AI Article Synopsis

  • The study examined the swarming behavior of two forms of malaria mosquitoes, Anopheles gambiae and An. coluzzii, in rural Burkina Faso from 2006 to 2009.
  • Most swarms were observed above visual markers near houses, with a significant number of pairs collected for analysis.
  • While segregated swarms occurred at both sites, some visual markers were shared, indicating interaction, although no mixed inseminations were observed, suggesting mechanisms individuals use to avoid hybridization.

Article Abstract

The swarming behaviour of natural populations of Anopheles gambiae and An. coluzzii (formerly known as An. gambiae S and M forms, respectively) were investigated through longitudinal surveys conducted between July 2006 and October 2009 in two rural areas of south-western Burkina Faso where these forms are sympatric. In both sites, the majority of swarms were recorded above visual markers localised among houses. In Soumousso, a wooded area of savannah, 108 pairs caught in copula from 205 swarms were sampled; in VK7, a rice growing area, 491 couples from 250 swarms were sampled. If segregated swarms were the norm in both sites, many visual markers were shared by the two forms of An. gambiae. Furthermore, mixed swarms were collected annually in frequencies varying from one site to another, though no mixed inseminations were recorded, corroborating the low hybrid rate previously reported in the field. The occurrence of inter-specific mate-recognition mechanisms, which allow individuals to avoid hybridisation, is discussed.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.actatropica.2013.12.011DOI Listing

Publication Analysis

Top Keywords

swarming behaviour
8
behaviour natural
8
natural populations
8
populations anopheles
8
anopheles gambiae
8
gambiae coluzzii
8
rural areas
8
burkina faso
8
visual markers
8
swarms sampled
8

Similar Publications

Enhanced technologies of the future are gradually improving the digital landscape. Internet of Things (IoT) technology is an advanced technique that is quickly increasing owing to the development of a network of organized online devices. In today's digital era, the IoT is considered one of the most robust technologies.

View Article and Find Full Text PDF

With increasing worldwide attention on environmental sustainability, microgrids that harness renewable sources have become more prominent. The changing characteristics of renewable energy sources and energy demand's unpredictable patterns might cause disruptions in the sustainable working of microgrids. Moreover, EVs (electric vehicles), being dynamic loads, might significantly affect the security administration of the microgrid.

View Article and Find Full Text PDF

Improved aquila optimizer for swarm-based solutions to complex engineering problems.

Sci Rep

December 2024

Department of Computer Science, College of Computer and Information Sciences, King Saud University, 11543, Riyadh, Saudi Arabia.

The traditional optimization approaches suffer from certain problems like getting stuck in local optima, low speed, susceptibility to local optima, and searching unknown search spaces, thus requiring reliance on single-based solutions. Herein, an Improved Aquila Optimizer (IAO) is proposed, which is a unique meta-heuristic optimization method motivated by the hunting behavior of Aquila. An improved version of Aquila optimizer seeks to increase effectiveness and productivity.

View Article and Find Full Text PDF

The COVID-19 pandemic highlighted the urgent need for effective surface disinfection solutions, which has led to the use of mobile robots equipped with ultraviolet (UVC) lamps as a promising technology. This study aims to optimize the navigation of differential mobile robots equipped with UVC lamps to ensure maximum efficiency in disinfecting complex environments. Bio-inspired metaheuristic algorithms such as the gazelle optimization algorithm, whale optimization algorithm, bat optimization algorithm, and particle swarm optimization are applied.

View Article and Find Full Text PDF

Nature-Inspired Approach: A Novel Rat Optimization Algorithm for Global Optimization.

Biomimetics (Basel)

December 2024

School of Electrical and Photoelectronic Engineering, West Anhui University, Lu'an 237012, China.

This work presents a rat optimization algorithm (ROA), which simulates the social behavior of rats and is a new nature-inspired optimization technique. The ROA consists of three operators that simulate rats searching for prey, chasing and fighting prey, and jumping and hunting prey to deal with optimization issues. The Levy flight strategy is introduced into the ROA to keep the algorithm from running into issues with slow convergence and local optimums.

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!