Evidence map›Paper›PMID 40605787›Full record

ArticleEcological applications : a publication of the Ecological Society of America2025

Species aggregation models resolve essential foraging habitat: Implications for conservation and management.

Jarrod A Santora, Justin J Suca, Megan Cimino, Elliott L Hazen, John C Field, Steven J Bograd, Brian K Wells, Isaac D Schroeder

Abstract read
In one paragraph

Article in Ecological applications : a publication of the Ecological Society of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Species aggregation models resolve essential foraging habitat: Implications for conservation and management.Ecological applications : a publication of the Ecological Society of America · 2025
    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

8 authors.

Jarrod A SantoraFisheries Ecology Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Santa Cruz, California, USA.ORCID https://orcid.org/0000-0002-5991-4283
Justin J SucaDepartment of Oceanography, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA.
Megan CiminoInstitute of Marine Sciences, University of California-Santa Cruz, Santa Cruz, California, USA.
Elliott L HazenEcosystem Science Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Monterey, California, USA.ORCID https://orcid.org/0000-0002-0412-7178
John C FieldFisheries Ecology Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Santa Cruz, California, USA.
Steven J BogradEcosystem Science Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Monterey, California, USA.
Brian K WellsFisheries Ecology Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Santa Cruz, California, USA.
Isaac D SchroederInstitute of Marine Sciences, University of California-Santa Cruz, Santa Cruz, California, USA.

Funding

Biological and Physical Sciences Division 80NSSC20M0001Biological and Physical Sciences Division 80NSSX21M003
6 · The paper itself

Abstract

Species aggregations are a culmination of behavioral events arising from an array of biophysical interactions, dynamically shifting in space and time. Prediction of species' aggregation dynamics remains a challenge in studies of their distribution patterns. Species distribution models (SDMs) are statistical tools for understanding spatial patterns of marine biodiversity, ranging from essential species habitat, assessing fisheries bycatch, and projecting future distribution changes. SDMs involving pelagic species abundance generally do not typically resolve aggregation patterns. We use a 20-year observation record of seabird species aggregations, with seabirds being the most easily quantified "pelagic" species, to develop SDMs and a regional ocean modeling system to identify physical drivers and changes in aggregation location and intensity over time. We apply a conceptual ecosystem model to organize environmental covariates according to habitat production within coastal upwelling systems. The SDM used a 2-step modeling approach: a presence/absence model and a binary aggregation model. Thus, we aim to predict factors that characterize baseline ocean habitat for a species (presence/absence) and that aggregate large numbers of the species. Prediction of seabird aggregation results in realistic spatial distribution patterns that reflect known species habitat associations. Temporally, aggregation indices indicate mixed responses both within and between resident and migrant species, reflecting interannual effects of warm/cool ocean years and mesoscale structure supporting enhanced or decreased productive foraging habitat. The most abundant species were more likely to form aggregations during warmer years, indicating a response to a decrease in productive foraging habitat. The occurrence of species aggregations in spring is predictable by examining ocean-climate conditions in the preceding winter, thus providing a potential early warning system of anticipated ecosystem shifts. We contend that the aggregation occurrence model may improve the realism of pelagic SDMs and their utility for assessing spatial and temporal variability of trophic interactions. We discuss the utility of species aggregation models for quantifying the variability in critical pelagic habitats, the ecology and response of seabird species as indicators, advancement of ecosystem modeling and monitoring, and conservation applications (e.g., bycatch, wind energy, and oil spills).

Indexed as

BirdsConservation of Natural ResourcesEcosystemFeeding BehaviorModels, BiologicalAnimalsaggregationconservationdistributionecosystem oceanographyforaging habitatpatchinessrealismspatial organizationspecies distribution model

Identifiers

PMID40605787
PMCPMC12223939

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.