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There is a significant disconnection between the richness of data and the effectiveness of decision-making in current marine observation practices. This study argues that the root cause lies in the “ontological” bias and “methodological” mismatch in the logic that guides observation design. We first examine the “uniformity assumption” that views the ocean as a spatially homogeneous and temporally gradual system. Based on the “land-sea heterogeneity isomorphism” framework, we demonstrate that the ocean is essentially a heterogeneous landscape dominated by key dynamic processes, characterized by “resource-rich areas”, “risk-concentrated areas”, and “pulsatile events” that drive their changes. These local, transient, and nonlinear threshold processes often dominate the function and evolution of coastal and estuarine ecosystems. Traditional “mission-oriented” or “undifferentiated census” observations, which ignore this essence, lead to systematic omissions of core processes and key risk signals. Based on this, we propose a fundamental shift in the marine science observation paradigm: from “routine observation-driven alone” to “a combination of routine observation and scientific questions/management goal-driven”. We construct a logical framework of “scientific questions/management goals-key processes-observation requirements”, and systematically expound on three methodological breakthroughs to address the “fluid medium” characteristics of the ocean: building a “dynamic adaptive perception network” to replace fixed grids, establishing “full-chain process analysis” to replace isolated hypothesis testing, and achieving an intelligent closed loop of “real-time assimilation and predictive decision-making”. This study aims to provide a comprehensive theoretical pathway from ontological cognition to methodological practice to build the next generation of “precise, efficient, and applicable” marine science observation systems.
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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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