scholarly journals Bulinus senegalensis and Bulinus umbilicatus Snail Infestations by the Schistosoma haematobium Group in Niakhar, Senegal

Pathogens ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 860
Author(s):  
Papa Mouhamadou Gaye ◽  
Souleymane Doucoure ◽  
Bruno Senghor ◽  
Babacar Faye ◽  
Ndiaw Goumballa ◽  
...  
Keyword(s):  
Rainy Season ◽  
Schistosoma Haematobium ◽  
Temporal Dynamics ◽  
Treatment Strategies ◽  
Molecular Techniques ◽  
Diagnostic Pcr ◽  
Blood Flukes ◽  
The North ◽  
Spatio Temporal ◽  
Pcr Targeting

Thorough knowledge of the dynamics of Bulinus spp. infestation could help to control the spread of schistosomiasis. This study describes the spatio-temporal dynamics of B. senegalensis and B. umbilicatus infestation by the Schistosoma haematobium group of blood flukes in Niakhar, Senegal. Molecular identification of the S. haematobium group was performed by real-time PCR, targeting the Dra 1 gene in 810 samples of Bulinus spp. collected during the schistosomiasis transmission season in 2013. In addition to Dra 1 PCR, a rapid diagnostic-PCR was performed on a sub-group of 43 snails to discriminate S. haematobium, S. bovis, and S. mattheei. Out of 810 snails, 236 (29.1%) were positive for Dra 1 based on the PCR, including 96.2% and 3.8% of B. senegalensis and B. umbilicatus, respectively. Among the sub-group, 16 samples were confirmed to be S. haematobium while one was identified as a mixture of S. haematobium and S. bovis. Snails infestations were detected in all villages sampled and infestation rates ranged from 15.38% to 42.11%. The prevalence of infestation was higher in the north (33.47%) compared to the south (25.74%). Snail populations infestations appear early in the rainy season, with a peak in the middle of the season, and then a decline towards the end of the rainy season. Molecular techniques showed, for the first time, the presence of S. bovis in the Bulinus spp. population of Niakhar. The heterogeneity of snail infestations at the village level must be taken into account in mass treatment strategies. Further studies should help to improve the characterizations of the schistosome population.

scholarly journals Assessing the Wall-To-Wall Spatial and Qualitative Dynamics of the Brazilian Pasturelands, between 2010 and 2018, Based on the Analysis of the Landsat Data Archive

2021 ◽  
Author(s):  
Claudinei Oliveira-Santos ◽  
Vinicius Vieira Mesquita ◽  
Leandro Leal Parente ◽  
Alexandre de Siqueira Pinto ◽  
Laerte Guimaraes Ferreira
Keyword(s):  
Temporal Dynamics ◽  
Spatial Dynamics ◽  
Limited Resource ◽  
Change Scenario ◽  
The North ◽  
Pasture Quality ◽  
Spatio Temporal ◽  
Pasture Area ◽  
Degraded Pastures

The Brazilian livestock is predominantly extensive, with approximately 90% of the production being sustained on pasture, which occupies around 20% of the territory. In the current climate change scenario and where cropland is becoming a limited resource, there is a growing need for a more efficient land use and occupation. It is estimated that more than half of the Brazilian pastures have some level of degradation; however there is still no mapping of the quality of pastures on a national scale. In this study, we mapped and evaluated the spatio-temporal dynamics of pasture quality in Brazil, between 2010 and 2018, considering three classes of degradation: Absent (D0), Intermediate (D1), and Severe (D2). There was no variation in the total area occupied by pastures in the evaluated period, in spite of the accentuated spatial dynamics, with a retraction in the center-south and expansion to the north, over areas of ​​native vegetation. The percentage of non-degraded pastures increased ~12%, due to the recovery of degraded areas and the emergence of new pasture areas as a result of the prevailing spatial dynamics. However, about 44 Mha of the pasture area is currently severely degraded. The dynamics in pasture quality were not homogeneous in property size classes. We observed that in the approximately 2.68 million properties with livestock activity, the proportion with quality gains was twice as low in small properties compared to large ones, and the proportion with losses was three times greater, showing an increase in inequality between properties with more and less resources (large and small, respectively). The areas occupied by pastures in Brazil present an unique opportunity to increase livestock production and make available areas for agriculture, without the need for new deforestation in the coming decades.

scholarly journals Adaptation of sperm whales to open-boat whalers: rapid social learning on a large scale?

2021 ◽  
Vol 17 (3) ◽  
Author(s):  
Hal Whitehead ◽  
Tim D. Smith ◽  
Luke Rendell
Keyword(s):  
Social Learning ◽  
North Pacific ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Rapid Decline ◽  
Sperm Whales ◽  
The North ◽  
Spatio Temporal ◽  
Social Units ◽  
The North Pacific

Animals can mitigate human threats, but how do they do this, and how fast can they adapt? Hunting sperm whales was a major nineteenth century industry. Analysis of data from digitized logbooks of American whalers in the North Pacific found that the rate at which whalers succeeded in harpooning (‘striking’) sighted whales fell by about 58% over the first few years of exploitation in a region. This decline cannot be explained by the earliest whalers being more competent, as their strike rates outside the North Pacific, where whaling had a longer history, were not elevated. The initial killing of particularly vulnerable individuals would not have produced the observed rapid decline in strike rate. It appears that whales swiftly learned effective defensive behaviour. Sperm whales live in kin-based social units. Our models show that social learning, in which naive social units, when confronted by whalers, learned defensive measures from grouped social units with experience, could lead to the documented rapid decline in strike rate. This rapid, large-scale adoption of new behaviour enlarges our concept of the spatio-temporal dynamics of non-human culture.

scholarly journals Oxytocin modulates the temporal dynamics of resting EEG networks

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Bastian Schiller ◽  
Thomas Koenig ◽  
Markus Heinrichs
Keyword(s):  
Neural Networks ◽  
Social Interaction ◽  
Temporal Dynamics ◽  
Average Duration ◽  
Temporal Stability ◽  
Treatment Strategies ◽  
High Anxiety ◽  
Anxiety Levels ◽  
Spatio Temporal ◽  
Rapid Switching

Abstract Oxytocin is a key modulator of social interaction, but we possess little knowledge of its underlying effects on neuropsychological processes. We used a spatio-temporal EEG microstates analysis to reveal oxytocin’s effects on the temporal dynamics of intrinsically generated activity in neural networks. Given oxytocin’s known anxiolytic effects, we hypothesized that it increases the temporal stability of the four archetypal EEG resting networks. Eighty-six male participants had received oxytocin or placebo intranasally before we recorded their resting EEG. As hypothesized, oxytocin globally increased the average duration of the four archetypal resting networks and specifically decreased the occurrence and coverage of an autonomic processing-related network to benefit greater coverage of an attention-related network. Moreover, these neurophysiological changes were more pronounced in participants with high anxiety levels and strong subjectively experienced effects of the oxytocin administration. In sum, our study shows that oxytocin reduces rapid switching among neural resting networks by increasing their temporal stability. Specifically, it seems to reduce the brain’s need for preparing the internally-oriented processing of autonomic information, thus enabling the externally-oriented processing of social information. Changes in the temporal dynamics of resting networks might underlie oxytocin’s anxiolytic effects - potentially informing innovative psychobiological treatment strategies.

Alluvial farming in Ayeyarwady floodplains. Spatio-temporal dynamics of a complex human-water system

2020 ◽  
Author(s):  
Prof. Mariele Evers ◽  
Linda Taft ◽  
Michelle Zülich ◽  
Adrian Almoradie
Keyword(s):  
Agricultural Production ◽  
Rainy Season ◽  
Temporal Dynamics ◽  
Water System ◽  
Farming System ◽  
Research Area ◽  
Residual Moisture ◽  
Poor Households ◽  
Extreme Flood ◽  
Spatio Temporal

<p>Floodplains are important locations for agricultural production in many regions of the world. In monsoon-dominated regions with a pronounced rainy season, the floodplains are often used seasonally, which can improve food security and the income of poor households in particular. Alluvial farming benefits from fertile sediment deposits, residual moisture in the soil and good access to water from the river or groundwater. At the same time, farmers have to deal with flood risks and highly dynamic hydromorphological and hydrological conditions.<br>Agriculture is the main economic activity in Myanmar and accounts for 38% of the Gross domestic product. The most important production areas are the central drying zone (CDZ) and the Ayeyarwady Delta. The CDZ, however, is particularly characterized by irregular rainfall, significantly rising temperatures, droughts, a shift in the onset of the rainy season and extreme flood events, which makes agricultural production very challenging and difficult.<br>By using the Plural Water Research framework the physical and human boundary conditions of a research area in a floodplain in the CDZ were studied in order to identify relevant components which are shaping this complex human-water system. With the help of satellite images, hydrological data, on-site mapping and surveying farmers, the spatio-temporal dynamics of the alluvial farming system was examined and the interactions between hydrological variabilities and extremes and the handling of farmers within this complex system were examined and adaptation strategies were identified.</p>

scholarly journals Prioritization of the vector factors controlling <i>Emiliania huxleyi</i> blooms in subarctic and arctic seas: A multidimensional statistical approach

2019 ◽  
Author(s):  
Dmitry Kondrik ◽  
Eduard Kazakov ◽  
Svetlana Chepikova ◽  
Dmitry Pozdnyakov
Keyword(s):  
Statistical Approach ◽  
Temporal Dynamics ◽  
Remote Sensing Data ◽  
Marine Ecology ◽  
Arctic Seas ◽  
Prediction Ability ◽  
The North ◽  
Spatio Temporal ◽  
The Individual ◽  
The Impact

Abstract. Producing very extensive blooms in the world's oceans in both hemispheres, a coccolithophore E. huxleyi is capable of affecting both the marine ecology and carbon fluxes at the atmosphere-ocean interface. At the same time, it is subject to the impact of multiple co-acting environmental forcings, which determine the spatio-temporal dynamics of E. huxleyi blooming phenomenon. To reveal the individual importance of each forcing factor (FF) that is known to significantly control the extent and intensity of E. huxleyi blooms and can be retrieved from remote sensing data, we used long-term spatial time series (1998–2016) of sea surface temperature and salinity, incident photosynthetically active radiation, and Ekman layer depth relevant to the marine environments located in the North Atlantic, Arctic and North Pacific oceans, namely the North, Norwegian, Greenland, Labrador, Barents and Bering seas. The FFs retrieved were subjected to statistical analyses. The descriptive statistical approach has shown that E. huxleyi phytoplankton were highly adaptive to the environmental conditions and capable of arising and developing within wide FFs ranges, which proved to be expressly sea-specific. It was also found that there were FFs optimal ranges (also sea-specific), within which the blooms were particularly extensive. The application of the Random Forest Classifier (RFC) approach to each target sea allowed to reliably rank the FFs considered in terms of their role in the spatio-temporal dynamics of E. huxleyi blooms. With the only exception of the Bering Sea, allegedly due to temporally established untypical hydrological conditions, the prediction ability of RFC modeling characterized in terms of precision, recall, and f1-score generally was in excess of 70 %, thus indicating the adequacy of the developed models for FFs prioritization with regard to E. huxleyi blooms.

scholarly journals Spatio-temporal dynamics of milk production in Brazil

2022 ◽  
Vol 43 (1) ◽  
pp. 241-262
Author(s):  
Matheus Demambre Bacchi ◽  
◽  
Alexandre Nunes Almeida ◽  
Tiago Santos Telles ◽  
◽  
...  
Keyword(s):  
Milk Production ◽  
Spatial Data ◽  
Temporal Dynamics ◽  
Temporal Distribution ◽  
Principal Component ◽  
Location Quotient ◽  
Production Chain ◽  
The North ◽  
Spatio Temporal ◽  
Family Based

The milk production chain has relevance for the Brazilian economy, generating jobs and income. In addition, milk production, because of family-based farms, has an important social function. However, milk production is spatially heterogeneous in Brazil, especially due to the different technological patterns of production. In this context, the objective of this study was to verify the spatio-temporal distribution and dynamics of milk production in Brazil. For this purpose, milk production in Brazil in 2000 and 2016 was analyzed. The Brazilian microregions that specialize in milk production were identified using location quotient (LQ). An exploratory analysis of spatial data and Moran’s I were used to measure spatial autocorrelation among regions. Finally, principal component analysis (PCA) was used to assess the grouping relationships of variables as a function of the regions that specialize in milk production. Between 2000 and 2016, there was a decrease in the number of microregions that specialize in milk production. Thus, in 2016, approximately 20% of the microregions and over 22% of Brazilian municipalities specialized in milk production. The microregions and municipalities that specialize in milk production were concentrated mainly in the states of Minas Gerais and Goiás and in the Southern region of Brazil. There was an increase in milk productivity in all regions of the country, especially in those regions where production was concentrated. The formation of high-high clusters was found in the most productive regions of the country, i.e., in the South and Southeast, where the effects of technological spillover were observed, and the formation of low-low clusters was observed in the less productive regions, i.e., in the North and Northeast. Two main components were formed. The first component aggregated variables related to milk production in volume, and the second component aggregated variables inherent to productivity. It was possible to verify the recent growth in milk production and productivity in the country as well as to demonstrate the heterogeneity in production. Although there was a decrease in the number of microregions and municipalities that specialize in milk production, there was a concentration and increase in milk production and productivity in Brazil.

scholarly journals Mapping the Dynamics of Winter Wheat in the North China Plain from Dense Landsat Time Series (1999 to 2019)

2021 ◽  
Vol 13 (6) ◽  
pp. 1170
Author(s):  
Wenmin Zhang ◽  
Martin Brandt ◽  
Alexander V. Prishchepov ◽  
Zhaofu Li ◽  
Chunguang Lyu ◽  
...  
Keyword(s):  
Food Security ◽  
Winter Wheat ◽  
North China Plain ◽  
North China ◽  
Temporal Dynamics ◽  
Google Earth ◽  
Landsat Images ◽  
The North ◽  
The North China Plain ◽  
Spatio Temporal

Monitoring spatio-temporal changes in winter wheat planting areas is of high importance for the evaluation of food security. This is particularly the case in China, having the world’s largest population and experiencing rapid urban expansion, concurrently, it puts high pressure on food demands and the availability of arable land. The relatively high spatial resolution of Landsat is required to resolve the historical mapping of smallholder wheat fields in China. However, accurate Landsat-based mapping of winter wheat planting dynamics over recent decades have not been conducted for China, or anywhere else globally. Based on all available Landsat TM/ETM+/OLI images (~28,826 tiles) using Google Earth Engine (GEE) cloud computing and a Random Forest machine-learning classifier, we analyzed spatio-temporal dynamics in winter wheat planting areas during 1999–2019 in the North China Plain (NCP). We applied a median value of 30-day sliding windows to fill in potential data gaps in the available Landsat images, and six EVI-based phenological features were then extracted to discriminate winter wheat from other land cover types. Reference data for training and validation were extracted from high-resolution imagery available via Google Earth™ online mapping service, Sentinel-2 and Landsat imagery. We ran a sensitivity analysis to derive the optimal training sample class ratio (β = 1.8) accounting for the unbalanced distribution of land-cover types. We mapped winter wheat planting areas for 1999–2019 with overall accuracies ranging from 82% to 99% and the user’s/producer’s accuracies of winter wheat range between 90% and 99%. We observed an overall increase in winter wheat planting areas of 1.42 × 106 ha in the NCP as compared to the year 2000, with a significant increase in the Shandong and Hebei provinces (p < 0.05). This result contrasts the general discourse suggesting a decline in croplands (e.g., rapid urbanization) and climate change-induced unfavorable cropping conditions in the NCP. This suggests adjustments of the winter wheat planting area over time to satisfy wheat supply in relation to food security. This study highlights the application of Landsat images through GEE in documenting spatio-temporal dynamics of winter wheat planting areas for adequate management of cropping systems and assessing food security in China.

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