Evidence map›Paper›PMID 41272402›Full record

ArticleEcological applications : a publication of the Ecological Society of America2025

Weak effects of local prey density and spatial overlap on predation intensity in a temperate marine ecosystem.

Max Lindmark, Christopher A Griffiths, Valerio Bartolino, Viktor Thunell, Federico Maioli, Sean C Anderson, Andrea Belgrano, Michele Casini, Katarzyna Nadolna-Ałtyn, Joanna Pawlak and 7 more

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. Weak effects of local prey density and spatial overlap on predation intensity in a temperate marine ecosystem.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

17 authors.

Max LindmarkDepartment of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, Lysekil, Sweden.ORCID https://orcid.org/0000-0002-3841-4044
Christopher A GriffithsDepartment of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, Lysekil, Sweden.ORCID https://orcid.org/0000-0001-7203-0426
Valerio BartolinoDepartment of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, Lysekil, Sweden.ORCID https://orcid.org/0000-0002-4506-4329
Viktor ThunellDepartment of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, Lysekil, Sweden.ORCID https://orcid.org/0000-0003-1383-6387
Federico MaioliNational Institute of Aquatic Resources, Technical University of Denmark, Kongens Lyngby, Denmark.ORCID https://orcid.org/0000-0002-8305-1609
Sean C AndersonPacific Biological Station, Fisheries and Oceans Canada, Nanaimo, British Columbia, Canada.ORCID https://orcid.org/0000-0001-9563-1937
Andrea BelgranoDepartment of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, Lysekil, Sweden.ORCID https://orcid.org/0000-0002-7768-1946
Michele CasiniDepartment of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, Lysekil, Sweden.ORCID https://orcid.org/0000-0003-4910-5236
Katarzyna Nadolna-AłtynNational Marine Fisheries Research Institute, Gdynia, Poland.ORCID https://orcid.org/0000-0001-5507-2595
Joanna PawlakNational Marine Fisheries Research Institute, Gdynia, Poland.ORCID https://orcid.org/0000-0002-4684-9670
Marzenna PachurNational Marine Fisheries Research Institute, Gdynia, Poland.ORCID https://orcid.org/0000-0002-7689-4886
Marcin RakowskiNational Marine Fisheries Research Institute, Gdynia, Poland.ORCID https://orcid.org/0000-0002-7943-8851
Karolina WikströmDepartment of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, Lysekil, Sweden.ORCID https://orcid.org/0000-0002-6490-2690
Murray S A ThompsonCentre for Environment, Fisheries and Aquaculture Science (Cefas), Lowestoft, UK.ORCID https://orcid.org/0000-0002-9567-175X
Mayya GoginaLeibniz Institute for Baltic Sea Research Warnemünde, Rostock, Germany.ORCID https://orcid.org/0000-0003-0909-4296
Didzis UstupsFish Resources Research Department, Institute of Food Safety, Animal Health and Environment BIOR, Riga, Latvia.ORCID https://orcid.org/0000-0002-3322-2211
Nis S JacobsenNational Institute of Aquatic Resources, Technical University of Denmark, Kongens Lyngby, Denmark.ORCID https://orcid.org/0000-0001-8754-4518

Funding

German Federal Ministry of Education and Research 03F0937ANatural Environment Research Council NE/V017039/1Oscar and Lili Lamm Memorial Foundation FO2023-0037
6 · The paper itself

Abstract

Quantifying the impact of lower trophic level species abundance on higher trophic level predators (and vice versa) is critical for understanding marine ecosystem dynamics and for implementing ecosystem-based management. Trophic ecosystem models generally predict a tight coupling between prey and fish predators, such that higher abundance of lower trophic species increases the abundance of higher trophic level predators. This assumes that predator feeding rates are limited by prey availability to some degree. Despite being a key component of predator-prey interactions and multispecies fisheries management, relatively few studies have assessed the impacts of prey availability on predation patterns of mobile, generalist fish predators using spatiotemporal models and local-scale stomach content, predator, and prey data. In this study, we explore the association between local density of key prey and predator stomach contents, and predator-prey spatiotemporal overlap and predation indices, using the Baltic Sea as a case study. We use three decades of spatially resolved biomass and stomach content data on Atlantic cod (Gadus morhua), and biomass data on three of its key prey: herring (Clupea harengus), the isopod Saduria entomon, and sprat (Sprattus sprattus). Using geostatistical generalized linear mixed-effects models fitted to relative biomass density and prey-mass-per-predator-mass, we estimate spatiotemporal trends and annual indices of biomass- weighted and area-expanded per-capita and population-level predation, predator-prey overlap, and the correlation between these indices. Range shifts have resulted in reduced predator-prey overlap over time, which is now the lowest in three decades. For Saduria, we find an association between prey availability and stomach contents, but not for herring or sprat. Similarly, only in Saduria do we find a positive correlation between population-level predation indices and the spatiotemporal overlap. Although behavioral interactions with pelagic prey are challenging to infer from stomach content and acoustic data due to high mobility leading to fine-scale spatiotemporal mismatch, the weak connection with local-scale availability, and low correlation between population-level predation and spatial overlap, could imply weaker coupling between pelagic prey and cod than previously thought. These findings provide key information on the strength of species interactions, which is crucial for the continued development of multispecies models and ecosystem-based fisheries management.

Indexed as

EcosystemFishesFood ChainIsopodaPredatory BehaviorAnimalsOceans and SeasPopulation DensityAtlantic codBaltic Seadietecosystem‐based fisheries managementpredator–prey dynamicsspatiotemporal mixed modelsspecies distribution modelingstomach data

Identifiers

PMID41272402
PMCPMC12638530

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.