scholarly journals Experiences from the Danish Fungal Atlas: Linking mushrooming, nature conservation and primary biodiversity research 

2021 ◽  
Vol 5 ◽  
Author(s):  
Jacob Heilmann-Clausen ◽  
Tobias Frøslev ◽  
Jens Petersen ◽  
Thomas Læssøe ◽  
Thomas Jeppesen
Keyword(s):  
Nature Conservation ◽  
Dna Sequencing ◽  
Citizen Science ◽  
High Throughput Sequencing ◽  
Low Cost ◽  
Mobile App ◽  
Science Data ◽  
Global Biodiversity Information Facility ◽  
Validation Data ◽  
Species Discovery

The Danish Fungal Atlas is a citizen science project launched in 2009 in collaboration among the University of Copenhagen, Mycokey and the Danish Mycological Society. The associated database now holds almost 1 million fungal records, contributed by more than 3000 recorders. The records represent more than 8000 fungal species, of which several hundred have been recorded as new to Denmark during the project. In addition several species have been described as new to science. Data are syncronized with the Global Biodiversity Information Facility (GBIF) on a weekly basis, and is hence freely available for research and nature conservation. Data have been used for systematic conservation planning in Denmark, and several research papers have used data to explore subjects such as host selection in wood-inhabiting fungi (Heilmann‐Clausen et al. 2016), recording bias in citizen science (Geldmann et al. 2016), fungal traits (Krah et al. 2019), biodiversity patterns (e.g. Andrew et al. 2018), and species discovery (Heilmann-Clausen et al. 2019). The project database is designed to faciliate direct interactions and communication among volunteers. The validation of submitted records is interactive and combines species-specific smart filters, user credibility, and expert tools to secure the highest possible data credibility. In 2019, an AI (artificial intelligence) trained species identification tool was launched along with a new mobile app, enabling users to identify and record species directly in the field (Sulc et al. 2020). At the same time, DNA sequencing was tested as an option to test difficult identifications, and in 2021 a high-throughput sequencing facility was developed to allow DNA sequencing of hundreds of fungal collections at a low cost. The presentation will give details on data validation, data use and how we have worked with cultivation of volunteers to provide a truly coherent model for collaboration on mushroom citizen science.

scholarly journals Remote Sensing of Aerated Flows at Large Dams: Proof of Concept

2021 ◽  
Vol 13 (14) ◽  
pp. 2836
Author(s):  
Matthias Kramer ◽  
Stefan Felder
Keyword(s):  
Free Surface ◽  
Citizen Science ◽  
Scale Effects ◽  
Free Surface Flows ◽  
Design Guidelines ◽  
Full Scale ◽  
Stepped Spillway ◽  
Proof Of Concept ◽  
Science Data ◽  
Validation Data

Dams are important for flood mitigation, water supply, and hydroelectricity. Every dam has a water conveyance structure, such as a spillway, to safely release extreme floods when needed. The flows down spillways are often self-aerated and spillway design has typically been investigated in laboratory experiments, which is due to limitations in suitable full scale flow measurement instrumentation and safety considerations. Prototype measurements of aerated flows are urgently needed to quantify potential scale effects and to provide missing validation data for design guidelines and numerical simulations. Herein, an image-based analysis of free-surface flows on a stepped spillway was conducted from a top-view perspective at laboratory scale (fixed camera installation) and prototype scale (drone footage). The drone videos were obtained from citizen science data. Analyses allowed to remotely estimate the location of the inception point of free-surface aeration, air–water surface velocities, and their fluctuations, as well as the residual energy at the downstream end of the chute. The laboratory results were successfully validated against intrusive phase-detection probe data, while the prototype observations provided proof of concept at full scale. This study highlights the feasibility of image-based measurements at prototype spillways. It demonstrates how citizen science data can be used to advance our understanding of real world air–water flow processes and lays the foundations for the remote collection of long-missing prototype data.

scholarly journals Design and Development of Interoperable Cloud Sensor Services to Support Citizen Science Projects

2020 ◽  
Author(s):  
Henning Bredel ◽  
SImon Jirka ◽  
Joan Masó Pau ◽  
Jaume Piera
Keyword(s):  
Citizen Science ◽  
Low Cost ◽  
Flow Analysis ◽  
Open Data ◽  
Building Blocks ◽  
It Infrastructure ◽  
Science Data ◽  
Area Of Interest ◽  
Observatory Data ◽  
Set Up

<p><span>Citizen Observatories are becoming a more and more popular source of input data in many scientific domains. This includes for example research on biodiversity (e.g. counts of specific species in an area of interest), air quality monitoring (e.g. low-cost sensor boxes), or traffic flow analysis (e.g. apps collecting floating car data).</span></p><p><span>For the collection of such data, different approaches exist. Besides frameworks providing re-usable software building blocks (e.g. wq framework, Open Data Kit), many projects rely on custom developments. However, these solutions are mainly focused on providing the necessary software components. Further work is necessary to set-up the necessary IT infrastructure. In addition, aspects such as interoperability are usually less considered which often leads to the creation of isolated information silos.</span></p><p><span>In our presentation, we will introduce selected activities of the European H2020 project COS4CLOUD (Co-designed citizen observatories for the EOS-Cloud). Among other objectives, COS4CLOUD aims at providing re-usable services for setting up Citizen Observatories based on the European Open Science (EOS) Cloud. We will especially discuss how it will make use of interoperability standards such as the Sensor Observation Service (SOS), SensorThings API as well as Observations and Measurements (O&M) of the Open Geospatial Consortium (OGC).</span></p><p><span>As a result, COS4CLOUD will not only facilitate the collection of Citizen Observatory data by reducing the work necessary to set-up a corresponding IT infrastructure. It will also support the exchange and integration of Citizen Observatory data between different projects as well as the integration with other authoritative data sources. This shall increase the sustainability of data collection efforts as Citizen Science data may be used as input for many data analysis processes beyond the project that originally collected the data.</span></p>

scholarly journals Notes of Life: A platform for recording species observations driven by artificial intelligence

2019 ◽  
Vol 3 ◽  
Author(s):  
Congtian Lin ◽  
Jiangning Wang ◽  
Liqiang Ji
Keyword(s):  
Artificial Intelligence ◽  
Citizen Science ◽  
Higher Plants ◽  
Mobile App ◽  
Biodiversity Data ◽  
Science Data ◽  
Biodiversity Research ◽  
Large Numbers ◽  
In The Wild ◽  
Speed Up

Biodiversity research is stepping into a big data era with the rapid increase in the abundance of biodiversity data, especially the large number of species images. It has been a new trend and hot topic on how to utilize artificial intelligence to mine big biodiversity data to support wildlife observation and recognition. In this research, we integrate large numbers of species images, including higher plants, birds and insects, and use a state-of-the-art image deep learning technique to train species auto-recognition models. Currently, we get a model that can recognize more than 900 Chinese birds with top 1 accuracy 81% and top 5 accuracy 95% (top n accuracy means the probability that the correct answer presents in top n predicted results), and more models are coming soon. Based on these models, we developed a platform named Notes of Life (NOL, http://nol.especies.cn), which includes a website and a mobile application (app) for assisting biological scientists and citizen scientists to recognize and record wildlife. Users can upload their observation records and images of wildlife through our mobile app while they are investigating in the wild. The website is used for bulk data uploading and management. Species images can be classified by taxon-specific, plug-in recognition models that speed up the process of identification. There is an expert module in NOL where citizen scientists can work interactively with information provided by biological scientists, and post a species image identification request to experts when they cannot recognize the species by themselves or from models. The expert module is for improving the quality of citizen science data, and it is a supplement of the disadvantage of species auto-recognition models. Above all, NOL embraces the idea that scientific research supports citizen science and citizen science gives feedback to science, and of finding a sustainable way to collect increasingly more reliable data for biodiversity research.

scholarly journals Modelling the Heterogeneity within Citizen Science Data for Biodiversity Research

2021 ◽  
Vol 5 ◽  
Author(s):  
Diana Bowler ◽  
Nick Isaac ◽  
Aletta Bonn
Keyword(s):  
Citizen Science ◽  
Heterogeneous Data ◽  
Sampling Effort ◽  
Occupancy Models ◽  
Species Occurrence ◽  
Science Data ◽  
Global Biodiversity Information Facility ◽  
Occurrence Data ◽  
Occupancy Detection ◽  
Species Population

Large amounts of species occurrence data are compiled by platforms such as the Global Biodiversity Information Facility (GBIF) but these data are collected by a diversity of methods and people. Statistical tools, such as occupancy-detection models, have been developed and tested as a way to analyze these heterogeneous data and extract information on species’ population trends. However, these models make many assumptions that might not always be met. More detailed metadata associated with occurrence records would help better describe the observation/detection submodel within occupancy models and improve the accuracy/precision of species’ trend estimates. Here, we present examples of occupancy-detection models applied to citizen science datasets, including dragonfly data in Germany, and typical approaches to account for variation in sampling effort and species detectability, including visit covariates, such as list length. Using results from a recent questionnaire in Germany asking citizen scientists about why and how they collect species occurrence data, we also characterize the different approaches that citizen scientists take to sample and report species observations. We use our findings to highlight examples of key metadata that are often missing (e.g., length of time spent searching, complete checklist or not) in data sharing platforms but would greatly aid modelling attempts of heterogeneous species occurrence data.

The HEMERA Balloon Research Infrastructure

2021 ◽  
Author(s):  
Felix Friedl-Vallon ◽  
Philippe Raizonville ◽  
André Vargas ◽  
Kristine Dannenberg ◽  
Marta Albano ◽  
...  
Keyword(s):  
Low Cost ◽  
Ground Surface ◽  
Earth Observation ◽  
Research Infrastructure ◽  
User Needs ◽  
Science Data ◽  
Joint Research ◽  
Validation Data ◽  
Horizon 2020 ◽  
Research Activities

<p>Stratospheric balloons are useful platforms for various research and technology needs. They allow to collect valuable data in many science fields, e.g. atmospheric science and astrophysics; they can be used for demonstrations in preparation of new space and Earth observation missions; they can be used to provide calibration/validation data for Earth observation space missions, or for dropping test objects from the stratosphere.</p><p>Various types of balloons are available, corresponding to different missions: Zero Pressure Balloons (ZPB) for heavy payloads (100 kg to 3 tons) and short to medium duration (1 day to several days), Sounding Balloons (SB) for very light payloads (3 kg).</p><p>Payloads can be flown at various altitudes between the ground surface up to 40 km, according the type of balloon and the kind of mission. Compared to satellites, stratospheric balloons can be operated at relatively low cost and with shorter lead times from the experiment idea to the flight.</p><p>Mid-2017, a new Research Infrastructure called HEMERA has been selected by the European Commission within its programme Horizon 2020. The HEMERA objectives are to:</p><ul><li>Provide better and coordinated balloon access to the troposphere and stratosphere for scientific and technological research, in response to the scientific user needs.</li> <li>Attract new users to enlarge the community accessing the balloon infrastructure and foster scientific and technical collaboration.</li> <li>Enlarge the fields of science and technology research conducted with balloons.</li> <li>Improve the balloon service offered to scientific and technical users through innovative developments.</li> <li>Favour standardization, synergy, complementarities and industrialization through joint developments with greater cost-effectiveness.</li> </ul><p>The project is coordinated by CNES and involves 13 partners in total, from various European entities and Canada. The project was kicked-off in late January 2018 and will be executed during 2018-2022.</p><p>Six ZPB flights with a target payload mass of at least 150 kg are foreseen within HEMERA, offering free of charge access to users and scientists for various science measurements and/or for technology tests. In addition, several SB flights are foreseen. The launch sites will be Esrange in Sweden, Timmins in Canada, for the ZPB and Aire sur l'Adour in France for the SB. The selected experiments will fly on balloons during the years 2019-2022. </p><p>Two Calls for Proposals were planned in the HEMERA project, the first was launched in 2018 and 39 answers from 12 countries have been received; 23 experiments have been selected. 31 answers have been received in the frame of the second call, from 10 countries. In total 39 experiments from 13 countries have been selected. The first HEMERA flights occurred in summer 2019 from Kiruna and Timmins.</p><p>In addition, Open Access to balloon data will be organized in the frame of the Data Center, giving access to science data collected during the flights. Networking activities are planned in order to promote the Infrastructure in the European countries, and Joint Research activities are conducted in order to improve as far as possible the balloon offer in the view of the user needs.</p>

From crowdsourcing environmental measurements to their integration in the GEOSS portal

2020 ◽  
Author(s):  
Valantis Tsiakos ◽  
Maria Krommyda ◽  
Athanasia Tsertou ◽  
Angelos Amditis
Keyword(s):  
Environmental Monitoring ◽  
Citizen Science ◽  
Low Cost ◽  
Earth Observation ◽  
Observation System ◽  
Observation Data ◽  
The European Union ◽  
Science Data ◽  
Portable Sensors ◽  
Areas Of Interest

<p>Environmental monitoring is based on time-series of data collected over long periods of time from expensive and hard to maintain in-situ sensors available only in specific areas. Due to the climate change it is important to monitor extended areas of interest. This need has raised the question of whether such monitoring can be complemented or replaced by Citizen Science.</p><p>Crowdsourced measurements from low-cost and easy to use portable sensors and devices can facilitate the collection of the needed information with the support of volunteers, enabling the monitoring of environmental ecosystems and extended areas of interest. In particular, during the last years there has been a rapid increase of citizen-generated knowledge that has been facilitated by the wider use of mobile devices and low-cost portable sensors. To enable their easy integration to existing models and systems as well as their utilisation in the context of new applications, citizen science data should be easily discoverable, re-usable, accessible and available for future use.</p><p>The Global Earth Observation System of Systems (GEOSS) offers a single access point to Earth Observation data (GEOSS Portal), connecting users to various environmental monitoring systems around the world while promoting the use of common technical standards to support their utilisation. </p><p>Such a connection was demonstrated in the context of SCENT project. SCENT is a EU project which has implemented an integrated toolbox of smart collaborative and innovating technologies that allows volunteers to collect environmental measurements as part of their everyday activities.</p><p>These measurements may include images that include information about the land cover and land use of the area, air temperature and soil moisture measurements from low-cost portable environmental sensors or river measurements, water level and water velocity extracted from multimedia, images and video, through dedicated tools.</p><p>The collected measurements are provided to policy makers and scientists to facilitate the decision making regarding needed actions and infrastructure improvements as well as the monitoring of environmental phenomena like floods through the crowdsourced information.</p><p>In order to ensure that the provided measurements are of high quality, a dedicated control mechanism has been implemented that uses a custom mechanism, based on spatial and temporal clustering, to identify biased or low quality contributions and remove them from the system.</p><p>Finally, recognising the importance of making the collected data available all the validated measurements are modelled, stored and provisioned using the Open Geospatial Consortium (OGC) standards Web Feature Service (WFS) and Web Map Service (WMS) as applicable.</p><p>This allows the spatial and temporal discovery of information among the collected measurements, encourages their re-usability and allows their integration to systems and platforms utilizing the same standards. The data collected by the SCENT Campaigns organized at the Kifisos river basin and the Danube Delta can be found at the GEOSS portal under the WFS here https://www.geoportal.org/?f:sources=wfsscentID and under the WMS here https://www.geoportal.org/?f:sources=wmsSCENTID.  </p><p>This activity is showcased as part of WeObserve project that has received funding from the European Union’ s Horizon 2020 research and innovation programme under grant agreement No 776740.</p>

scholarly journals Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing

BMC Biology ◽  
2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Amrita Srivathsan ◽  
Emily Hartop ◽  
Jayanthi Puniamoorthy ◽  
Wan Ting Lee ◽  
Sujatha Narayanan Kutty ◽  
...  
Keyword(s):  
Dna Sequences ◽  
Large Scale ◽  
Low Cost ◽  
Small Body ◽  
Small Subset ◽  
Similar Species ◽  
Large Species ◽  
Morphological Examination ◽  
Species Discovery ◽  
Short Period

Abstract Background More than 80% of all animal species remain unknown to science. Most of these species live in the tropics and belong to animal taxa that combine small body size with high specimen abundance and large species richness. For such clades, using morphology for species discovery is slow because large numbers of specimens must be sorted based on detailed microscopic investigations. Fortunately, species discovery could be greatly accelerated if DNA sequences could be used for sorting specimens to species. Morphological verification of such “molecular operational taxonomic units” (mOTUs) could then be based on dissection of a small subset of specimens. However, this approach requires cost-effective and low-tech DNA barcoding techniques because well-equipped, well-funded molecular laboratories are not readily available in many biodiverse countries. Results We here document how MinION sequencing can be used for large-scale species discovery in a specimen- and species-rich taxon like the hyperdiverse fly family Phoridae (Diptera). We sequenced 7059 specimens collected in a single Malaise trap in Kibale National Park, Uganda, over the short period of 8 weeks. We discovered > 650 species which exceeds the number of phorid species currently described for the entire Afrotropical region. The barcodes were obtained using an improved low-cost MinION pipeline that increased the barcoding capacity sevenfold from 500 to 3500 barcodes per flowcell. This was achieved by adopting 1D sequencing, resequencing weak amplicons on a used flowcell, and improving demultiplexing. Comparison with Illumina data revealed that the MinION barcodes were very accurate (99.99% accuracy, 0.46% Ns) and thus yielded very similar species units (match ratio 0.991). Morphological examination of 100 mOTUs also confirmed good congruence with morphology (93% of mOTUs; > 99% of specimens) and revealed that 90% of the putative species belong to the neglected, megadiverse genus Megaselia. We demonstrate for one Megaselia species how the molecular data can guide the description of a new species (Megaselia sepsioides sp. nov.). Conclusions We document that one field site in Africa can be home to an estimated 1000 species of phorids and speculate that the Afrotropical diversity could exceed 200,000 species. We furthermore conclude that low-cost MinION sequencers are very suitable for reliable, rapid, and large-scale species discovery in hyperdiverse taxa. MinION sequencing could quickly reveal the extent of the unknown diversity and is especially suitable for biodiverse countries with limited access to capital-intensive sequencing facilities.

scholarly journals The Use of Citizen Science to Achieve Multivariate Management Goals on Public Lands

Diversity ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 293
Author(s):  
Sara Souther ◽  
Vincent Randall ◽  
Nanebah Lyndon
Keyword(s):  
Citizen Science ◽  
Land Management ◽  
Ecological Integrity ◽  
Public Land ◽  
Suitable Habitat ◽  
Science Data ◽  
Public Land Management ◽  
Federal Land ◽  
Botanical Research ◽  
Federal Land Management

Federal land management agencies in the US are tasked with maintaining the ecological integrity of over 2 million km2 of land for myriad public uses. Citizen science, operating at the nexus of science, education, and outreach, offers unique benefits to address socio-ecological questions and problems, and thus may offer novel opportunities to support the complex mission of public land managers. Here, we use a case study of an iNaturalist program, the Tribal Nations Botanical Research Collaborative (TNBRC), to examine the use of citizen science programs in public land management. The TNBRC collected 2030 observations of 34 plant species across the project area, while offering learning opportunities for participants. Using occurrence data, we examined observational trends through time and identified five species with 50 or fewer digital observations to investigate as species of possible conservation concern. We compared predictive outcomes of habitat suitability models built using citizen science data and Forest Inventory and Analysis (FIA) data. Models exhibited high agreement, identifying the same underlying predictors of species occurrence and, 95% of the time, identifying the same pixels as suitable habitat. Actions such as staff training on data use and interpretation could enhance integration of citizen science in Federal land management.

scholarly journals Abundant Citizen Science Data Reveal That the Peacock Butterfly Aglais io Recently Became Bivoltine in Belgium

Insects ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 683
Author(s):  
Marc Herremans ◽  
Karin Gielen ◽  
Jos Van Kerckhoven ◽  
Pieter Vanormelingen ◽  
Wim Veraghtert ◽  
...  
Keyword(s):  
Citizen Science ◽  
Western Europe ◽  
Environmental Changes ◽  
Early Summer ◽  
Science Data ◽  
The Public ◽  
Online Portal ◽  
Spring Generation ◽  
Reproductive Cycles ◽  
New Generation

The peacock butterfly is abundant and widespread in Europe. It is generally believed to be univoltine (one generation per year): adults born in summer overwinter and reappear again in spring to reproduce. However, recent flight patterns in western Europe mostly show three peaks during the year: a first one in spring (overwintering butterflies), a second one in early summer (offspring of the spring generation), and a third one in autumn. It was thus far unclear whether this autumn flight peak was a second new generation or consisted of butterflies flying again in autumn after a summer rest (aestivation). The life cycle of one of Europe’s most common butterflies is therefore still surprisingly inadequately understood. We used hundreds of thousands of observations and thousands of pictures submitted by naturalists from the public to the online portal observation.orgin Belgium and analyzed relations between flight patterns, condition (wear), reproductive cycles, peak abundances, and phenology to clarify the current life history. We demonstrate that peacocks have shifted towards two new generations per year in recent decades. Mass citizen science data in online portals has become increasingly important in tracking the response of biodiversity to rapid environmental changes such as climate change.

scholarly journals Satellite-Based Personal UV Dose Estimation

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 268
Author(s):  
Todd C. Harris ◽  
Laurent Vuilleumier ◽  
Claudine Backes ◽  
Athanasios Nenes ◽  
David Vernez
Keyword(s):  
Measurement Errors ◽  
Low Cost ◽  
Public Health Research ◽  
Mobile App ◽  
Population Exposure ◽  
Dose Estimation ◽  
Annual Dose ◽  
Significant Step ◽  
Uv Dose ◽  
Dosimetry Measurement

Epidemiology and public health research relating to solar ultraviolet (UV) exposure usually relies on dosimetry to measure UV doses received by individuals. However, measurement errors affect each dosimetry measurement by unknown amounts, complicating the analysis of such measurements and their relationship to the underlying population exposure and the associated health outcomes. This paper presents a new approach to estimate UV doses without the use of dosimeters. By combining new satellite-derived UV data to account for environmental factors and simulation-based exposure ratio (ER) modelling to account for individual factors, we are able to estimate doses for specific exposure periods. This is a significant step forward for alternative dosimetry techniques which have previously been limited to annual dose estimation. We compare our dose estimates with dosimeter measurements from skiers and builders in Switzerland. The dosimetry measurements are expected to be slightly below the true doses due to a variety of dosimeter-related measurement errors, mostly explaining why our estimates are greater than or equal to the corresponding dosimetry measurements. Our approach holds much promise as a low-cost way to either complement or substitute traditional dosimetry. It can be applied in a research context, but is also fundamentally well-suited to be used as the basis for a dose-estimating mobile app that does not require an external device.

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