Evidence map›Paper›PMID 42746656›Full record

ArticleEcology and evolution2026

ACERT: Agent-Based Model of Complex Life Cycle Evolution-R Tools.

Jesus A Lopez, Robert B Page, Ashley I Teufel

Abstract read
In one paragraph

Article in Ecology and evolution, 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
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1 · What the graph read from it

What it found

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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.

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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

3 authors.

Jesus A LopezDepartment of Natural Sciences Texas A&M University-San Antonio San Antonio Texas USA.
Robert B PageDepartment of Biology & Microbiology Northwestern State University Natchitoches Louisiana USA.
Ashley I TeufelDepartment of Natural Sciences Texas A&M University-San Antonio San Antonio Texas USA.ORCID https://orcid.org/0000-0003-3613-9517

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Agent-based models (ABMs) are increasingly used to study eco-evolutionary dynamics in organisms with complex life cycles, but downstream analysis of model output remains a bottleneck. Simulations can generate millions of records across individuals, time points, and replicates, often spread across many files and requiring extensive custom preprocessing before biological interpretation is possible. We present ACERT (Agent-based model of Complex life cycle Evolution-R Tools), an open-source R package that provides an integrated workflow for importing, cleaning, analyzing, and visualizing ABM outputs tailored to systems with complex life cycles. ACERT reads individual-level records for mobile agents, called "turtles" in NetLogo terminology, patch-level environment data, and allelic mutation files; standardizes these streams into analysis-ready structures; and links directly to established population-genetic inference methods. The package supports phenotype and demographic summaries, spatial and landscape diagnostics, migration and replicate similarity assessment, population-genetic diversity and differentiation statistics, and exploratory microevolutionary tools including major-allele trajectory tracking and selection-screening workflows. ACERT also includes functions for generating synthetic example datasets and building reproducible reports. By consolidating domain-specific preprocessing and analysis steps into a single, coherent package, ACERT reduces the technical overhead associated with simulation-based inference and improves reproducibility.

Indexed as

agent‐based modelingcomplex life cyclesmetamorphosispopulation geneticssimulation analysis

Identifiers

PMID42746656
PMCPMC13577703

What OpenQuestion holds

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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.