An assessment of scup (Stenotomus chrysops) and black sea bass (Centropristas striata) discards in the directed otter trawl fisheries in the Mid-Atlantic Bight

This study was undertaken to re-assess the level of scup (Stenotomus chrysops) discards by weight and to evaluate the effect of various codend mesh sizes on the level of scup discards in the winter-trawl scup fishery. Scup discards were high in directed scup tows regardless of codend mesh — typically one to five times the weight of landings. The weight of scup discards in the present study did not differ significantly from that recorded in scup-targeted tows in the NMFS observer database. Most discards were required as such by the 22.86 cm TL (total length) fish-size limit for catches. Mesh sizes ≤12.7 cm, including the current legal mesh size (11.43 cm) did not adequately filter out scup smaller than 22.86 cm. The median length of scup discards was about 19.83 cm TL. Lowering the legal size for scup from 22.86 to 19.83 cm TL would greatly reduce discard mortality. Scup discards were a small fraction (0.4%) of black sea bass (Centropristis striata) landings in blacksea-bass−targeted tows. The black sea bass fishery is currently regulated under the small-mesh fishery gearrestricted area plan in which fishing is prohibited in some areas to reduce scup mortality. Our study found no evidence to support the efficacy of this management approach. The expectations that discarding would increase disproportionately as the trip limit (limit [in kilograms] on catch for a species) was reached towards the end of the trip and that discards would increase when the trip limit was reduced from 4536 kg to 454 kg at the end of the directed fishing season were not supported. Trip limits did not significantly affect discard mortality

Photometric Decomposition of Barred Galaxies

We present a non-parametric method for decomposition of the light of disk galaxies into disk, bulge and bar components. We have developed and tested the method on a sample of 68 disk galaxies for which we have acquired I-band photometry. The separation of disk and bar light relies on the single assumption that the bar is a straight feature with a different ellipticity and position angle from that of the projected disk. We here present the basic method, but recognise that it can be significantly refined. We identify bars in only 47% of the more nearly face-on galaxies in our sample. The fraction of light in the bar has a broad range from 1.3% to 40% of the total galaxy light. If low-luminosity galaxies have more dominant halos, and if halos contribute to bar stability, the luminosity functions of barred and unbarred galaxies should differ markedly; while our sample is small, we find only a slight difference of low significance.Comment: Accepted to appear in AJ, 36 pages, 9 figures, full on-line figures available at http://www.physics.rutgers.edu/~sellwood/Reese.htm

A Modelling Study of the Influence of Environment and Food Supply on Survival of Crassostrea gigas Larvae

A biochemically based model was developed to simulate the growth, development, and metamorphosis of larvae of the Pacific oyster (Crassostrea gigas). The unique characteristics of the model are that it: (1) defines larvae in terms of their protein, neutral lipid, polar lipid, carbohydrate, and ash content; (2) tracks weight separately from length to follow larval condition; and (3) includes genetic variation in growth efficiency and egg quality to better simulate cohort population dynamics. The model includes parameterizations for filtration, ingestion, and respiration, which determine larval growth rate, and processes controlling larval mortality and metamorphosis. Changes in larval tissue composition occur as the larva grows and in response to the biochemical composition of the food. Simulations of larval growth indicate that departures of temperature, salinity, or food content from optimum levels reduce larval cohort survival, either because of metabolic constraints that result in death, unsuccessful metamorphosis, or increased predation resulting from increased larval lifespan. Temperatures and salinities near optimal values improve larval survival at low food concentration by increasing ingestion rate or growth efficiency. Also, survival at a given food concentration can vary widely depending on food composition, which determines food quality. The simulations suggest that the ratio of carbohydrate + lipid-to-protein may best describe the overall food quality, with optimal food compositions being characterized by ratios near 1.2 to 1.4 over a range of food concentrations. In contrast, food compositions containing too much or too little protein reduce larval survival, even at saturating food concentrations. In simulations emphasizing genetic variability within the cohort, larvae with high growth efficiency originating from large eggs out-perform other egg quality-growth efficiency combinations over a wide range of temperature, salinity, and food contents. As a consequence, suboptimal temperature, salinity, or food content compresses genetic variation by uniformly favouring larvae from large eggs with a high growth efficiency. However, the larval survival obtained from simulations that use a range of food qualities is representative of a much broader range of genetic types. Thus, the simulations support the supposition that food quality is an important variable controlling the survival and genetic variability of C. gigas larval cohorts. (C) 2004 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved

Fluxes and distribution of dissolved iron in the eastern (sub-) tropical North Atlantic Ocean

Aeolian dust transport from the Saharan/Sahel desert regions is considered the dominant external input of iron (Fe) to the surface waters of the eastern (sub-) tropical North Atlantic Ocean. To test this hypothesis, we investigated the sources of dissolved Fe (DFe) and quantified DFe fluxes to the surface ocean in this region. In winter 2008, surface water DFe concentrations varied between <0.1 nM and 0.37 nM, with an average of 0.13 ± 0.07 nM DFe (n = 194). A strong correlation between mixed layer averaged concentrations of dissolved aluminum (DAl), a proxy for dust input, and DFe indicated dust as a source of DFe to the surface ocean. The importance of Aeolian nutrient input was further confirmed by an increase of 0.1 nM DFe and 0.05 ?M phosphate during a repeat transect before and after a dust event. An exponential decrease of DFe with increasing distance from the African continent, suggested that continental shelf waters were a source of DFe to the northern part of our study area. Relatively high Fe:C ratios of up to 3 × 10?5 (C derived from apparent oxygen utilization (AOU)) indicated an external source of Fe to these African continental shelf waters. Below the wind mixed layer along 12°N, enhanced DFe concentrations (>1.5 nM) correlated positively with apparent oxygen utilization (AOU) and showed the importance of organic matter remineralization as an DFe source. As a consequence, vertical diffusive mixing formed an important Fe flux to the surface ocean in this region, even surpassing that of a major dust event

A Biochemically Based Model of the Growth and Development of Crassostrea Gigas Larvae

A biochemically based model was developed to simulate the growth, development and metamorphosis of larvae of the Pacific oyster, Crassostrea gigas. The model is unique in that (1) it defines larvae in terms of their protein, neutral lipid, polar lipid, carbohydrate, and ash content; (2) it tracks weight separately from length to follow larval condition index; and (3) it includes genetic variation in growth efficiency and egg quality to better simulate cohort population dynamics. The model includes parameterizations for larval filtration, ingestion, and respiration, which determine growth rate, and processes controlling larval mortality and metamorphosis. The initial biochemical content of the larva is determined by the composition of the egg. Changes in the initial ratios of protein, carbohydrate, neutral lipid, and polar lipid occur in response to the biochemical composition of available food as the larva grows. Modeling the process of metamorphosis requires a series of size-based and biochemically based triggers: (1) larvae become potentially competent to metamorphose at 275 mum, following a decrease in filtration rate at 250 mum; (2) larvae become competent to metamorphose when a daily decline in neutral lipid of 25% or more occurs; and (3) larvae metamorphose successfully if neutral lipid stores exceed polar lipid stores. Although based on simple biochemistry, the model succeeds in simulating such basic characteristics of C. gigas larval development and metamorphosis as larval life span and size structure at metamorphosis and the influence of egg and food quality and food quantity on survival. These results suggest that simple biochemical constructs may encompass the biochemical transitions most prominent in determining cohort success. Simulations of larval development show that for the smallest larvae, assimilation does not provide adequate resources to explain observed growth, although measured filtration rates would indicate otherwise. Egg lipid stores are needed to sustain the larva, The simulations also identify egg sizes in the range 37-73 mum to be viable, very similar to observations. Egg sizes outside this range are predicted to be nonviable due to lipid deficiencies in early larval life. Similarly, simulations identify upper and lower genetic limits on growth efficiency beyond which larvae cannot acquire sufficient neutral lipid stores to successfully metamorphose. As food supply declines, animals with high growth efficiencies are selected in the simulation. Low-protein food diets are predicted to increase larval survival. High-protein diets result in insufficient carbohydrate and neutral lipid to cover metabolic and storage needs. Thus, the influence of growth efficiency is nonrandomly distributed across egg size and respiration rate and the influence seems to be mediated in part by food quantity and to a larger measure by food quality

Influence of Short-Term Variations in Food on Survival of Crassotrea Gigas Larvae: A Modeling Study

A biochemically-based model was developed to simulate the growth, development, and metamorphosis of larvae of the Pacific oyster, Crassostrea gigas. The model defines larvae in terms of their protein, lipid, carbohydrate, and ash content and includes variation in growth efficiency and egg quality to better simulate cohort population dynamics. Changes in tissue composition occur as the larva grows and in response to the biochemical composition of the food. The premise behind this modeling study was that certain periods of larval life are more critical than others with respect to the availability of food and that food quality is as important as food quantity. The results of the simulations indicate that critical periods do exist, but that the period of larval life which is critical depends upon the composition of the available food supply and how it varies over time. Overall, the most critical time is late in larval life, near the time of metamorphosis. At this point, some variations in food quality are particularly efficacious, others particularly disastrous. But, under certain circumstances, events early or midway in larval life also dramatically change cohort survival. Simulations show that cohort survival varies in a relatively predictable way when salinity or food quantity vary. Both control time-integrated food supply to the larva by varying the amount of food ingested. Reduction of time-integrated ingestion reduces survival. Larvae with high growth efficiency are more successful, as are larvae coming from large eggs. The simple effect of time-integrated food presents a stark contrast to the complexity introduced by varying food quality. Simulations indicate that it is late in larval life when larvae are most sensitive to changes in food quality. Increased protein at this time always improves survival. Increased lipid is most efficacious midway in larval life, but also exerts a positive impact late in larval life. Variations in carbohydrate are relatively inconsequential in affecting larval survival. Simulations in which food quantity and food quality vary independently show that cohort survival is sensitive to the exact timing and type of environmental change. Transient changes in food quantity influence survival primarily by varying the length of larval life. Transient changes in food quality, on the other hand, can produce large changes in survivorship by restricting the range of genotypes in the cohort that can survive, as well as by varying larval life span. The simulations support the adaptive advantage of larval cohorts with a relatively wide range of genotypes and suggest the important influence of variations in food quality in maintaining genetic variability

Multiple Stable Reference Points in Oyster Populations: Biological Relationships for the Eastern Oyster (Crassostrea virginica) in Delaware Bay

In the first of two companion papers, a 54-yr time series for the oyster population in the New Jersey waters of Delaware Bay was analyzed to develop biological relationships necessary to evaluate maximum sustainable yield (MSY) reference points and to consider how multiple stable points affect reference point-based management. The time series encompassed two regime shifts, one circa 1970 that ushered in a 15-yr period of high abundance, and a second in 1985 that ushered in a 20-yr period of low abundance. The intervening and succeeding periods have the attributes of alternate stable states. The biological relationships between abundance, recruitment, and mortality were unusual in four ways. First, the broodstock-recruitment relationship at low abundance may have been driven more by the provision of settlement sites for larvae by the adults than by fecundity. Second, the natural mortality rate was temporally unstable and bore a nonlinear relationship to abundance. Third, combined high abundance and low mortality, though likely requiring favorable environmental conditions, seemed also to be a self-reinforcing phenomenon. As a consequence, the abundance-mortality relationship exhibited both compensatory and depensatory components. Fourth, the geographic distribution of the stock was intertwined with abundance and mortality, such that interrelationships were functions both of spatial organization and inherent population processes

Multiple Stable Reference Points in Oyster Populations: Implications for Reference Point-Based Management

In the second of two companion articles, a 54-year time series for the oyster population in the New Jersey waters of Delaware Bay is analyzed to examine how the presence of multiple stable states affects reference-point-based management. Multiple stable states are described by four types of reference points. Type I is the carrying capacity for the stable state: each has associated with it a type-II reference point wherein surplus production reaches a local maximum. Type-II reference points are separated by an intermediate surplus production low (type III). Two stable states establish a type-IV reference point, a point-of-no-return that impedes recovery to the higher stable state. The type-II to type-III differential in surplus production is a measure of the difficulty of rebuilding the population and the sensitivity of the population to collapse at high abundance. Surplus production projections show that the abundances defining the four types of reference points are relatively stable over a wide range of uncertainties in recruitment and mortality rates. The surplus production values associated with type-II and type-III reference points are much more uncertain. Thus, biomass goals are more easily established than fishing mortality rates for oyster populations

Why do networks have inhibitory/negative connections?

Why do brains have inhibitory connections? Why do deep networks have negative weights? We propose an answer from the perspective of representation capacity. We believe representing functions is the primary role of both (i) the brain in natural intelligence, and (ii) deep networks in artificial intelligence. Our answer to why there are inhibitory/negative weights is: to learn more functions. We prove that, in the absence of negative weights, neural networks with non-decreasing activation functions are not universal approximators. While this may be an intuitive result to some, to the best of our knowledge, there is no formal theory, in either machine learning or neuroscience, that demonstrates why negative weights are crucial in the context of representation capacity. Further, we provide insights on the geometric properties of the representation space that non-negative deep networks cannot represent. We expect these insights will yield a deeper understanding of more sophisticated inductive priors imposed on the distribution of weights that lead to more efficient biological and machine learning.Comment: ICCV2023 camera-read

Modeling the Dispersal of Eastern Oyster (Crassostrea virginica) larvae in Delaware Bay

The interactions of circulation and growth processes in determining the horizontal distribution of eastern oyster (Crassostrea virginica) larvae in the Delaware Bay estuary were investigated with a coupled circulation-individual-based larvae model that used environmental conditions from the spawning seasons (mid-June to mid-September) of 1984, 1985, 1986, 2000, and 2001. Particles, representing oyster larvae, were released at five-day intervals from areas in Delaware Bay that correspond to natural oyster reefs. The simulated larval development time was used to estimate potential larval success, determined by the percent of larvae that successfully reached settlement size (330 µm) within the planktonic larval duration of 30 days. Success rates for simulated larvae released in the upper estuary were less than half of those released in the lower estuary because of the reduction in growth rate from exposure to low salinity. Simulated larval success rates were further reduced during periods of increased river discharge, which produced low salinity conditions. The simulated transport patterns showed a down-estuary drift of oyster larvae during the spawning season, which is consistent with the observed reduction in settlement and recruitment rates in the upper estuary. The simulated transport pathways patterns showed that larvae originating in the middle and lower regions of the estuary had low rates of dispersion and high rates of self-settlement. Larvae released in the upper reaches of the estuary had limited contributions to the Delaware Bay oyster population, in part because of the lower overall simulated larval success in the low salinity regions. The simulated transport patterns suggested that the upper bay exports rather than receives larvae, which has implications for the establishment of genetic traits