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Marine protected areas (MPAs) are effective tools for preserving marine organisms and ecosystems against the background of climate change and intense human activities. Community participation is a helpful management approach for MPAs and has received substantial attention from researchers worldwide. To identify the research status of the field of community participation in MPAs, we reviewed 391 papers from the Web of Science with bibliometric methods and VOSviewer. The results showed that the number of publications continued to grow from 1994 to 2022, with the USA producing the most publications followed by Australia. Environmental science was the major thematic area. Studies have concentrated on community-based marine resource management, the participation mode of communities, and participatory planning and monitoring. In addition, we summarized the experience and lessons of community participation to illustrate the role of community involvement in constructing and managing MPAs. Finally, the outlook for future research was presented based on the analysis above. We recommend promoting cross-disciplinary cooperation and combining quantitative and qualitative methods to support this research. Meanwhile, it is critical to further study the specific path of community participation and fully utilize local knowledge to supplement scientific data. The current study provided an overview of publication characteristics, research trends, and primary research methods in studies of community participation in MPAs. The results will help to find ways to mitigate conflicts between MPAs and communities. We hope that our study promotes their coordinated and sustainable development and contributes to marine biodiversity conservation and human well-being. [ABSTRACT FROM AUTHOR]

Existing red tide detection methods have mainly been developed for ocean color satellite data with low spatial resolution and high spectral resolution. Higher spatial resolution satellite images are required for red tides with fine scale and scattered distribution. However, red tide detection methods for ocean color satellite data cannot be directly applied to medium–high spatial resolution satellite data owing to the shortage of red tide responsive bands. Therefore, a new red tide detection method for medium–high spatial resolution satellite data is required. This study proposes the red tide detection U−Net (RDU−Net) model by considering the HY−1D Coastal Zone Imager (HY−1D CZI) as an example. RDU−Net employs the channel attention model to derive the inter−channel relationship of red tide information in order to reduce the influence of the marine environment on red tide detection. Moreover, the boundary and binary cross entropy (BBCE) loss function, which incorporates the boundary loss, is used to obtain clear and accurate red tide boundaries. In addition, a multi−feature dataset including the HY−1D CZI radiance and Normalized Difference Vegetation Index (NDVI) is employed to enhance the spectral difference between red tides and seawater and thus improve the accuracy of red tide detection. Experimental results show that RDU−Net can detect red tides accurately without a precedent threshold. Precision and Recall of 87.47% and 86.62%, respectively, are achieved, while the F1−score and Kappa are 0.87. Compared with the existing method, the F1−score is improved by 0.07–0.21. Furthermore, the proposed method can detect red tides accurately even under interference from clouds and fog, and it shows good performance in the case of red tide edges and scattered distribution areas. Moreover, it shows good applicability and can be successfully applied to other satellite data with high spatial resolution and large bandwidth, such as GF−1 Wide Field of View 2 (WFV2) images. [ABSTRACT FROM AUTHOR]