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Expert judgment underpins assessment of threatened ecosystems. However, experts are often narrowly defined, and variability in their judgments may be substantial. Models built from structured elicitation with large diverse expert panels can contribute to more consistent and transparent decision-making. We conducted a structured elicitation under a broad definition of expertise to examine variation in judgments of ecosystem viability and collapse in a critically endangered ecosystem. We explored whether variation in judgments among 83 experts was related to affiliation and management expertise and assessed performance of an average model based on common ecosystem indicators. There were systematic differences among individuals, much of which were not explained by affiliation or expertise. However, of the individuals affiliated with government, those in conservation and environmental departments were more likely to determine a patch was viable than those in agriculture and rural land management. Classification errors from an average model, in which all individuals were weighted equally, were highest among government agriculture experts (27%) and lowest among government conservation experts (12%). Differences were mostly cases in which the average model predicted a patch was viable but the individual thought it was not. These differences arose primarily for areas that were grazed or cleared of mature trees. These areas are often the target of restoration, but they are also valuable for agriculture. These results highlight the potential for conflicting advice and disagreement about policies and actions for conserving and restoring threatened ecosystems. Although adoption of an average model can improve consistency of ecosystem assessment, it can fail to capture and convey diverse opinions held by experts. Structured elicitation and models of ecosystem viability play an important role in providing data-driven evidence of where differences arise among experts to support engagement and discussion among stakeholders and decision makers and to improve the management of threatened ecosystems.
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http://dx.doi.org/10.1111/cobi.14370 | DOI Listing |
J Relig Health
September 2025
Department of Midwifery, Faculty of Health Sciences, Agri Ibrahim Cecen University, Agri, Turkey.
This study aims to examine the effect of education interventions given to women with religious orientation on cervical cancer and Pap smear test health beliefs.The study used a quasi-experimental research design with the pre-test-post-test control group. It was conducted in Qur'an courses in a province in eastern Turkey between January and October 2023.
View Article and Find Full Text PDFAnal Chem
September 2025
Department of Applied Chemistry, Faculty of Science and Technology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary.
In this Article, we present a novel data analysis method for the determination of copolymer composition from low-resolution mass spectra, such as those recorded in the linear mode of time-of-flight (TOF) mass analyzers. Our approach significantly extends the accessible molecular weight range, enabling reliable copolymer composition analysis even in the higher mass regions. At low resolution, the overlapping mass peaks in the higher mass range hinder a comprehensive characterization of the copolymers.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
Key Laboratory of Micro-nano Sensing and IoT of Wenzhou, Wenzhou Institute of Hangzhou Dianzi University, Wenzhou 325038, China.
Transcription factors (TFs) are essential proteins that regulate gene expression by specifically binding to transcription factor binding sites (TFBSs) within DNA sequences. Their ability to precisely control the transcription process is crucial for understanding gene regulatory networks, uncovering disease mechanisms, and designing synthetic biology tools. Accurate TFBS prediction, therefore, holds significant importance in advancing these areas of research.
View Article and Find Full Text PDFAm J Ind Med
September 2025
National Institute for Occupational Safety and Health, Division of Field Studies and Engineering, Cincinnati, Ohio, USA.
Background: Workers in industry settings are often exposed to complex noise, which poses a greater risk to hearing loss than continuous noise at equivalent energy levels. Previous studies have identified kurtosis as an essential metric for evaluating complex noise-induced hearing loss (NIHL). This study aimed to characterize the distribution of workers exposed to complex noise, examine the associations between kurtosis and changes in hearing thresholds at various frequencies, and explore kurtosis's role in estimating NIHL and its integration into occupational hearing loss prevention programs.
View Article and Find Full Text PDFComput Methods Biomech Biomed Engin
September 2025
International School of Microelectronics, Dongguan University of Technology, Dongguan, China.
Many traditional classification networks directly use the limb two-lead signal (MLII) ECG signals as input for training. However, this method suffers from reduced accuracy when ECG features are not obvious, especially for premature heartbeats. To solve the issue, this paper proposed a novel network, namely CDLR-Net, that combines a Deep Residual Shrinkage Network (DRSN) with a Long Short-Term Memory (LSTM).
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