scholarly journals Spatio-Temporal Model for Predicting Spring Hatch of the Spotted Lanternfly (Hemiptera: Fulgoridae)

2020 ◽  
Author(s):  
Erica C Smyers ◽  
Julie M Urban ◽  
Andrew C Dechaine ◽  
Douglas G Pfeiffer ◽  
Stephen R Crawford ◽  
...  
Keyword(s):  
Logistic Models ◽  
Effect Of Temperature ◽  
Temperature Threshold ◽  
Data Sets ◽  
Base Temperature ◽  
Combined Model ◽  
Egg Development ◽  
Developmental Duration ◽  
Egg Hatch ◽  
Spatio Temporal

Abstract The effect of temperature on the rate of spotted lanternfly, Lycorma delicatula (White) (Hemiptera: Fulgoridae), egg development was investigated for a population in Pennsylvania. Mean developmental duration (days ± SE) for egg hatch was evaluated at five constant temperatures of 19.9, 24.2, 25.1, 26.7, and 30°C using egg masses laid during the fall of 2018 and collected in 2019 from Berks Co., Pennsylvania. Base temperature thresholds for egg development were estimated using intercept and slope parameters by fitting a linear relationship between average temperature and developmental rate for the Pennsylvania study, two Korean studies, and the combined data sets. The base threshold estimates were then used to calculate seasonal accumulated degree-days (ADD) and construct logistic equations for predicting cumulative proportion of hatch in the spring. The fitted logistic prediction equations were then graphed against the egg hatch observations from field sites in Pennsylvania (2017) and Virginia (2019). When base temperature estimates from the three studies and combined studies were used to calculate ADD, the logistic models predicted similar timing for seasonal egg hatch. Because the slopes and intercepts for these four data sets were not statistically different, a base temperature threshold of 10.4°C derived from the combined model is a good estimate for computing ADD to predict spotted lanternfly spring emergence across a spatio-temporal scale. The combined model was linked with open source weather database and mapping programs to provide spatiotemporal prediction maps to aid pest surveillance and management efforts for spotted lanternfly.

A TEMPERATURE-DEPENDENT MODEL OF EGG DEVELOPMENT OF THE WESTERN CORN ROOTWORM, DIABROTICA VIRGIFERA VIRGIFERA LECONTE (COLEOPTERA: CHRYSOMELIDAE)

1991 ◽  
Vol 123 (6) ◽  
pp. 1183-1197 ◽  
Author(s):  
A.W. Schaafsma ◽  
G.H. Whitfield ◽  
C.R. Ellis
Keyword(s):  
Simulation Model ◽  
Diabrotica Virgifera Virgifera ◽  
Base Temperature ◽  
Diabrotica Virgifera ◽  
Degree Days ◽  
Egg Development ◽  
Egg Hatch ◽  
Developmental Threshold ◽  
Soil Temperatures ◽  
Developmental Rates

AbstractDevelopmental rates of post-diapause eggs of Diabrotica virgifera virgifera LeConte were compared in the laboratory at six constant temperatures, 12, 16, 20, 24, 28, and 32°C. Linear and nonlinear models were fitted to temperature versus developmental data and were used to predict egg hatch in the field. A four-parameter model fitted to median developmental rates (r2 = 0.99) indicated that development was linear between 16 and 28°C, optimal at 28°C, and decreased at 32°C. The lower development threshold (± SE) (10.5 ± 0.1°C) was determined by linear regression and the x-intercept method. Completion of post-diapause egg development required 258 ± 3 degree-days (± SE) above the base temperature. This compared well with the mean degree-days accumulated to 50% hatch (± SE) of 265 ± 24 which we observed in the field at several locations over 3 years using a degree-day model incorporating an 11°C developmental threshold and soil temperatures at 5- and 10-cm depths. A stochastic simulation model, incorporating a nonlinear developmental function dependant on soil temperatures taken every 2 h also predicted 50% hatch within 2 days. This model was validated in the field with 19 independent records of soil temperatures for several locations at two depths in the soil over 3 years. The simulation model accurately predicted time of 5 and 95% hatch, which indicates that this model has broad application in predicting the pattern of egg hatch for pest management.

scholarly journals Spatio-Temporal Variation Characteristics of Snow Depth and Snow Cover Days over the Tibetan Plateau

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 307
Author(s):  
Chi Zhang ◽  
Naixia Mou ◽  
Jiqiang Niu ◽  
Lingxian Zhang ◽  
Feng Liu
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Snow Depth ◽  
Feedback Effect ◽  
Effect Of Temperature ◽  
The Tibetan Plateau ◽  
Reanalysis Dataset ◽  
Spatio Temporal ◽  
The Impact ◽  
Main Factor

Changes in snow cover over the Tibetan Plateau (TP) have a significant impact on agriculture, hydrology, and ecological environment of surrounding areas. This study investigates the spatio-temporal pattern of snow depth (SD) and snow cover days (SCD), as well as the impact of temperature and precipitation on snow cover over TP from 1979 to 2018 by using the ERA5 reanalysis dataset, and uses the Mann–Kendall test for significance. The results indicate that (1) the average annual SD and SCD in the southern and western edge areas of TP are relatively high, reaching 10 cm and 120 d or more, respectively. (2) In the past 40 years, SD (s = 0.04 cm decade−1, p = 0.81) and SCD (s = −2.3 d decade−1, p = 0.10) over TP did not change significantly. (3) The positive feedback effect of precipitation is the main factor affecting SD, while the negative feedback effect of temperature is the main factor affecting SCD. This study improves the understanding of snow cover change and is conducive to the further study of climate change on TP.

A unified degree day model describes survivorship of Copitarsia corruda Pogue & Simmons (Lepidoptera: Noctuidae) at different constant temperatures

2008 ◽  
Vol 99 (1) ◽  
pp. 65-72 ◽  
Author(s):  
N.N. Gómez ◽  
R.C. Venette ◽  
J.R. Gould ◽  
D.F. Winograd
Keyword(s):  
Survival Curve ◽  
The United States ◽  
Physiological Age ◽  
Alien Invasive Species ◽  
Temperature Threshold ◽  
Base Temperature ◽  
Survival Curves ◽  
Degree Day ◽  
Effects Of Temperature ◽  
Lepidoptera Noctuidae

AbstractPredictions of survivorship are critical to quantify the probability of establishment by an alien invasive species, but survival curves rarely distinguish between the effects of temperature on development versus senescence. We report chronological and physiological age-based survival curves for a potentially invasive noctuid, recently described as Copitarsia corruda Pogue & Simmons, collected from Peru and reared on asparagus at six constant temperatures between 9.7 and 34.5°C. Copitarsia spp. are not known to occur in the United States but are routinely intercepted at ports of entry. Chronological age survival curves differ significantly among temperatures. Survivorship at early age after hatch is greatest at lower temperatures and declines as temperature increases. Mean longevity was 220 (±13 SEM) days at 9.7°C. Physiological age survival curves constructed with developmental base temperature (7.2°C) did not correspond to those constructed with a senescence base temperature (5.9°C). A single degree day survival curve with an appropriate temperature threshold based on senescence adequately describes survivorship under non-stress temperature conditions (5.9–24.9°C).

scholarly journals Historical drought patterns over Canada and their teleconnections with large-scale climate signals

2018 ◽  
Vol 22 (6) ◽  
pp. 3105-3124 ◽  
Author(s):  
Zilefac Elvis Asong ◽  
Howard Simon Wheater ◽  
Barrie Bonsal ◽  
Saman Razavi ◽  
Sopan Kurkute
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Low Frequency ◽  
Kendall Test ◽  
Wavelet Coherence ◽  
Climate Indices ◽  
Data Sets ◽  
Canadian Prairies ◽  
Agriculture Industry ◽  
Spatio Temporal

Abstract. Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950–2013. The Mann–Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified – the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific–North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.

Use of Functional Response Modeling to Evaluate the Effect of Temperature on Predation of Amblyseius swirskii (Acari: Phytoseiidae) Adults Preying on Tetranychus urticae (Acari: Tetranychidae) Nymphs

2021 ◽  
Author(s):  
Azadeh Farazmand ◽  
Masood Amir-Maafi
Keyword(s):  
Functional Response ◽  
Tetranychus Urticae ◽  
Attack Rate ◽  
Handling Time ◽  
Effect Of Temperature ◽  
Coefficient Of Determination ◽  
Temperature Threshold ◽  
Amblyseius Swirskii ◽  
Functional Responses ◽  
Wide Range

Abstract In this research, functional responses of Amblyseius swirskii Athias-Henriot preying on different Tetranychus urticae Koch nymphal densities (2, 4, 8, 16, 32, 64, and 128) were studied at eight constant temperatures (15, 20, 25, 27.5, 30, 32.5, 35 and 37.5°C) in a circular Petri dish (3-cm diameter × 1-cm height) under lab conditions. At all temperatures, the logistic regression showed a type II functional response. A nonlinear relationship was found between temperature and attack rate and the reciprocal of handling time. The reciprocal of handling time decreased exponentially with increasing temperature. In contrast, the attack rate grew rapidly with increasing temperatures up to an optimum, showing a decreasing trend at higher temperatures. In order to quantify the functional response of A. swirskii over a broad range of temperatures and to gain a better estimation of attack rate and handling time, a temperature-settled functional response equation was suited to our data. Our model showed that the number of prey consumed increased with rising prey density. Also, the predation rates increased with increasing temperatures but decreased at extremely high temperatures. Based on our model, the predation rate begins at the lower temperature threshold (11.73°C) and reaches its peak at upper temperature threshold (29.43°C). The coefficient of determination (R2) of the random predator model was 0.99 for all temperatures. The capability of A. swirskii to search and consume T. urticae over a wide range of temperatures makes it a good agent for natural control of T. urticae in greenhouses.

scholarly journals MULTIVARIATE MATHEMATICAL MORPHOLOGY FOR DCE-MRI IMAGE ANALYSIS IN ANGIOGENESIS STUDIES

2014 ◽  
Vol 34 (1) ◽  
pp. 1 ◽  
Author(s):  
Guillaume Noyel ◽  
Jesus Angulo ◽  
Dominique Jeulin ◽  
Daniel Balvay ◽  
Charles-André Cuenod
Keyword(s):  
Noise Reduction ◽  
Data Sets ◽  
Computer Aided Detection ◽  
Segmentation Method ◽  
Temporal Segmentation ◽  
Dce Mri ◽  
Contrast Enhanced ◽  
Key Points ◽  
Multivariate Images ◽  
Spatio Temporal

We propose a new computer aided detection framework for tumours acquired on DCE-MRI (Dynamic Contrast Enhanced Magnetic Resonance Imaging) series on small animals. To perform this approach, we consider DCE-MRI series as multivariate images. A full multivariate segmentation method based on dimensionality reduction, noise filtering, supervised classification and stochastic watershed is explained and tested on several data sets. The two main key-points introduced in this paper are noise reduction preserving contours and spatio temporal segmentation by stochastic watershed. Noise reduction is performed in a special way to select factorial axes of Factor Correspondence Analysis in order to preserves contours. Then a spatio-temporal approach based on stochastic watershed is used to segment tumours. The results obtained are in accordance with the diagnosis of the medical doctors.

scholarly journals Determinants of SARS-CoV-2 transmission to guide vaccination strategy in a city

2020 ◽  
Author(s):  
Sarah C. Brüningk ◽  
Juliane Klatt ◽  
Madlen Stange ◽  
Alfredo Mari ◽  
Myrta Brunner ◽  
...  
Keyword(s):  
Vaccination Strategy ◽  
Population Level ◽  
Data Sets ◽  
Epidemic Dynamics ◽  
Modelling Analysis ◽  
City Population ◽  
Senior Population ◽  
Spatio Temporal ◽  
Socioeconomic Data ◽  
The City

Transmission chains within cities provide an important contribution to case burden and economic impact during the ongoing COVID-19 pandemic, and should be a major focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of SARS-CoV-2 transmission in a medium-sized European city. We combined detailed epidemiological, mobility, and socioeconomic data-sets with whole genome sequencing during the first SARS-CoV-2 wave. Both phylogenetic clustering and compartmental modelling analysis were performed based on the dominating viral variant (B.1-C15324T; 60% of all cases). Here we show that transmissions on the city population level are driven by the socioeconomically weaker and highly mobile groups. Simulated vaccination scenarios showed that vaccination of a third of the population at 90% efficacy prioritising the latter groups would induce a stronger preventive effect compared to vaccinating exclusively senior population groups first. Our analysis accounts for both social interaction and mobility on the basis of molecularly related cases, thereby providing high confidence estimates of the underlying epidemic dynamics that may readily be translatable to other municipal areas.

scholarly journals INTERESTING SPATIO-TEMPORAL REGION DISCOVERY COMPUTATIONS OVER GPU AND MAPREDUCE PLATFORMS

2015 ◽  
Vol II-4/W2 ◽  
pp. 35-41 ◽  
Author(s):  
M. McDermott ◽  
S. K. Prasad ◽  
S. Shekhar ◽  
X. Zhou
Keyword(s):  
Parallel Architecture ◽  
Computation Time ◽  
Data Sets ◽  
Temporal Region ◽  
Data Set ◽  
Atmospheric Sciences ◽  
3 Dimensional ◽  
Linear Speedup ◽  
Spatio Temporal ◽  
Mapreduce Model

Discovery of interesting paths and regions in spatio-temporal data sets is important to many fields such as the earth and atmospheric sciences, GIS, public safety and public health both as a goal and as a preliminary step in a larger series of computations. This discovery is usually an exhaustive procedure that quickly becomes extremely time consuming to perform using traditional paradigms and hardware and given the rapidly growing sizes of today’s data sets is quickly outpacing the speed at which computational capacity is growing. In our previous work (Prasad et al., 2013a) we achieved a 50 times speedup over sequential using a single GPU. We were able to achieve near linear speedup over this result on interesting path discovery by using Apache Hadoop to distribute the workload across multiple GPU nodes. Leveraging the parallel architecture of GPUs we were able to drastically reduce the computation time of a 3-dimensional spatio-temporal interest region search on a single tile of normalized difference vegetative index for Saudi Arabia. We were further able to see an almost linear speedup in compute performance by distributing this workload across several GPUs with a simple MapReduce model. This increases the speed of processing 10 fold over the comparable sequential while simultaneously increasing the amount of data being processed by 384 fold. This allowed us to process the entirety of the selected data set instead of a constrained window.

scholarly journals CLUSTER–STAFF search coil magnetometer calibration – comparisons with FGM

2014 ◽  
Vol 3 (2) ◽  
pp. 153-177 ◽  
Author(s):  
P. Robert ◽  
N. Cornilleau-Wehrlin ◽  
R. Piberne ◽  
Y. de Conchy ◽  
C. Lacombe ◽  
...  
Keyword(s):  
Transfer Functions ◽  
Low Frequency ◽  
Temporal Analysis ◽  
Fluxgate Magnetometer ◽  
Data Sets ◽  
Spectral Matrix ◽  
Spatio Temporal ◽  
Cross Calibration ◽  
The Waves ◽  
The Way

Abstract. The main part of the Cluster Spatio-Temporal Analysis of Field Fluctuations (STAFF) experiment consists of triaxial search coils allowing the measurements of the three magnetic components of the waves from 0.1 Hz up to 4 kHz. Two sets of data are produced, one by a module to filter and transmit the corresponding waveform up to either 10 or 180 Hz (STAFF-SC), and the second by the onboard Spectrum Analyser (STAFF-SA) to compute the elements of the spectral matrix for five components of the waves, 3 × B and 2 × E (from the EFW experiment), in the frequency range 8 Hz to 4 kHz. In order to understand the way the output signals of the search coils are calibrated, the transfer functions of the different parts of the instrument are described as well as the way to transform telemetry data into physical units across various coordinate systems from the spinning sensors to a fixed and known frame. The instrument sensitivity is discussed. Cross-calibration inside STAFF (SC and SA) is presented. Results of cross-calibration between the STAFF search coils and the Cluster Fluxgate Magnetometer (FGM) data are discussed. It is shown that these cross-calibrations lead to an agreement between both data sets at low frequency within a 2% error. By means of statistics done over 10 yr, it is shown that the functionalities and characteristics of both instruments have not changed during this period.

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