Evidence map›Paper›PMID 38281273›Full record

ArticleBulletin of mathematical biology2024

Making Your Own Luck: Weak Vertical Swimming Improves Dispersal Success for Coastal Marine Larvae.

Alexander D Meyer, Alan Hastings, John L Largier

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alexander D MeyerDepartment of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA. ameyer7@nd.edu.ORCID 0000-0002-1512-5741
Alan HastingsDepartment of Environmental Science and Policy, University of California, Davis, CA, USA.ORCID 0000-0002-0717-8026
John L LargierDepartment of Environmental Science and Policy, University of California, Davis, CA, USA.ORCID 0000-0003-4273-4443

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dispersive early life stages are common in nature. Although many dispersing organisms ("propagules") are passively moved by outside forces, some improve their chances of successful dispersal through weak movements that exploit the structure of the environment to great effect. The larvae of many coastal marine invertebrates, for instance, swim vertically through the water column to exploit depth-varying currents, food abundance, and predation risk. Several swimming behaviors and their effects on dispersal between habitats are characterized in the literature, yet it remains unclear when and why these behaviors are advantageous. We addressed this gap using a mathematical model of larval dispersal that scored how well behaviors allowed larvae to simultaneously locate habitats, avoid predators, and gather energy. We computed optimal larval behaviors through dynamic programming, and compared those optima against passive floating and three well documented behaviors from the literature. Optimal behaviors often (but not always) resembled the documented ones. However, our model predicted that the behaviors from the literature performed robustly well, if not optimally, across many conditions. Our results shed light on why some larval behaviors are widespread geographically and across species, and underscore the importance of carefully considering the weak movements of otherwise passive propagules when studying dispersal.

Indexed as

Models, BiologicalSwimmingAnimalsEcosystemLarvaMathematical ConceptsBehavioral ecologyDispersal ecologyDynamic programmingMarine ecologyOptimal control

Identifiers

PMID38281273
PMCPMC10822797

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.