Evidence map›Paper›PMID 34347854›Full record

ArticlePloS one2021

Towards a better characterisation of deep-diving whales' distributions by using prey distribution model outputs?

Auriane Virgili, Laura Hedon, Matthieu Authier, Beatriz Calmettes, Diane Claridge, Tim Cole, Peter Corkeron, Ghislain Dorémus, Charlotte Dunn, Tim E Dunn and 16 more

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

26 authors.

Auriane VirgiliObservatoire PELAGIS, UMS 3462 CNRS-La Rochelle Université, La Rochelle, France.ORCID 0000-0002-7581-7985
Laura HedonObservatoire PELAGIS, UMS 3462 CNRS-La Rochelle Université, La Rochelle, France.
Matthieu AuthierObservatoire PELAGIS, UMS 3462 CNRS-La Rochelle Université, La Rochelle, France.
Beatriz CalmettesSpace Oceanography Division, CLS, Ramonville, France.
Diane ClaridgeBahamas Marine Mammal Research Organisation, Marsh Harbour, Abaco, Bahamas.
Tim ColeProtected Species Branch, NOAA Fisheries Northeast Fisheries Science, Woods Hole, Massachusetts, United States of America.
Peter CorkeronProtected Species Branch, NOAA Fisheries Northeast Fisheries Science, Woods Hole, Massachusetts, United States of America.
Ghislain DorémusObservatoire PELAGIS, UMS 3462 CNRS-La Rochelle Université, La Rochelle, France.
Charlotte DunnBahamas Marine Mammal Research Organisation, Marsh Harbour, Abaco, Bahamas.
Tim E DunnJoint Nature Conservation Committee, Inverdee House, Aberdeen, United Kingdom.
Sophie LaranObservatoire PELAGIS, UMS 3462 CNRS-La Rochelle Université, La Rochelle, France.
Patrick LehodeySpace Oceanography Division, CLS, Ramonville, France.
Mark LewisProtected Species Branch, NOAA Fisheries Northeast Fisheries Science, Woods Hole, Massachusetts, United States of America.
Maite LouzaoAZTI, Marine Research, Basque Research and Technology Alliance (BRTA), Pasaia, Spain.
Laura MannocciMARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Sète, France.
José Martínez-CedeiraCEMMA, Pontevedra, Spain.
Pascal MonestiezBioSP, INRA, Avignon, France.
Debra PalkaProtected Species Branch, NOAA Fisheries Northeast Fisheries Science, Woods Hole, Massachusetts, United States of America.
Emeline PettexADERA, Pessac Cedex, Pessac, France.ORCID 0000-0002-3395-8405
Jason J RobertsMarine Geospatial Ecology Laboratory, Duke University, Durham, North Carolina, United States of America.
Leire RuizAMBAR Elkartea Organisation, Bizkaia, Spain.ORCID 0000-0001-6511-2503
Camilo SaavedraInstituto Español de Oceanografía, Centro Oceanográfico de Vigo, Vigo, Spain.
M Begoña SantosInstituto Español de Oceanografía, Centro Oceanográfico de Vigo, Vigo, Spain.ORCID 0000-0002-5759-1695
Olivier Van CanneytObservatoire PELAGIS, UMS 3462 CNRS-La Rochelle Université, La Rochelle, France.
José Antonio Vázquez BonalesAlnilam Research and Conservation, Madrid, Spain.
Vincent RidouxObservatoire PELAGIS, UMS 3462 CNRS-La Rochelle Université, La Rochelle, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In habitat modelling, environmental variables are assumed to be proxies of lower trophic levels distribution and by extension, of marine top predator distributions. More proximal variables, such as potential prey fields, could refine relationships between top predator distributions and their environment. In situ data on prey distributions are not available over large spatial scales but, a numerical model, the Spatial Ecosystem And POpulation DYnamics Model (SEAPODYM), provides simulations of the biomass and production of zooplankton and six functional groups of micronekton at the global scale. Here, we explored whether generalised additive models fitted to simulated prey distribution data better predicted deep-diver densities (here beaked whales Ziphiidae and sperm whales Physeter macrocephalus) than models fitted to environmental variables. We assessed whether the combination of environmental and prey distribution data would further improve model fit by comparing their explanatory power. For both taxa, results were suggestive of a preference for habitats associated with topographic features and thermal fronts but also for habitats with an extended euphotic zone and with large prey of the lower mesopelagic layer. For beaked whales, no SEAPODYM variable was selected in the best model that combined the two types of variables, possibly because SEAPODYM does not accurately simulate the organisms on which beaked whales feed on. For sperm whales, the increase model performance was only marginal. SEAPODYM outputs were at best weakly correlated with sightings of deep-diving cetaceans, suggesting SEAPODYM may not accurately predict the prey fields of these taxa. This study was a first investigation and mostly highlighted the importance of the physiographic variables to understand mechanisms that influence the distribution of deep-diving cetaceans. A more systematic use of SEAPODYM could allow to better define the limits of its use and a development of the model that would simulate larger prey beyond 1,000 m would probably better characterise the prey of deep-diving cetaceans.

Indexed as

Animal DistributionAnimalsBiomassDivingEcosystemFeeding BehaviorOceans and SeasPredatory BehaviorSperm WhaleZooplankton

Identifiers

PMID34347854
PMCPMC8336804

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.