scholarly journals Ontogenetic and seasonal trends in recent growth rates of Atlantic cod and haddock larvae on Georges Bank: effects of photoperiod and temperature

2006 ◽  
Vol 325 ◽  
pp. 205-226 ◽  
Author(s):  
LJ Buckley ◽  
EM Caldarone ◽  
RG Lough ◽  
JM St. Onge-Burns
1987 ◽  
Vol 44 (1) ◽  
pp. 14-25 ◽  
Author(s):  
L. J. Buckley ◽  
R. G. Lough

A transect across southern Georges Bank in May 1983 showed higher levels of available prey for haddock (Melanogrammus aeglefinus) and cod (Gadus morhua) larvae at two stratified sites than at a well-mixed site. At the stratified sites, prey biomass was high (30–300 μg dry wt∙L−1) near the surface above the thermocline; values were lower and more uniform with depth (10–30 μg dry wt∙L−1) at the well-mixed site. Larval population centers generally coincided with prey biomass vertically. Recent growth in dry weight of haddock larvae as estimated by RNA–DNA ratio analysis was higher at the stratified sites (8–13%∙d−1) than at the well-mixed site (7%∙d−1). Larvae appeared to be in excellent condition at the stratified sites, but up to 50% of haddock larvae from the well-mixed site had RNA–DNA ratios in the range observed for starved larvae in the laboratory. Cod collected at the same site were in better condition and growing faster than haddock. The data support the hypotheses that (1) stratified conditions in the spring favor good growth and survival of haddock larvae and (2) cod larvae are better adapted to grow and survive in well-mixed waters at lower levels of available food than haddock larvae.


1979 ◽  
Vol 36 (12) ◽  
pp. 1497-1502 ◽  
Author(s):  
L. J. Buckley

The protein, DNA, and RNA content of larvae maintained at 1.0 plankter/mL increased at the rates of 9.3, 9.9, and 9.8% per day, respectively, for the 5 wk after hatching. Protein reserves of larvae held at 0 or 0.2 plankters/mL were depleted by 45 and 35%, respectively, prior to death 12–13 d after hatching. Starved larvae had similar protein concentrations (percent of dry weight), lower RNA concentrations, and higher DNA concentrations than fed larvae. Larvae held at higher plankton densities had higher RNA–DNA ratios and faster growth rates than larvae held at lower plankton densities. The RNA–DNA ratio was significantly correlated (P < 0.01) with the protein growth rate. The RNA–DNA ratio appears to be a useful index of nutritional status in larval Atlantic cod (Gadus morhua) and may be useful for determining if cod larvae were in a period of rapid or slow growth at the time of capture. Key words: RNA–DNA ratio, starvation, protein, nucleic acids, growth, larval fish, Atlantic cod


2003 ◽  
Vol 60 (9) ◽  
pp. 1111-1121 ◽  
Author(s):  
Tara M McIntyre ◽  
Jeffrey A Hutchings

Life histories of Atlantic cod (Gadus morhua) from the Gulf of St. Lawrence south to Georges Bank differ significantly through time and space. Within the Southern Gulf, fecundity per unit body mass differed by more than 40% over short (2 years) and long (42–45 years) periods of time. Significant variation in size-specific fecundity is also evident among populations: Southern Gulf cod produce almost 30% more eggs per unit body mass than those on Georges Bank, whereas fecundity of Scotian Shelf cod is almost half that of cod in Sydney Bight. Compared with those on Georges Bank, Southern Gulf cod life histories are characterized by high fecundity, late maturity, high gonadosomatic index, and large eggs. Relative to the influence of body size, neither temporal nor spatial differences in fecundity can be attributed to physiological condition, as reflected by liver weight, hepatosomatic index, and Fulton's K. Delayed maturity and higher reproductive allotment among Southern Gulf cod can be explained as selection responses to slower growth, higher prereproductive mortality, and fewer lifetime reproductive events. Patterns of covariation in heritable, fitness-related traits suggest the existence of adaptive variation and evolutionarily significant units at spatial scales considerably smaller than the species range in the Northwest Atlantic.


2006 ◽  
Vol 53 (23-24) ◽  
pp. 2771-2788 ◽  
Author(s):  
R.G. Lough ◽  
E.A. Broughton ◽  
L.J. Buckley ◽  
L.S. Incze ◽  
K. Pehrson Edwards ◽  
...  

2017 ◽  
Vol 74 (6) ◽  
pp. 1587-1601 ◽  
Author(s):  
Gregory R. DeCelles ◽  
David Martins ◽  
Douglas R. Zemeckis ◽  
Steven X. Cadrin

Abstract The spawning dynamics of Atlantic cod (Gadus morhua) on Georges Bank and Nantucket Shoals are not well understood. To address this uncertainty, we combined Fishermen’s Ecological Knowledge (FEK) with traditional scientific data to develop a more holistic understanding of cod spawning on Georges Bank. Data from historical reports, trawl surveys, fisheries observers, and ichthyoplankton surveys were used to describe the spatial and temporal distribution of cod spawning activity. We also collected FEK regarding cod spawning dynamics through semi-structured interviews (n = 40). The fishermen had detailed knowledge of the spatial and temporal distribution of cod spawning, and identified persistent fine-scale (i.e. &lt;50 km2) spawning grounds that were often associated with specific habitat features, including spawning grounds that were previously unreported in the scientific literature. The spawning seasons and locations identified by fishermen generally agreed with information from traditional scientific data, but it was evident that seasonal scientific surveys lack the spatial and temporal resolution needed to fully characterize the distribution of cod spawning activity. Our results will help inform management measures designed to promote the rebuilding of Georges Bank cod, and also provide a basis for further investigations of cod spawning dynamics and stock structure.


2009 ◽  
Vol 99 (1) ◽  
pp. 47-54 ◽  
Author(s):  
Alexandre Alonso-Fernández ◽  
Ann Carole Vallejo ◽  
Fran Saborido-Rey ◽  
Hilario Murua ◽  
Edward A. Trippel

1996 ◽  
Vol 23 (4) ◽  
pp. 332-342 ◽  
Author(s):  
Matthias Ruth ◽  
James Lindholm

SummaryMany factors influence the dynamics of fisheries and feedback mechanisms amongst these factors are poorly understood. The ecological systems are too large and complex to conduct controlled experiments and economic adjustments to changes in fish populations defy traditional equilibrium analysis. New modelling approaches are required to identify the driving forces behind the dynamics of exploited fish populations, assess likely consequences of alternative management measures, and achieve consensus among stakeholders.We present an interdisciplinary modelling approach that can be used easily to assess dynamic consequences of alternative assumptions for certain key biological and economic parameters, and incorporates the input of various stakeholder groups in the fishery. Contributions of scientists, economists and managers to the model can be augmented with contributions from the fisherfolk.Our approach is illustrated by a dynamic computer model capturing the interactions of three demersal fish species on Georges Bank, namely Atlantic Cod (Gadus morhua), Haddock (Melanogramus aeglefimts) and Pollack (Pollachius virens), population sizes of which are assumed to be density-dependent for the purposes of the model and are significantly affected by management decisions. The model addresses how management measures for one species influence the population dynamics of other commercially exploited species. Various scenarios are run to explore the implications of viable management strategies under alternative assumptions on the driving forces behind complex ecological-economic processes. The analyses indicate that neither small reductions in effort nor mesh size increases are likely to prevent the further demise of the Georges Bank ground fisheries, and, in fact, stocks of the three targeted species may decline. Alternative management measures seem to be necessary to prevent collapse, and might include various strategies, such as effort controls and mesh size reductions, in conjunction with a dramatic change in fishing technology. The assessment and viability of alternative management measures in turn require that consensus is generated among stakeholders about data and models.


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