AI Article Synopsis

  • * A new eco-evolutionary simulation model leverages metabarcoding data to analyze community assembly dynamics, predicting species abundance, genetic variation, and other community characteristics across various environmental conditions.
  • * The model was tested on soil microarthropod data from Cyprus, revealing that community structures in different habitats are influenced by either neutral processes or abiotic filters, with the findings available through the ibiogen R package.

Article Abstract

Understanding the relative contributions of ecological and evolutionary processes to the structuring of ecological communities is needed to improve our ability to predict how communities may respond to future changes in an increasingly human-modified world. Metabarcoding methods make it possible to gather population genetic data for all species within a community, unlocking a new axis of data to potentially unveil the origins and maintenance of biodiversity at local scales. Here, we present a new eco-evolutionary simulation model for investigating community assembly dynamics using metabarcoding data. The model makes joint predictions of species abundance, genetic variation, trait distributions and phylogenetic relationships under a wide range of parameter settings (e.g. high speciation/low dispersal or vice versa) and across a range of community states, from pristine and unmodified to heavily disturbed. We first demonstrate that parameters governing metacommunity and local community processes leave detectable signatures in simulated biodiversity data axes. Next, using a simulation-based machine learning approach we show that neutral and non-neutral models are distinguishable and that reasonable estimates of several model parameters within the local community can be obtained using only community-scale genetic data, while phylogenetic information is required to estimate those describing metacommunity dynamics. Finally, we apply the model to soil microarthropod metabarcoding data from the Troodos mountains of Cyprus, where we find that communities in widespread forest habitats are structured by neutral processes, while high-elevation and isolated habitats act as an abiotic filter generating non-neutral community structure. We implement our model within the ibiogen R package, a package dedicated to the investigation of island, and more generally community-scale, biodiversity using community-scale genetic data.

Download full-text PDF

Source
http://dx.doi.org/10.1111/mec.16958DOI Listing

Publication Analysis

Top Keywords

genetic data
12
ecological evolutionary
8
metabarcoding data
8
local community
8
community-scale genetic
8
community
7
data
7
genetic
5
model
5
inferring ecological
4

Similar Publications

Background: Predicting response to targeted cancer therapies increasingly relies on both simple and complex genetic biomarkers. Comprehensive genomic profiling using high-throughput assays must be evaluated for reproducibility and accuracy compared with existing methods.

Methods: This study is a multicenter evaluation of the Oncomine™ Comprehensive Assay Plus (OCA Plus) Pan-Cancer Research Panel for comprehensive genomic profiling of solid tumors.

View Article and Find Full Text PDF

Background: Continuous veno-venous hemodiafiltration (CVVHDF) is used in critically ill patients, but its impact on O₂ and CO₂ removal, as well as the accuracy of resting energy expenditure (REE) measurement using indirect calorimetry (IC) remains unclear. This study aims to evaluate the effects of CVVHDF on O₂ and CO₂ removal and the accuracy of REE measurement using IC in patients undergoing continuous renal replacement therapy.

Design: Prospective, observational, single-center study.

View Article and Find Full Text PDF

Long-term epidemiological trends in (primary) pediatric central nervous system tumors: a 25-year cohort analysis in Western Mexico.

Childs Nerv Syst

January 2025

Ph.D. Human Genetics Program, Molecular Biology and Genomics Department, Human Genetics Institute "Dr. Enrique Corona-Rivera", University Center of Health Sciences, University of Guadalajara, Guadalajara, Mexico.

Background: Central nervous system tumors (CNSTs) represent a significant oncological challenge in pediatric populations, particularly in developing regions where access to diagnostic and therapeutic resources is limited.

Methods: This research investigates the epidemiology, histological classifications, and survival outcomes of CNST in a cohort of pediatric patients aged 0 to 19 years within a 25-year retrospective study at the Civil Hospital of Guadalajara, Mexico, from 1999 to 2024.

Results: Data was analyzed from 273 patients who met inclusion criteria, revealing a higher incidence in males (51.

View Article and Find Full Text PDF

Unraveling the potential mechanism and prognostic value of pentose phosphate pathway in hepatocellular carcinoma: a comprehensive analysis integrating bulk transcriptomics and single-cell sequencing data.

Funct Integr Genomics

January 2025

Institute of Infectious Diseases, Guangdong Province, Guangzhou Eighth People's Hospital, Guangzhou Medical University, 8 Huaying Road, Baiyun District, Guangzhou, 510440, China.

Hepatocellular carcinoma (HCC) remains a malignant and life-threatening tumor with an extremely poor prognosis, posing a significant global health challenge. Despite the continuous emergence of novel therapeutic agents, patients exhibit substantial heterogeneity in their responses to anti-tumor drugs and overall prognosis. The pentose phosphate pathway (PPP) is highly activated in various tumor cells and plays a pivotal role in tumor metabolic reprogramming.

View Article and Find Full Text PDF

Phenomic selection based on parental spectra can be used to predict GCA and SCA in a sparse factorial design. Prediction approaches such as genomic selection can be game changers in hybrid breeding. They allow predicting the genetic values of hybrids without the need for their physical production.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!