Changes in trophic flows and ecosystem properties of the Beibu Gulf ecosystem before and after the collapse of fish stocks

Ocean & Coastal Management 54 (2011) 601e611

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Ocean & Coastal Management journal homepage: www.elsevier.com/locate/ocecoaman

Changes in trophic flows and ecosystem properties of the Beibu Gulf ecosystem before and after the collapse of fish stocks Zuozhi Chen*, Yongsong Qiu, Shannan Xu South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China

a r t i c l e i n f o

a b s t r a c t

Article history: Available online 13 June 2011

Mass-balance models (Ecopath) of the ecosystem before and after collapse (1959e1961 and 1997e1999) of fish stocks were developed with Ecopath software to compare the differences in ecosystem structure, functioning and ecosystem properties of the Beibu Gulf. The model includes 20 functional groups consisting of commercial important fish groups and other ecologically important groups in the ecosystem such as zooplankton, phytoplankton, and detritus. Results indicated that biomass and catches of the system have changed drastically between the 1960s and 1990s, especially for the high trophic levels (TL). The biomass of level V in the early 1960s was 32 times higher than that of the late 1990s, however, the biomass of level I and II in the 1990s was higher than the 1960s. Despite the higher catches in the 1990s, fishing was ecologically less expensive during the 1990s than 1960s due to small fish catches were large. Mean transfer efficiency decreased from for 10.2% in the 1960s to 9.1% in the 1990s periods. According to the summary statistics, the parameters of net system production (NPS) and total primary production to total respiration ratio were increased from 1.013 in the 1960s to 2.184 in the 1990s, however, the connectance index (CI), system omnivore index, Finn’s cycling index and mean path length decreased from the 1960s to the 1990s. The overhead (O) was higher in the 1990s model while the ascendancy (A) decreased nearly 10% in the 1960s. The ‘Keystoneness’ result indicate that zooplankton was identified as keystone species in 1960s, however, the elasmobranches was keystone species in the late 1990s. The average trophic level of the fishery decreased from 3.32 in the 1960s to 2.98 in the 1990s, and exhibits classic symptoms of “fishing down the food web”. All the indices of the system attributes suggests that the Beibu Gulf ecosystem in 1960s was found to be more mature than in the 1990s due to the collapse of demersal ecosystem, and the ecosystem changed from being dominated by long-lived, high trophic level groundfish dominated system toward a system with small-size and low-value species over fifty years. Ó 2011 Elsevier Ltd. All rights reserved.

1. Introduction Fishing activities have altered and degraded marine ecosystems through both direct and indirect effects, especially in coastal regions where fishing and other anthropogenic perturbations are most intense (Botsford et al., 1997; Pauly et al., 2002; Dulvy et al., 2004; Hilborn et al., 2004). Over the past few decades, fisheryinduced collapses of 90% large predatory fishes have occurred throughout the world (Myers and Worm, 2003). The Beibu Gulf ecosystem is no exception to this common picture. The Beibu Gulf ecosystem is very productive and its living marine resources have been exploited for nearly half a century. Historically, the system has been very important as a fishing ground in the South

* Corresponding author. Tel.: þ86 20 8910 8007; fax: þ86 20 8445 1442. E-mail address: [email protected] (Z. Chen). 0964-5691/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.ocecoaman.2011.06.003

China Sea. However, with the engine boats introduced in the Gulf since the 1960s, the fishing effort and catches increased drastically during the past four decades (Chen and Qiu, 2002). With heavy exploitation, the catch compositions had changed significantly. Red snapper Lutjanus sanguineus was a large demersal fish and a dominant commercial species in the Gulf. The annual landing of the snapper in the Beibu Gulf markedly declined from137.2 kg km
2 in 1960s to 2.5 kg km
2 in 1992 (Yuan, 1995).Consequently, the catches became dominated by substantial amounts of juveniles and small pelagic species, and small-size, low-value fishes prevailed instead of high quality, high trophic level, large-size fishes. Large demersal fishes including groupers (Serranidae), snappers (Lutjanidae), yellow croakers and giant croakers (Sciaendiae) etc., which were traditionally targeted by the trawl fisheries, are now depleted (Sun and Lin, 2004; Qiu et al., 2010). The Beibu Gulf has been relatively well studied during the last 20 years. Over this time period, large amounts of data have been

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Z. Chen et al. / Ocean & Coastal Management 54 (2011) 601e611

collected and analyzed and sampling techniques have also become more sophisticated. However, previous studies in this area have consisted of fisheries surveys (Zeng et al., 1989; Luo et al., 1999) or focused on individual species (Cai et al., 1986; Qiu, 1996), there is few studies have been constructed on species interactions or on the ecosystem effects of fishing in the Gulf (Cheung and Sumaila, 2008). The ecological modeling software, Ecopath is a “snapshot” of given ecosystem and practical method to quantitatively improve knowledge on structure and functioning of different ecosystems. Among the analyze of exploited ecosystems undertaken using the EwE approach, the comparison of ecological models representing different situation of a given ecosystem through time has been shown to be a useful exercise (Shannon et al., 2003; Heymans et al., 2004). In this paper, two periods are modeled: the early 1960s, before the collapse of large groundfish, and the late 1990s, after the collapse. The results were used to evaluate and compare the structure and function between the two periods. The changes in the trophic interactions, the community structure and function of the

ecosystem during the half century were analyzed and evaluated to gain an insight into the status of the ecosystem development. This work also serves as a basis for future comparisons of the results of possible consequences of fisheries management scenarios derived from static networks of trophic flows to dynamic simulations of fishing impacts. 2. Materials and methods 2.1. Study site The Beibu Gulf is a semi-enclosed sea surrounded by land territories ofChina, Vietnam, and China’s Hainan Dao (Fig. 1). Its total area is 128,000 km2. The width of the Gulf is relatively narrow with the widest part of 180 nm (nautical mile). The Gulf has a maximum depth of 60 m and an average depth of 38 m, except at the mouth where depths reach about 100 m (Jia et al., 2003). Its bottom is flat, while sloping from the northwest to the southeast. Several rivers flow into the Gulf, including the Red River, Fangcheng

Fig. 1. Map showing the geographic location of the Beibu Gulf.

Z. Chen et al. / Ocean & Coastal Management 54 (2011) 601e611

River, Nanliujiang River, Qinjiang River, Dafengjiang River, Beilunhe River, and Changhuajiang River, thus having an extensive estuarine ecosystem (Chen et al., 1991). It is interesting to note that the rivers take nutrient from the land to the Gulf. Abundant nutrient, especially nitrates and phosphates, are necessary for the growth of phytoplankton. The climate of this Gulf is subtropical and monsoonal. The average annual air temperature is about 24  C and the surface temperature is 32.1  C and bottom of 8  C; the annual average rainfall is about 1670 mm (Sun et al., 1981). The Beibu Gulf is also subjected to land-based sources of pollutants from industrial and agricultural activities on the northeastern side (China), one of the more industrialized areas in the region (Zeng et al., 1989). In addition, petroleum exploration and extraction in the waters of the Gulf may also impacts on the Gulf ecosystem. However, there is no concrete indication of actual or potential effects of these activities on the Gulf ecosystem. 2.2. Ecological modeling approach The Ecopath model approach uses a set of linear equations for all groups i in the system assuming mass balance (Walters et al., 1997; Christensen et al., 2000) for species or group i, to quantify trophic flows among trophic groups (Christensen and Pauly, 1992, 1993). The basic equation is expressed as follows:

Bi



 n X P Q EEi
Bj DC
EXi
BAi ¼ 0 B i B j ji j¼1

(1)

where subscript j represents predators, Bj is predator biomass in tons wet weight, (P/B)i ¼ production/biomass ratio of i, which is equal to the coefficient of total mortality Z under steady-state conditions (Allen, 1971); EEi ¼ ecotrophic efficiency which is the proportion of production that goes to predation (Ricker, 1968), catches, or exports from the system; (Q/B)j ¼ consumption/biomass ratio of predator j; DCji ¼ fraction of prey i in the diet of predator j; and EXi is the export of group i, which in this study is represented by fishery catch. At least three of the parameters B, P/B, EE, and Q/B must be known for each group, while the model estimates the fourth. In addition, diet compositions and catches are required for each living group in the model. The components in the system are linked by trophic flows between them from prey to predators. Consumption by predators can be described by: consumption ¼ production þ non-assimilated food þ respiration (Winberg, 1956). This equation assumes that energy input and output of all living groups must be balanced in an ecosystem (Christensen et al., 2000). Mass-balance models of the Beibu Gulf were constructed for two periods, 1959e1961 and 1997e1999 to compare the fluctuations that occurred within each of these years before and after the large groundfish collapse. We used a total of 20 functional groups to represent the Beibu Gulf ecosystem. These groups were defined groups taking into consideration similarities within groups, such as the species have similar sizes, similar population parameters, similar food and predators, so as to allow for straightforward comparisons in strictly the same manner and all groups in the model covered the main trophic flows among the living marine groups and detritus. For the Beibu Gulf Ecopath model, the preliminary producers were phytoplankton and benthic producer; plankton was split into two groups, zooplankton and jellyfish; benthic invertebrates were divided into zoobenthos, prawns, benthic crustacean, and cephalopods. Traditionally, the fisheries resources were divided into pelagic and demersal, so other six groups were small pelagic, medium and large pelagic, small demersal, medium and large demersal. The apex predators were seabirds, sharks and marine mammals.

603

2.3. Ecopath model parameterization Inputs for each group include biomass (B) in t km
2, production/ biomass ratio (P/B) per year, consumption/biomass ratio (Q/B)i per year, ecotrophic efficiency (EE) i, diet composition (DC) ji, and catch per year. Although accurate estimated of all parameters for each functional species group lead to greater confidence in model outputs, only three of four (Bi, Pi/Bi, Qi/Bi, EEi) primary inputs are necessary. The model input data were collected from published stock assessment reports, peer-reviewed journal publication, and government reports. For the 1990s model, the research data were collected in spring, summer, autumn, and winter during 1997e1999 to consider seasonal changes. For the early-1960s model, it was originally constructed largely on data presented at a Sino-Vietnam joint trawl survey in the Beibu Gulf during 1959e1961. 2.3.1. Biomass (Bi) Biomass is defined as the total mass (measured in weight) of a certain group of organism per unit of area. Biomass data were obtained from different sources includes stock assessment reports, field survey data, or other models. The detritus biomass was calculated as a function of primary production and euphotic depth by employing the relationship suggested by Christensen and Pauly (1993).

LogD ¼
2:41 þ 0:954logPP þ 0:863logE

(2)

Where D is the standing stock of detritus, in gC m
2, PP the primary production in gC m
2 year
1 and E is the euphotic depth in meters (¼38 m). Phytoplankton biomass was estimated through the conversion factor of 0.3 mg chlorophyll a per 100 mg phytoplankton (Zhang and He, 1991). A regression equation was used to convert phytoplankton abundance to chlorophyll a per 100 concentrations. Biomass of coral and zooplankton were obtained directly from similar Ecopath model (Pitcher et al., 2002). For zoobenthos and jellyfish, the biomass was estimated from stock assessment literature (Jia et al., 2003). Biomass of fisheries resources, such demersal fish groups, pelagic fish groups and invertebrate groups were estimated with the swept area method (Pauly, 1984) from the captures with bottom trawl samples during the two periods. The swept area method takes into account the efficiency of the fishing gear, which is commonly proposed as 0.5 in survey work for trawlers in Southeast Asia (Pauly, 1984). For those species, such as elasmobranches, fish-eating birds and marine mammals, whose biomass data were not available, reference was made to similar ecosystem model (Pitcher et al., 2002). 2.3.2. Production/biomass (P/B)i The (P/B)i ratio was calculated for fish is considering total mortality (Z) in the mass-balance model (Christensen et al., 2000). Z (¼P/B) was estimated by the method of Beverton and Holt (1957) and calculated using the ELEFAN (Pauly, 1986, 1987). The average maximum attainable length LN and the average maximum attainable weight WN were either estimated with the data collected in this study using the von Bertalanffy growth function (VBGF). They were then used for the estimation of Z. For those species whose (P/ B)i ratio were not available the parameters values were obtained from similar ecosystem model (Pitcher et al., 2002; Lin et al., 2004). 2.3.3. Consumption/biomass (Q/B)i The (Q/B)i ratio represents the amount of food ingested by a group with respect to its own biomass in a given time period. For fish groups, Q/B ratios were computed using the predictive model of

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Z. Chen et al. / Ocean & Coastal Management 54 (2011) 601e611

Palomares and Pauly (1998). The aspect ratio of the caudal fin (A), indicative of metabolic activity and expressed as the ratio of the square of the height of the caudal fin and its surface area, is obtained mainly from Fishbase (www.fishbase.org; Froese & Pauly, 2006). For other groups, Q/B was estimated from published papers, or were calculated from the deviation of (P/B)i and (P/Q)i if (P/Q)i was known. 2.3.4. Ecotrophic efficiency (EEi) The ecotrophic efficiency is the fraction of the total production that is utilized in the ecosystem, either passed up the food web, used fro biomass accumulation migration or export (Christensen et al., 2000). The entry of these dimensionless EEi values is optional, but for a group, if biomass value is not available, the EEi value becomes an important alternative input parameter. Ecopath can estimate an EEi value for each group. A balanced model must have the EEi values of all groups between 0 and 1, because biomass consumed must be less than the biomass produced. In our model, we estimated EEi values for almost all groups and fine-tuned the model to ensure that the EEi values for all the groups were smaller than 1. 2.3.5. Diet composition (DCji) and yields (Yi) DCji is the fraction that prey group i contributes to the overall stomach contents of predator groups j (Christensen et al., 2000). Compared with other parameters, DCji is the most important parameter in the Ecopath model because any one of the Bi, (P/B)i, (Q/B)i or EEi values can be estimated if we know the other three. However, the DCji is an irreplaceable parameter that must be entered as an input parameter in the model for each species/group. This information is difficult to collect for part of the period or area modeled, biasing the mean estimates. Taxonomic resolution is low in some stomach analysis. In this study, we used the DCji values averaged over values reported in multiple studies. For the early1960s model, the diet composition data were mainly from SinoVietnam joint survey reports (unpublished). For the 1990s model, stomach content data were available from research surveys conducted on the Beibu Gulf during 1997e1999. Percent diet composition was estimated in weight percentage (Zhang, 2005). Catch values of two modeling periods were obtained from China fisheries statistical records (Bureau of Fisheries Ministry of Agriculture, 2002). 2.4. Balancing the model One of the most important steps in modeling is to verify whether a model yields a biologically realistic outcome and conforms to observed data. To balance the Ecopath model, the important step in verifying the realism of the model was to check whether the EE was less than 1.0 for all groups, since it is not possible for any group to be consumed in higher terms than its production. Those groups with an EE larger than 1 were often referred to as “unbalanced groups”. When unbalanced groups were encountered in modeling, we used the “automatic mass-balance” function that built-in in the Ecopath model to re-evaluate and modify parameters to achieve the goal of having EE smaller than 1 for all groups. This “automatic mass-balance” function adjusts each parameter within a defined confidence interval (normally, 20% higher or lower than the input parameter value). In the case when the above approaches were not effective for balancing models, we had to tune the input data manually by increasing the ranges for key parameters so that the model could search for appropriate parameters from a wider range of values. The key outputs included the estimates of trophic levels, tuned B, P/B, Q/B, EE, and production/consumption ration values for each function groups in the Beibu Gulf Ecopath model is described in Table 1.

2.5. Uncertainty and sensitivity analysis Uncertainties of the input parameters were specified using the module ‘pedigree’ in Ecopath modeling tool. The ‘pedigree’ index was calculated to quantify the uncertainty related to the input values in the model (Christensen et al., 2000). For each input value, a description was made of the data and their confidence (sample-based, high or low precision, approximate or indirect method, or from other models, from literatures also, etc.). Percent ranges of uncertainty, based on a set of qualitative choices relative to the origin of B, P/B, Q/B, Y. diet input or model estimates were used in the routine and resulted in an index value scaled from 0 (data not rooted in local) to 1 (data fully rooted in local data) for each input data. Based on the individual pedigree index value, an overall ‘pedigree index’ P of the information in ECOPATH can be calculated:

P ¼

n X X Iij n i¼1 j¼1

(3)

where Iij is the pedigree index for model group i and parameter j, n is the total number of modeled groups (Christensen and Walters, 2004). Because of uncertainty in the input parameters, a series of sensitivity analysis were also conducted for evaluating how robust the results were with respect to uncertainty in input parameters. All basic input parameters were changed, independently, in steps of 10%, from
50 to þ50% and the effects and the effects of these changes on all the missing basic parameters for all groups in the system were examined. The output is given as (estimated parameter
original parameter)/original parameter (Christensen et al., 2000; Bundy, 2005). 2.6. Trophic levels and transfer efficiencies Fractional trophic levels (Odum and Heald, 1975) were estimated for all ecological groups. The routine assigns TL 1 to producers and a TL of 1 þ the weighted average of the prey’s TL to consumers. To describe the proportional of energy transferred from one TL to the next, all ecological groups assigned discrete TLs sensu Lindeman. The transfer efficiencies (TE) (%) between successive TLs was calculated was the ratio between the sum of exports from a given TL, plus the flow that is transferred from the TL to the next, and the throughput on the TL. Catches are compared by converting flows in each path (toward the catch of a particular group) to primary production equivalents using the product of catch, production/consumption and the proportion of each group in the path in the diets of the other groups (Christensen et al., 2000):

" X Yi PPRc ¼ Pi paths

Y predato;prey

Qpredator 0  DCpredator;prey Ppredator EEpredator

# (4)

where P is production, Q consumption, Y is the catch of a given group and DC’ is the diet composition for each predator/prey constellation in each path (with cycles removed from the diet compositions). 2.7. Identifying an index of keystoneness Keystones are defined as relatively low biomass species with a structuring role in their food webs. Thus, identifying keystone species in a given ecosystem may be formulated as: (1) estimating the impact on the different elements of an ecosystem resulting

Z. Chen et al. / Ocean & Coastal Management 54 (2011) 601e611

605

Table 1 Balanced parameter estimates for the Beibu Gulf model for two periods 1960s and 1990s. Italics showed parameters that were estimated to balance the model.

1990s Function groups Benthic producers Phytoplankton Coral Zooplankton Jellyfish Zoobenthos Benthic crustaceans Penaeid prawns Cephalopods Small pelagic fishes Medium pelagic fishes Large pelagic fishes Small demersal fishes Medium demersal fishes Large demersal fishes Rays and Skates Elasmobranches Fish-eating birds Mar. mammals Detritus 1960s Function groups Benthic producers Phytoplankton Coral Zooplankton Jellyfish Zoobenthos Benthic crustaceans Penaeid prawns Cephalopods Small pelagic fishes Medium pelagic fishes Large pelagic fishes Small demersal fishes Medium demersal fishes Large demersal fishes Rays and Skates Elasmobranches Fish-eating birds Mar. mammals Detritus

Catch (t km
2)

B (t km
2)

P/B (y
1)

Q/B (y
1)

EE

Trophic level

e e e e 0.03 e 0.39 0.73 1.20 1.89 1.24 0.04 2.62 1.16 0.06 0.001 0.001 e

10.000 26.000 0.75 13.000 1.520 32.000 1.280 1.050 0.850 1.690 0.680 0.093 2.310 0.620 0.079 0.016 0.0035 0.00065 0.00120 163.800

11.860 230.00 1.090 36.00 6.124 6.570 5.950 7.600 3.110 3.850 2.560 0.500 3.000 2.200 0.900 0.500 0.300 0.060 0.060 e

e e

0.128 0.306 0.55 0.244 0.139 0.533 0.885 0.944 0.901 0.776 0.915 0.935 0.921 0.924 0.902 0.854 0.875 0.000 0.000 0.263

1.00 1.00 1.80 2.00 3.00 2.11 2.36 2.71 3.12 2.83 3.09 3.54 2.91 3.34 3.55 3.63 3.96 3.87 4.02 1.00

18.000 13.000 1.120 21.000 0.890 4.800 1.450 0.650 0.32 1.680 0.850 0.330 2.120 1.220 0.550 0.260 0.085 0.00165 0.0036 163.800

11.860 230.00 1.090 32.000 5.011 6.570 5.650 5.978 2.089 3.250 2.100 0.700 3.000 2.200 0.600 0.490 0.300 0.060 0.060 e

0.047 0.938 0.539 0.145 0.244 0.417 0.814 0.735 0.662 0.901 0.637 0.800 0.506 0.497 0.879 0.124 0.175 0.00 0.030 0.863

1.00 1.00 1.80 2.00 3.00 2.11 2.36 2.71 3.32 2.75 3.23 3.73 2.97 3.47 3.78 3.68 4.095 3.78 4.23 1.00

e e e e e e 0.103 0.14 0.21 0.084 0.40 0.165 0.331 0.412 0.263 0.1 0.002 e e

9.000 186.00 25.050 27.400 26.90 41.537 11.970 14.70 8.650 6.350 13.50 8.630 5.110 6.350 4.120 61.280 14.500 e e e 9.000 186.00 25.050 27.400 28.310 28.017 11.970 10.564 7.590 6.350 10.470 7.790 5.110 6.350 4.120 60.280 14.500 e

P/B ¼ production/biomass ratio; Q/B ¼ consumption/biomass ratio; EE ¼ ecotrophic efficiency; P/Q ¼ production/consumption ratio; trophic levels (TL) estimated herein were assigned as fractional numbers based on the suggestion made by Odum and Heald (1975).

from a small change to the biomass of the species to be evaluated for its ‘keystoneness’; and (2) deciding on the keystoneness of a given species as a function of both the impact estimated in (1) and its own biomass. In Ecopath model, it can be implemented by plotting the relative overall effect (ei) against the keystoneness (KSi). Here the overall effect of each group is defined as (Libralato et al., 2006):

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi uX u n ei ¼ t m2ij

(5)

jsi

where mij is obtained from the MTI analysis as the product of all the net impacts for all the possible pathways in the food web linking functional groups i and j. The relative overall effect (ei) is expressed to be relative to the maximum effect measured in the trophic web. In Eq. (5), the effect of the change in biomass on the group itself (i.e., mij) is excluded. The keystoneness (KSi) of each group is described as (Libralato et al., 2006):

KSi ¼ log ½ei  ð1
pi Þ

(6)

where pi is the contribution of the functional group to the total biomass of the food web.

2.8. Ecosystem maturity, structure and flow analyses Ecopath yielded lots of statistics to assess the status of an ecosystem and to describe the scale, stability, and maturity status of the ecosystem (Odum, 1969; Christensen, 1995). The total system throughput is the sum of all flows in the system, estimated as the sum of the four flow components; (1) sum of all consumption, (2) sum of all exports; i.e., exported from the system by fisheries or buried in the sediments, (3) sum of all respiration flows and (4) sum of all flows into detritus. The total system throughput represents the sizes of the system in terms of flow, and is important for comparison of flow networks (Ulanowicz, 1986). The ratio between total primary production and total system respiration (TPP/TR) and the ratio between total primary production and total biomass (TPP/TB) were considered to be other important descriptors of system maturity (Odum, 1971; Christensen, 1995). Primary production would exceed total respiration (i.e., TPP/TR > 1) for the ‘immature’ system, and the total biomass was enriched as the system came to maturity. So, a ‘mature’ system would be characterized as TPP/TR move toward unity (Odum, 1971) and lower TPP/TB (Christensen and Pauly, 1993).

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Z. Chen et al. / Ocean & Coastal Management 54 (2011) 601e611

A measure of the average mutual information in the system is the ascendancy (A), which is derived from information theory (Ulanowicz, 1986; Ulanowicz and Norden, 1990). It is measure of the networks’ potential for competitive advantage over other network configurations. The upper limit for the ascendancy is the develop capacity and the differences between them is the system overhead (O), which reflects the system’s strength in reserve to meet unexpected perturbations (Ulanowicz, 1986). The connectance index (CI) and the system omnivory index (SOI) are correlated with system maturity since a food chain is expected to change from linear to web-like as the system matures (Odum, 1971). CI is computed as the number of actual links in relation to the number of possible links in the food web (Gardner and Ashby, 1970), SOI is a measure of how the feeding interactions are distributed between trophic levels (Pauly and Christensen, 1993), and it is inspired by perceived drawbacks of CI. According to Odum (1969), the capacity of an ecosystem to entrap, withhold and cycle nutrients increases with maturity. The degree of recycling in a system can be measured with Finn’s cycling index (FCI) and Finn’s mean path length (FML). The FCI represents the proportion of the total throughput that is devoted to recycling of material. The FML, i.e., the average number of groups that an inflow or outflow passes through (Finn, 1976), is strongly correlated with the FCI. ‘Mature’ and ‘stable’ systems generally display a high degree of recycling (i.e., high-FCI and long-FML) (Christensen, 1995). 3. Results 3.1. Trophic structure and biomass The trophic structure of the ecosystem could be aggregated into eight trophic levels, most energy flows occurred in trophic levels I to V, and the values over trophic VI were extremely small. Thus, the Beibu Gulf ecosystem consisted of five main aggregated trophic level during the two periods. The throughput, biomass and production at each trophic level are identical in both decades (Table 2). The throughput and production were larger at lower trophic levels (Level I and II) in the 1990s than those in the early 1960s. However, for the higher trophic levels (Level IV to V), the values of those in the 1960s were much larger than in the 1990s.Therefore, the biomass of high trophic level, such as level IV and V, were larger in the early 1960s, especially for trophic level V, the biomass of level V in the early 1960s was 32 times higher than that of the 1990s. During the early 1960s, the large demersal fish, such as L. sanguineus, Nemipterus virgatus and Priacanthidae were the dominant species, and account for 39.7% of the total catch in the Gulf. Others dominant species included Upeneus moluccensis, Decapterus maruads and Nemipterus bathybiusi compromised 13.2%, 8.5% and 3.5% of total catch respectively (Fig. 2). By comparison, the species of catch compositions were different between the late 1990s and the early 1960s. In the late 1990s, the small and low trophic fish species, Stolephorus heteroloba, Table 2 Comparison between distribution of throughput, biomass and production at effective trophic levels in the Beibu Gulf ecosystem for the early 1960s and late 1990s. Trophic level

Throughput

Biomass

Production

1960s

1990s

1960s

1990s

1960s

1990s

Ⅰ Ⅱ Ⅲ Ⅳ Ⅴ

3650.144 2256.516 121.404 12.008 1.011

5921.855 3977.402 48.32 2.489 0.04

294.81 67.23 8.320 1.537 0.151

232.00 55.134 7.746 0.786 0.047

2145.32 228.77 14.97 1.12 0.04

2321.547 362.849 10.054 0.652 0.0094

Fig. 2. Catch composition of bottom trawl survey of the Beibu Gulf ecosystem in the early 1960 and late 1990s.

Stolephorus commersoni, Leiognathus berbis, Parargyrops edita and Siganus oramin had markedly increased and dominated in the system, whereas the large predator species, such as red snapper L. sanguineus, threadfin breams Nemipterus japonicus and Nemipterus metopias, and shark Carcharhinu menisorrala had markedly decreased. The catch composition shifted as the large predatory species became depleted and small fishes (Leiognathidae, Engraulidae) and invertebrate gained dominance (Fig. 2). In addition to the changes noted from the research survey data, Ecopath model estimates indicate that the biomass of large pelagic fishes, large demersal fish and others top predators between the two periods, while the biomass of small fishes, invertebrates, in particular cephalopods, increase nearly 3 times from 1960s to 1990s (Table 2). As longer large demersal predators were removed by fishing, the abundance of short-lived small pelagics increased, due to release from predation pressure. 3.2. Transfer efficiency In the Beibu Gulf, although the ecosystem was aggregated in to eight discrete trophic levels, the magnitude of flows at trophic levels greater that the fifth is negligible, representing only a small fraction of the flows associated with the top predators (Fig. 3). Most of the energy flow occurred mainly in trophic II (detritivores and herbivores), in both the 1960s and 1990s models. However, there are discrepancies between transfer efficiencies in the system. During the early 1960s, fishes, in particular large predator fishes, played

Z. Chen et al. / Ocean & Coastal Management 54 (2011) 601e611

0.441

(1960s)

1.964

4950 (PP)

123.3

0.469

0.043

11.93

4.5%

10.7%

3081.54

69.37

607

0.043

1.005 11.3%

8.4%

0.648

6.636

388.04 1742.6

40.11

3.82

0.271

(D)

Export 0.99

(1990s)

3.625

TL

0.527

0.002

Consum.

TE To Detritus

3215 (PP)

2647 8.0%

13.1%

83.40

3637

4253

8.47

1437

3215

0.11

0.4 8.5%

Resp.

4.4%

4.49

32

0.22

1.5

(D) Fig. 3. Flow network of organic matter and trophic efficiencies (%) of the Beibu Gulf model. The trophic flow (t km
2 y
1) web is aggregated into a concatenated chain of transfer through six integer trophic levels. Flows from primary producers (P) and from detritus (D) and flows out of the tops of boxes represent export, and flows out of the bottoms represent respiration.

a more important role in energy flow, and the geometric transfer efficiency for level IV and V were 11.3%, 8.4% respectively. In the late 1990s model, the transfer efficiencies declined sharply for IV and V, decreased to 8.5% and 4.4%. However, the transfer efficiencies for level II increased from 4.5% in the early 1960s to 8.0% in the late 1990s. The mean transfer efficiency values for the early 1960s and the late 1990s phases were 10.2% and 9.1% respectively (Fig. 3). 3.3. Primary production required to sustain catches The fraction of primary production required (PPR) to sustain the predators are higher for most groups in the 1990s, with except large pelagic fish and large demersal fish, which are higher in the 1960s (Fig. 4). The ratio of PPR by the fisheries to total annual harvest is 9.68 in the 1990s model, compared to 2.98 in the 1960s. This reflects the higher landing in 1990s than in the 1960s also. The greatest amounts of total primary production required to support catch in models of the Beibu Gulf ecosystem during 1990s are small pelagic fish and small demersal fish (Table 1). 3.4. Total system indices The total production (TP) of the system increased from 4192.00 t km
2 y
1 in the early 1960s to 6057.00 t km
2 y
1 in the late 1990s

(Table 3). Total system throughput (TST), which describes the size of the system in terms of flow (Ulanowicz, 1986; Field et al., 1989) is an important parameter for comparison of flow networks. For the Gulf, TST increased about 30% from 1960s to 1990s (Table 3). Total detritus flow (TDET) and net primary production (NPP) were much higher during the late 1990s than in the early 1960s. The high total net primary production in the late 1990s was reflected in the high net systems production. For the Gulf, the system overhead (O) was high in the late 1990s model, while the ascendancy was decreased nearly 10% in the early 1960s. In additional, a generalized decrease of CI, SOI, FCI and MPL were observed from the early 1960s to the late 1990s, especially for FCI, which it was about half those values in the early 1960s in the Gulf (Table 3). 3.5. Keystone species analysis The keystone species are those groups with proposed index values close to or greater than zero. Fig. 5 shows the keystoneness index (KSi) of the function groups in the early 1960s and late 1990s of the Beibu Gulf ecosystem. Within each trophic web the species are ordered by decreasing keystoneness, therefore the keystone functional groups are those ranking between the first groups. Zooplankton was identified as keystone species in 1960s, while

% PPR for catch

3 2.5

1960s 1990s

2 1.5 1 0.5 0

Benthic crustaceans

Penaeid prawns

Cephalopods Small pelagic Medium Large pelagic fishes pelagic fishes fishes

Small demersal fishes

Medium demersal fishes

Large demersal fishes

Fig. 4. The percentage of primary production required (%PPR) to sustain the harvest of commercially exploited fish in the Beibu Gulf ecosystem.

608

Z. Chen et al. / Ocean & Coastal Management 54 (2011) 601e611

Table 3 Comparison of ecosystem properties for the Beibu Gulf model as computed by Ecopath (flows in t$km
2 y
1) for the early 1960s and late 1990s. Attribute

Estimated by Ecopath

Total Consumption (TC) Total Biomass (excluding detritus) (TB) Total Respiratory Flow (TR) Total Detritus Flow (TDET) Total System Throughput (TST) Total Production (TP) Calculated net Primary Production (PP) Net system production (PLS) Finn Cycling Index (FCI) Mean Path Length (MPL) Mean trophic level of the fishery Detritivory:Herbivory (D:H) Connectance Index (CI) System Omnivore Index (SOI) Ascendancy (%) (A) Overhead (%) (O)

1960s

1990s

5196.837 110.793 3163.129 2175.535 10557.000 4192.000 3204.090 40.961 18.6 3.30 3.32 0.75:1 0.316 0.186 22.75% 77.25%

4037.865 96.089 2391.695 4490.589 13753.000 6057.000 5223.008 2831.393 9.73 2.847 2.98 0.46:1 0.31 0.176 31.03% 68.97%

benthic producers, zoobenthos and phytoplankton rank the first four in terms of overall effects and keytonesness. Elasmobranches, however, have high keystoneness and ranked first in the late 1990s, rays and skates, zooplankton rank are still important and rank second and third, respectively (Fig. 5). 3.6. Pedigree and sensitivity The pedigree index was 0.58 for the early 1960s model and 0.65 for the late 1990s model. The sensitivity analysis revealed that the relations between changes in input parameters and the affected parameters were nearly linear, hence only the effects of a 50% increase in one parameter on the other were considered (Appendix). In the early 1960s, a 50% increase in B or P/B for zooplankton increased EE of both 0.333 and 0.521. The most prominent changes resulted from an increase in B or Q/B of large demersal fishes. While EE for benthic crustaceans, small demersal

fishes and medium demersal fishes had a >42% increase, and the biomasses of zoobenthos, small demersal fished, medium demersal fishes and large demersal fishes increased by 0.325e0.650 (Appendix). A change in input parameters of small demersal fishes affected benthic crustaceans, penaeid prawn and zoobenthos. In the late 1990s model, a 50% increase in B or P/B for marine mammals increased EE for demersal fishes by 26.5e45.8%. A change in input parameters of zooplankton affected cephalopods and small pelagic fishes. The most sensitive sets of parameters were the effect of calculated ecotrophic efficiency (EE) of small demersal fish groups，changes in input of small demersal fishes were shown to affect the ‘missing’ parameters of six other groups in the system over 20% (Appendix). In general term, sensitivity analysis suggested that the estimated parameters were sensitive to the input parameters within a functional group, while the outputs were generally robust to parameters from other functional groups.

4. Discussion The collapse of the commercial fish stocks and the subsequent increase in invertebrate and small and low trophic level of fish abundance had little significant effect on the Beibu Gulf ecosystem when measured at the ecosystem level. Our comparative massbalance model of the Beibu Gulf for the early 1960s (1959e1961) and late 1990s (1997e1999) shows a significantly change of the tropical marine ecosystem during the two periods. The major changes in the ecosystem properties of the Gulf were observed in the summary statistics attributes. Pauly and Christensen (1995) relate PPR to the potential net primary production used in terrestrial system by Vitousek et al. (1986). According to Christensen et al. (2000), PPR is similar to Odum’s concept of energy, and proportional to Wackernagel and Rees’ (1996) ecological footprint. The lower PPR for the catches in the 1960s (Table 1) corresponds to the higher mean trophic level in the 1960s than in the 1990s, therefore, fishing was ecologically more expensive (from higher trophic levels) during the 1960s than in the 1990s. Fig. 2 also reflects the decreased fraction of large demersal and pelagic fish in the total catch from 1960s to 1990s.

0.5

0.5

Relative overall effect

Relative overall effect (1990s)

1960s 1

0.0 5 43

0.0

1

2 5

6 7

13

9 10 11 12

17

11

-1.5

15

16

18 19 1 Zooplankton

-1.0 8 Marine mammals

15 Rays and Skates

2 Benthic producers

9 Benthic crustaceans

16 Medium demersal fishes

3 Zoobenthos

10 Medium pelagic fishes 17 Cephalopods

4 Phytoplankton

11 Jellyfish

5 Small pelagic fishes 12 Penaeid prawns

7 Elasmobranches

14 Large demersal fishes

14

12 13

16 17 18 1 Elasmobranches 19 2 Rays and Skates

8 Phytoplankton

15 Marine mammals

9 Benthic producers

16 Large demersal fishes

3 Zooplankton

10 Jellyfish

17 Large pelagic fishes

18 Coral

4 Penaeid prawns

11 Zoobenthos

18 Coral

19 Fish-eating birds

5 Benthic crustaceans

12 Medium demersal fishes

19 Fish-eating birds

6 Cephalopods

13 Medium pelagic fishes

7 Small pelagic fishes

14 Small demersal fishes

-1.5

6 Small demersal fishes 13 Large pelagic fishes -2.0

2

9 10

-0.5

14 15 -1.0

3

6 87

8 -0.5

4

-2.0

Fig. 5. Keystoneness index (KSi) and relative overall effect (ei) for the function groups from the ecological models in 1960s and late 1990s. The species are numbered by decreasing KSi, therefore the keystone functional groups are those ranking between the first groups (value close or grater than zero).

Z. Chen et al. / Ocean & Coastal Management 54 (2011) 601e611

Primary production equivalents required to sustain catches in the Beibu Gulf ecosystem are relative small proportional (2.98e9.68%) in comparison to the peruvian system (13e15%), and slightly lower than the 9.5% mean for the seven upwelling systems examined by Jarre-Teichmann and Christensen (1998). They are more line with percentages required to sustain catches in open ocean (Shannon et al., 2003) or coastal areas than in other upwelling systems or shelf systems (Pauly and Christensen, 1995). Primary production equivalents are also used to compare effects of fishing at different trophic levels. In the Beibu Gulf ecosystem, the average trophic level of the fishery decreased from 3.32 in the early 1960s to 2.98 in the late 1990s, this reflect a larger proportion of the catch in the late 1990s were of small fishes. Therefore, the Beibu Gulf ecosystem has been shown the ‘fishing down the food web’ as many regions (Pauly et al., 1998). This is in line with what has been found for the Gulf where fishing at a lower trophic level in the late 1990s than in the early 1960s (Table 2). The ecosystem in the early 1960s could be classified as an mature ecosystem due to the TPP/TR ratio was 1.013, close to 1; while in the late 1990s, the TPP/TR ratio increasing to 2.184. Meanwhile, the ratio TPP/TB increased from 28.92 in the early 1960 to 54.355 in the late 1990s (Table 4). CI and SOI are also correlated with system maturity since the food chain is expected to change from linear to web-like as the system matures (Odum, 1971). For the Gulf, the values CI and SOI were 0.316 and 0.186 in the early 1960s and 0.31 and 0.176 in the late 1990s (Table 4). The nearly same of CI values may result from the same average diet composition data we used for the early 1960s model and the 1990s model. And the change in SOI values indicates that the late 1990s ecosystem displayed less web-like features. Ascendancy (A) and overhead (O) have been shown to be related to stability (Christensen, 1995; Cropp and Gabric, 2002), maturity (Ulanowicz and Abarca-Arenas, 1997; Nielsen and Ulanowicz, 2000; Perez-Espana and Arreguin-Sanchez, 2001; Fath et al., 2001), eutrophication (Aoki, 1995), and human disturbance (Genoni and Pahl-Wostl, 1991). Overhead is a measure of the energy in an ecosystem that is available to resist perturbations (Christensen, 1995; Angelini and Petrere, 2000).We found a decrease in relative overhead (8.28%) in the late 1990s due to the impact of fishing activity. This also implied that the late 1990s food web was less resistant, and the early 1960s food web was more resistant to perturbations, which is in conjunction with the findings of Heymans et al. (2004), relative overhead changed 10% in a marine system before and after the system was “severely stressed” by fishing.

609

The FCI and MPL were 18.6 and 3.30, respectively, in the 1960s. In 1990s, the FCI and MPL decreased from those in the early 1960s to 9.73 and 2.847, respectively (Table 4), which reflects the early 1960s ecosystem was more mature and more complex ecosystem, compared with the late 1990s. Detritus was found to be almost 21% of the total system throughput in the early 1960s and 33.3% in the late 1990s, and hence has an important role in the system. We found that the contribution of detritus to the Beibu Gulf ecosystem is in the range of what is observed in other tropical water bodies (Christensen and Pauly, 1993; Moreau et al., 2001). The trophic flows, which constitute about 80% of the total system throughput, are trapped within the system acting as nutrient storehouse, which may later lead to eutrophication. As eutrophication can be defined as ‘an increase in the rate of supply of organic matter to an ecosystem’ (Nixon, 1995), Brando et al. (2004) reported a reduction in the accumulation rate of organic matter in the Orbetello ecosystem suggesting a decrease in the tendency toward eutrophication in the system. However, in our study a large increase (30.27%) in total system throughput in the late 1990s showed increased detritus accumulation, which indicated an increased tendency for eutrophication, a negative impact of the fishing activity of the Gulf (Table 4). This tropical marine ecosystem possesses great amount of reserve energy (overhead), showing that it is a system that can support unpredictable disturbances. These observations could be made use of in other tropical marine ecosystems to assess the impact of fishery. Keystone species are relatively low biomass species with a structuring role in the food web. These species have strong effect on the abundance of other species and ecosystem dynamics in a manner disproportionate to their own abundance (Power et al., 1996; Libralato et al., 2006). Generally, marine mammals ranked high (most often first) in most ecosystems such as Alaska gyre, Azores, Newfoundland, Norwegian Barents Sea models (Duan et al., 2009). In our models, the marine mammals had low rank and ranked 8 and 15, in the 1960s and 1990s model, respectively. In the early 1960s model, the lower trophic level function, such as zooplankton, benthic producers, zoobenthos and phytoplankton becomes important and had high keystoneness index, suggesting the bottom-up control in the gulf during this period. On the contrary, there were obvious changes in rank of keystone species over time, and the top predators groups, elasmobranches, rays and skates ranked first two in the 1990s model, indicating a typical topdown control for the late 1990s system. These indices changes of the two periods in the gulf have shown the collapse of its demersal ecosystem due to the anthropogenic disturbances, mostly in over-

Table 4 Odum’s (1969) ecosystem attributes Ecopath estimates and status for the selected attribute of in the Beibu Gulf for the early 1960s and late 1990s. Ecosystem attribute

Developing

Mature

Estimated by Ecopath

<1>

z1

TPP/TR

high

low

TPP/TB

low high linear small broad open unimportant “r” poor low

high low web-like z1 narrow closed important “k” good high

TB/TST PLS CI TB/TDET SOI FCI TDC/TC TB/TST O A

Period 1960s

1 Total Primary Production/ Total Respiration 2 Total Primary Production/ Total Biomass 3 Total Biomass/Total Throughput 4 Net production 5 Food chains 6 Organic matter 12 Niche speciliz. 15 Mineral cycles 17 Detritus 18 Growth form 22 Stability 24 Information

1.013 28.92 0.01 1686.961 0.316 0.571 0.186 18.6 0.52 0.652 31.03% 68.97%

1990s 2.184 54.355 0.007 2831.393 0.31 0.066 0.176 9.73 0.43 0.234 22.75% 77.25%

610

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fishing. In conclusion, the Beibu Gulf ecosystem seems to have gone through various anthropogenic changes caused from fishing over the past forty years. It changes from a structured, channel-like ecosystem in the early 1960s, when large predators were the most important in catches, to a system of small fish and invertebrates were dominant in the late 1990s. This study suggests that the Beibu Gulf ecosystem experienced a regime shift switch from high trophic groundfish dominated to low trophic species from the 1960s to 1990s. These changes are similar to those occurred in the southern Benguela ecosystem from 1950s to 1970s (Cury and Shannon, 2004), in the eastern Scotian Shelf ecosystem from 1980s (Bundy, 2005). Even if the results of this study can be viewed as preliminary and unable to fully understanding the predatoryeprey interactions, a comparative study is particularly valuable. Firstly, they are the best pictures of the ecosystem with the available information, and the standardization process helps to minimize the errors associated with the structure of the model so that the features of the ecosystems can be revealed and compared. Furthermore, it can serve as a basis for developing and testing hypotheses using dynamic simulations of fishing and environmental effects in future. Acknowledgments We are very grateful to many scientists in the region for assistance with, provision of and discussions about data used in our models. This study was supported by the Special Project of the Social Commonwealth Research of the National Science Research Institute (South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences) (No. 2010ZD01) and Guangdong Natural Science Foundation (No. 9451030002002475). We are grateful to all the staff of the above-mentioned institutions for implementing the fishery resources survey in the Beibu Gulf and for assisting in the collection of the data. We also thank three anonymous referees for their valuable comments and suggestions to improve the manuscript. Appendix. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.ocecoaman.2011.06.003. References Allen, R.R., 1971. Relation between production and biomass. Journal of the Fisheries Research Board of Canada 28, 1573e1581. Angelini, R., Petrere, J.M., 2000. A model for the plankton system of the Broa reservoir, Sao Carlos. Brazil. Ecological Modelling 126, 131e137. Aoki, I., 1995. Flow-indices characterizing eutrophication in lake-ecosystems. Ecological Modelling 82, 225e232. Bureau of Fisheries Ministry of Agriculture, People’s Republic of China, 2002. China Fisheries Yearbook (1949–2001). Agriculture Press, Beijing (in Chinese). Beverton, R.J., Holt, S.J., 1957. On the Dynamics of Exploited Fish Populations. Chapman & Hall, London, 533 pp. Botsford, L.W., Castilla, J.C., Peterson, C.H., 1997. The management of fisheries and marine ecosystems. Science 277, 509e515. Brando, V., Ceccarelli, R., Simone, L., Ravagnan, G., 2004. Assessment of environment management effects in a shallow water basin using mass balance models. Ecological Modelling 172, 213e232. Bundy, A., 2005. Structure and functioning of the eastern Scotian Shelf ecosystem before and after the collapse of groundfish stocks in the early 1990s. Canadian Journal of Fisheries and Aquatic Sciences 62, 1453e1473. Cai, Y.Y., Liu, Z.G., Zhang, Z.Q., Deng, C.M., 1986. The amphioxus in the Beibu Gulf of China. Tropic Oceanology 5 (2), 42e50 (in Chinese, with English abstract). Chen, G., Gu, X., Gao, H., 1991. Marine Fishery Environment in China. Zhejiang Scientific & Technological Press, Hangzhou. 233pp (in Chinese). Chen, Z.Z., Qiu, Y.S., 2002. Status and sustainable utilization of fishery resources of South China Sea. Journal of Hubei Agriculture College 22 (6), 508e510 (in Chinese with English abstract).

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