Evidence map›Paper›PMID 40439603›Full record

ArticleEcology letters2025

Eltonian Niche Modelling: Applying Joint Hierarchical Niche Models to Ecological Networks.

D Matthias Dehling, Hao Ran Lai, Daniel B Stouffer

Abstract read
In one paragraph

Article in Ecology letters, 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. 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

3 authors.

D Matthias DehlingSecuring Antarctica's Environmental Future, School of Biological Sciences, Monash University, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0002-2863-5580
Hao Ran LaiCentre for Integrative Ecology, School of Biological Sciences, University of Canterbury, Christchurch, New Zealand.ORCID https://orcid.org/0000-0001-6871-0146
Daniel B StoufferCentre for Integrative Ecology, School of Biological Sciences, University of Canterbury, Christchurch, New Zealand.ORCID https://orcid.org/0000-0001-9436-9674

Funding

Australian Research Council SRIEAS Securing Antarctica's Environmental Future SR200100005Marsden Fund MFP-UOC2102
6 · The paper itself

Abstract

There is currently a dichotomy in the modelling of Grinnellian and Eltonian niches. Despite similar underlying data, Grinnellian niches are modelled with species-distribution models (SDMs), whereas Eltonian niches are modelled with ecological-network analysis, mainly because the sparsity of species-interaction data prevents the application of SDMs to Eltonian-niche modelling. Here, we propose to adapt recently developed joint species distribution models (JSDMs) to data on ecological networks, functional traits, and phylogenies to model species' Eltonian niches. JSDMs overcome sparsity and improve predictions for individual species by considering non-independent relationships among co-occurring species; this unique ability makes them particularly suited for sparse datasets such as ecological networks. Our Eltonian JSDMs reveal strong relationships between species' Eltonian niches and their functional traits and phylogeny. Moreover, we demonstrate that JSDMs can accurately predict the interactions of species for which no empirical interaction data are available, based solely on their functional traits. This facilitates prediction of new interactions in communities with altered composition, for example, following climate-change induced local extinctions or species introductions. The high interpretability of Eltonian JSDMs will provide unique insights into mechanisms underlying species interactions and the potential impacts of environmental changes and invasive species on species interactions in ecological communities.

Indexed as

EcosystemModels, BiologicalAnimalsPhylogenycommunity ecologyfrugivorous birdsfunctional traitsGrinnellian nicheinteraction networksjoint species distribution modelsphylogenyspecies interactions

Identifiers

PMID40439603
PMCPMC12121635

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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.