Evidence map›Paper›PMID 42525649›Full record

ArticlePloS one2026

Predicting daily lactation costs of marine mammals for use in bioenergetic models.

Elizabeth A McHuron

Abstract read
In one paragraph

Article in PloS one, 2026. 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

1 author.

Elizabeth A McHuronCooperative Institute for Climate, Ocean, and Ecosystem Studies, University of Washington, Seattle, Washington United States of America.ORCID https://orcid.org/0000-0003-3147-2628

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Empirical estimates of energetic processes are limited or absent for many marine mammal species, hindering the ability to quantify disturbance-related impacts on population dynamics using bioenergetic approaches. In this study, published estimates of mass-specific milk intake rates and milk energy density from marine mammals and taxonomically related terrestrial mammals were used to examine how these variables changed as a function of the percentage of time into the lactation interval. Predictions of milk energy intake derived from these relationships were compared with independent estimates from other approaches to inform their utility in estimating daily lactation costs of data-poor species. Daily mass-specific milk intake rates declined between the start and end of lactation for all taxonomic groups, but the rate of decline was much steeper for ursids, artiodactyls, and mustelids than it was for otariids or phocids. Similarly, most taxonomic groups exhibited some increases in milk energy density as lactation progressed, but the magnitude and timing varied among families. Comparisons with independent estimates revealed the likely utility for using the derived relationships in estimating daily lactation costs of data-poor phocids, otariids, and mustelids, with some caveats. There was a large mismatch in the temporal pattern between independent estimates for cetaceans and predictions derived from semi-aquatic and terrestrial species, indicating that cetaceans have higher mass-specific milk intake rates early in lactation compared to most other species that then rapidly decline during the first 10-25% of the lactation interval. Such differences may be an adaptation to a fully aquatic lifestyle and highlight the importance of other methods for estimating daily lactation costs of data-poor cetaceans in bioenergetic models.

Indexed as

Aquatic OrganismsEnergy MetabolismLactationMammalsModels, BiologicalAnimalsFemaleMilk

Identifiers

PMID42525649
PMCPMC13419228

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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.