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8,460 results for “MONITORING”
Bathymetry data from the Western Australian Southwest Weland Monitoring Program
<p>The Microsoft excel file contains lake bathymetry data for 23 lakes in southwest Western Australia. Each sheet conatins volume and or lake area data as a function of elevation above the lowest point of each lake. The names of sheets correspond to the Code field that can be found in the file SiteSummary.xlsx, storred at <span><a href="https://zenodo.org/records/14015326">https://zenodo.org/records/14015326</a>.</span></p>
Dataset for "Fiber-Seismometer Hybrid Sensing for Seismic Imaging and Monitoring"
<p>The ambient noise dataset was collected on May 8, 2023, from a fiber-seismometer hybrid sensing deployment positioned along the Qiantang River in Hangzhou. The DAS data, Z-component and R-component data of seismometers are all stored in MAT format. Please refer to our study for detailed information on the dataset.</p> <p>Abstract about this study:</p> <p>Extreme climate events and geological disasters have intensified the urgency for advancing seismic imaging and monitoring. Despite developments in seismic instrumentation, particularly with seismometers and Distributed Acoustic Sensing (DAS), fine-scale observations remain challenging due to their inherent limitations and deployment configurations. This study introduces a novel hybrid sensing interferometry method that enhances multi-component signal extraction—especially poor horizontal components—through a two-step cross-correlation of DAS and seismometers. A field application near the Qiantang River in Hangzhou illustrates how our proposed framework retrieves high-quality multi-component empirical Green’s functions and advances ultra-short duration ambient noise seismic imaging techniques, including surface wave dispersion measurements and horizontal-to-vertical spectral ratio assessments. Our approach also facilitates monitoring of near-surface seismic velocity changes, dv/v, with an unprecedented 10-minute resolution, shedding light on shallow dynamic hydraulic responses. This innovative hybrid sensing framework offers new perspectives and methodologies for transforming future research in seismological observation, imaging, and monitoring. </p>
A first tentative of Structural Health Monitoring considering the Joule effect and active thermographic techniques
Open the record for dataset details and reuse information.
Data from: Spatio-temporal monitoring of deep-sea communities using metabarcoding of sediment DNA and RNA
We assessed spatio-temporal patterns of diversity in deep-sea sediment communities using metabarcoding. We chose a recently developed eukaryotic marker based on the v7 region of the 18S rRNA gene. Our study was performed in a submarine canyon and its adjacent slope in the Northwestern Mediterranean Sea, sampled along a depth gradient at two different seasons. We found a total of 5,569 molecular operational taxonomic units (MOTUs), dominated by Metazoa, Alveolata and Rhizaria. Among metazoans, Nematoda, Arthropoda and Annelida were the most diverse. We found a marked heterogeneity at all scales, with important differences between layers of sediment and significant changes in community composition with zone (canyon vs slope), depth, and season. We compared the information obtained from metabarcoding DNA and RNA and found more total MOTUs and more MOTUs per sample with DNA (ca. 20% and 40% increase, respectively). Both datasets showed overall similar spatial trends, but most groups had higher MOTU richness with the DNA template, while others, such as nematodes, were more diverse in the RNA dataset. We provide metabarcoding protocols and guidelines for biomonitoring of these key communities in order to generate information applicable to management efforts.
Data from: How much would it cost to monitor farmland biodiversity in Europe?
To evaluate progress on political biodiversity objectives, biodiversity monitoring provides information on whether intended results are being achieved. Despite scientific proof that monitoring and evaluation increase the (cost) efficiency of policy measures, cost estimates for monitoring schemes are seldom available, hampering their inclusion in policy programme budgets. Empirical data collected from 12 case studies across Europe were used in a power analysis to estimate the number of farms that would need to be sampled per major farm type to detect changes in species richness over time for four taxa (vascular plants, earthworms, spiders and bees). A sampling design was developed to allocate spatially, across Europe, the farms that should be sampled. Cost estimates are provided for nine monitoring scenarios with differing robustness for detecting temporal changes in species numbers. These cost estimates are compared with the Common Agricultural Policy (CAP) budget (2014–2020) to determine the budget allocation required for the proposed farmland biodiversity monitoring. Results show that the bee indicator requires the highest number of farms to be sampled and the vascular plant indicator the lowest. The costs for the nine farmland biodiversity monitoring scenarios corresponded to 0·01%–0·74% of the total CAP budget and to 0·04%–2·48% of the CAP budget specifically allocated to environmental targets. Synthesis and applications. The results of the cost scenarios demonstrate that, based on the taxa and methods used in this study, a Europe-wide farmland biodiversity monitoring scheme would require a modest share of the Common Agricultural Policy budget. The monitoring scenarios are flexible and can be adapted or complemented with alternate data collection options (e.g. at national scale or voluntary efforts), data mobilization, data integration or modelling efforts.
Data from: Interspecies interference and monitoring duration affect detection rates in chew cards
Pest monitoring methods should provide unbiased accurate estimates of pest densities and locations, while also minimizing time-in-field and costs. Recent pest mammal monitoring studies have found that chew cards are more effective than conventional mammal monitoring methods, but little experimental work has been done to determine optimal experimental duration or quantify the risks of saturation by one species biasing detections of other species. Here, we used chew cards in three sites within Awarua wetland (Southland, New Zealand) to investigate the optimal amount of time required to detect targeted pest species (rats, possums and mice), and to examine the potential of rats and possums to bias detection rates of other species. We found depressed detections of possums and rats where a contraspecific had been detected on a card, which is consistent with previous studies of a similar duration on interspecies interference. This experiment is the first to analyse the rates at which species detections accrue over the course of a survey, and we found rat detections lagged behind possums for the first four nights. We modelled the effect of survey duration and relative rat abundance on the likelihood of further possum detections. Duration and rat abundance interacted, meaning there are trade-offs to be considered with regard to duration: shorter durations may avoid the risk of saturation in areas of high pest density, but risk not sampling sparse or neophobic populations. Our data suggest that chew cards remain one of the most sensitive pest monitoring tools for rats and possums, compared to conventional methods such as tracking tunnels and wax tags. In areas of moderate pest densities, we suggest that a duration of five nights is optimal for detecting pests. However, in areas of high pest density the sensitivity of chew cards may render them unsuitable because of saturation and interspecies interference effects.
Data and Code for Shriver et al. 2021, Quantifying the demographic vulnerabilities of dry woodlands to climate and competition using range-wide monitoring data
<p>Data and code for demographic analyses in Shriver et al. 2021. See paper and ReadMe for analysis description and further details. </p> <p>Shriver, R.K., C.B. Yackulic, D.M. Bell, J.B. Bradford. (2021)Quantifying the demographic vulnerabilities of dry woodlands to climate and competition using range-wide demographic models. Ecology. <a href="https://doi.org/10.1002/ecy.3425">https://doi.org/10.1002/ecy.3425</a></p> <p> </p>
Brazilian academic network monitoring data
<p>The <a href="https://rnp.br/en/ipe-network">Ipê Network</a> is an academic network connecting several education, research, and health institutes across Brazil. This dataset is composed of a collection of JSON files made available by the monitoring tool <a href="https://viaipe.rnp.br">Via Ipê</a>. Each file contains information related to a specific minute. The period covers November 2020, with 55 minutes missing from the dataset. The folder hierarchy defines each file's corresponding time. For instance, the file 11/10/8/20/1d.json.gz corresponds to the JSON file for the monitoring information at 8:20 am on November 10th, 2020.<br> More details and useful code can be found on <a href="https://github.com/VitorSpa/ViaIpe-Tools">GitHub</a>.</p>
Data from: Active sound production of scarab beetle larvae opens up new possibilities for species-specific pest monitoring in soils
Root-feeding Scarabaeidae larvae can pose a serious threat to agricultural and forest ecosystems, but many details of larval ecology are still unknown. We developed an acoustic data analysis method based on active sound production by larvae (i.e. stridulations) for gaining new insights into larval ecology. In a laboratory study, third instar larvae of the Common Cockchafer (Melolontha melolontha) (n = 38) and the Forest Cockchafer (M. hippocastani) (n = 15) kept in soil-filled containers were acoustically monitored for 5 min each, resulting in the first known stridulation recordings for each species. Subsequent continuous monitoring of three M. hippocastani larvae over several hours showed that a single larva could stridulate more than 70 times per hour, and stridulation rates increased drastically with increasing larval abundance. The new fractal dimension-based data analysis method automatically detected audio sections with stridulations and provided a semi-quantitative estimate of stridulation activity. It is the first data analysis method specifically targeting Scarabaeidae larvae stridulations in soils, enabling for the first time non-invasive species-specific pest monitoring.
Data from: Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding
Global biodiversity in freshwater and the oceans is declining at high rates. Reliable tools for assessing and monitoring aquatic biodiversity, especially for rare and secretive species, are important for efficient and timely management. Recent advances in DNA sequencing have provided a new tool for species detection from DNA present into the environment. In this study, we tested if an environmental DNA (eDNA) metabarcoding approach, using water samples, can be used for addressing significant questions in ecology and conservation. Two key aquatic vertebrate groups were targeted: amphibians and bony fish. The reliability of this method was cautiously validated in silico, in vitro, and in situ. When compared with traditional surveys or historical data, eDNA metabarcoding showed a much better detection probability overall. For amphibians, the detection probability with eDNA metabarcoding was 0.97 (CI = 0.90-0.99) versus 0.58 (CI = 0.50-0.63) for traditional surveys. For fish, in 89% of the studied sites, the number of taxa detected using the eDNA metabarcoding approach was higher or identical to the number detected using traditional methods. We argue that the proposed DNA-based approach has the potential to become the next-generation tool for ecological studies and standardized biodiversity monitoring in a wide range of aquatic ecosystems.
Data from: Bioacoustic monitoring reveals details of tricolored blackbird breeding phenology
<p>Bioacoustic monitoring has been used to study behaviors of organisms from insects to whales. Studies using multiple vocalizations of a single species have the potential to determine detailed phenology, but to date are rare. We tested whether bioacoustic monitoring of multiple gender- and age-specific vocalizations of the imperiled tricolored blackbird <i>Agelaius tricolor</i> could provide detailed information on reproductive phenology and breeding success. Using inexpensive cell phones and free software applications, we collected audio recordings of tricolored blackbird colonies during their breeding season. Adding solar panels enabled the stations to run autonomously, and use of cellular data enabled remote uploading of recordings. Analysis of the presence or absence of three vocalizations (male song, female song, and nestling call) provided a rich and detailed description of the breeding phenology, including the dates for courtship, onset of nest building, incubation, nestling hatching, and fledgling departure from nesting colonies. The resulting detail was more granular and accurate than comparable data from field monitoring, although field monitoring provides data such as abundance counts that bioacoustic monitoring does not. This information has a wide range of applications to research and conservation, from enabling more accurate abundance estimates, to assessing colony success or failure with fewer visits, to providing stronger guidance for when a colony must be protected from disruption.</p>
Data from: A general-purpose spatial survey design for collaborative science and monitoring of global environmental change: the global grid
Recent guidance on environmental modeling and global land-cover validation stresses the need for a probability-based design. Additionally, spatial balance has also been recommended as it ensures more efficient sampling, which is particularly relevant for understanding land use change. In this paper I describe a global sample design and database called the Global Grid (GG) that has both of these statistical characteristics, as well as being flexible, multi-scale, and globally comprehensive. The GG is intended to facilitate collaborative science and monitoring of land changes among local, regional, and national groups of scientists and citizens, and it is provided in a variety of open source formats to promote collaborative and citizen science. Since the GG sample grid is provided at multiple scales and is globally comprehensive, it provides a universal, readily-available sample. It also supports uneven probability sample designs through filtering sample locations by user-defined strata. The GG is not appropriate for use at locations above ±85° because the shape and topological distortion of quadrants becomes extreme near the poles. Additionally, the file sizes of the GG datasets are very large at fine scale (resolution ~600 m × 600 m) and require a 64-bit integer representation.
Data from: Towards the automatic classification of avian flight calls for bioacoustic monitoring
Automatic classification of animal vocalizations has great potential to enhance the monitoring of species movements and behaviors. This is particularly true for monitoring nocturnal bird migration, where automated classification of migrants' flight calls could yield new biological insights and conservation applications for birds that vocalize during migration. In this paper we investigate the automatic classification of bird species from flight calls, and in particular the relationship between two different problem formulations commonly found in the literature: classifying a short clip containing one of a fixed set of known species (N-class problem) and the continuous monitoring problem, the latter of which is relevant to migration monitoring. We implemented a state-of-the-art audio classification model based on unsupervised feature learning and evaluated it on three novel datasets, one for studying the N-class problem including over 5000 flight calls from 43 different species, and two realistic datasets for studying the monitoring scenario comprising hundreds of thousands of audio clips that were compiled by means of remote acoustic sensors deployed in the field during two migration seasons. We show that the model achieves high accuracy when classifying a clip to one of N known species, even for a large number of species. In contrast, the model does not perform as well in the continuous monitoring case. Through a detailed error analysis (that included full expert review of false positives and negatives) we show the model is confounded by varying background noise conditions and previously unseen vocalizations. We also show that the model needs to be parameterized and benchmarked differently for the continuous monitoring scenario. Finally, we show that despite the reduced performance, given the right conditions the model can still characterize the migration pattern of a specific species. The paper concludes with directions for future research.
Seasonal monitoring of Drosophila suzukii and its non-crop hosts in Wuhu, Eastern China
<p><i>Drosophila</i><i> suzukii</i> (Matsumura) (Diptera: Drosophilidae) is a serious pest that prefers fresh fruits native to Southeast Asia. In our study apple cider vinegar bait traps were used to capture and monitor the population dynamics of this native pest in Wuhu City, China, from May/June, 2017 to May, 2018. The research was conducted at 15 locations in two fruit orchards in Wuhu. Traps caught more adults in general in Meiling blueberry orchard than in Xicun mixed orchard, and the highest trap counts occurred near harvest time (October). Females had more mature eggs from September to November and the number of mature eggs declined thereafter. We found several non-crop hosts of this pest, which can provide food and reproductive resources for <i>D. suzukii</i>, are common in forests and field margins. By comparing the number of captured adults in the Meiling and Xicun orchards, we found that blueberry was preferred by <i>D. suzukii </i>among the fruits in our search. Fruit ripening time differed among crops and therefore fly populations moved between crop and non-crop habitats during the year or had varying population dynamics on different crops in different seasons. The <i>D. suzukii</i> population and the number of mature eggs decreased in summer and winter but increased in spring and autumn. <i>Drosophila suzukii</i> had higher survival rates on blueberry than other fruits and <i>D. suzukii </i>could use four non-crop species growing around the orchards as host plants.</p>
Poor quality monitoring data underestimate the impact of Australia's megafires on a critically endangered songbird
<p>Aim: Catastrophic events such as south-eastern Australia's 2019/20 megafires are predicted to increase in frequency and severity under climate change. Rapid, well-informed conservation prioritisation will become increasingly crucial for minimising biodiversity losses resulting from megafires. However, such assessments are susceptible to bias, because the quality of monitoring data underpinning knowledge of species' distributions is highly variable and they fail to account for differences in life-history traits such as aggregative breeding. We aimed to assess how impact estimates of the 2019/20 megafires on the critically endangered regent honeyeater <i>Anthochaera phrygia </i>varied according to the quality of available input data and assessment methodology.</p> <p>Innovation: Using Google Earth Engine Burnt Area Mapping, we estimated the impact of the megafires on the regent honeyeater using six monitoring datasets that differ in quality and temporal span. These datasets are representative of the variable quality of monitoring data available for assessing fire impact on 326 other threatened species; most are poorly monitored and few have standardised, species-specific monitoring programs. We found that assessments based on Area of Occupancy (AOO), Extent of Occurrence (EOO) and public sightings underestimated the fire impact relative to recent, targeted monitoring datasets; a MaxEnt model, sightings from a national monitoring program and nest locations since 2015. Using an impact threshold of 30% of habitat burned, regent honeyeaters would not meet this criteria using estimates derived from EOO, AOO or public sightings, but would exceed the cut-off based on estimates derived from the targeted monitoring data that account for population density.</p> <p>Main conclusions: To ensure that conservation prioritisation has the greatest capacity to minimise biodiversity losses, we highlight the need to improve targeted, threatened species monitoring. We demonstrate the importance of using recent, standardised monitoring data to estimate accurately the impact of major ecological disturbances, particularly for declining, nomadic species undergoing range contractions.</p>
Supplementary Material for: 'An impedance pneumography signal quality index: design, assessment and application to respiratory rate monitoring'
<p>This supplementary material accompanies:</p> <p>Charlton P.H. <em>et al.</em>, "<a href="https://doi.org/10.1016/j.bspc.2020.102339">An impedance pneumography signal quality index for respiratory rate monitoring: design, assessment and application</a>", <em>Biomedical Signal Processing and Control</em>, 65, 102339, 2021.</p> <p>The Impedance Pneumography Signal Quality Index (SQI) dataset and accompanying scripts (in Matlab format) are provided to facilitate reproduction of the analyses using data from the MIMIC III dataset in this publication.</p> <p><strong>Summary of Publication</strong></p> <p>In this article we developed and assessed the performance of a signal quality index (SQI) for the impedance pneumography signal.<br> The SQI was developed using data from the <a href="http://peterhcharlton.github.io/RRest/listen_dataset.html">Listen dataset</a>, and assessed using data from the <a href="http://peterhcharlton.github.io/RRest/listen_dataset.html">Listen dataset</a> and MIMIC III datasets.<br> The SQI was found to accurately classify segments of impedance pneumography signal as either high or low quality. Furthermore, when it was coupled with a high performance RR algorithm, highly accurate and precise RRs were estimated from those segments deemed to be high quality. In this study performance was assessed in the critical care environment - further work is required to deteremine whether the SQI is suitable for use with wearable sensors. Both the dataset and code used to perform this study are publicly available.</p> <p><strong>Reproducing this Publication</strong></p> <p>The work relating to the MIMIC dataset in this publication can be reproduced as follows:</p> <p><strong> - Reproducing the analysis</strong><br> These steps can be used to quickly reproduce the analysis using the curated and annotated dataset.</p> <p>* Download the curated and annotated dataset from <a href="https://doi.org/10.5281/zenodo.3973770">Zenodo</a> using this <a href="https://zenodo.org/record/3973771/files/mimic_imp_sqi_data.mat?download=1">direct download link</a>.<br> * Run the analysis using the <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_imp_sqi_mimic.m</em></a> script.</p> <p><strong> - Full reproduction</strong><br> These steps include downloading the raw data files, extracting data from these files, collating the dataset, manually annotating the data, and performing the analysis.</p> <p>* Use the <a href="https://zenodo.org/record/3973771/files/ImP_SQI_mimic_data_importer.m?download=1"><em>ImP_SQI_mimic_data_importer.m</em></a> script to download raw MIMIC data files from PhysioNet, and collate them into a single Matlab file.<br> * Prepare the dataset for manual annotation by running the <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_imp_sqi_mimic.m</em></a> script.<br> * Manually annotate the signals by running the <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_mimic_imp_annotation.m</em></a> script - the annotations are stored in separate files (the original annotation files are available <a href="https://zenodo.org/record/3974113/files/2019_annotations.zip?download=1">here</a>).<br> * Import the manual annotations into the collated data file by re-running the <a href="https://zenodo.org/record/3973771/files/ImP_SQI_mimic_data_importer.m?download=1"><em>ImP_SQI_mimic_data_importer.m</em></a> script.<br> * Run <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_imp_sqi_mimic.m</em></a> to perform the analysis described in the publication.</p> <p><strong> - Submitted manuscript</strong></p> <p>The submitted manuscript is available <a href="https://zenodo.org/record/5211463/files/Impedance%20SQI%20manuscript%20-%20Oct%202020%20revision.docx?download=1">here</a>.</p> <p>The scripts are also stored (alongside details of how to use them) are available in the <a href="http://peterhcharlton.github.io/RRest/">RRest GitHub repository</a> at: <a href="https://github.com/peterhcharlton/RRest/tree/master/RRest_v3.0/Publication_Specific_Scripts/ImP_SQI">https://github.com/peterhcharlton/RRest/tree/master/RRest_v3.0/Publication_Specific_Scripts/ImP_SQI</a></p> <p>License: The dataset (<a href="https://zenodo.org/record/3974113/files/mimic_imp_sqi_data.mat?download=1"><em>mimic_imp_sqi_data.mat</em></a>) is distributed under the terms specified in the accompanying LICENSE file. The scripts are distributed under the GNU General Public Licence (as specified towards the start of each file).</p> <p>Version 1.0: This version includes the submitted manuscript.</p> <p> </p>
Data for: Using a digital twin of an electrical stimulation device to monitor and control the electrical stimulation of cells in vitro
<p>Replication data for "Using a digital twin of an electrical stimulation device to monitor and control the electrical stimulation of cells in vitro".</p>
Figure 1 in Molecular data extend Australian Cricotopus midge (Chironomidae) species diversity, and provide a phylogenetic hypothesis for biogeography and freshwater monitoring
Figure 1. Schematic phylogeny based on a majority rule consensus maximum-likelihood (ML) topology for the reduced data set. Relevant nodal support values are shown, which correspond to Bayesian posterior probabilities and ML bootstrap support, respectively; –, nodes unresolved by ML; *, posterior probabilities of 1.00 or bootstrap support of 100. Thick branches denote Australian clades; thin branches are non-Australian taxa. Geographical distributions and tolerances to ecosystem impact for Australian Cricotopus species are shown according to the inset legend, with the forms of divergent species coded based on assumptions made from the current sampled localities.
Fig. 2 in A Solar-Powered UV Light Trap for Long-Term Monitoring of Insects in Remote Habitats
Fig. 2. The solar-powered UV light trap in A) stabilized-vegetated sands, B) open sand dunes, and C) agricultural crop margin. Note that in addition to the components in Fig. 1, 6–8 ft (1.8–2.4 m) pieces of steel rebar and wire are used to position the solar panel.
Fig. 1 in A Solar-Powered UV Light Trap for Long-Term Monitoring of Insects in Remote Habitats
Fig. 1. Exploded view of solar-powered UV light trap, with component labels corresponding to the items in Table 1. The light trap components battery (n), ballast box (a), photoelectric switch (g), and battery clamps (l) were put inside a second bucket to protect them from corrosion and overheating.
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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.