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The health status assessment of marine benthic ecosystems, as an important basis for maintaining the ecological balance of the oceans, relies on the long-term dynamic monitoring of benthic communities. In this study, we systematically reviewed the history and current applications of ecological assessment indices developed based on benthic organisms, including the perspectives of future fields in marine ecosystem health assessment. Traditional biological indices—including biodiversity indices (Shannon-Wiener index, Pielou index, etc.), functional group analyses (feeding evenness index), and indices (AMBI, M-AMBI, BENTIX index, etc.) based on the proportion of pollution-tolerant/sensitive species have advanced ecosystem health assessment by quantifying the responses of community structure to environmental stressors and facilitating the shift from qualitative to quantitative assessments. Nevertheless, traditional methods are limited by cumbersome procedures for morphological characterization, the limitations of single indicators, and regional differences in applicability. In recent years, environmental DNA (eDNA) technology has made up for the shortcomings of traditional methods by rapidly obtaining biodiversity information through high-throughput sequencing, and has derived novel indices such as gAMBI, which validates its complementarity with morphological methods. Integration of Artificial Intelligence (AI) techniques such as machine learning algorithms (Random Forests, Convolutional Neural Networks, and so on) with statistical analysis has improved the ability of ecosystem assessment models to resolve nonlinear relationships and multiple stressors. Meanwhile, automatic and intelligent image recognition technology offers the possibility of accurate and rapid identification of macrofauna and their monitoring. Future research shall integrate multidimensional data and interdisciplinary techniques to construct a more universal and dynamically responsive assessment system to cope with the potential impacts of global climate change and human activities on marine ecosystems.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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