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FIGURE 25 in An overview of the mosquitoes of Saudi Arabia (Diptera: Culicidae), with updated keys to the adult females
FIGURE 25. Aedes albopictus, male (Natural History Museum, London, photo by James Turner, National Museum of Wales).
Do it yourself: 3D-printed miniature CDC trap for adult mosquito (Diptera: Culicidae) surveillance
<p>The central component of mosquito and vector surveillance programs globally is the adult mosquito trap, which is intended to collect host-seeking mosquitoes. The miniature CDC trap is a widely distributed trap style in part due to its relative affordability and compact nature. Despite already being a simple trap, in-house production methods, such as 3D printing, could improve the accessibility of the CDC trap by eliminating some of the supply chain variables. We present here several trials with the Salt Lake City (SLC) trap, a three-dimensional (3D) printed trap design. Functional assessments were made on secondary components and found no statistically significant differences when comparing CO<sub>2</sub> line height (above vs. below fan), battery types (sealed lead acid vs. USB battery pack), and trap body collection shape (funnel body vs. simple/straight body). The SLC trap was compared directly to a commercial equivalent, the ABC trap, with comparative assessment on species diversity and evenness in collections and found to be statistically equivalent on all metrics. Methods also detail an accompanying optional transport system for a pressurized CO<sub>2</sub>/regulator set-up, should a practitioner elect not to use dry ice. Our final design is presented here with the publicly published stereolithography (STL) files and a detailed outline of the transport container system. Alternative models are available for in-house manufacture of mosquito traps, and we contribute these designs in an effort to stimulate further growth in vector surveillance.</p>
Social clues in risky pools: Perceived conspecific rivals modify individual mosquito oviposition decisions in response to larval predation and competition
Open the record for dataset details and reuse information.
MosqVision-3K: A Balanced Multi-Source Dataset of 3,000 Annotated Images for Culex, Anopheles, and Aedes Mosquito Species Classification
<p><strong>Comprehensive Mosquito Species Image Dataset for Machine Learning</strong><br><strong>Description:</strong><br>This dataset is a meticulously curated collection of high-quality images featuring three major mosquito species: <strong>Culex</strong>, <strong>Anopheles</strong>, and <strong>Aedes</strong>. These species are significant vectors for transmitting vector-borne diseases such as malaria, dengue, and Zika. The dataset has been compiled to support research and development in entomology, vector-borne disease control, and image recognition.<br>With <strong>3,000 images in total</strong>, the dataset is structured to ensure a balanced representation of the three species, each having <strong>1,000 images</strong>. Images were sourced from four reputable platforms, including <strong>MosquitoAlert.com</strong>, <strong>Mendeley Data</strong>, <strong>IEEE DataPort</strong>, and the <strong>Dryad Digital Repository</strong>. These sources ensure a comprehensive and diverse representation of mosquito appearances, including variations in morphology, lighting conditions, and orientations.</p> <h2>The dataset is organized into directories for each species, making it easy to integrate into machine learning workflows for tasks like species identification and classification. The collection also includes metadata and annotations to enhance usability.</h2> <p><strong>Key Features:</strong></p> <ul> <li><strong>Species Represented:</strong> <ul> <li><em>Culex</em></li> <li><em>Anopheles</em></li> <li><em>Aedes</em></li> </ul> </li> <li><strong>Total Images:</strong> 3,000 (1,000 images per species)</li> <li><strong>Image Sources:</strong> <ul> <li><strong>MosquitoAlert.com</strong> (1,234 images)</li> <li><strong>Mendeley Data</strong> (876 images)</li> <li><strong>IEEE DataPort</strong> (748 images)</li> <li><strong>Dryad Digital Repository</strong> (600 images)</li> </ul> </li> </ul> <h2>- <strong>Image Annotations:</strong> Metadata and species labels are included for enhanced usability.</h2> <p><strong>Applications:</strong><br>This dataset is ideal for a variety of applications, including:</p> <ul> <li>Training machine learning models for mosquito species identification.</li> <li>Developing computer vision algorithms for pest control and public health.</li> </ul> <h2>- Enhancing vector control strategies to mitigate disease spread.</h2> <p><strong>Data Structure:</strong><br>The dataset is organized as follows:</p> <pre><code>Mosquito_Dataset/ ├── Anopheles/ │ ├── img_001<span>.jpg</span> │ ├── img_002<span>.jpg</span> │ └── ... ├── Aedes/ │ ├── img_001<span>.jpg</span> │ ├── img_002<span>.jpg</span> │ └── ... └── Culex/ ├── img_001<span>.jpg</span> ├── img_002<span>.jpg</span> └── ... </code></pre> <h2> </h2> <h2><strong>Acknowledgments:</strong><br>We acknowledge the following data sources for their contributions:</h2> <blockquote> <ul> <li>MosquitoAlert.com</li> <li>Mendeley Data</li> <li>IEEE DataPort</li> <li> Dryad Digital Repository</li> </ul> </blockquote>
Data for "Cross-modal sensory compensation increases mosquito attraction to humans"
<p>These supplementary files accompany the manuscript by Morita et al. entitled "Cross-modal sensory compensation increases mosquito attraction to humans".</p> <p>This includes all raw data in the paper, code, and supplementary data.</p>
FIGURE 3 in Rediscovering the mosquito fauna (Diptera: Culicidae) of Estonia: an annotated checklist with distribution maps and DNA evidence
FIGURE 3. Maps showing the historic and current collection points of individual mosquito species in Estonia. A, Aedes (Ochlerotatus) dorsalis; B, Aedes (Ochlerotatus) excrucians; C, Aedes (Ochlerotatus) flavescens; D, Aedes (Ochlerotatus) hexodontus; E, Aedes (Ochlerotatus) intrudens; F, Aedes (Ochlerotatus) leucomelas; G, Aedes (Ochlerotatus) nigrinus; H, Aedes (Ochlerotatus) punctor. For details, see Fig. 2.
FIGURE 1 in Rediscovering the mosquito fauna (Diptera: Culicidae) of Estonia: an annotated checklist with distribution maps and DNA evidence
FIGURE 1. Sampling localities in Estonia: 1—Kalana, 2—Vanajõe, 3—Kerema, 4—Viidumäe, 5—Karujärve, 6—Mändjala, 7—Orissaare, 8—Igaküla, 9—Muraste, 10—Üksnurme, 11—Lihula, 12—Tõstamaa, 13—Jõesuu, 14—Punaküla, 15—Nigula NR, 16—Viivre, 17—Lasila, 18—Mäetaguse, 19—Kibuvitsa, 20—Omedu, 21—Kursi, 22—Luua, 23—Laeva, 24—Undi, 25— Kolkja, 26—Maiorg, 27—Külitse, 28—Tartu, 29—Pargi, 30—Hurda, 31—Melliste, 32—Järvselja, 33—Puka, 34—Leoski. Base maps of Europe and Estonia: © 2007–2021 https://d-maps.com (accessed on 11 August 2021).
FIGURE 4 in Rediscovering the mosquito fauna (Diptera: Culicidae) of Estonia: an annotated checklist with distribution maps and DNA evidence
FIGURE 4. Maps showing the historic and current collection points of individual mosquito species in Estonia. A, Aedes (Ochlerotatus) sticticus; B, Aedes (Ochlerotatus) riparius; C, Anopheles (Anopheles) algeriensis; D, Anopheles (Anopheles) claviger; E, Anopheles maculipennis complex; F, Anopheles (Anopheles) plumbeus; G, Coquillettidia (Coquillettidia) richiardii; H, Culex pipiens complex.. For details, see Fig. 2.
FIGURE 5 in Rediscovering the mosquito fauna (Diptera: Culicidae) of Estonia: an annotated checklist with distribution maps and DNA evidence
FIGURE 5. Maps showing the historic and current collection points of individual mosquito species in Estonia. A, Culex (Neoculex) territans; B, Culiseta (Culicella) fumipennis; C, Culiseta (Culicella) morsitans; D, Culiseta (Culicella) ochroptera; E, Culiseta (Culiseta) alaskaensis; F, Culiseta (Culiseta) annulata; G, Culiseta (Culiseta) bergrothi. For details, see Fig. 2, except for data for Cs. bergrothi, which is provided according to Khalin & Aibulatov (2020).
FIGURE 2 in Rediscovering the mosquito fauna (Diptera: Culicidae) of Estonia: an annotated checklist with distribution maps and DNA evidence
FIGURE 2. Maps showing the historic and current collection points of individual mosquito species in Estonia. A, Aedes (Aedes) cinereus; B, Aedes (Aedimorphus) vexans; C, Aedes annulipes group; D, Aedes (Ochlerotatus) caspius; E, Aedes (Ochlerotatus) cataphylla; F, Aedes (Ochlerotatus) communis; G, Aedes (Ochlerotatus) cyprius; H, Aedes (Ochlerotatus) diantaeus. Numbers indicate original data and correspond to on the numbers in Fig. 1. Red diamonds indicate localities collected by Remm (1955). In cases where Remm indicated the species was widely distributed in Estonia, the area is shaded in gray.
Skin microbiome alters attractiveness to Anopheles mosquitoes
<p>16S skin microbiome dataset V3/4 variable region and human attractiveness to mosquitoes</p> <p>MCRO-D-21-00316</p>
Data from: Blood-red colour as a prey-choice cue for mosquito specialist predators
<p>Specialist predators are innately and distinctively proficient at targeting specific prey types. This is enabled by behavioural, perceptual, and cognitive mechanisms that can only be understood using carefully-designed experiments. <i>Evarcha culicivora </i>is<i> </i>an East African jumping spider that feeds on vertebrate blood acquired indirectly by actively targeting blood-carrying female mosquitoes as preferred prey. Here we asked whether these spiders use the colour red to locate this prey. In Objective 1, we used spectrophotometry to document the changing redness of mosquitoes in the 17 hours following blood meals. In Objective 2, we used vision-based choice tests to document how <i>E</i>. <i>culicivora</i>'s preference for blood-carrying mosquitoes changes over time (using an interval comparable to that in Objective 1). We found that <i>E. culicivora</i> exhibits the strongest preference for blood-carrying mosquitoes during the first 6 hours after those mosquitoes had fed on blood and that this time interval corresponded to when mosquitoes exhibit the reddest coloration. Based on this, we then took mosquitoes that had never fed on blood and manipulated their colour using a blend of red food dye to make them appear blood-fed (i.e., by matching their spectral properties to mosquitoes that had fed on blood within the previous 6 hours). We also created grey-dyed mosquitoes that matched the spectral properties of those that had never fed on blood. In Objective 3, we found that <i>E. culicivora</i> did not visually discriminate between our red-dyed mosquitoes and blood-carrying mosquitoes; this indicated that, to <i>E. culicivora</i>, our red-dyed mosquitoes appropriately resembled blood-carrying mosquitoes. Finally, in Objective 4, we showed that <i>E. culicivora</i> consistently preferred red-dyed mosquitoes over grey-dyed mosquitoes, supporting the hypothesis that <i>E. culicivora</i> uses some aspect of red coloration to locate their preferred prey. We discuss how these findings relate to cognitive processes, colour-based communication, and sensory exploitation. </p>
Life-history stage and the population genetics of the tiger mosquito Aedes albopictus at a fine spatial scale
<p>As a widespread vector of disease, the mosquito species <em>Aedes albopictus </em>Skuse<em> </em>(Diptera: Culicidae) is a high priority for both public health and invasive species research and management. Like all mosquitoes, <em>A. albopictus </em>has a complex life history with aquatic egg, larval, and pupal stages and a terrestrial adult stage. This requires targeted management strategies for each life stage, coordinated across time and space. Researchers use population genetics to inform control of <em>A. albopictus</em>. However, these studies do not consider the impact on life stage on population genetic characteristics and subsequent conclusions. Our objective was to examine whether the life stage impacted patterns of <em>A. albopictus </em>genetic diversity and differentiation at a spatial scale relevant to management efforts. We first conducted a literature review of field-caught <em>A. albopictus </em>population genetic papers and identified 74 peer-reviewed publications, none of which compared results between life stages.<em> </em>We them examined population genetic patterns of egg and adult <em>A. albopictus </em>at five sites in Wake County, North Carolina USA using 8,425 single nucleotide polymorphisms. We found that level of genetic diversity and connectivity between sites varied between adults and eggs. This warrants further study and is critical for research aimed at informing local management.</p>
Data from: Wolbachia infection alters the relative abundance of resident bacteria in adult Aedes aegypti mosquitoes, but not larvae
Insect-symbiont interactions are known to play key roles in host functions and fitness. The common insect endosymbiont Wolbachia can reduce the ability of several human pathogens, including arboviruses and the malaria parasite, to replicate in insect hosts. Wolbachia does not naturally infect Aedes aegypti, the primary vector of dengue virus, but transinfected Ae. aegypti have anti-dengue virus properties and are currently being trialled as a dengue biocontrol strategy. Here, we assess the impact of Wolbachia infection of Ae. aegypti on the microbiome of wild mosquito populations (adults and larvae) collected from release sites in Cairns, Australia, by profiling 16S rRNA gene using next generation sequencing. Our data indicate that Wolbachia reduces the relative abundance of a large proportion of bacterial taxa in Ae. aegypti adults, that is in accordance with the known pathogen-blocking effects of Wolbachia on a variety of bacteria and viruses. In adults, several of the most abundant bacterial genera were found to undergo significant shifts in relative abundance. However, the genera showing the greatest changes in relative abundance in Wolbachia-infected adults represented a low proportion of the total microbiome. In addition, there was little effect of Wolbachia infection on the relative abundance of bacterial taxa in larvae, or on species diversity (accounting for species richness and evenness together) detected in adults or larvae. These results offer insight into the effects of Wolbachia on the Ae. aegypti microbiome in a native setting, an important consideration for field releases of Wolbachia into the population.
Assessing the effects of native and alien plant ash on mosquito abundance
<p class="MsoNormal"><span>Plant invasions have been linked to displacement of native vegetation and altering of fire regimes and might influence vector mosquito populations by altering habitats or nutrient inputs. Whereas wildfire effects on terrestrial ecosystems are relatively well-studied,</span> <span>ash depositions into aquatic ecosystems and effects on semi-aquatic taxa such as mosquitoes have remained overlooked</span><span>. Here, we investigated mosquito colonization in water treated with ash from native plants [quinine tree (<em>Rauvolfia caffra</em>), Transvaal milk plum (<em>Englerophytum magalismontanum</em>), apple leaf (<em>Philenoptera violacea</em>)] and invasive alien plants [i.e., lantana (<em>Lantana camara</em>), guava (<em>Psidium guajava</em>), red river gum (<em>Eucalyptus camaldulensis</em>)] in containers at two ash concentrations (i.e., 1 g L<sup>-1</sup>, 2 g L<sup>-1</sup>)<em>.</em> Overall, there was no statistically clear difference in colonization between ash from native and alien species. We recorded colonization by two mosquito genera (<em>Culex </em>spp. and <em>Anopheles</em> spp.), with <em>Culex</em> generally much more abundant than <em>Anopheles</em>.</span><span> Few differences were identified among the plants, with statistically clear effects of ash type and concentration on larval and pupal stages. H</span><span>igh<em> Culex</em> egg and larval abundances were shown in lantana and apple leaf treatments compared to controls, and milkplum versus controls for pupae of both genera. Further research is required to elucidate the influence of nutrient inputs from different ash species on vector mosquito population dynamics.</span></p>
Supplementary material 6 from: Rozo-Lopez P, Mengual X (2015) Mosquito species (Diptera, Culicidae) in three ecosystems from the Colombian Andes: identification through DNA barcoding and adult morphology. ZooKeys 513: 39-64. https://doi.org/10.3897/zookeys.513.9561
NJ tree based on 1,292 sequences of Neotropical mosquitoes: Explanation note: Original Neighbour-Joining tree of the barcoding sequences of mosquito species listed for the Neotropics, based on Tamura-Nei genetic distances (.tre).
Supplementary material 2 from: Rozo-Lopez P, Mengual X (2015) Mosquito species (Diptera, Culicidae) in three ecosystems from the Colombian Andes: identification through DNA barcoding and adult morphology. ZooKeys 513: 39-64. https://doi.org/10.3897/zookeys.513.9561
COI mosquito sequences downloaded from NCBI and BOLD: Explanation note: Sequences from NCBI and BOLD. Sequences downloaded between December 2013 and February 2014 for all identified species with a minimum length of 480 bp of COI barcoding region, no stop codons and possible alignment among the majority of the sequences. Total of 1,159 sequences. In blue: Additional species sequences from other geographic areas for those Neotropical groups without available sequences from the Neotropics.
Supplementary material 8 from: Rozo-Lopez P, Mengual X (2015) Mosquito species (Diptera, Culicidae) in three ecosystems from the Colombian Andes: identification through DNA barcoding and adult morphology. ZooKeys 513: 39-64. https://doi.org/10.3897/zookeys.513.9561
ML tree based on 1,292 sequences of Neotropical mosquitoes: Explanation note: Original Maximum likelihood tree of the barcoding sequences of mosquito species listed for the Neotropics (.tre).
Supplementary material 1 from: Rozo-Lopez P, Mengual X (2015) Mosquito species (Diptera, Culicidae) in three ecosystems from the Colombian Andes: identification through DNA barcoding and adult morphology. ZooKeys 513: 39-64. https://doi.org/10.3897/zookeys.513.9561
Mosquito specimens collected in the present study: Explanation note: Full collection site details, including geo-references and environmental conditions, of the mosquito taxa identified in this study.
Supplementary material 7 from: Rozo-Lopez P, Mengual X (2015) Mosquito species (Diptera, Culicidae) in three ecosystems from the Colombian Andes: identification through DNA barcoding and adult morphology. ZooKeys 513: 39-64. https://doi.org/10.3897/zookeys.513.9561
ML tree based on 1,292 sequences of Neotropical mosquitoes: Explanation note: Original Maximum likelihood tree of the barcoding sequences of mosquito species listed for the Neotropics.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.