ReviewNature ecology & evolution2025
More realistic plankton simulation models will improve projections of ocean ecosystem responses to global change.
Review in Nature ecology & evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
32 authors.
Funding
Abstract
Plankton models form the core of marine ecosystem simulators, with uses from regional resource and ecosystem management to climate change projections. In this Perspective, we suggest that stronger alignment of models with empirical knowledge about plankton physiology, diversity and trophic roles will improve model utility and the reliability of their outputs regarding biodiversity, ecophysiology, trophic dynamics and biogeochemistry. We recommend key steps to resolve the disconnect between empirical research and simulation models accounting for well-established plankton processes with an aim to increase the utility of such models for applied uses. A central challenge is characterizing the complexity of plankton diversity and activity in ways that are amenable to model incorporation. We argue that experts in empirical science are best placed to advise the development of next-generation models to address these challenges, and we propose a series of actions to achieve that engagement, including involvement of these experts in the design and exploitation of plankton digital twins.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.