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Citizen science has recently emerged as a powerful tool for wildlife monitoring and conservation efforts, offering cost-effective, large-scale data collection that supports traditional scientific research methods. This study explores the integration of citizen science into wildlife monitoring, citizen science data applications, and challenges that could be faced while giving insights into future directions. Citizen-generated dataincluding observational, environmental, geospatial, acoustic, photographic, and genetic informationcontribute to population estimations, health and biodiversity assessments, and threat detection. Moreover, the fusion of advanced technologies including mobile applications, web platforms, remote sensing, and artificial intelligence has significantly improved data quality, citizen engagement, and geographical coverage. However, challenges persist, including concerns about data accuracy, long-term participant engagement, and technical knowledge gaps. Addressing these issues through user-friendly technologies and robust training programs is crucial for maximizing the potential of citizen science in wildlife conservation. As global biodiversity faces increasing threats from climate change and deforestation, citizen science offers a vital solution for wildlife monitoring and protection, fostering stronger connections between humans and nature while supporting evidence-based conservation efforts.
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Moussa et al. (2024) studied this question.
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