---|---|
| author | Michael J. Malick Samantha A. Siedlecki Emily L. Norton Isaac C. Kaplan Melissa A. Haltuch Mary E. Hunsicker Sandra L. Parker-Stetter Kristin N. Marshall Aaron M. Berger Albert J. Hermann Nicholas A. Bond Stéphane Gauthier |
| author_facet | Michael J. Malick Samantha A. Siedlecki Emily L. Norton Isaac C. Kaplan Melissa A. Haltuch Mary E. Hunsicker Sandra L. Parker-Stetter Kristin N. Marshall Aaron M. Berger Albert J. Hermann Nicholas A. Bond Stéphane Gauthier |
| author_sort | Michael J. Malick |
| collection | DOAJ |
| description | Changing ecosystem conditions present a challenge for the monitoring and management of living marine resources, where decisions often require lead-times of weeks to months. Consistent improvement in the skill of regional ocean models to predict physical ocean states at seasonal time scales provides opportunities to forecast biological responses to changing ecosystem conditions that impact fishery management practices. In this study, we used 8-month lead-time predictions of temperature at 250 m depth from the J-SCOPE regional ocean model, along with stationary habitat conditions (e.g., distance to shelf break), to forecast Pacific hake (Merluccius productus) distribution in the northern California Current Ecosystem (CCE). Using retrospective skill assessments, we found strong agreement between hake distribution forecasts and historical observations. The top performing models [based on out-of-sample skill assessments using the area-under-the-curve (AUC) skill metric] were a generalized additive model (GAM) that included shelf-break distance (i.e., distance to the 200 m isobath) (AUC = 0.813) and a boosted regression tree (BRT) that included temperature at 250 m depth and shelf-break distance (AUC = 0.830). An ensemble forecast of the top performing GAM and BRT models only improved out-of-sample forecast skill slightly (AUC = 0.838) due to strongly correlated forecast errors between models (r = 0.88). Collectively, our results demonstrate that seasonal lead-time ocean predictions have predictive skill for important ecological processes in the northern CCE and can be used to provide early detection of impending distribution shifts of ecologically and economically important marine species. |
| first_indexed | 2024-12-11T09:51:11Z |
| format | Article |
| id | doaj.art-5eb6095fe4c04f80b91486ac5b4956a1 |
| institution | Directory Open Access Journal |
| issn | 2296-7745 |
| language | English |
| last_indexed | 2024-12-11T09:51:11Z |
| publishDate | 2020-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Marine Science |
| spelling | doaj.art-5eb6095fe4c04f80b91486ac5b4956a12022-12-22T01:12:23ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452020-10-01710.3389/fmars.2020.578490578490Environmentally Driven Seasonal Forecasts of Pacific Hake DistributionMichael J. Malick0Samantha A. Siedlecki1Emily L. Norton2Isaac C. Kaplan3Melissa A. Haltuch4Mary E. Hunsicker5Sandra L. Parker-Stetter6Kristin N. Marshall7Aaron M. Berger8Albert J. Hermann9Nicholas A. Bond10Stéphane Gauthier11NRC Research Associateship Program, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, United StatesDepartment of Marine Sciences, University of Connecticut, Groton, CT, United StatesJoint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA, United StatesConservation Biology Division, Northwest Fisheries Science Center, National Oceanic and Atmospheric Administration, Seattle, WA, United StatesFishery Resource Analysis and Monitoring Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, United StatesFish Ecology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Newport, OR, United StatesFishery Resource Analysis and Monitoring Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, United StatesFishery Resource Analysis and Monitoring Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, United StatesFishery Resource Analysis and Monitoring Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Newport, OR, United StatesJoint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA, United StatesJoint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA, United StatesInstitute of Ocean Sciences, Fisheries and Oceans Canada, Sidney, BC, CanadaChanging ecosystem conditions present a challenge for the monitoring and management of living marine resources, where decisions often require lead-times of weeks to months. Consistent improvement in the skill of regional ocean models to predict physical ocean states at seasonal time scales provides opportunities to forecast biological responses to changing ecosystem conditions that impact fishery management practices. In this study, we used 8-month lead-time predictions of temperature at 250 m depth from the J-SCOPE regional ocean model, along with stationary habitat conditions (e.g., distance to shelf break), to forecast Pacific hake (Merluccius productus) distribution in the northern California Current Ecosystem (CCE). Using retrospective skill assessments, we found strong agreement between hake distribution forecasts and historical observations. The top performing models [based on out-of-sample skill assessments using the area-under-the-curve (AUC) skill metric] were a generalized additive model (GAM) that included shelf-break distance (i.e., distance to the 200 m isobath) (AUC = 0.813) and a boosted regression tree (BRT) that included temperature at 250 m depth and shelf-break distance (AUC = 0.830). An ensemble forecast of the top performing GAM and BRT models only improved out-of-sample forecast skill slightly (AUC = 0.838) due to strongly correlated forecast errors between models (r = 0.88). Collectively, our results demonstrate that seasonal lead-time ocean predictions have predictive skill for important ecological processes in the northern CCE and can be used to provide early detection of impending distribution shifts of ecologically and economically important marine species.https://www.frontiersin.org/article/10.3389/fmars.2020.578490/fullCalifornia Currentnon-stationaryPacific hakeclimatetemperatureforecast |
| spellingShingle | Michael J. Malick Samantha A. Siedlecki Emily L. Norton Isaac C. Kaplan Melissa A. Haltuch Mary E. Hunsicker Sandra L. Parker-Stetter Kristin N. Marshall Aaron M. Berger Albert J. Hermann Nicholas A. Bond Stéphane Gauthier Environmentally Driven Seasonal Forecasts of Pacific Hake Distribution Frontiers in Marine Science California Current non-stationary Pacific hake climate temperature forecast |
| title | Environmentally Driven Seasonal Forecasts of Pacific Hake Distribution |
| title_full | Environmentally Driven Seasonal Forecasts of Pacific Hake Distribution |
| title_fullStr | Environmentally Driven Seasonal Forecasts of Pacific Hake Distribution |
| title_full_unstemmed | Environmentally Driven Seasonal Forecasts of Pacific Hake Distribution |
| title_short | Environmentally Driven Seasonal Forecasts of Pacific Hake Distribution |
| title_sort | environmentally driven seasonal forecasts of pacific hake distribution |
| topic | California Current non-stationary Pacific hake climate temperature forecast |
| url | https://www.frontiersin.org/article/10.3389/fmars.2020.578490/full |
| work_keys_str_mv | AT michaeljmalick environmentallydrivenseasonalforecastsofpacifichakedistribution AT samanthaasiedlecki environmentallydrivenseasonalforecastsofpacifichakedistribution AT emilylnorton environmentallydrivenseasonalforecastsofpacifichakedistribution AT isaacckaplan environmentallydrivenseasonalforecastsofpacifichakedistribution AT melissaahaltuch environmentallydrivenseasonalforecastsofpacifichakedistribution AT maryehunsicker environmentallydrivenseasonalforecastsofpacifichakedistribution AT sandralparkerstetter environmentallydrivenseasonalforecastsofpacifichakedistribution AT kristinnmarshall environmentallydrivenseasonalforecastsofpacifichakedistribution AT aaronmberger environmentallydrivenseasonalforecastsofpacifichakedistribution AT albertjhermann environmentallydrivenseasonalforecastsofpacifichakedistribution AT nicholasabond environmentallydrivenseasonalforecastsofpacifichakedistribution AT stephanegauthier environmentallydrivenseasonalforecastsofpacifichakedistribution |