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7 results for “Expert elicitation”
Responses from an expert elicitation of lynx viability and persistence in the continental United States
<p>The data and code provided here is associated with an October 13-15 Lnyx expert elicitation workshop that assessed the viability and persistence of lynx in the continental United States. The expert elicitation captured the knowledge, professional judgments, and opinions of lynx experts to assess the status of, and the drivers influencing, these lynx populations. We elicited the likelihood and level of uncertainty regarding future persistence over several time frames (at years 2025, 2050, and 2100). This data was used to inform the species status assessment and providing scientific information to the United States Fish and Wildlife Service used to complete the November 2017 5-year Endangered Species Act status review which recommended that the lynx DPS be removed from the list of threatened and endangered species.</p>
A global expert elicitation on present-day human-fire interactions: data & analysis code
<p>These files support "A global expert elicitation on present-day human-fire interactions", accepted for publication in the Philosophical Transactions of the Royal Society B. doi: <span>10.1098/rstb.2023-0463</span></p> <p>The files contain data from a survey of experts on human-fire interactions as well as code used to process and analyse it.</p> <p>An overview of the files is given below. </p> <h2><strong>1) Data</strong></h2> <p>Raw survey data are provided by geographic region ("GFUS_region"). Data processed to produce analyses in the associated paper are provided as "GFUS_Processed".</p> <p>Columns in data files are named by the question of the survey that generated them (Q1b through Q90). The contents of the associated questions that were asked are given in the data_dictionary.xlsx file.</p> <p>- GFUS_spatial provides the data merged with a shapefile of the survey regions. </p> <p>- "Gov_compare" and "LIFE_SH_fire" provide files to compare survey data with the DAFI and LIFE literature meta-analyses (see Supplementary 3 to the main text).</p> <p>- Question meta-data and question-summary provides an overview of the questions, as well as a topline overview of the numbers of responses and internal coherence (entropy) of survey responses. </p> <h2>2) Code</h2> <p>4 scripts are provided. </p> <p>- Firstly the script that was used to summarise survey responses by geographic region (Summarise_by_region)<br>- Secondly the code used to conduct statistical tests presented in the paper<br>- Thirdly the code used to produce plots in the paper<br>- Fourthly the code used to produce topline descriptive statistics presented in the paper</p>
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>
Responses from an expert elicitation of lynx viability and persistence in the continental United States
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Fishing effort data, fishing fleet segmentation, and statistical details used in the expert knowledge elicitation experiment
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Data from: Group elicitations yield more consistent, yet more uncertain experts in understanding risks to ecosystem services in New Zealand bays
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Interview data for 'Risks in the offshore wind supply chain and tendering process impacts: Insights from industry expert elicitations'
<p>Updated 3 category labels to reduce potential for confusion. (v3)</p> <p>Interview data with restored functionality of some unused data analysis methods. (v2)</p> <p>Original upload. (v1)</p>
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