Standard Deviation Of Elevation Research Articles

Integration of Analytical Hierarchy Process and Landslide Susceptibility Index Based Landslide Susceptibility Assessment of the Pearl River Delta Area, China

Landslide is one of the most disastrous geological hazards in the Pearl River Delta area. In the article, landslide susceptibility index (LSI) and analytical hierarchy process (AHP) have been adopted to assess landslide susceptibility (LS) of the Pearl River Delta area. A total of 294 historical landslide sites were extracted from China Geological Survey Result CGS2015-008 and remote sensing images as landslide inventory. In each experiment, 198 landslide points were randomly selected as training samples and the remaining 96 as verification samples. Nine influencing factors, i.e., standard deviation (STD) of elevation, terrain roughness, curvature, lithology, fault, land use, water density, road density, and aspect, were obtained through ASTER GDEM, China Geological Survey Result CGS2015-008, Geographical Information Monitoring Cloud Platform, Open Street Map, and Google Earth. LSI was used to represent the contribution of each category within the influencing factors to the occurrence of landslides (LSIi), and AHP was used to calculate the weights between different influencing factors (Wi). Finally, the summation of the product of LSIi by Wi was used to represent the LS value for each pixel. Then, the study area was grouped into five susceptibility classes based on the landslide susceptibility. It is indicated that terrain factors have the greatest impact on landslides, followed by engineering geological lithology and land use types. The high and very high susceptibility classes were mainly distributed in the area of: 1) STD of elevation of 0.8–2.5, roughness of 1.004–1.030, and curvature 2.7–7.2; 2) sand-shale stone and coal, bedded clastic rock, and bedded epimetamorphic rock; and 3) woodland and the urban and rural land. The receiver operating characteristic curves of many experimental results prove that the model has fine prediction performance and good stability. This article could provide a basis for landslide prevention and land development in the Pearl River Delta area.

An Attempt to Improve Snow Depth Retrieval Using Satellite Microwave Radiometry for Rough Antarctic Sea Ice

Snow depth on sea ice is a major constituent of the marine cryosphere. It is a key parameter for the derivation of sea-ice thickness from satellite altimetry. One way to retrieve the basin-scale snow depth on sea ice is by satellite microwave radiometry. There is evidence from measurements and inter-comparison studies that current retrievals likely under-estimate the snow depth over deformed, rough sea ice. We follow up on an earlier study, where satellite passive microwave data were combined with information on the sea-ice topography from the satellite laser altimeter on board the Ice, Cloud and land Elevation Satellite (ICESat) in a hybrid approach. Such topography information is spatiotemporally limited because of ICESat’s operation mode. In this paper, we aim to derive a proxy for this topography information from satellite microwave radiometry. For this purpose, we co-locate parameters describing the sea-ice deformation taken from visual ship-based observations and the surface elevation standard deviation derived from ICESat laser altimetry with the microwave brightness temperatures (TB) measured via the Advanced Microwave Scanning Radiometer aboard Earth Observation Satellite (AMSR-E) and aboard Global Change Observation Mission-Water 1 (GCOM-W1) (AMSR2). We find that the TB polarization ratio at 6.9 GHz and the TB gradient ratio between 10.7 GHz (horizontal polarization) and 6.9 GHz (vertical polarization), might be suited as such a proxy. Using this proxy, we modify the above-mentioned hybrid approach and compute the snow depths on sea ice from the AMSR-E and AMSR2 data. We compare our snow depths with those of the commonly used approach, the hybrid approach, with the ship-based observations for the years 2002 through 2015 and with the measurements made by drifting buoys for the period of 2014 through 2018. We find a convincing overall agreement with the hybrid approach and some improvement over the common approach. However, our approach is sensitive to the presence of thin ice—here, the retrieved snow depths are too large; and our approach performs sub-optimally over old ice—here, the retrieved snow depths are too small. More investigations and, in particular, more evaluations are required to optimize our approach so that the snow depths retrieved for the combined AMSR-E/AMSR2 period could serve as a data set for sea-ice thickness retrieval based on satellite altimetry.

Effects of Sand Addition and Bed Flushing on Gravel Bed Surface Microtopography and Roughness

AbstractGravel riverbeds naturally present a range of sediment size that can span several orders of magnitude. However, fine sediment (i.e., size <2 mm) additions affect sediment transport and are potentially harmful to the river ecology. Limited research has been done to understand the effects of sand addition on gravel bed topography. For this study, we conducted flume experiments testing the effectiveness of topography remote sensing to measure the response of a water‐worked gravel bed to varying sand additions and bed flushing. Repeated measurements of the bed topography with through‐water photogrammetry show that sand deposits primarily in low‐lying areas of the bed, where it is sheltered. Observed changes in bed elevation standard deviation, skewness, and inclination index indicate a smoother bed, as sand fills the depressions on the surface and conceals gravel imbrication. The overall bed morphology (e.g., small bedforms and coarse grain arrangement), however, is preserved. Increasing the sand supply resulted in a gravel bed buried by sand and the formation of sand dunes. Bed flushing with a flow sufficient to move sand allowed a return of the bed roughness to the prepulse conditions, while flushing the bed with a discharge equivalent to the armoring discharge reworked the normally stable surface layer without removing infiltrated sand from the subsurface. This new data set contributes to providing missing information on the small‐scale topographic effects of sand addition upon gravel beds. It might be used with measurements of near‐bed flow hydraulics obtained in other studies to explain variations of sediment transport.

Flood Risk Evaluation in the Middle Reaches of the Yangtze River Based on Eigenvector Spatial Filtering Poisson Regression

A Poisson regression based on eigenvector spatial filtering (ESF) is proposed to evaluate the flood risk in the middle reaches of the Yangtze River in China. Regression analysis is employed to model the relationship between the frequency of flood alarming events observed by hydrological stations and hazard-causing factors from 2005 to 2012. Eight factors, including elevation (ELE), slope (SLO), elevation standard deviation (ESD), river density (DEN), distance to mainstream (DIST), NDVI, annual mean rainfall (RAIN), mean annual maximum of three-day accumulated precipitation (ACC) and frequency of extreme rainfall (EXE) are selected and integrated into a GIS environment for the identification of flood-prone basins. ESF-based Poisson regression (ESFPS) can filter out the spatial autocorrelation. The methodology includes construction of a spatial weight matrix, testing of spatial autocorrelation, decomposition of eigenvectors, stepwise selection of eigenvectors and calculation of regression coefficients. Compared with the pseudo R squared obtained by PS (0.56), ESFPS exhibits better fitness with a value of 0.78, which increases by approximately 39.3%. ESFPS identifies six significant factors including ELE, DEN, EXE, DIST, ACC and NDVI, in which ACC and NDVI are the first two main factors. The method can provide decision support for flood risk relief and hydrologic station planning.

Factors influencing the incidence of bacterial dysentery in parts of southwest China, using data from the geodetector

Objective: To analyze the relationship between the incidence of bacterial dysentery and related meteorological, environmental and socio-economic factors in parts of southwest China, under the geodetector. Methods: Incidence data on bacillary dysentery from 2005 to 2014 was collected from the China infectious disease reporting system and meteorological, terrain environment and socio-economic related data were used for statistical analysis with geodetector also used, in Sichuan province, Yunnan province and the Tibet autonomous region (southwest China). Results: Through geodetector model, results showed that the elevation maximum value of power of determinant (PD) (PD=0.308), ethnicity (PD=0.260), followed by summer mean temperature, topography, elevation standard deviation, slope, population density were noticed. The maximum value of PD of summer average relative humidity, summer average precipitation, and regional GDP were all less than 0.200. In the ecological detector model, value of PD appeared significantly different from multiple factors such as summer average precipitation, regional GDP, average altitude, elevation standard deviation, slope, terrain and ethnicity (P<0.05). In the interactive detector model, after the spatial interaction, factors as: value on PD of summer average relative humidity, population density and regional GDP were larger than the value on the sum of PD of two factors with nonlinear superposition enhancing trend. Results from the risk zone detection showed that areas of moderate average summer temperature, low average precipitation, moderate average summer relative humidity, high average altitude, large elevation standard deviation, high slope, mountain topography, Tibeto-Burmese of ethnicity, low population density, low regional GDP were all related to the high incidence rates of bacterial dysentery. Conclusions: Meteorological conditions and topography environments were related to the bacterial dysentery in southwest China, socio-economic behaviors depends on the level of economic development and sanitary conditions etc. were all directing influencing the transmission and incidence of bacterial dysentery. For developing a better intervention programs on bacillary dysentery, socio-economic means should be used for the control of bacillary dysentery, in the region.

A new method of terrain self-adaptive matching algorithm for autonomous underwater vehicle

As different underwater terrain features will affect the accuracy of unscented Kalman filter terrain matching algorithm, a new terrain self-adaptive matching method is proposed which adjusts sigma point distribution by terrain features. The connection between sigma point distribution distance and three basic terrain features were analysed. Positioning error range were calculated using navigation positioning errors and underwater digital map. Terrain elevation standard deviation was used to characterize the information quantity of decision region. Scaling parameter was adjusted using linear mapping method and sigma point distribution distance was determined by terrain features. The simulation results proved better terrain adaptability and positioning precision of improved self-adaptive matching algorithm.

The Mixed Kernel Function SVM-Based Point Cloud Classification

Measurement and detection of ground information by airborne Lidar are one of the hot topics in the field of intelligent sensing in recent years. This study proposes a new point cloud classification algorithm of Mixed Kernel Function SVM to distinguish different types of ground objects. Firstly, the combined features including the coordinate values, the RGB value, normalized elevation, standard deviation of elevation, and elevation difference of point cloud data were extracted. A mixed kernel function of Gauss and Polynomial was designed. Then, one-versus-rest SVM multiple classifiers was constructed. Finally, the feature of 3D point cloud data was employed to train the SVM classifiers. The overall classification accuracies of test data were 97.69% and 99.13% for two data sets, I and II respectively. In addition, the experimental results have showed that the performance of the proposed method with mixed kernel function SVM was better than standard SVM method with Gaussian kernel function and polynomial kernel function only, which demonstrates the effectiveness of the proposed method.

The impact of road alignment characteristics on different types of traffic accidents

Among the factors affecting road traffic safety, road alignment characteristics are often ignored by people because they cause traffic accidents in an indirect way. In view of this problem, the total number of accidents, the total casualties of accidents (deaths, minor injuries, serious injuries), and the total time of road closures were chosen as road safety evaluation indices and ranked by the technique for order preference by similarity to an ideal solution (TOPSIS) method. The road sections whose ranking index value C < 0.8 were identified as accident blackspots. On this basis, the slope direction, absolute value of the elevation difference, Standard Deviation of elevation, curve radius, and transition curve ratio were chosen to describe the characteristics of road alignment. Combined with historical accident data, binary logistic regression models were established to analyze the effects of alignment factors on the frequent occurrence of three accident types (rear-end, hitting the fixture, rollover).

Flood Hazard Mapping and Assessment on the Angkor World Heritage Site, Cambodia

World Heritage sites in general are exposed to the impacts of natural hazards, which threaten their integrity and may compromise their value. Floods are a severe threat to the Angkor World Heritage site. Studies of regional floods and flood hazard zoning have played an increasingly important role in ensuring sustainability of the Angkor site. This study developed a flood hazard index (FHI) model based on a geographic information system (GIS) and used synthetic aperture radar (SAR) data to extract historical floods at Angkor from 2007 to 2013. Four indices (flood affected frequency, absolute elevation, elevation standard deviation, drainage density) were used to identify flood-prone areas. The Analytic Hierarchy Process (AHP) and the Delphi method were employed to determine the weight of each index. The weighted indices were then used to develop a distribution map of flood hazards at Angkor. The results show that 9 monuments are at risk by potential floods among the 52 components of the Angkor monuments. The high hazard and moderate-to-high hazard areas in the core zone are mainly located surrounding the West Baray but will not bring direct risk impact on the monuments located in the core archaeological zone. The moderate hazard areas are located on both sides of the Siem Reap and Roluos rivers and in the flooded area of the Tonle Sap Lake in the core archaeological zone. These areas cover 19.4 km2, accounting for 9.13% of the total area of the core zone. This moderate hazard zone poses a greater flood threat to the core zone and must be given higher attention. The buffer zone is a small area with fewer sites. As such, flooding has a low impact on the buffer zone. The methods used in this study can be applied to flood hazard assessments of other heritage sites in Southeast Asia.

Spatial structure of near-bed flow properties at the grain scale

Expanding the existing knowledge of the role of roughness on near-bed flow properties is vital to provide deeper insights into the interactions between the flow, sediment transport, morphology and ecology. This study uses four fixed beds, from both the laboratory and the field, to characterise the structure of near-bed flow properties. Dense measurements over a grid of 6 mm spacing were conducted across each cast, using an Acoustic Doppler Velocimeter. These measurements followed the line of the bed topography, with the sampling location being 2 mm away from the maximum bed elevations. Near-bed flow properties were calculated across the surface; including velocity, turbulence intensity, turbulent kinetic energy, Reynolds stress and quadrant analysis. Improved visualisation of flow properties involves contour plots of the spatial distribution of flow over the DEM of the gravel bed to facilitate attributions of flow patterns to roughness and topography. Using the standard deviation of elevations as a proxy for grain roughness of each surface, we observed that a decrease in roughness led to an increase in the average near-bed velocity. In contrast, an increase in roughness resulted in an increase in both turbulence intensity and turbulent production (TKE). Analysis of quadrant events dominating across the surface can provide indications into the potential for erosion and/or deposition across the natural mobile surfaces. Finally, second-order structure function analysis is used to quantify the spatial structure of flow properties, presenting novel isopleth maps of flow properties. For the majority of flow properties across all surfaces, the range in the spatial extent of flow structures is between 1 and 2.25 × D50A, except for transverse and vertical velocities, which have a wider range up to 3.5 × D50A.

Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks

ABSTRACTAutomated generalization software must accommodate multi-scale representations of hydrographic networks across a variety of geographic landscapes, because scale-related hydrography differences are known to vary in different physical conditions. While generalization algorithms have been tailored to specific regions and landscape conditions by several researchers in recent years, the selection and characterization of regional conditions have not been formally defined nor statistically validated. This paper undertakes a systematic classification of landscape types in the conterminous United States to spatially subset the country into workable units, in preparation for systematic tailoring of generalization workflows that preserve hydrographic characteristics. The classification is based upon elevation, standard deviation of elevation, slope, runoff, drainage and bedrock density, soil and bedrock permeability, area of inland surface water, infiltration-excess of overland flow, and a base flow index. A seven class solution shows low misclassification rates except in areas of high landscape diversity such as the Appalachians, Rocky Mountains, and Western coastal regions.

Correlation Analysis of Gradient and Elevation in Henan Province

Gradient is an important terrain factor in describing the regional topographic features from elevation and slope. Based on 30m×30m digital elevation model, this paper uses geo-statistical analysis methods to analyze the spatial distribution features of elevation, slope and gradient from the aspect of structure and proportion, and discusses the spatial correlation between gradient and elevation in Henan province, in order to provide some scientific reference for further understanding of its regional terrain. The results show that the topography of the province is dominated by low and medium altitude elevation, the elevation maximum values on longitude lines show 4 ladders, and there is a north-south wind tunnel with average maximum elevation lower than the standard mountain it located in each ladder. On the latitude lines, the elevation maximum values show 3 ladders, the wind tunnel width on the first ladder is the widest, which affects the climate change in the southeast part of the province. The topography of the province is dominated by low terrain slope, the maximum values show 3 ladders on longitude lines, 2 ladders on latitude lines, the change frequency and amplitude of the slope in the southern are significantly smaller than those in the northern part. The slope range on the latitude is extremely higher than that on the latitude. The terrain gradient shows 3 ladders with the decrease average maximums on longitude lines, the change in the second ladder is obviously higher than that in other ladders, it shows 2 ladders on latitude lines, the gradient change frequency and amplitude in the southern are significantly higher than that in the northern part. The varying curve of gradient versus the elevation varying shows a normal distribution, the extreme value appears at elevation 1000m. The gradient standard deviation in different elevation belts are always less than the elevation standard deviation. The gradient has a strong correlation with elevation in the region around 400m. There is significant positive correlation between gradient and elevation in the region above 1430m.

Autogenic influence on the morphology of submarine fans: an approach from 3D physical modelling of turbidity currents

ABSTRACT: Autogenic controls have significant influence on deep-water fans and depositional lobes morphology. In this work, we aim to investigate autogenic controls on the topography and geometry of deep-water fans. The influence of the sediment concentration of turbidity currents on deep-water fans morphology was also investigated. From the repeatability of 3D physical modeling of turbidity currents, two series of ten experiments were made, one of high-density turbidity currents (HDTC) and another of low-density turbidity currents (LDTC). All other input parameters (discharge, sediment volumetric concentration and grain size median) were kept constant. Each deposit was analyzed from qualitative and quantitative approaches and statistical analysis. In each experimental series, the variability of the morphological parameters (length, width, L/W ratio, centroid, area, topography) of the simulated deep-water fans was observed. Depositional evolution of the HDTC fans was more complex, showing four evolutionary steps and characterized by the self-channelizing of the turbidity current, while LDTC fans neither present self-channelizing, nor evolutionary steps. High disparities on the geometrical parameters of the fans, as characterized by the elevated relative standard deviation, suggest that autogenic controls induced a stochastic morphological behaviour on the simulated fans of the two experimental series.

Influence of Posture Variation on Shoulder Muscle Activity, Heart Rate, and Perceived Exertion in a Repetitive Manual Task

OCCUPATIONAL APPLICATIONS In repetitive work, more physical variation is believed to reduce the risk of eventually developing musculoskeletal disorders. We investigated the extent to which workstation designs leading to more variation in upper arm postures during a pick-and-place task influenced outcomes of relevance to musculoskeletal disorder risk, including muscle activity, cardiovascular response, and perceived exertion, measured through the maximal acceptable work pace. Posture variation to the extent obtained in our experiment had only minor effects on these outcomes, and considerably less impact than a moderate change in working height. Apparently, substantial manipulations of the workstation or of the work task will be needed to accomplish variation to an extent that can significantly change outcomes of relevance to occupational musculoskeletal disorders and, thus, represent a potential for reduction in musculoskeletal disorder risk.TECHNICAL ABSTRACT Background: Repetitive light assembly work is associated with an increased risk for developing work-related musculoskeletal disorders. More exposure variation, for instance by redesigning the workstation, has been proposed as an effective intervention. Purpose: We investigated the effect of upper arm posture variation in a 1-hour repetitive pick-and-place task on shoulder muscle activity, heart rate, and perceived exertion, measured on the Borg CR-10 scale and in terms of maximal acceptable work pace (MAWP). Methods: Thirteen healthy participants performed the task in three workstation designs where the hand was moved either horizontally (H30/30), diagonally (D20/40), or vertically (V10/50), with a mean upper arm elevation of ∼30°. In a fourth design, the hand was moved horizontally at ∼50° mean arm elevation (H50/50). Results: As intended, upper arm posture variation, measured by the upper arm elevation standard deviation and range of motion, differed between H30/30, D20/40, and V10/50. However, MAWP (10.7 cycles·min−1 on average across conditions; determined using a psychophysical approach), mean upper trapezius activity (54% reference voluntary exertion [RVE]), and heart rate (69 bpm) did not differ between these workstation designs. In H50/50, MAWP was lower (9.3 cycles·min−1), while trapezius activity (78% RVE) and perceived exertion (Borg CR-10) tended to be higher. Conclusions: Our results indicate that posture variation to the extent achieved in the current experiment leads to less effects on muscle activity and perceived exertion than a moderate change in working height.

Using UAS optical imagery and SfM photogrammetry to characterize the surface grain size of gravel bars in a braided river (Vénéon River, French Alps)

This paper explores the potential of unmanned aerial system (UAS) optical aerial imagery to characterize grain roughness and size distribution in a braided, gravel-bed river (Vénéon River, French Alps). With this aim in view, a Wolman field campaign (19 samples) and five UAS surveys were conducted over the Vénéon braided channel during summer 2015. The UAS consisted of a small quadcopter carrying a GoPro camera. Structure-from-Motion (SfM) photogrammetry was used to extract dense and accurate three-dimensional point clouds. Roughness descriptors (roughness heights, standard deviation of elevation) were computed from the SfM point clouds and were correlated with the median grain size of the Wolman samples. A strong relationship was found between UAS-SfM-derived grain roughness and Wolman grain size. The procedure employed has potential for the rapid and continuous characterization of grain size distribution in exposed bars of gravel-bed rivers. The workflow described in this paper has been successfully used to produce spatially continuous grain size information on exposed gravel bars and to explore textural changes following flow events.

DEM Fusion using a modified k-means clustering algorithm

ABSTRACTDigital elevation models (DEMs) are a necessary dataset for modelling the Earth’s surface; however, all DEMs contain error. Researchers can reduce this error using DEM fusion techniques since numerous DEMs can be available for a region. However, the use of a clustering algorithm in DEM fusion has not been previously reported. In this study a new DEM fusion algorithm based on a clustering approach that works on multiple DEMs to exploit consistency in the estimates as indicators of accuracy and precision is presented. The fusion approach includes slope and elevation thresholding, k-means clustering of the elevation estimates at each cell location, as well as filtering and smoothing of the fusion product. Corroboration of the input DEMs, and the products of each step of the fusion algorithm, with a higher accuracy reference DEM enabled a detailed analysis of the effectiveness of the DEM fusion algorithm. The main findings of the research were: the k-means clustering of the elevations reduced the precision which also impacted the overall accuracy of the estimates; the number of final cluster members and the standard deviation of elevations before clustering both had a strong relationship to the error in the k-means estimates.

A peak-cluster assessment method for the identification of upland planation surfaces

ABSTRACTResidual upland planation surfaces serve as strong evidence of peneplains during long intervals of base-level stability in the peneplanation process. Multi-stage planation surfaces could aid the calculation of uplift rates and the reconstruction of upland plateau evolution. However, most planation surfaces have been damaged by crustal uplift, tectonic deformation, and surface erosion, thus increasing the difficulty in automatically identifying residual planation surfaces. This study proposes a peak-cluster assessment method for the automatic identification of potential upland planation surfaces. It consists of two steps: peak extraction and peak-cluster characterization. Three critical parameters, namely, landform planation index (LPI), peak elevation standard deviation, and peak density, are employed to assess peak clusters. The proposed method is applied and validated in five case areas in the Tibetan Plateau using a Shuttle Radar Topography Mission digital elevation model (SRTM DEM) with 3 arc-second resolution. Results show that the proposed method can effectively extract potential planation surfaces, which are found to be stable with different resolutions of DEM data. A significant planation characteristic can be obtained in the relatively flat areas of the Gangdise–Nyainqentanglha Mountains and Qaidam Basin. Several vestiges of potential former planation areas are also extracted in the hilly-gully areas of the western part of the Himalaya Mountains, the northern part of the Tangula–Hengduan Mountains, and the northeastern part of the Kunlun–Qinling Mountains despite the absence of significant topographical features characterized by low slope angles or low terrain reliefs. Vestiges of planation surfaces are also identified in these hilly-gully upland areas. Hence, the proposed method can be effectively used to extract potential upland planation surfaces not only in flat areas but also in hilly-gully areas.

High variability of soil erosion and hydrological processes in Mediterranean hillslope vineyards (Montes de Málaga, Spain)

Conventional Mediterranean vineyards from the Montes de Málaga (Axarquía region, Spain) are characterized by high average temperatures, extreme rainfall events during autumn and winter, elevated stoniness and steep slopes (20–50°). Traditionally, several problems of high soil loss, rill and ephemeral gully generation, and elevated runoff are observed by farmers, which are increasing land degradation processes and a decrease of the productivity.According to this, the main aims of this paper were: i) to quantify the initial soil loss, surface flow and infiltration processes; ii) to characterize and describe the hydrological and geomorphological dynamics; iii) to detect the key factors, which control the soil erosion processes.For this purpose, a combined methodology was applied, using soil analysis, a small portable rainfall simulator and a Guelph permeameter on one experimental plot cultivated with vineyards with steep slopes. Results showed a high variability of soil erosion and permeability processes. Soil analysis showed an elevated concentration of silt particles and stoniness, with higher contents of sand particles between 0 and 5cm, and clays from 5cm. With a Guelph permeameter, high average of permeability and saturated hydraulic conductivity with elevated standard deviation were observed. Furthermore, an increase of these parameters from the upper to the foot slope was registered. By using rainfall simulations, on the upper and the foot slope positions the highest runoff coefficient and soil loss were registered. The most elevated peak of sediment concentration was obtained on the middle slope. In general, high infiltration coefficients between 66.5 and 100% were observed.In conclusion it was observed that the activation of the soil erosion processes was due to the distribution of the surface soil components (high roughness, several cracks and high stoniness and silt content), the steep slopes and the impact of the soil traditional tillage practices. These Mediterranean hillslope vineyards registered a mixed Hortonian-Hewlettian model, which combines surface and sub-surface flow conditioned by the micro-topographical changes and its saturation degree.

Reduced pH affects pulsing behaviour and body size in ephyrae of the moon jellyfish, Aurelia aurita

Our understanding of how reduced seawater pH affects the behaviour and growth of scyphozoan jellyfish is poor. Here, we investigated the effects of simulated Ocean Acidification (OA) (pH=7.6 for 7d) on pulsing behaviour (as an index of swimming behaviour) and aspects of the morphology of ephyrae of the moon jellyfish Aurelia aurita. Ephyrae exposed to reduced pH had a significantly smaller surface area, central disc area, and lappet length and width than controls. Pulsation rate was significantly lower, and the mean pulse-to-pulse period shorter, in the reduced pH treatment. There was, however, no significant treatment effect on either the maximum or minimum pulse-to-pulse period, suggesting that the ability for rapid pulsations was maintained. Ephyrae from the reduced pH treatment displayed a more variable pulsation behaviour, with an elevated standard deviation and root mean square of successive difference (RMSSD) in pulse-to-pulse period. In summary, reduced pH simulating future predicted Ocean Acidification conditions, had important effects on aspects of swimming behaviour and size of A. aurita ephyra, which may have consequences for survival and the population dynamics of field populations.

Modelling the Northward Expansion of Culicoides sonorensis (Diptera: Ceratopogonidae) under Future Climate Scenarios.

Climate change is affecting the distribution of pathogens and their arthropod vectors worldwide, particularly at northern latitudes. The distribution of Culicoides sonorensis (Diptera: Ceratopogonidae) plays a key role in affecting the emergence and spread of significant vector borne diseases such as Bluetongue (BT) and Epizootic Hemorrhagic Disease (EHD) at the border between USA and Canada. We used 50 presence points for C. sonorensis collected in Montana (USA) and south-central Alberta (Canada) between 2002 and 2012, together with monthly climatic and environmental predictors to develop a series of alternative maximum entropy distribution models. The best distribution model under current climatic conditions was selected through the Akaike Information Criterion, and included four predictors: Vapour Pressure Deficit of July, standard deviation of Elevation, Land Cover and mean Precipitation of May. This model was then projected into three climate change scenarios adopted by the IPCC in its 5th assessment report and defined as Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5. Climate change data for each predictor and each RCP were calculated for two time points pooling decadal data around each one of them: 2030 (2021–2040) and 2050 (2041–2060). Our projections showed that the areas predicted to be at moderate-high probability of C. sonorensis occurrence would increase from the baseline scenario to 2030 and from 2030 to 2050 for each RCP. The projection also indicated that the current northern limit of C. sonorensis distribution is expected to move northwards to above 53°N. This may indicate an increased risk of Culicoides-borne diseases occurrence over the next decades, particularly at the USA-Canada border, as a result of changes which favor C. sonorensis presence when associated to other factors (i.e. host and pathogen factors). Recent observations of EHD outbreaks in northern Montana and southern Alberta supported our projections and considerations. The results of this study can inform the development of cost effective surveillance programs, targeting areas within the predicted limits of C. sonorensis geographical occurrence under current and future climatic conditions.