Evidence map›Paper›PMID 41673439›Full record

ArticleScientific reports2026

Integrating species distribution modeling and climate projections to predict ant species redistribution.

Arsalan Khalili-Moghadam, Pejman Tahmasebi

Abstract read
In one paragraph

Article in Scientific reports, 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

2 authors.

Arsalan Khalili-MoghadamPlant Protection Department, Agricultural College, Shahrekord University, Shahrekord, Iran. arsalan.khalili@gmail.com.ORCID http://orcid.org/0000-0002-5806-1207
Pejman TahmasebiRangeland and Watershed Department, Faculty of Natural Resources and Rangeland Sciences, Shahrekord University, Shahrekord, Iran.ORCID http://orcid.org/0000-0003-4315-6251

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As ecologically dominant keystone species, ants play critical roles in ecosystem functioning and trophic interactions. This study examines current and future distribution patterns of five ant species (Cataglyphis nodus, Crematogaster subdentata, Lasius neglectus, Messor platyceras, and Messor syriacus) across central Iran's forest, grassland, and human-modified landscapes. Species were collected along an ecological gradient extending from the central Zagros Mountains to Gavkhouni Lake on the Iranian Plateau. Using an ensemble species distribution modeling (SDM) approach incorporating five machine learning algorithms (Generalized Additive Model, GAM, Generalized Boosted Model, GBM, Generalized Linear Model, GLM, Random Forests, RF, and Extreme Gradient Boosting, XGBOOST), we evaluated habitat suitability under climate change scenarios (Shared Socioeconomic Pathways, SSP126 to SSP585, 2021-2040, 2041-2060, 2061-2080, 2081-2100). Environmental predictors included 19 bioclimatic variables, topography, and NDVI-derived vegetation indices to assess current habitat suitability and to project future distributions under climate change scenarios from 2021 to 2100. Our best ensemble model (GBM) showed strong predictive performance (Receiver Operating Characteristic, ROC,: 0.78-0.90; max True Skill Statistic, TSS,: 0.75), identifying temperature variables, precipitation metrics, and the Normalized Difference Vegetation Index ,NDVI, as key environmental drivers. Projected range changes (2021-2100) revealed species-specific responses: C. nodus, C. subdentata and M. platyceras showed maximum gains and losses under SSP126 and SSP585 respectively in different period; L. neglectus displayed extreme reduction potential, exhibited maximum gains and losses under SSP245 and SSP585 respectively in different period; while M. syriacus showed relative stability maximum gains and losses under SSP370 and SSP585 in different period, highlighting significant interspecific variability in climate change vulnerability across emission scenarios. Niche breadth analysis identified C. nodus and M. platyceras as "winners" transitioning toward generalist strategies, while C. subdentata remained a vulnerable specialist. These findings highlight: (1) substantial interspecific variability in climate vulnerability, (2) the critical influence of emission scenarios on distributional outcomes, and (3) the importance of vegetation-mediated microclimates in buffering climate impacts. Conservation efforts must prioritize microhabitat preservation and landscape connectivity, particularly for functionally important species. The results provide crucial insights for conservation prioritization in arid land ecosystems under global change.

Indexed as

AntsClimate ChangeAnimalsBoosting Machine Learning AlgorithmsClimateEcosystemIranBIOMOD2Global climate changeSpecies distribution modeling

Identifiers

PMID41673439
PMCPMC12963368

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.