An examination of spatial and temporal genetic variation in walleye pollock (Theragra chalcogramma) using allozyme, mitochondrial DNA, and microsatellite data

We used allozyme, microsatellite, and mitochondrial DNA (mtDNA) data to test for spatial and interannual genetic diversity in wall-eye pollock (Theragra chalcogramma) from six spawning aggregations representing three geographic regions: Gulf of Alaska, eastern Bering Sea, and eastern Kamchatka. Interpopulation genetic diversity was evident primarily from the mtDNA and two allozyme loci (SOD-2*, MPI*). Permutation tests ˆindicated that FST values for most allozyme and microsatellite loci were not significantly greater than zero. The microsatellite results suggested that high locus polymorphism may not be a reliable indicator of power for detecting population differentiation in walleye pollock. The fact that mtDNA revealed population structure and most nuclear loci did not suggests that the effective size of most walleye pollock populations is large (genetic drift is weak) and migration is a relatively strong homogenizing force. The allozymes and mtDNA provided mostly concordant estimates of patterns of spatial genetic variation. These data showed significant genetic variation between North American and Asian populations. In addition, two spawning aggregations in the Gulf of Alaska, in Prince William Sound, and off Middleton Island, appeared genetically distinct from walleye pollock spawning in the Shelikof Strait and may merit management as a distinct stock. Finally, we found evidence of interannual genetic variation in two of three North American spawning aggregations, similar in magnitude to the spatial variation among North American walleye pol-lock. We suggest that interannual genetic variation in walleye pollock may be indicative of one or more of the following factors: highly variable reproductive success, adult philopatry, source-sink metapopulation structure, and intraannual variation (days) in spawning timing among genetically distinct but spatially identical spawning aggregates.

Spatio-temporal clustering of probabilistic region trajectories

We propose a novel model for the spatio-temporal clustering of trajectories based on motion, which applies to challenging street-view video sequences of pedestrians captured by a mobile camera. A key contribution of our work is the introduction of novel probabilistic region trajectories, motivated by the non-repeatability of segmentation of frames in a video sequence. Hierarchical image segments are obtained by using a state-of-the-art hierarchical segmentation algorithm, and connected from adjacent frames in a directed acyclic graph. The region trajectories and measures of confidence are extracted from this graph using a dynamic programming-based optimisation. Our second main contribution is a Bayesian framework with a twofold goal: to learn the optimal, in a maximum likelihood sense, Random Forests classifier of motion patterns based on video features, and construct a unique graph from region trajectories of different frames, lengths and hierarchical levels. Finally, we demonstrate the use of Isomap for effective spatio-temporal clustering of the region trajectories of pedestrians. We support our claims with experimental results on new and existing challenging video sequences. © 2011 IEEE.

Temporal Coherence of Chlorophyll a during a Spring Phytoplankton Bloom in Xiangxi Bay of Three-Gorges Reservoir, China

Algal bloom phenomenon was defined as "the rapid growth of one or more phytoplankton species which leads to a rapid increase in the biomass of phytoplankton", yet most estimates of temporal coherence are based on yearly or monthly sampling frequencies and little is known of how synchrony varies among phytoplankton or of the causes of temporal coherence during spring algal bloom. In this study, data of chlorophyll a and related environmental parameters were weekly gathered at 15 sampling sites in Xiangxi Bay of Three-Gorges Reservoir (TGR, China) to evaluate patterns of temporal coherence for phytoplankton during spring bloom and test if spatial heterogeneity of nutrient and inorganic suspended particles within a single ecosystem influences synchrony of spring phytoplankton dynamics. There is a clear spatial and temporal variation in chlorophyll a across Xiangxi Bay. The degree of temporal coherence for chlorophyll a between pairs of sites located in Xiangxi Bay ranged from -0.367 to 0.952 with mean and median values of 0.349 and 0.321, respectively. Low levels of temporal coherence were often detected among the three stretches of the bay (Down reach, middle reach and upper reach), while high levels of temporal coherence were often found within the same reach of the bay. The relative difference of DIN between pair sites was the strong predictor of temporal coherence for chlorophyll a in down and middle reach of the bay, while the relative difference in Anorganic Suspended Solids was the important factor regulating temporal coherence in middle and upper reach. Contrary to many studies, these results illustrate that, in a small geographic area (a single reservoir bay of approximately 25 km), spatial heterogeneity influence synchrony of phytoplankton dynamics during spring bloom and local processes may override the effects of regional processes or dispersal.

Identical sequences but different expression patterns of Hira gene in gynogenetic and gonochoristic crucian carps

Hir/Hira (histone regulation) genes were first identified in yeast as negative regulators of histone gene expression. It has been confirmed that HIRA is a conserved family of proteins present in various animals and plants. In this paper, the cDNAs of the Hira homolog named CagHira and CaHira were isolated from gynogenetic gibel carp (gyno-carp) and gonochoristic color crucian carp (gono-carp) respectively. The full-length CagHira is 3,860 bp in length with an open reading frame (ORF) of 3,033 bp that encodes 1,011 amino acids, while the full-length CaHira is 3,748 bp in length and also has an ORF of 3,033 bp. The deduced amino acid sequences of both Hira homologs contain seven WD domains and show high identity with other HIRA family members. RT-PCR analyses revealed strong expression of Hira in the ovaries, whereas no expression was detected in the testes of either of the fishes. Hira transcription was not detected in the liver of gyno-carp, but a high level of Hira mRNA was observed in gono-carp. The temporal expression pattern showed that the Hira mRNA is consistently expressed during all embryonic development stages in gyno-carp. However, the abundance of CaHira mRNA significantly decreased (P < 0.05) shortly after fertilization and then increased again and remained stable from gastrula till hatching. The varying spatiotemporal expression patterns of Hira genes in gyno-carp and gono-carp may be associated with the differing reproductive modes used by these two closely related fishes. Our results suggest that Hira may play a role not only in the decondensation of sperm nucleus and the formation of pronucleus during fertilization, but also in gastrulation and the subsequent development of embryos.

Analysis of spatio-temporal dynamic pattern and driving forces of urban land in China in 1990s using TM images and GIS

China has witnessed fast urban growth in the recent decade. This study analyzes spatio-temporal characteristics of urban expansion in China using satellite images and regionalization methods. Landsat TM images at three time periods, 1990/1991, 1995/1996, and 1999/2000, are interpreted to get 1:100000 vector land use datasets. The study calculates the urban land percentage and urban land expansion index of every 1 km(2) cell throughout China. The study divides China into 27 urban regions to conceive dynamic patterns of urban land changes. Urban development was achieving momentum in the western region, expanding more noticeably than in the previous five years, and seeing an increased growth percentage. Land use dynamic changes reflect the strong impacts of economic growth environments and macro-urban development policies. The paper helps to distinguish the influences of newly market-oriented forces from traditional administrative controls on China's urban expansion. (c) 2005 Elsevier Ltd. All rights reserved.

Dynamics of dimethylsulfide and dimethylsulfoniopropionate produced by phytoplankton in the Chinese seas - Distribution patterns and affecting factors

Distribution of dimethylsulfide (DMS) and/or particulate dimethylsulfoniopropionate (DMSPp) concentrations in the Jiaozhou Bay, Zhifu Bay and East China Sea were investigated during the period of 1994 - 1998. Both DMS and DMSPp levels showed remarkable temporal and spatial variations. High values occurred in the coastal or shelf waters and low values in the offshore waters. The highest levels were observed in spring or summer and lowest in autumn. DMS or DMSPp distribution patterns were associated with water mass on a large geographical scale, while biological and chemical factors were more likely influential on smaller-scale variations. Diatoms could play an important role in total DMS or DMSPp abundance in coastal waters. Nitrate was found to have a two-phase relationship with DMSPp concentrations: positive when nitrate concentration was lower than 1 mumol/L, and negative when it was above. Anthropogenic factors such as sewage input and aquaculture also showed influences on DMS or DMSPp concentration.

Changes in Web Client Access Patterns: Characteristics and Caching Implications

Understanding the nature of the workloads and system demands created by users of the World Wide Web is crucial to properly designing and provisioning Web services. Previous measurements of Web client workloads have been shown to exhibit a number of characteristic features; however, it is not clear how those features may be changing with time. In this study we compare two measurements of Web client workloads separated in time by three years, both captured from the same computing facility at Boston University. The older dataset, obtained in 1995, is well-known in the research literature and has been the basis for a wide variety of studies. The newer dataset was captured in 1998 and is comparable in size to the older dataset. The new dataset has the drawback that the collection of users measured may no longer be representative of general Web users; however using it has the advantage that many comparisons can be drawn more clearly than would be possible using a new, different source of measurement. Our results fall into two categories. First we compare the statistical and distributional properties of Web requests across the two datasets. This serves to reinforce and deepen our understanding of the characteristic statistical properties of Web client requests. We find that the kinds of distributions that best describe document sizes have not changed between 1995 and 1998, although specific values of the distributional parameters are different. Second, we explore the question of how the observed differences in the properties of Web client requests, particularly the popularity and temporal locality properties, affect the potential for Web file caching in the network. We find that for the computing facility represented by our traces between 1995 and 1998, (1) the benefits of using size-based caching policies have diminished; and (2) the potential for caching requested files in the network has declined.

Constraint-based Mining of Frequent Arrangements of Temporal Intervals

The problem of discovering frequent arrangements of temporal intervals is studied. It is assumed that the database consists of sequences of events, where an event occurs during a time-interval. The goal is to mine temporal arrangements of event intervals that appear frequently in the database. The motivation of this work is the observation that in practice most events are not instantaneous but occur over a period of time and different events may occur concurrently. Thus, there are many practical applications that require mining such temporal correlations between intervals including the linguistic analysis of annotated data from American Sign Language as well as network and biological data. Two efficient methods to find frequent arrangements of temporal intervals are described; the first one is tree-based and uses depth first search to mine the set of frequent arrangements, whereas the second one is prefix-based. The above methods apply efficient pruning techniques that include a set of constraints consisting of regular expressions and gap constraints that add user-controlled focus into the mining process. Moreover, based on the extracted patterns a standard method for mining association rules is employed that applies different interestingness measures to evaluate the significance of the discovered patterns and rules. The performance of the proposed algorithms is evaluated and compared with other approaches on real (American Sign Language annotations and network data) and large synthetic datasets.

A Neural Network Model of Spatio-Temporal Pattern Recognition, Recall and Timing

This paper describes the design of a self~organizing, hierarchical neural network model of unsupervised serial learning. The model learns to recognize, store, and recall sequences of unitized patterns, using either short-term memory (STM) or both STM and long-term memory (LTM) mechanisms. Timing information is learned and recall {both from STM and from LTM) is performed with a learned rhythmical structure. The network, bearing similarities with ART (Carpenter & Grossberg 1987a), learns to map temporal sequences to unitized patterns, which makes it suitable for hierarchical operation. It is therefore capable of self-organizing codes for sequences of sequences. The capacity is only limited by the number of nodes provided. Selected simulation results are reported to illustrate system properties.

Temporal dynamics of host molecular responses differentiate symptomatic and asymptomatic influenza a infection.

Exposure to influenza viruses is necessary, but not sufficient, for healthy human hosts to develop symptomatic illness. The host response is an important determinant of disease progression. In order to delineate host molecular responses that differentiate symptomatic and asymptomatic Influenza A infection, we inoculated 17 healthy adults with live influenza (H3N2/Wisconsin) and examined changes in host peripheral blood gene expression at 16 timepoints over 132 hours. Here we present distinct transcriptional dynamics of host responses unique to asymptomatic and symptomatic infections. We show that symptomatic hosts invoke, simultaneously, multiple pattern recognition receptors-mediated antiviral and inflammatory responses that may relate to virus-induced oxidative stress. In contrast, asymptomatic subjects tightly regulate these responses and exhibit elevated expression of genes that function in antioxidant responses and cell-mediated responses. We reveal an ab initio molecular signature that strongly correlates to symptomatic clinical disease and biomarkers whose expression patterns best discriminate early from late phases of infection. Our results establish a temporal pattern of host molecular responses that differentiates symptomatic from asymptomatic infections and reveals an asymptomatic host-unique non-passive response signature, suggesting novel putative molecular targets for both prognostic assessment and ameliorative therapeutic intervention in seasonal and pandemic influenza.

Spatial and temporal scales of neuronal correlation in visual area V4.

The spiking activity of nearby cortical neurons is correlated on both short and long time scales. Understanding this shared variability in firing patterns is critical for appreciating the representation of sensory stimuli in ensembles of neurons, the coincident influences of neurons on common targets, and the functional implications of microcircuitry. Our knowledge about neuronal correlations, however, derives largely from experiments that used different recording methods, analysis techniques, and cortical regions. Here we studied the structure of neuronal correlation in area V4 of alert macaques using recording and analysis procedures designed to match those used previously in primary visual cortex (V1), the major input to V4. We found that the spatial and temporal properties of correlations in V4 were remarkably similar to those of V1, with two notable differences: correlated variability in V4 was approximately one-third the magnitude of that in V1 and synchrony in V4 was less temporally precise than in V1. In both areas, spontaneous activity (measured during fixation while viewing a blank screen) was approximately twice as correlated as visual-evoked activity. The results provide a foundation for understanding how the structure of neuronal correlation differs among brain regions and stages in cortical processing and suggest that it is likely governed by features of neuronal circuits that are shared across the visual cortex.

Representing and recognizing scenario patterns

This paper presents a formal method for representing and recognizing scenario patterns with rich internal temporal aspects. A scenario is presented as a collection of time-independent fluents, together with the corresponding temporal knowledge that can be relative and/or with absolute values. A graphical representation for temporal scenarios is introduced which supports consistence checking as for the temporal constraints. In terms of such a graphical representation, graph-matching algorithms/methodologies can be directly adopted for recognizing scenario patterns.

Matching case history patterns in case-based reasoning

This paper introduces a mechanism for representing and recognizing case history patterns with rich internal temporal aspects. A case history is characterized as a collection of elemental cases as in conventional case-based reasoning systems, together with the corresponding temporal constraints that can be relative and/or with absolute values. A graphical representation for case histories is proposed as a directed, partially weighted and labeled simple graph. In terms of such a graphical representation, an eigen-decomposition graph matching algorithm is proposed for recognizing case history patterns.

Temporal changes in plankton of the North Sea: community shifts and environmental drivers

This paper analyses long-term and seasonal changes in the North Sea plankton community during the period 1970 to 2008. Based on Continuous Plankton Recorder (CPR) data covering 38 yr, major changes in both phytoplankton and zooplankton abundance and community structure were identified. Regime changes were detected around 1978, 1989 and 1998. The first 2 changes have been discussed in the literature and are defined as a cold episodic event (1978) and a regime shift towards a warm dynamic regime (1989). The effect of these 2 regime changes on plankton indicators was assessed and checked against previous studies. The 1998 change represents a shift in the abundance and seasonal patterns of dinoflagellates and the dominant zooplankton group, the neritic copepods. Furthermore, environmental factors such as air temperature, wind speed and the North Atlantic water inflow were identified as potential drivers of change in seasonal patterns, and the most-likely environmental causes for detected changes were assessed. We suggest that a change in the balance of dissolved nutrients driven by these environmental factors was the cause of the latest change in plankton community structure, which in turn could have affected the North Sea fish community.

Spatial and temporal variability in Scotian Shelf zooplankton communities

Zooplankton are indicators of the response of marine ecosystems to environmental variability. The relationships between zooplankton communities on the Scotian Shelf and hydrographic and geographic regions of the Scotian Shelf in the 1990s and 2000s were described using complementary data sets, each resolving different space and time scales. The Atlantic Zone Monitoring Program (AZMP) sampled Scotian Shelf zooplankton from the whole water column twice per year at stations along three cross-shelf transects and semi-monthly at a fixed station on the inshore central shelf, while Continuous Plankton Recorder (CPR) samples were collected from near-surface waters approximately monthly on an along-shelf transect. Variability patterns were compared among these three data sets to identify robust spatial and interannual trends. Stations were clustered based on taxonomic composition, and spatial clusters were compared to hydrographic boundaries and bathymetry to determine whether temporal changes in community composition were driven by changes in water mass distributions on the shelf. This project identifies zooplankton community and abundance shifts that may affect fish recruitment in the northwest Atlantic and contributes to development of ecosystem-based fisheries management on the Scotian Shelf.