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The Evidence for Evolution

The Evidence for Evolution

Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.

Convergent Evolution

Convergent Evolution

Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.

Mixtures of Acids

Mixtures of Acids

The pH of a solution containing an acid can be determined using its acid dissociation constant and its initial concentration. If a solution contains two different acids, then its pH can be determined using one of several methods depending upon the relative strength of the acids and their dissociation constants.
A Mixture of a Strong Acid and a Weak Acid
In a mixture of a strong acid and a weak acid, the strong acid dissociates completely and becomes a source of almost all the hydronium ions...

Mixtures of Acids

Mixtures of Acids

The pH of a solution containing an acid can be determined using its acid dissociation constant and initial concentration. If a solution contains two different acids, then its pH can be determined using one of several methods depending on the relative strength of the acids and their dissociation constants.
In a strong and weak acid mixture, the strong acid dissociates completely and becomes a source of almost all the hydronium ions present in the solution. In contrast, the weak acid shows...

Genome Size and the Evolution of New Genes

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Per-Unit Sequence Models

Per-Unit Sequence Models

An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
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Related Experiment Video

Updated: Feb 14, 2026

Bioassays for Monitoring Insecticide Resistance

Bioassays for Monitoring Insecticide Resistance

Published on: December 30, 2010

Insecticide resistance evolution with mixtures and sequences: a model-based explanation.

Andy South¹, Ian M Hastings²

¹Department of Parasitology, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK. southandy@gmail.com.

Malaria Journal

|February 17, 2018

Summary

Insecticide resistance management can be improved using modeling. Mixtures slow resistance evolution more than sequences, especially with effective insecticides, aiding vector control strategies.

Keywords:

Infectious diseases Insecticide resistance Malaria Mosquitoes Population genetics Public health Vector-borne diseases

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Area of Science:

Vector control
Insecticide resistance evolution
Mathematical modeling

Background:

Insecticide resistance poses a significant threat to effective vector control, particularly for mosquitoes and malaria.
Current strategies for managing resistance include insecticide mixtures, sequences, and rotations.
There is a need for accessible modeling to understand resistance evolution under different operational strategies.

Purpose of the Study:

To provide a concise and accessible description of a flexible model for insecticide resistance evolution.
To develop a mechanistic understanding of how resistance evolves in response to various insecticide use strategies.
To inform operational decision-making in insecticide resistance management.

Main Methods:

Development of a flexible model representing two independent genes for resistance to two insecticides.
Simulation of insecticide use in isolation, sequence, and mixture scenarios.
Analysis of resistance evolution under different selection pressures and insecticide effectiveness.

Main Results:

Using an insecticide in a mixture consistently slows resistance evolution compared to using it alone.
Sequences may lead to resistance thresholds being reached later than mixtures when considering resistance to both insecticides.
Higher insecticide effectiveness significantly favors mixtures over sequences by enhancing protection.

Conclusions:

The developed model offers an accessible explanation of insecticide resistance evolution and response to use strategies.
An online user interface is provided for further exploration of resistance dynamics.
These tools can enhance discussions and decisions regarding operational insecticide resistance management.