Regimes and stock-recruitment relationships in Japanese sardine (Sardinops melanostictus), 1951-1995

We used reproductive success, rather than abundance or catch, to identify regimes because reproductive success responds faster to environmental changes. Peak abundance of Japanese sardine during 1951-1995 was about 1000 times higher than minimum abundance. A regime shift occurred in the early 1970s when carrying capacity (measured using spawner-recruit models) increased by about 75 times. We hypothesize that this was due to large-scale changes in the Kuroshio and Oyashio Current systems. Long-term environmental variation (regimes), interannual variability in recruitment success, and density-dependent recruitment and growth rates affected dynamics of Japanese sardine. We hypothesize that density-dependent effects on recruitment of Sardinops spp. are common but usually obscured in short data sets by environmental variability and measurement error. Virtual population analysis and forward-simulation modeling approaches gave similar biomass and recruitment estimates. The relationship between sardine biomass and catch per unit search time was nonlinear. Mass-at-age and biomass were correlated, and it may be possible to use mass-at-age as an abundance index. Current abundance is low, and we believe that the environment has shifted to a regime that is unfavorable for Japanese sardine.

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Chemical–environment interactions affecting the risk of impacts on aquatic organisms: A review with a Canadian perspective — interactions affecting vulnerability

Environmental Reviews ◽

10.1139/a07-008 ◽

2008 ◽

Vol 16 (NA) ◽

pp. 19-44 ◽

Cited By ~ 24

Author(s):

Catherine M. Couillard ◽

Simon C. Courtenay ◽

Robie W. Macdonald

Keyword(s):

Large Scale ◽

Municipal Wastewater ◽

Environmental Changes ◽

Environmental Variability ◽

Atlantic Cod ◽

Aquatic Organisms ◽

The Body ◽

Toxic Chemicals ◽

Aquatic Species ◽

Species Vulnerability

Environmental change can increase the vulnerability of aquatic species to toxic chemicals by challenging an organism’s aptitude to respond to chemicals or to repair toxic injury or by modifying animal behaviours like migration or predation. On the other hand, xenobiotics may affect the capacity of aquatic species to adapt to environmental challenges that come with change (e.g., pathogens, temperature). Across Canada we have identified a number of circumstances where chemicals and environmental variability have likely worked together to affect vulnerability of aquatic organisms. For example in the Maritimes, exposure to municipal wastewater or bleached kraft pulp mill effluent altered immune function in bivalves and increased their risk of developing haemocytic neoplasia, a disease known to cause high mortality. Northwest Atlantic cod stocks have experienced large-scale changes in environment and exhibit marked seasonal cycles in energy reserves. The risk associated with subsequent redistribution of persistent chemicals in the body together with nutritional deficiency is presently under evaluation since it could affect the recovery of these endangered stocks. In the Great Lakes, the introduction of an invasive fish species, the alewife, modified the diet of salmonids, which led to a deficiency of the vitamin thiamine in eggs causing early mortality. Contaminants may interact with thiamine deficiency and thus critically impair recruitment of salmonids. Viewing the risks presented by toxic chemicals from the point of view of species vulnerability, offers managers opportunities to mitigate such risks, for example, through habitat, ocean and fisheries management. Further research is needed to develop biomarkers of vulnerability, identify most vulnerable life stages and populations, to understand the interactions between global environmental changes, nutritional status, pathogens and toxic chemicals, and to develop integrated approaches to manage vulnerability of aquatic ecosystems to toxic chemicals.

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Population analysis of retrotransposons in giraffe genomes supports RTE decline and widespread LINE1 activity in Giraffidae

Mobile DNA ◽

10.1186/s13100-021-00254-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Malte Petersen ◽

Sven Winter ◽

Raphael Coimbra ◽

Menno J. de Jong ◽

Vladimir V. Kapitonov ◽

...

Keyword(s):

Large Scale ◽

Population Analysis ◽

Model Organism ◽

Population Level ◽

Data Sets ◽

Ltr Retrotransposons ◽

Scale Population ◽

Mammalian Genomes ◽

Genome Assemblies ◽

First Time

Abstract Background The majority of structural variation in genomes is caused by insertions of transposable elements (TEs). In mammalian genomes, the main TE fraction is made up of autonomous and non-autonomous non-LTR retrotransposons commonly known as LINEs and SINEs (Long and Short Interspersed Nuclear Elements). Here we present one of the first population-level analysis of TE insertions in a non-model organism, the giraffe. Giraffes are ruminant artiodactyls, one of the few mammalian groups with genomes that are colonized by putatively active LINEs of two different clades of non-LTR retrotransposons, namely the LINE1 and RTE/BovB LINEs as well as their associated SINEs. We analyzed TE insertions of both types, and their associated SINEs in three giraffe genome assemblies, as well as across a population level sampling of 48 individuals covering all extant giraffe species. Results The comparative genome screen identified 139,525 recent LINE1 and RTE insertions in the sampled giraffe population. The analysis revealed a drastically reduced RTE activity in giraffes, whereas LINE1 is still actively propagating in the genomes of extant (sub)-species. In concert with the extremely low activity of the giraffe RTE, we also found that RTE-dependent SINEs, namely Bov-tA and Bov-A2, have been virtually immobile in the last 2 million years. Despite the high current activity of the giraffe LINE1, we did not find evidence for the presence of currently active LINE1-dependent SINEs. TE insertion heterozygosity rates differ among the different (sub)-species, likely due to divergent population histories. Conclusions The horizontally transferred RTE/BovB and its derived SINEs appear to be close to inactivation and subsequent extinction in the genomes of extant giraffe species. This is the first time that the decline of a TE family has been meticulously analyzed from a population genetics perspective. Our study shows how detailed information about past and present TE activity can be obtained by analyzing large-scale population-level genomic data sets.

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Faculty Opinions recommendation of Comparative assessment of large-scale data sets of protein-protein interactions.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1006598.82257 ◽

2002 ◽

Author(s):

Rob Russell

Keyword(s):

Protein Interactions ◽

Large Scale ◽

Comparative Assessment ◽

Data Sets ◽

Protein Protein Interactions ◽

Large Scale Data ◽

Scale Data ◽

Large Scale Data Sets

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Galaxy spin direction distribution in HST and SDSS show similar large-scale asymmetry

Publications of the Astronomical Society of Australia ◽

10.1017/pasa.2020.46 ◽

2020 ◽

Vol 37 ◽

Author(s):

Lior Shamir

Keyword(s):

Large Scale ◽

Spiral Galaxies ◽

Hubble Space Telescope ◽

Gravitational Interaction ◽

Large Data ◽

Sloan Digital Sky Survey ◽

Data Sets ◽

Dipole Axis ◽

Data Set ◽

The Asymmetry

Abstract Several recent observations using large data sets of galaxies showed non-random distribution of the spin directions of spiral galaxies, even when the galaxies are too far from each other to have gravitational interaction. Here, a data set of $\sim8.7\cdot10^3$ spiral galaxies imaged by Hubble Space Telescope (HST) is used to test and profile a possible asymmetry between galaxy spin directions. The asymmetry between galaxies with opposite spin directions is compared to the asymmetry of galaxies from the Sloan Digital Sky Survey. The two data sets contain different galaxies at different redshift ranges, and each data set was annotated using a different annotation method. The results show that both data sets show a similar asymmetry in the COSMOS field, which is covered by both telescopes. Fitting the asymmetry of the galaxies to cosine dependence shows a dipole axis with probabilities of $\sim2.8\sigma$ and $\sim7.38\sigma$ in HST and SDSS, respectively. The most likely dipole axis identified in the HST galaxies is at $(\alpha=78^{\rm o},\delta=47^{\rm o})$ and is well within the $1\sigma$ error range compared to the location of the most likely dipole axis in the SDSS galaxies with $z>0.15$ , identified at $(\alpha=71^{\rm o},\delta=61^{\rm o})$ .

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Temporal changes in reproductive success and optimal breeding decisions in a long-distance migratory bird

Scientific Reports ◽

10.1038/s41598-020-78565-y ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Cynthia Reséndiz-Infante ◽

Gilles Gauthier

Keyword(s):

Reproductive Success ◽

Clutch Size ◽

Environmental Changes ◽

Migratory Bird ◽

Laying Date ◽

Negative Consequences ◽

Breeding Phenology ◽

Additional Time ◽

Long Distance ◽

Seasonal Decline

AbstractMany avian migrants have not adjusted breeding phenology to climate warming resulting in negative consequences for their offspring. We studied seasonal changes in reproductive success of the greater snow goose (Anser caerulescens atlantica), a long-distance migrant. As the climate warms and plant phenology advances, the mismatch between the timing of gosling hatch and peak nutritive quality of plants will increase. We predicted that optimal laying date yielding highest reproductive success occurred earlier over time and that the seasonal decline in reproductive success increased. Over 25 years, reproductive success of early breeders increased by 42%, producing a steeper seasonal decline in reproductive success. The difference between the laying date producing highest reproductive success and the median laying date of the population increased, which suggests an increase in the selection pressure for that trait. Observed clutch size was lower than clutch size yielding the highest reproductive success for most laying dates. However, at the individual level, clutch size could still be optimal if the additional time required to acquire nutrients to lay extra eggs is compensated by a reduction in reproductive success due to a delayed laying date. Nonetheless, breeding phenology may not respond sufficiently to meet future environmental changes induced by warming temperatures.

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Accelerating In-Transit Co-Processing for Scientific Simulations Using Region-Based Data-Driven Analysis

Algorithms ◽

10.3390/a14050154 ◽

2021 ◽

Vol 14 (5) ◽

pp. 154

Author(s):

Marcus Walldén ◽

Masao Okita ◽

Fumihiko Ino ◽

Dimitris Drikakis ◽

Ioannis Kokkinakis

Keyword(s):

Large Scale ◽

Data Driven ◽

Data Sets ◽

Output Constraints ◽

Data Driven Approach ◽

Scientific Simulations ◽

Multiple Metrics ◽

In Transit ◽

Multiple Compression ◽

Large Scale Simulations

Increasing processing capabilities and input/output constraints of supercomputers have increased the use of co-processing approaches, i.e., visualizing and analyzing data sets of simulations on the fly. We present a method that evaluates the importance of different regions of simulation data and a data-driven approach that uses the proposed method to accelerate in-transit co-processing of large-scale simulations. We use the importance metrics to simultaneously employ multiple compression methods on different data regions to accelerate the in-transit co-processing. Our approach strives to adaptively compress data on the fly and uses load balancing to counteract memory imbalances. We demonstrate the method’s efficiency through a fluid mechanics application, a Richtmyer–Meshkov instability simulation, showing how to accelerate the in-transit co-processing of simulations. The results show that the proposed method expeditiously can identify regions of interest, even when using multiple metrics. Our approach achieved a speedup of 1.29× in a lossless scenario. The data decompression time was sped up by 2× compared to using a single compression method uniformly.

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Spatio-temporal associations of albacore CPUEs in the Northeastern Pacific with regional SST and climate environmental variables

ICES Journal of Marine Science ◽

10.1093/icesjms/fst238 ◽

2014 ◽

Vol 71 (7) ◽

pp. 1717-1727 ◽

Cited By ~ 10

Author(s):

A. Jason Phillips ◽

Lorenzo Ciannelli ◽

Richard D. Brodeur ◽

William G. Pearcy ◽

John Childers

Keyword(s):

North Pacific ◽

Large Scale ◽

Environmental Variability ◽

Southern Oscillation ◽

Spatial Dynamics ◽

Catch Per Unit Effort ◽

Variable Effect ◽

Positive Effects ◽

The North ◽

Additive Mixed Models

Abstract This study investigated the spatial distribution of juvenile North Pacific albacore (Thunnus alalunga) in relation to local environmental variability [i.e. sea surface temperature (SST)], and two large-scale indices of climate variability, [the Pacific Decadal Oscillation (PDO) and the Multivariate El Niño/Southern Oscillation Index (MEI)]. Changes in local and climate variables were correlated with 48 years of albacore troll catch per unit effort (CPUE) in 1° latitude/longitude cells, using threshold Generalized Additive Mixed Models (tGAMMs). Model terms were included to account for non-stationary and spatially variable effects of the intervening covariates on albacore CPUE. Results indicate that SST had a positive and spatially variable effect on albacore CPUE, with increasingly positive effects to the North, while PDO had an overall negative effect. Although albacore CPUE increased with SST both before and after a threshold year of 1986, such effect geographically shifted north after 1986. This is the first study to demonstrate the non-stationary spatial dynamics of albacore tuna, linked with a major shift of the North Pacific. Results imply that if ocean temperatures continue to increase, US west coast fisher communities reliant on commercial albacore fisheries are likely to be negatively affected in the southern areas but positively affected in the northern areas, where current albacore landings are highest.

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Impact of the municipal merger on watershed management: a study of Lake Kasumigaura, Japan

Asia-Pacific Journal of Regional Science ◽

10.1007/s41685-021-00190-y ◽

2021 ◽

Author(s):

Takeshi Mizunoya ◽

Noriko Nozaki ◽

Rajeev Kumar Singh

Keyword(s):

Watershed Management ◽

Large Scale ◽

Environmental Changes ◽

Water Environment ◽

Reduction Rate ◽

Oxygen Demand ◽

Policy Implications ◽

Pollution Reduction ◽

Lake Kasumigaura ◽

The Impact

AbstractIn the early 2000s, Japan instituted the Great Heisei Consolidation, a national strategy to promote large-scale municipal mergers. This study analyzes the impact that this strategy could have on watershed management. We select the Lake Kasumigaura Basin, the second largest lake in Japan, for the case study and construct a dynamic expanded input–output model to simulate the ecological system around the Lake, the socio-environmental changes over the period, and their mutual dependency for the period 2012–2020. In the model, we regulate and control the following water pollutants: total nitrogen, total phosphorus, and chemical oxygen demand. The results show that a trade-off between economic activity and the environment can be avoided within a specific range of pollution reduction, given that the prefectural government implements optimal water environment policies, assuming that other factors constraining economic growth exist. Additionally, municipal mergers are found to significantly reduce the budget required to improve the water environment, but merger budget efficiency varies nonlinearly with the reduction rate. Furthermore, despite the increase in financial efficiency from the merger, the efficiency of installing domestic wastewater treatment systems decreases drastically beyond a certain pollution reduction level and eventually reaches a limit. Further reductions require direct regulatory instruments in addition to economic policies, along with limiting the output of each industry. Most studies on municipal mergers apply a political, administrative, or financial perspective; few evaluate the quantitative impact of municipal mergers on the environment and environmental policy implications. This study addresses these gaps.

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Compartment and hub definitions tune metabolic networks for metabolomic interpretations

GigaScience ◽

10.1093/gigascience/giz137 ◽

2020 ◽

Vol 9 (1) ◽

Cited By ~ 3

Author(s):

T Cameron Waller ◽

Jordan A Berg ◽

Alexander Lex ◽

Brian E Chapman ◽

Jared Rutter

Keyword(s):

Large Scale ◽

Metabolic Networks ◽

Shortest Paths ◽

Large Data ◽

Differential Regulation ◽

Large Data Sets ◽

Data Sets ◽

Human Metabolism ◽

Experimental Conditions ◽

Systemic Model

Abstract Background Metabolic networks represent all chemical reactions that occur between molecular metabolites in an organism’s cells. They offer biological context in which to integrate, analyze, and interpret omic measurements, but their large scale and extensive connectivity present unique challenges. While it is practical to simplify these networks by placing constraints on compartments and hubs, it is unclear how these simplifications alter the structure of metabolic networks and the interpretation of metabolomic experiments. Results We curated and adapted the latest systemic model of human metabolism and developed customizable tools to define metabolic networks with and without compartmentalization in subcellular organelles and with or without inclusion of prolific metabolite hubs. Compartmentalization made networks larger, less dense, and more modular, whereas hubs made networks larger, more dense, and less modular. When present, these hubs also dominated shortest paths in the network, yet their exclusion exposed the subtler prominence of other metabolites that are typically more relevant to metabolomic experiments. We applied the non-compartmental network without metabolite hubs in a retrospective, exploratory analysis of metabolomic measurements from 5 studies on human tissues. Network clusters identified individual reactions that might experience differential regulation between experimental conditions, several of which were not apparent in the original publications. Conclusions Exclusion of specific metabolite hubs exposes modularity in both compartmental and non-compartmental metabolic networks, improving detection of relevant clusters in omic measurements. Better computational detection of metabolic network clusters in large data sets has potential to identify differential regulation of individual genes, transcripts, and proteins.

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