Interacciones troficas en el ecosistema de surgencia del norte de Chile, ano 1997.
In the last three decades scientists and managers have been recognizing the need for incorporating wider ecosystem considerations into fisheries management (FAO, 2003; Parsons 2005; Constable 2011). The necessity of an ecosystem approach to fisheries (EAF) results from i) the increasing knowledge on stock dynamics and their relationships with their physical and biological environment (Pauly et al., 1998; Neira & Arancibia, 2002; Shannon & Cury, 2003), and ii) the pervasive negative impacts of fishing on target species and their ecosystems (Pauly et al., 2000; Shannon & Cury, 2003; Heymans et al, 2004).
Multispecies, community and ecosystem models are expected to complement the traditional fisheries management based only on single-species models, and then increasing societal capacity to attain sustainable fisheries (Bostford et al, 1997). Several modelling platforms have been developed and applied to marine ecosystems with the aim of better understanding their structure and function, and to support EAF (Plaganyi, 2007). Among them, the Ecopath with Ecosim approach (EwE) is a useful family of models that allow the analysis of trophic interactions in aquatic systems (Polovina, 1984; Christensen & Pauly, 1992; Walters et al, 1997; Christensen & Walters, 2000). EwE is useful and practical for summarizing information about the main components in a system and their trophic relationships, allowing descriptions and comparisons among ecosystems (Christensen & Pauly, 1993; Jarre-Teichmann & Christensen, 1998; Jarre-Teichmann et al, 1998; Shannon & Jarre-Teichmann 1999; Neira, 2003; Neira & Arancibia, 2004; Arancibia et al, 2010).
The upwelling ecosystem off northern Chile (UENCh) sustains an important purse-seine fishery targeting anchovy (Engraulis ringens), sardine (Sardinops sagax), mackerel (Scomber japonicus) and jack mackerel (Trachurus murphyi). However, in the 90's decade, landings of these pelagic species exhibited a sustained declining trend (Fig. 1). This situation has strongly impacted the local economy in northern Chile, with a series of fusions (first) and closing (more recently) of several fishing companies, which resulted in a noticeable contraction of the fleet (Aliaga et al., 2001; Canon, 2004).
Fluctuations of fish populations can be explained by several factors such as fishing pressure, trophic interactions and environmental variability such as intensity of the upwelling front and temperature change produced by El Nino Southern Oscillation (ENSO) events, among others (Serra, 1986; Bernal, 1990; Yanez et al., 2001; Blanco et al, 2002). The inter-annual variability in the oceanographic and atmospheric conditions in the UENCh are determined by large-scale events such ENSO (Montecinos et al., 2003), which presents a warm phase (known as El Nino) and a cold phase (known as La Nina). In the Chilean coast, the warm phase of ENSO is determined mostly by ocean-atmosphere processes, allowing the transport of equatorial waters towards the south (Thomas et al, 2001; Ulloa et al, 2001). However, fisheries studies carried out in northern Chile do not normally assess ecological interactions among populations or the effects of the physical environment on the dynamics of target species. On the other hand, it is necessary to advance our
understanding on the trophic relationships of target species, the community structure in which they inhabit, and the potential effects of the fishery on target species in this system.
Medina et al. (2007) modelled the pelagic food web in the upwelling ecosystem of northern Chile (18[degrees]20'-24[degrees]00'S), to describe trophic interactions and energy flows among 13 functional groups during 1989, a period of rather normal oceanographic conditions (i.e., non ENSO). In this paper we built a model representing the same food web in year 1997, which is a period characterized by the presence of ENSO (McPhaden, 1999; Escribano et al, 2004). The aim of this paper is to describe prey-predator relationships, community structure and trophic flows in the UENCh in 1997 and compare these system features with those in year 1989 informed by Medina et al. (2007).
MATERIALS AND METHODS
Study area and study period
The study area corresponds to the upwelling ecosystem in northern Chile (UENCh) that extends from 18[degrees]20'S to 24[degrees]00'S, and from the coastline to 60 nm westward, encompassing a total surface area of 65,000 [km.sup.2] (Fig. 2). This area has been delimited considering the distribution of the fishing fleets (Serra, 1986), and the influence of the coastal upwelling (Thiel et al, 2007). The oceanography of the study area is influenced by the Humboldt Current System, which is characterized by high biological and fish production (Carr, 2002). This is also the main fishing area for the industrial and artisanal purse-seine fleets targeting pelagic fish such anchovy, mackerel, jack mackerel and sardine (Castillo et al, 1997, 1999; Braun et al, 1999). In year 2011, the UENCh provided about 31% of total fish landings in Chile (www.sernapesca.cl).
The main oceanographic features in the study area are low turbulence, a quasi permanent positive anomaly of the sea surface temperature with a narrow coastal band of cold water (Bernal, 1990; Cubillos et al, 1998), low frequency events (ENSO) with inter-annual periodicity (Fuenzalida, 1992), while high frequency events (e.g., upwelling) are permanent throughout the year (Fuenzalida, 1990, Shaffer et al., 1999; Blanco et al., 2001).
In this paper we selected the year 1997 to build the food web model because of the presence of a strong ENSO conditions in the whole area. However, considering that the snapshot model corresponds to one year, we assume steady-state conditions and mass-balance for all functional groups (sensu Christensen & Pauly, 1993).
Describing the food web model for northern Chile
EwE is an ecotrophic model that incorporates interactions among functional groups in an ecosystem. It is based in two main equations focusing on (1) the usage of the production, and (2) the mass-balance of each group included in the model.
The production of each group i can be split in the following components:
Production = catches + predation mortality + biomass accumulation + net migration + other mortalities
The mathematical equation is:
[P.sub.i] = [Y.sub.i] + [B.sub.i]M [2.sub.i] + E + B[A.sub.i] + [B.sub.i](1 - E[E.sub.i]) (1)
where: [P.sub.i] is total production rate for group i; [Y.sub.i] is total catch for i; Bi is total biomass of i; [M2.sub.i] is predation mortality of for i; Ei is the net migration rate for i (emigration minus immigration); B[A.sub.i] is the biomass accumulation for i; Pi (1 - E[E.sub.i]) = BM0i is other mortalities for i, those independent from predation and catches. Equation (1) can be re-expressed as: ~ [B.sub.i](P/B) - [n.summation over (j=1)] [B.sub.j] [(Q/B).sub.i] D[C.sub.ij] - (P/B) [B.sub.i](1 - E[E.sub.i]) - [Y.sub.i] - [E.sub.i] - B[A.sub.i] = 0 (1a)
where (P/B)i is the production to biomass ratio equal to total mortality (Z) under steady-state conditions (sensu Allen, 1971); (Q/B) is consumption to biomass ratio; D[C.sub.ji] is the fraction (in weight) of the prey i in the diet of the predator j; E[E.sub.i] is the ecotrophic efficiency of i that corresponds to the fraction of the production of group i that is utilized within the system as predation and/or catches; [E.sub.i] corresponds to the exports of i (either as emigration or catches).
The mass-balance for each group is given by:
Q = P + R + U (2)
where Q is prey consumption, P is production, R is respiration, U is unassimilated food. This equation defines the consumption as the sum of gonadal and somatic growth, metabolic costs and excretion products.
Building the food web model
The model considers 21 functional groups from primary producers to top predators. The model is focused on target species and their main prey and predators. The groups are: phytoplankton, microzoo-plankton, mesozooplankton (copepods), macrozoo-plankton (euphausiids), gelatinous zooplankton (siphonphores and salps), mackerel (Scomber japonicus), sardine (Sardinops sagax), anchovy (Engraulis ringens), mesopelagic fish (Myctophidae), jack mackerel (Trachurus murphyi), demersal fish (black cusk-eel Genypterus maculatus and Genypterus chilensis red cusk-eel (check www.fishbase.org); southern grut Cilus gilberti and rock seabass Paralabrax humeralis), jumbo squid (Dosidicus gigas), palm ruff (Seriolella violacea), Eastern Pacific bonito (Sarda chilensis), common dolphinfish (Coryphaena hippurus), swordfish (Xiphias gladius), pelagic sharks (short fin mako Isurus oxirynchus and blue shark Prionace glauca), sea lions (Otaria flavescens), cetaceans (small cetaceans and dolphins), marine birds (guanay cormorants Leucocarbo bougainvilli, Peruvian booby Sula variegata and pelicans Pelecanus thagus), and detritus.
The model was built using available information on landings, life history parameters and biomass assessments for each functional group in the ecosystem model. The information was obtained from published literature, reports and thesis. We estimate some parameters using empirical equations that integrate information reported for the study area. Table 1 presents the corresponding source and estimation method for input parameters in each functional group.
When parameters were unknown, they were calculated by solving equations 1 and 2 under the assumption that E[E.sub.i] = 0.999. The above implies that EwE calculates the unknown parameter (e.g., Bi, P/Bi, Q/Bi) for each i assuming that M0 for that group is 0.001.
The mass-balance assumption for each group was verified considering: i) that 0 < E[E.sub.i] < 1; and that ii) the gross food conversion (G[E.sub.i] = [P.sub.i]/[Q.sub.i]) was 0.1 < GE < 0.35 (Christensen & Pauly, 1992). When either EE or GE was beyond the accepted range, we performed changes in inputs parameters (B, P/B, Q/B and DC) following criteria proposed by Christensen et al. (2005).
Network analysis routines proposed by Ulanowicz (1986, 1995) and Ulanowicz & Kay (1991) included in EwE were run to calculate ecological indicators and flow indices based on theoretical concepts developed by Odum (1969) and Ulanowicz (1986). With these routines we calculated and compared the distribution of biomass and flows by aggregated trophic level and the trophic transfer efficiency between trophic levels. We quantified and compared the total system flow ([F.sub.T]), the Finn's cycling index (FCI), which corresponds to the fraction of Ft used for cycling (Finn, 1976 fide Christensen & Pauly, 1992), and the connectance index (CI), which is the ratio between the actual trophic unions in the model and the maximum theoretical number that could be realized. The mixed trophic impact routine (MTI) included in EwE was used to quantify direct and indirect interactions among functional groups (ITC), including the fishery (Ulanowicz & Puccia, 1990).
Results of this model were compared with results obtained by Medina et al. (2007) that represent a different state of the same system, i.e., a sardine dominated non-ENSO period (Medina et al., 2007) versus an anchovy dominated ENSO period (this study).
Table 2 shows input parameters and those estimated using EwE for each functional group in the balanced model for the UENCh in year 1997 and the Table 3 shows the diet composition (in weight) for predators in the same model.
In general terms, total biomass ([B.sub.T]) (i.e., system biomass excluding detritus) sustained by the UENCh was estimated at 624.7 ton [km.sup.-2]. Overall, pelagic species such as mackerel (11.01 ton [km.sup.-2]), jack mackerel (15.4 ton [km.sup.-2]), sardine (26.9 ton [km.sup.-2]), anchovy (39.1 ton [km.sup.-2]), and mesopelagic fish (67.3 ton [km.sup.-2]) dominated the system (Table 2), representing 26% of [B.sub.T], while the combined biomass of demersal fish represented 0.1% of Bt.
Table 2 presents the production/biomass ratio (P/B = Z) for all groups and fishing mortality (F) for target species. Fig. 3 shows the contribution (percentage) in which each mortality coefficient (F; M2 and M0) contributes to Z. Fishing mortality is important in species such common dolphinfish (42%), jack mackerel (30%), anchovy (27%), mackerel and pelagic sharks, both with 21%. In groups such Eastern Pacific bonito, mesopelagic fish and demersal fish, the main source of mortality is predation (M2) exceeding 90%; the coefficient of other mortalities (M0) is important in sardine and swordfish, also about 90%. Overall, in 1997 predators consumed more production of functional groups than the fishery (Fig. 3).
Fig. 4 shows the main flows in the UENCh in year 1997 and the distribution of the functional groups according to their trophic level (TL), from TL = 1 (phytoplankton and detritus) up to apical predators with TL > 4.0 such jumbo squid (TL = 4.68), sea lions (TL = 4.85), marine birds (TL = 4.91), common dolphinfish (TL = 4.95), cetaceans (TL = 5.0), pelagic sharks (TL = 5.2) and swordfish (TL = 5.2). The most important flows of consumption occur between primary producers (phytoplankton) and plankton invertebrates (micro-, macro--and mesozooplankton), and from the latter groups towards small pelagic fish (anchovy and sardine). Other important flows occur from mesozooplankton towards mesopelagic fish, and from anchovy and sardine towards predators such demersal fish, jumbo squid, sea lions and marine birds.
The 21 functional groups in the model representing the UENCh were grouped into seven discrete trophic levels, with discrete TL I and discrete TL II concentrating the bulk of total flows. Just like in other upwelling systems (e.g., Jarre-Teichmann & Christensen, 1998; Neira & Arancibia, 2004), the UENCh exhibited a decline in flows (Ft) and biomass (Bt) towards higher trophic levels (Table 4). This is related to the rather low trophic transfer efficiency (TTE) calculated for aggregated trophic levels higher than TL IV. However, TTE was higher in TL II (TTE = 11.8%), TL III (TTE = 28%) and TL IV (TTE = 17.8%). These results differ from what occurred in 1989 (Medina et al., 2007), when TTE was high in TL II (TTE = 65.2%) and TL III (TTE = 9.5%), and the fishery was sustained by both anchovy and sardine. During 1997, instead, the fishery was sustained by functional groups located at TLs III and IV, including anchovy (84% of total landings), jack mackerel (11% of total landings), mackerel (6% of total landings) and sardine (0.5% of total landings).
Fig. 5 shows the mixed trophic impacts (MTI) between functional groups including the industrial and artisanal fleets operating in the study area in 1997. Overall, predators have direct negative impacts on prey, while preys have positive direct impacts on predators. Some MTIs can be highlighted from this figure. For example, the negative impact of cannibalism in jumbo squid and the negative MTIs of predators such jack mackerel, palm ruff, common dolphinfish, pelagic sharks and sea lions on anchovy.
The industrial fleet showed a negative impact on jack mackerel and positive impact on gelatinous zooplankton because fishing removes biomass of predators of this group. On the other hand, the artisanal fleet impacted negatively dolphinfish, sea lions and pelagic sharks with positive impact on demersal fish because this fleet removes biomass of their predators. The two fleets also impacted indirectly and positively some fishery resources (especially anchovy). This is the case of the positive impact of the artisanal fleet on demersal fish and palm ruff, which resulted from the fishing removal of sea lions and pelagic sharks. Mesopelagic fish showed an indirect negative impact on gelatinous zooplankton since both groups share mesozooplankton as preferred prey. The impacts of species such palm ruff, Eastern Pacific bonito and common dolphfish on other groups are almost unnoticeable.
Fig. 6 shows the trophic level (TL) calculated for the main predators in the UENCh model in 1989 (Medina et al., 2007) and 1997 (this study). A noticeable difference in the magnitude of individual TL between the two periods is observed. In 1989, for instance, the most of the groups exhibited a TL < 4.0, with the exception of pelagic sharks. On the other hand, in 1997 most of the groups exhibited TLs > 4.0.
Table 5 presents network indices for the food web in the UENCh. The mean trophic level of the fishery (TLm) as a whole was estimated at 3.7. When examined by fleets, TLm of the artisanal fleet (TLm = 3.6) was slightly lower than the industrial fleet (TLm = 3.7). This is because both fleets caught mainly anchovy and sardine. The primary production required to sustain landings (PPR) was estimated at 2979.5 ton [km.sup.-2] [yr.sup.-1], corresponding to 7.5% of the calculated net primary production of the system. The flows related to total transfers and total biomasses are indicators for the size of the ecosystem. The total transfers correspond to the sum of all flows in the system (consumption, exports, respiration and flow to detritus) and were estimated at 83,204 ton [km.sup.-2] [yr.sup.-1]. The main component resulted to be the consumption flow with 43% of total transfers. Total biomass without detritus was estimated at 624.7 ton [km.sup.-2].
One of the indicators to characterize system maturity is the primary production to respiration ratio (PP/R), which should approach to 1 in mature systems (Christensen & Pauly, 1992; Christensen et al, 2005). In 1997, PP/R was estimated at 1.61 [yr.sup.-1] meaning that this system was far from maturity or in an early stage of development. Other indicator of system maturity is the primary production to total biomass ratio (PP/[B.sub.T]), which in mature ecosystems is low and in the UENCh was estimated at 61.40 in 1997.
The model representing the UENCh in 1997 includes eight additional groups compared to the model built by Medina et al. (2007) for the same area in year 1989. These groups are microzooplankton, mesozooplankton, macrozooplankton, gelatinous zooplankton, demersal fish, jumbo squid, common dolphinfish, and swordfish. In addition, both models represent two different conditions: i) during non-ENSO conditions (year 1989) and ii) during ENSO conditions (year 1997). Regardless the difference in model structure and system conditions, comparing indicators derived from both models is still valid and interesting. Moreover, if more predators are included in a new, updated model, then the predation mortality in a prey group will be higher than the previous model.
Even in heavily exploited upwelling systems, predation mortality (M2) is the main source of mortality for fish species (Jarre-Teichman et al, 1998; Jarre-Teichman & Christensen, 1998; Neira & Arancibia, 2004; Neira et al, 2004). Results of our work are in agreement with this observation and M2 explained the most of Z, meaning that the most of the production of functional groups in the UENCh was removed by predators and secondarily by fishing. However, Medina et al. (2007) informed that in 1989 the main source of mortality in the system was fishing and not predation. This may be explained by the increase in fishing effort from 1985 onwards after anchovy recovery, likely driven by strong recruitments (Aliaga et al., 2001).
The highest Z values in the 1997 model were found in anchovy and jumbo squid. This is explained because both species have low longevity and high productivity, and are also important prey items in the diet of several predators. For example, anchovy is the main prey for jack mackerel, horse mackerel, palm ruff, Eastern Pacific bonito, pelagic sharks, sea lions and cetaceans. Anchovy sustained also the fishing landings in 1997. In turn, jumbo squid is important prey for cetaceans, dolphinfish, swordfish, and exhibits strong cannibalism (Table 3).
In the 1997 model, predators exhibited TL > 4.0. When comparing this result with the 1989 model (Medina et al., 2007) (Fig. 6), we observed an increase in TLs from one period to another (Fig. 6). A switch in sardine and anchovy diet may explain this change. During 1989, anchovy diet was based on zooplankton (85%) and phytoplankton (15%) (Alamo et al., 1997) and the diet of sardine on zooplankton (26%) and phytoplankton (74%) (Oliva et al, 1987fide Medina et al, 2007). In 1997, a dramatic change in the diet of both species occurred, with zooplankton being the most important prey in both species (> 97%). This value was obtained considering the diet (numbers) informed by Alamo et al. (1997); Alamo & Espinoza (1998) and the carbon contents of each prey item expressed in percentage of fish total wet weight obtained from Espinoza & Bertrand (2006). During ENSO, a marked decline in the abundance of phytoplankton and a concomitant increase in the abundance of zooplankton have been observed (Gonzalez et al., 1998; Daneri et al., 2000), and this could explain the change in the diet of small pelagic fish.
However, Espinoza & Bertrand (2006) monitored the gut content of 21,203 anchovies from acoustic surveys conducted in Peru from 1996 to 2003, reporting that zooplankton (mainly euphausiids and copepods) is the main component in anchovy diet, in opposition to previous studies by Pauly et al. (1998), Jarre et al. (1991) and Jarre-Teichman et al. (1998) who indicate a similar importance of phytoplankton and zooplankton in the diet of anchovy. Nevertheless, Espinoza & Bertrand (2006) highlight that their study was based on qualitative descriptions, i.e., frequency of occurrence and percentage in number of the items, rather than stomach content expressed in weight.
Therefore, the increase in TL in anchovy and sardine, which in turn are the main prey for predators and the bulk of the catch in the UENCh in 1997, resulted in an increase in trophic level of the fishery as a whole with TLm > 3. In this year the landings of anchovy reached 27 ton [km.sup.-2] [yr.sup.-1], and was higher than the landings of the same species in 1989 (Medina et al., 2007), when the fishery had a TLm = 2.7 and landings were sustained mostly by sardine (26 ton [km.sup.-2] [yr.sup.-1]).
In the decade of 1990s, landings of sardine progressively declined and in 1997/1998 with an El Nino, landings have the lowest values. In 1982/1983 a strong ENSO event affected the study area (Aceituno, 1988), negatively impacting anchovy and horse mackerel (Braun et al, 2000). However, landings of sardine were not affected by this condition (SERNAPESCA, 1980-1990). In this context, the impact of the ENSO 1997/1998 on fish stocks in the Humboldt Current System is not yet clear, since for example, the fisheries of anchovy and sardines in Peru were not noticeably affected by the 1982/1983 ENSO (Arntz & Fahrbach, 1996). Therefore, it is suggested that the strong decline in the landings/biomass of sardine during the 1990s could result from recruitment overfishing (Serra, 1986; Aliaga et al, 2001; Cubillos & Arcos, 2002) and predation and in a minor degree to ENSO. Unfortunately, the model representing the system in 1989 (Medina et al., 2007) did not include some important predators of anchovy and sardine, such demersal fish, jumbo squid, swordfish, dolphinfish and cetaceans. This shortcoming impedes observing which groups predated on these small pelagic fish in 1989 and quantifying the strength of this trophic interaction. This is the importance of including these groups in the 1997 model.
The mixed trophic impacts (MTI) allowed assessing the influence of direct and indirect trophic interactions (including food competition) in the UENCh. MTI was also useful in identifying strong and weak interacting groups in the food web. For example, anchovy, mesopelagic fish and jack mackerel are strong interactors impacting positively and negatively many groups in the systems. On the other hand, palm ruff, Eastern Pacific bonito and common dophinfish are weak interactors with little impacts on other groups in the system.
The primary production required to sustain fishery landings (PPR) is an ecological indicator to track the ecological cost of fishing in an ecosystem during a time period, along years and/or compare the ecosystem effect of fishing in different ecosystems (Pauly & Christensen, 1995; Jarre-Teichman et al, 1998). During 1997, the fishery removed only a small fraction (i.e., 7.5%) of total primary production in the UENCh. This value is slightly higher compared to the value (PPR = 6.7%) informed by Medina et al. (2007) for 1989, but much lower than the PPR = 68.7% informed by Cubillos et al. (1998) for 1997, both for the same area. PPR in the UENCh in 1997 was also lower than the PPR = 15% informed by Neira & Arancibia (2004) for central Chile, and the global estimate for upwelling areas PPR = 25.1% (Pauly & Cristhensen, 1995). However, the value 7.4% is in the minimum range reported by Jarre-Teichmann et al. (1998), who compared the upwelling systems from Peru, South Africa, Namibia and California, with PPR ranging from 4 to 15% of net production.
In this work we obtained seven discrete trophic levels, while (Medina et al., 2007) reported five. This is due to the most of the species that are present in the 1997 model but not in the 1989 model are in high trophic levels (cetaceans, swordfish, dolphinfish and jumbo squid). In fact, the mean trophic transfer efficiency among trophic levels was relatively high (18%) in the 1997 model. Nevertheless, TTE in the UENCh is in the range informed for aquatic systems 10-20% (Christensen & Pauly, 1993; Lalli & Parsons, 1993), but it is higher than the 10-15% reported for upwelling systems (Pauly & Christensen, 1995).
After analysing the food web and the fisheries in the UENCh, we consider that there is still necessary to advance our knowledge on biological parameters for species that are not target species (it might became in the future), but play an important role as prey or predators in the ecosystem. Some of the groups could reach high biomass levels in the system, e.g., mesopelagic fish. In this study the biomass of this group was estimated under the assumption that EE = 0.999, and reached 67.3 ton [km.sup.-2], which is almost two times the biomass estimated by Braun et al. (2000) for this group in 1998 (i.e., 33.7 ton [km.sup.-2]). The difference between the mesopelagic fish biomass estimated by Braun et al. (2000) and this work could be method-dependent, i.e., acoustic underestimates the biomass in relation to Ecopath.
Results of our study confirm conclusions by Medina et al. (2007) related to the low maturity (in terms of structure and flows) of the UENCh. However, in theoretical terms the system in 1997 seems to have been in a situation closer to maturity (sensu Odum, 1969) compared to 1989. This can be inferred from the PP/R values estimated at 1.60 [yr.sup.-1] in 1997 (this study) and 3.2 [yr.sup.-1] in 1989 (Medina et al., 2007). Another indicator that support the previous conclusion is the Finn's cycling index (IF), which indicate the fraction of total transfers that are cycled in the system (Christensen & Pauly, 1992) with more cycling related to higher system maturity (Odum, 1969). The IF in the USNCh was higher in 1997 model (8.75%) compared to 1989 (2.80%), and the IF obtained in central Chile (8.97%) (Neira & Arancibia, 2002).
In 1997 flows related to total transfers indicated that the system presented more flows (106,447 ton [km.sup.-2] [yr.sup.-1]) compared to 1989 (38,674 ton [km.sup.-2] [yr.sup.-1]) (Medina et al, 2007), which seems reasonable considering that the 1997 model includes more groups than the 1989 one. However, in 1989 total biomass (707.7 ton [km.sup.-2]) and total landings (91 ton [km.sup.-2]) were higher than the same parameters in 1997.
The impact of the 1997/1998 ENSO on fishing resources is not clear, and results of this study allow hypothesising that the strong decline in landings and biomass of pelagic resources, especially sardine and anchovy in the USNCh, might have resulted from a combination of overfishing (affecting recruitment) (Serra, 1986; Aliaga et al., 2001; Cubillos & Arcos, 2002), in addition to predation, and secondarily to the effects of ENSO. Therefore, we suggest a combined analysis of the effect of fishing (F), predation (M2) and the environment (changes at ENSO scale), on sardine and anchovy that allow identifying the strength of each factor and their combined effects on the dynamics of these important fish species.
Authors are thankful to two anonymous reviewers whose comments greatly improved the final version of this manuscript. SN acknowledges financial support from Project FONDECYT N[degrees]11110545, the COPAS Sur Austral Program and the INCAR Centre.
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Received: 30 September 2013; Accepted: 10 September 2014
Monica E. Barros (1), Sergio Neira (1,2,3) & Hugo Arancibia (1)
(1) Departmento de Oceanografia, Universidad de Concepcion, P.O. Box 160-C, Concepcion, Chile
(2) Programa COPAS Sur-Austral
(3) Interdisciplinary Center for Aquaculture Research
Corresponding author: Monica E. Barros: (firstname.lastname@example.org)
Table 1. Functional groups included in the model representing the upwelling system of northern Chile, year 1997, and the source of input parameters. B: biomass, P/B: production to biomass ratio, Q/B: consmnption to biomass ratio, Y: total catch, EE: ecotrophic efficiency = 0.999, DC: fraction (in weight) of the prey in the diet of the predator, assuming that the functional group is highly predated and/or exploited by the fishery. Parameter\ B ton P/B Group [km.sup.-2] [yr.sup.-1] Phyto- a Daneri et plankton al. (2002) Micro- a Moloney et zooplanklon al. (2002) Meso- a Escribano et zooplankton al. (1999) Macro- a Moloney et zooplankton al. (2002) Gelatinous Vargas & Moloney et zooplankton Gonzalez (2004) al. (2002) Mackerel Braun et Ganoza et al. (2000) al (2002) Sardine Braun et c: Ganoza et al. (2000) al (2002) Anchovy Braun et Ganoza et al. (2000) al (2002) Mesopelagic fish a Moloney et al (2002) Jack mackerel Braun et Ganoza et al. (1999) al. (2002) Demersal fish a Oyar/im el al (1999); Slanzi (2003); Tascheri et al (2003) Jumbo squid Moloney el al. (2002) Palm niff b: Ganoza et c: Wolff & al (2002); f Aron (1992) Eastern a c: Nunez (1993) Pacific bonito Common a Olson & dolphinfish Watters (2003) Swordfish Bernal (1990) Olson & Watters (2003) Pelagic b: Arancibia Arancibia et sharks et al. (2002); al. (2002) SERNAPESCA Sea lions Sielteld et Moloney et al. (1997) al. (2002) Cetaceans Moloney et Moloney et al. (2002) al. (2002) Marine birds Moloney et Moloney et al. (2002) al. (2002) Parameter\ Q/B [yr.sup.-1] Y ton Group [km.sup.-2] Phyto- plankton Micro- Neira & zooplanklon Arancibia (2004) Meso- Vargas & zooplankton Gonzalez (2004) Macro- Vargas & zooplankton Gonzalez (2004) Gelatinous Vargas & zooplankton Gonzalez (2004) Mackerel e f Sardine e f Anchovy e f Mesopelagic fish e Jack mackerel Robotham et f al. (1995) Demersal fish e: Oyarzun et al. (1999); Slanzi (2003); Tascheri (2003) Jumbo squid Arancibia et f al. (2007) Palm niff e f Eastern e f Pacific bonito Common Olson & Galvan- f dolphinfish Magana (2002) Swordfish e Pelagic e f sharks Sea lions Moloney et f al (2002) Cetaceans Moloney et al. (2002) Marine birds Moloney et al. (2002) Parameter\ EE DC Group Phyto- Gonzalez et plankton al (1998) Micro- 0.999 Gonzalez et zooplanklon al. (1998) Meso- 0.999 Gonzalez et zooplankton al. (1998), Moloney et al (2002) Macro- 0.999 Gonzalez et zooplankton al. (1998), Moloney et al. (2002) Gelatinous Gonzalez et zooplankton al. (1998) Mackerel Medina & Arancibia (1992), Vargas & Gonzalez (2004) Sardine Espinoza et al. (1998), Espinoza & Bertrand (2006) Anchovy Alamo (1997), Alamo & Espinoza et al. (1998), Espinoza & Bertrand (2006) Mesopelagic fish 0.999 Palma (1993) Jack mackerel Medina & Arancibia (1992, 1995) Demersal fish 0.999 Medina et al. (2004), Oyarzun et al. (1999), Pizarro & Medina (2006) Jumbo squid Arancibia et al (2007), Clarke & Paliza (2000) Palm niff Ganoza et al. (2002) Eastern 0.999 Blaskovic et Pacific bonito al (2002a, 2002b, 2002c) Common Olson & dolphinfish Galvan- Magana (2002) Swordfish Daza (2002) Pelagic Olson & sharks Watters (2003) Sea lions Sielfeld et al. (1997) Cetaceans Olson & Watters (2003) Marine birds Goya & Garcia- Godos (1999) The reference indicates the origin of information, in bold indicate the values of the parameters. Key: a) Estimated by Ecopath, b) Estimated using the equation B = Y/F (Baranov, 1918), where F = obtained from literature, Y = Fisheries Statistics National Fisheries Service (SERNAPESCA), c) Estimated using the equation Z = F+M (Beverton & Holt, 1957), d) Estimated using the empirical equation of Hoening (1983): Ln(Z) = 1,44-0.982*ln(Tmax); Tmax (maximum age), e) Estimated using the empirical equation of Palomares & Pauly (1998): log Q/B = 7.964- 0.204 log [W.sub.inf]- 1.9651'+ 0.083Ar+ 0.532h+ 0.398d, f) SERNAPESCA. Table 2. Input parameters and outputs (bold) of the balanced model representing the food web in the upwelling system of northern Chile in 1997. TL: trophic level, B: biomass, P/B: production to biomass ratio, Q/B: consumption to biomass ratio, F: fishing mortality, Y: catches, EE: ecotrophic efficiency and GE: gross efficiency. Group name TL B P/B (ton ([yr.sup.-1]) [km.sup.-2]) 1. Phytoplankton 1# 319.68# 120.00 2. Microzooplankton 2.21# 17.48# 482.00 3. Mesozooplankton 2.48# 47.02# 45.00 4. Macrozooplankton 2.75# 68.51# 13.00 5. Gelatinous zooplankton 3.42# 6.90 0.58 6. Mackerel 4.19# 11.01 1.20 7. Sardine 3.49# 26.88 1.46 8. Anchovy 3.57# 39.09 2.01 9. Mesopelagic fish 3.53# 67.31 1.20 10. Jack mackerel 4.38# 15.39 0.36 11. Demersal fish 4.88# 0.57# 0.31 12. Jumbo squid 4.68# 3.60 3.50 13. Palm ruff 3.86# 0.30 1.46 14. Eastern pacific bonito 4.11# 0.26# 0.99 15. Common dolphinfish 4.95# 0.00 1.20 16. Swordfish 5.23# 0.42 0.44 17. Pelagic sharks 5.21# 0.06 0.49 15. Sea lions 4.85# 0.09 0.30 19. Cetaceans 5.03# 0.06 0.15 20. Marine birds 4.92# 0.06 0.10 21. Detritus 1# 1 Total 624.70# Group name Q/B F ([yr.sup.-1]) ([yr.sup.-1]) 1. Phytoplankton -- 2. Microzooplankton 1928.00 -- 3. Mesozooplankton 128.57 -- 4. Macrozooplankton 31.71 -- 5. Gelatinous zooplankton 2.45 -- 6. Mackerel 7.00 0.25 7. Sardine 17.60 0.01 8. Anchovy 21.90 0.55 9. Mesopelagic fish 12.00 0 10. Jack mackerel 8.12 0.11 11. Demersal fish 4.12 0.01 12. Jumbo squid 8.64 0 13. Palm ruff 4.20 0.03 14. Eastern pacific bonito 5.50 0.02 15. Common dolphinfish 5.60 0.50 16. Swordfish 7.20 0 17. Pelagic sharks 6.10 0.10 15. Sea lions 20.00 0.03 19. Cetaceans 10.00 -- 20. Marine birds 62.00 -- 21. Detritus -- Total Group name Y EE (ton [km.sup.-2]) 1. Phytoplankton -- 0.70 2. Microzooplankton -- 1.00 3. Mesozooplankton -- 1.00 4. Macrozooplankton -- 1.00 5. Gelatinous zooplankton -- 0.31# 6. Mackerel 2.766 0.88# 7. Sardine 0.139 0.10# 8. Anchovy 21.387 0.94# 9. Mesopelagic fish 0 1.00# 10. Jack mackerel 1.618 0.41# 11. Demersal fish 0.006 1.00# 12. Jumbo squid 0 0.50# 13. Palm ruff 0.009 0.41# 14. Eastern pacific bonito 0.004 1.00# 15. Common dolphinfish 0.001 0.42# 16. Swordfish 0.001 0.00# 17. Pelagic sharks 0.006 0.21# 15. Sea lions 0.003 0.10# 19. Cetaceans -- 0.00# 20. Marine birds -- 0.00# 21. Detritus -- 0.28# Total 25.94# Group name GE 1. Phytoplankton -- 2. Microzooplankton 0.25# 3. Mesozooplankton 0.35# 4. Macrozooplankton 0.41# 5. Gelatinous zooplankton 0.239# 6. Mackerel 0.171# 7. Sardine 0.083# 8. Anchovy 0.092# 9. Mesopelagic fish 0.1# 10. Jack mackerel 0.044# 11. Demersal fish 0.075# 12. Jumbo squid 0.405# 13. Palm ruff 0.348# 14. Eastern pacific bonito 0.179# 15. Common dolphinfish 0.214# 16. Swordfish 0.061# 17. Pelagic sharks 0.08# 15. Sea lions 0.015# 19. Cetaceans 0.015# 20. Marine birds 0.002# 21. Detritus -- Total Note: Input parameters and outputs of the balanced model representing the food web in the upwelling system of northern Chile in 1997 is indicated with #. Table 3. Diet composition of the predators included in the balanced model representing the food web in the upwelling system of central Chile, year 1997. Prey Predator 2 3 4 5 6 1 Phytoplankton 0.728 0.200 0.500 0.092 2 Microzooplankton 0.171 0.400 0.038 0.055 0.011 3 Mesozooplankton 0.400 0.514 0.135 4 Macrozooplankton 0.063 0.339 0.190 5 Gelatinous zooplankton 6 Mackerel 7 Sardine 8 Anchovy 0.269 9 Mesopelagic fish 0.259 10 Jack mackerel 11 Demersal fish 12 Jumbo squid 13 Palm ruff 14 Eastern Pacific bonito 15 Common dolphinfish 16 Swordfish 17 Pelagic sharks 18 Sea lions 19 Cetaceans 20 Marine birds 21 Detritus 0.101 0.4 22 Import 0.137 23 Total 1.00 1.00 1.00 1.00 1.00 Prey Predator 7 8 9 10 11 1 Phytoplankton 0.0003 0.022 2 Microzooplankton 0.222 0.058 3 Mesozooplankton 0.500 0.514 0.681 4 Macrozooplankton 0.278 0.464 0.220 0.21 0.001 5 Gelatinous zooplankton 0.01 6 Mackerel 0.05 7 Sardine 0.054 8 Anchovy 0.21 0.164 9 Mesopelagic fish 0.31 10 Jack mackerel 11 Demersal fish 0.0002 12 Jumbo squid 0.089 13 Palm ruff 14 Eastern Pacific bonito 15 Common dolphinfish 16 Swordfish 17 Pelagic sharks 18 Sea lions 19 Cetaceans 20 Marine birds 21 Detritus 22 Import 0.041 0.21 0.692 23 Total 1.00 1.00 1.00 1.00 1.00 Prey Predator 12 13 14 15 16 1 Phytoplankton 2 Microzooplankton 3 Mesozooplankton 0.13 4 Macrozooplankton 0.06 0.54 0.01 5 Gelatinous zooplankton 6 Mackerel 0.054 0.14 7 Sardine 0.081 0.17 0.066 0.12 8 Anchovy 0.081 0.08 0.29 0.075 0.12 9 Mesopelagic fish 0.704 0.465 0.05 10 Jack mackerel 0.030 11 Demersal fish 12 Jumbo squid 0.134 0.310 0.50 13 Palm ruff 14 Eastern Pacific bonito 0.06 15 Common dolphinfish 0.0003 16 Swordfish 17 Pelagic sharks 18 Sea lions 19 Cetaceans 20 Marine birds 21 Detritus 22 Import 0.73 23 Total 1.00 1.00 1.00 1.00 1.00 Prey Predator 17 18 19 20 1 Phytoplankton 2 Microzooplankton 3 Mesozooplankton 4 Macrozooplankton 0.04 5 Gelatinous zooplankton 6 Mackerel 0.15 0.05 0.01 0.40 7 Sardine 0.22 0.14 8 Anchovy 0.15 0.40 0.26 0.45 9 Mesopelagic fish 0.10 10 Jack mackerel 0.15 0.05 0.07 0.11 11 Demersal fish 0.10 12 Jumbo squid 0.33 0.05 0.34 13 Palm ruff 0.03 0.04 0.04 14 Eastern Pacific bonito 0.15 0.04 15 Common dolphinfish 16 Swordfish 17 Pelagic sharks 18 Sea lions 19 Cetaceans 20 Marine birds 21 Detritus 22 Import 0.13 23 Total 1.00 1.00 1.00 1.00 Table 4. Total biomass ([B.sub.t]), total catches ([Y.sub.t]), total flows ([F.sub.t]) and trophic transfer efficiencies (TTE) by discrete trophic level in the model representing the upwelling system of northern Chile, year 1997. Trophic level (TL). TL [B.sub.t] [Y.sub.t] [F.sub.t] TTE (ton (ton (ton (%) [km.sup.-2] [km.sup.-2] [km.sup.-2] [yr.sup.-1]) [yr.sup.-1]) [yr.sup.-1]) I 320.0 58802.0 II 83.7 0.5 32676.3 11.8 III 129.0 12.9 4353.6 28.0 IV 74.2 9.5 1184.0 17.6 V 16.8 2.9 195.3 7.1 VI 1.6 0.2 12.7 5.4 VII 0.1 0.0 1.4 Total 625.4 25.9 97058.0 17.8 Table 5. Ecosystem indicators that describe the model representing the upwellig system of northern Chile, in year 1997 and its comparison to Medina et al. (2007) model representing the system in 1989. Parameter Year 1989 1997 System size Sum of all 13091.8 44326.8 consumption (ton [km.sup.-2] [yr.sup.-1]) Sum of all the 4244.0 24744.3 respiration flows (ton [km.sup.-2] [yr.sup.-1]) Sum of all flows to 12060.2 20954.6 detritus (ton [km.sup.-2] [yr.sup.-1]) Total system flows 38674.0 106447.0 (ton [km.sup.-2] [yr.sup.-1]) Total biomass 707.7 645.4 (without detritus)(ton [km.sup.-2]) Total catch (ton 91.0 26.1 [km.sup.-2] [yr.sup.-1]) System maturity Sum of all the 19684.0 50030.7 production (ton [km.sup.-2] [yr.sup.-1]) Calculated net 13452.8 38362.1 primary production (PPt) (ton [km.sup.-2] [yr.sup.-1]) Total primary 3.2 1.6 production/total respiration (PP/R) Total primary 19.0 61.4 production/total biomass (PP/[B.sub.T]) Trophic transfer 9.8 17.8 efficiency (%) Finn's cycling index 8.81 8.75 (IF) (%) Fishing impact Mean trophic level 2.7 3.7 of the catch Primary production 1321.4 2834.4 required to sustain landings PPR (ton [km.sup.-2] [yr.sup.-1]) (PPR) (%) 6.7 7.3
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|Title Annotation:||articulo en ingles|
|Author:||Barros, Monica E.; Neira, Sergio; Arancibia, Hugo|
|Publication:||Latin American Journal of Aquatic Research|
|Date:||Nov 1, 2014|
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