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72 results for “Biodiversity monitoring”
Estimating the carbon footprint of citizen science biodiversity monitoring
<p>Datasets used in the production of the paper Gillings, S. & Harris, S.J. 2022. Estimating the carbon footprint of citizen science biodiversity monitoring. People & Nature.</p> <p>The dataset comprises a) the estimated round-trip distances from approximate locations of observers to survey locations for the UK Breeding Bird Survey and b) questionnaire responses concerning mode of travel used to access survey locations. Data have been anonymised and locations have been coarsened to preserve anonymity.</p> <p>We would also greatly appreciate if you could fill out <a href="https://forms.gle/DCc58VXpdmqnTmTk8" target="_blank" rel="noopener">this very short form</a> to tell us how you intend to use these data. Thanks in advance!</p> <p> </p> <p> </p>
Automated monitoring of biodiversity in the tropics: A pilot study at Barro Colorado Island
<p>Automated monitoring of biodiversity using camera systems and acoustic devises is becoming increasingly common practise. The development of camera traps for insects, however, is relatively new, and has not been tested in tropical environments. To understand both the challenges and opportunities for automated monitoring in the tropics we deployed three newly developed cameras systems for monitoring insects, with a focus on night-flying insects. In addition we deployed audible and ultrasound recording equipment. The locations of each device was changed over the 5 day pilot study, and the configuration of each system was changed to allow an assessment of the relative importance of position, light, etc. The study was undertaken on Barro Colorado Island, Panama, in January 2023.</p> <p>Data are aggregated into <em>.zip</em> files, and details of their contents, and metadata are given in <em>read_me.txt</em> and <em>metadata.csv</em>.</p>
The Effect of Soundscape Composition on Bird Vocalization Classification in a Citizen Science Biodiversity Monitoring Project
<p>This archive includes sound clips (.wav files) and associated mel-scale spectrograms of bird vocalizations for 54 species in Sonoma County, California, USA. These data were used for training and validating convolutional neural network (CNN) models for bird species detection. We also include xeno-canto training and validation mel spectrograms used to pretrain CNNs. Details on these data are explained in the paper by Clark et al. (2023) titled "The effect of soundscape composition on bird vocalization classification in a citizen science biodiversity monitoring project". These data are available for use without restrictions, with no warranty on data quality or utility for a given application. We request that any work that does use these data cite the Clark et al. (2023) paper.<br> <br> Clark, M.L., Salas, L., Baligar, S., Quinn, C., Snyder, R.L., Leland, D., Schackwitz, W., Goetz, S.J., Newsam, S. (2023). The effect of soundscape composition on bird vocalization classification in a citizen science biodiversity monitoring project. <em>Ecological Informatics</em>. <a href="https://doi.org/10.1016/j.ecoinf.2023.102065">https://doi.org/10.1016/j.ecoinf.2023.102065</a></p> <p>Associated code for training CNN models, performing inference, and applying post-classification corrections can be found in the GitHub archive <a href="https://github.com/pointblue/Soundscapes2Landscapes/tree/master/CNN_Bird_Species">https://github.com/pointblue/Soundscapes2Landscapes/tree/master/CNN_Bird_Species</a></p> <p>Raw sound data from the Soundscapes to Landscapes project are available upon request: Dr. Matthew Clark, matthew.clark@sonoma.edu</p> <p>These data were collected as part of the Soundscapes to Landscapes project (<a href="https://soundscapes2landscapes.org/">soundscapes2landscapes.org</a>), funded by NASA’s Citizen Science for Earth Systems Program (CSESP) 16-CSESP 2016-0009 under cooperative agreement 80NSSC18M0107.<br> <br> ----------------------------<br> This depository includes the following archives:</p> <ul> <li> <p>mel_specs.zip: contains 2-sec mel spectrograms split into training (“tr”), validation (“val”), testing (“test”) data for each target bird species (n = 54) used to fine-tune the CNNs. Select spectrogram files are appended with “aug” if they are augmented versions for the training data.</p> </li> <li> <p>wav.zip: contains the associated wav-format sound recordings used to generate the training, validation, testing mel spectrograms found in mel_specs.zip.</p> </li> <li> <p>Xeno-canto_pretrain.tar: contains 2-sec mel spectrograms split into training and validation data for 40 bird species used for CNN pre-training that were generated using a warbleR segmentation methodology described in the paper. The sound files used to generate these mel spectrograms came from the Kaggle competition, <a href="https://www.kaggle.com/datasets/imoore/xenocanto-bird-recordings-dataset">https://www.kaggle.com/datasets/imoore/xenocanto-bird-recordings-dataset</a><br> Mel spectrogram naming reflects the XC number used for cataloging on Xeno-canto in the format XC123456_2.png. The six numbers following the XC characters can be used to search for unique recordings on Xeno-canto (<a href="https://xeno-canto.org/">https://xeno-canto.org/</a>) using the search query “nr:123456” in the search tool or queried using the Xeno-canto API (<a href="https://xeno-canto.org/explore/api">https://xeno-canto.org/explore/api</a>). Unique recording names can be extracted from the mel spectrogram filenames.</p> </li> <li> <p>soundscape_test_wavs.zip: the wav-format sound recordings used to perform soundscape testing.</p> </li> </ul>
Data from: DNA metabarcoding for biodiversity monitoring in a national park: screening for invasive and pest species
<ol> <li><span>DNA metabarcoding was utilized for a large-scale, multi-year assessment of biodiversity in Malaise trap collections from the Bavarian Forest National Park (Germany, Bavaria). </span></li> <li><span>Principal Component Analysis of read count-based biodiversities revealed clustering in concordance with whether collection sites were located inside or outside of the National Park.</span></li> <li><span>Jaccard distance matrices of the presences of BINs at collection sites in the two survey years (2016 and 2018) were significantly correlated.</span></li> <li><span>Overall similar patterns in the presence of total arthropod BINs, as well as BINs belonging to four major arthropod orders across the study area, were observed in both survey years, and are also comparable with results of a previous study based on DNA barcoding of Sanger-sequenced specimens.</span></li> <li><span>A custom reference sequence library was assembled from publicly available data to screen for pest or invasive arthropods among the specimens or from the preservative ethanol.</span></li> <li> <span>A single 98.6% match to the invasive bark beetle </span><span>Ips duplicatus</span><span> was detected in an ethanol sample. This species has not previously been detected in the National Park.</span> </li> </ol>
The FAIR-Device - a non-lethal and generalist semi-automatic Malaise trap for insect biodiversity monitoring: Proof of concept - Supplementary Material
<h3>Abstract</h3> <p>Field monitoring plays a crucial role in understanding insect dynamics within ecosystems. It facilitates pest distribution assessment, control measure evaluation, and prediction of pest outbreaks. Additionally, it provides important information on bioindicators with which the state of biodiversity and ecological integrity in specific habitats and ecosystems can be accurately assessed. However, traditional monitoring systems can present various difficulties, leading to a limited temporal and spatial resolution of the obtained information. Despite recent advancements in automatic insect monitoring traps, also called e-traps, most of these systems focus exclusively on studying agricultural pests, rendering them unsuitable for monitoring diverse insect populations. To address this issue, we introduce the Field Automatic Insect Recognition (FAIR)-Device, a novel non-lethal field tool that relies on semi-automatic image capture and species identification using artificial intelligence via the iNaturalist platform. Our objective was to develop an automatic, cost-effective, and non-specific monitoring solution capable of providing high-resolution data for assessing insect diversity. During a 26-day proof-of-concept evaluation, the FAIR-Device recorded 24.8 GB of video, identifying 431 individuals from 9 orders, 50 families, and 69 genera. While improvements are possible, our device demonstrated potential as a cost-effective, non-lethal tool for monitoring insect biodiversity. Looking ahead, we envision new monitoring systems such as e-traps as valuable tools for real-time insect monitoring, offering unprecedented insights for ecological research and agricultural practices.</p> <h3>Description of the data and file structure</h3> <p>This repository complements the publication <a href="https://www.biorxiv.org/content/10.1101/2024.03.22.586299v2" target="_blank" rel="noopener">"The FAIR-Device - a non-lethal and generalist semi-automatic Malaise trap for insect biodiversity monitoring: Proof of concept".</a> It contains the result data from the proof of concept field test of V1.0 of the FAIR-Device, conducted between July and August 2021 at the Thünen Institute of Agricultural Technology in Braunschweig. The repository comprises three compressed files (.zip):</p> <ul> <li><strong>FAIR-D_captures.zip</strong>: <ul> <li>Video captures from the field tests organized by recording day.</li> <li>Filenames indicating recording time (hh-mm-ss).</li> </ul> </li> </ul> <ul> <li><strong>FAIR-D_Tables&Code.zip</strong>: <ul> <li>Processed results from the obtained image captures, organized into: <ul> <li><strong>Monitoring2021_TotalPeriod.xlsx: </strong>Result table with taxonomic classifications, data analysis, and charts.</li> <li><strong>iNat_observations.xlsx: </strong>iNaturalist reviews analysis table.</li> <li><strong>R: </strong>code for generating article graphics.</li> </ul> </li> </ul> </li> </ul> <ul> <li><strong>FAIR-D_V1.0_3D_Models.zip</strong>: <ul> <li>Complete 3D design of the FAIR-D V1.0 in .stl format, organized into: <ul> <li><strong>3D_print_parts</strong>: 3D-printable parts with spatial coordinates for correct positioning in CAD software.</li> <li><strong>other_3Dparts</strong>: Non-printable parts, also in .stl format with spatial coordinates.</li> </ul> </li> </ul> </li> </ul> <p> </p> <p>NOTE: For visualizing the videos, we recommend <strong>VLC media player</strong> - <a href="https://www.videolan.org/vlc/">https://www.videolan.org/vlc/</a> </p>
Biofouling sponges as natural eDNA samplers for marine vertebrate biodiversity monitoring
<p>These are the raw sequencing data and associated analysis codes for the study of "biofouling sponges as natural eDNA samplers for marine <span>vertebrate </span>biodiversity monitoring".</p>
Adjusting for bias in biodiversity monitoring data
<p>Supporting information to Boyd et al. (2023, <i>Ecology</i>, forthcoming). Includes code to conduct bias adjustments and data supporting the article. </p>
Data from: Optimizing passive acoustic monitoring (PAM) for Biodiversity Studies: using species-area relationship (SAR) to predict species richness
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Unlocking natural history collections to improve eDNA reference databases and biodiversity monitoring
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Data from: Testing multiple substrates for terrestrial biodiversity monitoring using environmental DNA (eDNA) metabarcoding
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Data from: DNA metabarcoding for biodiversity monitoring in a national park: screening for invasive and pest species
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Effects of soil preservation for biodiversity monitoring using environmental DNA
Environmental DNA metabarcoding is becoming a key tool for biodiversity monitoring over large geographical or taxonomic scales and for elusive taxa like soil organisms. Increasing sample sizes and interest in remote or extreme areas often require the preservation of soil samples and thus deviations from optimal standardized protocols. However, we still ignore the impact of different methods of soil sample preservation on the results of metabarcoding studies and there is no guidelines for best practices so far. Here, we assessed the impact of four methods of soil sample preservation commonly used in metabarcoding studies (preservation at room temperature for 6h, preservation at 4°C for three days, desiccation immediately after sampling and preservation for 21 days, and desiccation after 6h at room temperature and preservation for 21 days). For each preservation method, we benchmarked resulting estimates of taxon diversity and community composition of three different taxonomic groups (bacteria, fungi and eukaryotes) in three different habitats (forest, river bank and grassland) against results obtained under optimal conditions (i.e. extraction of eDNA right after sampling). Overall, the different preservation methods only marginally impaired results and only under certain conditions. When rare taxa were considered, we detected small but significant changes in MOTU richness of bacteria, fungi and eukaryotes across treatments, while the exclusion of rare taxa led to robust results across preservation methods. The differences in community structure among habitats were evident for all treatments, and the communities retrieved using the different preservation conditions were extremely similar. We propose guidelines on the selection of the optimal soil sample preservation conditions for metabarcoding studies, depending on the practical constraints, costs and ultimate research goals.
Data from: Using terrestrial haematophagous leeches to enhance tropical biodiversity monitoring programmes in Bangladesh
1. Measuring mammal biodiversity in tropical rainforests is challenging, and methods which reduce effort while maximizing success are crucial for long-term monitoring programmes. Commonly used methods to assess mammal biodiversity may require substantial sampling effort to be effective. Genetic methods are a new and important sampling tool on the horizon, but obtaining sufficient DNA samples can be a challenge. 2. We evaluated the efficacy of using parasitic leeches Haemadipsa spp., as compared to camera trapping, to sample biodiversity. We collected 200 leeches from four forest patches in northeast Bangladesh, and identified recent vertebrate hosts using Sanger sequencing of the 16S rRNA gene extracted from each individual leech's blood meals. We then compared this data to species data from camera trapping conducted in the same forest patches. 3. Overall, 41.9% of sequenced leeches contained amplifiable non-human mammal DNA. Four days of collecting leeches led to the identification of 12 species, compared to 26 species identified in 1334 camera trap nights. 4. Synthesis and applications. After assessing the cost, effort, and power of each technique, there are pros and cons to both camera trapping and leech blood meal analysis. Camera trapping and leech collection appear to be complementary approaches. When used together, they may provide a more complete monitoring tool for mammal biodiversity in tropical rainforests. Managers should consider adding leech collection to their biodiversity monitoring toolkit, as improved information will allow managers to create more effective conservation programmes. R scripts are available upon request.
Data from: environmental DNA reveals temporal variation in mesophotic reefs of the Humboldt upwelling ecosystems of central Chile: towards a baseline for biodiversity monitoring of unexplored marine habitats
<p>Temperate mesophotic reef ecosystems (TMREs) are among the least known marine habitats. Information on their diversity and ecology is geographically and temporally scarce, especially in highly productive large upwelling ecosystems. Lack of information remains an obstacle to understanding the importance of TMREs as habitats, biodiversity reservoirs and their connections with better-studied shallow reefs. Here, we use environmental DNA (eDNA) from water samples to characterize the community composition of TMREs on the central Chilean coast generating the first baseline for monitoring the biodiversity of these habitats. We analyzed samples from two depths (30 and 60m) over four seasons (spring, summer, autumn, and winter) and at two locations approximately 16 km apart. We used a panel of three metabarcodes, two that target all eukaryotes (18S rRNA and mitochondrial COI) and one specifically targeting fishes (16S rRNA). All panels combined encompassed eDNA assigned to 42 phyla, 90 classes, 237 orders, and 402 families. The highest family richness was found for the phyla Arthropoda, Bacillariophyta and Chordata. Overall, family richness was similar between depths but decreased during summer, a pattern consistent at both locations. Our results indicate that the structure (composition) of the mesophotic communities varied predominantly with seasons. We analyzed further the better-resolved fish assemblage and compared eDNA with other visual methods at the same locations and depths. We recovered eDNA from nineteen genera of fish, six of these have also been observed on towed underwater videos, while thirteen were unique to eDNA. We discuss the potential drivers of seasonal differences in community composition and richness. Our results suggest that eDNA can provide valuable insights for monitoring TMRE communities but highlight the necessity of completing reference DNA databases available for this region.</p>
Using eDNA for monitoring fish and invertebrate biodiversity in freshwater ecosystems
<p>Global biodiversity is facing an extinction crisis leading to increasing pressure on industries to monitor their potential environmental impact. Relatedly, there is demand for more efficient biodiversity monitoring methods, resulting in growing interest in the use of environmental DNA (eDNA). Many questions, however, regarding the reliability of this relatively novel method remain, particularly for non-specialist end-users of the technology.</p> <p>Here, the use of commercially available (in the UK) eDNA assays for monitoring freshwater fish and invertebrate biodiversity was compared to conventional surveillance techniques. Samples were collected from different habitats, on varying spatial scales and using multiple sampling regimes to assess how eDNA results were affected.</p> <p>For aquatic macroinvertebrates and fish, more taxa were detected by eDNA than conventional surveys conducted in parallel, and for fish, all taxa detected by conventional monitoring were confirmed by eDNA.</p> <p>For aquatic macroinvertebrates, several species were only detected through conventional methods, and the number of families detected by eDNA was lower than for conventional monitoring at all sites.</p> <p>eDNA results varied significantly between sampling locations within lentic sites and, for lotic sites, with the number of subsamples collected.</p> <p>In terms of practical implications, this study demonstrates the need for bespoke sampling protocols when collecting eDNA samples. This study improves understanding of using eDNA for detecting aquatic taxa that could inform species surveillance protocols. These are essential if eDNA is to be used by practitioners as a regulatory monitoring tool.</p>
Script and data from: The best of two worlds: toward large-scale monitoring of biodiversity combining metabarcoding and optimised parataxonomic validation.
<h2>Description</h2> <div> <p>Zenodo linked to : Penel, B., Meynard, C.N., Benoit, L., Bourdonné, A., Clamens, A., Soldati, L., Migeon, A., Chapuis, M.-P., Piry, S., Kergoat, G. and Haran, J. (2025), The best of two worlds: toward large-scale monitoring of biodiversity combining COI metabarcoding and optimized parataxonomic validation. Ecography, 2025: e07699. <a href="https://doi.org/10.1111/ecog.07699">https://doi.org/10.1111/ecog.07699</a></p> <div> <div> <div> <div> <p><strong>Publication abstract </strong></p> </div> </div> </div> <p>In a context of unprecedented insect decline, it is critical to have reliable monitoring tools to measure species diversity and their dynamic at large-scales. High-throughput DNA-based identification methods, and particularly metabarcoding, were proposed as an effective way to reach this aim. However, these identification methods are subject to multiple technical limitations, resulting in unavoidable false-positive and false-negative species detection. Moreover, metabarcoding does not allow a reliable estimation of species abundance in a given sample, which is key to document and detect population declines or range shifts at large scales. To overcome these obstacles, we propose here a Human-Assisted Molecular Identification (HAMI) approach, a framework based on a combination of metabarcoding and image-based parataxonomic validation of outputs and recording of abundance. We assessed the advantages of using HAMI over the exclusive use of a metabarcoding approach by examining 492 mixed beetle samples from a biodiversity monitoring initiative conducted throughout France. On average, 23% of the species are missed when relying exclusively on metabarcoding, this percent being consistently higher in species-rich samples. Importantly, on average, 20% of the species identified by molecular-only approaches correspond to false positives linked to cross-sample contaminations or mis-identified barcode sequences in databases. The combination of molecular methodologies and parataxonomic validation in HAMI significantly reduces the intrinsic biases of metabarcoding and recovers reliable abundance data. This approach also enables users to engage in a virtuous circle of database improvement through the identification of specimens associated with missing or incorrectly assigned barcodes. As such, HAMI fills an important gap in the toolbox available for fast and reliable biodiversity monitoring at large scales.</p> <div> <h4><strong>File description: </strong></h4> <h4>MiSeq raw sequences of the COI barcode from 492 Coleoptera field samples :</h4> <div>The Raw_sequencage_data ZIP directory contains the FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each Coleoptera field samples in duplicate using the MiSeq platform GenSeq (ISEM - University of Montpellier)</div> <div> </div> <div>The HAMI_data_script_results_R zip directory contains Rmarkdown script files (.Rmd and .html) and associated data used to analyse the systemic errors of the metabarcoding approach (N= 492 Coleoptera field samples).</div> <div> </div> <div>The HAMI_pipeline zip directory contains all the codes associated with the HAMI pipeline, as well as a ReadMe file and a test data set.</div> <div> </div> <div>The Residual_chimera.zip directory contains lists of MOTUs associated to residual chimeric sequences that were not filtered using FROGS pipeline but secondarily detected with the <em>de novo</em> approach implemented in HAMI pipeline with ‘isBimeraDenovo’ R function from DADA2 v1.28.0. It contains two distinct files according to the two sequencing runs.</div> <div> </div> <div>The NUMTS_filtered.zip directory contains lists of MOTUs that were excluded of the final dataset according to the NUMTS filtering. File xxx_pseudogene_f1_deteled.csv corresponds to MOTUs that were excluded according to the first filtrering step based on DNA sequencing. File xxx_pseudogene_f2_deteled.csv corresponds to merged MOTUs that were excluded according to the second filter based on occurrence and percentage of identity. This folder contains files for the two sequencing runs.</div> </div> </div> </div>
Monitoring vertebrate biodiversity of a protected coastal wetland using eDNA metabarcoding
<p>Monitoring plans using environmental DNA have the potential to offer a standardized and cost-efficient method to survey biodiversity in aquatic ecosystems. Among these ecosystems, coastal wetlands are key elements that serve as transition zones between marine and freshwater ecosystems and are today the target of many conservation and restoration efforts. In this sense, eDNA monitoring could provide a rapid and efficient tool for studying and generating baseline biodiversity information to guide coastal wetland management programs. Here we test an eDNA metabarcoding assay as a tool to characterize vertebrate biodiversity in one of the largest coastal wetlands of Chile, the Rio Cruces Wetland, a Ramsar designated site since 1981. We sampled surface water from 49 sites along the entire wetland. Our eDNA approach detected 91 genera of vertebrates including amphibians, fishes, mammals, and birds, as well as identified several cryptic, exotic, and endangered species. Our results also indicated that the spatial distribution of eDNA from different species is spatially structured despite the complex hydrodynamics inherent in this wetland due to the influence of daily tidal regimes. For amphibians and fishes, the number of taxa detected with eDNA was higher in the periphery of the wetland, and increased with proximity to the ocean, a pattern consistent with small-scale spatial sensitivity for some species and eDNA accumulation downstream for others. Birds and mammals showed somewhat more idiosyncratic distributions. Taken together our results add to the growing body of evidence showing eDNA can serve as a rapid cost-effective tool to characterize vertebrate communities in protected coastal wetlands, where visual surveys are difficult and animal collections are often prohibited. The use of multiple primer sets is also recommended as it facilitates the detection of ephemeral terrestrial organisms and resident aquatic organisms that make use of these wetlands.</p>
King's College Cambridge wildflower meadow monitoring data: biodiversity, climate change and society
<p class="MsoNormal">The biodiversity and climate crises are critical challenges of this century. Wildflower meadows in urban areas could provide important nature-based solutions, addressing the biodiversity and climate crises jointly, and benefitting society in the process. King's College Cambridge (England, UK) established a wildflower meadow over a portion of its iconic Back Lawn in 2019, replacing a fine lawn first laid in 1772.</p> <p class="MsoNormal">We used biodiversity surveys, Wilcoxon signed rank, and ANOVA models to compare species richness, abundance, and composition of plants, spiders, bugs, bats, and nematodes supported by the meadow, and remaining lawn, over three years. We estimated the climate change impact of meadow vs lawn from maintenance emissions, soil carbon sequestration, and reflectance effect. We surveyed members of the university to quantify the societal benefits of, and attitudes towards, increased meadow planting on the collegiate university estate.</p> <p class="MsoNormal">In spite of its small size (0.36 ha), the meadow supported approximately three times more plant species, three times more spider and bug species and individuals, and bats were recorded three times more often over the meadow than the remaining lawn. Terrestrial invertebrate biomass was 25 times higher in the meadow compared with the lawn. Fourteen species with conservation designations were recorded on the meadow (six for lawn), alongside meadow specialist species.</p> <p class="MsoNormal">Reduced maintenance and fertilising associated with meadow reduced emissions by an estimated 1.36 Mg CO<sub>2</sub>-e per hectare per year compared with lawn. Relative reflectance increased by 25-34% for meadow relative to lawn. Soil carbon stocks did not differ between meadow and lawn.</p> <p class="MsoNormal">Respondents thought meadows provided greater aesthetic, educational, and mental well-being services than lawns. In open responses, lawns were associated with undesirable elitism and social exclusion (most colleges in Cambridge restrict lawn access to senior members of the college), and respondents proved overwhelmingly in favour of meadow planting in place of lawns on the collegiate university estate.</p> <p class="MsoNormal">This study demonstrates the substantial benefits of small urban meadows for local biodiversity, cultural ecosystem services, and climate change mitigation, supplied at a lower cost than maintaining conventional lawn.</p>
Forestry and Biodiversity monitoring in Lithuania with hyperspectral camera and UAV
<p>Acquisition dates: to be updated.</p> <p>Location: Scots pine and mixed forest in Lithuania</p> <p>Camera data: </p> <p>Spectral Range 400 – 1000 nm</p> <p>Spectral sampling 2.68 nm</p> <p>Spectral resolution 5.5 nm</p> <p>Fore lens focal length 15 mm</p> <p>Field of view 38 deg</p> <p>Spectral bands 224</p> <p>Spatial pixels 1024</p> <p>Flight altitude: 70 m</p> <p>Spatial resolution: 0.05 m/pixel</p> <p> </p> <p> The dataset consists of pine tree forest hyperspectral imaging data acquired with a UAV on several dates. </p> <p>The data from each UAV flight are given as a separate dataset. </p> <p>Each dataset consists of raw and processed hyperspectral imaging data. The raw data include calibration images of white reference and dark background, raw hyperspectral images, and information on the UAV flight path. </p> <p>TheSPECIM CaliGeoPRO software was used to process raw images into hyperspectral data cubes, which are provided in the format ENVI standard. </p> <p><strong>Each flight data will come as a separate hyperlink to the storage.</strong></p> <p><strong>zip file structure (folders):<br> calibration - holds the radiometric calibration ENVI type file (raster of size 1x1024)<br> capture - raw camera capture data, navigation files, log file.<br> metdata, results - config and empty folder<br> out - holds generated ENVI data cube raster file.</strong></p> <p><strong>Download:</strong></p> <p><a href="https://icaerus-data-1.s3.eu-central-1.amazonaws.com/Uzkresti_miskai_new_fl7_20230510_151005.zip">https://icaerus-data-1.s3.eu-central-1.amazonaws.com/Uzkresti_miskai_new_fl7_20230510_151005.zip</a></p>
Using eDNA for monitoring fish and invertebrate biodiversity in freshwater ecosystems
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.