Elemental Fingerprinting of Mussel Shells to Predict Population Sources and Redistribution Potential in the Gulf of Maine

As the climate warms, species that cannot tolerate changing conditions will only persist if they undergo range shifts. Redistribution ability may be particularly variable for benthic marine species that disperse as pelagic larvae in ocean currents. The blue mussel, Mytilus edulis, has recently experienced a warming-related range contraction in the southeastern USA and may face limitations to northward range shifts within the Gulf of Maine where dominant coastal currents flow southward. Thus, blue mussels might be especially vulnerable to warming, and understanding dispersal patterns is crucial given the species'' relatively long planktonic larval period (>1 month). To determine whether trace elemental “fingerprints” incorporated in mussel shells could be used to identify population sources (i.e. collection locations), we assessed the geographic variation in shell chemistry of blue mussels collected from seven populations between Cape Cod, Massachusetts and northern Maine. Across this ∼500 km of coastline, we were able to successfully predict population sources for over two-thirds of juvenile individuals, with almost 80% of juveniles classified within one site of their collection location and 97% correctly classified to region. These results indicate that significant differences in elemental signatures of mussel shells exist between open-coast sites separated by ∼50 km throughout the Gulf of Maine. Our findings suggest that elemental “fingerprinting” is a promising approach for predicting redistribution potential of the blue mussel, an ecologically and economically important species in the region.     

Competitive and demographic leverage points of community shifts under climate warming

Accelerating rates of climate change and a paucity of whole-community studies of climate impacts limit our ability to forecast shifts in ecosystem structure and dynamics, particularly because climate change can lead to idiosyncratic responses via both demographic effects and altered species interactions. We used a multispecies model to predict which processes and species'' responses are likely to drive shifts in the composition of a space-limited benthic marine community. Our model was parametrized from experimental manipulations of the community. Model simulations indicated shifts in species dominance patterns as temperatures increase, with projected shifts in composition primarily owing to the temperature dependence of growth, mortality and competition for three critical species. By contrast, warming impacts on two other species (rendering them weaker competitors for space) and recruitment rates of all species were of lesser importance in determining projected community changes. Our analysis reveals the importance of temperature-dependent competitive interactions for predicting effects of changing climate on such communities. Furthermore, by identifying processes and species that could disproportionately leverage shifts in community composition, our results contribute to a mechanistic understanding of climate change impacts, thereby allowing more insightful predictions of future biodiversity patterns.     

Application of an optimized marker amplification protocol in immunohistochemistry — a valuable tool for visualizing antigenic sites of low signal strength or sparse distribution

Amplification of immunohistochemical markers received considerable attention during the 1980s and 1990s. The amplification approach was largely abandoned following the development of antigen retrieval and reporter amplification techniques, because the latter were incorporated more easily into high throughput automated procedures in industrial and diagnostic laboratories. There remain, however, a number of instances where marker amplification still has much to offer. Consequently, we examined experimentally the utility of an optimized marker amplification technique in diagnostically relevant tissue where either the original signal strength was low or positive sites were visible, but sparsely distributed. Marker amplification in the former case not only improved the visibility of existing positive sites, but also revealed additional sites that previously were undetectable. In the latter case, positive sites were rendered more intense and therefore more easily seen during low magnification examination of large areas of tissue.     

EFFECT OF VITAMIN E SUPPLEMENTATION AND PARTIAL SUBSTITUTION OF POLY- WITH MONO-UNSATURATED FATTY ACIDS IN PIG DIETS ON MUSCLE,AND MICROSOME EXTRACT a-TOCOPHEROL CONCENTRATION AND LIPID OXIDATION

The experiment was organized in a 3×2 factorial arrangement with three dietary fat blends and a basal (20 mg kg^?1 diet) or supplemented (220 mg kg^?1) level of α-tocopheryl acetate. Dietary vitamin E and monounsaturated to polyunsaturated fatty acid ratio (dietary MUFA/PUFA) affected muscle α-tocopherol concentration (α-tocopherol [log μg g^?1]=0.18 (±0.105)+0.0034 (±0.0003)·dietary α-tocopherol [mg kg^?1 diet] (P<0.0001)+0.39 (±0.122)·dietary MUFA/PUFA (P<0.0036)). An interaction between dietary α-tocopherol and dietary MUFA/PUFA exists for microsome α-tocopherol concentration (α-tocopherol [log μg g^?1]=1.14 (±0.169) (P<0.0001)+0.0056 (±0.00099)·dietary α-tocopherol [mg kg^?1 diet] (P<0.0001)+0.54 (±0.206)·dietary MUFA/PUFA (P<0.0131)?0.0033 (±0.0011)·dietary α-tocopherol [mg kg^?1)]×dietary MUFA/PUFA (P<0.0067)), and hexanal concentration in meat (hexanal [ng·g^?1]=14807.9 (±1489.8)?28.8 (±10.6) dietary α-tocopherol [mg·kg^?1] (P<0.01)?8436.6 (±1701.6)·dietary MUFA/PUFA (P<0.001)+24.0 (±11.22)·dietary α-tocopherol·dietary MUFA/PUFA (P<0.0416)). It is concluded that partial substitution of dietary PUFA with MUFA lead to an increase in the concentration of α-tocopherol in muscle and microsome extracts. An interaction between dietary α-tocopherol and fatty acids exists, in which at low level of dietary vitamin E inclusion, a low MUFA/PUFA ratio leads to a reduction in the concentration of α-tocopherol in microsome extracts and a concentration of hexanal in meat above the expected values.     

Can Observation Skills of Citizen Scientists Be Estimated Using Species Accumulation Curves?

Volunteers are increasingly being recruited into citizen science projects to collect observations for scientific studies. An additional goal of these projects is to engage and educate these volunteers. Thus, there are few barriers to participation resulting in volunteer observers with varying ability to complete the project’s tasks. To improve the quality of a citizen science project’s outcomes it would be useful to account for inter-observer variation, and to assess the rarely tested presumption that participating in a citizen science projects results in volunteers becoming better observers. Here we present a method for indexing observer variability based on the data routinely submitted by observers participating in the citizen science project eBird, a broad-scale monitoring project in which observers collect and submit lists of the bird species observed while birding. Our method for indexing observer variability uses species accumulation curves, lines that describe how the total number of species reported increase with increasing time spent in collecting observations. We find that differences in species accumulation curves among observers equates to higher rates of species accumulation, particularly for harder-to-identify species, and reveals increased species accumulation rates with continued participation. We suggest that these properties of our analysis provide a measure of observer skill, and that the potential to derive post-hoc data-derived measurements of participant ability should be more widely explored by analysts of data from citizen science projects. We see the potential for inferential results from analyses of citizen science data to be improved by accounting for observer skill.     

Impact of QTL properties on the accuracy of multi-breed genomic prediction

Background

Although simulation studies show that combining multiple breeds in one reference population increases accuracy of genomic prediction, this is not always confirmed in empirical studies. This discrepancy might be due to the assumptions on quantitative trait loci (QTL) properties applied in simulation studies, including number of QTL, spectrum of QTL allele frequencies across breeds, and distribution of allele substitution effects. We investigated the effects of QTL properties and of including a random across- and within-breed animal effect in a genomic best linear unbiased prediction (GBLUP) model on accuracy of multi-breed genomic prediction using genotypes of Holstein-Friesian and Jersey cows.

Methods

Genotypes of three classes of variants obtained from whole-genome sequence data, with moderately low, very low or extremely low average minor allele frequencies (MAF), were imputed in 3000 Holstein-Friesian and 3000 Jersey cows that had real high-density genotypes. Phenotypes of traits controlled by QTL with different properties were simulated by sampling 100 or 1000 QTL from one class of variants and their allele substitution effects either randomly from a gamma distribution, or computed such that each QTL explained the same variance, i.e. rare alleles had a large effect. Genomic breeding values for 1000 selection candidates per breed were estimated using GBLUP modelsincluding a random across- and a within-breed animal effect.

Results

For all three classes of QTL allele frequency spectra, accuracies of genomic prediction were not affected by the addition of 2000 individuals of the other breed to a reference population of the same breed as the selection candidates. Accuracies of both single- and multi-breed genomic prediction decreased as MAF of QTL decreased, especially when rare alleles had a large effect. Accuracies of genomic prediction were similar for the models with and without a random within-breed animal effect, probably because of insufficient power to separate across- and within-breed animal effects.

Conclusions

Accuracy of both single- and multi-breed genomic prediction depends on the properties of the QTL that underlie the trait. As QTL MAF decreased, accuracy decreased, especially when rare alleles had a large effect. This demonstrates that QTL properties are key parameters that determine the accuracy of genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0124-6) contains supplementary material, which is available to authorized users.     

Warming and Elevated CO2 Interact to Drive Rapid Shifts in Marine Community Production

Predicting the outcome of future climate change requires an understanding of how alterations in multiple environmental factors manifest in natural communities and affect ecosystem functioning. We conducted an in situ, fully factorial field manipulation of CO₂ and temperature on a rocky shoreline in southeastern Alaska, USA. Warming strongly impacted functioning of tide pool systems within one month, with the rate of net community production (NCP) more than doubling in warmed pools under ambient CO₂ levels relative to initial NCP values. However, in pools with added CO₂, NCP was unaffected by warming. Productivity responses paralleled changes in the carbon-to-nitrogen ratio of a red alga, the most abundant primary producer species in the system, highlighting the direct link between physiology and ecosystem functioning. These observed changes in algal physiology and community productivity in response to our manipulations indicate the potential for natural systems to shift rapidly in response to changing climatic conditions and for multiple environmental factors to act antagonistically.     

Quantitative variability of 342 plasma proteins in a human twin population

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2–7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis‐SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood‐based biomarker studies.     

Invasiveness and homogenization: synergism of wide dispersal and high local abundance

Aim To determine whether invasive and locally abundant non‐native species have a more homogenizing effect on plant communities than non‐invasive and less abundant non‐native species. Location California and Florida counties, conservation areas in the USA, and eight US cities. Methods Species lists among counties, conservation areas and cities were compared to see whether invasive and abundant non‐native species increased the Jaccard index of similarity between localities beyond any increases caused by non‐invasive and less abundant non‐native species. Results For all comparisons, we found that invasive non‐native species have a significantly greater homogenizing effect than non‐invasive non‐native species. For the US conservation areas, we found that locally abundant invasive species tend to be more widespread and more widely shared than less abundant invasive species. There is also a positive relationship between homogenization by invasive species and the magnitude of human disturbance. Main conclusions Invasive non‐native species tend to be disproportionately shared among communities relative to non‐invasive non‐native species. This effect is enhanced by human disturbance, as measured by the ratio of non‐native to native species. There is a synergism between abundance and geographical range which enhances the homogenizing effects of abundant species. Invasive species, with wide ecological niches, are more widely shared among communities and more locally abundant. Abundant invasive species are thus more spatially homogenizing, and more ecologically dominant (functionally homogenizing). Also, ‘perceived homogenization’ is probably greater than homogenization measured by the increase in shared species. The abundant species typically seen by the casual observer in a biological community are probably more commonly shared between communities than less common species. Studies that lack abundance data and measure homogenization only on the basis of shared species, which includes most homogenization studies to date, probably underestimate the homogenizing impacts of non‐native species as perceived by people.