Thermotoga neapolitana sp. nov. of the extremely thermophilic,eubacterial genus Thermotoga

A second species of the extremely thermophilic, eubacterial genus Thermotoga is described as clearly distinguished from the type species Thermotoga maritima by physiological and phylogenetic criteria. It is named Thermotoga neapolitana.     

Population dynamics of a tree-dwelling aphid: regulation and density-independent processes

1. A population of the Turkey-oak aphid ( Myzocallis boerneri Stroyan) was sampled at approximately weekly intervals on two Turkey-oak trees for 19 years.
2. On one tree (A), the aphids exhibited a distinct seasonal pattern with a spring increase, summer decrease, early autumn increase, and late autumn decline. On the other tree (B) the aphids remained at low densities after the decrease in summer.
3. On tree A, significant undercompensating density dependence occurred during all periods of the seasonal population development, and their strength varied little during the course of the season. On tree B, significant density dependence compensated exactly for increase, but appeared only after the decrease in summer when the population remained at very low densities for the rest of the season.
4. Density-independent weather variables affected the population dynamics very little. Their influence was marginally significant only at very low densities when the aphids were regulated exactly by compensating density-dependent factors.
5. The results suggest a curvilinear density dependence, with strong regulation at low densities, and weak at high densities. That is, this aphid was most regulated not at the peak but at the trough densities.     

Meteorological effects on the daily activity patterns of tabanid biting flies in northern Queensland,Australia

Information on the daily activity patterns of tabanid flies is important in the development of strategies that decrease the risk of pathogens transmitted by them. In addition, this information is useful to maximize numbers of tabanids trapped during short‐term studies and to target feeding behavior studies of certain tabanid species to their times of peak activity. The current study examined the effects of various meteorological factors on the daily activity patterns of common tropical species of tabanids in north Queensland. Each species studied responded differently to weather factors. Tabanus townsvilli Ricardo (Diptera: Tabanidae) was most active during late morning and early afternoon, whereas Pseudotabanus silvester (Bergroth) and Tabanus pallipennis Macquart were most active in the late afternoon. Tabanus dorsobimaculatus Macquart was most active in the morning and early afternoon. Data on daily activity patterns of tabanid flies indicates that in an area such as Townsville, North Queensland, where several species of tabanid are present concurrently in high numbers, the overlapping periods of high activity for these species indicate a high risk of pathogen transmission for most of the day (10.00–19.00 hours). Similarly, because each species responds differently to weather variables, only extreme weather conditions are likely to inhibit activity of all species. These data also indicate that for maximal results, trapping and feeding behavior studies should be tailored to the preferred activity period of the species under investigation.     

Extreme heat events and the vulnerability of endemic montane fishes to climate change

Identifying how close species live to their physiological thermal maxima is essential to understand historical warm‐edge elevational limits of montane faunas and forecast upslope shifts caused by future climate change. We used laboratory experiments to quantify the thermal tolerance and acclimation potential of four fishes (Notropis leuciodus, N. rubricroceus, Etheostoma rufilineatum, E. chlorobranchium) that are endemic to the southern Appalachian Mountains (USA), exhibit different historical elevational limits, and represent the two most species‐rich families in the region. All‐subsets selection of linear regression models using AIC_c indicated that species, acclimation temperature, collection location and month, and the interaction between species and acclimation temperature were important predictors of thermal maxima (T_max), which ranged from 28.5 to 37.2°C. Next, we implemented water temperature models and stochastic weather generation to characterize the magnitude and frequency of extreme heat events (T_extreme) under historical and future climate scenarios across 25 379 stream reaches in the upper Tennessee River system. Lastly, we used environmental niche models to compare warming tolerances (acclimation‐corrected T_max minus T_extreme) between historically occupied versus unoccupied reaches. Historical warming tolerances, ranging from +2.2 to +10.9°C, increased from low to high elevation and were positive for all species, suggesting that T_max does not drive warm‐edge (low elevation) range limits. Future warming tolerances were lower (?1.2 to +9.3°C) but remained positive for all species under the direst warming scenario except for a small proportion of reaches historically occupied by E. rufilineatum, indicating that T_max and acclimation potentials of southern Appalachian minnows and darters are adequate to survive future heat waves. We caution concluding that these species are invulnerable to 21st century warming because sublethal thermal physiology remains poorly understood. Integrating physiological sensitivity and warming exposure demonstrates a general and fine‐grained approach to assess climate change vulnerability for freshwater organisms across physiographically diverse riverscapes.     

bioRad: biological analysis and visualization of weather radar data

Weather surveillance radars are increasingly used for monitoring the movements and abundances of animals in the airspace. However, analysis of weather radar data remains a specialised task that can be technically challenging. Major hurdles are the difficulty of accessing and visualising radar data on a software platform familiar to ecologists and biologists, processing the low‐level data into products that are biologically meaningful, and summarizing these results in standardized measures. To overcome these hurdles, we developed the open source R package bioRad, which provides a toolbox for accessing, visualizing and analyzing weather radar data for biological studies. It provides functionality to access low‐level radar data, process these data into meaningful biological information on animal speeds and directions at different altitudes in the atmosphere, visualize these biological extractions, and calculate further summary statistics. The package aims to standardize methods for extracting and reporting biological signals from weather radars. Here we describe a roadmap for analyzing weather radar data using bioRad. We also define weather radar equivalents for familiar measures used in the field of migration ecology, such as migration traffic rates, and recommend several good practices for reporting these measures. The bioRad package integrates with low‐level data from both the European radar network (OPERA) and the radar network of the United States (NEXRAD). bioRad aims to make weather radar studies in ecology easier and more reproducible, allowing for better inter‐comparability of studies.     

澳门九澳山海滨群落10种植物盛花期物候对极端气候事件的响应

为探究极端气候事件对植物的影响,对澳门九澳山海滨群落10种植物2012-2017年盛花期物候进行了观察。结果表明,植物的盛花期一般在3-9月,其中有4种植物为5月。2013和2016年早春澳门的极端强降水使植物的盛花期出现了明显的提前或者推迟。9种植物的盛花期与盛花期前0～2个月和上一年的秋冬季的月均温度或月降水存在显著相关性。温度和降水对植物盛花期的影响差异不大,但晚花植物对降水更加敏感。这为澳门和邻近岛屿的生态恢复和园林树种选材提供参考。     

Viruses in extreme environments

The tolerance limits of extremophiles in term of temperature, pH, salinity, desiccation, hydrostatic pressure, radiation, anaerobiosis far exceed what can support non-extremophilic organisms. Like all other organisms, extremophiles serve as hosts for viral replication. Many lines of evidence suggest that viruses could no more be regarded as simple infectious “fragments of life” but on the contrary as one of the major components of the biosphere. The exploration of niches with seemingly harsh life conditions as hypersaline and soda lakes, Sahara desert, polar environments or hot acid springs and deep sea hydrothermal vents, permitted to track successfully the presence of viruses. Substantial populations of double-stranded DNA virus that can reach 10⁹ particles per milliliter were recorded. All these viral communities, with genome size ranging from 14 kb to 80 kb, seem to be genetically distinct, suggesting specific niche adaptation. Nevertheless, at this stage of the knowledge, very little is known of their origin, activity, or importance to the in situ microbial dynamics. The continuous attempts to isolate and to study viruses that thrive in extreme environments will be needed to address such questions. However, this topic appears to open a new window on an unexplored part of the viral world. Marc Le Romancer and Mélusine Gaillard contributed equally to this work.     

Using a BP Neural Network for Rapid Assessment of Populations with Difficulties Accessing Drinking Water Because of Drought

Accurately predicting the populations with difficulties accessing drinking water because of drought and taking appropriate mitigation measures can minimize economic loss and personal injury. Taking the 2013 Guizhou extreme summer drought as an example, on the basis of collecting meteorological, basic geographic information, socioeconomic data, and disaster effect data of the study area, a rapid assessment model based on a backpropagation (BP) neural network was constructed. Six factors were chosen for the input of the network: the average monthly precipitation, Digital Elevation Model (DEM), river density, population density, road density, and gross domestic product (GDP). The population affected by drought was the model's output. Using samples from 50 drought-affected counties in Guizhou Province for network training, the model's parameters were optimized. Using the trained model, the populations in need were predicted using the other 74 drought-affected counties. The accuracy of the prediction model, represented by the coefficient of determination (R²) and the normalized root mean square error (N-RMSE), yielded 0.7736 for R² and 0.0070 for N-RMSE. The method may provide an effective reference for rapid assessment of the population in need and disaster effect verification.