An Experimental Investigation of a Triangular Wing of Aspect Ratio 2 and a Body Warped to be Trimmed at M = 2.24

A cambered and twisted triangular wing of aspect ratio 2 in combination with a cambered body was investigated experimentally to determine the effectiveness of the camber in reducing the drag due to lift at trim at supersonic speeds. Four arrangements were tested comprising all combinations of a symmetrical and a cambered wing with a symmetrical and a cambered body. The camber shape investigated was derived by linearized lifting surface theory for triangular wings with sonic leading edges and satisfied the requirement that the wing be trimmed at the design Mach number and lift coefficient. The experimental results for the cambered wing and cambered body showed that the drag coefficient at trim was always greater, at the same lift coefficient, than that for the untrimmed symmetrical wing and body. The trim lift coefficient was positive and decreased with increasing Mach number. At the design Mach number of 2.24, the trim lift coefficient was somewhat lower and the drag coefficient was higher than values predicted by linearized lifting surface theory for the wing alone. A comparison of the trim lift-drag ratio of the cambered wing and cambered body with values obtained by trimming the symmetrical wing and symmetrical body either with a canard or a trailing-edge flap showed that, at approximately the design Mach number the cambered configuration developed a somewhat higher value than the trailing-edge flap configuration but a lower value than the canard configuration

Diet assessment of the Atlantic Sea Nettle Chrysaora quinquecirrha in Barnegat Bay, New Jersey, using next-generation sequencing

Next-generation sequencing (NGS) methodologies have proven useful in deciphering the food items of generalist predators, but have yet to be applied to gelatinous animal gut and tentacle content. NGS can potentially supplement traditional methods of visual identification. Chrysaora quinquecirrha (Atlantic sea nettle) has progressively become more abundant in Mid-Atlantic United States’ estuaries including Barnegat Bay (New Jersey), potentially having detrimental effects on both marine organisms and human enterprises. Full characterization of this predator’s diet is essential for a comprehensive understanding of its impact on the food web and its management. Here, we tested the efficacy of NGS for prey item determination in the Atlantic sea nettle. We implemented a NGS ‘shotgun’ approach to randomly sequence DNA fragments isolated from gut lavages and gastric pouch/tentacle picks of eight and 84 sea nettles, respectively. These results were verified by visual identification and co-occurring plankton tows. Over 550 000 contigs were assembled from ~110 million paired-end reads. Of these, 100 contigs were confidently assigned to 23 different taxa, including soft-bodied organisms previously undocumented as prey species, including copepods, fish, ctenophores, anemones, amphipods, barnacles, shrimp, polychaete worms, flukes, flatworms, echinoderms, gastropods, bivalves and hemichordates. Our results not only indicate that a ‘shotgun’ NGS approach can supplement visual identification methods, but targeted enrichment of a specific amplicon/gene is not a prerequisite for identifying Atlantic sea nettle prey items

qPCR Detection of Early Life History Stage Chrysaora quinquecirrha (Sea Nettles) in Barnegat Bay, New Jersey

The sea nettle Chrysaora quinquecirrha has become abundant in the Barnegat Bay estuary and frequently blooms in warm summer months. Various factors have been attributed to the increasing localized appearance of sea nettles and other jellyfish including eutrophication, overfishing, global warming, construction, and species introduction. Despite its abundance and frequent distribution within estuarine systems, very little work has been done to detect and quantify the early life history stages of this organism. Free-swimming larval stages of C. quinquecirrha can be detected and quantified using a quantitative polymerase chain reaction assay specific for the C. quinquecirrha 16S ribosomal (r)DNA locus of the mitochondrial DNA. This assay is species specific, linear over a 9-log range, and can detect as few as 10 copies of 16S rDNA. Twenty-liter field samples were sequentially filtered through 500- and 100-µm mesh to separate ephyra from planula larvae and gametes, respectively. Quantifiable levels of C. quinquecirrha 16S rDNA were detected at all eight paired locations in Barnegat Bay, with levels varying on both spatial and temporal scales. This research is apparently the first comprehensive field-based survey mapping, both spatially and temporally, the early life history stages of a scyphozoan in a major estuary using environmental DNA. Quantitative molecular data on the distribution of early stage C. quinquecirrha may prove useful in both understanding and managing blooms of sea nettles in Barnegat Bay

First occurrence of the invasive hydrozoan Gonionemus vertens A. Agassiz, 1862 (Cnidaria: Hydrozoa) in New Jersey, USA

Gonionemus vertens A. Agassiz, 1862 is a small hydrozoan native to the Pacific Ocean. It has become established in the northern and southern Atlantic Ocean as well as the Mediterranean Sea. We report on the first occurrence of this species in estuaries in New Jersey, USA,and confirm species identification through molecular sequence analysis. Given the large number of individuals collected, we contend that this is a successful invasion into this region with established polyps. The remaining question is the vector and source of these newly established populations

Top-Down Impacts of Sea Nettles (Chrysaora quinquecirrha) on Pelagic Community Structure in Barnegat Bay, New Jersey, U.S.A.

Coastal communities are substantially affected by human activities and create environments conducive to opportunistic species and structural changes in food webs. The Mid-Atlantic coast of the United States is highly urbanized with significant landscape modification and elevated pollutant loads. The appearance and development of resident populations of the Atlantic sea nettle (Chrysaora quinquecirrha) in Barnegat Bay, New Jersey demonstrates a successful establishment to this estuary. This research indicates that two species of gelatinous zooplankton (Mnemiopsis leidyi, C. quinquecirrha) play important structuring roles in the pelagic community. Specifically, M. leidyi exerts significant top-down control of calanoid copepods, cladocerans, fish eggs, and fish larvae, whereas C. quinquecirrha’s impact is felt through control of M. leidyi, whose density is two orders of magnitude greater. It was expected that if C. quinquecirrha exerted top-down control of M. leidyi, then a trophic cascade would result. However, no trophic cascade was observed, as C. quinquecirrha demonstrated broad control of pelagic community structure as a nonspecific, generalist predator. Consequently, the strength of M. leidyi’s ability to exert predation pressure is mediated by the development of the C. quinquecirrha bloom, but pelagic community structure is broadly defined by the combined impact of these predators within the system

Genomic selection using random regressions on known and latent environmental covariates

KEY MESSAGE: The integration of known and latent environmental covariates within a single-stage genomic selection approach provides breeders with an informative and practical framework to utilise genotype by environment interaction for prediction into current and future environments. ABSTRACT: This paper develops a single-stage genomic selection approach which integrates known and latent environmental covariates within a special factor analytic framework. The factor analytic linear mixed model of Smith et al. (2001) is an effective method for analysing multi-environment trial (MET) datasets, but has limited practicality since the underlying factors are latent so the modelled genotype by environment interaction (GEI) is observable, rather than predictable. The advantage of using random regressions on known environmental covariates, such as soil moisture and daily temperature, is that the modelled GEI becomes predictable. The integrated factor analytic linear mixed model (IFA-LMM) developed in this paper includes a model for predictable and observable GEI in terms of a joint set of known and latent environmental covariates. The IFA-LMM is demonstrated on a late-stage cotton breeding MET dataset from Bayer CropScience. The results show that the known covariates predominately capture crossover GEI and explain 34.4% of the overall genetic variance. The most notable covariates are maximum downward solar radiation (10.1%), average cloud cover (4.5%) and maximum temperature (4.0%). The latent covariates predominately capture non-crossover GEI and explain 40.5% of the overall genetic variance. The results also show that the average prediction accuracy of the IFA-LMM is [Formula: see text] higher than conventional random regression models for current environments and [Formula: see text] higher for future environments. The IFA-LMM is therefore an effective method for analysing MET datasets which also utilises crossover and non-crossover GEI for genomic prediction into current and future environments. This is becoming increasingly important with the emergence of rapidly changing environments and climate change. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00122-022-04186-w

Long-term comparison between index selection and optimal independent culling in plant breeding programs with genomic prediction

In the context of genomic selection, we evaluated and compared breeding programs using either index selection or independent culling for recurrent selection of parents. We simulated a clonally propagated crop breeding program for 20 cycles using either independent culling or an economic index with two unfavourably correlated traits under selection. Cycle time from crossing to selection of parents was kept the same for both strategies. Both methods led to increasingly unfavourable genetic correlations between traits and, compared to independent culling, index selection led to larger changes in the genetic correlation between the two traits. When linkage disequilibrium was not considered, the two methods had similar losses of genetic diversity. Two independent culling approaches were evaluated, one using optimal culling levels and one using the same selection intensity for both traits. Optimal culling levels outperformed the same selection intensity even when traits had the same economic importance. Therefore, accurately estimating optimal culling levels is essential for maximizing gains when independent culling is performed. Once optimal culling levels are achieved, independent culling and index selection lead to comparable genetic gains

Genomic selection strategies for clonally propagated crops

For genomic selection (GS) in clonal breeding programs to be effective, parents should be selected based on genomic predicted cross-performance unless dominance is negligible. Genomic prediction of cross-performance enables efficient exploitation of the additive and dominance value simultaneously. Here, we compared different GS strategies for clonally propagated crops with diploid (-like) meiotic behavior, using strawberry as an example. We used stochastic simulation to evaluate six combinations of three breeding programs and two parent selection methods. The three breeding programs included (1) a breeding program that introduced GS in the first clonal stage, and (2) two variations of a two-part breeding program with one and three crossing cycles per year, respectively. The two parent selection methods were (1) parent selection based on genomic estimated breeding values (GEBVs) and (2) parent selection based on genomic predicted cross-performance (GPCP). Selection of parents based on GPCP produced faster genetic gain than selection of parents based on GEBVs because it reduced inbreeding when the dominance degree increased. The two-part breeding programs with one and three crossing cycles per year using GPCP always produced the most genetic gain unless dominance was negligible. We conclude that (1) in clonal breeding programs with GS, parents should be selected based on GPCP, and (2) a two-part breeding program with parent selection based on GPCP to rapidly drive population improvement has great potential to improve breeding clonally propagated crops

Induction of temperate cyanophage AS-1 by heavy metal – copper

BACKGROUND: It has been reported that some marine cyanophage are temperate and can be induced from a lysogenic phase to a lytic phase by different agents such as heavy metals. However, to date no significant reports have focused on the temperate nature of freshwater cyanophage/cyanobacteria. Previous experiments with cyanophage AS-1 and cyanobacteria Anacystis nidulans have provided some evidence that AS-1 may have a lysogenic life cycle in addition to the characterized lytic cycle. RESULTS: In this study, the possible temperate A. nidulans was treated with different concentrations of heavy metal-copper. CuSO(4 )with concentrations of 3.1 × 10(-3 )M, 3.1 × 10(-4 )M, 3.1 × 10(-5 )M and 3.1 × 10(-6 )M were used to detect the induction of AS-1 from A. nidulans. The population of the host, unicellular cyanobacteria Anacystis nidulans, was monitored by direct count and turbidity while the amount of virus produced was derived from plaque forming units (PFU) by a direct plating method. The ratio of AS-1 release from A. nidulans was also determined. From these results it appears that AS-1 lysogenic phage can be induced by copper at concentrations from 3.1 × 10(-6 )M to 3.1 × 10(-4 )M. Maximal phage induction occurred at 6 hours after addition of copper, with an optimal concentration of 3.1 × 10(-6 )M. CONCLUSION: Cu(2+ )is a significant inducer for lysogenic cyanobacterial cells and consequently would be a potential control agent in the cyanobacteria population in fresh water ecosystems