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858 results for “monitoring data”
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.
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>
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.
Data from: Monitoring soil moisture at the catchment scale – A novel approach combining antecedent precipitation index and radar-derived rainfall data
<p>Knowledge about soil moisture is important for event-based rainfall-runoff models but monitoring conditions at the catchment scale is not a trivial task. Soil moisture is highly variable in space and time, particularly in dry climates with seasonal and spatially heterogeneous rainfall. Point measurements are difficult to upscale, and remotely sensed (RS) data often lack in spatial or temporal resolution for local or regional studies. Longer latency periods – the time required before data becomes available – of some RS data make them less applicable to time-sensitive analyses such as flash flood forecasting. This study evaluated a novel approach for estimating catchment-scale volumetric soil moisture using an antecedent precipitation index (API) -based model. The model was trained and tested using in-situ soil moisture measurements collected during a 3-month field sampling campaign in a 142 km<sup>2</sup><span><span><span><span><span><span><span><span><span> study area in central New Mexico. The calibrated model was applied at the catchment scale to produce soil moisture grids from radar-derived rainfall estimates. Model performance, resolution and latency were compared to satellite-based soil moisture estimates. Benefits of the proposed new method include high spatial resolution (1 × 1 km or less depending on the precipitation data source) and high prediction accuracy (root mean square errors 0.014–0.018 m</span></span></span></span></span></span></span></span></span><sup>3</sup><span><span><span><span><span><span><span><span><span>/m</span></span></span></span></span></span></span></span></span><sup>3</sup><span><span><span><span><span><span><span><span><span>). Given the short latency period for radar-derived rainfall data, the method has potential for use in operational flood risk assessment and forecasting.</span></span></span></span></span></span></span></span></span></p>
Monitoring small mammal abundance using NEON data: Are calibrated indices useful?
<p>Small mammals are important to the functioning of ecological communities with changes to their abundances used to track impacts of environmental change. While capture-recapture estimates of absolute abundance are preferred, indices of abundance continue to be used in cases of limited sampling, rare species with little data, or unmarked individuals. Improvement to indices can be achieved by calibrating them to absolute abundance but their reliability across years, sites, or species is unclear. To evaluate this, we used the US National Ecological Observatory Network (NEON) capture-recapture data for 63 small mammal species over 46 sites from 2013–2019. We generated 17,155 absolute abundance estimates using capture-recapture analyses and compared these to two standard abundance indices, and three types of calibrated indices. We found that neither raw abundance indices nor index calibrations were reliable approximations of absolute abundance, with raw indices less correlated with absolute abundance than index calibrations (raw indices overall R<sup>2</sup> < 0.5, index calibration overall R<sup>2</sup> > 0.6). Performance of indices and index calibrations varied by species, with those having higher and less variable capture probabilities performing best. We conclude that indices and index calibration methods should be used with caution with a count of individuals being the best index to use, especially if it can be calibrated with capture probability. None of the indices we tested should be used for comparing different species due to high variation in capture probabilities. Hierarchical models that allow for sharing of capture probabilities over species or plots (i.e., joint likelihood models) may offer a better solution to mitigate the cost and effort of large-scale small mammal sampling while still providing robust estimates of abundance.</p>
Long-term snow chemical composition monitoring - Ariebreen glacier (Hornsund) - raw data
<p>Since 2020, snow samples have been taken from the Ariebreen glacier several times a season during the accumulation season. The snow samples are collected in polyethylene sterile bags and transported to the Polish Polar Station Hornsund. After melting at room temperature, they are analysed in the chemical laboratory of the Polish Polar Station for pH, conductivity and chemical composition (major ions).<br> <br> Site Information Ariebreen - 0.5 km long glacier between Skoddefjellet and the northern part of Ariekammen, southernmost in Wedel Jarlsberg Land.</p> <p>Presented data from 2020 to 2022</p> <p>The data has not been checked, which means that it is raw data.</p> <p>Principal investigator (PI) Adam Nawrot</p>
The NO2 monitoring data for "Satellite-based long-term spatiotemporal trends in ambient NO2 concentrations and attributable health burdens in China from 2005 to 2020"
<p>The current dataset is about NO2 monitoring data used in Geohealth manuscript entitled "Satellite-based long-term spatiotemporal trends in ambient NO2 concentrations and attributable health burdens in China from 2005 to 2020". It was collected from the air quality monitoring stations administered by the China National Environmental Monitoring Center. </p>
Bold Park reptile species capture data for: Decadal abundance patterns in an isolated urban reptile assemblage: Monitoring under a changing climate
<p class="MsoNormal"><span>Fenced pitfall trapping in four sampling sites <span>representing different habitats and fire history</span> over the primary reptile activity period for 35 consecutive years with over 17000 individuals captured during 3300 days of sampling; the trapping regime was modified for the last 28 years.</span></p>
Data from: Decision and response monitoring during working memory are sequentially represented in the human insula
<p>This dataset is associated with the manuscript "Decision and response monitoring during working memory are sequentially represented in the human insula", and provides all preprocessed files necessary to replicate the results.</p> <p>In this study, we recorded intracranial EEG data (specifically, SEEG) from the insula of 12 patients with pharmacoresistant epilepsy while they were performing a verbal working memory task.</p> <p>The present dataset consists of preprocessed neural activity (Time-Frequency Representation, 4-150 Hz), electrode coordinates (in MNI template space), related insula subregion labels, and 3D mesh of bilateral insula. TFR data is sampled at 200 Hz, and epoched into 12-second trials.</p> <p>The code we used to preprocess and analyze the data is hosted <a href="https://github.com/ludovicbellier/InsulaWM">on Github</a>.</p>
Monitoring programme on strict forest reserves in Flanders (Belgium) - site level stand structure, regeneration and vegetation data
<p>This dataset contains comprehensive statistics on stand structure, rejuvenation, and vegetation for each forest reserve included in the monitoring program on strict forest reserves in Flanders (Belgium). The data collection and processing methodology used are described in <a href="https://purews.inbo.be/ws/portalfiles/portal/41050863/Vandekerkhove_etal_2021_MonitoringProgrammeOnStrictForestReservesFlanders.pdf">Vandekerkhove et al., 2021</a>.</p> <p>The dataset encompasses information on 15 distinct strict forest reserves and covers one to three consecutive forest inventories following a 10-year cycle. </p> <p>The "<strong>site_info.xlsx</strong>" file provides details on the 15 sites, including central coordinates, surface area, forest type, and the year when they were set aside. For detailed descriptions of the information provided, please refer to the "<strong>_metadata_site_info.xlsx</strong>" file.</p> <p>The “<strong>statistics_per_reserve.zip</strong>” file contains 12 separate csv-files with the following data:</p> <ul> <li> <p><strong>stat_dendro(_by)(_diam)(_species).csv</strong> : statistics on basic stand structure attributes (volume, basal area, number of trees per hectare, …) for living and dead standing trees (DBH-threshold 5cm): overall values and values per diameter class and/or species </p> </li> <li> <p><strong>stat_carbon.csv </strong>: statistics on biomass and carbon stock related to living trees</p> </li> <li> <p><strong>stat_logs(_by)(_decay)(_species).csv</strong> : statistics on volume per hectare of lying deadwood: values per decay stage and/or species </p> </li> <li> <p><strong>stat_reg(_by)(_height)(_species).csv</strong> : statistics on rejuvenation (numbers per ha of young trees - seedlings up to trees with DBH< 5cm): overall values and values per heightclass and/or species </p> </li> <li> <p><strong>stat_veg.csv</strong> : statistics on vegetation characteristics, including number of species, moss, herb, shrub, tree and waterlayer cover, cumulated canopy cover and soil disturbance by game</p> </li> <li> <p><strong>stat_herbs.csv</strong> : species-specific mean cover, percentage of plots where each species occurs</p> </li> </ul> <p>For descriptions of the common fields used in the above csv-files, please consult the "<strong>_metadata_statistics.xlsx</strong>" file. </p> <p>For detailed and comprehensive information regarding the meaning and characteristics of the calculated variables, please refer to the "<strong>_metadata_variables.xlsx</strong>" file. </p> <p>Plot-level results regarding dendrometry and regeneration are published separately<a href="https://zenodo.org/record/7588680"> here</a>, while information on vegetation can be found<a href="https://zenodo.org/record/7870740"> here</a>.</p> <p><strong>For any inquiries or further information, please contact Kris.vandekerkhove@inbo.be or Anja.leyman@inbo.be</strong>. The provided csv-files will be updated as required to address any issues or include data from additional surveys. . Please check for updated versions periodically.</p> <p><strong>We ask the users of the dataset to notify us of its use.</strong></p>
Data from: Long term monitoring reveals the importance of large, long unburnt areas and smaller fires in moderating mammal declines in fire-prone savanna of northern Australia
<p>Biodiversity loss is often attributable to multiple interacting pressures that are moderated across environmental gradients. These processes contribute to complex responses that are challenging to interpret and understand. Well-designed and well-implemented monitoring can play a vital role in this but is rarely undertaken.</p> <p>Mounting evidence suggests that current fire regimes across savanna ecosystems have contributed to the decline of a range of biota. Hence, contemporary fire regimes are at odds with conservation goals.</p> <p>Using an extensive spatio-temporal monitoring dataset from three large National Parks in northern Australia, we applied generalised linear mixed models to examine: 1) trends in mammal richness and abundance through time and how these vary across environmental gradients such as productivity or landscape position (e.g., terrain ruggedness); and 2) how fire, a potential driver, is moderated by environmental gradients.</p> <p>Across 24-years, major declines in mammal richness and abundance were observed with greater reductions in less rugged and less mesic habitats. Patterns of decline were related to multiple aspects of fire regimes, but not changes in vegetation structure and composition, or the arrival of Cane Toads <em>Rhinella marina</em> and concomitant poisoning of predatory animals during consumption. More pronounced declines occurred in sites that were exposed to larger fires, had less long unburnt (5 years without fire) vegetation, and were more distant from large, long unburnt patches.</p> <p>Relationships between mammal persistence and fire varied among vegetation communities, with the strongest fire effects observed in lowland woodland – relatively drier with few barriers to fire spread – where the availability of long unburnt areas moderated declines more than in other vegetation communities.</p> <p><em>Synthesis and applications</em>. Current fire regimes are contributing to mammal declines in northern Australian savanna. Collectively, our results highlight: 1) the value of long term monitoring, and importance of considering landscape position when assessing faunal responses to landscape-level perturbations like fire; 2) that significant improvements in fire regimes are required to ameliorate mammal declines; and 3) the need to shift management focus from retaining small, short-lived unburnt patches towards preserving relatively large contiguous areas of long unburnt habitat, particularly in less rugged lowland and sandstone woodlands.</p>
Dataset for "Improving data quality of low-cost light-scattering PM sensors: Towards automatic air quality monitoring in urban environments"
<p>The dataset contains the data used in the article "Improving data quality of low-cost light-scattering PM sensors: Towards automatic air quality monitoring in urban environments".</p> <p>A low-cost monitoring system composed of 14 monitoring stations was positioned at the official monitoring station of Torino Rubino in the city of Turin (Italy). The official station is managed by the environmental agency ARPA Piemonte.</p> <p>Each low-cost station contains four low-cost light-scattering PM sensors (Honeywell HPMA115S0-XXX), one temperature and relative humidity sensor (DHT22), and one atmospheric pressure sensor (BME/BMP280).<br>The sampling time of the PM sensors was set to one second, while the other sensors generated measurements every 3-4 seconds.</p> <p>The official monitoring station uses both a gravimetric and a beta attenuation instrument for measuring PM.</p> <p>The data contained in this dataset was collected from October 2020 to November 2021. It contains the PM2.5, relative humidity, and temperature measurements of the low-cost monitoring system and the official measurements of the beta attenuation device.</p> <p>Measurements of low-cost sensors are expressed in UTC, while official measurements are expressed in UTC+1.</p> <p>Official PM measurements can be also found at https://aria.ambiente.piemonte.it/qualita-aria/dati.</p>
Raw Starlink/OneWeb monitoring data from Altrincham UK for March 2023 - Test for IAU 385
<p>This zip file contains data for one calendar month of low level scan data (March 2023) from a home-based monitoring station in Altrincham, UK. This is a test dataset to be presented at the IAU Symposium 385: "Astronomy and Satellite Constellations: Pathways Forward", to see if it is useful.</p> <p>2GHz band downlink band data from a HackRF and beacon monitoring at 11.325 GHz via a Kerberos SDR</p> <p>Daily TLE files and 10 minute scan plots</p> <p>Readme file on data formats and script used to make the 10 minute plots</p>
data for "A machine-learned approach to monitor chemical reaction via in-situ infrared spectroscopy"
<p>Source spectral and structural data of the AIMD trajectory and NEB calculation</p> <p>1. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/180-structure-IR.zip">180-structure-IR</a>.zip Source spectral and structural data of the AIMD trajectory for the selected 180 configurations</p> <p>2. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/md-pos-1.xyz?versionId=1a43760b-5cba-4548-85e6-6a45252403fc">md-pos-1.xyz</a> AIMD trajectories</p> <p>3. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/ML-0-5100.tar.gz?versionId=ed65c63f-aa96-4be4-abef-e7a5bb7bf22f">ML-0-5100.tar.gz</a> <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/ML-0-5100.tar.gz?versionId=ed65c63f-aa96-4be4-abef-e7a5bb7bf22f">ML-5101-7500.tar.gz</a> <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/ML-0-5100.tar.gz?versionId=ed65c63f-aa96-4be4-abef-e7a5bb7bf22f">ML-7501-9500.tar.gz</a> Source spectral and structural data of the AIMD trajectory for the extracted 9500 configurations</p> <p>4. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/split-neb-75.zip?versionId=a30f0f34-3ce2-4619-abd3-62e71174069b">split-neb-75.zip</a> Source spectral and structural data of the AIMD trajectory for the CO-CO dimerization reaction</p>
Continuous air pollution monitoring data for the Kanto region (Japan) derived from original observations by the National Institute for Environmental Studies Environmental Observatory (https://tenbou.nies.go.jp/download/).
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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.