Predicting Barents Sea Cod Stock Dynamics Using Oceanographic Data and Neural Network Analysis

The growth biochronology extracted from the BLUP for the Year random effect was successful in reconstructing population-level variations of NEA cod growth, as shown by the correlation with mean size-at-age and growth rate time series extracted from survey data.Considering

Understanding the drivers behind fluctuations in fish populations remains a key objective in fishery science. Our predictive capacity to explain these fluctuations is still relatively low, due to the amalgam of interacting bottom-up and top-down factors, which vary across time and space among and within populations. Gaining a mechanistic understanding of these recruitment drivers requires a holistic approach, combining field, experimental and modelling efforts. Here, we use the Western Baltic Spring-Spawning (WBSS) herring (Clupea harengus) to exemplify the power of this holistic approach and the high complexity of the recruitment drivers (and their interactions). Since the early 2000s, low recruitment levels have promoted intense research on this stock. Our literature synthesis suggests that the major drivers are habitat compression of the spawning beds (due to eutrophication and coastal modification mainly) and warming, which indirectly leads to changes in spawning phenology, prey abundance and predation pressure. Other factors include increased intensity of extreme climate events and new predators in the system. Four main knowledge gaps were identified related to life-cycle migration and habitat use, population structure and demographics, life-stage specific impact of multi-stressors, and predator–prey interactions. Specific research topics within these areas are proposed, as well as the priority to support a sustainable management of the stock. Given that the Baltic Sea is severely impacted by warming, eutrophication and altered precipitation, WBSS herring could be a harbinger of potential effects of changing environmental drivers to the recruitment of small pelagic fishes in other coastal areas in the world.Graphical abstract

Chapter 15 - Variable Replenishment and the Dynamics of Reef Fish Populations

The difference between the yearly maximum and minimum water levels (YMXR) is an index of lake dynamics: shoals are exposed and inundated, nutrients are oxidized and reduced, and the diversity and density of the aquatic plant community are affected. Shoals and emergent macrophytes provide spawning habitat for fish. The 5-yr moving variance of YMXR fluctuates regularly with periods of about 11.2 yr (periodicity of sunspot cycles). This reflects the effects of within-year consecutive periods of storms and dry spells. Water level regulations resulted in changes in both amplitudes and frequencies of YMXR compared with natural fluctuations. We established links between fluctuations in YMXR and fluctuations in fish populations. Water level regulations, through their effects on YMXR, corresponded to changes in interspecific interactions on Rainy Lake and the Namakan Reservoir. In both, walleye's (Stizostedion vitreum) fluctuations were synchronized with both those of lake whitefish (Coregonus clupeaformis) and northern pike (Esox lucius) more than those of either species with the other two. On the Namakan Reservoir, YMXR fluctuations were accentuated by water level regulation; on Rainy Lake, they were dampened. Regulations should consider frequencies and amplitudes of changes in water level and their effect on fish populations.

Oceanographers have long viewed `intensive area study' as a step in the internal development of oceanography. But for its first American practitioner, Henry Bryant Bigelow, intensive area study was a new and innovative approach that allowed him to pursue fundamental questions of hydrology and zoology within the restrictions imposed by his patron, the US Bureau of Fisheries. Intellectually, such methods promised a long-term solution to the problem of predicting fluctuations in fish populations; practically, they required little money and allowed Bigelow to stay physically near the New England fisheries. Reconstructing Bigelow's relationship to the USBF provides the political and social context necessary for understanding the origins and acceptance of a scientific practice. It also shows how scientists must often negotiate between the demands of their patrons for practical information and the demands of their disciplines for `pure' science.

Fluctuations in fish populations in lakes can cascade through food webs to alter nutrient cycling, algal biomass and primary production. Trophic cascades may interact with nutrients and physical factors to explain most of the variance in lake ecosystem process rates. In this 1993 book, a multidisciplinary research team tests this idea by manipulating whole lakes experimentally, and coordinating this with palaeolimnological studies, simulation modelling, and small-scale enclosure experiments. Consequences of predator-prey interactions, behavioural responses of fishes, diel vertical migration of zooplankton, plankton community change, primary production, nutrient cycling and microbial processes are described. Palaeolimnological techniques enable the reconstruction of trophic interactions from past decades. Prospects for analysing the interaction of food web structure and nutrient input in lakes are explored.

Fossil fish scales hold potential for elucidating past fluctuations in fish populations. Only certain pilchard Sardinops ocellatus and anchovy Engraulis capensis scales can be distinguished easily from each other. Misidentification of the less-typical scales of the two species can introduce a bias in scale-based population studies and, in order to overcome this bias, scales removed from pilchard and anchovy reared in captivity were examined. A complete set of reference photographs of the scales of each species was compiled and study of these showed that both pilchard and anchovy have five distinctive scale types, each of which is found on different parts of the fish. It was also shown that the "typical" scales of each species, i.e. those referred to in the literature, constitute less than 50 per cent of the scales found on the fish.

A central and classic question in ecology is what causes populations to fluctuate in abundance. Understanding the interaction between natural drivers of fluctuating populations and human exploitation is an issue of paramount importance for conservation and natural resource management. Three main hypotheses have been proposed to explain fluctuations: (i) species interactions, such as predator-prey interactions, cause fluctuations, (ii) strongly nonlinear single-species dynamics cause fluctuations, and (iii) environmental variation cause fluctuations. We combine a general fisheries model with data from a global sample of fish species to assess how two of these hypothesis, nonlinear single-species dynamics and environmental variation, interact with human exploitation to affect the variability of fish populations. In contrast with recent analyses that suggest fishing drives increased fluctuations by changing intrinsic nonlinear dynamics, we show that single-species nonlinear dynamics alone, both in the presence and absence of fisheries, are unlikely to drive deterministic fluctuations in fish; nearly all fish populations fall into regions of stable dynamics. However, adding environmental variation dramatically alters the consequences of exploitation on the temporal variability of populations. In a variable environment, (i) the addition of mortality from fishing leads to increased temporal variability for all species examined, (ii) variability in recruitment rates of juveniles contributes substantially more to fluctuations than variation in adult mortality, and (iii) the correlation structure of juvenile and adult vital rates plays an important and underappreciated role in determining population fluctuations. Our results are robust to alternative model formulations and to a range of environmental autocorrelation.

Analysing how fish populations and their ecological communities respond to perturbations such as fishing and environmental variation is crucial to fisheries science. Researchers often predict fish population dynamics using species‐level life‐history parameters that are treated as fixed over time, while ignoring the impact of intraspecific variation on ecosystem dynamics. However, there is increasing recognition of the need to include processes operating at ecosystem levels (changes in drivers of productivity) while also accounting for variation over space, time and among individuals. To address similar challenges, community ecologists studying plants, insects and other taxa increasingly measure phenotypic characteristics of individual animals that affect fitness or ecological function (termed “functional traits”). Here, we review the history of trait‐based methods in fish and other taxa, and argue that fisheries science could see benefits by integrating trait‐based approaches within existing fisheries analyses. We argue that measuring and modelling functional traits can improve estimates of population and community dynamics, and rapidly detect responses to fishing and environmental drivers. We support this claim using three concrete examples: how trait‐based approaches could account for time‐varying parameters in population models; improve fisheries management and harvest control rules; and inform size‐based models of marine communities. We then present a step‐by‐step primer for how trait‐based methods could be adapted to complement existing models and analyses in fisheries science. Finally, we call for the creation and expansion of publicly available trait databases to facilitate adapting trait‐based methods in fisheries science, to complement existing public databases of life‐history parameters for marine organisms.

10 Environmental and resource variability off Northwest Africa and in the gulf of guinea: A review

Taiwan Bank (TB) is located in the southern Taiwan Strait (TS). The uplifted continental slope and bottom currents in this area result in the formation of upwelling areas, which serve as crucial fishing grounds. Climate-induced fluctuations in fish populations occur in the TS. However, how predation and competition affect the interspecies relationships in the TB ecosystem warrants clarification. In this study, we collected high-grid-resolution data on fishery activity (2013–2019) and constructed ecosystem models using Ecopath with Ecosim (EwE). Three mass-balanced models for determining the influence of El Niño–Southern Oscillation (ENSO) events on the TB ecosystem were constructed using EwE. A range of groups, including representative pelagic, benthic, and reef species, were collected for analyzing the relationship between migratory and sedentary species in terms of ecosystem structure variation due to climate change. The results demonstrated that the total system throughput (TST) was 10,556–11,122 t km−2 year−1, with an average transfer efficiency of 12.26%. According to the keystoneness index, calculated through mixed trophic impact analysis, Polydactylus sextarius and Scomber japonicus were the key species with top–down control and relatively high impact on the ecosystem in normal years. The keystone species also shifted to the predator fish Thunnus albacares and Katsuwonus pelamis during El Niño and La Niña events, respectively. Moreover, total biomass, TST, consumption, and respiration were noted to increase during ENSO events. However, during La Niña events, the diversity and connectance indexes were relatively low but pelagic species’ biomass was relatively high, whereas the biomass of most benthic and reef species was relatively high during El Niño events.

ABSTRACTCategorical time series regression was applied to 55 fish stocks in the Potomac, Hudson, Narragansett, Delaware, and Connecticut estuaries for the period 1929–1975. Interannual variability in catch per unit effort (CPUE) was related to CPUE, hydrographic variables, and pollution variables, lagged back in time to represent the conditions contributing to the multiple ages comprising each fishery. Hydrographic variables included water temperature and flow in the estuary– and, for offshore spawning stocks, wind direction and magnitude–during the months of spawning and early life stage development. Pollution variables included measures of dissolved oxygen conditions in the estuaries, volume of material dredged, and sewage loading (or human population). Lagged CPUE, hydrographic variables, and pollution variables all played important roles in explaining historical variability in CPUE. Lagged CPUE was significant in 45 of 55 stocks generally accounting for 5–35% of the variability. Lagged hydrographic variables were significant in 53 of 55 stocks, explaining an additional 5–40% of the variability unaccounted for by lagged CPUE. Lagged pollution variables were significant in 35 of 55 stocks, generally accounting for an additional 5–30% of the variability not explained by lagged CPUE and hydrographic variables. Results did not exhibit expected patterns of consistency in the importance of lagged CPUE for a species across estuaries or consistency in the importance of pollution variables across estuaries. Results did exhibit the expected north‐to‐south longitudinal pattern in the importance of timing of the hydrographic variables, the months of importance being one or two months later in more northerly estuaries. Higher‐order interaction effects were important in almost all stocks that were well‐modeled by categorical time series regression. Of the 30 stocks with final regression models having R2 > 0.55, 26 stocks involved significant interaction effects, five had only significant interaction effects (no significant main effects), and 20 stocks had significant interactions involving variables not significant as main effects. The difficulties involved in analyzing long‐term trends in fish populations and partitioning variability between natural and anthropogenic sources are discussed.

Using data on biomass and fishing mortality in stock production modelling of flatfish

The complexity and spatio–temporal scale of populations’ dynamics influence how populations respond to large‐scale ecological pressures. Detecting and attributing synchrony (i.e. temporally coincident fluctuations in populations’ parameters) is key as synchronous populations can become more vulnerable to stochastic events that can affect the viability of harvest and have profound consequences to community structure. Here, we aimed to estimate the level of synchrony in fish growth within and among species across 1 million km 2 and identify the environmental drivers contributing to synchronous population fluctuations. We developed otolith increment‐based growth chronologies for two deep‐sea scorpaenid fishes ( Helicolenus dactylopterus and Pontinus kuhlii ) from geographically and bathymetrically disjunct populations in the northeast Atlantic (one species in three locations; two species with different depth preferences). We used hierarchical models to partition variation in growth within and between populations attributing it to intrinsic (age, species, population) and extrinsic (environmental variables) drivers. We assessed synchrony in growth variation within and among species and identified common change points in population specific growth patterns. We documented time‐variant synchrony in growth variation of geographically and bathymetrically segregated deep‐sea fish populations, lasting 25 and 18 years, respectively. The observed synchrony was likely driven by shared environmental forcing (Moran effect) as large‐scale climate indices (East Atlantic pattern and North Atlantic Oscillation) were important environmental drivers of overall growth variation while the onset of synchrony in growth variation was likely related to marine regime shifts occurring in a wide area of the northeast Atlantic that affected the entire ecosystem. However, our capacity to extrapolate growth information across species and locations was dependent on the timing and magnitude of environmental change. Developing a better understanding of the mechanisms driving growth synchrony is key to ensure sustainable management of populations in habitats that are fragile and highly sensible to environmental change, such as the deep‐sea.

Climate variability and fisheries of black hakes ( Merluccius polli and Merluccius senegalensis) in NW Africa: A first approach