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13 results for “expert knowledge”
A map selection of wigeon stopover sites (core areas) based on wetland expert knowledge
<p>Stopover areas (core areas only) along the migration route of wigeons tracked with GPS transmitters were selected when they exhibited forests on more than 50% of their total surface or had less than 50% cover by water and/or wetland on the ESA’s global land cover map. We created a sample of 5,630 regions of interest (3,403 for training and 2,227 for validation), delineated with polygons assigned to land classes listed in the Table 1. We used archives of Google Earth, ESRI, and BING satellites for the photointerpretation of the land classes as described in Table 1. The classification was performed with a Sentinel-2 MultiSpectral Instrument, Level-2A image collection in Google Earth Engine (GEE) through the R-package Rgee to create a batch process applying the GEE Random forest classifier to each selected core home range. The cloudless (maximum 3%) images were selected within the period from 01/06/2021 to 30/09/2021. The optimal number of trees was estimated at 100 for an out of bag error of 14%. The overall accuracy on the validation sample was 82 %. </p>
Global knowledge and use of soil biodiversity: Results of an expert survey
<p>A global survey on soil biodiversity (see file Global Biodiversity Survey.pdf provided as an attachment) was conducted over a three-week period in March 2022 by the Global Soil Partnership (GSP) of the Food and Agriculture Organization (FAO) of the United Nations, as part of the activities of the International Network on Soil Biodiversity (NETSOB). The survey intended to obtain information on the current status of knowledge and use of soil organisms worldwide, i.e., to identify who is doing what, where, and how, as well as the main gaps, pitfalls, and opportunities across existing national initiatives and research.</p> <p>The survey included 122 questions that characterized the work undertaken by experts regarding microbes, fauna, and their activity in soils, community & functional assessments, inventories, mapping and monitoring activities, ecosystem services, applications, and threats to soil biodiversity, education, and communication activities, as well as public policies related to soil biodiversity. The online survey was created using the software Survey Monkey v. 11 and was sent out to over 70 thousand e-mail addresses with a link to complete the survey. </p> <p>Over 2,600 responses were received, representing >1,350 institutions from 135 countries, mainly from experts active in research and academia. The number of respondents was not equal for all questions, as the survey guided the respondents to different parts, depending on their replies.</p> <p>The 122 questions and the replies of the respondents are presented as separate tabs in the attached Excel file (Results survey for Zenodo.xlsx). The respondents and their identities, as well as their e-mails and any personal websites were removed in the current file to maintain anonymity. Institutional websites were maintained as long as they did not identify the respondent(s) directly. </p> <p>A detailed written description of the survey results was prepared as a manuscript for a special issue of the journal Soil Organisms, volume 97 (Brown et al., 2025). The survey was prepared by a team of scientists from the Brazilian Corporation for Agricultural Research (Embrapa) and collaborating institutions, with assistance from the board of the International Network on Soil Biodiversity (NETSOB), and with funding provided by the FAO. The work was further supported by the Fundação de Apoio a Pesquisa e Desenvolvimento Agropecuário Edmundo Gastal (FAPEG), Brazil, a grant of CNPq (Processo No. 312824/2022-0) to GGB, and of the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant program (# 05901–2019) to ZL, who was also supported by Western University.</p>
Data from: Use of opportunistic sightings and expert knowledge to predict and compare Whooping Crane stopover habitat
Predicting a species' distribution can be helpful for evaluating management actions such as critical habitat designations under the U.S. Endangered Species Act or habitat acquisition and rehabilitation. Whooping Cranes (Grus americana) are one of the rarest birds in the world, and conservation and management of habitat is required to ensure their survival. We developed a species distribution model (SDM) that could be used to inform habitat management actions for Whooping Cranes within the state of Nebraska (U.S.A.). We collated 407 opportunistic Whooping Crane group records reported from 1988 to 2012. Most records of Whooping Cranes were contributed by the public; therefore, developing an SDM that accounted for sampling bias was essential because observations at some migration stopover locations may be under represented. An auxiliary data set, required to explore the influence of sampling bias, was derived with expert elicitation. Using our SDM, we compared an intensively managed area in the Central Platte River Valley with the Niobrara National Scenic River in northern Nebraska. Our results suggest, during the peak of migration, Whooping Crane abundance was 262.2 (90% CI 40.2−3144.2) times higher per unit area in the Central Platte River Valley relative to the Niobrara National Scenic River. Although we compared only 2 areas, our model could be used to evaluate any region within the state of Nebraska. Furthermore, our expert-informed modeling approach could be applied to opportunistic presence-only data when sampling bias is a concern and expert knowledge is available.
Fishing effort data, fishing fleet segmentation, and statistical details used in the expert knowledge elicitation experiment
<p><span>Based on an explorative</span> <span>but rigorous elicitation framework, we obtained the bycatch fishing probability</span> <span>at the fishing fleet segment level using expert estimates. Based on the knowledge of three scientific experts, we developed a new and creative structured method for smart and fast fishery-related risk assessments for </span><span>species of high conservation concern. In order to test the method here propose, we applied it to 76 cartilaginous</span><span> fish</span><span> species </span><span>(</span><span>included in the IUCN Red Lists) and on five different fishing segments at both Italian and Mediterranean scale. The method produced qualitative results specific to the threat posed by fishing for each species and each segment with information between and within the segments. Based on the interpretation of resilience-disturbance interactions developed for ecological systems, the quantitative results provided reliable cumulative metrics, measuring the extinction risk due to fishing and the response to overfishing for the species considered. Additionally, the results highlight that the method performs best on a small geographic scale. Therefore, the application of this new method on other subregional</span> <span>or local scales where very few data are available (e.g. fishing effort) could be a valuable tool for the preliminary assessment for species of conservation concern. In fact, despite the absence of detailed catch data at local geographic scales, the flexibility of this method could help to highlight potential fishery-related conservation problems and thus redirect conservation strategies for threatened marine species such as many sharks and rays species.</span></p>
Fishing effort data, fishing fleet segmentation, and statistical details used in the expert knowledge elicitation experiment
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Data from: Habitat mapping of coastal wetlands using expert knowledge and Earth observation data
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Data from: Use of opportunistic sightings and expert knowledge to predict and compare Whooping Crane stopover habitat
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Supplementary material 1 from: Dehnen-Schmutz K, Pescott OL, Booy O, Walker KJ (2022) Integrating expert knowledge at regional and national scales improves impact assessments of non-native species. NeoBiota 77: 79-100. https://doi.org/10.3897/neobiota.77.89448
Survey and Tables S1–S3
Supplementary material 3 from: Dehnen-Schmutz K, Pescott OL, Booy O, Walker KJ (2022) Integrating expert knowledge at regional and national scales improves impact assessments of non-native species. NeoBiota 77: 79-100. https://doi.org/10.3897/neobiota.77.89448
Figure S1
Supplementary material 2 from: Dehnen-Schmutz K, Pescott OL, Booy O, Walker KJ (2022) Integrating expert knowledge at regional and national scales improves impact assessments of non-native species. NeoBiota 77: 79-100. https://doi.org/10.3897/neobiota.77.89448
Table S2
References to expert knowledge in Google Android, Google Search (Shopping) and Google Search (AdSense) decisions
<p>The dataset includes references to expert knowledge identified in Google Android, Google Search (Shopping), and Google Search (AdSense) decisions issued by the Commission. It is divided into types of sources invoked in the decisions (to what type of source they refer).</p>
Obstetrics and Gynecology Residents and Experts' Knowledge of, Attitudes Toward, Practice Behaviors, and Self-confidence Levels of Caring for Lesbian, Bisexual, and Transgender (LBT+) Patients in Turk
ClinicalTrials.gov study NCT05699434. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality
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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.