Richness and Abundance of Carabidae and Staphylinidae (Coleoptera), in Northeastern Dairy Pastures Under Intensive Grazing

Dairy cattle has become popular to dairy farmers in the Northeast looking for management schemes to cut production costs. Carabidae (ground beetles) and Staphylinidae (rove beetles) are indicators of habitat disturbances, such as drainage of wetlands, or grassland for grazing animals, and their monitoring could provide one measure of ecosystem sustainability if intensive management systems expand or intensify in the future. Our objective was assess the abundance and species richness of these two beetle families under intensive grazing throughout Pennsylvania, southern New York and Vermont. We collected 4365 ground beetles (83 species) and 4,027 rove beetles (79 species) by pitfall traps in three years in Pennsylvania. Nine ground beetle species, Amara aenea, Poecilus chalcites, Pterostichus melanarius, Bembidion quadrimaculatum oppositum, Amara familiaris, Poecilus lucublandus, Agonum muelleri, Bembidion obtusum and Bembidion mimus represented 80% of the Carabidae collected. Five other species were new to Pennsylvania. Four rove beetle species, Philonthus cognatus, Meronera venustula, Amischa analis, and Philonthus various = (carbonarius), comprised 74% of the total Staphylinidae collected. Yearly distributions of the dominant species did not change significantly in the three years with A. aenea and P. cognatus being most abundant every year. A parasitic rove beetle, Aleochara tristis, was recovered for the first time in Pennsylvania and Vermont since its release in the 1960\u27s to control face fly, Musca autumnalis. Similar results were found in New York and Vermont. We collected 1,984 ground beetles (68 species). Pterostichus melanarius was most abundant. Pterostichus vernalis was detected for the first time in the United States (Vermont). It was previously reported from Montreal, Canada. We collected 843 rove beetles (45 species). Philonthus cognatus was the most abundant rove beetle. In addition, Tachinus corticinus, previously known only from Canada, was discovered for the first time in the United States in Vermont. Pastures in Pennsylvania were diverse, containing 14 species of forage plants and 17 weed species. Botanical composition was similar in New York and Vermont. Sixteen species of grasses and legumes made up 90% of the plant composition and 36 species of weeds made up the remainder. This di­verse plant ecosystem may explain the richness of ground and rove beetles in northeastern U.S. pastures because the heterogeneity in the plant population provided additional resources which can support a rich assemblage of beetles. Monitoring richness and abundance of Carabidae and Staphylinidae over three years in Pennsylvania suggests intensive grazing systems are eco­logically sustainable

Richness and Abundance of Carabidae and Staphylinidae (Coleoptera), in Northeastern Dairy Pastures Under Intensive Grazing

Dairy cattle has become popular to dairy farmers in the Northeast looking for management schemes to cut production costs. Carabidae (ground beetles) and Staphylinidae (rove beetles) are indicators of habitat disturbances, such as drainage of wetlands, or grassland for grazing animals, and their monitoring could provide one measure of ecosystem sustainability if intensive management systems expand or intensify in the future. Our objective was assess the abundance and species richness of these two beetle families under intensive grazing throughout Pennsylvania, southern New York and Vermont. We collected 4365 ground beetles (83 species) and 4,027 rove beetles (79 species) by pitfall traps in three years in Pennsylvania. Nine ground beetle species, Amara aenea, Poecilus chalcites, Pterostichus melanarius, Bembidion quadrimaculatum oppositum, Amara familiaris, Poecilus lucublandus, Agonum muelleri, Bembidion obtusum and Bembidion mimus represented 80% of the Carabidae collected. Five other species were new to Pennsylvania. Four rove beetle species, Philonthus cognatus, Meronera venustula, Amischa analis, and Philonthus various = (carbonarius), comprised 74% of the total Staphylinidae collected. Yearly distributions of the dominant species did not change significantly in the three years with A. aenea and P. cognatus being most abundant every year. A parasitic rove beetle, Aleochara tristis, was recovered for the first time in Pennsylvania and Vermont since its release in the 1960\u27s to control face fly, Musca autumnalis. Similar results were found in New York and Vermont. We collected 1,984 ground beetles (68 species). Pterostichus melanarius was most abundant. Pterostichus vernalis was detected for the first time in the United States (Vermont). It was previously reported from Montreal, Canada. We collected 843 rove beetles (45 species). Philonthus cognatus was the most abundant rove beetle. In addition, Tachinus corticinus, previously known only from Canada, was discovered for the first time in the United States in Vermont. Pastures in Pennsylvania were diverse, containing 14 species of forage plants and 17 weed species. Botanical composition was similar in New York and Vermont. Sixteen species of grasses and legumes made up 90% of the plant composition and 36 species of weeds made up the remainder. This di­verse plant ecosystem may explain the richness of ground and rove beetles in northeastern U.S. pastures because the heterogeneity in the plant population provided additional resources which can support a rich assemblage of beetles. Monitoring richness and abundance of Carabidae and Staphylinidae over three years in Pennsylvania suggests intensive grazing systems are eco­logically sustainable

AGMIAL: implementing an annotation strategy for prokaryote genomes as a distributed system

We have implemented a genome annotation system for prokaryotes called AGMIAL. Our approach embodies a number of key principles. First, expert manual annotators are seen as a critical component of the overall system; user interfaces were cyclically refined to satisfy their needs. Second, the overall process should be orchestrated in terms of a global annotation strategy; this facilitates coordination between a team of annotators and automatic data analysis. Third, the annotation strategy should allow progressive and incremental annotation from a time when only a few draft contigs are available, to when a final finished assembly is produced. The overall architecture employed is modular and extensible, being based on the W3 standard Web services framework. Specialized modules interact with two independent core modules that are used to annotate, respectively, genomic and protein sequences. AGMIAL is currently being used by several INRA laboratories to analyze genomes of bacteria relevant to the food-processing industry, and is distributed under an open source license

AGMIAL: implementing an annotation strategy for prokaryote genomes as a distributed system

We have implemented a genome annotation system for prokaryotes called AGMIAL. Our approach embodies a number of key principles. First, expert manual annotators are seen as a critical component of the overall system; user interfaces were cyclically refined to satisfy their needs. Second, the overall process should be orchestrated in terms of a global annotation strategy; this facilitates coordination between a team of annotators and automatic data analysis. Third, the annotation strategy should allow progressive and incremental annotation from a time when only a few draft contigs are available, to when a final finished assembly is produced. The overall architecture employed is modular and extensible, being based on the W3 standard Web services framework. Specialized modules interact with two independent core modules that are used to annotate, respectively, genomic and protein sequences. AGMIAL is currently being used by several INRA laboratories to analyze genomes of bacteria relevant to the food-processing industry, and is distributed under an open source license

Notch signaling during human T cell development

Notch signaling is critical during multiple stages of T cell development in both mouse and human. Evidence has emerged in recent years that this pathway might regulate T-lineage differentiation differently between both species. Here, we review our current understanding of how Notch signaling is activated and used during human T cell development. First, we set the stage by describing the developmental steps that make up human T cell development before describing the expression profiles of Notch receptors, ligands, and target genes during this process. To delineate stage-specific roles for Notch signaling during human T cell development, we subsequently try to interpret the functional Notch studies that have been performed in light of these expression profiles and compare this to its suggested role in the mouse

Managing Spoilers in a Hybrid War: The Democratic Republic of Congo (1996-2010)

Scholarship on the management of spoilers in a hybrid type of conflict is almost non-existent. Through an examination of the recent Congolese wars and peace efforts (1996–2010), we develop an understanding of how spoilers are managed in a conflict characterised by both interstate and intrastate dynamics. Certainly, more strategies of dealing with spoiler behaviours in this type of conflict are likely to emerge as similar cases are investigated, but our discussion recommends these non-related, but strongly interacting principles: the practice of inclusivity, usually preferred in the management of spoilers, is more complex, and in fact ineffective, particularly when concerned groups’ internal politics and supportive alliances are unconventional. Because holding elections is often deemed indispensable in peacemaking efforts, it is vital that total spoilers be prevented from winning or disrupting them. The toughest challenge is the protection of civilians, especially when the state lacks a monopoly on the use of violence and governance remains partitioned across the country

A Genetically Encoded Tag for Correlated Light and Electron Microscopy of Intact Cells, Tissues, and Organisms

Electron microscopy (EM) achieves the highest spatial resolution in protein localization, but specific protein EM labeling has lacked generally applicable genetically encoded tags for in situ visualization in cells and tissues. Here we introduce “miniSOG” (for mini Singlet Oxygen Generator), a fluorescent flavoprotein engineered from Arabidopsis phototropin 2. MiniSOG contains 106 amino acids, less than half the size of Green Fluorescent Protein. Illumination of miniSOG generates sufficient singlet oxygen to locally catalyze the polymerization of diaminobenzidine into an osmiophilic reaction product resolvable by EM. MiniSOG fusions to many well-characterized proteins localize correctly in mammalian cells, intact nematodes, and rodents, enabling correlated fluorescence and EM from large volumes of tissue after strong aldehyde fixation, without the need for exogenous ligands, probes, or destructive permeabilizing detergents. MiniSOG permits high quality ultrastructural preservation and 3-dimensional protein localization via electron tomography or serial section block face scanning electron microscopy. EM shows that miniSOG-tagged SynCAM1 is presynaptic in cultured cortical neurons, whereas miniSOG-tagged SynCAM2 is postsynaptic in culture and in intact mice. Thus SynCAM1 and SynCAM2 could be heterophilic partners. MiniSOG may do for EM what Green Fluorescent Protein did for fluorescence microscopy

An analysis of single amino acid repeats as use case for application specific background models

Background Sequence analysis aims to identify biologically relevant signals against a backdrop of functionally meaningless variation. Increasingly, it is recognized that the quality of the background model directly affects the performance of analyses. State-of-the-art approaches rely on classical sequence models that are adapted to the studied dataset. Although performing well in the analysis of globular protein domains, these models break down in regions of stronger compositional bias or low complexity. While these regions are typically filtered, there is increasing anecdotal evidence of functional roles. This motivates an exploration of more complex sequence models and application-specific approaches for the investigation of biased regions. Results Traditional Markov-chains and application-specific regression models are compared using the example of predicting runs of single amino acids, a particularly simple class of biased regions. Cross-fold validation experiments reveal that the alternative regression models capture the multi-variate trends well, despite their low dimensionality and in contrast even to higher-order Markov-predictors. We show how the significance of unusual observations can be computed for such empirical models. The power of a dedicated model in the detection of biologically interesting signals is then demonstrated in an analysis identifying the unexpected enrichment of contiguous leucine-repeats in signal-peptides. Considering different reference sets, we show how the question examined actually defines what constitutes the 'background'. Results can thus be highly sensitive to the choice of appropriate model training sets. Conversely, the choice of reference data determines the questions that can be investigated in an analysis. Conclusions Using a specific case of studying biased regions as an example, we have demonstrated that the construction of application-specific background models is both necessary and feasible in a challenging sequence analysis situation