Tree migration-rates : narrowing the gap between inferred post-glacial rates and projected rates

Faster-than-expected post-glacial migration rates of trees have puzzled ecologists for a long time. In Europe, post-glacial migration is assumed to have started from the three southern European peninsulas (southern refugia), where large areas remained free of permafrost and ice at the peak of the last glaciation. However, increasing palaeobotanical evidence for the presence of isolated tree populations in more northerly microrefugia has started to change this perception. Here we use the Northern Eurasian Plant Macrofossil Database and palaeoecological literature to show that post-glacial migration rates for trees may have been substantially lower (60–260 m yr–1) than those estimated by assuming migration from southern refugia only (115–550 m yr–1), and that early-successional trees migrated faster than mid- and late-successional trees. Post-glacial migration rates are in good agreement with those recently projected for the future with a population dynamical forest succession and dispersal model, mainly for early-successional trees and under optimal conditions. Although migration estimates presented here may be conservative because of our assumption of uniform dispersal, tree migration-rates clearly need reconsideration. We suggest that small outlier populations may be a key factor in understanding past migration rates and in predicting potential future range-shifts. The importance of outlier populations in the past may have an analogy in the future, as many tree species have been planted beyond their natural ranges, with a more beneficial microclimate than their regional surroundings. Therefore, climate-change-induced range-shifts in the future might well be influenced by such microrefugia

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Climate change impacts on banana yields around the world

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this r4ecordData availability: All data used are publicly available and open access. All banana production data sources are listed in Supplementary Table 1. All climatic and topographic data sources are listed in the Methods.Nutritional diversity is a key element of food security1,2,3. However, research on the effects of climate change on food security has, thus far, focused on the main food grains4,5,6,7,8, while the responses of other crops, particularly those that play an important role in the developing world, are poorly understood. Bananas are a staple food and a major export commodity for many tropical nations9. Here, we show that for 27 countries—accounting for 86% of global dessert banana production—a changing climate since 1961 has increased annual yields by an average of 1.37 t ha−1. Past gains have been largely ubiquitous across the countries assessed and African producers will continue to see yield increases in the future. However, global yield gains could be dampened or disappear, reducing to 0.59 t ha−1 and 0.19 t ha−1 by 2050 under the climate scenarios for Representative Concentration Pathways 4.5 and 8.5, respectively, driven by declining yields in the largest producers and exporters. By quantifying climate-driven and technology-driven influences on yield, we also identify countries at risk from climate change and those capable of mitigating its effects or capitalizing on its benefits.Biotechnology and Biological Sciences Research Council (BBSRC)European Union Horizon 202

The deuteron: structure and form factors

A brief review of the history of the discovery of the deuteron in provided. The current status of both experiment and theory for the elastic electron scattering is then presented.Comment: 80 pages, 33 figures, submited to Advances in Nuclear Physic

Aerobic fitness is a potential crucial factor in protecting paralympic athletes with locomotor impairments from atherosclerotic cardiovascular risk

PurposeTo test the hypothesis that aerobic fitness is inversely related to the risk of atherosclerotic cardiovascular disease (ACVD) in athletes with locomotor impairments deriving from health conditions, such as spinal cord injury (SCI), lower limb amputation, cerebral palsy, poliomyelitis, and other health conditions different from the previous ones.MethodsA total of 68 male athletes who competed in either summer or winter Paralympic games were divided in two health conditions groups (35 with SCI, mean age 37.28.0 years, and 33 with different health conditions, mean age 37.89.9 years) and in four sport type groups (skill, power, intermittent-mixed metabolism-and endurance). They were evaluated through anthropometric and blood pressure measurements, laboratory blood tests, and graded cardiopulmonary maximal arm cranking exercise test, with oxygen uptake peak (VO2peak) measurement. Cardiovascular risk profile was assessed in each athlete.ResultsThe prevalence of ACVD-risk factors in the overall population was 20.6% for hypertension; 47% and 55.9% for high values of total and LDL cholesterol, respectively; 22.1% for reduce glucose tolerance; and 8.8% for obesity. No difference was found between athletes with and without SCI, while the prevalence of obesity was significantly higher in those practicing skill sports (22.7%, p=0.035), which was the sport type group with Paralympic athletes with the lowest VO2peak (22.5 +/- 5.70 ml kg(-1) min(-1)). VO2peak was lower in athletes with SCI than those with different health conditions (28.6 +/- 10.0 vs 33.6 +/- 8.9 ml kg(-1) min(-1)p=0.03), and in those with 3-4 risk factors (19.09 +/- 5.34 ml kg(-1) min(-1)) than those with 2 risk factors (27.1 +/- 5.50 ml kg(-1) min(-1)), 1 risk factor (31.6 +/- 8.55 ml kg(-1) min(-1)), or none (36.4 +/- 8.76 ml kg(-1) min(-1)) (p<0.001).ConclusionsThe present study suggests that having higher VO2peak seems to offer greater protection against ACVD in individuals with a locomotor impairment. Prescribing physical exercise at an intensity similar to that of endurance and intermittent sports should become a fundamental tool to promote health among people with a locomotor impairment.Open access funding provided by Universita degli Studi dell'Aquila within the CRUI-CARE Agreement

Taxonomic and functional turnover are decoupled in European peat bogs

In peatland ecosystems, plant communities mediate a globally significant carbon store. The effects of global environmental change on plant assemblages are expected to be a factor in determining how ecosystem functions such as carbon uptake will respond. Using vegetation data from 56 Sphagnum-dominated peat bogs across Europe, we show that in these ecosystems plant species aggregate into two major clusters that are each defined by shared response to environmental conditions. Across environmental gradients, we find significant taxonomic turnover in both clusters. However, functional identity and functional redundancy of the community as a whole remain unchanged. This strongly suggests that in peat bogs, species turnover across environmental gradients is restricted to functionally similar species. Our results demonstrate that plant taxonomic and functional turnover are decoupled, which may allow these peat bogs to maintain ecosystem functioning when subject to future environmental change

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Mouse mammary stem cells express prognostic markers for triple-negative breast cancer

Introduction Triple negative breast cancer (TNBC) is a heterogeneous group of tumours in which chemotherapy, the current mainstay of systemic treatment, is often initially beneficial but with a high risk of relapse and metastasis. There is currently no means of predicting which TNBC will relapse. We tested the hypothesis that the biological properties of normal stem cells are re-activated in tumour metastasis and that, therefore, the activation of normal mammary stem cell-associated gene sets in primary TNBC would be highly prognostic for relapse and metastasis. Methods Mammary basal stem and myoepithelial cells were isolated by flow cytometry and tested in low dose transplant assays. Gene expression microarrays were used to establish expression profiles of the stem and myoepithelial populations; these were compared to each other and to our previously established mammary epithelial gene expression profiles. Stem cell genes were classified by Gene Ontology (GO) analysis and the expression of a subset analysed in the stem cell population at single cell resolution. Activation of stem cell genes was interrogated across different breast cancer cohorts and within specific subtypes and tested for clinical prognostic power. Results A set of 323 genes was identified that was expressed significantly more highly in the purified basal stem cells compared to all other cells of the mammary epithelium. 109 out of 323 genes had been associated with stem cell features in at least one other study in addition to our own, providing further support for their involvement in the biology of this cell type. GO analysis demonstrated an enrichment of these genes for an association with cell migration, cytoskeletal regulation and tissue morphogenesis, consistent with a role in invasion and metastasis. Single cell resolution analysis showed that individual cells co-expressed both epithelial- and mesenchymal-associated genes/proteins. Most strikingly, we demonstrated that strong activity of this stem cell gene set in TNBCs identified those tumours most likely to rapidly progress to metastasis. Conclusions Our findings support the hypothesis that the biological properties of normal stem cells are drivers of metastasis and that these properties can be used to stratify patients with a highly heterogeneous disease such as TNBC