scholarly journals Complementary Contribution of Wild Bumblebees and Managed Honeybee to the Pollination Niche of an Introduced Blueberry Crop

Insects ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 595
Author(s):  
Marcos Miñarro ◽  
Daniel García
Keyword(s):  
Weather Conditions ◽  
Phenotypic Traits ◽  
Crop Pollination ◽  
Northern Spain ◽  
Vaccinium Ashei ◽  
Visitation Rate ◽  
Spatio Temporal ◽  
Pollinator Assemblage ◽  
Pollination Strategy ◽  
Environmental Tolerances

The entomophilous pollination niche (abundance, phenotypic traits, foraging behaviours and environmental tolerances of insect pollinators) helps to understand and better manage crop pollination. We apply this niche approach to assess how an entomophilous crop (blueberry, Vaccinium ashei) can be expanded into new territories (i.e., northern Spain) far from their original area of domestication (North America). Insect visits to blueberry flowers were monitored in a plantation on 12 different days, at 8 different times during day and covering various weather conditions. Abundance, visitation rate, pollen gathering behaviour, and frequency of inter-plant and inter-row movements were recorded. The pollinator assemblage was basically composed of one managed honeybee species (50.8% of visits) and three native bumblebee species (48.3%). There was a marked pattern of seasonal segregation throughout bloom, with bumblebees dominating the early bloom and honeybee the late bloom. Pollinators also segregated along gradients of daily temperature and relative humidity. Finally, the two pollinator types differed in foraging behaviour, with bumblebees having a visitation rate double that of honeybee, collecting pollen more frequently and changing plant and row more frequently. The spatio-temporal and functional complementarity between honeybee and bumblebees suggested here encourages the consideration of an integrated crop pollination strategy for blueberries, based on the concurrence of both wild and managed bees.

scholarly journals Rainfall and weather conditions inducing intense landslide activity in northern Spain (Deba, Guipúzcoa)

2020 ◽  
Author(s):  
Victoria Rivas ◽  
Juan Remondo ◽  
Jaime Bonachea ◽  
Javier Sánchez-Espeso
Keyword(s):  
Weather Conditions ◽  
Rainfall Threshold ◽  
Large Network ◽  
Antecedent Rainfall ◽  
Northern Spain ◽  
Rainfall Events ◽  
Landslide Activity ◽  
Long Time ◽  
Span 60

Abstract. The Deba area is intensely affected by frequent shallow landslides triggered by rainfall. Relationships between rainfall and landslides in northern Spain, particularly for rainfall events driving multiple movements simultaneously, have not been explored in depth so far. This contribution explores the role of rainfall in landslide activity during a quite long time span, (60 years), from a large network of rainfall gauges and a complete inventory of landslides, and utilizing three different strategies of analysis. 1,180 landslides have been inventoried, and 3,241 rainfall episodes automatically recognized and characterized in terms of rainfall amount, duration and intensity. Antecedent rainfall has also been considered. Six episodes of intense rainfall, which have produced multiple landslides (> 50 % of the recent past occurrences) have been identified. The analysis provides different results: the extraordinary character of the triggering rainfall has been assessed, the meteorological conditions associated to those extreme episodes have been recognized and empirical rainfall threshold producing multiple landslides has been found (I = 7.7D-0.428) and compared with others described in literature. Results show that multiple landslide occurrences are triggered by extreme convective rainfall, intense, short and with limited horizontal extent, as well as a marked summer-autumn seasonality, characteristic of Mediterranean climate.

scholarly journals Variability and correlations of economically valuable traits in cowpea from the VIR collection in the environments of Astrakhan provincer

2019 ◽  
Vol 180 (1) ◽  
pp. 59-65
Author(s):  
M. V. Gurkina
Keyword(s):  
Seed Weight ◽  
Weather Conditions ◽  
Seed Maturation ◽  
Stem Length ◽  
Phenotypic Traits ◽  
Mean Values ◽  
Agricultural Produce ◽  
Economically Valuable Traits ◽  
Early Ripening ◽  
Number Of Seeds

Background. The problem of a deficit in vegetable protein and the need to diversify agricultural produce require involvement of new and little-known crops, such as cowpea, in the production. Cowpea (Vigna unguiculata (L.) Walp.) is a high-protein leguminous crop; its breeding and production have been intensified in Russia only in recent years. The study of the VIR collection, carried out at the Institute’s branch in Astrakhan, makes it possible to disclose the crop’s breeding potential. Objective: Studying the range of variability and tracing the relationships of economically valuable traits in vegetable (green pod) cowpea under the conditions of Astrakhan Province.Materials and methods. In 2008‑2010, a study was implemented at an experiment plot of the Astrakhan branch of VIR. Thirty- three accessions of green pod cowpea from the VIR collection were studied to analyze the variability of 12 phenotypic traits. Positive and negative correlations were identified between the following characters: interphase periods (flowering, industrial ripeness and seed maturation), shape of the shrub, lengths of the stem and to the first pod, length and weight of the pod, number of seeds per pod, presence of a parchment layer and fiber in pod valves, pod yield per plant, number of pods and peduncles, seed weight per plant, and weight of 1000 seeds.Results and conclusion. Medium variability was observed for such characters as the interphase periods ‘shoots–industrial ripeness’ and ‘shoots– seed maturation’, number of seeds per pod, and weight of 1000 seeds: the coefficient of variation (CV) was 15‑18%. High variation was registered for the length and weight of the pod (CV = 26‑32%), shrub shape, stem length, and length of the stem up to the first pod (CV = 35‑37%). The widest ranges of variability were demonstrated in the quantitative yield characters of cowpea accessions: number of pods per plant (CV = 33‑49%), number of flower stalks (CV = 38‑51%), and seed weight per plant (CV = 38‑44%), which means that cowpea yield is quite susceptible to weather conditions. During the three years of studying, the lowest levels of variability in economically valuable traits were characteristic of the accessions of the early-ripening group: k‑668 and k‑873 (China); mid- ripening group: k‑971 (India); and late-ripening group: k‑141 (China). Cowpea pod productivity depended to the greatest degree from mean values of the number of pods per plant (r = 0,73) and the number of peduncles (r = 0,71). The identified correlations in the productivity components make it possible to optimize the selection of accessions promising as source materials for the development of new high-yielding cultivars.

Spatio-temporal variations of caddisfly assemblages in a chalk stream, Balaton Upland, Hungary

Zoosymposia ◽  
2011 ◽  
Vol 5 (1) ◽  
pp. 439-452
Author(s):  
ILDIKÓ SZIVÁK ◽  
ARNOLD MÓRA ◽  
JÚLIA KATALIN TÖRÖK
Keyword(s):  
Indicator Species ◽  
Cold Water ◽  
Human Impacts ◽  
Temporal Structure ◽  
Temporal Distribution ◽  
Weather Conditions ◽  
Temporal Variations ◽  
Aquatic Habitats ◽  
Indicator Value ◽  
Spatio Temporal

In 2006–2007 larval caddisfly assemblages of a semi-natural calcareous stream (Örvényesi Creek) were studied. Characteristic sections can be detected along the whole length of the stream, which passes through diverse types of vegetation, resulting in highly heterogeneous aquatic habitats. Based on an annual survey of different aquatic habitats, our aims were to give an overview of the spatio-temporal distribution of the larval caddisfly assemblages in the Örvényesi Creek and to find indicator species characterizing different sections of the stream. In order to show the spatio-temporal patterns, samples were collected at 7 locations with different streambed morphology, from spring to the mouth of the stream. Caddisfly larvae were collected in every 3rd week during a 1 year period using the “kick and sweep” method. Multivariate analyses were carried out to explore the spatio-temporal structure of caddisfly assemblages. The indicator value method was applied to detect indicator species for different sections of the stream. A rich caddisfly fauna (20 taxa) was found in the Örvényesi Creek. Fast-running and relatively cold-water hypocrenal sections were characterized by Beraea maurus and Apatania muliebris at high indicator value. Three Limnephilidae species (Limnephilus rhombicus, Limnephilus lunatus and Glyphotaelius pellucidus) were identified as significant indicator species for slow flowing, lentic habitats. Along the length of the stream, distinctive spatial and temporal changes were detected in the distribution of the caddisfly assemblages. These changes were mainly connected to variations in morphology of the streambed, phenology of individual taxa, extreme weather conditions and human impacts.

scholarly journals Automated location of active fire perimeters in aerial infrared imaging using unsupervised edge detectors

2018 ◽  
Vol 27 (4) ◽  
pp. 241 ◽  
Author(s):  
M. M. Valero ◽  
O. Rios ◽  
E. Pastor ◽  
E. Planas
Keyword(s):  
Forest Fires ◽  
Large Scale ◽  
Infrared Imaging ◽  
Weather Conditions ◽  
Automated System ◽  
Rate Of Spread ◽  
Active Fire ◽  
Edge Detectors ◽  
Spatio Temporal ◽  
Manual Tasks

A variety of remote sensing techniques have been applied to forest fires. However, there is at present no system capable of monitoring an active fire precisely in a totally automated manner. Spaceborne sensors show too coarse spatio-temporal resolutions and all previous studies that extracted fire properties from infrared aerial imagery incorporated manual tasks within the image processing workflow. As a contribution to this topic, this paper presents an algorithm to automatically locate the fuel burning interface of an active wildfire in georeferenced aerial thermal infrared (TIR) imagery. An unsupervised edge detector, built upon the Canny method, was accompanied by the necessary modules for the extraction of line coordinates and the location of the total burned perimeter. The system was validated in different scenarios ranging from laboratory tests to large-scale experimental burns performed under extreme weather conditions. Output accuracy was computed through three common similarity indices and proved acceptable. Computing times were below 1 s per image on average. The produced information was used to measure the temporal evolution of the fire perimeter and automatically generate rate of spread (ROS) fields. Information products were easily exported to standard Geographic Information Systems (GIS), such as GoogleEarth and QGIS. Therefore, this work contributes towards the development of an affordable and totally automated system for operational wildfire surveillance.

Temporal dynamics of emergence and dispersal of garter snakes from a communal den in Manitoba

2006 ◽  
Vol 33 (2) ◽  
pp. 103 ◽  
Author(s):  
R. Shine ◽  
T. Langkilde ◽  
M. Wall ◽  
R. T. Mason
Keyword(s):  
Body Condition ◽  
Temporal Dynamics ◽  
Weather Conditions ◽  
Phenotypic Traits ◽  
Behavioural Ecology ◽  
Adult Males ◽  
Garter Snakes ◽  
Temporal And Spatial Variation ◽  
Canadian Prairies ◽  
Temporal And Spatial

Although garter snakes at communal overwintering dens on the Canadian prairies have attracted considerable behavioural ecology research, previous studies have relied upon sampling of active animals to describe broad patterns of distribution and abundance of snakes within the den population. We conducted a mark–recapture study to directly quantify temporal and spatial variation in the phenotypic traits (sex, size, body condition) of snakes at the den itself, and those dispersing through woodland 50 m away. Captures of 909 snakes on the days they emerged, and 6653 snakes as they dispersed, revealed massive spatiotemporal heterogeneity in phenotypic traits among samples. Day-to-day variation in weather conditions affected numbers and sex ratios of emerging and dispersing snakes; for example, small females dispersed in greater numbers after unusually cold nights, when harassment by courting males was reduced. Most snakes stayed at the den only briefly (<5 days) prior to dispersal, so that sampling at the den itself (the only evidence available from most previous studies) underestimates the number of animals in the population, as well as the proportions of females, of small adult males and of juvenile animals. Overall, the heterogeneous and temporally dynamic distributions of phenotypic traits (such as sex and size) among our samples are predictable on the basis of the central roles of male–male competition and sexual conflict in the mating system of these snakes. Surprisingly, however, many of the snakes that overwinter at this den play no part in den-based breeding aggregations

scholarly journals Spatio-Temporal Correlates of Gene Expression and Cortical Morphology across Life Course and Aging

2020 ◽  
Author(s):  
Anqi Qiu ◽  
Han Zhang ◽  
Brian K. Kennedy ◽  
Annie Lee
Keyword(s):  
Gene Expression ◽  
Life Course ◽  
Signaling Pathway ◽  
Brain Aging ◽  
Phenotypic Traits ◽  
Signal Pathways ◽  
Biological Mechanisms ◽  
Spatio Temporal ◽  
Development And Aging ◽  
The Life Course

AbstractEvidence from independent neuroimaging and genetic studies supports the concept that brain aging mirrors development. However, it is unclear whether mechanisms linking brain development and aging provide new insights to delay aging and potentially reverse it. This study determined biological mechanisms and phenotypic traits underpinning brain alterations across the life course and in aging by examining spatio-temporal correlations between gene expression and cortical volumes (n=3391) derived from the life course dataset (3-82 years) and the aging dataset (55-82 years). We revealed that a large proportion of genes whose expression was associated with cortical volume across the life course were in astrocytes. These genes, which showed up-regulation during development and down-regulation during aging, contributed to fundamental homeostatic functions of astrocytes crucial, in turn, for neuronal functions. Included among these genes were those encoding components of cAMP and Ras signal pathways, as well as retrograde endocannabinoid signaling. Genes associated with cortical volumes in the aging dataset were also enriched for the sphingolipid signaling pathway, renin-angiotensin system (RAS), proteasome, and TGF-beta signaling pathway, which is linked to the senescence-associated secretory phenotype. Neuroticism, drinking, and smoking were the common phenotypic traits in the life course and aging, while memory was the unique phenotype associated with aging. These findings provide biological mechanisms and phenotypic traits mirroring development and aging as well as unique to aging.

Deep Spatio-temporal Adaptive 3D Convolutional Neural Networks for Traffic Flow Prediction

2022 ◽  
Vol 13 (2) ◽  
pp. 1-21
Author(s):  
He Li ◽  
Xuejiao Li ◽  
Liangcai Su ◽  
Duo Jin ◽  
Jianbin Huang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Intelligent Transportation System ◽  
Historical Data ◽  
Temporal Correlation ◽  
Weather Conditions ◽  
External Factors ◽  
Traffic Flow Prediction ◽  
Flow Prediction ◽  
Spatio Temporal ◽  
The Impact

Traffic flow prediction is the upstream problem of path planning, intelligent transportation system, and other tasks. Many studies have been carried out on the traffic flow prediction of the spatio-temporal network, but the effects of spatio-temporal flexibility (historical data of the same type of time intervals in the same location will change flexibly) and spatio-temporal correlation (different road conditions have different effects at different times) have not been considered at the same time. We propose the Deep Spatio-temporal Adaptive 3D Convolution Neural Network (ST-A3DNet), which is a new scheme to solve both spatio-temporal correlation and flexibility, and consider spatio-temporal complexity (complex external factors, such as weather and holidays). Different from other traffic forecasting models, ST-A3DNet captures the spatio-temporal relationship at the same time through the Adaptive 3D convolution module, assigns different weights flexibly according to the influence of historical data, and obtains the impact of external factors on the flow through the ex-mask module. Considering the holidays and weather conditions, we train our model for experiments in Xi’an and Chengdu. We evaluate the ST-A3DNet and the results show that we have better results than the other 11 baselines.

Using Webcam Video Feed to Measure and Evaluate National Park Recreation Patterns

2020 ◽  
Author(s):  
Emily Schill Gray ◽  
Jocelyn Wikle
Keyword(s):  
Data Collection ◽  
New Technologies ◽  
Cost Effective ◽  
Weather Conditions ◽  
Travel Costs ◽  
Live Feeds ◽  
Video Feed ◽  
Spatio Temporal ◽  
Conducting Research ◽  
Data Collection Technique

Park managers and researchers have increasingly sought new approaches for data collection to understand recreation patterns and experiences in a more sophisticated and holistic manner. Traditional methods of monitoring visitors through on-site observation and surveys can be time consuming, expensive, and prone to error, and park managers recognize the value of new technologies in providing reliable and cost-effective visitor monitoring programs that achieve a balance between precision, accuracy, and efficiency. Live webcam video feeds are becoming increasingly available online and provide an opportunity to monitor aspects of recreation that have previously been difficult to measure. Additionally, webcam monitoring, which can be done remotely, provides a cost-effective alternative to on-site data collection because it eliminates the need for travel costs and on-site personnel. The purpose of this study is to provide a methodological investigation of extracting recreation data from webcams to introduce park managers and leisure researchers to this new data collection technique. We provide a typology for the types of questions this method can address, carefully document an approach for conducting research with webcam video feeds, and provide a proof-of-principle through presenting a case study. Taken together, we demonstrate that an online approach using webcam footage for recreation research is feasible and viable. This research has broad applications in recreation contexts, allowing the study of detailed spatio-temporal recreation patterns, visit volumes, user heterogeneity, and large tour tracking. Webcam information can also be combined with relevant data on weather conditions, air quality, gas prices, or other conditions to learn about factors shaping the timing of recreation experiences. This study has implications for park and recreation managers, who make decisions about facilitating or hindering the use of webcams at their sites through their attention to expanding or contracting the supply of webcams on public lands, positioning cameras, and maintaining live feeds. Decisions made by park staff about webcams should not only consider the impacts of webcams on enhancing user experience, but also consider their use as a tool to monitor recreation patterns by park personnel and by leisure and tourism researchers more broadly.

scholarly journals Simulating the effects of weather and climate on large wildfires in France

2018 ◽  
Author(s):  
Renaud Barbero ◽  
Thomas Curt ◽  
Anne Ganteaume ◽  
Eric Maillé ◽  
Marielle Jappiot ◽  
...  
Keyword(s):  
Linear Models ◽  
Weather Conditions ◽  
Historical Period ◽  
Natural Ecosystem ◽  
Atmospheric Variability ◽  
Modeling Framework ◽  
Weather And Climate ◽  
Change Context ◽  
Spatio Temporal

Abstract. Large wildfires across parts of France can cause devastating damages which put lives, infrastructures, and natural ecosystem at risk. One of the most challenging questions in the climate change context is how these large wildfires relate to weather and climate and how they might change in a warmer world. Such projections rely on the development of a robust modeling framework linking wildfires to atmospheric variability. Drawing from a MODIS product and a gridded meteorological dataset, we derived a suite of biophysical and fire danger indices and developed generalized linear models simulating the probability of large wildfires (> 100 ha) at 8-km spatial and daily temporal resolutions across the entire country over the MODIS period. The models were skillful in reproducing the main spatio-temporal patterns of large wildfires across different environmental regions. Long-term drought was found to be a significant predictor of large wildfires in flammability-limited systems such as the Alpine and Southwest regions. In the Mediterranean, large wildfires were found to be associated with both short-term fire weather conditions and longer-term soil moisture deficits, collectively facilitating the occurrence of large wildfires. Simulated probabilities during the day of large wildfires were on average 2–3 times higher than normal with respect to the mean seasonal cycle. The model has wide applications, including improving our understanding of the drivers of large wildfires over the historical period and providing a basis to estimate future changes to large wildfire from climate scenarios.

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