U.S. Dept. of Commerce / NOAA / OAR / PMEL / Publications
A major area of research in fisheries oceanography examines relationships between recruitment dynamics of fish populations and the marine environment. A primary goal is to understand the natural causes of variability in year-class strength of commercially valuable species and apply this knowledge to management [Perry, 1994]. The paradigm that the majority of mortality occurs during transport of early life history stages from spawning to nursery grounds [Rothschild, 1986; Houde, 1987] provides an initial temporal focus for most research. The spatial domain includes the region occupied by early life history stages. Since global climate variability impacts regional ecosystem dynamics, however, the spatial domain often must be expanded. The relative importance and manifestation of biological factors (starvation and predation) that limit survival varies each year. Marked interannual and longer period variations in temperature (an influence on metabolic rates and behavior), transport of planktonic stages, and turbulence can exert an influence on both survival of early life history stages, and distribution of juveniles and adults. To understand how these environmental factors influence reproductive success of fish stocks also requires knowledge of the impact of these factors on predators and prey throughout the food web.
Our research, Fisheries-Oceanography Coordinated Investigations (FOCI, a NOAA
program), examines recruitment dynamics of walleye pollock (Theragra chalcogramma)
in Alaskan ecosystems [Reed
et al., 1988; Schumacher
and Kendall, 1991; Reed
et al., 1994]. Fisheries oceanography is a very broad field of research
with many programs and various approaches; FOCI represents a subset of this
research. FOCI began in 1984 in Shelikof Strait, Alaska; in summer 1991 another
element (a component of NOAA's Coastal Ocean Program) began in the Bering Sea.
Pollock constitute the world's largest single species fishery with annual catches
from Alaskan waters exceeding 1.2 million metric tonnes [Westpested,
1993]. In both regions, large variations in recruitment
The inherent complexity of the ecosystem requires research specialization, which then must be integrated to provide a useful product. A better understanding of the population dynamics process requires more interdisciplinary research among fisheries scientists and oceanographers [Beamish et al., 1989]. Unfortunately, such varied backgrounds traditionally result in disparate rather than integrated research [Wooster, 1986]. The tendency to do research without being responsible for implementation of results also detracts from achieving holistic goals. It has long been known that humans impact their environment. "Man did not weave the web of life; he is merely a strand of it. Whatever he does to the web, he does to himself" (Chief Seattle, 1854). Integrating research conducted by people from disparate academic backgrounds and maintaining a goal of responsible implementation of results can ensure that fishing mortality does not detrimentally interact with natural fluctuations in recruitment. In this way we acknowledge the gifts nature provides and leave a legacy for future generations. This is not only our moral responsibility, it is mandated by Federal law (Magnuson Fisheries Management and Conservation Act, 1976).
In this overview, we present some of the major developments and results from FOCI. First, we present background information for both FOCI programs (Shelikof Strait and Bering Sea), including research strategy and regional circulation features. We then present results that couple the biology and physics and are important features in both programs, as are the methods and techniques that follow. Finally, we present the application of research results from Shelikof Strait FOCI to management. The goal of FOCI, to understand natural fluctuations in year-class strength of pollock and to provide information to reduce uncertainty in status-of-pollock-stock models, is applied science. The initial examination of the physical and biological environment and the time/space distribution of various life history stages of pollock is viewed as fundamental science. Development and implementation of models to integrate biophysical observations, and technologies to measure conditions, as well as developing methods to apply new findings to management occur as FOCI matures.
Prior to FOCI, only very limited knowledge existed of either the physical environment or the life history of pollock in the western Gulf of Alaska. What was known suggested the following hypothesis: optimum survival and subsequent recruitment result when larvae are transported to nursery grounds in coastal regions along the Alaska Peninsula, rather than into the Gulf of Alaska. Further, biophysical processes occurring during transport have significant impact on survival. Initially studies focussed on the life history of pollock and the nature of the regional circulation. As these aspects became known, field operations switched to maintenance time series of selected biological and physical characteristics, studies of biophysical processes, and development of methods to examine preferential survival. Simultaneously, we began implementation of coupled biophysical and correlative models, and development of methods to transfer FOCI results to the assessment and prediction models used to provide biomass scenarios to management.
Separation of pollock larvae from those of similar species in field samples
was first accomplished in 1981 [Dunn
and Matarese, 1987]. At the same time, the strong year-classes in the
mid-1970's resulted in a large fishery [Megrey,
1990], and hydroacoustic surveys were conducted to estimate the adult population
for input to assessment and prediction models. The surveys showed that large
concentrations of pre-spawning walleye pollock migrate from the southwest end
of Shelikof Strait (taken to include the sea valley that extends from the Barren
Islands southwestward to the slope off Chirikof Island, Figure 1) primarily
to the area near Cape Kekurnoi. Spawning takes place mainly in the deep sea
valley in early April [Kim
and Nunnallee, 1991], at depths between 150-
Figure 1. Upper Panel: The FOCI study area in the western Gulf of Alaska with a schematic showing the location of pollock life history stages. The outlined arrows represent potential transport of larvae off the shelf. Lower Panel: Circulation in the study area as derived from satellite-tracked buoys (51) drogued at 40 m and deployed between 1986 and 1994 (after Schumacher and Kendall [1991]).
The larvae are about
By late May considerable year-to-year variation exists in abundance and location
of larvae [Kendall
and Picquelle, 1990] as well as the zooplankton that produce their prey
[Incze
and Ainaire, 1994]. Two primary tracks characterize westward larval
drift: along the Alaska Peninsula in the relatively slow moving flow
We have established the life history pattern between spawning migration and young of the year (Figure 1). Using results from egg and larval surveys, together with estimates of the spawning adult population from hydroacoustic observations and indices of juvenile abundance [Bailey and Spring, 1992], the stages when year-class strength is established have been determined. A low abundance of larvae results in weak recruitment. A large abundance of larvae, however, does not imply strong recruitment. This suggests that processes during the juvenile stage can also be critical [e.g., Bailey et al., 1994b]. Recently, we have focussed more research on understanding young of the year juveniles since interannual variability in their survival also affects year class strength [Bailey and Spring, 1992].
Much of the variability in the physical environment in the Gulf of Alaska results from large scale atmospheric phenomena. Global patterns in the upper level atmospheric pressure generate climatic conditions that include an annual cycle in the number of low pressure centers traversing the region [Niebauer, 1988]. The consistent passage of storms along the Aleutian Island chain (the Aleutian Low) dominates wintertime atmospheric circulation. Interaction of frequent storms with the mountainous coastline results in a high precipitation rate (>200 cm yr-1) along the coastal region. The discharge rate of freshwater reflects seasonal variations in air temperature, precipitation, runoff and storage from the previous winter [Royer, 1982].
Along the Alaska Peninsula, along with a deep
The dominant circulation feature is the Alaska Coastal Current (ACC), a distinct
flow that only 20 years ago was unknown. FOCI research has elucidated many of
the characteristics of the ACC, which extends for
In Shelikof Strait, horizontal density gradients and vertical shear in the
mean flow create the baroclinic instability, evident in satellite images [Vastano
et al., 1992; Schumacher
et al., 1991] and in analysis of current records [Mysak
et al., 1981], which dominates flow patterns and generates eddies [Schumacher
et al., 1993]. The ACC does not span the sea valley, and estimates of
coherence become insignificant for separations
FOCI research has found and elucidated the dominant circulation and mesoscale features: the ACC, eddies generated by baroclinic instability, and an estuarine-like flow of slope waters into the sea valley. These features must be simulated in any numerical model of the region. Further, results show that the timing and location of hatching determines whether larvae enter an eddy, or are transported with either the slow-moving coastal flow or the rapid ACC. Modeling studies [Stabeno et al., 1995] suggest that the location of late larvae varies greatly year to year depending on advection. The phasing between biological and physical processes determines transport of larvae and presumably their eventual recruitment.
Recommendations from an International Symposium on Pollock [Aron and Balsiger, 1989] provide the research objectives for FOCI: determine stock structure in the Bering Sea and its relationship to physical features, and understand recruitment processes in the eastern Bering Sea. Both of these have direct implication to management of the vast resources that exist in U.S., Russian and international waters. To attain the first objective, field and modeling studies have investigated circulation throughout the deep basin. Another component seeks to establish genetic "finger-prints" to evaluate stock structure. In addressing the second objective, we are investigating differences between survival of eggs and larvae over the deep waters to that over the adjacent shelf. A newly established component is comparing habitats of juvenile animals around the Pribilof Islands.
Many of the characteristics of walleye pollock early life history are common
to all populations of the species. In the Bering Sea, however, both the population
structure and early life history pattern are much more complex than in the Gulf
of Alaska. Genetic characteristics [Mulligan
et al., 1992] and length-at-age and fecundity relationships [Hinckley,
1987] suggest several spawning stocks exist. The importance of pollock in
the ecosystem [e.g.,
Springer, 1992], as well as the relationships and interchange among
stocks are largely unknown. Spawning begins earlier in the year in some parts
of the Bering Sea than it does in Shelikof Strait and apparently different groups
of fish spawn at different times and places. We began our efforts focusing on
the population that spawns in February over the southeastern slope, and supported
a substantial fishery in the late 1980's. Here we found indications that some
of the eggs and larvae were much deeper in the water column
Prior to FOCI research many schematics existed of circulation in the Bering
Sea, and wind stress was considered to provide the primary forcing [Hughes
et al., 1974]. Results from FOCI have refined our knowledge of circulation
(Figure 2) and meteorological forcing over the basin from both observations
[Stabeno
and Reed, 1994] and model studies [Overland
et al., 1994]. A cyclonic gyre dominates circulation over the basin,
with a western boundary current (Kamchatka Current) along the Asian side of
the basin [Reed
et al., 1993]. This gyre is mainly an extension of the Alaskan Stream,
and the majority of volume transport enters through Near Strait
Figure 2. Upper Panel: A schematic of the general circulation over the basin of the Bering Sea as derived from ongoing FOCI research (after Stabeno and Reed [1994]). Lower Panel: A schematic of circulation over the eastern shelf based on previous results [Schumacher and Kinder, 1983], together with more recent satellite-tracked buoy [Stabeno and Reed, 1994] and moored current observations [Schumacher and Reed, 1992]. ACC is the Alaska Coastal Current, which enters through Unimak Pass, and W represents regions with weak or statistically insignificant mean flow.
The flux
We use the term coupled biophysical processes to mean physical processes that influence biological conditions affecting various life history stages of pollock.
In both Shelikof Strait and the Bering Sea, eddies play a role in coupled biophysical processes. These features frequently occur over the sea valley west of Kodiak Island, as revealed in infrared, synthetic aperture radar, and color scanner satellite imagery [Reed et al., 1988; Schumacher et al., 1991; Vastano et al., 1992; Liu et al., 1994], buoy trajectories [Incze et al., 1990], water property and larval distributions [Schumacher et al., 1993], and moored current records [Bograd et al., 1994]. The location of eddy formation coincides with the spawning region. Formation of three or four eddies per month during spring [Bograd et al., 1994] assures that some eggs hatch into an eddy. As a result of limited dispersion, high abundances of larvae often exist in such features. Further, since some eddies tend to remain nearly stationary for periods of weeks, they retain larvae in the sea valley [Reed et al., 1989; Vastano et al., 1992; Schumacher et al., 1993]. Some eddies have unique chemical properties [Incze et al., 1989], which may aid prey production and survival of larvae in the eddy [Schumacher and Kendall, 1991]. Nutritional condition of first-feeding larvae can be reflected by the ratio of ribonucleic acid to deoxyribonucleic acid (RNA/DNA). Concentrations of nauplii, larval gut contents, and RNA/DNA were higher for larvae in an eddy than for those in adjacent waters [Canino et al., 1991; Bograd et al., 1994].
Results from observations during May 1990 showed a connection between an eddy and larvae [Schumacher et al., 1993]. Contours of larval abundance coincide with those of salinity, and lie in close proximity to buoy trajectories. Physical data showed little or no exchange of water between the eddy and adjacent waters, permitting estimates of mortality that reflect only predation and/or starvation. The observations yield a daily mortality (4.4%) low compared to other estimates based on observations (6.3%, Reed et al. [1989]; 5-11%, Yoklavich and Bailey [1990]), or from dispersion model simulation (5.9-8.0%, Kim and Bang [1990]).
In the eastern Bering Sea, the presence of relatively small eddies (diameter
General results from modeling studies suggest that wind mixing of the upper water column can both be beneficial or detrimental to larval survival, depending on the intensity of the turbulence [Davis et al., 1991]. Many processes exist that connect pollock larval survival to mixing [Bailey and Macklin, 1994]. These authors determined a time series of abundance of larvae hatched on a given day that survived through the early feeding stage, and established a mixing index using the cube of the wind speed. Comparing these series revealed two patterns: strong wind events during the first-feeding period coincided with lower than expected survival, and periods of higher than expected larval survival were associated with calm periods of wind often bracketed by strong mixing. During a spring with moderate winds and a shallow mixed layer, concentrations of food, growth at age and mortality rates were more conducive to larval survival than during a spring when strong winds were accompanied by a deep mixed layer [Bailey et al., 1994b].
Bailey and Macklin suggest how larval survival may be related to an integration of wind-mixing, stratification within an eddy, and larval behavior. The eddy observed in 1989 had enhanced prey and feeding conditions and a low-salinity core relative to surrounding waters. Pollock larvae in the laboratory avoid turbulence [Olla and Davis, 1990] by moving deeper in the water column. Reduced light intensity with increasing depth has detrimental effects on the ability of larvae to search for and capture prey [Heath, 1989]. The vertical stratification of the eddy required more wind-induced turbulence than adjacent waters to mix to comparable depths. Thus, under similar winds, larvae within the eddy could remain higher in the water column in better feeding conditions than larvae outside the eddy. Hence, first-feeding larvae are more likely to survive in the eddy than in the surrounding waters giving similar prey fields.
We have used models in many ways, including to conceptualize program strategies, to expand the time-space domain of field observations, to guide program direction through hypothesis generation, to elucidate potential linkages among sets of biological and physical factors, and to provide information into the fisheries management stream.
Ongoing modeling studies examine potential impact of interannual changes in
circulation on survival of larvae in the western Gulf of Alaska. Physical factors
that pose challenges include complex bathymetry with many islands, mesoscale
Thus far SPEM has reproduced the observed general spatial features of circulation [Stabeno et al., 1995]. A comparison between model output and measured currents yielded reasonable agreement. The model also generates eddies with similar spatial scales to those observed. Results from SPEM show that during 1978 (the strongest year class) larvae were more likely transported into coastal waters along the Alaska Peninsula, while in 1990 (a below average year class) they remained in the sea valley where currents then result in transport offshore [Stabeno et al., 1995]. This latter scenario implies loss of recruits. These results support the original transport hypothesis.
SPEM is being coupled to a spatially explicit, individual-based, probabilities model (IBM) of egg and larval development. The IBM has distinct advantages over more traditional approaches that consider only the "mean" individual [Huston et al., 1988]; since it follows the unique life history of each fish, the IBM approach yields specific information about survivors. The model employs a spatial tracking algorithm for each individual, that includes vertical migration according to life stage. Horizontal transport, growth, and behavior are governed by velocity, salinity and temperature fields generated by SPEM. Low-pass filtered velocity and scalar fields from SPEM are stored once per model day, then used as input for multiple runs of the biological model. The model-generated spatial distributions qualitatively compare favorably with observed distributions of larvae and juveniles. Interannual differences in wind and freshwater runoff lead to differences in the modeled spatial paths of individuals, and in the distributions of population attributes (e.g., growth).
The objective of this component is to adapt and extend a coupled physical biological 1-D model to investigate production dynamics of the pelagic ecosystem as it pertains to survival of larval pollock. The approach uses field observations to determine rates and appropriate species composition for several of the distinct physical [Coachman, 1986] and biological [Smith and Vidal, 1986] domains in the eastern Bering Sea. The present model includes stage-structured dynamics of copepod populations (Calanus and Neocalanus) and larval pollock feeding and growth (S. Bollens, pers. comm.). The temporal behavior of the mixed layer comes from observations (see below). Model results include that the species composition of zooplankton has a strong influence on growth of larval pollock; the presence of protozoan prey becomes important when young copepods are scarce (i.e., early spring over the slope). Results from the model also suggest that variability of the mixed-layer depth has significant impact on larval growth by affecting lower trophic level production. These results have led to the addition of a research component that addresses the potential importance of protozoans as prey for larval pollock.
Many studies attempt to examine the causes of recruitment variation in fishes and relate these to biotic and abiotic factors. Hollowed [1992] lists 47 such studies along the coast of the northeast Pacific. There are two schools of thought regarding the utility of the correlative approach. It can be considered futile because of biases, measurement error, and the near certainty of spurious correlations [Walters and Collie, 1988]. Others claim that these studies provide information on patterns that lead to testable hypothesis [Kope and Botsford, 1990]. Recent studies [Tyler, 1992; Hollowed, 1992] advocate the use of correlative studies with the constraint that the analysis be based on a sound conceptual framework and judicious use of statistical methods. This approach was applied to a recruitment time series for adult pollock for the period of 1962-1989 and egg and larval series for 1981-1989 [Megrey et al., 1995]. The physical time series included estimates of precipitation, sea-level atmospheric pressure, wind-driven mixing, transport and water properties. Statistical techniques suggest that recruitment, as well as indices of age-0 and age-1 abundance, were related to precipitation, an index of sea level pressure, and wind mixing. Given the time period and phasing of the physical factors, the results imply that stratification can influence behavior of and predation on juveniles, and that increased baroclinicity influences larval survival through its impact on eddy generation and wind mixing. The former implication supports previous studies of juvenile behavior [Olla and Davis, 1995], while the latter two have been inferred from analysis of biophysical observations.
In order to examine biophysical conditions from pre-spring bloom conditions
through the summer, we have deployed a mooring over the outer slope
Results from both Shelikof Strait and the slope waters of the eastern Bering Sea indicate that the highest abundances of pollock larvae often reside in eddies. To examine the nature of biophysical processes extant in these features and determine their influence upon survival requires in situ observations. Finding a reliable method to locate an eddy for field studies provides a challenge. Although infrared imagery has proved useful, cloud cover and generally weak sea surface temperature gradients limit this approach. High resolution Synthetic Aperture Radar (SAR) eliminates both of these constraints. Mesoscale features are imaged by SAR through several possible mechanisms that are not well understood, including modulation of the short surface waves by current shear, alteration of the stability of the surface wind across a relatively sharp sea surface temperature gradient, surface film damping of short surface waves, shifts in the Doppler frequency due to variability in the surface currents, and current-induced wave refraction. This latter mechanism has been examined for features in Shelikof Strait [Liu et al., 1994].
During April and early May 1992, three eddies
It has long been thought that processes involving nutrition and predation of larval fishes play significant roles in their survival and ultimately in the strength of year classes. Until recently, however, lack of suitable technology has hampered efforts to study these processes. The recent discovery of a record of daily growth of larvae in their otoliths (ear bones) has been applied to estimate growth and survival rates of a large number of species [Campana and Neilsen, 1985; Jones, 1986]. Immunoassay techniques, in which antibodies to particular fish species are developed and used to detect the presence of macerated remains of eggs or larvae of that species in predator guts, have also found increasing use [Theilacker et al., 1993]. Determining the nutritional state of larvae through histological assessment, and determining RNA-DNA ratios of whole larvae, or in cells of particular organs, has proven very valuable [Theilacker, 1978; Buckley, 1984; Clemmensen, 1988; Theilacker and Shen, 1993; Canino, 1994]. All of these techniques have been refined and applied in FOCI studies.
Laboratory rearing studies with larval pollock confirmed that increments are deposited daily in their otoliths [Bailey and Stehr, 1988]. Growth rates and hatch dates, based on length and age determined by otolith increments, of field-collected pollock larvae from various years and areas, have been compared [Yoklavich and Bailey, 1990]. Growth rates were found not to vary interannually, but the hatching period did. By estimating decreases in the abundance of cohorts within year classes with time during the larval period, mortality rates have been calculated [Yoklavich and Bailey, 1990]. These techniques were used to investigate differences in larval survival during the season. It was found that larvae that were at a first feeding stage during calm weather, had higher survival rates than larvae that reached first feeding during storms [Bailey and Macklin, 1994]. Growth rates of young-of-the-year juveniles have been determined, although beyond the larval period otolith growth is more complex and grinding is required to discern all of the increments [Brown and Bailey, 1992; Bailey et al., 1994a]. Besides using the record of daily growth in larval otoliths, studies have analyzed the elements deposited in the otoliths as a record of the environment experienced by the larvae at various times during their development. This technique has been investigated as a means of discriminating among juvenile pollock of various geographic/genetic origins [Severin et al., 1995].
To investigate predation on fish eggs and larvae by invertebrates that macerate their prey, antibodies against yolk proteins were developed, and potential predator gut contents have been assayed for the presence of these proteins [Bailey et al., 1993; Brodeur and Merati, 1993]. Decapod shrimp, euphausids, and gammarid amphipods were all found to consume significant numbers of pollock eggs and yolk-sac larvae. We are now developing immunoassays for later stage larvae to investigate the role of predators in their mortality (Brodeur, R.D. and N. Merati, pers. comm.).
DNA of individual cells is fairly constant, so the DNA content of whole animals increases proportional to increases in cell number (growth). However, RNA content of cells is variable, and reflects active protein synthesis. RNA/DNA ratios have been found to be accurate indicators of recent feeding of larvae: higher ratios indicate better feeding condition [Canino, 1994]. Condition of pollock larvae, measured by RNA/DNA in whole individual larvae, has been found to vary with location, time of year, and interannually [Canino et al., 1991; Bailey et al., 1994b]. Variations in larval condition were concordant with variations in prey abundances. Thus it appears that pollock larvae in Shelikof Strait may experience feeding conditions that may limit growth. A prolongation of the larval stage due to reduced growth rate likely increases mortality. Even more precise indicators of larval nutritional condition and recent growth history have been developed using flow cytometry to measure RNA and DNA contents of brain cells of individual larvae [Theilacker and Shen, 1993]. These methods can be applied to assay larvae at sea in near real time.
NOAA's National Marine Fisheries Service (NMFS) advises the North Pacific Fisheries Management Council on the status of pollock stocks in the Gulf of Alaska and Bering Sea. The process includes a stock projection model, initialized with results from a model of stock assessment. The latter model employs commercial catch statistics and operational survey information to produce estimates of stock abundance. Given these results, the stock projection model forecasts future abundance as a function of different harvest and recruitment scenarios. The stock assessment model requires information independent of the fishery to calibrate estimates of absolute population. Prior to FOCI guidance, these were limited to the hydroacoustic and bottom-trawl surveys. For the last 2 years, estimates of spawning biomass for the Gulf of Alaska derived from the Annual Egg Production Method [Picquelle and Megrey, 1993] have provided a third source of information.
The effects of management decisions on the Shelikof Strait pollock population are examined using alternative harvest and recruitment scenarios in the stock projection model. Beginning in 1992, FOCI has analyzed biological and physical time series to estimate recruitment qualitatively. This prediction significantly simplifies the stock projection analysis by limiting the number of viable recruitment scenarios. The forecast of year-class strength uses hydroacoustic survey results of spawning aggregations, ichthyoplankton surveys of eggs and larvae, estimates of spawning biomass/recruitment from the annual stock assessment [Hollowed et al., 1993], and a suite of biological and physical factors. Previous modeling of pollock recruitment [Megrey et al., 1995] did not address the autocorrelated nature of the recruitment data. In 1993, the recruitment modeling was augmented with the development of a transfer function model. This model uses the same physical environmental data as before, but accounts for the autocorrelation of recruitment. In addition, it directly predicts recruitment. In 1993 it was used to generate recruitment scenario candidates for the stock projection model. FOCI's prediction made in 1992 was for weak 1989-90 year classes, a weak to average 1991 year class, and a strong 1992 year class. Recent observations of recruitment to the 1989 and 1990 year classes are consistent with this prediction.
Acknowledgments. We thank the numerous scientists who planned, conducted and published their research, and those who have provided information not yet published. In particular, Phyllis Stabeno, Ron Reed, and Jeff Napp for their continuous support and critical comments on this manuscript, and Allen Macklin, FOCI Program Coordinator. We also thank all the technical staff who assisted with the data acquisition, preparation, and analysis. Continued superlative support has been provided by the NOAA Ship Miller Freeman, and on specific cruises by the NOAA Ships Discoverer and Surveyor. A portion of this research and analysis was funded by Minerals Management Service, Interagency Agreement #14-35-0001-14165. The majority of research was funded by Fisheries Oceanography Coordinated Investigations and NOAA's Coastal Ocean Program. Wopila Tunkashila, Maki Unci and Grandmother Ocean. This is FOCI contribution #212 and Pacific Marine Environmental Laboratory contribution #1535.
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