Open Access
How to translate text using browser tools
1 May 2013 Long-Term Changes in Fish Assemblage Structure in the Yellow River Estuary Ecosystem, China
Xiujuan Shan
Author Affiliations +
Abstract

The Yellow River estuary ecosystem is an important spawning ground for many species found in the Bohai Sea and Yellow Sea and contributes substantially to the fishery resource structure and biological reproduction in the northern China Sea. Based on long-term ecosystem surveys in the Yellow River estuary during the main spawning period (May) of most fishery species from 1959 to 2011, the responses of the ecosystem, including regime shifts in species composition, biomass, diversity, and other related factors, were analyzed in this study. Since the 1980s, the dominant large-size species of high economic value (e.g., Largehead Hairtail Trichiurus lepturus) have been replaced by short-lived, low-trophic-level, planktivorous pelagic species (e.g., Scaly Hairfin Anchovy Setipinna taty and Japanese Anchovy Engraulis japonicus). Currently, traditional commercially targeted fishes, such as the Largehead Hairtail, Red Seabream Pagrus major, and Pacific Herring Clupea pallasii, are locally extinct. There has been a rapid shift of dominant species from highly valued, high-trophic-level, large-sized demersal species with complicated age structures to low-value, low-trophic-level, small-sized pelagic species with simple age structures; this shift has resulted in major changes to the ecological cycle and restoration of fishery resources. The fish catch declined from 421.66 kg/h in 1959 to 0.25 kg/h in 2008 and then increased to 3.62 kg/h in 2011. Diversity and evenness indices showed a continuously increasing trend during 1959–2011. The Yellow River estuary may be significantly compromised by overfishing, climate change, dam construction, and pollution, resulting in the decline of traditional fishing industries and reduced biodiversity in this ecosystem.

Estuaries play an essential role as feeding, spawning, and breeding grounds for many fishes, including freshwater and marine species, and they are important for many resident estuarine species because they offer a favorable habitat and support the migratory routes for catadromous and anadromous species (Elliott and McLusky 2002; Martinho et al. 2007, 2008). However, estuarine ecosystems have been suffering from eutrophication, overfishing, climate change, and general environmental degradation (Martinho et al. 2008). Thus, several studies on ecosystem health have been conducted (James et al. 2008; Selleslagh et al. 2009; Nicolas et al. 2010), including long-term studies that are used to analyze trends in fish assemblages (Elliott et al. 2007; Purcell et al. 2010). Overfishing and climate change are increasingly threatening the world's marine ecosystems, and the effects of fishing on marine ecosystems worldwide have consequences for populations and communities (Pauly et al. 2002; Myers and Worm 2003; Jennings and Blanchard 2004). It is important to identify the dynamics of the fish community in response to climatic regime shifts and anthropogenic activities (Yasunaka and Hanawa 2002).

The Yellow River estuary ecosystem is a spawning zone for many commercial species of the Bohai Sea and Yellow Sea; it also constitutes the major fishing ground in the northern China Sea. In recent years, with a growing population and increasing economic development along the Bohai Sea coast, the Yellow River estuary ecosystem has greatly changed (Zhao et al. 2000), resulting in further impacts on the growth, survival, and reproduction of fishery species (Liu et al. 2003). These impacts, coupled with high fishing intensity—particularly the rapid development of bottom-trawl prawn fisheries—have led to an abundance of juveniles of commercial species in the catch. The demersal fisheries have declined, and due to high fishing intensity the major fishery stocks have changed through cascading trophic chain reactions, particularly regime shifts of dominant species and variations in individual size and age (Jin and Tang 1998; Jin and Deng 2000; Wang 2009). However, long-term variations in fish assemblage diversity and trophic spectrum structure in the Yellow River estuary ecosystem have not been fully addressed.

Fish assemblage diversity is the basis of survival and development for some societies, as fish supply high-quality protein and improve the dietary structure. Conservation of fish assemblage diversity is related to the future of sustainable development, so it is necessary to understand the processes and mechanisms of long-term variations in biodiversity. These variations are of worldwide concern, and the measures to be implemented in management initiatives aimed at sustainable fisheries and biodiversity conservation should be fully considered. Species composition and richness describe qualitative variations of fish species; biomass and productivity refer to the quantity and rate of production. Stability can refer to the temporal constancy of a community, resistance to environmental change, or resilience after a disturbance. Based on long-term fishery survey data collected in May (the spawning period for most of the Bohai Sea and Yellow Sea fish species that spawn in the Yellow River estuary), the present study involved analysis of variations in species composition and fish assemblage diversity, as well as trophic spectrum structure, stability, and related factors, over the past 50 years.

METHODS

Study Area and Field Sampling Procedures

The Yellow River estuary ecosystem (Figure 1) is located in the southern Bohai Sea (south to 38°50′N; 119°30′E to 120°30′E) and accounts for approximately 10% of the total Bohai Sea area. The estuary is characterized by a shallow-water shelf, where the water depth is less than 15 m, and the sediments are composed of soft mud and sand. The Yellow River estuary is an important ecological zone because the Yellow, Xiaoqing, Bailang, Guangli, Wei, and Jiaolai rivers enter the sea at this location. These rivers deliver abundant freshwater and terrestrial materials, such as sediment and nutrients, thereby providing resources for the high productivity in this area. The estuary forms the main spawning grounds and habitats for many commercial species of the Yellow Sea and Bohai Sea, such as the Small Yellow Croaker Larimichthys polyactis, Largehead Hairtail Trichiurus lepturus, Yellow Drum Nibea albiflora, and Red Seabream Pagrus major. The Yellow River estuary also supports the Bohai Sea fishing industry, supplying up to 40% of the Bohai Sea total catch. The coastal waters of the Yellow River estuary are bounded by a heavily urbanized area, the fluvial plain along the estuary is surrounded by agricultural land, and the freshwater from the Yellow River is greatly regulated by dams and rainfall.

In the present study, fish assemblage data were obtained from bottom-trawl surveys in May of 1959, 1982, 1993, 1998, 2003, 2008, and 2011 at 20 designated stations (Figure 1). Two trawlers (∼200-hp vessels) were deployed for 1- or 2-h tows; CPUE was standardized to 1 h at each station (for fish species only). All specimens were sorted at the species level and were counted and weighed on-board. Only fish were included in the analysis. The same net was used for all sampling; the mesh size for the net opening was 6.3 cm, the depth of the net opening was 6 m, the width of the net opening was 22.6 m, the mesh size of the cod end was 2 cm, and the trawling speed was approximately 4.82 km/h (2.6 knots). During each sampling cruise, duplicate water samples were collected to measure water temperature (with a reversal thermometer) and salinity (with an induction salinometer).

FIGURE 1.

Sampling stations in the Yellow River estuary ecosystem.

f01_65.jpg

Data Analysis

Functional groups.—Functional groups were determined based on feeding habits and adult mobility (Bellwood et al. 2004; Micheli and Halpern 2005). The fish species in the Yellow River estuary were divided into eight functional groups: planktivores (G1), planktivores/benthivores (G2), benthivores (G3), benthivores/piscivores (G4), omnivores (G5), mobile piscivores (G6), elasmobranchs (G7), and roving piscivores (G8; Bellwood et al. 2004; Zhuang et al. 2006; Zhang et al. 2007; Jiang 2008).

Diversity indices.—The variation in fish species composition was examined by using cluster analysis based on the Bray—Curtis similarity matrix calculated from square-roottransformed biomass (kg/h) data (Clarke and Warwick 2001). Species richness was estimated with Margalef's richness index (R; Margalef 1958). The Shannon-Weaver diversity index (H'; Shannon and Weaver 1949) and Lande's index (1 — λ; Lande 1996) were used to assess species diversity. Pielou's evenness index (J'; Pielou 1975) was used to determine evenness. All of the biodiversity indices were calculated from relative biomass (kg/h).

Trophic category and mean trophic level index.—Fish species were stratified into five trophic categories (from planktivores to roving piscivores) based on trophic level and food habits: (1) trophic levels less than 3.0 (e.g., Dotted Gizzard Shad Konosirus punctatus and Redeye Mullet Liza haematocheila); (2) trophic levels ≥ 3.0 but less than 3.5 (e.g., Japanese Anchovy Engraulis japonicus, Scaly Hairfin Anchovy Setipinna taty, and Osbeck's Grenadier Anchovy Coilia mystus); (3) trophic levels ≥ 3.5 but less than 4.0 (e.g., Silver Pomfret Pampus argenteus and Marbled Flounder Pseudopleuronectes yokohamae); (4) trophic levels ≥ 4.0 but less than 4.5 (e.g., Fat Greenling Hexagrammos otakii and most of the flatfishes); and (5) trophic levels ≥ 4.5 but less than 5.0 (e.g., Japanese Seabass Lateolabrax japonicus, Monkfish Lophius litulon [also known as Yellow Goosefish], Mottled Skate Raja pulchra, and Mi-iuy Croaker Miichthys miiuy). Trophic level information for each species was based on the literature and prey analysis (Yang et al. 2001; Zhang 2005).

The mean trophic level (MTL) of fish landings can be used as an index of sustainability in exploited marine ecosystems (Pauly et al. 2002). The MTL for the fish community not only depended on the trophic level of each species but also reflected the proportion of biomass for each species. In the present study, the MTL of each fish community was estimated according to Tian et al. (2006),

e01_65.gif

where Yi represents the catch of species i in every sampling period, Y represents the sum of catch for the total number of species n in every sampling period; and TLi is the trophic level for species i. The MTL values were compared with values from similar studies in the Bohai Sea (Yang et al. 2001; Zhang 2005).

Climatic and oceanographic indices.—The Southern Oscillation Index (SOI;  www.bom.gov.au/climate/current/soihtm1. shtml), monthly sea surface temperature (SST) anomalies ( www.coaps.fsu.edu/pub/JMA_SST_Index/), and warm and cold SST phases ( www.coaps.fsu.edu/jma.shtml) were chosen as the climatic indices for the western Pacific Ocean. These indices were well documented and associated with interannual— interdecadal variability not only of atmospheric and oceanic conditions but also of marine ecosystems in the North Pacific (Beamish et al. 2000; Tian et al. 2004). Data on Yellow River runoff, sediments, and basinwide precipitation in each year were obtained from the Bulletin of Sediments and Runoff for the Yellow River (YRCC 1950–2009). The El Niño—Southern Oscillation (ENSO) events identified from the SOI and SST data correspond well with lows in annual water and sediment flux to the western Pacific Ocean, showing that climate oscillation dominates short-term (interannual) fluctuations in sediment flux and rainfall.

RESULTS

Species Composition and Dominant Species

In total, 77 fish species belonging to 33 families were collected in the Yellow River estuary ecosystem during 1959–2011. Eight fish species (10.4% of species) were collected during every sampling year. With the exception of the Silver Pomfret and Small Yellow Croaker, most of these eight species were pelagic fishes, including the Japanese Anchovy, Scaly Hairfin Anchovy, Smallhead Hairtail Eupleurogrammus muticus, Dotted Gizzard Shad, Madura Anchovy Thryssa kammalensis, and White Gunnel Pholis fangi. Species composition analysis indicated that for more than 99% of the total weight of fish catch, there were extreme changes in fish species composition during 1959–2011 (Table 1).

In 1959, fish catch mostly consisted of commercial species, such as the Largehead Hairtail, Small Yellow Croaker, Tongue Sole, Tiger Puffer, White Croaker, and Japanese Seabass. The Largehead Hairtail was the predominant species of the total catch, with a CPUE reaching 330.03 kg/h. The CPUE for the Small Yellow Croaker was 65.20 kg/h. The Largehead Hairtail and Small Yellow Croaker catches accounted for 93.9% of the total CPUE, whereas for other species the CPUE was below 10 kg/h and the catch was not above 2% of the total catch.

TABLE 1.

Top-ten fish species composition (average catch [kg/h] and contribution to total fish catch [%]) for each sampling year in the Yellow River estuary ecosystem, 1959–2011.

t01_65.gif

The dominant species in 1982 were mainly pelagic fishes; the Japanese Anchovy and Scaly Hairfin Anchovy were the most common species, accounting for 68.5% of the total catch. The Yellow Drum was also a dominant species. In 1993, the Japanese Anchovy, Madura Anchovy, and Scaly Hairfin Anchovy were the dominant species; the combined catch of the three species accounted for 87.7% of the total catch, but the CPUEs of these species had sharply declined in comparison with the CPUEs observed in 1982, particularly for the Scaly Hairfin Anchovy. The CPUE of Japanese Anchovy declined from 40.66 kg/h in 1982 to 22.64 kg/h in 1993; the CPUE of Scaly Hairfin Anchovy decreased from 67.21 kg/h in 1982 to 2.45 kg/h in 1993. In 1998, the CPUE for Madura Anchovy was greater than 1 kg/h, whereas the CPUEs for all other species did not exceed 1 kg/h; the dominant fishes were pelagic species.

In 2003, the CPUE was 2.28 kg/h for the Scaly Hairfin Anchovy and 1.57 kg/h for the Madura Anchovy; these two species accounted for 77.9% of the total catch. In 2008, the predominant fishes were pelagic species, including the Silver Pomfret, Japanese Spanish Mackerel, and Scaly Hairfin Anchovy; however, the CPUE was below 0.1 kg/h for each species. In 2011, the Japanese Anchovy and Madura Anchovy were the dominant species, and the Small Yellow Croaker and Japanese Seabass again were among the most common species in the catch, but CPUEs for all species were less than 1 kg/h and were equivalent to less than 1% of the CPUEs observed in 1959. During the study period (1959–2011), the CPUE of every species declined, most noticeably after 1998, when most of the species had CPUEs below 1 kg/h. The dominant species changed from large-sized commercial species in 1959 to small-sized pelagic species beginning in 1982. In addition, some Chondrichthyes species, such as the Rayfish (also known as the Ocellate Spot Skate) and Spotless Smooth-hound Mustelus griseus, were not observed during recent sampling years.

Dynamics in Abundance

Figure 2a represents the dynamics of fish catch and species composition in the Yellow River estuary ecosystem during 1959–2011. Average fish catch decreased from 1959 to 2008 and then increased from 2008 to 2011. The highest fish catch (421.66 kg/h) was obtained in 1959, and catch reached its lowest value (0.25 kg/h) in 2008. Demersal species were the main component of the fish catch structure in 1959, whereas in 1982 the percentage of demersal fish in the catch had greatly declined. Correspondingly, the proportion of pelagic fish in the total catch increased, peaking in 1993 and then stabilizing from 1998 to 2008. The contribution of demersal species to the total catch gradually increased after 1993; during 2011, the proportion of demersal fish in the total catch exceeded the proportion of pelagic fish.

Table 2 shows the family-level composition of the fish catch in the Yellow River estuary during 1959–2011. Engraulidae was the common dominant family in the fish catch during all sampling years (except 1959), particularly from 1982 to 2005. Engraulidae accounted for more than 50% of the total catch. Trichiuridae (78.4%) and Sciaenidae (16.3%) shared dominance in the fish catch composition during 1959, with lesser contributions from Cynoglossidae, Tetraodontidae, and Platycephalidae. In 1982, the fish catch mainly consisted of Engraulidae (68.6%) and Sciaenidae (12.8%), followed by Clupeidae, Percidae, and Tetraodontidae; other families contributed less than 2% of the total catch. In 1993, Engraulidae (87.7%) was the dominant fish family in the catch, followed by Clupeidae, Rajidae, Sciaenidae, and Trichiuridae. During 1998, Engraulidae (69.4%) and Clupeidae (9.9%) were the predominant families in the catch, followed by Trichiuridae and Stromateidae. In 2003, Engraulidae (78.5%) was again the dominant family represented in the total catch, followed by Stromateidae and Sciaenidae. During 2008, Stromateidae (29.8%), Engraulidae (18.8%), and Polynemidae (14.5%) were the dominant families in the total catch. The total catch in 2011 primarily included Engraulidae (30.9%), Percidae (21.8%), and Sciaenidae (16.9%) as the dominant families, along with contributions from Lophiidae and Stromateidae.

FIGURE 2.

Dynamics of (a) the average fish catch and (b) the mean trophic level (MTL) of fish catch in the Yellow River estuary from 1959 to 2011.

f02_65.jpg

Trophic and Community Structure

The MTL decreased from 1959 to 1998, increased slightly in 2003, maintained a stable level from 2003 to 2008, and then increased again in 2011 (Figure 2b). Figure 3 shows the trophic structure of the fish catch in the Yellow River estuary ecosystem. There were some differences among sampling years, so the fish catch at different trophic levels was calculated by using log10 transformed CPUE. In 1959, the fish catch was mainly distributed at trophic levels 3.5–4.5 (particularly 4.0–4.5), followed by 4.5–5.0; thus, the trophic level of the fish catch was relatively high in that sampling year. During 1982, the trophic level of the fish catch was also 3.5–4.5, but the most abundant trophic level was 3.5–4.0. In addition, fish from trophic levels lower than 3.5 accounted for a high proportion of the catch in 1982. Correspondingly, the proportion of the fish catch at trophic levels 4.0–5.0 decreased. In 1993, the fish catch representing trophic levels 3.0–4.5 showed a distribution pattern similar to that seen in 1982, but the catch from trophic levels less than 3.0 and greater than 4.5 decreased. In 1998, the fish catch greatly decreased, and the trophic level of the catch was mainly distributed at 3.0–4.0. During that year, the fish catch at trophic levels 4.0–4.5 decreased, and the fish catch representing trophic levels less than 3.0 and greater than 4.5 also decreased. In 2003 and 2008, the trophic level of the fish catch showed similar trends as were observed in 1998; however, in 2008, few individuals at trophic levels 4.5–5.0 were present in the catch. During 2011, the trophic level of the catch showed similar trends as in 1993, with fish being mainly distributed at trophic levels 3.0–4.5 (particularly 3.5–4.0).

TABLE 2.

Family-level composition of the fish catch (kg/h) in the Yellow River estuary ecosystem during 1959–2011.

t02_65.gif

The functional groups included the fish species with a total weight greater than 100 g in each survey, and functional groups were determined by feeding habits and the motility of adults. Table 3 shows the functional group structure of the fish catch from 1959 to 2011. In 1959, the fish catch by weight consisted primarily of G6, followed by G4 and G5; the observed fish species were mainly distributed in G1 and G4, followed by G6. Although G1 encompassed the highest number of species, the total catch weight contribution from G1 was just 1.0%. In 1982, the fish catch by weight consisted mainly of G1, followed by G5 and G2; however, the observed species were mainly distributed in G1, G2, and G3. During 1993, G1, G5, and G7 accounted for high proportions of the fish catch by weight; high numbers of species from G1, G3, and G6 were observed. In 1998, G1, G3, and G6 contributed high proportions of the catch weight; the percentage of observed species was highest for G1, G3, and G5. In 2003 and 2008, functional group distribution patterns showed a similar trend. Groups G1, G3, and G5 accounted for high proportions of the fish catch by weight as well as high percentages of the observed fish species. In 2011, the highest fish catch percentages by weight were from G1, G5, and G8; however, G1, G3, and G6 contributed the greatest numbers of species.

A cluster analysis dendrogram based on Bray—Curtis similarity in fish weight was used to assess similarity between sampling years (Figure 4). The similarity analysis indicated significant differences in the fish catch from 1959 to 2011. Excluding the 2008 sampling results, relatively high similarity in fish catch was detected between proximate sampling years. The greatest similarity was observed between the 2003 and 2011 fish catches, whereas the lowest similarity was found between fish catch in 1959 and catches observed during the other years.

Species Diversity

The total number of species in the fish community was an unambiguous index of species richness. The highest species number was observed in 1982, followed by 1998 and 1959; the lowest species number was found in 2008; and the species number in the other sampling years was relatively stable at approximately 25 species. The number of families in the fish catch from 1959 to 2011 showed the same fluctuating trend as species number (Figure 5a). The indices H', 1 — λ, J', and Margalef's R showed the comprehensive characteristics of the fish community's ecological diversity and heterogeneity. Margalef's R increased from 1959 to 1993, decreased through 2003, slightly increased in 2008, and exhibited another decrease in 2011. The value of J' slightly increased over the study period; however, H' and 1 — λ both showed a fluctuating, increasing trend from 1959 to 2011. The two diversity indices (H' and 1 — λ) increased from 1959 to 1982, decreased in 1993, increased in 1998, and decreased through 2003; H' increased in 2008 and then remained stable between 2008 and 2011, whereas 1 — λ greatly increased from 2008 to 2011 (Figure 5b).

FIGURE 3.

Trophic structure of the fish catch in the Yellow River estuary from 1959 to 2011 (x-axis labels indicate the trophic levels).

f03_65.jpg

FIGURE 4.

Cluster analysis dendrogram based on Bray—Curtis similarity (%) between samples of fish assemblages in the Yellow River estuary from 1959 to 2011.

f04_65.jpg

DISCUSSION

Variations in Community Structure and Diversity

In the Yellow River estuary, no more than 40 fish species were collected during the main spawning season in each study year from 1959 to 2011, with the exception of the 1982 season, during no more than 25 families were collected. According to the survey analysis, the fish species composition changed in the Yellow River estuary. Only a few species were found consistently in every sampling year, and most of these were pelagic species, including the Japanese Anchovy, Scaly Hairfin Anchovy, Smallhead Hairtail, Dotted Gizzard Shad, Madura Anchovy, and White Gunnel; two benthopelagic species, the Silver Pomfret and Small Yellow Croaker, were also collected in each study year. Values of J', H', and 1 — λ gradually increased from 1959 to 2011, but Margalef's R fluctuated, increasing from 1959 to 1993, decreasing through 2003, and increasing again in 2008. The high diversity of fish might be related to high primary production in this estuary, which forms the major spawning grounds and habitat for many commercial species in the Bohai Sea and Yellow Sea. In 1959, the dominant species in the fish catch were the Largehead Hairtail and Small Yellow Croaker, accounting for 93.9% of the total catch and exhibiting CPUEs greater than 60 kg/h. In recent years, pelagic species were the dominant species in the fish catch, but their CPUEs were less than 1 kg/h. Similar results were found during a study of the fishery resource structure and dynamics of the dominant species composition in Laizhou Bay (Jin and Deng 2000) and during a study of the ichthyoplankton composition in Laizhou Bay (Wang 2009). The larval abundance was primarily a measure of the spawning biomass and reproductive effort of the adult stock in each year, and long-term trends in larval abundance reflected trends in adult biomass. Several studies have shown that larval abundance is a good indicator of adult biomass (Moser et al. 2000, 2001).

TABLE 3.

Functional group composition of fish in the Yellow River estuary ecosystem during 1959–2011 (G1 = planktivores; G2 = planktivores/benthivores; G3 = benthivores; G4 = benthivores/piscivores; G5 = omnivores; G6 = mobile piscivores; G7 = elasmobranchs; G8 = roving piscivores).

t03_65.gif

FIGURE 5.

Changes in (a) the number of fish species or families and (b) fish diversity in the Yellow River estuary from 1959 to 2011 (indices: R = Margalef's richness index; J' = Pielou's evenness index; H'= Shannon—Weaver diversity index; 1 — λ = Lande's diversity index).

f05_65.jpg

In the present study, Engraulidae was the common dominant family in the fish catch during the study years (except 1959), particularly from 1982 to 2003. The engraulid catch accounted for more than 50% of the total catch. Two families, Trichiuridae (78.4%) and Sciaenidae (16.3%), were predominant components of the fish catch during 1959. In 2008, Stromateidae (29.8%), Engraulidae (18.8%), and Polynemidae (14.5%) were the dominant families in the total catch. Engraulidae (30.9%), Percidae (21.8%), and Sciaenidae (16.9%) were the dominant families in the total catch during 2011. Correspondingly, the MTL of the fish catch decreased from 1959 to 1998, increased slightly in 2003, maintained a stable level from 2003 to 2008, and then increased in 2011. Fish species in the catch were mainly distributed at trophic levels 3.5–4.5 from 1959 to 1993; thereafter, the MTL of the fish catch was mainly distributed from 3.0 to 4.0. Over the study period, the functional groups G6 and G5 were replaced by Gl and G2. In addition, distinct differences were found in the fish catch from 1959 to 2011 based on Bray— Curtis similarity analysis. The fish community structure in the Yellow River estuary ecosystem became simpler; regime shifts of the fish community increased, which would be helpful in restoring pelagic fish resources with high restoration potential (Jin and Deng 2000). Thus, with the increase in human activities and climate change, the fishery resource structure and the dominant species composition in the Yellow River estuary changed, the average fish catch declined, and small-sized, low-trophic-level pelagic fishes became the dominant species in the catch.

Threats to Fish Assemblage Structure

Changes in the fish assemblage structure within the Yellow River estuary are mainly due to human-induced disturbance and climate change. The anthropogenic activities include overfishing, dam construction, land reclamation, and eutrophication. Climate change includes alterations in SST, rainfall, and other related factors. Overfishing, dam construction, and climate change are among the most serious problems contributing to the variations in fish assemblage structure and fisheries.

Overfishing.—Overfishing is considered the key reason for the decline of fish stock abundance in the Yellow River estuary (Jin and Tang 1998; Jin and Deng 2000). For example, the biomass of the fishery resources declined continuously from 423.6 kg·haul-1 in 1959 to 164.6 kg·haul-1 in 1982, 37.7 kg·haul-1 in 1993, and less than 8 kg·haul-1 in 1998–2008, largely due to overfishing (Jin et al. 2013). Figure 6D illustrates the decrease in fish abundance with increasing total fishing effort in the Bohai Sea, particularly for the Japanese Anchovy and Scaly Hairfin Anchovy. Although small-sized fishing vessels (hp < 50 kW) dominated the fishing industry in the Yellow River estuary, they were characterized by high fishing intensity (total hp in 2010 was approximately 40 times that in 1959) due to the greater availability of fishing gears. Nonselective fishing gears had serious impacts on juveniles of the fishery-targeted species and greatly destroyed their habitats, thereby causing some migrant species to be extirpated and leading to a sharp decline in the fishery resources (Zhang et al. 2010b). The changes in the Yellow River estuary's fish assemblage structure directly impacted the recruitment and fisheries in the Bohai Sea and Yellow Sea (Jin and Deng 2000).

Overfishing is now widely recognized as one of the most significant anthropogenic activities (Edgar et al. 2005). Overfishing not only has direct impacts on the stock fluctuation of target species at high trophic levels (Hutchings and Baum 2005) but also affects fish communities and ecosystems via cascading ecosystem effects (Pinnegar et al. 2000). Overfishing also results in a decrease in the MTL of catches (Pauly et al. 1998) by altering the extent of top-down regulation of fish assemblage structure (Tegner and Dayton 2000). Overfishing causes changes in the food habits of some dominant species and alters food chains and food webs in marine ecosystem (Pauly et al. 1998; Jin et al. 2010); it also impacts the spatial and temporal distributions of some species. Previous studies have shown that fishing has depleted 50–70% of marine fish populations (Hilborn et al. 2003), and the trophic level in the global fishery catch decreased from 3.3 in the 1950s to 3.1 in 1994. In recent decades, the trophic level has decreased by 0.1 every 10 years (Pauly et al. 1998). Correspondingly, the trophic level in the Bohai Sea decreased from 4.1 in 1959 to 3.4 in 1998– 1999, and this decrease was higher than that observed worldwide (Zhang and Tang 2004). Because fisheries tend to target large, commercially important species, the removal of large, top-level predators can effectively reduce the amount of predation risk for smaller individuals, leading to an increased abundance of nontarget species. Nontarget species, particularly those with earlier maturity and smaller size, are generally more resistant to fishing pressure (Piet et al. 2009). Consequently, fluctuations in these small pelagic fishes change the biological structure of the community or ecosystem via the “wasp-waist” middle-trophic-level mechanism (Cury et al. 2000). The Japanese Anchovy, which is the key species of the food web and the main commercial species in the Yellow River estuary, has greatly declined since 1993, thus accelerating the changes in the estuarine food web and trophic levels (Jin and Deng 2000). These changes led to the succession in fisheries from long-lived, high-trophic-level, piscivorous fish to short-lived, low-trophic-level, planktivorous pelagic fish (Jin and Tang 1998; Pauly et al. 1998; Jin and Deng 2000; Savenkoff et al. 2007; Jin et al. 2010), and fisheries decreased to the point that some stocks in the ecosystem collapsed (Jackson et al. 2001).

In addition, studies have shown that the decline in Small Yellow Croaker stock abundance due to overfishing has caused the average body length of this species in the Yellow Sea to greatly decrease from 20 cm in the 1960s to 10 cm in the 2000s; a simpler age structure found in the Small Yellow Croaker population was also attributed to overfishing (Johannessen et al. 2001; Zhang et al. 2010a; Shan et al. 2011). Maturation patterns were seriously affected by continuous high fishing intensity, possibly leading to reversible changes in the age and length at 50% maturity (Ernande et al. 2004; Li 2011). The fishing-induced change in the ecosystem by selectively harvesting immature fish or only mature fish in populations has been characterized (Engelhard et al. 2004). Overfishing can lead to a decrease in stock abundance (Chen and Mello 1999); can affect population parameters, including growth rate, size (Hutchings and Baum 2005; de Roos et al. 2006), reproductive age, and age structure (Rochet 1998; Bianchi et al. 2000); and can cause variations in genetic structure (de Roos et al. 2006). This signals significant changes in the structure and function of the ecosystem.

FIGURE 6.

Correlation of (D) fish catch (kg/h) in the Yellow River estuary and (A) the Southern Oscillation Index (SOI), (B) monthly sea surface temperature (SST) anomalies, (C) warm and cold SST phases, (E) annual basinwide precipitation (mm/year) in the Yellow River drainage basin, and (F) annual water discharge (pink line; 109 m3/year) and annual sediment flux (deep-blue line;109 metric tons/year) at Lijin during 1950–2011 (green bars show the years of construction for main dams on the Yellow River).

f06_65.jpg

Climate change.—There is considerable evidence that pelagic species naturally dominate global ecosystems and that the large fluctuations in small pelagic species are driven by climate change rather than fishing (Rijnsdorp et al. 2009; Alheit and Bakun 2010). In recent years, the fishery catch from the Bohai Sea was approximately 1.3 million metric tons, including 0.5 million metric tons from the Yellow River estuary. The dominant species in the catch were mainly warmwater and warm-temperate pelagic species, and the fishery abundance increased during warm periods or 1–2 years after a warm period (Figure 6A–E). Recent studies have revealed that regime shifts, decadal-scale variability in atmospheric and oceanic environments, or a combination of these strongly influence the dynamics of fish stocks and ecosystems (Stige et al. 2006; Perry et al. 2010), particularly for pelagic species. In addition, long-term variability in the abundance of larval fish is strongly affected by climate; there was an 85% increase in larval abundance from the cold period to the warm period, and 71% had a significant relationship with environmental signals (Tian et al. 2004). Growing evidence suggests that the dynamics of the demersal fish community are linked with climate variability (Attrill and Power 2002; Tian et al. 2004). In the present study, an understanding of the link between fishery species and climate change includes (1) changes in distribution due to the changes in SST (Perry et al. 2010; Dulvy et al. 2008; Brander 2010); (2) changes in the trophic structure via changes in primary and secondary production (Salen-Picard et al. 2002); (3) changes in stock abundance, such as recruitment, growth, survival, reproduction, and migration behavior (Reist et al. 2006; Pörtner et al. 2007; Li 2011); and (4) changes in the diversity of the fish community (Butchart et al. 2010; Powers et al. 2010). Previous studies have shown that the spawning, recruitment, and distribution of fish were closely related to climatic indices, such as the North Atlantic Oscillation and ENSO (Alheit et al. 2005; Rojas-Mendez et al. 2008). The growth of Zooplankton and phytoplankton also changed with the increase in SST and further affected the predator—prey relationship. For example, changes in SST caused a mismatch between the fish spawning period and the algal bloom in spring, leading to starvation of the larvae and juveniles and further impacting the fish community structure, distribution, and abundance (Fan et al. 2001). Such changes in turn lead to changes in the marine ecosystem (Reid et al. 2001; Beaugrand et al. 2004). For example, distribution of the Skipjack Tuna Katsuwonus pelamis increased with the expansion of the ENSO warm pool, and the Skipjack Tuna fishing grounds extended to 6,000 km along the equator (Lehodey et al. 1997); furthermore, distribution areas of the Peruvian Anchovy Engraulis ringens extended to southern Peru, and their abundance decreased during the ENSO period. The abundance of other pelagic species (e.g., Pacific Sardine Sardinops sagax, Chilean Jack Mackerel Trachurus murphyi [also known as Inca Scad], Chub Mackerel Scomber japonicus, and Longnose Anchovy Anchoa nasus) increased during and after the ENSO period, and the Shannon—Weaver diversity index increased from 0.87 to 1.23–1.70 during the ENSO period in 1997–1998 (Ñiquen and Bouchon 2004). The dynamics of Pacific Herring Clupea pallasii corresponded to the 36-year wet— dry period and 36 years of atmospheric circulation (Tang 1981). Other threats.—The recent trend in Asia has been toward more and larger dams. Through 2006, a total of 2,752 dams or reservoirs were built in the Yellow River basin; collectively, these reservoirs hold more than 77,500 million m3, including 22 mid-size and large reservoirs that hold more than 68,200 million m3 and thus account for 88% of the total water stor- age. The Sanmenxia, Liujiaxia, Longyangxia, and Xiaolangdi dams were constructed in 1960, 1968, 1985, and 1999, respectively, causing declines in sediment flux and runoff into the sea (Figure 6F); zero flow was observed in the Yellow River during 1997. The decreases in sediment flux and runoff were directly responsible for coastal erosion in the Yellow River estuary basin; additionally, degradation of ecological service function and the frequency of pollution accidents and harmful algal blooms have increased. Consequently, the marine ecological environment has been destroyed, which directly threatens biological reproduction in and ecological security of the inshore ecosystem (Tang et al. 2010). With the decrease in runoff from the Yellow River, the diversity, abundance, and recruitment of fishery species in the Bohai Sea decreased, particularly for the fleshy prawn Fenneropenaeus chinensis. Changes in sediment flux into the sea caused alterations in the Yellow River estuary coastline, thereby changing the circulation fields in the coastal waters. These changes further impacted the distribution of fleshy prawn eggs and juveniles, eventually leading to the loss of fleshy prawn eggs and juvenile habitat in Laizhou Bay (Huang and Su 2002). In addition, some studies have reported that the changes in Yellow River runoff were related to climate changes in the basin. Precipitation accounted for 40–50% of the changes in Yellow River runoff (Wang et al. 2006). Based on an analysis of runoff, water consumption, and precipitation at the main hydrological stations from 1950 to 2005, Wang et al. (2006) reported that the global ENSO occurrence directly affected basinwide precipitation and accounted for 51% of the changes in Yellow River runoff, whereas dam construction accounted for 49%.

Land reclamation, eutrophication, pollution, and aquaculture in the coastal waters are also serious problems in the Yellow River estuary, as they contribute to the decline in fish biodiversity and the changes in fish assemblage structure. The effects of these anthropogenic factors on fish assemblage structure in the Yellow River estuary have been discussed in detail by other authors (Zhao et al. 2000; Cui et al. 2005; Li 2011). Land reclamation, eutrophication, pollution, and aquaculture in coastal waters have destroyed the spawning grounds and habitats of many species and have affected fish migration by causing changes in hydrological characteristics, leading to declines in fishery resources.

Conclusions

Fish assemblage structure and fish diversity in the Yellow River estuary ecosystem have changed, and the estuary is at risk for being significantly compromised by overfishing, climate change, dam construction, and pollution. These problems are causing the decline of traditional fishing industries and a reduction in biodiversity in the Yellow River estuary. Currently, certain traditional commercially targeted fishes (e.g., Largehead Hairtail, Red Seabream, and Pacific Herring) are locally extinct, and the dominant species have rapidly shifted from highly valued, high-trophic-level, large-sized demersal species with complicated age structures to low-value, low-trophic-level, small-sized pelagic species with simple age structures, resulting in major disruption of the ecological cycle and hindering the restoration of fishery resources.

ACKNOWLEDGMENTS

This work was supported by the National Key Basic Research of the Ministry of Science and Technology of China (Grant Number 2010CB951204), the Special Fund for Agro-Scientific Research in the Public Interest (Grant Number 200903005), the Promotive Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (Grant Number BS2012HZ030), and the Taishan Scholar Program of Shandong Province.

REFERENCES

1.

J. Alheit , and A. Bakun . 2010. Population synchronies within and between ocean basins: apparent teleconnections and implications as to physical—biological linkage mechanisms. Journal of Marine Systems 79:267–285. Google Scholar

2.

J. Alheit , C. Möllmann , J. Dutz , G. Kornilovs , P. Loewe, V. Mohrholz , and N. Wasmund . 2005. Synchronous ecological regime shifts in the central Baltic and the North Sea in the late 1980s. ICES Journal of Marine Science 62:1205–1215. Google Scholar

3.

M. J. Attrill , and M. Power . 2002. Climatic influence on a marine fish assemblage. Nature 417:275–278. Google Scholar

4.

R. J. Beamish , G. A. McFarlane , and J. R. King . 2000. Fisheries climatology: understanding decadal scale processes that naturally regulate British Columbia fish populations. Pages 94–139 in P. J. Harrison and T. R. Parsons , editors. Fisheries oceanography: an integrative approach to fisheries ecology and management. Blackwell Science, London. Google Scholar

5.

G. Beaugrand 2004. The North Sea regime shift: evidence, causes, mechanisms and consequences. Progress in Oceanography 60:245–262. Google Scholar

6.

D. R. Bellwood , T. P. Hughes , C. Folke , and M. Nyström . 2004. Confronting the coral reef crisis. Nature 429:827–833. Google Scholar

7.

G. Bianchi , H. Gislason , K. Graham , L. Hill , X. Jin , K. Koranteng , S. Manickchand-Heileman , I. Paya , K. Sainsbury , F. Sanchez , and K. Zwanenburg . 2000. Impact of fishing on size composition and diversity of demersal fish communities. ICES Journal of Marine Science 57:558–571. Google Scholar

8.

K. Brander 2010. Impacts of climate change on fisheries. Journal of Marine Systems 79:389–102. Google Scholar

9.

S. H. M. Butchart , M. Walpole , B. Collen , A. van Strien , J. P. W. Scharlemann , R. E. A. Almond , J. E. M. Baillie , B. Bomhard , C. Brown , J. Bruno , K. E. Carpenter , G. M. Carr , J. Chanson , A. M. Chenery , J. Csirke , N. C. Davidson , F. Dentener , M. Foster , A. Galli , J. N. Galloway , P. Genovesi , R. D. Gregory , M. Hockings , V. Kapos , J. F. Lamarque , F. Leverington , J. Loh , M. A. McGeoch , L. McRae , A. Minasyan , M. Hernández Morcillo , T. E. E. Oldfield , D. Pauly , S. Quader , C. Revenga , J. R. Sauer , B. Skolnik , D. Spear , D. Stanwell-Smith , S. N. Stuart , A. Symes , M. Tierney , T. D. Tyrrell, J. C. Vié, and R. Watson . 2010. Global biodiversity: indicators of recent declines. Science 328:1164–1168. Google Scholar

10.

Y. Chen , and L. G. S. Mello . 1999. Growth and maturation of cod (Gadus morhua) of different year classes in the northwest Atlantic, NAFO subdivision 3Ps. Fisheries Research 42:87–101. Google Scholar

11.

K. R. Clarke , and R. M. Warwick . 2001. Change in marine communities: an approach to statistical analysis and interpretation, 2nd edition. PRIMER-E, Plymouth, UK. Google Scholar

12.

Y. Cui , B. J. Chen , and J. F. Chen . 2005. [Evaluation on self-pollution of marine culture in the Yellow Sea and Bohai Sea]. Chinese Journal of Applied Ecology 16:180–185. (In Chinese.) Google Scholar

13.

P. Cury , A. Bakun , R. J. M. Crawford , A. Jarre , R. A. Quiñones, L. J. Shannon, and H. M. Verheye . 2000. Small pelagics in upwelling systems: patterns of interaction and structural changes in “wasp-waist” ecosystems. ICES Journal of Marine Science 57:603–618. Google Scholar

14.

A. M. de Roos , D. S. Boukal , and L. Persson . 2006. Evolutionary regime shifts in age and size at maturation of exploited fish stocks. Proceedings of the Royal Society of London B 273:1873–1880. Google Scholar

15.

N. K. Dulvy , S. I. Rogers , S. Jennings , V. Stelzenmüller, S. R. Dye, and H. R. Skjoldal . 2008. Climate change and deepening of the North Sea fish assemblage: a biotic indicator of warming seas. Journal of Applied Ecology 45:1029–1039. Google Scholar

16.

G. J. Edgar , C. R. Samson , and N. S. Barrett . 2005. Species extinction in the marine environment: Tasmania as a regional example of overlooked losses in biodiversity. Conservation Biology 19:1294–1300. Google Scholar

17.

M. Elliott , and D. S. McLusky . 2002. The need for definitions in understanding estuaries. Estuarine, Coastal and Shelf Science 55:815–827. Google Scholar

18.

M. Elliott , A. K. Whitfield , I. C. Potter , S. J. M. Blaber , D. P. Cyrus, F. G. Nordlie, and T. D. Harrison . 2007. The guild approach to categorizing estuarine fish assemblages: a global review. Fish and Fisheries 8:241–268. Google Scholar

19.

G. H. Engelhard , and M. Heino . 2004. Maturity changes in Norwegian springspawning herring Clupea harengus: compensatory or evolutionary responses? Marine Ecology Progress Series 272:245–256. Google Scholar

20.

B. Ernande , U. Dieckmann , and M. Heino . 2004. Adaptive changes in harvested populations: plasticity and evolution of age and size at maturation. Proceedings of the Royal Society of London B 271:415–423. Google Scholar

21.

W. Fan , Y. H. Cheng , and X. Q. Shen . 2001. Effects of climate changes and human activities on fishery resources. Journal of Fishery Sciences of China 8:91–94. Google Scholar

22.

R. Hilborn , T. P. Quinn , D. E. Schindler , and D. E. Rogers . 2003. Biocomplexity and fisheries sustainability. Proceedings of the National Academy of Sciences of the USA 100:6564–6568. Google Scholar

23.

D. J. Huang , and J. L. Su . 2002. The effects of the Huanghe River Delta on the circulation and transportation of larvae. Acta Oceanologica Sinica 24:104–111. Google Scholar

24.

J. A. Hutchings , and J. K. Baum . 2005. Measuring marine fish biodiversity: temporal changes in abundance, life history, and demography. Philosophical Transactions of the Royal Society of London B 360:315–338. Google Scholar

25.

D. A. Jackson , P. R. Peres-Neto , and J. D. Olden . 2001. What controls who is where in freshwater fish communities—the roles of biotic, abiotic, and spatial factors. Canadian Journal of Fisheries and Aquatic Sciences 58:157–170. Google Scholar

26.

N. C. James , A. K. Whitfield , and P. D. Cowley . 2008. Long-term stability of the fish assemblages in a warm-temperate South African estuary. Estuarine, Coastal and Shelf Science 76:723–738. Google Scholar

27.

S. Jennings , and J. L. Blanchard . 2004. Fish abundance with no fishing: predictions based on macroecological theory. Journal of Animal Ecology 73:632–642. Google Scholar

28.

Y. Z. Jiang 2008. Variations in fish community structure and biodiversity in the northern East China Sea. Master's thesis. Chinese Academy of Sciences, Beijing. Google Scholar

29.

X. S. Jin , and J. Y. Deng . 2000. Variations in community structure of fishery resources and biodiversity in the Laizhou Bay, Shandong. Biodiversity Science 8:65–72. Google Scholar

30.

X. S. Jin , X. J. Shan , X. S. Li , J. Wang, Y. Cui, and T. Zuo . 2013. Long-term changes in the fishery ecosystem structure of Laizhou Bay, China. Science China Earth Sciences 56:366–374. DOI: 10.1007/s11430-012-4528-7. Google Scholar

31.

X. S. Jin , and Q. S. Tang . 1998. Fishery resource structure, quantity distribution and their dynamics in the Bohai Sea. Journal of Fishery Sciences of China 5:18–24. Google Scholar

32.

X. S. Jin , B. Zhang , and Y. Xue . 2010. The response of the diets of four carnivorous fishes to variations in the Yellow Sea ecosystem. Deep-Sea Research, Part II 57:996–1000. Google Scholar

33.

A. Johannessen , S. A. Iversen , X. Jin, F. Li, and X. Zhao . 2001. Biological investigations of anchovy and some selected fish species caught during the R/V “Bei Dou” surveys 1984–1999. Marine Fisheries Research 22:45–56. Google Scholar

34.

R. Lande 1996. Statistics and partitioning of species diversity, and similarity among multiple communities. Oikos 76:5–13. Google Scholar

35.

P. Lehodey , M. Bertignac , J. Hampton, A. Lewis, and J. Picaut . 1997. El Niño southern oscillation and tuna in the western Pacific. Nature 389:715–718. Google Scholar

36.

Z. L. Li 2011. Interannual changes in biological characteristics and population dynamics of small Yellow Croaker Larimichthys poly actis, Pacific Cod Gadus macrocephalus and Anglerfish Lophius litulon in the Bohai Sea and Yellow Sea. Doctoral dissertation. Chinese Academy of Science, Beijing. Google Scholar

37.

Z. Liu , H. Wei , and S. N. Jiang . 2003. [Characteristics of seasonal variation of monthly mean temperature and salinity fields in the Bohai Sea and analysis of the related dynamics]. Periodical of Ocean University of China 33(1):7–4. (In Chinese.) Google Scholar

38.

D. R. Margalef 1958. Information theory in ecology. General System 3:36–71. Google Scholar

39.

F. Martinho , R. Leitão , J. M. Neto , H. Cabrai, F. Lagardère, and M. A. Pardal . 2008. Estuarine colonization, population structure and nursery functioning for 0-group Sea Bass (Dicentrarchus labrax), flounder (Platichthys flesus) and sole (Solea solea) in a mesotidal temperate estuary. Journal of Applied Ichthyology 24:229–237. Google Scholar

40.

F. Martinho , R. Leitão , J. M. Neto , H. N. Cabrai, J. C. Marques, and M. A. Pardal . 2007. The use of nursery areas by juvenile fish in a temperate estuary, Portugal. Hydrobiologia 587:281–290. Google Scholar

41.

F. Micheli , and B. S. Halpern . 2005. Low functional redundancy in coastal marine assemblages. Ecology Letters 8:391–400. Google Scholar

42.

H. G Moser , R. L. Charter , P. E. Smith , D. A. Ambrose , W. Watson , S. R. Charter , and E. M. Sandknop . 2001. Distributional atlas of fish larvae and eggs in the Southern California Bight region: 1951–1998. California Cooperative Oceanic Fisheries Investigations Atlas 34. Google Scholar

43.

H. G. Moser , R. L. Charter , W. Watson , D. A. Ambrose , J. L. Butler, S. R. Charter, and E. M. Sandknop . 2000. Abundance and distribution of rockfish (Sebastes) larvae in the Southern California Bight in relation to environmental conditions and fishery exploitation. California Cooperative Oceanic Fisheries Investigations Reports 41:132–147. Google Scholar

44.

R. A. Myers , and B. Worm . 2003. Rapid worldwide depletion of predatory fish communities. Nature 423:280–283. Google Scholar

45.

D. Nicolas , J. Lobry, O. Le Pape , and P. Boët . 2010. Functional diversity in European estuaries: relating the composition of fish assemblages to the abiotic environment. Estuarine, Coastal and Shelf Science 88:329–338. Google Scholar

46.

M. Ñiquen , and M. Bouchon . 2004. Impact of El Niño events on pelagic fisheries in Peruvian waters. Deep-Sea Research, Part II 51:563–574. Google Scholar

47.

D. Pauly , V. Christensen , J. Dalsgaard, R. Froese, and F. Torres Jr . 1998. Fishing down marine food webs. Science 279:860–863. Google Scholar

48.

D. Pauly , V. Christensen , S. Guénette , T. J. Pitcher , U. R. Sumaila , C. J. Walters, R. Watson, and D. Zeller . 2002. Towards sustainability in world fisheries. Nature 418:689–695. Google Scholar

49.

R. L Perry , P. Cury , K. Brander , S. Jennings , C. Möllmann , and B. Planque . 2010. Sensitivity of marine systems to climate and fishing: concepts, issues and management responses. Journal of Marine Systems 79:427–435. Google Scholar

50.

E. C. Pielou 1975. Ecological diversity. Wiley, New York. Google Scholar

51.

G. J. Piet , R. van Hal , and S. P. R. Greenstreet . 2009. Modelling the direct impact of bottom trawling on the North Sea fish community to derive estimates of fishing mortality for non-target fish species. ICES Journal of Marine Science 66:1985–1998. Google Scholar

52.

J. K. Pinnegar , N. V. C. Polunin , P. Francour , F. Badalamenti , R. Chemello , M. L. Harmelin-Vivien, B. Hereu , M. Milazzo , M. Zabala, G. D'Anna, and C. Pipitone . 2000. Trophic cascades in benthic marine ecosystems: lessons for fisheries and protected-area management. Environmental Conservation 27:179–200. Google Scholar

53.

H. O. Pörtner , and R. Knust . 2007. Climate change affects marine fishes through the oxygen limitation of thermal tolerance. Science 315:95–97. Google Scholar

54.

J. E. Powers 2010. Fisheries: measuring biodiversity in marine ecosystems. Nature 468:385–386. Google Scholar

55.

K. M. Purcell , P. L. Klerks , and P. L. Leberg . 2010. Adaptation to sea level rise: does local adaptation influence the demography of coastal fish populations? Journal of Fish Biology 77:1209–1218. Google Scholar

56.

P. C. Reid , M. de Fatima Borges , and E. Svendsen . 2001. A regime shift in the North Sea circa 1988 linked to changes in the North Sea Horse Mackerel fishery. Fisheries Research 50:163–171. Google Scholar

57.

J. D. Reist , F. J. Wrona , T. D. Prowse , M. Power , J. B. Dempson , R. J. Beamish , J. R. King, T. J. Carmichael, and C. D. Sawatzky . 2006. General effects of climate change on Arctic fishes and fish populations. Ambio 35:370–380. Google Scholar

58.

A. D. Rijnsdorp , M. A. Peck , G. H. Engelhard, C. Möllmann, and J. K. Pinnegar . 2009. Resolving the effect of climate change on fish populations. ICES Journal of Marine Science 66:1570–1583. Google Scholar

59.

M. J. Rochet 1998. Short-term effects of fishing on life history traits of fishes. ICES Journal of Marine Science 55:371–391. Google Scholar

60.

J. A. Rojas-Mendez , and C. J. Robinson Mendoza . 2008. Effects of ENSO 1997–1998 on the distribution of small pelagic fish off the west coast of Baja California. International Journal of Environment and Health 2:45–63. Google Scholar

61.

C. Salen-Picard , A. M. Darnaude , D. Arlhac , and M. L. Harmelin-Vivien . 2002. Fluctuations of macrobenthic populations: a link between climate-driven river run-off and sole fishery yields in the Gulf of Lions. Oecologia 133:380–388. Google Scholar

62.

C. Savenkoff , M. ECastonguay , D. Chabot , M. O. Hammill, H. Bourdages, and L. Morissette . 2007. Changes in the northern Gulf of St. Lawrence ecosystem estimated by inverse modelling: evidence of a fishery-induced regime shift? Estuarine, Coastal and Shelf Science 73:711–724. Google Scholar

63.

J. Selleslagh , R. Amara , P. Laffargue , S. Lesourd, M. Lepage, and M. Girardin . 2009. Fish composition and assemblage structure in three eastern English Channel macrotidal estuaries: a comparison with other French estuaries. Estuarine, Coastal and Shelf Science 81:149–159. Google Scholar

64.

X. J. Shan , Z. L. Li, F. Q. Dai, and X. S. Jin . 2011. Seasonal and annual variations in biological characteristics of small Yellow Croaker Larimichthys polyactis in the central and southern Yellow Sea. Progress in Fishery Sciences 32(6):1–8. Google Scholar

65.

C. E. Shannon , and W. Weaver . 1949. The mathematical theory of communication. University of Illinois Press, Urbana. Google Scholar

66.

L. C Stige , G. Ottersen , K. Brander , K. S. Chan , and N. C. Stenseth . 2006. Cod and climate: effect of the North Atlantic oscillation on recruitment in the North Atlantic. Marine Ecology Progress Series 325:227–241. Google Scholar

67.

Q. S. Tang 1981. A preliminary study on cause of generation fluctuation of the Yellow Sea Herring Clupea harengus pallasi. Transactions of Oceanology and Limnology 2:38–45. Google Scholar

68.

Q. S. Tang , J. L. Su , and J. Zhang . 2010. China GLOBEC II: a case study of the Yellow Sea and East China Sea ecosystem dynamics. Deep-Sea Research, Part II 57:993–995. Google Scholar

69.

M. J. Tegner , and P. K. Dayton . 2000. Ecosystem effects of fishing in kelp forest communities. ICES Journal of Marine Science 57:579–589. Google Scholar

70.

Y. J. Tian , H. Kidokoro , and T. Watanabe . 2006. Long-term changes in the fish community structure from the Tsushima warm current region of the Japan/East Sea with an emphasis on the impacts of fishing and climate regime shift over the last four decades. Progress in Oceanography 68: 217–237. Google Scholar

71.

Y. J. Tian , Y. Ueno, M. Suda, and T. Akamine . 2004. Decadal variability in the abundance of Pacific Saury and its response to climatic/oceanic regime shifts in the northwestern subtropical Pacific during the last half century. Journal of Marine Systems 52:235–257. Google Scholar

72.

A. Y. Wang 2009. Preliminary study of the ichthyoplankton assemblage structure in Laizhou Bay in spring and its correlation with environmental factors. Master's thesis. Ocean University of China, Qingdao. Google Scholar

73.

H. J. Wang , Z. S. Yang , Y. Saito, J. P. Liu, and X. X. Sun . 2006. Interannual and seasonal variation of the Huanghe (Yellow River) water discharge over the past 50 years: connections to impacts from ENSO events and dams. Global and Planetary Change 50:212–225. Google Scholar

74.

J. M. Yang 2001. A study on food and trophic levels of Baohai Sea fish. Modern Fisheries Information 16(10):10–19. Google Scholar

75.

S. Yasunaka , and K. Hanawa . 2002. Regime shifts found in the northern hemisphere SST field. Journal of the Meteorological Society of Japan 80:119–135. Google Scholar

76.

YRCC (Yellow River Conservancy Commission). 1950–2009. Bulletin of sediments and runoff for the Yellow River, 60 reports. Available:  http://www.yellowriver.gov.cn/nishagonggao/. (April 2013). Google Scholar

77.

B. Zhang 2005. Preliminary studies on marine food web and trophodynamics in China coastal seas. Doctoral dissertation. Ocean University of China, Qingdao. Google Scholar

78.

B. Zhang , and Q. S. Tang . 2004. The studies on trophic class of the major species at high trophic level in the Bohai, the Yellow Sea and the East China Sea. Advances in Marine Sciences 22:393–404. Google Scholar

79.

B. Zhang , Q. S. Tang , and X. S. Jin . 2007. Functional groups of fish assemblages and their major species at high trophic level in the East China Sea. Journal of Fishery Sciences of China 14:939–948. Google Scholar

80.

G. Z. Zhang , X. S. Li , X. S. Jin, J. C. Zhu, and F. Q. Dai . 2010a. Changes of biological characteristics of small Yellow Croaker (Larimichthys polyactis) in the central and southern Yellow Sea. Acta Ecologica Sinica 30:6854–6861. Google Scholar

81.

X. Zhang , X. M. Zhang , and T. X. Gao . 2010b. Comparative analysis on catch composition with two fishing gears at Yellow River estuary in spring. South China Fisheries Science 6:59–67. Google Scholar

82.

Z. Y. Zhao , and L. H. Kong . 2000. Environmental status quo and protection countermeasures in Bohai marine areas. Research of Marine Science 13(2):23–27. Google Scholar

83.

P. Zhuang , Y. H. Wang , and S. F. Li . 2006. Fishes of the Yangtze River estuary. Shanghai Science and Technology Press, Shanghai, China. Google Scholar
© American Fisheries Society 2013
Xiujuan Shan "Long-Term Changes in Fish Assemblage Structure in the Yellow River Estuary Ecosystem, China," Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science 5(5), 65-78, (1 May 2013). https://doi.org/10.1080/19425120.2013.768571
Received: 30 August 2012; Accepted: 11 January 2013; Published: 1 May 2013
Back to Top