Risk analysis of climate change on coffee nematodes and leaf miner in Brazil

The objective of this work was to assess the potential impact of climate change on the spatial distribution of coffee nematodes (races of Meloidogyne incognita) and leaf miner (Leucoptera coffeella), using a Geographic Information System. Assessment of the impacts of climate change on pest infestations and disease epidemics in crops is needed as a basis for revising management practices to minimize crop losses as climatic conditions shift. Future scenarios focused on the decades of the 2020's, 2050's, and 2080's (scenarios A2 and B2) were obtained from five General Circulation Models available on Data Distribution Centre from Intergovernmental Panel on Climate Change. Geographic distribution maps were prepared using models to predict the number of generations of the nematodes and leaf miner. Maps obtained in scenario A2 allowed prediction of an increased infestation of the nematode and of the pest, due to greater number of generations per month, than occurred under the climatological normal from 1961-1990. The number of generations also increased in the B2 scenario, but was lower than in the A2 scenario for both organisms.

Impacts of climate change on Swiss biodiversity: An indicator taxa approach

We present a new indicator taxa approach to the prediction of climate change effects on biodiversity at the national level in Switzerland. As indicators, we select a set of the most widely distributed species that account for 95% of geographical variation in sampled species richness of birds, butterflies, and vascular plants. Species data come from a national program designed to monitor spatial and temporal trends in species richness. We examine some opportunities and limitations in using these data. We develop ecological niche models for the species as functions of both climate and land cover variables. We project these models to the future using climate predictions that correspond to two IPCC 3rd assessment scenarios for the development of 'greenhouse' gas emissions. We find that models that are calibrated with Swiss national monitoring data perform well in 10-fold cross-validation, but can fail to capture the hot-dry end of environmental gradients that constrain some species distributions. Models for indicator species in all three higher taxa predict that climate change will result in turnover in species composition even where there is little net change in predicted species richness. Indicator species from high elevations lose most areas of suitable climate even under the relatively mild B2 scenario. We project some areas to increase in the number of species for which climate conditions are suitable early in the current century, but these areas become less suitable for a majority of species by the end of the century. Selection of indicator species based on rank prevalence results in a set of models that predict observed species richness better than a similar set of species selected based on high rank of model AUC values. An indicator species approach based on selected species that are relatively common may facilitate the use of national monitoring data for predicting climate change effects on the distribution of biodiversity.

Maize leaf development under climate change scenarios

The objective of this work was to simulate maize leaf development in climate change scenarios at Santa Maria, RS, Brazil, considering symmetric and asymmetric increases in air temperature. The model of Wang & Engel for leaf appearance rate (LAR), with genotype-specific coefficients for the maize variety BRS Missões, was used to simulate tip and expanded leaf accumulated number from emergence to flag leaf appearance and expansion, for nine emergence dates from August 15 to April 15. LAR model was run for each emergence date in 100-year climate scenarios: current climate, and +1, +2, +3, +4 and +5°C increase in mean air temperature, with symmetric and asymmetric increase in daily minimum and maximum air temperature. Maize crop failure due to frost decreased in elevated temperature scenarios, in the very early and very late emergence dates, indicating a lengthening in the maize growing season in warmer climates. The leaf development period in maize was shorter in elevated temperature scenarios, with greater shortening in asymmetric temperature increases, indicating that warmer nights accelerate vegetative development in maize.

Early prediction of response to sunitinib after imatinib failure by 18F-fluorodeoxyglucose positron emission tomography in patients with gastrointestinal stromal tumor.

PURPOSE: Positron emission tomography with (18)F-fluorodeoxyglucose (FDG-PET) was used to evaluate treatment response in patients with gastrointestinal stromal tumors (GIST) after administration of sunitinib, a multitargeted tyrosine kinase inhibitor, after imatinib failure. PATIENTS AND METHODS: Tumor metabolism was assessed with FDG-PET before and after the first 4 weeks of sunitinib therapy in 23 patients who received one to 12 cycles of sunitinib therapy (4 weeks of 50 mg/d, 2 weeks off). Treatment response was expressed as the percent change in maximal standardized uptake values (SUV). The primary end point of time to tumor progression was compared with early PET results on the basis of traditional Response Evaluation Criteria in Solid Tumors (RECIST) criteria. RESULTS: Progression-free survival (PFS) was correlated with early FDG-PET metabolic response (P < .0001). Using -25% and +25% thresholds for SUV variations from baseline, early FDG-PET response was stratified in metabolic partial response, metabolically stable disease, or metabolically progressive disease; median PFS rates were 29, 16, and 4 weeks, respectively. Similarly, when a single FDG-PET positive/negative was considered after 4 weeks of sunitinib, the median PFS was 29 weeks for SUVs less than 8 g/mL versus 4 weeks for SUVs of 8 g/mL or greater (P < .0001). None of the patients with metabolically progressive disease subsequently responded according to RECIST criteria. Multivariate analysis showed shorter PFS in patients who had higher residual SUVs (P < .0001), primary resistance to imatinib (P = .024), or nongastric GIST (P = .002), regardless of the mutational status of the KIT and PDGFRA genes. CONCLUSION: Week 4 FDG-PET is useful for early assessment of treatment response and for the prediction of clinical outcome. Thus, it offers opportunities to individualize and optimize patient therapy.

Prediction of plant species distributions across six millennia.

The usefulness of species distribution models (SDMs) in predicting impacts of climate change on biodiversity is difficult to assess because changes in species ranges may take decades or centuries to occur. One alternative way to evaluate the predictive ability of SDMs across time is to compare their predictions with data on past species distributions. We use data on plant distributions, fossil pollen and current and mid-Holocene climate to test the ability of SDMs to predict past climate-change impacts. We find that species showing little change in the estimated position of their realized niche, with resulting good model performance, tend to be dominant competitors for light. Different mechanisms appear to be responsible for among-species differences in model performance. Confidence in predictions of the impacts of climate change could be improved by selecting species with characteristics that suggest little change is expected in the relationships between species occurrence and climate patterns.

Owl melanin-based plumage redness is more frequent near than away from the equator: implications on the effect of climate change on biodiversity

Climate change acts as a major new selective agent on many organisms, particularly at high latitudes where climate change is more pronounced than at lower latitudes. Studies are required to predict which species are at a high risk of extinction and whether certain phenotypes may be more affected by climate change than others. The identification of susceptible phenotypes is important for evaluating the potential negative effect of climate change on biodiversity at the inter- and intraspecific levels. Melanin-based coloration is an interesting and easily accessible candidate trait because, within certain species, reddish pheomelanin-based coloration is associated with adaptations to warm climates. However, it is unclear whether the same holds among species. We tested one prediction of this hypothesis in four owl genera (wood, scops, screech, and pygmy owls), namely that darker reddish species are more prevalent near the equator than polewards. Our comparative analysis is consistent with this prediction for the northern hemisphere, suggesting that pale reddish species may be adapted to cold climates and dark reddish species to warmer climates. Thus, climate change may have a larger negative impact on pale pheomelanic owls and favour dark pheomelanic species.

Barley development as affected by rate of change of photoperiod

The rate of leaf appearance of barley varies substantially with time of sowing. This variation has been related to both the length and the rate of change of photoperiod at the time of plant emergence. An outdoor pot experiment was conducted to test if rate of change of photoperiod directly affects phasic development and rate of leaf emergence of spring barley. Two photoperiod-sensitive cultivars (Bandulla and Galleon) were subjected to five photoperiod regimes: two constant photoperiods, of 14 and 15·5 h, and three different rates of change of photoperiod of c. 2, 9 and 13 min/day from seedling emergence to awn initiation. Photoperiod treatments significantly affected the duration from seedling emergence to awn initiation in both cultivars. Rate of change of photoperiod did not affect the rate of development towards awn initiation independently of the absolute daylength it produced. Although Bandulla had a longer duration than Galleon at any photoperiod regime, the cultivars did not vary in their sensitivity to photoperiod. When this phase was divided into the leaf initiation (LI) and spikelet initiation (SI) phases, it was evident that the sensitivity to photoperiod was not constant, being in general higher during the SI than during the LI phase. However, the magnitude of the change in sensitivity was cultivar-dependent, indicating that sensitivity to photoperiod during the different phases could be under independent genetic control. Final numbers of primordia (leaves together with maximum spikelet number) were negatively affected by increasing photoperiods, but once again, there was no evidence of any effect of the rate of change of photoperiod which was independent of the average photoperiod. Both cultivars showed similar sensitivities for final leaf number but maximum spikelet number was more sensitive to photoperiod in Galleon than in Bandulla. Highly significant linear relationships between leaf number and thermal time were found for all combinations of cultivars and photoperiod regimes (r2 > 0·98). The rate of leaf appearance (RLA) was similar for both cultivars (c. 0·0185 leaves/°Cd) and did not alter during plant development or in response to the change in photoperiod at awn initiation. The range in RLA was greater for Galleon (0·0170–0·0205 leaves/°Cd) than for Bandulla (0·0173–0·0186 leaves/°Cd). Neither of these cultivars exhibited a significant relationship between rate of leaf emergence and photoperiod or rate of change of photoperiod. The lack of significant relationships between RLA and length or rate of change of photoperiod is in contrast with previous reports using time of sowing as a main treatment.

Climate change impacts on lakes: an integrated ecological perspective based on a multi-faceted approach, with special focus on shallow lakes

Freshwater ecosystems and their biodiversity are presently seriously threatened by global development and population growth, leading to increases in nutrient inputs and intensification of eutrophication-induced problems in receiving fresh waters, particularly in lakes. Climate change constitutes another threat exacerbating the symptoms of eutrophication and species migration and loss. Unequivocal evidence of climate change impacts is still highly fragmented despite the intensive research, in part due to the variety and uncertainty of climate models and underlying emission scenarios but also due to the different approaches applied to study its effects. We first describe the strengths and weaknesses of the multi-faceted approaches that are presently available for elucidating the effects of climate change in lakes, including space-for-time substitution, time series, experiments, palaeoecology and modelling. Reviewing combined results from studies based on the various approaches, we describe the likely effects of climate changes on biological communities, trophic dynamics and the ecological state of lakes. We further discuss potential mitigation and adaptation measures to counteract the effects of climate change on lakes and, finally, we highlight some of the future challenges that we face to improve our capacity for successful prediction.

Validation of and comparison between a semidistributed rainfall-runoff hydrological model (PREVAH) and a spatially distributed snow-evolution model (SnowModel) for snow cover prediction in mountain ecosystems

Snow cover is an important control in mountain environments and a shift of the snow-free period triggered by climate warming can strongly impact ecosystem dynamics. Changing snow patterns can have severe effects on alpine plant distribution and diversity. It thus becomes urgent to provide spatially explicit assessments of snow cover changes that can be incorporated into correlative or empirical species distribution models (SDMs). Here, we provide for the first time a with a lower overestimation comparison of two physically based snow distribution models (PREVAH and SnowModel) to produce snow cover maps (SCMs) at a fine spatial resolution in a mountain landscape in Austria. SCMs have been evaluated with SPOT-HRVIR images and predictions of snow water equivalent from the two models with ground measurements. Finally, SCMs of the two models have been compared under a climate warming scenario for the end of the century. The predictive performances of PREVAH and SnowModel were similar when validated with the SPOT images. However, the tendency to overestimate snow cover was slightly lower with SnowModel during the accumulation period, whereas it was lower with PREVAH during the melting period. The rate of true positives during the melting period was two times higher on average with SnowModel with a lower overestimation of snow water equivalent. Our results allow for recommending the use of SnowModel in SDMs because it better captures persisting snow patches at the end of the snow season, which is important when modelling the response of species to long-lasting snow cover and evaluating whether they might survive under climate change.

Association between parental history and genetic risk scores for coronary heart disease prediction: The population-based CoLaus study.

BACKGROUND AND AIMS: Parental history (PH) and genetic risk scores (GRSs) are separately associated with coronary heart disease (CHD), but evidence regarding their combined effects is lacking. We aimed to evaluate the joint associations and predictive ability of PH and GRSs for incident CHD. METHODS: Data for 4283 Caucasians were obtained from the population-based CoLaus Study, over median follow-up time of 5.6 years. CHD was defined as incident myocardial infarction, angina, percutaneous coronary revascularization or bypass grafting. Single nucleotide polymorphisms for CHD identified by genome-wide association studies were used to construct unweighted and weighted versions of three GRSs, comprising of 38, 53 and 153 SNPs respectively. RESULTS: PH was associated with higher values of all weighted GRSs. After adjustment for age, sex, smoking, diabetes, systolic blood pressure, low and high density lipoprotein cholesterol, PH was significantly associated with CHD [HR 2.61, 95% CI (1.47-4.66)] and further adjustment for GRSs did not change this estimate. Similarly, one standard deviation change of the weighted 153-SNPs GRS was significantly associated with CHD [HR 1.50, 95% CI (1.26-1.80)] and remained so, after further adjustment for PH. The weighted, 153-SNPs GRS, but not PH, modestly improved discrimination [(C-index improvement, 0.016), p = 0.048] and reclassification [(NRI improvement, 8.6%), p = 0.027] beyond cardiovascular risk factors. After including both the GRS and PH, model performance improved further [(C-index improvement, 0.022), p = 0.006]. CONCLUSION: After adjustment for cardiovascular risk factors, PH and a weighted, polygenic GRS were jointly associated with CHD and provided additive information for coronary events prediction.

A Meta-Analysis of Trabecular Bone Score in Fracture Risk Prediction and Its Relationship to FRAX.

Trabecular bone score (TBS) is a gray-level textural index of bone microarchitecture derived from lumbar spine dual-energy X-ray absorptiometry (DXA) images. TBS is a bone mineral density (BMD)-independent predictor of fracture risk. The objective of this meta-analysis was to determine whether TBS predicted fracture risk independently of FRAX probability and to examine their combined performance by adjusting the FRAX probability for TBS. We utilized individual-level data from 17,809 men and women in 14 prospective population-based cohorts. Baseline evaluation included TBS and the FRAX risk variables, and outcomes during follow-up (mean 6.7 years) comprised major osteoporotic fractures. The association between TBS, FRAX probabilities, and the risk of fracture was examined using an extension of the Poisson regression model in each cohort and for each sex and expressed as the gradient of risk (GR; hazard ratio per 1 SD change in risk variable in direction of increased risk). FRAX probabilities were adjusted for TBS using an adjustment factor derived from an independent cohort (the Manitoba Bone Density Cohort). Overall, the GR of TBS for major osteoporotic fracture was 1.44 (95% confidence interval [CI] 1.35-1.53) when adjusted for age and time since baseline and was similar in men and women (p > 0.10). When additionally adjusted for FRAX 10-year probability of major osteoporotic fracture, TBS remained a significant, independent predictor for fracture (GR = 1.32, 95% CI 1.24-1.41). The adjustment of FRAX probability for TBS resulted in a small increase in the GR (1.76, 95% CI 1.65-1.87 versus 1.70, 95% CI 1.60-1.81). A smaller change in GR for hip fracture was observed (FRAX hip fracture probability GR 2.25 vs. 2.22). TBS is a significant predictor of fracture risk independently of FRAX. The findings support the use of TBS as a potential adjustment for FRAX probability, though the impact of the adjustment remains to be determined in the context of clinical assessment guidelines. © 2015 American Society for Bone and Mineral Research.

Patterns of faunal change at an upper Cambrian trilobite extinction event, Nolichucky Formation, Tennessee and Virginia

During the Upper Cambrian there were three mass extinctions, each of which eliminated at least half of the trilobite families living in North American shelf seas. The Nolichucky Formation preserves the record of one of these extinction events at the base of the Steptoean Stage. Sixty-six trilobite collections were made from five sections In Tennessee and Virginia. The lower Steptoean faunas are assigned to one low diversity, Aphelaspis-dominated biofacies, which can be recognized in several other parts of North America. In Tennessee, the underlying upper Marjuman strata contain two higher diversity biofacies, the Coosella-Glaphyraspis Biofacies and the Tricrepicephalus-Norwoodiid Biofacies. At least four different biofacies are present in other parts of North America: the Crepicephalus -Lonchocephalus Biofacies, the Kingstonia Biofacies, the Cedaria Biofacies, and the Uncaspis Biofacies. A new, species-based zonation for the Nolichucky Formation imcludes five zones, three of which are new. These zones are the Crepicephalus Zone, the Coosella perplexa Zone, the Aphelaspis buttsi Zone, the A. walcotti Zone and the A. tarda Zone. The Nolichucky Formation was deposited within a shallow shelf basin and consists largely of subtidal shales with stormgenerated carbonate interbeds. A relative deepening is recorded In the Nolichucky Formation near the extinction, and is indicated In some sections by the appearance of shale-rich, distal storm deposits above a carbonate-rich, more proximal storm deposit sequence. A comparable deepening-upward sequence occurs near the extinction in the Great Basin of southwestern United States and in central Texas, and this suggests a possible eustatic control. In other parts of North America, the extinction IS recorded In a variety of environmental settings that range from near-shore to slope. In shelf environments, there is a marked decrease in diversity, and a sharp reduction in biofacies differentiation. Although extinctions do take place in slope environments, there IS no net reduction in diversity because of the immigration of several new taxa.

Flow regime prediction via froude number calculation in a rock-bedded stream

Mathematical predictions of flow conditions along a steep gradient rock bedded stream are examined. Stream gage discharge data and Manning's Equation are used to calculate alternative velocities, and subsequently Froude Numbers, assuming varying values of velocity coefficient, full depth or depth adjusted for vertical flow separation. Comparison of the results with photos show that Froude Numbers calculated from velocities derived from Manning's Equation, assuming a velocity coefficient of 1.30 and full depth, most accurately predict flow conditions, when supercritical flow is defined as Froude Number values above 0.84. Calculated Froude Number values between 0.8 and 1.1 correlate well with observed transitional flow, defined as the first appearance of small diagonal waves. Transitions from subcritical through transitional to clearly supercritical flow are predictable. Froude Number contour maps reveal a sinuous rise and fall of values reminiscent of pool riffle energy distribution.

The Hidden Truths of Self-Presentation, Self-Disclosure, and Deception on Online Dating Profiles: A Call for Change

The way in which individuals seek romantic partners has changed considerably in the past decades, most notably through online dating sites (ODSs). Despite the possibility of misrepresentation amongst client users, such sites continue to grow in popularity because ODSs provide a large pool from which individuals can select and attract potential partners. While much research has been undertaken on ODSs, little empirical research has examined postsecondary students’ use of ODSs. Therefore, this study sought to investigate why postsecondary students have become involved with and how they present themselves on ODSs. The researcher surveyed 20 postsecondary students and conducted in-depth interviews with 2 participants who use ODSs. Although the limited sample prevented results from being generalized, quantitative and qualitative analyses suggest that participants became involved with ODSs for various purposes, such as seeking long-term relationships and/or marriage partners, or simply exploring or visiting ODSs out of curiosity. Findings indicate that ODS users’ physical appearance and/or “attractiveness” is considered the strongest predictor of relationship success. The study discusses how participants’ self-presentation affects outcomes of ODS usage, particularly when negative self-identification and presentation corresponding to factors such as individuals’ weight and age are taken into account.

Statistical model based 3D shape prediction of postoperative trunks for non-invasive scoliosis surgery planning

One of the major concerns of scoliosis patients undergoing surgical treatment is the aesthetic aspect of the surgery outcome. It would be useful to predict the postoperative appearance of the patient trunk in the course of a surgery planning process in order to take into account the expectations of the patient. In this paper, we propose to use least squares support vector regression for the prediction of the postoperative trunk 3D shape after spine surgery for adolescent idiopathic scoliosis. Five dimensionality reduction techniques used in conjunction with the support vector machine are compared. The methods are evaluated in terms of their accuracy, based on the leave-one-out cross-validation performed on a database of 141 cases. The results indicate that the 3D shape predictions using a dimensionality reduction obtained by simultaneous decomposition of the predictors and response variables have the best accuracy.