Ecosystem Health Assessment in the Pearl River Estuary of China by Considering Ecosystem Coordination

Abstract

Marine ecosystem is a complex nonlinear system. However, ecosystem health assessment conventionally builds on a linear superposition of changes in ecosystem components and probably fails to evaluate nonlinear interactions among various components. To better reflect the intrinsic interactions and their impacts on ecosystem health, an ecosystem coordination index, defined as the matching level of ecosystem structure/services, is proposed and incorporated into the ecosystem health index for a systematic diagnosis in the Pearl River Estuary, China. The analysis results show that the ecosystem health index over the last three decades decreased from 0.91 to 0.50, indicating deteriorating from healthy to unhealthy status. The health index is 3–16% lower than that calculated using the common method without considering ecosystem coordination. Ecosystem health degradation in the Pearl River Estuary manifested as significant decreases in structure/services and somewhat mismatching among them. Overall, the introduction of coordination in ecosystem health assessment could improve the understanding of the mechanism of marine ecosystem change and facilitate effective restoration of ecosystem health.

The world's second largest population of humpback dolphins in the waters of Zhanjiang deserves the highest conservation priority

“…Most Grade IV and greater than Grade IV waters are concentrated in the Pearl River Estuary, with inorganic nitrogen and active phosphate being the main pollutants 16 . An ecosystem health assessment in the Pearl River Estuary shows that the ecosystem health index (EHI) over the last three decades has decreased from 0.91 to 0.50, indicating deterioration from healthy to unhealthy status 17 . Although a small portion of Leizhou Bay is lightly polluted by oil and inorganic nitrogen, the rest of Leizhou Bay is within Grade I or II of the National Seawater Quality Standards for China.…”

Marine Ranching Construction and Management in East China Sea: Programs for Sustainable Fishery and Aquaculture

“…For marine ranching management, the choice to assess marine resources and their environments using quantified and habitat factors is ideal when creating appropriate ecosystem-based models and obtaining a wide range of information simultaneously via real-time monitoring and long-range data communication. Generally, real-time monitoring data-such as sea surface (or bottom) temperature, chlorophyll-a (chl-a), harmful algae abundance, sea surface height, nutrient salt, salinity, dissolved oxygen, and turbidity-are closely correlated with the enhancement of fishery resources, the evaluation of a real-time-monitoring-based ecosystem health index (EHI), and the development of automatic data processing [139,140]. Amongst the different methods available for real-time monitoring in the ECS (e.g., remote sensing, Argo global observation networks, aquaculture platform monitoring systems), each method has its own advantages and scale.…”

Uncertainties Brought by Weight Assignment in Ecosystem Health Modelling

“…There are other objective mehods, such as artificial neural networks [13], principal component analysis [19] and knowledge granularity [21] employed to determine the weight of indicators in the modelling of ecosystem health. Limited by the data, these methods were not covered in this research.…”

“…Entropy method [7,8], variation coefficient method [9], mean square error method [10] and Critic method [11,12] are four objective methods which were often employed to determine the indicator weight in researches of ecosystem health modelling. Some researchers deemed that the weight assigned by objective method could reflect the real relationship between different ecological elements [13]. However, some researchers put forward the opinion that the weight assigned by objective method was greatly influenced by the data and it cannot represent the relative importance of specific indicator [14].…”