High levels of gene flow among song dialect populations of the Puget Sound white‐crowned sparrow

Poesel, Angelika; Fries, Anthony C; Miller, Loren M.; Gibbs, H. Lisle; Soha, Jill A.; Nelson, Douglas A.

doi:10.1111/eth.12632

Cited by 12 publications

(9 citation statements)

References 88 publications

(173 reference statements)

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“…2008] and Puget Sound White‐crowned Sparrow [ Zonotrichia leucophrys pugetensis ] [Poesel et al. 2017]). Other studies show some genetic structuring related to dialect differences (e.g., Mountain White‐crowned Sparrows [ Zonotrichia leucophrys oriantha ] [MacDougall‐Shackleton & MacDougall‐Shackleton 2001]).…”

Section: Importance Of Variation In Vocalizations To Processes Of Conservation Interestmentioning

confidence: 99%

“…A number of studies report substantial genetic mixing between populations despite dialect differences (e.g., Orange-tufted Sunbirds [Cinnyris bouvieri] [Leader et al 2008] and Puget Sound White-crowned Sparrow [Zonotrichia leucophrys pugetensis] [Poesel et al 2017]). Other studies show some genetic structuring related to dialect differences (e.g., Mountain White-crowned Sparrows [Zonotrichia leucophrys oriantha] ).…”

Section: Gene Flowmentioning

confidence: 99%

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The uses and implications of avian vocalizations for conservation planning

Lewis

Williams

Gilman

2020

Conservation Biology

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There is a growing recognition that animal behavior can affect wildlife conservation, but there have been few direct studies of animal behavior in conservation programs. However, a great deal of existing behavioral research can be applied in the context of conservation. Research on avian vocalizations provides an excellent example. The conspicuous nature of the vocal behavior of birds makes it a useful tool for monitoring populations and measuring biodiversity, but the importance of vocalizations in conservation goes beyond monitoring. Geographic song variants with population‐specific signatures, or dialects, can affect territory formation and mate choice. Dialects are influenced by cultural evolution and natural selection and changes can accumulate even during the timescale of conservation interventions, such as translocations, reintroductions, and ex situ breeding. Information from existing research into avian vocalizations can be used to improve conservation planning and increase the success of interventions. Vocalizations can confer a number of benefits for conservation practitioners through monitoring, providing baseline data on populations and individuals. However, the influence of cultural variation on territory formation, mate choice, and gene flow should be taken into account because cultural differences could create obstacles for conservation programs that bring birds from multiple populations together and so reduce the success of interventions.

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Section: Importance Of Variation In Vocalizations To Processes Of Conservation Interestmentioning

confidence: 99%

Section: Gene Flowmentioning

confidence: 99%

The uses and implications of avian vocalizations for conservation planning

Lewis

Williams

Gilman

2020

Conservation Biology

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“…Indeed, according to recent research in biology [29], singing birds have regional accents precisely like human beings. Indeed, the ability to sing and create a complete song that birds possess is inherited in large part from their parents.…”

Section: -The Bird Accent Conceptmentioning

confidence: 99%

A new multi-agent particle swarm algorithm based on birds accents for the 3D indoor deployment problem

et al. 2019

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h i g h l i g h t s• Proving the efficiency of optimization algorithms in solving real-world problems.• A new concept of accent birds introduced to the particle swarm optimization. • A new hybrid scheme that integrates PSO and MAS.• The hybridization improves the performance of the original tested algorithms. • A comparison between simulation and experimental validation is given. a r t i c l e i n f o Keywords: Accent based PSO Multi-agent Many-objective optimization Experimental validation 3D indoor deployment DL-IoT collection networks a b s t r a c tThe 3D indoor deployment of sensor nodes is a complex real world problem, proven to be NP-hard and difficult to resolve using classical methods. In this context, we propose a hybrid approach relying on a novel bird's accent-based many objective particle swarm optimization algorithm (named acMaPSO) to resolve the problem of 3D indoor deployment on the Internet of Things collection networks. The new concept of bird's accent is presented to assess the search ability of particles in their local areas. To conserve the diversity of the population during searching, particles are separated into different accent groups by their regional habitation and are classified into different categories of birds/particles in each cluster according to their common manner of singing. A particle in an accent-group can select other particles as its neighbors from its group or from other groups (which sing differently) if the selected particles have the same expertise in singing or are less experienced compared to this particle. To allow the search escaping from local optima, the most expert particles (parents) ''die'' and are regularly replaced by a novice (newborn) randomly generated ones. Moreover, the hybridization of the proposed acMaPSO algorithm with multi-agent systems is suggested. The new variant (named acMaMaPSO) takes advantage of the distribution and interactivity of particle agents. Experimental, numerical and statistical found results show the effectiveness of the two proposed variants compared to different other recent state-of-the-art of many-objective evolutionary algorithms.✩ This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. * Correspondence to: bureau C107, Batiment C, 1 Place Georges positions and the topology of the network. In this study, we are interested in the deployment of nodes in a three-dimensional space that reflects the real topology of the RoI (region of interest) better than the two-dimensional case. We are particularly interested in improving the initial 3D indoor deployment by adding new nodes while optimizing a set of objectives such as coverage, connectivity, localization, quality of links and network utilization. These objectives will be detailed in the modeling section. To resolve the deployment problem in WSN, the topology of the network can be modeled as an identification problem in a graph as addressed in [1] and [2]. In this static case, the deployment algorithm is run off-...

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“…Recent research in biology [12] affirmed that songbirds have regional dialects such as humans. In fact, birds inherit from their parents the ability to sing and create a complete song.…”

Section: The Proposed Acmapso Algorithm: Including Thementioning

confidence: 99%

The 3D indoor deployment in DL-IoT with experimental validation using a particle swarm algorithm based on the dialects of songs

Mnasri

Nasri

Val

2018

2018 14th International Wireless Communications &Amp; Mobile Computing Conference (IWCMC)

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The use of real prototyping systems allows implementing real-world deployments which permit evaluating new protocols, algorithms and network solutions. This study investigates the problem of 3D indoor redeployment of connected objects in IoT collection networks. The objective is to choose the right positions in which connected objects are added to an initial configuration, while optimizing a set of objectives. To solve this problem, a novel bird's dialect-based particle swarm optimization algorithm (named acMaPSO) is introduced. The new concept of bird's dialect is based on a set of birds which are separated into different dialect groups by their regional habitation and are classified into groups according to their common manner of singing. The obtained numerical results and the real experiments on our testbed prove the effectiveness of the two proposed variants compared with the standard PSO algorithm and a recent state of art of many-objective evolutionary algorithms: the NSGA-III.

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High levels of gene flow among song dialect populations of the Puget Sound white‐crowned sparrow

Cited by 12 publications

References 88 publications

The uses and implications of avian vocalizations for conservation planning

The uses and implications of avian vocalizations for conservation planning

A new multi-agent particle swarm algorithm based on birds accents for the 3D indoor deployment problem

The 3D indoor deployment in DL-IoT with experimental validation using a particle swarm algorithm based on the dialects of songs

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