The interrelation between temperature regimes and fish size in juvenile Atlantic cod (Gadus morhua): effects on growth and feed conversion efficiency

The present paper describes the growth properties of juvenile Atlantic cod (Gadus morhua) reared at 7, 10, 13 and 16 °C, and a group reared under “temperature steps” i.e. with temperature reduced successively from 16 to 13 and 10 °C. Growth rate and feed conversion efficiency of juvenile Atlantic cod were significantly influenced by the interaction of temperature and fish size. Overall growth was highest in the 13 °C and the T-step groups but for different reasons, as the fish at 13 °C had 10% higher overall feeding intake compared to the T-step group, whereas the T-step had 8% higher feeding efficiency. After termination of the laboratory study the fish were reared in sea pens at ambient conditions for 17 months. The groups performed differently when reared at ambient conditions in the sea as the T-step group was 11.6, 11.5, 5.3 and 7.5% larger than 7, 10, 13 and 16 °C, respectively in June 2005. Optimal temperature for growth and feed conversion efficiency decreased with size, indicating an ontogenetic reduction in optimum temperature for growth with increasing size. The results suggest an optimum temperature for growth of juvenile Atlantic cod in the size range 5–50 g dropping from 14.7 °C for 5–10 g juvenile to 12.4 °C for 40–50 g juvenile. Moreover, a broader parabolic regression curve between growth, feed conversion efficiency and temperature as size increases, indicate increased temperature tolerance with size. The study confirms that juvenile cod exhibits ontogenetic variation in temperature optimum, which might partly explain different spatial distribution of juvenile and adult cod in ocean waters. Our study also indicates a physiological mechanism that might be linked to cod migrations as cod may maximize their feeding efficiency by active thermoregulation

Trophic Relationships of Coastal and Estuarine Ecosystems

[Extract] Food has been one of the major drivers of human interaction with coastal and estuarine ecosystems, and this has impelled much of the study of these systems. In its initial phase, greater understanding would have brought direct payoffs in the form of greater catches and, now, greater understanding is necessary to not just to counter past mistakes (such as overexploitation, habitat loss, and pollution) but also future pressures (such as climate change). The key change has been in the recognition that the oceans were not an infinite resource, and that sustainability of the resources was the key not only regarding commercial returns, but also in terms of socioeconomic stability of the human populations. As a result, scientific investigations in the cause of exploitation of the fisheries' resources, for example, has progressed from a simple goal of maximizing the catches through one where long-term yields (e.g., MSY or maximum sustainable yield) of single species were the required model outputs to the present situation in which the sustainability of the ecosystem itself is the overriding goal

Using social network analysis tools in ecology: Markov process transition models applied to the seasonal trophic network dynamics of the Chesapeake Bay

Ecosystem components interact in complex ways and change over time due to a variety of both internal and external influences (climate change, season cycles, human impacts). Such processes need to be modeled dynamically using appropriate statistical methods for assessing change in network structure. Here we use visualizations and statistical models of network dynamics to understand seasonal changes in the trophic network model described by Baird and Ulanowicz [Baird, D., Ulanowicz, R.E., 1989. Seasonal dynamics of the Chesapeake Bay ecosystem. Ecol. Monogr. 501 (59), 329-364] for the Chesapeake Bay (USA). Visualizations of carbon flow networks were created for each season by using a network graphic analysis tool (NETDRAW). The structural relations of the pelagic and benthic compartments (nodes) in each seasonal network were displayed in a two-dimensional space using spring-embedder analyses with nodes color-coded for habitat associations (benthic or pelagic). The most complex network was summer, when pelagic species such as sea nettles, larval fishes, and carnivorous fishes immigrate into Chesapeake Bay and consume prey largely from the plankton and to some extent the benthos. Winter was the simplest of the seasonal networks, and exhibited the highest ascendency, with fewest nodes present and with most of the flows shifting to the benthic bacteria and sediment POC compartments. This shift in system complexity corresponds with a shift from a pelagic- to benthic-dominated system over the seasonal cycle, suggesting that winter is a mostly closed system, relying on internal cycling rather than external input. Network visualization tools are useful in assessing temporal and spatial changes in food web networks, which can be explored for patterns that can be tested using statistical approaches. A simulation-based continuous-time Markov Chain model called SIENA was used to determine the dynamic structural changes in the trophic network across phases of the annual cycle in a statistical as opposed to a visual assessment. There was a significant decrease in outdegree (prey nodes with reduced link density) and an increase in the number of transitive triples (a triad in which i chooses j and h, and j also chooses h, mostly connected via the non-living detritus nodes in position i), suggesting the Chesapeake Bay is a simpler, but structurally more efficient, ecosystem in the winter than in the summer. As in the visual analysis, this shift in system complexity corresponds with a shift from a pelagic to a more benthic-dominated system from summer to winter. Both the SIENA model and the visualization in NETDRAW support the conclusions of Baird and Ulanowicz [Baird, D., Ulanowicz, R.E., 1989. Seasonal dynamics of the Chesapeake Bay ecosystem. Ecol. Monogr. 501 (59), 329-364] that there was an increase in the Chesapeake Bay ecosystem's ascendancy in the winter. We explain such reduced complexity in winter as a system response to lowered temperature and decreased solar energy input, which causes a decline in the production of new carbon, forcing nodes to go extinct; this causes a change in the structure of the system, making it simpler and more efficient than in summer. It appears that the seasonal dynamics of the trophic structure of Chesapeake Bay can be modeled effectively using the SIENA statistical model for network change. © 2009 Elsevier B.V. All rights reserved

Estrutura populacional de Hyale media (Dana) (Amphipoda, Gammaridea, Hyalidae), habitante dos fitais de Caiobá, Matinhos, Paraná, Brasil Population structure of the seaweed dweller Hyale media (Dana) (Amphipoda, Gammaridea, Hyalidae) from Caiobá, Matinhos, Paraná, Brazil

<abstract language="eng">A study of correlation between the total body length and the somites length was carried out in a population of Hyale media (Dana, 1857), in order to know which somite or group of somites has the highest correlation index with the total body length. As the sum of the length of the first to fourth pereonites showed the highest linear correlation index (Y=0.0764+0.2736X; r=0.9723), this meristic parameter was chosen to describe the population structure of the species. The following aspects were treated: distribution of the body size classes in the various phytals, population composition, seasonal fluctuation of population density. relative frequency of the ovigerous females and correlation between the body length and the number of eggs inside the marsupium of the ovigerous females. The amphipods were obtained from the seasonal collections of six phytals from a rocky seashore of Caiobá, Paraná State: Pterosiphonia pennata (Roth) Falkenberg. Gymrogongrus griffithsiae (Turner) Martius, Pterocladia capillacea (Gmelin) Bornet & Thured, Sargassum cymosum Garth, Gelidium sp and Ulva fasciata Delile; they did not occurred in Padina gymnospora (Kútsing) Vickers and Porphyra atropurpurea (Olivi) De Toni. The air temperature oscillated from 16ºC (winter and autumn) to 23ºC (summer), the surface water temperature from 17ºC (winter) to 25ºC (summer) and the surface water salinity, from 29.3‰ (autumn) to 32.8‰ (winter). The density oi Hyale media varied from 0.20 ind.g-1 (in Ulva) to 26.37 ind.g-1 (in Pterosiphonia) of alga-substratum weigth, and the population was distributed mainly in branched algae. It was determined three size classes in the population, within a range from 0.01 to 2.99mm of pereonits 1-4 length. Small amphipods prefer finely branched algae like Gymnogongrusand Pterosiphonia, whereas broad-thallii or less branched algae such as Sargassum, Pterocladia, Gelidium and Ulva harbour proporcionally high number of large individuais. The life cycle of Hyale media takes place wholly in the phytals and the species reproduces continually all year round: males, ovigerous females and juveniles are present every season. The highest femalc reproductive activity occurs in winter and the juveniles are more numerous in summer. The number of eggs inside the marsupium and the pereonites 1-4 length has a linear correlation (Y=-9,9682+12,0729X; r=0.8024)

Group-Level Analysis and Visualization of Social Networks

Social network analysis investigates the structure of relations amongst social actors. A general approach to detect patterns of interaction and to filter out irregularities is to classify actors into groups and to analyze the relational structure between and within the various classes. The first part of this paper presents methods to define and compute structural network positions, i. e., classes of actors dependent on the network structure. In the second part we present techniques to visualize a network together with a given assignment of actors into groups, where specific emphasis is given to the simultaneous visualization of micro and macro structure