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38 results for “insect monitoring”
Figure 2 in Future of DNA-based insect monitoring
Figure 2. The four crucial areas where concerted actions are required are (i) DNA reference database generation to fill the dark taxa barcode gaps, (ii) a collective framework for method standardisation and the identification of gold-standard tools and indices for terrestrial monitoring, (iii) scaling up monitoring efforts by lowering the barrier to participation through citizen science engagement and technological developments, and (iv) integration of molecular tools with non-genetic monitoring technologies to scale up insect monitoring and retrieve biomass and sex information simultaneously (middle panel). Abbreviation: LIDAR, laser imaging, detection, and ranging.
Figure I in Future of DNA-based insect monitoring
Figure I. Standing on the shoulders of giants – three significant pioneering research developments have paved the way for DNA-based insect monitoring: the discovery of DNA barcoding for species identification, bulk insect metabarcoding for large-scale and rapid species identification, and overcoming PCR biases with PCR-free shotgun metagenomics. Abbreviation: mtDNA, mitochondrial DNA.
Data from: Monitoring insect pollinators and flower visitation: the effectiveness and feasibility of different survey methods
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Data from: Designing monitoring protocols to measure population trends of threatened insects: a case study of the cryptic, flightless grasshopper Brachaspis robustus
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Data from: Towards a standardized quantitative and qualitative insect monitoring scheme
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Camera traps for monitoring insects - supporting information
<p>Insect and pollinator populations are vitally important to the health of ecosystems, food production, and economic stability, but are declining worldwide. New, cheap, and simple monitoring methods are necessary to inform management actions and should be available to researchers around the world.</p> <p>Here we evaluate the efficacy of commercially available, close-focus automated camera traps to monitor insect-plant interactions. We compared two video settings—scheduled and motion-activated—to a traditional human observation method.</p> <p>Our results show that camera traps with scheduled video settings detected more insects overall than humans, but relative performance varied by insect order. Scheduled cameras significantly outperformed motion-activated cameras, detecting more insects of all orders and size classes.</p> <p>We conclude that scheduled camera traps are an effective and relatively inexpensive tool for monitoring interactions between plants and insects of all size classes, and their ease of accessibility and set-up allows for the potential of widespread use. The digital format of video also offers the benefits of recording, sharing, and verifying observations.</p>
Supplementary material 1 from: Landvik M, Miraldo A, Niemelä P, Valainis U, Cibuļskis R, Roslin T (2017) Evidence for geographic substructuring of mtDNA variation in the East European Hermit beetle (Osmoderma barnabita). In: Campanaro A, Hardersen S, Sabbatini Peverieri G, Carpaneto GM (Eds) Monitoring of saproxylic beetles and other insects protected in the European Union. Nature Conservation 19: 171-189. https://doi.org/10.3897/natureconservation.19.12877
Details of the Osmoderma barnabita specimens included in the data set : Data type: specimens data
Supplementary material 2 from: Romiti F, Redolfi De Zan L, Rossi de Gasperis S, Tini M, Scaccini D, Anaclerio M, Carpaneto G (2017) Latitudinal cline in weapon allometry and phenology of the European stag beetle. In: Campanaro A, Hardersen S, Sabbatini Peverieri G, Carpaneto GM (Eds) Monitoring of saproxylic beetles and other insects protected in the European Union. Nature Conservation 19: 57-80. https://doi.org/10.3897/natureconservation.19.12681
Monthly total precipitations and temperatures : Data type: еnvironment data
Supplementary material 1 from: Della Rocca F, Bogliani G, Milanesi P (2017) Patterns of distribution and landscape connectivity of the stag beetle in a human-dominated landscape. In: Campanaro A, Hardersen S, Sabbatini Peverieri G, Carpaneto GM (Eds) Monitoring of saproxylic beetles and other insects protected in the European Union. Nature Conservation 19: 19-37. https://doi.org/10.3897/natureconservation.19.12457
Additional information :
Supplementary material 1 from: Thomaes A, Verschelde P, Mader D, Sprecher-Uebersax E, Fremlin M, Onkelinx T, Méndez M (2017) Can we successfully monitor a population density decline of elusive invertebrates? A statistical power analysis on Lucanus cervus. In: Campanaro A, Hardersen S, Sabbatini Peverieri G, Carpaneto GМ (Eds) Monitoring of saproxylic beetles and other insects protected in the European Union. Nature Conservation 19: 1-18. https://doi.org/10.3897/natureconservation.19.11761
Figures of statistical support : Data type: statistical data
Supplementary material 2 from: Kadej M, Zając K, Smolis A, Tarnawski D, Tyszecka K, Malkiewicz A, Pietraszko M, Warchałowski M, Gil R (2017) The great capricorn beetle Cerambyx cerdo L. in south-western Poland – the current state and perspectives of conservation in one of the recent distribution centres in Central Europe. In: Campanaro A, Hardersen S, Sabbatini Peverieri G, Carpaneto GM (Eds) Monitoring of saproxylic beetles and other insects protected in the European Union. Nature Conservation 19: 111-134. https://doi.org/10.3897/natureconservation.19.11838
Distribution data of Cerambyx cerdo : Data type: occurence
Camera transects as a method to monitor high temporal and spatial ephemerality of flying nocturnal insects
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Camera traps for monitoring insects - supporting information
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Figure 1. Insect species account for 70 in The Importance of Insect Monitoring to Conservation Actions in Hawaii
Figure 1. Insect species account for 70% of Hawaii's total number of endemic animal species.
Figura 1 in Device for monitoring population density of insects from acoustic signals emitted
Figura 1 – Guido instalado em Muzambinho/MG
Simultaneous Detection of Gene Expression of insects, nematode and bacterial specific genes to monitor the infection.
GEO Series GSE197737. Bombyx mori; Heterorhabditis bacteriophora; Spodoptera frugiperda; Galleria mellonella; Drosophila melanogaster; Xenorhabdus; Photorhabdus. 10 samples. Type: Expression profiling by array.
Figure 1 in Future of DNA-based insect monitoring
Figure 1. Sources of insect DNA and common applications. Abbreviation: eDNA, environmental DNA.
Revolutionising Insect Biodiversity Monitoring with Cutting-Edge Sensors, Deep Learning, and Computer Vision
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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.