Valuing the Natural Capital of Sea Areas Based on Emergy Analysis

Abstract

Marine natural capital is an important component of natural capital yields goods and service flows benefiting the human being. The emergy analysis method allows one to account for mass, energy and money flows in an ecosystem, providing technical support for assessing its broader value regarding our economic dependence. Thus, we used this method to evaluate the natural capital of the Zhoushan archipelago sea area from 2011 to 2016 and proposed a formula to estimate the marine organism’s transformity. The average total emergy of our study area was 6.93 × 10²² sej and emdollar was about 9.20 billion yuan, which is equivalent to 9.3% of the average regional GDP of 98.5 billion during the same period. The Zhoushan archipelago sea area has high emergy density (ED) and low emergy self-sufficiency ratio (ESR), which shows low input–output efficiency for local use. In addition, the high purchased emergy (PR), high emergy exchange ratio (EER) and low renewable resources emergy ratio (%R) imply an increasing dependence on the outside social and economic inputs. Overall, Zhoushan sea area was in an early but steady state of development. The results can serve as a benchmark for policy making and implementation to achieve local sustainable development. As a tool for emergy-based sea area capital assessment, the model is of great significance for quantifying the ecosystem service value and accounting for marine/land natural capital value.

1. Introduction

Marine natural capital comprises marine ecosystem elements that directly or indirectly create value for people, including environmental inputs (e.g., renewable resources), human-driven ecosystem service (ES) flows, and external environmental support resulting from human labor, services, and capital [1,2,3]. In the context of global natural resources depletion and environment degradation, natural capital accounting is critical to support conservation strategies ensuring continued ES supply into the future and the ecological, social, and economic sustainable development [4,5,6,7]. The ocean accounts for more than 70% of the Earth’s area and is an important part of natural capital. Various international policies, including the United Nations Convention on the Law of the Sea (UNCLOS) and the Convention on Biological Diversity (CBD), have paid much importance to marine natural capital. Emergy analysis (EA) is one of the key methods to evaluate natural capital. In the last decades, it has been widely applied in the valuation of terrestrial and costal ecosystems [8,9,10,11,12,13,14]. Some scholars have realized the spatialization of emergy-based natural capital assessment by combining it with geospatial information technology [5,15,16,17,18].

Emergy analysis theory was formulated in 1980s by H.T. Odum [19,20]. Emergy is the total amount of solar available energy consumed in direct or indirect conversions required to create a product or service, and measured in sej (solar emergy joules) [21]. From a donor perspective, emergy accounting as an environmental accounting method can measure the cumulative environmental support for a process, that is, the biophysical value of natural capital components [22,23]. Transformity is a ratio of emergy required to make something to the energy of the product or service. By using transfromity, we can convert every kind of energy mass or flows to solar emergy [24]. From an energy point of view, the greater the emergy of the system, the higher the energy consumed in the formation process. Compared to the other commonly known methods for natural capital accounting, e.g., ecosystem services valuation and ecological footprint, EA focuses on natural resources themselves and converts various types of the flows of energy and matter stored in the ecosystem into emergy values of the same standard. Additionally, emergy theory is also used in conjunction with other commonly known methods [25,26,27]. Recently, the natural capital evaluation of Marine Protected Areas (MPAs), based on biophysical and nutritional dynamics accounting models, has become a research point of interest [28,29,30]. However, due to the complexity, openness, fluidity, and homogeneity of the marine environment [31], there still exist challenges in completing the assessment methods of natural capital in the sea area [32,33,34,35]. Under the background of high ocean development intensity [36], there is no scientific pre-accounting system of natural capital in the Chinese sea area, which will lead to greater subjectivity in marine resource development decisions. Here, we therefore apply the emergy theory to estimate marine natural capital in Zhoushan sea area (eastern China) as the demonstration area. Furthermore, people used species as one indicator to estimate the emergy of marine organisms, but ignored the trophic level. For example, the tropical level is high in hairtail (Trichiurus lepturus) and low in algae and if they are considered as a whole, the results would be largely affected. To address the problem, we propose a method to estimate the emergy of marine organisms based on the tropical levels and law of energy flows. Our research case can provide a reference for the sea area natural capital evaluation system, thereby guiding the rational development marine economy under the national marine strategy.

2. Materials and Methods

2.1. Study Site

The Zhoushan Archipelago is China’s largest archipelago, located in the eastern part of Zhejiang Province (29°32′ N–31°04′ N, 121°30′ E–123°25′ E, Figure 1), facing the East China Sea and adjacent to the Yangtze River Estuary. It is composed of 1390 islands with a total area of 22,200 km² [37], of which the sea area accounts for about 94% (20,800 km²). Zhoushan City has jurisdiction over 2 municipal districts (Dinghai District, Putuo District), 2 counties (Daishan County, Shengsi County). To the west of Zhoushan lies the Yangtze River delta with large and medium-sized cities such as Shanghai, Hangzhou, Ningbo, and to the east of it is the vast Pacific Ocean. Thus, it works as an important maritime portal for inland cities along the river and the Yangtze River Delta.

Zhoushan’s fishing ground, known as the “East Sea Fish Tank”, enjoys a high reputation in the country and even the world. It is China’s largest seafood production, processing, and sales base. In addition, the winding coastline of Zhoushan makes it have many natural deep-water harbors, and its Ningbo-Zhoushan Port has the highest cargo throughput in the world [38]. A series of ocean economic development strategies were put forward by government, including the Zhoushan Archipelago New Area, the Zhejiang Zhoushan Islands New District Development Plan, and the China (Zhejiang) Pilot Free Trade Zone, in order to anchor the River–Sea Intermodal Transport strategy, expand opening up, and enhance the role of ports in supporting the economy [39].

2.2. Emergy Anlaysis Method

The emergy flows model was drawn with Odum’s energy systems language [40] after referring to the experience of early researchers [41] and considering the reality of Zhoushan sea area. Figure 2 contains the main components of the system (renewable resources, material input and economic output of human society, and system output) and the energy and currency flows relationships between the components, which helped to have a global understanding of the research objects.

These related flows were categorized into renewable resources (R, such as sun, wind, rain chemical, rain potential, wave, tides, runoff chemical, phosphate, and inorganic nitrogen of upwelling), imported emergy (I, such as fishing vessel fuel, labor, service & capital), and output emergy (O, such as net primary production, marine aquaculture products and marine fishing products). The following step was converting the collected raw data into solar emergy by multiplication by the transformity (generally derived from published papers).

2.2.1. Renewable Resources (R)

In terms of basic natural resources such as wind energy, the energy calculation formulas were mostly derived from the earliest works of the emergy theory [22,42,43,44]. Since the study area was the sea area, the average altitude of rainwater was 0; thus, the rain potential was also 0. We also referred to some of the improvements proposed by later scholars [33], then took the evaporation factor into consideration and changed the rainfall to net rainfall. The calculation of nutrients quality in the upwelling was meant to obtain its total flux. However, there were some points we need to consider. First, the total mass of PO₄³⁻ and inorganic nitrogen was readily calculated from nutrient flux and the maximum concentration limits are 0.1–6.5 μm/L for nitrate and 0.12–0.55 μm/L for phosphate when they used nutrients [45]. In addition, the average content of inorganic nitrogen in Zhoushan Fishing Ground was 0.593 mg/L, and that of phosphate was 0.028 mg/L [46]. Based on the ratio of actual concentration to maximum concentration limit, we estimated the utilization ratios of phytoplankton to upwelling nutrients: 8.2% for inorganic nitrogen and 100% for phosphate.

2.2.2. Imported Emergy (I)

The imported emergy included the materials, services and funds imported by the research object from the outside world, whose proportion usually represented the extent to which the region was dependent on the outside world. In this study, labor had a direct transformity to calculate its emergy, and capital was converted into the form of emergy via emergy/money ratio [47]. The fishing vessel energy consumption (F) was calculated according to the following formula:

$${\mathit{F}=\mathrm{VP} \times \mathit{h} \times \mathit{C} \times \mathrm{CV}}_{\mathrm{F}}$$

(1)

where VP is vessel total power, h is the operating hours, C is fuel consumption per kW·h, and ${\mathrm{CV}}_{\mathrm{F}}$ is fuel calorific value. The fishing vessel operating hours were estimated to be 300 days a year and 4 h a day [48]. Then, F was converted to solar emergy by using its transformity.

2.2.3. Output Emergy (O)

Simply put, the output emergy was the output of a system. For a sea area, the system’s output was mainly net primary production and various types of seafood.

The formula for calculating net primary production was as follows:

$$\mathrm{NPP}=\mathit{P} \times \mathit{S} \times \mathit{Y}$$

(2)

where NPP refers to net primary production, P refers to production per unit area per unit time, S refers to sea area, Y refers to one year. Among them, P came from a satellite remote sensing calculation [49]; due to the data inaccessibility, we used the average annual level of P. Through multiplying transformity, we obtained the emergy of NPP.

The energy of marine aquaculture and fishing products is obtained by the calorie per unit mass from the website (http://fitness.39.net/food (accessed on 17 August 2020). Here, we referred to Belgrano et al. (2005) [50] to construct the information flows diagram of the marine food web. Then, we proposed a method to estimate the transformities based on the tropical level of different marine species and law of energy flows.

First, according to the basic principles of the ecosystem food chain [51], the energy fixed by each tropical level is:

$${\mathit{N}}_{n\mathrm{+}\mathrm{1} }={ \mathit{N}}_{\mathrm{1}} · {(E_L)}^{\mathit{n}}$$

(3)

where N_n+1 is the energy of n + 1 tropical level, N₁ is the energy obtained by primary producers, $E_L$ is Lindeman’s efficiency, and n is the number of tropical level transfers.

Assuming a 10% Lindeman efficiency, the secondary production of the n tropical level is:

$$N_n=N_1·{0.1}^{n-1}$$

(4)

The solar emergy is the same for all paths in the whole system; the transformity of one component (T_n) is defined as the solar emergy (E) flowing into the component divided by the energy it obtained (${\mathit{N}}_{\mathit{n}})$ [52]:

$${\mathit{T}}_{\mathit{n}}=\frac{\mathit{E}}{{\mathit{N}}_{\mathit{n}}}$$

(5)

$${\mathit{E}=\mathit{N}}_{1 }·{ \mathit{T}}_1$$

(6)

where T₁ is the transformity of the primary producer, which can be easily calculated by dividing the annual average emergy flows per square meter by the annual average primary production per square meter:

Based on the above Formulas (4)–(6), the transformity of a component can be simplified as follows:

$${\mathit{T}}_{\mathit{n}}{=\mathit{T}}_1{ \times 10}^{\mathit{n}-1}$$

(7)

It is easier to use the tropical level to estimate the transformities of various aquatic products according to the above formula. Most of the tropical level used in this paper was from research on the tropical level of the East China Sea catch [53], and a small part was from the Fishbase website (http://www.fishbase.org/search.php (accessed on 17 December 2020).

Table 1. Transformities of the products of marine aquaculture and marine fishing.

Item		Tropical Level	Transformity
Marine Aquaculture Products
1	Kelp (Laminaria japonica)	1 a	4.86 × 104
2	Nori (Porphyra spp.)	1 a	4.86 × 104
3	Chinese shrimp (Penaeus orientalis)	2.1 b	6.12 × 105
4	Razor clam (Sinonovacula constricta)	2.5 a	1.54 × 106
5	Mussel (Mytilus edulis)	2.5 a	1.54 × 106
6	Clam	2.5 a	1.54 × 106
7	Spiral shell	2.5 a	1.54 × 106
Marine fishing products
1	Algae	1 a	4.86 × 104
2	Crabs	2.1 b	6.12 × 105
3	Shrimps	2.1 b	6.12 × 105
4	Butterfish (Stromateidae)	2.3 b	9.70 × 105
5	Long-finned herring (Ilisha elongata)	2.4 b	1.22 × 106
6	Jerk filefish (Navodon septentrionalis)	2.4 b	1.22 × 106
7	Shellfish& Cephalopoda	2.5 b	1.54 × 106
8	Small yellow croaker (Pseudosciaena polyatis)	2.7 b	2.44 × 106
9	Large yellow croaker (Pseudosciaena crocea)	3.1 b	6.12 × 106
10	Mackerel and scad (Scombridae, Carangidae)	3.2 b	7.70 × 106
11	Spanish mackerel (Scomberomorus niphonius)	3.8 b	3.07 × 107
12	Hairtail (Trichiurus lepturus )	3.9 b	3.86 × 107

^a fishbase website, http://www.fishbase.org/search.php (accessed on 17 December 2020). ^b Chao et al. (2005) [53].

details the transformity for each aquatic product.

2.2.4. Data Collection

The statistical data we investigated and collected include physical datasets (renewable resources), meteorological conditions, and economic indicators related to the study area. Most of the data used in this paper come from the Zhoushan Statistical Yearbook [54], as well as some of Zhoushan’s administrative department’s annual report, such as the Zhoushan Water Resources Bulletin [55], and a little from published papers [45,46,56]. Runoff data were available only for 2014, so we replaced the remaining year data with that one. After collecting data, we need to classify them for subsequent emergy calculation. The transformity we used is based on the $9.44 \times 1024$ sej/a global emergy baseline, and all related reference sources were shown in Appendix A.

2.2.5. Emergy Indicators

A series of emergy indicators (

Table 2. Emergy indices of sea area eco-economic system.

Emergy Indices	Expression
Emergy source index
Emergy self-sufficiency ratio (ESR)	ESR = (R + N)/U
Purchased emergy ratio (PR)	PR = I/U
Social subsystem evaluation index
Emergy density (ED)	ED = U/Area
Economic subsystem evaluation index
Emergy/money ratio (EMR)	EMR = U/(GOP)
Emergy exchange ratio (EER)	EER = I/O
Renewable resources emergy ratio (%R)	RER = R/U
Emdollar	Emergy/(Emergy/money ratio)
Emdollar per area	U/Area of the research place

R: Renewable resources; N: Non-renewable resources; U: Total emergy; I: Imported emergy; O: Output emergy; GOP: Gross Ocean Product.

) can be derived from the emergy analysis of the marine eco-economic system, which comprehensively reflect the relationship between environment and economy, and between man and nature.

The total emergy (U) is the sum of renewable resources (R), non-renewable resources (N) and imported emergy (I), which represents the ‘‘total wealth’’ of the system and is the raw material of the entire sea area ‘‘factory’’. In contrast, the output emergy (O) is the ‘‘product’’ of the entire system. Emergy source indexes include Emergy Self-sufficiency Ratio (ESR) and Purchased Emergy Ratio (PER). The ESR is the ratio of R and N input of the sea to U. It can be used to describe the degree of external communication and economic development of a country or region. PER is the ratio of I from the outside to U, which indicates the degree of dependence on external resources. The trading partner that receives more emergy will receive greater real wealth, and therefore, greater economic stimulation due to the trade.

Emergy density (ED) belongs to the social subsystem evaluation index, which is the ratio of U to the area of the place. Renewable resources emergy ratio (RER) is the ratio of R to the U and belongs to the natural subsystem evaluation index, which can represent the potential of the natural environment.

The economic subsystem evaluation index contains the Emergy/Money ratio (EMR), Emergy Exchange Ratio (EER), Renewable resources emergy ratio (%R), emdollar, and emdollar per area. The EMR of the sea area is obtained by dividing the total ermergy of the sea area by its Gross Ocean Product (GOP) [57]. Through dividing the emergy of such a product or service by EMR, we can make the value of the item better understood by people, especially decision makers. EER, also known as the emergy benefit ratio, refers to the ratio of I to O%. R represents the proportion of renewable energy value in total emergy. Emdollar is the measure of the money that circulates in an economy as the result of some process. In practice, to obtain the emdollar value of the sea area, the emergy is multiplied by the ratio of total emergy to GOP.

3. Result and Discussion

3.1. Emergy Evaluation of Zhoushan Sea Area

The dynamic changes of emergy flows composed of renewable resources, imported emergy, and output emergy between 2011 and 2016, are shown in

Table 3. The emergy evaluation of Zhoushan sea area during 2011~2016.

Item		Solar Emergy (Sej)
		2011	2012	2013	2014	2015	2016
Renewable resources (R)
1	Sun	9.05 × 1019
2	Wind	4.27 × 1020
3	Rain chemical	−7.39 × 1020	6.57 × 1020	−9.99 × 1020	9.50 × 1020	1.20 × 1021	1.12 × 1021
4	Wave	1.40 × 1020
5	Tides	4.44 × 1019
6	Runoff chemical	6.60 × 1019
7	Phosphate (upwelling)	1.21 × 1022
8	Inorganic nitrogen (upwelling)	2.37 × 1021
Imported emergy (I)
9	Fishing vessel fuel	2.58 × 1021	2.77 × 1021	2.82 × 1021	2.88 × 1021	2.89 × 1021	2.96 × 1021
10	Labor (Fishing)	8.14 × 1020	8.32 × 1020	8.04 × 1020	7.84 × 1020	7.56 × 1020	7.77 × 1020
11	Labor (Aquaculture)	7.43 × 1019	6.56 × 1019	6.24 × 1019	5.74 × 1019	5.78 × 1019	5.75 × 1019
12	Service &Capital (Fishing)	4.46 × 1022	4.61 × 1022	4.82 × 1022	5.01 × 1022	4.99 × 1022	5.03 × 1022
13	Service &Capital (Aquaculture)	1.13 × 1021	1.29 × 1021	1.84 × 1021	1.79 × 1021	2.08 × 1021	2.78 × 1021
Output emergy (O)
14	Net primary production	9.56 × 1021	9.50 × 1021	9.56 × 1021	9.92 × 1021	9.68 × 1021	9.74 × 1021
15	Marine aquaculture products	2.73 × 1020	3.53 × 1020	3.72 × 1020	3.95 × 1020	4.42 × 1020	5.60 × 1020
16	Marine fishing products	3.50 × 1022	3.40 × 1022	3.38 × 1022	3.12 × 1022	3.28 × 1022	3.48 × 1022
	Sea food (sum15–16)	3.53 × 1022	3.44 × 1022	3.42 × 1022	3.16 × 1022	3.33 × 1022	3.54 × 1022
Total renewable resources		1.45 × 1022	1.59 × 1022	1.42 × 1022	1.62 × 1022	1.64 × 1022	1.63 × 1022
Total imported emergy		4.92 × 1022	5.10 × 1022	5.37 × 1022	5.56 × 1022	5.57 × 1022	5.68 × 1022
Total output emergy		4.49 × 1022	4.39 × 1022	4.38 × 1022	4.15 × 1022	4.30 × 1022	4.51 × 1022
Total emergy (U) (sun 1–13)		6.37 × 1022	6.69 × 1022	6.79 × 1022	7.18 × 1022	7.21 × 1022	7.31 × 1022

. With the rapid economic development of Zhoushan, it has been China’s largest seafood production, processing, and sales base. Thus, the imported emergy and output emergy played a more important role in this system, which were, respectively, about 3.4 and 2.8 times that of the renewable resources emergy (1.56 × 10²² sej per year). The nutrients carried by the upwelling were dominant in renewable emergy flows, accounting for over 80% every year, which reflected the upwelling’s importance for the Zhoushan fishing ground. As a coastal island, Zhoushan has abundant wind and wave energy resources, the contribution of which was between 3% and 4%. In addition, the rain chemical emergy accounted for ±7%, which was unexpected because the evaporation in some years would be greater than the precipitation. What is more, as shown in Table 3, the annual change of local renewable resources was caused by rain chemical ermergy, which showed an overall growth trend.

Compared with renewable resources, imported emergy (I) showed a steady growth trend, from 4.92 × 10²² sej (2011) to 5.68 × 10²² sej (2016), with an average annual growth rate of 2.91%. The increase of imported emergy largely contributed to that of the total emergy from the initial 6.37 × 10²² sej to 7.32 × 10²² sej in 2016 (Figure 3). In imported ermergy, the capital and service investment for marine fishing was the most important source, accounting for about 90%, followed by the fuel consumption of fishing boats (5%). It showed that the emphasis on fisheries was rising and the investment in fisheries was continuously strengthened. As a conventional pillar industry of Zhoushan, the fishery has received huge capital and service inputs to ensure stable output.

The output emergy is composed of net primary production and sea food. Unlike the stable increase in the total emergy, it decreased first and increased later in the six-year duration. The figures for 2011 and 2016 were basically the same (4.50 × 10²² sej), while the lowest value appeared in 2014 (4.15 × 10²² sej). Food is a very important gift from the sea, accounting for about 78%. However, sea food overharvesting has developed into a contagious resource exploitation model due to high global connectivity, advanced technology, and large market demand [58]. As we can see, the output of sea food has declined by 10.55% between 2011 and 2014, while in 2015, it increased significantly. In general, the fishery output in the Zhoushan sea area was basically maintained at a stable level.

3.2. Changes of Marine Aquaculture and Fishing Product

As we can see in

Table 4. The emergy flows of sea food in Zhoushan sea area (2011~2016).

Item		Solar Emergy (Sej)						Proportion in Sea Food (Mean)
		2011	2012	2013	2014	2015	2016
Marine aquaculture prodeucts								1.17%
1	Kelp	2.23 × 1016	2.58 × 1016	3.47 × 1016	3.02 × 1016	4.86 × 1016	3.61 × 1016	0.00%
2	Nori	6.17 × 1015	6.24 × 1015	6.03 × 1015	3.41 × 1015	3.05 × 1015	8.37 × 1015	0.00%
3	Chinese shrimp	8.64 × 1018	1.08 × 1019	1.06 × 1019	1.09 × 1019	1.17 × 1019	1.60 × 1019	0.03%
4	Razor clam	3.12 × 1019	2.72 × 1019	2.93 × 1019	2.96 × 1019	2.76 × 1019	2.94 × 1019	0.09%
5	Mussel	1.93 × 1020	2.78 × 1020	3.00 × 1020	3.24 × 1020	3.75 × 1020	4.75 × 1020	0.95%
6	Clam	3.58 × 1019	3.34 × 1019	2.95 × 1019	2.83 × 1019	2.51 × 1019	3.48 × 1019	0.09%
7	Spiral shell	4.13 × 1018	3.11 × 1018	2.48 × 1018	3.01 × 1018	2.52 × 1018	4.18 × 1018	0.01%
Marine fishing prodeucts								98.83%
1	Algae	5.86 × 1016	6.89 × 1016	1.04 × 1017	1.03 × 1017	1.13 × 1017	1.04 × 1017	0.00%
2	Crabs	2.36 × 1020	2.62 × 1020	3.47 × 1020	5.15 × 1020	4.48 × 1020	4.23 × 1020	1.10%
3	Shrimps	4.54 × 1020	5.09 × 1020	5.02 × 1020	4.61 × 1020	5.06 × 1020	4.99 × 1020	1.44%
4	Butterfish	1.55 × 1020	1.35 × 1020	9.42 × 1019	7.60 × 1019	8.76 × 1019	1.20 × 1020	0.33%
5	Long-finned herring	1.94 × 1018	3.17 × 1018	2.65 × 1018	2.72 × 1018	1.35 × 1019	2.38 × 1019	0.02%
6	Jerk filefish	8.62 × 1018	5.02 × 1018	3.81 × 1018	7.01 × 1018	3.31 × 1018	3.20 × 1018	0.02%
7	Shellfish& Cephalopoda	1.49 × 1021	1.74 × 1021	1.84 × 1021	2.37 × 1021	2.74 × 1021	3.11 × 1021	6.54%
8	Small yellow croaker	5.86 × 1020	5.35 × 1020	4.66 × 1020	5.29 × 1020	5.64 × 1020	5.41 × 1020	1.58%
9	Large yellow croaker	6.41 × 1018	9.84 × 1018	9.94 × 1018	1.28 × 1019	1.55 × 1019	1.84 × 1019	0.04%
10	Mackerel and scad	7.42 × 1021	5.88 × 1021	4.76 × 1021	3.96 × 1021	3.10 × 1021	3.68 × 1021	14.05%
11	Spanish mackerel	7.42 × 1020	8.86 × 1020	9.96 × 1020	1.05 × 1021	1.30 × 1021	1.56 × 1021	3.21%
12	hairtail	2.39 × 1022	2.41 × 1022	2.48 × 1022	2.22 × 1022	2.41 × 1022	2.48 × 1022	70.51%

, the hairtail (Trichiurus lepturus) has become the main emergy contribution item to sea food relying on its large production and high transformity, accounting for about 70.51%. The hairtail, large yellow croaker, small yellow croaker, and cuttlefish used to be the four major marine economic fishes in China, but currently, only the hairtail flood has survived, which was caused by overfishing and environmental pollution in the coastal marine ecosystem. Mackerel and scad was another outstanding indicator, but its proportion has dropped from 21% in 2011 to 10.41% in 2016, showing a significant change. In contrast, the emergy of shellfish and cephalopoda has increased from 4.23% in 2011 to 8.80% in 2016. The contributions of remaining aquaculture products were small, about 1.17% every year. According to the statistical data of the Zhoushan Statistical Yearbook [54], mussel, clam, razor clam, and Chinese shrimp were the main species of marine aquaculture in the Zhoushan Archipelago. The scale of mussel aquaculture has doubled largely in the past 10 years [59], and it is clear that mussel production was the highest.

We built an empirical formula for the emergy evaluation of marine organisms in order to accurately quantify the intrinsic value of the marine ecosystem [60]. The formula was mainly composed of three parts, namely, the transformity of the primary producer, nutritional level, and Lindeman’s efficiency. Due to the lack of relevant data and research on energy flows transfer efficiency between nutrient levels, food chain feedback mechanism, etc., we took the 10% Lindeman efficiency, which has been widely used in the aquatic ecosystem. Likewise, we used the tropical levels gathered from published paper, which may have been impacted by the anthropogenic factor, climate change, and ecosystem structure shifts [61].

However, the marine food web is complex and dynamic, and the applicability of Lindeman’s efficiency and the nutritional level of the species need to be further considered [62]. The nutritional position of marine species in the food web was initially determined by body size and gastric content analysis [63], then the carbon and nitrogen stable isotope analysis method provided a new method to estimate. At present, the isotope analysis method is widely used in land, salt marsh wetland, estuary, bay, offshore and ocean ecosystem food web, and nutrition niche changes. With the development of DNA sequencing technology, the DNA barcode method [64] has also been applied to the analysis of the diet of marine organisms. Comprehensive research methods and the reasonable marine food web model can be used to better understand the nutritional level relationship and energy flows inherent in the coastal ecosystem.

3.3. Emergy Indices of Zhoushan Sea Area

Table 5. Emergy indices of Zhoushan sea area during 2011~2016.

Item	Unit	2011	2012	2013	2014	2015	2016
ESR	%	22.71	23.71	20.91	22.52	22.76	22.32
PR	%	77.29	76.29	79.09	77.48	77.24	77.68
%R	%	22.71	23.71	20.91	22.52	22.76	22.32
EER	%	109.71	116.34	122.74	133.88	129.67	125.98
EMR	sej/yuan	7.52 × 1012
ED	sej/m2	3.06 × 1012	3.22 × 1012	3.27 × 1012	3.45 × 1012	3.47 × 1012	3.52 × 1012
Emdollar value	yuan	8.46 × 109	8.89 × 109	9.03 × 109	9.53 × 109	9.58 × 109	9.72 × 109
Emdollar valueper area	yuan/m2	0.41	0.43	0.43	0.46	0.46	0.47

ESR: Emergy self-sufficiency ratio; PR: Purchased emergy ratio; %R: Renewable resources emergy ratio; EER: Emergy exchange ratio; EMR: Emergy/money ratio; ED: Emergy density.

shows in detail the emergy indices of the Zhoushan sea area from 2011 to 2016 that can more intuitively explain the economic development status of the region. Emergy self-sufficiency ratio (ESR) was basically maintained at about 22%, which reflects the support ability of the local natural environment. Since there were no non-renewable resources locally, ESR mainly depends on renewable resources. Correspondingly, purchased emergy ration (PR) was up to around 78%. Thus, we came to a conclusion that the sea area was highly dependent on the outside world, in other words, the stable emergy output of Zhoushan sea area was mainly maintained by the investment of external capital and services. Renewable resources emergy ratio (%R) was about 22% and tended to decline, which indicated that the current utilization of sustainable resources in the Zhoushan sea area was inadequate. It is worth mentioning that renewable resources usage has been put on the agenda; two modules of the marine tidal energy generator with installed capacity of 3.4 MW were successfully operated in the southern part of Zhoushan in 2016. This was a step-by-step attempt to develop clean ocean energy and demonstrated the Zhoushan government’s determination to develop renewable resources. Emergy exchange ratio (EER) was greater than 100%, which was used to evaluate the gains and losses of regional exchanges. The emergy of the region was in a relatively enriched state and it had an advantage in the exchange of emergy. In addition, the index first increased and then declined in six years, but overall, it was in a growing trend. The emergy/money ratio (EMR) is a very important parameter in the emergy analysis theory, which links natural and socio-economic systems. Due to the lack of statistics on Zhoushan’s Gross Ocean Product, we used the EMR (7.52 × 10¹² sej/yuan) calculated by other scholars [47]. Then, we could obtain the emdollar value, which has grown year by year, from 8.46 billion yuan in 2011 to 9.72 billion yuan in 2016. In addition, the mean emdollar value per unit area was 0.44 yuan/m². Emergy density (ED) is the density and intensity of the area’s emergy. Since the sea area was constant, the trend of the ED was consistent with the total emergy, increasing steadily. These all indicated that the economy has developed in these years and was in a stable statue.

3.4. Comparison of Emergy Analysis in Different Sea Area

The scientific community has been confused with different geobiosphere emergy baselines (GEBs) and how to compare evaluations using different baselines reasonably [1]. To solve such problems, we unified the GEB to 9.44 × 10²⁴ sej/yr by conversion factors. Thus, the factor of 0.79 can be used to convert the results of Egadi Islands MPA (Marine Protected Area) [29], which were based on the 1.20 × 10²⁵ sej/yr emergy baseline. As can be seen in

Table 6. Comparison of the accounting of marine natural capital from relative studies based on emergy-based indices.

Location	Method	Total Emergy (sej)	ED (sej/m2)	EMR (sej/yuan)	Emdollar Value per Area (Yuan/m2)	References
Zhoushan	EA	6.93 × 1022	3.33 × 1012	7.52 × 1012	0.44	Current study (average)
Southern Italy		3.13 × 1019	6.24 × 1011	2.69 × 1011	2.32	Franzese et al. (2008) [34]
Egadi Islands MPA		8.85 × 1020	1.64 × 1012	1.31 × 1011	12.52	Picone et al. (2017) [29]
Zhejiang	ES based on EA	5.76 × 1022	2.21 × 1011	5.96 × 1011	0.37	Sun et al. (2018) [67]
Zhoushan		4.37 × 1022	2.10 × 1012	1.86 × 1012	1.13	Zhao et al. (2015) [65]
Wanshan		2.00 × 1022	6.25 × 1012	1.74 × 1012	3.60	Qin et al. (2015) [68]
Shandong		1.99 × 1024	1.25 × 1013	2.83 × 1012	4.41	Di et al. (2015) [57]

EMR: Emergy/money ratio; ED: Emergy density.

, on the one hand, in terms of emergy density (ED), the Zhoushan sea area ranked third among these studies. On the other hand, the emdollar per area of Zhoushan sea area (0.44 yuan/m²) was lower, but higher than that of the Zhejiang sea area (0.37 yuan/m²) and global marine ecosystem services market value per square meter [4]. This was caused by a high emergy/money ratio, indicating our research site was at a low-level development. Obviously, our evaluation results were different from Zhao et al. (2015) [65], which can be explained by differences in methods. Zhao et al. (2015) [65] linked emergy theory with ecosystem services, and they used the emergy/money ratio of China in 2004 [66]. Based on the data and method, we thought their assessment could not really reflect the Zhoushan sea area’s natural capital.

Most marine ecosystems are over-exploited, poorly managed, and vulnerable to climate change impacts in the world, so in-depth assessment is required [69]. Many scholars have carried out studies on the value of marine ecosystems or marine natural capital, both in terms of definition interpretation and methods improvement. Ecosystem services (ES) evaluate ecosystem value based on anthropocentric perspectives; thus, ecosystem service value only reflects human preference [70]. Then, the emergy-based ecosystem service method was proposed to improve the existing problems [57,65,67,68], but different scholars have different choices of types of marine ecosystem services. The subjectivity of the selection of service categories makes the evaluation results unable to reflect the real situation of the system accurately. Furthermore, they lack the market price of some ecosystem services or are not consist with the true value [71]. From the perspective of nature, the donor-side emergy analysis (EA) theory can objectively and truly reflect the value of each component in the ecosystem framework. Despite EA being based on a more scientific and objective theory, and its evaluation procedure being understandable and operable, the uncertainty problem of transformity (namely, unit emergy value), causing confusion in calculations and comparison, cannot be ignored [72]. Consequently, scientists need to make efforts in this regard and draw up more standardized framework guidelines on emergy baseline, the selection of transformity, and other uncertainty solutions.

4. Conclusions

The evaluation of marine natural capital is one of the hotspots of cross-disciplinary research in the natural sciences and social sciences in recent years. We evaluated the natural capital of the Zhoushan sea ecosystem using emergy theory, which is based on a natural point of view and makes up for the deficiency of traditional evaluation methods. We also innovatively calculated the transformities of marine organisms based on the marine food chain to accurately quantify biological natural capital. The average total emergy value of the Zhoushan sea area in six years was 6.93 × 10²² sej, maintaining a steady growth trend. In addition, the emergy exchange ratio was greater than 100%, which showed that the resources in the region were in a state of surplus every year. The region was in an evolving state and the amount of resources invested was increasing. However, the Zhoushan sea area had a low renewable resources emergy ratio, which was not conducive to regional sustainable development. In comparison with other sea areas, the Zhoushan sea area was at the primary development stage [36]. Due to a high emergy/money ratio, the emdollar per area of Zhoushan sea area was the lowest. Green development is the eternal theme, and local government needs to grasp the opportunity to rationally set the future development direction, to implement ecosystem-based marine management to increase the utilization level of the sea area in a stable and efficient manner.

According to the tropical levels and transformity of marine aquaculture and marine fishing, China can adjust the proportion of different economic species to optimize the structure of artificial fishery. In addition to maintaining the output value of hairtail, ecological restoration and yield increase of other economic species should also be emphasized. Chinese fishery operators need to consider the combination of mussel, clam, Chinese shrimp, and other mutually beneficial ecosystems, so as to improve resource utilization and economic efficiency. Furthermore, the Zhoushan Archipelago can develop the regional characteristic processing and service industry according to the regional differences in the emergy of mariculture and fishery products, promote the construction of the secondary and tertiary industries by increasing the added value of aquatic products, and improve the total output emergy.

From 2011 to 2016, the great dependence of Zhoushan on the input of emergy and the low renewable resources emergy ratio can become the resistance factors of Zhoushan’s future development. Therefore, Zhoushan is recommended to focus more on supporting local renewable energy enterprises and promoting the development of the marine service industry and high-tech industry, increasing the source of output emergy, optimizing and improving the emergy flows model of the marine ecosystem.

It is challenging to apply emergy analysis theory to assess marine natural capital [28,30]. Although we have carried out a systematic evaluation of the Zhoushan sea area, there still exist some problems to be solved. First of all, the emergy flows model needs to be further improved. In terms of the input and output flows, some indicators such as the heat exchange via ocean currents will be taken into consideration [65]. Second, due to the lack of data, some indicators can only use historical averages or values for a certain year, such as net primary production and nutrient flux. Data substitution will more or less affect the accuracy of the final result. Finally, the formula’s wide application relied on the thorough study of energy flows efficiency and tropical levels in marine food web [62,64]. Our research demonstrates the application potential of emergy-based evaluation of natural capital in the sea area. In the future, on the basis of considering the availability of data, all relevant flows in the marine ecosystem should be included in the indicator framework to ensure the integrity of the system’s emergy flows analysis; on the other hand, cross-validation work on case studies of emergy-based sea area capital assessments can be carried out. Through the horizontal comparison of natural capital of several near-shore ecosystems, the sea area emergy analysis model and evaluation method will be continuously improved in practice. This article shows the prototype of a rapid emergy assessment system of sea ecosystems in the whole of China, and will improve it in subsequent research.