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Record W4406544024 · doi:10.1002/lob.10679

The Next Generation of Marine Heatwaves Science: Takeaways from A Two Week Training Workshop

2025· article· en· W4406544024 on OpenAlexaffabout
Rae Fadlovich, Davíd Carrasco, Erica M. Ferrer, Olivia Graham, Alexandra Khrizman, Abigail Kreuser, Sina S. Pinter, Lydia D. Sims, Rose Una, Anthony Wilson, Wei Zhang, Yifan Zhu, Charles H. Greene

Bibliographic record

VenueLimnology and Oceanography Bulletin · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMarine researchTraining (meteorology)Political sciencePsychologyGeographyOceanographyMeteorologyGeology

Abstract

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Marine heatwaves (MHWs), periods of anomalously warm ocean temperatures lasting days to months (Hobday et al., 2016), have been linked to negative ecological impacts (Smale et al. 2019) and have been increasing in frequency and duration (Oliver et al. 2019). Considerable research is being conducted to identify the drivers of these extreme events and to assess their physical, ecological, and biogeochemical impacts (Oliver et al. 2021; Smith et al. 2023). As is the case for many questions in marine biological, ecological, and oceanographic sciences, there is an evident need in this area for interdisciplinary collaboration, where members of distinct research fields can benefit from sharing their expertise and data with a broader scientific community (Brodie et al. 2022). Interdisciplinary research is of high interest to early career researchers; however, they face particular barriers in developing and sustaining these research networks (Pannell et al. 2019; Brasier et al. 2020). This is in part because their progress is often evaluated in respect to a singular discipline and their career advancement relies upon fast publication rates that are not always compatible with large collaborations (Goring et al. 2014). From August 18–31, 2024, the Marine Heatwaves Training Workshop was held at the University of Washington Friday Harbor Laboratories to support early career researchers pursuing interdisciplinary research. In this piece, we, the 15 in-person workshop participants with the support of our workshop organizer (Fig. 1), discuss the importance of this instructional, project-focused workshop for developing interdisciplinary questions in marine science. Our career stages range from postbaccalaureate to postdoctoral researchers, with the majority being doctoral students or candidates. We, along with our remote participant counterparts, come from countries around the globe, including Australia, Brazil, Canada, Chile, China, Germany, India, Israel, Korea, Mexico, Portugal, and the United States. Our expertise covers a broad range of marine and climate science: we are physical and biological oceanographers, marine scientists, ocean–atmosphere scientists, marine ecologists and biologists, quantitative ecologists, climate scientists, and Earth systems scientists, with many of us identifying with more than one subdiscipline. We joined this workshop with different goals, but all arrived with a common desire to establish interdisciplinary research connections. Many of us were drawn to the opportunity to learn about emerging tools for detecting MHWs and assessing their impacts in our specific disciplines. Others primarily sought to establish collaborations with experts in the field and early career researchers from other institutions and disciplines. As early career researchers, we were primarily seeking to gain technical knowledge, broader research context, and collaborative opportunities to strengthen our current and future MHW research. Dr. Charles Greene organized the Marine Heatwaves Training Workshop, and the CO2 Foundation (https://co2foundation.org/) supported our student participation costs. Fifteen in-person participants were selected based on a review of their resume, statement of interest, and a letter of recommendation. Students were selected to diversify the career stages, number of countries, and the number of institutions/organizations represented. The original intention was to hold an in-person only workshop. However, because the applicant pool was so outstanding, the decision was made to hold a hybrid workshop with both in-person and remote student participants. During the first week of the workshop, recognized experts in the field delivered hybrid lectures designed to: (1) investigate the local and remote drivers of surface and subsurface MHWs, (2) quantify the links between MHWs and other physical or biogeochemical processes, and (3) explore the impacts of MHWs on ecosystem function and species interactions. In the second week, we worked collaboratively in small groups (2–5 people) to analyze MHW datasets that participants or instructors supplied for analysis. During the first week of the workshop, 14 MHW experts delivered 18 lectures and one hands-on training session. All expenses, including travel and honoraria, were covered for the instructors and guest speakers. The lectures are detailed in Supporting Information Table S1 and the recordings are available on the University of Washington Friday Harbor Laboratories YouTube channel (https://www.youtube.com/playlist?list=PLQLS9LFNU0SKLMgqLy9or3MqQ0rHCqYA-), which supported the participation of remote participants from widely different time zones. The lecture topics included defining and characterizing MHWs, available analytical tools, case studies highlighting MHW dynamics and impacts, and more. We also compiled an annotated bibliography of key readings that can be found in Supporting Information Table S2. During the second week of the workshop, we worked on small group projects with themes such as surface and subsurface MHW detection and tracking tool development, methods for characterizing MHWs, assessment of oceanic-atmospheric interactions during MHWs, analysis of the ecological impacts of MHWs that compound with other environmental stressors, climate change attribution, and this article. These short projects provided us with opportunities to establish interdisciplinary collaborations, and at least five groups have continued to develop their research with the hope of eventually publishing their workshop projects. The Marine Heatwaves Training Workshop provided us with a collaborative and intellectually diverse learning environment and helped us forge interdisciplinary connections with other early career researchers and established experts in the field. Common takeaways from the workshop included the importance of establishing a shared vocabulary across disciplines, fluency in multiple coding languages (notably Python, R, and MATLAB), and inclusive open access resources (e.g., data, toolboxes, and Python packages) for MHW analysis. As the workshop participants, we emphasize the importance of interdisciplinary collaboration and the need for open data and open science across disciplines. We encourage other early career researchers to access the recorded workshop material and reach out to authors with shared interests. We are overwhelmingly excited to continue the research established during the workshop but recognize that maintaining the momentum to do so will be challenging. We suggest that, when possible, future workshops seeking to build interdisciplinary collaboration among early career researchers should consider allocating a portion of funding towards providing computational resources, and supporting open-access post-workshop publications, perhaps by having portions of the first week be delivered to all participants via zoom. We recommend the use of pre-workshop surveys to gauge what resources students have regarding computing time and publication cost and the use of pre-workshop video conferencing to establish preliminary research connections. During the formation of workshop projects, we recommend identifying a project lead, connecting them with an established researcher project mentor, and developing a project goal and timeline. This workshop was instrumental in fostering cross-disciplinary research collaborations, and we thus strongly advocate for the development of similar training opportunities for other early career researchers. We would like to thank Dr. Chuck Greene for organizing and facilitating this workshop, and for securing funding for participants. We would also like to thank the CO2 Foundation for providing scholarships for attendance. A big thank you to the in-person and virtual workshop instructors who gave lectures: Drs. Alistair Hobday, Andy Pershing, Bruce Monger, Drew Harvell, Elliot Hazen, Emanuele Di Lorenzo, Erin Meyer-Gutbrod, Hillary Scannell, Julia Parrish, Kathy Mills, Malin Pinsky, Mark Eakin, and Stephen Palumbi. We are especially grateful to Drs. Andy Pershing, Chuck Greene, and Hillary Scannell for their mentorship during our group projects. We would also like to thank the support staff at Friday Harbor Laboratories, especially Megan Connelly, Maia Kreis, and the kitchen staff as well as Dylan Crosby and Don Ruffner for IT support. R.F., E.M.F., O.J.G., and C.E.K. developed the framework for this piece. R.F. led the writing. and all authors contributed to writing and revision. Data S1. Supporting Information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.249
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes2
Has abstractyes

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