Embracing local knowledge is vital to conserve and manage biodiversity, yet frameworks to do so are lacking. We need to understand which, and how many knowledge holders are needed to ensure that management recommendations arising from local knowledge are not skewed towards the most vocal individuals. Here, we apply a Wisdom of Crowds framework to a data-poor recreational catch-and-release fishery, where individuals interact with natural resources in different ways. We aimed to test whether estimates of fishing quality from diverse groups (multiple ages and years of experience), were better than estimates provided by homogenous groups and whether thresholds exist for the number of individuals needed to capture estimates. We found that diversity matters; by using random subsampling combined with saturation principles, we determine that targeting 31% of the survey sample size captured 75% of unique responses. Estimates from small diverse subsets of this size outperformed most estimates from homogenous groups; sufficiently diverse small crowds are just as effective as large crowds in estimating ecological state. We advocate for more diverse knowledge holders in local knowledge research and application.
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http://dx.doi.org/10.1038/s41598-024-84970-4 | DOI Listing |
Mucosal Immunol
January 2025
CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 101408, China. Electronic address:
Mucosal tissues, including those in the respiratory and gastrointestinal tracts, are critical barrier surfaces for pathogen invasion. Infections at these sites not only trigger local immune response, but also recruit immune cells from other tissues. Emerging evidence in mouse models and human samples indicate that the immune crosstalk between lung and gut critically impact and determine the course of respiratory disease.
View Article and Find Full Text PDFCell Commun Signal
January 2025
Centre of Postgraduate Medical Education, Centre of Translation Research, Department of Biochemistry and Molecular Biology, ul. Marymoncka 99/103, Warsaw, 01-813, Poland.
Background: Renal cell cancer (RCC) is the most common and highly malignant subtype of kidney cancer. Mesenchymal stromal cells (MSCs) are components of tumor microenvironment (TME) that influence RCC progression. The impact of RCC-secreted small non-coding RNAs (sncRNAs) on TME is largely underexplored.
View Article and Find Full Text PDFBMC Public Health
January 2025
Public Policy, Management, and Analytics, College of Urban Planning and Public Affairs, University of Illinois at Chicago, Chicago, IL, 60607, USA.
Background: Despite multiple years of government HIV educational efforts, the growing trend of new cases among women in Indonesia runs parallel with their seemingly overall lack of comprehensive knowledge about HIV. A major prevention challenge for the Indonesian government lies in delivering HIV prevention education across the world's largest archipelago. This study investigates comprehensive HIV knowledge among reproductive-age women in Southwest Sumba, Indonesia, and the sources through which they report having learned about HIV along with potential mediators of the relationship between socioeconomic status (SES) and HIV knowledge.
View Article and Find Full Text PDFBMC Med Educ
January 2025
School of Nursing, Xiangnan University, 889 Chenzhou Avenue, Suxian District, Chenzhou, 423000, Hunan, People's Republic of China.
Background: In the backdrop of the ongoing global digital revolution in education, the digital literacy of teachers stands out as a pivotal determinant within the educational milieu. This study aims to explore the current status and associated factors of digital literacy among academic nurse educators.
Methods: A cross-sectional design study utilizing an online questionnaire platform (Wenjuanxing) to collect data from August to October 2023.
Surg Endosc
January 2025
Surgery Department, Meander Medical Centre, Maatweg, Amersfoort, 3818 TZ, Utrecht, The Netherlands.
Background: Specific pelvic bone dimensions have been identified as predictors of total mesorectal excision (TME) difficulty and outcomes. However, manual measurement of these dimensions (pelvimetry) is labor intensive and thus, anatomic criteria are not included in the pre-operative difficulty assessment. In this work, we propose an automated workflow for pelvimetry based on pre-operative magnetic resonance imaging (MRI) volumes.
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