ArticlePeerJ2021
Measuring change in biological communities: multivariate analysis approaches for temporal datasets with low sample size.
Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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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Who cites it
9 citing papers in PubMed.
- Spatial Complexity and Rare-Taxon Turnover Structures Benthic Coral Reef eDNA Communities.Molecular ecology · 2026Article
- Characterization of the Oral Microbiome and Anticipated Functional Profiles of Companion Animals in Private and Cohabiting Environments: A Pilot Study.Animals : an open access journal from MDPI · 2026Article
- Projected compositional reorganization of Southern plant assemblages in South Korea under climate scenarios using species distribution models.Scientific reports · 2026Article
- Fungi without borders: cross-ecosystem decomposition of riparian leaf litter.ISME communications · 2026Article
- Temporal Dynamics and Disturbance Responses in Coral-Dwelling Decapods Provide a Novel Perspective on Their Ecological Role in Coral Reef Systems.Ecology and evolution · 2025Article
- Introduced substrates trigger colonization by reef-associated fish in a degraded coastal system.PloS one · 2025Article
- The response of soil microbial community to application of organic amendment to saline land.Frontiers in microbiology · 2024Article
- Beyond Basic Diversity Estimates-Analytical Tools for Mechanistic Interpretations of Amplicon Sequencing Data.Microorganisms · 2022Review
- Changes in the analysis of temporal community dynamics data: a 29-year literature review.PeerJ · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Effective and robust ways to describe, quantify, analyse, and test for change in the structure of biological communities over time are essential if ecological research is to contribute substantively towards understanding and managing responses to ongoing environmental changes. Structural changes reflect population dynamics, changes in biomass and relative abundances of taxa, and colonisation and extinction events observed in samples collected through time. Most previous studies of temporal changes in the multivariate datasets that characterise biological communities are based on short time series that are not amenable to data-hungry methods such as multivariate generalised linear models. Here, we present a roadmap for the analysis of temporal change in short-time-series, multivariate, ecological datasets. We discuss appropriate methods and important considerations for using them such as sample size, assumptions, and statistical power. We illustrate these methods with four case-studies analysed using the R data analysis environment.
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Registered trials
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.