Award Abstract # 2137684
NSF Convergence Accelerator Track E: Combining high-resolution climate simulations with ocean biogeochemistry, fisheries and decision-making models to improve sustainable fisheries

NSF Org: ITE
Innovation and Technology Ecosystems
Recipient: TEXAS A & M UNIVERSITY
Initial Amendment Date: September 10, 2021
Latest Amendment Date: October 24, 2022
Award Number: 2137684
Award Instrument: Standard Grant
Program Manager: Aurali Dade
ITE
 Innovation and Technology Ecosystems
TIP
 Directorate for Technology, Innovation, and Partnerships
Start Date: October 1, 2021
End Date: September 30, 2024 (Estimated)
Total Intended Award Amount: $749,548.00
Total Awarded Amount to Date: $749,548.00
Funds Obligated to Date: FY 2021 = $749,548.00
History of Investigator:
  • Zhe Zhang (Principal Investigator)
    zhezhang@tamu.edu
  • Gokhan Danabasoglu (Co-Principal Investigator)
  • Keri Stephens (Co-Principal Investigator)
  • Colleen Petrik (Co-Principal Investigator)
  • Piers Chapman (Former Principal Investigator)
  • Zhe Zhang (Former Co-Principal Investigator)
Recipient Sponsored Research Office: Texas A&M University
400 HARVEY MITCHELL PKY S STE 300
COLLEGE STATION
TX  US  77845-4375
(979)862-6777
Sponsor Congressional District: 10
Primary Place of Performance: Texas A&M University
College Station
TX  US  77843-3146
Primary Place of Performance
Congressional District:
10
Unique Entity Identifier (UEI): JF6XLNB4CDJ5
Parent UEI:
NSF Program(s): Convergence Accelerator Resrch
Primary Program Source: 01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):
Program Element Code(s): 131Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.084

ABSTRACT

NSF Convergence Accelerator Track E: Combining high-resolution climate simulations with ocean biogeochemistry, fisheries and decision-making models to improve sustainable fisheries.

Fish and shellfish populations are a vital source of protein for many of the world?s people, and several of the largest are found along the eastern boundaries of the Pacific and Atlantic Oceans, where cold, deep water moves towards the surface, bringing nutrients that support both production by plants (phytoplankton) and the fish populations that feed on them. To ensure sustainability, fish and shellfish managers need information not only on the number of animals available at any given time, but also on potential future numbers, so that they can plan for such things as the number of fishing boats required or the size of seafood processing plants. Forecasting what will occur in such eastern boundary areas is difficult, however, because local winds rapidly change conditions. Adverse climate impacts, such as rising ocean temperatures and increasing acidity, are already affecting many coastal fishing-dependent communities, and such longer-term changes also have to be considered. The project aims to develop a decision support system, which uses the latest ocean models incorporating marine physics, chemistry and biology, to assist fish and shellfish managers in making their decisions. This is important as there are many stakeholders involved in harvesting fish and shellfish, who may have potentially conflicting interests. To this end, the research is aimed at integrating the outputs from the ocean models with a web-based decision support system that will help fisheries managers and industry make informed decisions to ensure that both the industry and its associated food production are sustainable. The investigators will work directly with the stakeholders to develop tools that are specifically able to meet their needs. The initial focus of the work is the California Current system along the U.S. west coast from California to Washington, which supports a local seafood industry valued annually at about $12 billion, with additional billions from catches landed by foreign boats in the U.S. If successful, the new tools should be extendable to other similar regions of the global ocean, thus increasing the value of the research. The project will provide training for students, including those from under-represented groups, in the use of the latest ocean models, as well as development opportunities for young faculty members at the participating institutions.

Climate change-driven adverse ocean impacts are already affecting many rural, coastal, fishing-dependent communities, and these adverse impacts will likely accelerate for the foreseeable future.
Forecasting potential changes in eastern boundary upwelling systems has benefitted recently from improvements in the resolution of global Earth system models, so that the latest eddy-resolving models at 10 km ocean resolution have greatly reduced systematic errors relative to observations. This project aims to use these advancements to improve forecasts of the fisheries potential of the California Current Ecosystem and improve decision making by managers and other stakeholders. The project will couple the output from such a high-resolution model simulation with the Marine Biogeochemistry Library and Fisheries Size and Functional Type models, thus incorporating physics, chemistry and biology with climate variability. The results will be integrated with a prototype, web-based decision support system, that uses mathematical decision analysis capabilities, to assist fisheries managers to model the complex, climate-related decision problems on which fisheries production depends. This is vital to ensure that the region can continue to support a sustainable fishery in the long term and the communities that depend on fishing for a living. In Phase 1, the project will develop a prototype of this linked decision system. The project will also develop a well-networked multidisciplinary team of modelers, social scientists, fisheries managers, economists, and industry and community stakeholders to advance convergence science and develop avenues for more sustainable fisheries under a changing climate. This team is essential for developing tools that are directly applicable to the needs of fishery stakeholders and will be fostered by meaningful communication between all groups throughout the project period. If successful, the model suite and decision support system should be extendable to other similar regions of the global ocean. Students and post-doctoral researchers, the next generation of scientists, will be trained in decision analysis and to use the most current high-resolution models. Furthermore, the project will provide valuable professional development opportunities for early career female Co-PIs involved in the program.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Chang, Ping and Xu, Gaopeng and Kurian, Jaison and Small, R. Justin and Danabasoglu, Gokhan and Yeager, Stephen and Castruccio, Frederic and Zhang, Qiuying and Rosenbloom, Nan and Chapman, Piers "Uncertain future of sustainable fisheries environment in eastern boundary upwelling zones under climate change" Communications Earth & Environment , v.4 , 2023 https://doi.org/10.1038/s43247-023-00681-0 Citation Details
Krumhardt, Kristen M and Long, Matthew C and Petrik, Colleen M and Levy, Michael and Castruccio, Frederic S and Lindsay, Keith and Romashkov, Lev and Deppenmeier, Anna-Lena and Denéchère, Rémy and Chen, Zhuomin and Landrum, Laura and Danabasoglu, Gokhan a "From nutrients to fish: Impacts of mesoscale processes in a global CESM-FEISTY eddying ocean model framework" Progress in Oceanography , v.227 , 2024 https://doi.org/10.1016/j.pocean.2024.103314 Citation Details
Song, Zhenlei and Chapman, Piers and Tao, Jian and Chang, Ping and Gao, Huilin and Liu, Honggao and Brannstrom, Christian and Zhang, Zhe "Mapping the Unheard: Analyzing Tradeoffs Between Fisheries and Offshore Wind Farms Using Multicriteria Decision Analysis" Annals of the American Association of Geographers , v.114 , 2024 https://doi.org/10.1080/24694452.2023.2285371 Citation Details
Xu, Gaopeng and Chang, Ping and Ramachandran, Sanjiv and Danabasoglu, Gokhan and Yeager, Stephen and Small, Justin and Zhang, Qiuying and Jing, Zhao and Wu, Lixin "Impacts of Model Horizontal Resolution on Mean Sea Surface Temperature Biases in the Community Earth System Model" Journal of Geophysical Research: Oceans , v.127 , 2022 https://doi.org/10.1029/2022JC019065 Citation Details

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

While the eastern boundary upwelling systems of the Atlantic and Pacific Oceans occupy only about 1% of the ocean's surface, they produce around 20% of the global fish catch. The California Current System on the West Coast of the U.S. is one such upwelling system. It is a major fishing area, where the value of commercial fisheries is nearly $39 billion per year. 

Under continued climate change, species' ranges are expected to contract poleward, directly affecting their physiology, growth, survival, and reproduction, along with accompanying changes to food webs and ecosystem structure. Given such clear impacts of climate change and variability on the marine environment and dependent fishing communities, the need for climate-ready and forward-looking management approaches is increasing. This requires developing forward-looking decision-support tools that use accurate and reliable predictions of impacts on fishery production and marine ecosystems over various space and time scales to support management decisions and ensure system sustainability. 

The main objective of our project, entitled "Climate Change Adaptation Tools for California Current Fisheries,"  was to develop a decision support system called Sustainable Blue. This system focuses on fisheries management specifically for the California Current System and is capable of forecasting the impacts of climate variability and change on the fisheries along the U.S. West Coast. The Sustainable-Blue decision support system provides the climate, biogeochemistry, and fish model outputs in formats that are simple to use as a group of maps or time series plots accessible via drop down menus.  During Phase I, we established a well-connected, multidisciplinary team consisting of modeling experts, social scientists, fisheries managers, economists, and industry and community stakeholders. Having such a diverse team ensures that the Sustainable Blue is highly relevant to the needs of fishery management. We also conducted 16 interviews with scientists, fishermen, and fishing industry managers to enhance our use-inspired research and to create a decision support tool that meets the needs of stakeholders. To further understand these findings, two members of our team gave a presentation at the California Current Integrated Ecosystem Assessment Group and collected brief survey data. We also completed 8 low-fidelity prototyping interviews and found that, as our users have diverse questions and problems, they require multiple versions of model output and ways to interact with the data. Additionally, we organized a National Science Foundation Expo to showcase our research findings to various communities and stakeholders.

The team has published four journal articles, another is currently under review, and two more are in progress. Our findings highlight the need for a new global high-resolution (10–25 km) prediction system that integrates coupled climate, ocean biogeochemistry, and fish production models. Our findings show that high-resolution simulations provide a much more accurate representation of eastern boundary upwelling systems compared to low-resolution (100 km) models. The team also examined the uncertain future of sustainable fisheries in eastern boundary upwelling zones under climate change, revealing that high-resolution simulations capture significant spatial variations in future upwelling changes that low-resolution models miss. Moreover, the high-resolution coupled climate, ocean biogeochemistry, and fish production model provides a more realistic reconstruction of global ocean nutrients, oxygen, sea ice, plankton, and fish distributions by explicitly resolving mesoscale dynamics, which are crucial for accurately capturing trophodynamic structuring, especially in coastal ecosystems. 

In addition to the Sustainable Blue decision tools, we developed a spatial decision support system to model human-environment interactions. This system presents multiple perspectives and visualizes the balance between fisheries and wind power development. We applied three multicriteria decision models to analyze the decision matrix for selecting wind farm locations and assessing the impacts on fisheries using historical data. Our approach was applied to an upwelling system in Northern California, resulting in ten tailored decision scenarios for different stakeholder groups. Our findings indicate that adaptation scores for specific areas in Northern California decline as the weight assigned to fishery factors increases. Additionally, there is a tendency for high-scoring areas to shift southward as fishery parameters increase.


Last Modified: 01/11/2025
Modified by: Zhe Zhang

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