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Related Concept Videos

Entropy Changes Accompanying Specific Processes01:21

Entropy Changes Accompanying Specific Processes

Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression results...
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Entropy Change in Reversible Processes

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Entropy02:39

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Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
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The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
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Understanding the evolutionary relationships among microorganisms is fundamental to microbial ecology and taxonomy. Phylogenetic trees are essential tools for inferring these relationships, relying primarily on comparative analyses of molecular sequences such as DNA, RNA, or proteins. In microbial studies, these trees typically depict the evolutionary paths of diverse bacterial and archaeal species by mapping genetic differences accumulated over time.Phylogenetic trees are composed of tips,...
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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...

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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Decomposing phylogenetic entropy into α, β and γ components.

Maud A Mouchet1, David Mouillot

  • 1UMR CNRS-UM2-IFREMER-IRD 5119 Écosystèmes Lagunaires, Université, , Montpellier 2 cc 093, 34 095 Montpellier Cedex 5, France. maud.mouchet@univ-montp2.fr

Biology Letters
|October 22, 2010
PubMed
Summary

This study introduces a new method to measure phylogenetic diversity across different scales (α, β, γ). It ensures accurate biodiversity assessments by considering species abundance and phylogenetic relationships, overcoming limitations of existing indices.

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Area of Science:

  • Ecology
  • Evolutionary Biology
  • Conservation Biology
  • Biogeography

Background:

  • Measuring phylogenetic diversity is crucial for understanding biodiversity patterns and informing conservation efforts.
  • Existing phylogenetic diversity indices often fail to account for species abundance and can violate monotonicity principles, leading to inaccurate interpretations of biodiversity changes.
  • The concept of phylogenetic entropy addresses some limitations but lacks a multi-scale decomposition (α, β, γ).

Purpose of the Study:

  • To develop an additive decomposition framework for estimating alpha (α), beta (β), and gamma (γ) components of phylogenetic entropy.
  • To provide a robust method for partitioning phylogenetic diversity across different spatial and ecological scales.
  • To adapt the framework for partitioning functional diversity across scales.

Main Methods:

  • Proposed an additive decomposition framework for phylogenetic entropy.
  • Utilized simulated phylogenetic trees to test the framework's robustness against variations in tree shape and species richness.
  • Validated the decomposition for independence between components and weak monotonicity.

Main Results:

  • The proposed framework successfully decomposes phylogenetic entropy into α, β, and γ components.
  • The method demonstrates robustness to phylogenetic tree shape and species richness.
  • The decomposition ensures independence between components and adheres to the principle of weak monotonicity.

Conclusions:

  • The developed additive decomposition framework provides a reliable method for quantifying phylogenetic diversity at multiple scales.
  • This approach overcomes limitations of previous indices by incorporating species abundance and ensuring monotonic responses to biodiversity changes.
  • The framework is adaptable for partitioning functional diversity, offering a unified approach to understanding biodiversity across scales.