SPATIAL VARIATION IN ZOOPLANKTON SIZE AND TAXONOMIC COMMUNITY STRUCTURE ALONG A 50ºN TO 50°S TRANSECT OF THE ATLANTIC

Zooplankton play a vital role in the world's oceans in terms of transport of carbon out of the surface layer and providing food for fish. Zooplankton are patchily distributed on all scales, and this has important consequences for both sampling and understanding their role in the ocean. The distribution of zooplankton on different scales forms the focus of this study. Three Atlantic Meridional Transect (AMT) cruises were carried out and data made available from three previous cruises. Zoo plankton data were collected using a combination of vertical nets and using an optical plankton counter (OPC) sampling from the pumped seawater supply. Validation of methods showed that the OPC data could reliably be converted to carbon and numerical abundance estimates for open ocean conditions. Spectral analysis suggested that surface zooplankton heterogeneity followed a power law relationship over several scales. Over the 30 to 1000 km range this was approximately -1, and for smaller and larger scales the slope was reduced. Chlorophyll was less patchy, following temperature and salinity over the same range with a slope of -1.8. Analysis of large scale heterogeneity showed clear latitudinal trends in diversity, particularly evident in the copepod genera, with low diversity at high latitudes. The size structure appeared to be more closely related to the productivity of the area, with high zooplankton biomass associated with larger zooplankton. Regions with similar copepod communities were identified. These were found to be similar to other pelagic regions, but less closely related to watermasses or production regimes. Multiple linear regression of surface zooplankton biomass showed a strong relationship with the physics (temperature and salinity), chlorophyll and the time of day, accounting for 55% of the variability. Use of the regression equations to predict new transects gave R²=0.34. Improvement could be made by dividing the transect into smaller regions. Neural networks gave enhanced predictability (R² = 0.77 for the training set, and R²= 0.47 for the novel set) with a simpler model, although similar variables were important. This study has shown that copepods show latitudinal gradient in diversity, associated with seasonality, and form regions of similarity that do not conform to biogeochemical provinces or the watermasses. Neural networks may be used to predict zooplankton abundance from a few readily available parameters.CCMS Plymouth Marine Laborator

Life history strategies and spatial dynamics of the Barents Sea capelin (Mallotus villosus)

Dr. Scient. Thesis. / Department of Fisheries and Marine Biology. University of Bergen. NorwayThis thesis consists of four papers on the life history strategy and spatial distribution of the Barents Sea capelin (Mallotus villosus). In the first two papers, sex specific aspects of capelin life history are investigated from a combination of field sampling and modelling. Paper III deals with the development of a concept for modelling spatial distribution of fish, and in Paper IV the concept is applied for the Barents Sea capelin. Female capelin were found to invest much more energy into reproductive tissue than males. Capelin fecundity was found to depend upon body weight, and inter annual variation in fecundity is related to variation in body weight. A life history model (Paper II) predicts that males have a higher fitness associated with semelparity than females since males may fertilise many females, whereas female fitness is limited by her number of eggs. Given a high or variable adult mortality risk, it may be more profitable for males to be semelparous than iteroparous. Capelin is therefore predicted to have sex specific life history strategies with semelparous males and iteroparous females. This prediction is supported by literature on capelin ecology. In Paper III a concept for modelling spatial distribution of fish is developed. The background for applying a new approach to studying fish distribution, is the lack of approaches for solving specific problems related to capelin ecology. The model is individual based and behaviour is calculated using an artificial neural network where weights are evolved using a genetic algorithm. Through simulating evolution by natural selection in a seasonal spatial model with life cycle, physiology, mortality, and reproduction, the individuals with the best "genetic weights" become increasingly more common in the population. Eventually the population consists of well-adapted individuals, which migrate back to spawning areas in winter, and grow and avoid being eaten throughout the rest of the year. The importance of separating between reactive and predictive behaviour in controlling local search and long distance migration respectively, is discussed. In Paper IV this model is elaborated to include: explicit representation of each stage in the life cycle of the Barents Sea capelin, larval drift, and evolution of spawning areas and timing of reproduction. Furthermore the model includes life history traits such as size at maturity, allocation of energy, and number of reproductive events. Larval drift was associated with a warm water area, and the evolved spawning ground was situated upstream from this, in the outskirts of the range for capelin spawning. The migration pattern follows the same general pattern as that of the Barents Sea capelin. In a simulation with stochastic mortality rates, sex specific life history strategies with semelparous males and iteroparous females were evolved, which supports the predictions from Paper II. The major achievement of this study is the development of an evolutionary system for fish migration, and the way this is applied to provide predictions about the life history and spatial dynamics of the Barents Sea capelin. Another important finding is the recognition that some aspects of capelin life history strategy are sex specific, with female iteroparity and male semelparity

Machine learning techniques to characterize functional traits of plankton from image data

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms

Chapter 2 Towards an Optimal Design for Ecosystem-Level Ocean Observatories

Four operational factors, together with high development cost, currently limit the use of ocean observatories in ecological and fisheries applications: 1) limited spatial coverage; 2) limited integration of multiple types of technologies; 3) limitations in the experimental design for in situ studies; and 4) potential unpredicted bias in monitoring outcomes due to the infrastructure’s presence and functioning footprint. To address these limitations, we propose a novel concept of a standardized “ecosystem observatory module” structure composed of a central node and three tethered satellite pods together with permanent mobile platforms. The module would be designed with a rigid spatial configuration to optimize overlap among multiple observation technologies each providing 360° coverage of a cylindrical or hemi-spherical volume around the module, including permanent stereo-video cameras, acoustic imaging sonar cameras, horizontal multi-beam echosounders and a passive acoustic array. The incorporation of multiple integrated observation technologies would enable unprecedented quantification of macrofaunal composition, abundance and density surrounding the module, as well as the ability to track the movements of individual fishes and macroinvertebrates. Such a standardized modular design would allow for the hierarchical spatial connection of observatory modules into local module clusters and larger geographic module networks, providing synoptic data within and across linked ecosystems suitable for fisheries and ecosystem level monitoring on multiple scales

Towards an optimal design for ecosystem-level ocean observatories

Four operational factors, together with high development cost, currently limit the use of ocean observatories in ecological and fisheries applications: 1) limited spatial coverage; 2) limited integration of multiple types of technologies; 3) limitations in the experimental design for in situ studies; and 4) potential unpredicted bias in monitoring outcomes due to the infrastructure’s presence and functioning footprint. To address these limitations, we propose a novel concept of a standardized “ecosystem observatory module” structure composed of a central node and three tethered satellite pods together with permanent mobile platforms. The module would be designed with a rigid spatial configuration to optimize overlap among multiple observation technologies each providing 360° coverage around the module, including permanent stereo-video cameras, acoustic imaging sonar cameras, horizontal multi-beam echosounders and a passive acoustic array. The incorporation of multiple integrated observation technologies would enable unprecedented quantification of macrofaunal composition, abundance and density surrounding the module, as well as the ability to track the movements of individual fishes and macroinvertebrates. Such a standardized modular design would allow for the hierarchical spatial connection of observatory modules into local module clusters and larger geographic module networks, providing synoptic data within and across linked ecosystems suitable for fisheries and ecosystem level monitoring on multiple scales.Peer ReviewedPostprint (author's final draft

Acoustic correction factor estimate for compensating vertical diel migration of small pelagics

Differences in acoustic estimates of small pelagic fish biomass, due to data acquisition during daytime and nighttime surveys, have been recognized for many years as a problem in acoustic surveys. In the absence of a single rule for all species and for all locations, some expert groups identified specific time intervals for acoustic data acquisition in relation to the schooling behavior of the target species. In the Mediterranean Sea, the research groups working in the MEDIAS (Mediterranean International Acoustic Survey) agreed on the importance that acoustic sampling are conducted only during day-time. Only when available time does not permit to complete the survey during daytime, data collection might be extended. In this case, working on data collected during both daytime and nighttime, a bias may occur in the biomass estimates. In order to evaluate and correct such bias, specific experiments were performed in some geographical sub-areas of the Mediterranean Sea. The data analysis allowed the estimation of a mean correction factor for the Strait of Sicily, where five surveys were carried out in different years. The correction factor was estimated also for the Adriatic Sea, Tyrrhenian Sea and Northern Spain; the observed variability among areas highlighted the importance of the spatial and temporal coverage of the survey area in order to obtain reliable estimates of the correction factor. Further studies are necessary to improve the interpretation of the obtained estimates in relation to area-related peculiarities such as zooplankton composition and abundance along with small pelagic fish community structure

Chapter 5 Consequences of Anthropogenic Changes in the Sensory Landscape of Marine Animals

Human activities are altering a wide range of key marine cues at local and global scales, and it is important to know how animals may respond. Species survival and performance depend on the ability of individuals to successfully extract and interpret information from their environment about preferred abiotic conditions and the presence of prey, predators, competitors, mates and suitable habitats. Such information is made available via a wide range of abiotic and biotic cues that can be detected by organisms through various sensory modalities. Global anthropogenic changes, however, are rapidly altering the sensory landscape (‘cuescape’) and behaviour of animals by modifying the production, transmission and interpretation of critical natural cues, as well as introducing novel anthropogenic cues. To date, most studies have focussed on how animals respond to such changes rather than investigating how the cues themselves are changing. Because the responses that individuals show ultimately depend on factors affecting both the generation and reception of cues, better integration is needed to understand how these factors ultimately affect individual performance. This review provides a holistic assessment of how multiple cues (e.g. sounds, visual cues, chemicals, salinity, temperature and electromagnetism) are being altered at different spatial and temporal scales in marine habitats. Natural cuescapes are being modified by humans and novel anthropogenic cues are being introduced into the ocean, both of which can directly and indirectly alter the diversity and strength of natural cues. Examples are provided of how species might respond to such changes, focussing on what coping and adaptation mechanisms are available for species to persist in a future ocean. While ‘sensory generalist’ species may prevail in marine environments with diminishing or masked natural cues, some ‘sensory specialists’ might sustain themselves via sensory compensation, behavioural plasticity or avoidance of detrimental cues in the short term, or via genetic adaptation in the longer term. Due to the rapid loss of natural cuescapes, alternative research agendas are needed to monitor and measure multicue changes throughout the oceans. Together with mechanistic and field studies of animal responses, such research can inform management by identifying the species most at risk and the areas that may be suitable for cuescape preservation