Related Experiment Video
Updated: Nov 8, 2025
08:56
Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates
Published on: January 13, 2023
2.7K
Measuring change in biological communities: multivariate analysis approaches for temporal datasets with low sample
Hannah L Buckley1, Nicola J Day2, Bradley S Case1
1School of Science, Auckland University of Technology, Auckland, New Zealand.
Peerj
|April 23, 2021
Summary
This study provides a roadmap for analyzing temporal changes in ecological community structures using short time-series data. It offers methods for robustly quantifying biodiversity shifts, aiding environmental change management.
Area of Science:
- Ecology
- Environmental Science
- Data Analysis
Background:
- Understanding temporal changes in biological communities is crucial for ecological research and environmental management.
- Previous studies often used short time-series data, limiting advanced statistical analyses.
- Environmental changes necessitate robust methods to track community structure dynamics.
Purpose of the Study:
- To present a roadmap for analyzing temporal changes in multivariate ecological datasets with short time series.
- To discuss appropriate statistical methods and key considerations for such analyses.
- To illustrate these methods with practical case studies.
Main Methods:
- Development of a roadmap for analyzing temporal ecological data.
- Discussion of statistical methods suitable for short time-series, multivariate ecological datasets.
- Illustration using four case studies analyzed in the R environment.
Main Results:
- A framework for analyzing temporal ecological data is presented.
- Considerations such as sample size, assumptions, and statistical power are highlighted.
- The R data analysis environment is utilized for practical application.
Conclusions:
- The roadmap facilitates effective analysis of temporal changes in ecological communities.
- This approach supports understanding and managing responses to environmental changes.
- The methods are applicable to short-time-series, multivariate ecological datasets.
Keywords:
Beta diversityBiodiversityCommunity variationCompositional changeMultivariate analysisSpecies turnoverTemporal changeTemporal variabilityTime seriesZeta diversityMore Related Videos
Related Concept Videos
00:30What are Populations and Communities?
35.7K
Overview
35.7K
02:04Conservation of Small Populations
16.0K
Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
16.0K
02:07Conservation of Declining Populations
12.0K
Conservation of declining population focuses on ways of detecting, diagnosing, and halting a population decline. The approach uses methods to prevent populations from going extinct.
12.0K
01:20Applications of Molecular Taxonomy
269
Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
269
02:54Evolutionary Relationships through Genome Comparisons
6.5K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
6.5K
01:25Statistical Methods for Analyzing Epidemiological Data
678
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
678