scholarly journals Assessing the Value of a Citizen Science Approach for Ctenophore Identification

2021 ◽  
Vol 8 ◽  
Author(s):  
Ellie Johansen ◽  
Nicole Aberle ◽  
Mari-Ann Østensen ◽  
Sanna Majaneva

During the era of biodiversity loss, a complete species census and understanding where the different species occur is of high priority. Even though this knowledge has increased tremendously, mainly with expanded use of integrated taxonomic identification, there are groups where our knowledge is very limited, both in terms of diversity and distribution. Ctenophores are such a group. Due to a lack of identification literature, damage to specimens during net sampling and sample processing, difficulties with preservation and a considerably undescribed diversity within the phylum, this group is often hard to work with. A citizen science approach was applied during a mapping campaign on ctenophore diversity along the Norwegian coast in order to have a broad geographical coverage. This was achieved by a collaboration with five diving clubs along a south-north geographical gradient that were briefly introduced to ctenophore taxonomy and ecology and sampling techniques using Whatman® FTA® Cards. The data collected by the participating divers gave a broad spatial coverage and provided information on ctenophore diversity in these regions. The use of FTA® Cards in the sampling allowed successful species and genus level identification using DNA barcodes. However, small obstacles such as accurate morphological species identification and labor-intensive issues were identified that can impede the use of large-scale citizen science approaches to map ctenophore diversity and thus recommendations for future implications that address these issues are proposed here.

2020 ◽  
Vol 12 (5) ◽  
pp. 1835
Author(s):  
Anja Schmitz ◽  
Bettina Tonn ◽  
Ann-Kathrin Schöppner ◽  
Johannes Isselstein

Engaging farmers as citizen scientists may be a cost-efficient way to answering applied research questions aimed at more sustainable land use. We used a citizen science approach with German horse farmers with a dual goal. Firstly, we tested the practicability of this approach for answering ‘real-life’ questions in variable agricultural land-use systems. Secondly, we were interested in the knowledge it can provide about locomotion of horses on pasture and the management factors influencing this behaviour. Out of 165 volunteers, we selected 40 participants to record locomotion of two horses on pasture and provide information on their horse husbandry and pasture management. We obtained complete records for three recording days per horse from 28 participants, resulting in a dataset on more individual horses than any other Global Positioning System study published in the last 30 years. Time spent walking was greatest for horses kept in box-stall stables, and walking distance decreased with increasing grazing time. This suggests that restrictions in pasture access may increase stress on grass swards through running and trampling, severely challenging sustainable pasture management. Our study, involving simple technology, clear instructions and rigorous quality assessment, demonstrates the potential of citizen science actively involving land managers in agricultural research.


Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2328
Author(s):  
Mohammed Alzubaidi ◽  
Kazi N. Hasan ◽  
Lasantha Meegahapola ◽  
Mir Toufikur Rahman

This paper presents a comparative analysis of six sampling techniques to identify an efficient and accurate sampling technique to be applied to probabilistic voltage stability assessment in large-scale power systems. In this study, six different sampling techniques are investigated and compared to each other in terms of their accuracy and efficiency, including Monte Carlo (MC), three versions of Quasi-Monte Carlo (QMC), i.e., Sobol, Halton, and Latin Hypercube, Markov Chain MC (MCMC), and importance sampling (IS) technique, to evaluate their suitability for application with probabilistic voltage stability analysis in large-scale uncertain power systems. The coefficient of determination (R2) and root mean square error (RMSE) are calculated to measure the accuracy and the efficiency of the sampling techniques compared to each other. All the six sampling techniques provide more than 99% accuracy by producing a large number of wind speed random samples (8760 samples). In terms of efficiency, on the other hand, the three versions of QMC are the most efficient sampling techniques, providing more than 96% accuracy with only a small number of generated samples (150 samples) compared to other techniques.


Diversity ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 255
Author(s):  
Diana L. Soteropoulos ◽  
Caitlin R. De Bellis ◽  
Theo Witsell

Biodiversity data support conservation research and inform conservation decisions addressing the wicked problem of biodiversity loss. However, these data often need processing and compilation before use, which exceed the time availability of professional scientists. Nevertheless, scientists can recruit, train, and support a network of citizen scientists to prepare these data using online platforms. Here, we describe three citizen science projects sponsored by the Arkansas Natural Heritage Commission to transcribe and georeference historic herbarium specimens and document current biodiversity through iNaturalist for two highly biodiverse and rapidly developing counties in Northwest Arkansas, USA. Citizen science-generated data will be used in a county natural heritage inventory (CNHI) report, including a comprehensive list of taxa tied to voucher specimens and records for rare plant populations. Since the CNHI project started in 2018, citizen scientists have transcribed 8,855 and georeferenced 2,636 specimen records. From iNaturalist observations, 125 rare plant populations of 39 taxa have been documented. This CNHI report will determine the most critical taxa, habitats, and sites for conservation action in the region and will inform conservation stakeholders at the local, state, and federal levels as they engage in land acquisition, ecological restoration, natural resource management, planning of growth and development, and environmental review/regulation.


2021 ◽  
Author(s):  
Pedro M. Martin‐Sanchez ◽  
Eva‐Lena F. Estensmo ◽  
Luis N. Morgado ◽  
Sundy Maurice ◽  
Ingeborg B. Engh ◽  
...  

2018 ◽  
Vol 48 (4) ◽  
pp. 564-588 ◽  
Author(s):  
Dick Kasperowski ◽  
Thomas Hillman

In the past decade, some areas of science have begun turning to masses of online volunteers through open calls for generating and classifying very large sets of data. The purpose of this study is to investigate the epistemic culture of a large-scale online citizen science project, the Galaxy Zoo, that turns to volunteers for the classification of images of galaxies. For this task, we chose to apply the concepts of programs and antiprograms to examine the ‘essential tensions’ that arise in relation to the mobilizing values of a citizen science project and the epistemic subjects and cultures that are enacted by its volunteers. Our premise is that these tensions reveal central features of the epistemic subjects and distributed cognition of epistemic cultures in these large-scale citizen science projects.


PLoS ONE ◽  
2018 ◽  
Vol 13 (8) ◽  
pp. e0202077
Author(s):  
Christopher Kullenberg ◽  
Frauke Rohden ◽  
Anders Björkvall ◽  
Fredrik Brounéus ◽  
Anders Avellan-Hultman ◽  
...  

2018 ◽  
Vol 14 (8) ◽  
pp. 1229-1252 ◽  
Author(s):  
Carlye D. Peterson ◽  
Lorraine E. Lisiecki

Abstract. We present a compilation of 127 time series δ13C records from Cibicides wuellerstorfi spanning the last deglaciation (20–6 ka) which is well-suited for reconstructing large-scale carbon cycle changes, especially for comparison with isotope-enabled carbon cycle models. The age models for the δ13C records are derived from regional planktic radiocarbon compilations (Stern and Lisiecki, 2014). The δ13C records were stacked in nine different regions and then combined using volume-weighted averages to create intermediate, deep, and global δ13C stacks. These benthic δ13C stacks are used to reconstruct changes in the size of the terrestrial biosphere and deep ocean carbon storage. The timing of change in global mean δ13C is interpreted to indicate terrestrial biosphere expansion from 19–6 ka. The δ13C gradient between the intermediate and deep ocean, which we interpret as a proxy for deep ocean carbon storage, matches the pattern of atmospheric CO2 change observed in ice core records. The presence of signals associated with the terrestrial biosphere and atmospheric CO2 indicates that the compiled δ13C records have sufficient spatial coverage and time resolution to accurately reconstruct large-scale carbon cycle changes during the glacial termination.


PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259670
Author(s):  
Albertas Dvirnas ◽  
Callum Stewart ◽  
Vilhelm Müller ◽  
Santosh Kumar Bikkarolla ◽  
Karolin Frykholm ◽  
...  

Large-scale genomic alterations play an important role in disease, gene expression, and chromosome evolution. Optical DNA mapping (ODM), commonly categorized into sparsely-labelled ODM and densely-labelled ODM, provides sequence-specific continuous intensity profiles (DNA barcodes) along single DNA molecules and is a technique well-suited for detecting such alterations. For sparsely-labelled barcodes, the possibility to detect large genomic alterations has been investigated extensively, while densely-labelled barcodes have not received as much attention. In this work, we introduce HMMSV, a hidden Markov model (HMM) based algorithm for detecting structural variations (SVs) directly in densely-labelled barcodes without access to sequence information. We evaluate our approach using simulated data-sets with 5 different types of SVs, and combinations thereof, and demonstrate that the method reaches a true positive rate greater than 80% for randomly generated barcodes with single variations of size 25 kilobases (kb). Increasing the length of the SV further leads to larger true positive rates. For a real data-set with experimental barcodes on bacterial plasmids, we successfully detect matching barcode pairs and SVs without any particular assumption of the types of SVs present. Instead, our method effectively goes through all possible combinations of SVs. Since ODM works on length scales typically not reachable with other techniques, our methodology is a promising tool for identifying arbitrary combinations of genomic alterations.


2016 ◽  
Author(s):  
Dominik Paprotny ◽  
Oswaldo Morales Nápoles

Abstract. Large-scale hydrological modelling of flood hazard requires adequate extreme discharge data. Models based on physics are applied alongside those utilizing only statistical analysis. The former requires enormous computation power, while the latter are most limited in accuracy and spatial coverage. In this paper we introduce an alternate, statistical approach based on Bayesian Networks (BN), a graphical model for dependent random variables. We use a non-parametric BN to describe the joint distribution of extreme discharges in European rivers and variables describing the geographical characteristics of their catchments. Data on annual maxima of daily discharges from more than 1800 river gauge stations were collected, together with information on terrain, land use and climate of catchments that drain to those locations. The (conditional) correlations between the variables are modelled through copulas, with the dependency structure defined in the network. The results show that using this method, mean annual maxima and return periods of discharges could be estimated with an accuracy similar to existing studies using physical models for Europe, and better than a comparable global statistical method. Performance of the model varies slightly between regions of Europe, but is consistent between different time periods, and is not affected by a split-sample validation. The BN was applied to a large domain covering all sizes of rivers in the continent, both for present and future climate, showing large variation in influence of climate change on river discharges, as well as large differences between emission scenarios. The method could be used to provide quick estimates of extreme discharges at any location for the purpose of obtaining input information for hydraulic modelling.


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