scholarly journals Phytophthora acaciivora sp. nov. associated with dying Acacia mangium in Vietnam

2020 ◽  
Vol 6 (1) ◽  
pp. 243-252
Author(s):  
T.I. Burgess ◽  
Q.N. Dang ◽  
B.V. Le ◽  
N.Q. Pham ◽  
D. White ◽  
...  
Keyword(s):  
New Species ◽  
Acacia Mangium ◽  
Maximum Temperature ◽  
Optimum Temperature ◽  
Unknown Species ◽  
Exotic Plantations ◽  
Heterothallic Species ◽  
The Impact

Acacia mangium plantations account for more than 50 % of the exotic plantations in Vietnam. A new black butt symptom was discovered in 2012, followed by the wilting sign in Acacia seedlings in Tuyen Quang Province. Isolations recovered two Phytophthora species, the well-known Acacia pathogen P. cinnamomi, and an unknown species. The new species is described here as Phytophthora acaciivora sp. nov. Phylogenetically this species resides in clade 2d and is most closely related to P. frigida. Phytophthora acaciivora is a heterothallic species, oospores are aplerotic and antheridia are amphigynous. It produces predominantly elongated ovoid, semi papillate, persistent sporangia, no hyphal swellings and no chlamydospores. Optimum temperature for the growth is 25–30 °C and the maximum temperature is over 37.5 °C. Studies are underway to determine the impact of this new species on Acacia plantations in Vietnam.

scholarly journals Social media reveal ecoregional variation in how weather influences visitor behavior in U.S. National Park Service units

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily J. Wilkins ◽  
Peter D. Howe ◽  
Jordan W. Smith
Keyword(s):  
National Park ◽  
National Park Service ◽  
Spatial Behavior ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Daily Weather ◽  
Visitor Behavior ◽  
Park Service ◽  
The Impact

AbstractDaily weather affects total visitation to parks and protected areas, as well as visitors’ experiences. However, it is unknown if and how visitors change their spatial behavior within a park due to daily weather conditions. We investigated the impact of daily maximum temperature and precipitation on summer visitation patterns within 110 U.S. National Park Service units. We connected 489,061 geotagged Flickr photos to daily weather, as well as visitors’ elevation and distance to amenities (i.e., roads, waterbodies, parking areas, and buildings). We compared visitor behavior on cold, average, and hot days, and on days with precipitation compared to days without precipitation, across fourteen ecoregions within the continental U.S. Our results suggest daily weather impacts where visitors go within parks, and the effect of weather differs substantially by ecoregion. In most ecoregions, visitors stayed closer to infrastructure on rainy days. Temperature also affects visitors’ spatial behavior within parks, but there was not a consistent trend across ecoregions. Importantly, parks in some ecoregions contain more microclimates than others, which may allow visitors to adapt to unfavorable conditions. These findings suggest visitors’ spatial behavior in parks may change in the future due to the increasing frequency of hot summer days.

scholarly journals The impact of climate change in wheat and barley yields in the Iberian Peninsula

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Virgílio A. Bento ◽  
Andreia F. S. Ribeiro ◽  
Ana Russo ◽  
Célia M. Gouveia ◽  
Rita M. Cardoso ◽  
...  
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Model ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
Historical Period ◽  
Early Winter ◽  
Impact Of Climate Change ◽  
The Impact ◽  
Spring Maximum

AbstractThe impact of climate change on wheat and barley yields in two regions of the Iberian Peninsula is here examined. Regression models are developed by using EURO-CORDEX regional climate model (RCM) simulations, forced by ERA-Interim, with monthly maximum and minimum air temperatures and monthly accumulated precipitation as predictors. Additionally, RCM simulations forced by different global climate models for the historical period (1972–2000) and mid-of-century (2042–2070; under the two emission scenarios RCP4.5 and RCP8.5) are analysed. Results point to different regional responses of wheat and barley. In the southernmost regions, results indicate that the main yield driver is spring maximum temperature, while further north a larger dependence on spring precipitation and early winter maximum temperature is observed. Climate change seems to induce severe yield losses in the southern region, mainly due to an increase in spring maximum temperature. On the contrary, a yield increase is projected in the northern regions, with the main driver being early winter warming that stimulates earlier growth. These results warn on the need to implement sustainable agriculture policies, and on the necessity of regional adaptation strategies.

scholarly journals Phytophthora mediterranea sp. nov., a New Species Closely Related to Phytophthora cinnamomi from Nursery Plants of Myrtus communis in Italy

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 682
Author(s):  
Carlo Bregant ◽  
Antonio A. Mulas ◽  
Giovanni Rossetto ◽  
Antonio Deidda ◽  
Lucia Maddau ◽  
...  
Keyword(s):  
New Species ◽  
Root Rot ◽  
Phytophthora Cinnamomi ◽  
Colony Growth ◽  
Phytophthora Species ◽  
Maximum Temperature ◽  
Pathogenicity Test ◽  
Forest Nurseries ◽  
Collar And Root Rot ◽  
A New Species

Monitoring surveys of Phytophthora related diseases in four forest nurseries in Italy revealed the occurrence of fourteen Phytophthora species to be associated with collar and root rot on fourteen plants typical of Mediterranean and alpine regions. In addition, a multilocus phylogeny analysis based on nuclear ITS and ß-tubulin and mitochondrial cox1 sequences, as well as micromorphological features, supported the description of a new species belonging to the phylogenetic clade 7c, Phytophthora mediterranea sp. nov. Phytophthora mediterranea was shown to be associated with collar and root rot symptoms on myrtle seedlings. Phylogenetically, P. mediterranea is closely related to P. cinnamomi but the two species differ in 87 nucleotides in the three studied DNA regions. Morphologically P. mediterranea can be easily distinguished from P. cinnamomi on the basis of its smaller sporangia, colony growth pattern and higher optimum and maximum temperature values. Data from the pathogenicity test showed that P. mediterranea has the potential to threaten the native Mediterranean maquis vegetation. Finally, the discovery of P. cinnamomi in alpine nurseries, confirms the progressive expansion of this species towards cold environments, probably driven by climate change.

scholarly journals Analysis of the Accelerator-Driven System Fuel Assembly during the Steam Generator Tube Rupture Accident

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 1818
Author(s):  
Di-Si Wang ◽  
Bo Liu ◽  
Sheng Yang ◽  
Bin Xi ◽  
Long Gu ◽  
...  
Keyword(s):  
Fuel Assembly ◽  
Steam Generator ◽  
Metal Flow ◽  
Maximum Temperature ◽  
Steam Generator Tube ◽  
Driven System ◽  
Fuel Assemblies ◽  
Accelerator Driven System ◽  
The Impact ◽  
Steam Bubble

China is developing an ADS (Accelerator-Driven System) research device named the China initiative accelerator-driven system (CiADS). When performing a safety analysis of this new proposed design, the core behavior during the steam generator tube rupture (SGTR) accident has to be investigated. The purpose of our research in this paper is to investigate the impact from different heating conditions and inlet steam contents on steam bubble and coolant temperature distributions in ADS fuel assemblies during a postulated SGTR accident by performing necessary computational fluid dynamics (CFD) simulations. In this research, the open source CFD calculation software OpenFOAM, together with the two-phase VOF (Volume of Fluid) model were used to simulate the steam bubble behavior in heavy liquid metal flow. The model was validated with experimental results published in the open literature. Based on our simulation results, it can be noticed that steam bubbles will accumulate at the periphery region of fuel assemblies, and the maximum temperature in fuel assembly will not overwhelm its working limit during the postulated SGTR accident when the steam content at assembly inlet is less than 15%.

scholarly journals Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

2021 ◽  
Vol 13 (2) ◽  
pp. 323
Author(s):  
Liang Chen ◽  
Xuelei Wang ◽  
Xiaobin Cai ◽  
Chao Yang ◽  
Xiaorong Lu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Maximum Temperature ◽  
Maximum Temperature Difference ◽  
Rapid Urbanization ◽  
The Impact ◽  
The City

Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 °C and 2.6 °C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.

scholarly journals Predicting the Impact of Describing New Species on Phylogenetic Patterns

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
D C Blackburn ◽  
G Giribet ◽  
D E Soltis ◽  
E L Stanley
Keyword(s):  
New Species ◽  
Phylogenetic Trees ◽  
Branch Length ◽  
Length Variation ◽  
Tree Shape ◽  
Branch Lengths ◽  
Taxonomic History ◽  
Ecological Patterns ◽  
The Impact ◽  
Incomplete Sampling

Abstract Although our inventory of Earth’s biodiversity remains incomplete, we still require analyses using the Tree of Life to understand evolutionary and ecological patterns. Because incomplete sampling may bias our inferences, we must evaluate how future additions of newly discovered species might impact analyses performed today. We describe an approach that uses taxonomic history and phylogenetic trees to characterize the impact of past species discoveries on phylogenetic knowledge using patterns of branch-length variation, tree shape, and phylogenetic diversity. This provides a framework for assessing the relative completeness of taxonomic knowledge of lineages within a phylogeny. To demonstrate this approach, we use recent large phylogenies for amphibians, reptiles, flowering plants, and invertebrates. Well-known clades exhibit a decline in the mean and range of branch lengths that are added each year as new species are described. With increased taxonomic knowledge over time, deep lineages of well-known clades become known such that most recently described new species are added close to the tips of the tree, reflecting changing tree shape over the course of taxonomic history. The same analyses reveal other clades to be candidates for future discoveries that could dramatically impact our phylogenetic knowledge. Our work reveals that species are often added non-randomly to the phylogeny over multiyear time-scales in a predictable pattern of taxonomic maturation. Our results suggest that we can make informed predictions about how new species will be added across the phylogeny of a given clade, thus providing a framework for accommodating unsampled undescribed species in evolutionary analyses.

Design and Optimization of a Shape Memory Alloy-Based Self-Folding Sheet

2013 ◽  
Vol 135 (11) ◽  
Author(s):  
Edwin Peraza-Hernandez ◽  
Darren Hartl ◽  
Edgar Galvan ◽  
Richard Malak
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Three Dimensional ◽  
Building Blocks ◽  
Passive Layer ◽  
Von Mises Stress ◽  
Maximum Temperature ◽  
Radius Of Curvature ◽  
Folding Angle ◽  
The Impact

Origami engineering—the practice of creating useful three-dimensional structures through folding and fold-like operations on two-dimensional building-blocks—has the potential to impact several areas of design and manufacturing. In this article, we study a new concept for a self-folding system. It consists of an active, self-morphing laminate that includes two meshes of thermally-actuated shape memory alloy (SMA) wire separated by a compliant passive layer. The goal of this article is to analyze the folding behavior and examine key engineering tradeoffs associated with the proposed system. We consider the impact of several design variables including mesh wire thickness, mesh wire spacing, thickness of the insulating elastomer layer, and heating power. Response parameters of interest include effective folding angle, maximum von Mises stress in the SMA, maximum temperature in the SMA, maximum temperature in the elastomer, and radius of curvature at the fold line. We identify an optimized physical realization for maximizing folding capability under mechanical and thermal failure constraints. Furthermore, we conclude that the proposed self-folding system is capable of achieving folds of significant magnitude (as measured by the effective folding angle) as required to create useful 3D structures.

scholarly journals Modeling the Impact of Climate Changes on Crop Yield: Irrigated vs. Non-Irrigated Zones in Mississippi

2021 ◽  
Vol 13 (12) ◽  
pp. 2249
Author(s):  
Sadia Alam Shammi ◽  
Qingmin Meng
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Negative Impact ◽  
Positive Impact ◽  
Information Criterion ◽  
Growing Season ◽  
Maximum Temperature ◽  
Linear Regression Models ◽  
The Impact

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.

Calorimetric determination of the effect of additives on cement hydration process

2013 ◽  
Vol 67 (2) ◽  
Author(s):  
Pavel Šiler ◽  
Josef Krátký ◽  
Iva Kolářová ◽  
Jaromír Havlica ◽  
Jiří Brandštetr
Keyword(s):  
Portland Cement ◽  
Silica Fume ◽  
Maximum Temperature ◽  
Granulated Blast Furnace Slag ◽  
Mineral Components ◽  
Maximum Temperatures ◽  
The Impact ◽  
Furnace Slag ◽  
Calorimetric Determination

AbstractPossibilities of a multicell isoperibolic-semiadiabatic calorimeter application for the measurement of hydration heat and maximum temperature reached in mixtures of various compositions during their setting and early stages of hardening are presented. Measurements were aimed to determine the impact of selected components’ content on the course of ordinary Portland cement (OPC) hydration. The following components were selected for the determination of the hydration behaviour in mixtures: very finely ground granulated blast furnace slag (GBFS), silica fume (microsilica, SF), finely ground quartz sand (FGQ), and calcined bauxite (CB). A commercial polycarboxylate type superplasticizer was also added to the selected mixtures. All maximum temperatures measured for selected mineral components were lower than that reached for cement. The maximum temperature increased with the decreasing amount of components in the mixture for all components except for silica fume. For all components, except for CB, the values of total released heat were higher than those for pure Portland cement samples.

scholarly journals Verification of surface minimum, mean, and maximum temperature forecasts in Calabria for summer 2008

2011 ◽  
Vol 11 (2) ◽  
pp. 487-500 ◽  
Author(s):  
S. Federico
Keyword(s):  
Forecast Error ◽  
Background Field ◽  
Horizontal Resolution ◽  
Atmospheric Modeling ◽  
Forecast Skill ◽  
Maximum Temperature ◽  
Model Forecast ◽  
Maximum Temperatures ◽  
Analysis Error ◽  
The Impact

Abstract. Since 2005, one-hour temperature forecasts for the Calabria region (southern Italy), modelled by the Regional Atmospheric Modeling System (RAMS), have been issued by CRATI/ISAC-CNR (Consortium for Research and Application of Innovative Technologies/Institute for Atmospheric and Climate Sciences of the National Research Council) and are available online at http://meteo.crati.it/previsioni.html (every six hours). Beginning in June 2008, the horizontal resolution was enhanced to 2.5 km. In the present paper, forecast skill and accuracy are evaluated out to four days for the 2008 summer season (from 6 June to 30 September, 112 runs). For this purpose, gridded high horizontal resolution forecasts of minimum, mean, and maximum temperatures are evaluated against gridded analyses at the same horizontal resolution (2.5 km). Gridded analysis is based on Optimal Interpolation (OI) and uses the RAMS first-day temperature forecast as the background field. Observations from 87 thermometers are used in the analysis system. The analysis error is introduced to quantify the effect of using the RAMS first-day forecast as the background field in the OI analyses and to define the forecast error unambiguously, while spatial interpolation (SI) analysis is considered to quantify the statistics' sensitivity to the verifying analysis and to show the quality of the OI analyses for different background fields. Two case studies, the first one with a low (less than the 10th percentile) root mean square error (RMSE) in the OI analysis, the second with the largest RMSE of the whole period in the OI analysis, are discussed to show the forecast performance under two different conditions. Cumulative statistics are used to quantify forecast errors out to four days. Results show that maximum temperature has the largest RMSE, while minimum and mean temperature errors are similar. For the period considered, the OI analysis RMSEs for minimum, mean, and maximum temperatures vary from 1.8, 1.6, and 2.0 °C, respectively, for the first-day forecast, to 2.0, 1.9, and 2.6 °C, respectively, for the fourth-day forecast. Cumulative statistics are computed using both SI and OI analysis as reference. Although SI statistics likely overestimate the forecast error because they ignore the observational error, the study shows that the difference between OI and SI statistics is less than the analysis error. The forecast skill is compared with that of the persistence forecast. The Anomaly Correlation Coefficient (ACC) shows that the model forecast is useful for all days and parameters considered here, and it is able to capture day-to-day weather variability. The model forecast issued for the fourth day is still better than the first-day forecast of a 24-h persistence forecast, at least for mean and maximum temperature. The impact of using the RAMS first-day forecast as the background field in the OI analysis is quantified by comparing statistics computed with OI and SI analyses. Minimum temperature is more sensitive to the change in the analysis dataset as a consequence of its larger representative error.

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