scholarly journals Nested species distribution models of Chlamydiales in tick host Ixodes ricinus in Switzerland

2020 ◽  
Author(s):  
Estelle Rochat ◽  
Séverine Vuilleumier ◽  
Sebastien Aeby ◽  
Gilbert Greub ◽  
Stéphane Joost
Keyword(s):  
Environmental Factors ◽  
Ixodes Ricinus ◽  
Vegetation Index ◽  
Respiratory Infections ◽  
Smartphone Application ◽  
Temporal Variations ◽  
Lower Percentage ◽  
Distribution Models ◽  
Distribution Maps ◽  
Spatio Temporal

AbstractThe tick Ixodes ricinus is the vector of various pathogens, including Chlamydiales bacteria, potentially causing respiratory infections. In this study, we modelled the spatial distribution of I. ricinus and associated Chlamydiales over Switzerland from 2009 to 2019. We used a total of 2293 ticks and 186 Chlamydiales occurrences provided by a Swiss Army field campaign, a collaborative smartphone application and a prospective campaign. For each tick location, we retrieved from Swiss federal datasets the environmental factors reflecting the topography, climate and land cover. We then used the Maxent modelling technique to estimate the suitability for I. ricinus and to subsequently build the nested niche of Chlamydiales bacteria. Results indicate that I. ricinus high habitat suitability is determined by higher temperature and vegetation index (NDVI) values, lower temperature during driest months and a higher percentage of artificial and forests areas. The performance of the model was increased when extracting the environmental variables for a 100 m-radius buffer around the sampling points and when considering the data over the two years previous sampling date. For Chlamydiales bacteria, the suitability was favoured by lower percentage of artificial surfaces, driest conditions, high precipitation during coldest months and short distances to wetlands. From 2009 to 2018, we observed an extension of tick and Chlamydiales suitable areas, associated with a shift towards higher altitude. The importance to consider spatio-temporal variations of the environmental conditions for obtaining better prediction was also demonstrated.ImportanceIxodes ricinus is the vector of pathogens, including the agent of Lyme disease, the tick borne encephalitis virus and the less known Chlamydiales bacteria at the origin of some respiratory infections. In this study, we identified the environmental factors influencing the presence of I. ricinus and Chlamydiales in Switzerland and generated maps of their distribution from 2009 to 2018. We found an important expansion of suitable areas for both the tick and the bacteria during the last decade. Results provided also the environmental factors that determine the presence of Chlamydiales within ticks. Distribution maps as generated here are expected to bring valuable informations for decision-makers to control tick-borne diseases in Switzerland and establish prevention campaigns. The methodological framework presented could be used to predict the distribution and spread of other host-pathogen couples, to identify environmental factors driving their distribution and to develop control or prevention strategies accordingly.

scholarly journals Nested Species Distribution Models of Chlamydiales in Ixodes ricinus (Tick) Hosts in Switzerland

2020 ◽  
Vol 87 (1) ◽  
Author(s):  
Estelle Rochat ◽  
Séverine Vuilleumier ◽  
Sébastien Aeby ◽  
Gilbert Greub ◽  
Stéphane Joost
Keyword(s):  
Environmental Factors ◽  
Ixodes Ricinus ◽  
Vegetation Index ◽  
Respiratory Infections ◽  
Smartphone Application ◽  
Climatic Conditions ◽  
Lower Percentage ◽  
Distribution Models ◽  
Content Type ◽  
Distribution Maps

ABSTRACT The tick Ixodes ricinus is the vector of various pathogens, including Chlamydiales bacteria, which potentially cause respiratory infections. In this study, we modeled the spatial distribution of I. ricinus and associated Chlamydiales over Switzerland from 2009 to 2019. We used a total of 2,293 ticks and 186 Chlamydiales occurrences provided by a Swiss Army field campaign, a collaborative smartphone application, and a prospective campaign. For each tick location, we retrieved from Swiss federal data sets the environmental factors reflecting the topography, climate, and land cover. We then used the Maxent modeling technique to estimate the suitability of particular areas for I. ricinus and to subsequently build the nested niche of Chlamydiales bacteria. Results indicate that I. ricinus habitat suitability is determined by higher temperature and normalized difference vegetation index (NDVI) values, lower temperature during the driest months, and a higher percentage of artificial and forest areas. The performance of the model was improved when extracting the environmental variables for a 100-m radius buffer around the sampling points and when considering the climatic conditions of the 2 years previous to the sampling date. Chlamydiales bacteria were favored by a lower percentage of artificial surfaces, drier conditions, high precipitation during the coldest months, and short distances to wetlands. From 2009 to 2018, we observed an extension of areas suitable to ticks and Chlamydiales, associated with a shift toward higher altitude. The importance of considering spatiotemporal variations in the environmental conditions for obtaining better prediction was also demonstrated. IMPORTANCE Ixodes ricinus is the vector of pathogens including the agent of Lyme disease, the tick-borne encephalitis virus, and the less well-known Chlamydiales bacteria, which are responsible for certain respiratory infections. In this study, we identified the environmental factors influencing the presence of I. ricinus and Chlamydiales in Switzerland and generated maps of their distribution from 2009 to 2018. We found an important expansion of suitable areas for both the tick and the bacteria during the last decade. Results also provided the environmental factors that determine the presence of Chlamydiales within ticks. Distribution maps as generated here are expected to bring valuable information for decision makers in controlling tick-borne diseases in Switzerland and establishing prevention campaigns. The methodological framework presented could be used to predict the distribution and spread of other host-pathogen pairs to identify environmental factors driving their distribution and to develop control or prevention strategies accordingly.

scholarly journals Spatial Autocorrelation of Martian Surface Temperature and Its Spatio-Temporal Relationships with Near-Surface Environmental Factors across China’s Tianwen-1 Landing Zone

2021 ◽  
Vol 13 (11) ◽  
pp. 2206
Author(s):  
Yaowen Luo ◽  
Jianguo Yan ◽  
Fei Li ◽  
Bo Li
Keyword(s):  
Environmental Factors ◽  
Surface Temperature ◽  
Thermal Inertia ◽  
Temporal Variations ◽  
Spatial Aggregation ◽  
Driving Factors ◽  
Martian Surface ◽  
Near Surface ◽  
Landing Zone ◽  
Spatio Temporal

Variations in the Martian surface temperature indicate patterns of surface energy exchange. The Martian surface temperature at a location is similar to those in adjacent locations; but, an understanding of temperature clusters in multiple locations will deepen our knowledge of planetary surface processes overall. The spatial coherence of the Martian surface temperature (ST) at different locations, the spatio-temporal variations in temperature clusters, and the relationships between ST and near-surface environmental factors, however, are not well understood. To fill this gap, we studied an area to the south of Utopia Planitia, the landing zone for the Tianwen-1 Mars Exploration mission. The spatial aggregation of three Martian ST indicators (STIs), including sol average temperature (SAT), sol temperature range (STR), and sol-to-sol temperature change (STC), were quantitatively evaluated using clustering analysis at the global and local scale. In addition, we also detected the spatio-temporal variations in relations between the STIs and seven potential driving factors, including thermal inertia, albedo, dust, elevation, slope, and zonal and meridional winds, across the study area during 81 to 111 sols in Martian years 29–32, based on a geographically and temporally weighted regression model (GTWR). We found that the SAT, STR, and STC were not randomly distributed over space but exhibited signs of significant spatial aggregation. Thermal inertia and dust made the greatest contribution to the fluctuation in STIs over time. The local surface temperature was likely affected by the slope, wind, and local circulation, especially in the area with a large slope and low thermal inertia. In addition, the sheltering effects of the mountains at the edge of the basin likely contributed to the spatial difference in SAT and STR. These results are a reminder that the spatio-temporal variation in the local driving factors associated with Martian surface temperature cannot be neglected. Our research contributes to the understanding of the surface environment that might compromise the survival and operations of the Tianwen-1 lander on the Martian surface.

scholarly journals Water table fluctuation and its effects on vegetation in a semiarid environment

2011 ◽  
Vol 8 (2) ◽  
pp. 3271-3304 ◽  
Author(s):  
L. Duan ◽  
T. Liu ◽  
X. Wang ◽  
Y. Luo ◽  
W. Wang ◽  
...  
Keyword(s):  
Water Table ◽  
Vegetation Index ◽  
Potential Evapotranspiration ◽  
Meteorological Data ◽  
Depth Map ◽  
Northern China ◽  
Temporal Variations ◽  
Water Table Fluctuation ◽  
Semiarid Environment ◽  
Spatio Temporal

Abstract. A good understanding of water table fluctuation effects on vegetation is crucial for sustaining fragile hydrology and ecology of semiarid areas such as the Horqin Sandy Land (HSL) in northern China, but such understanding is not well documented in literature. The objectives of this study were to examine spatio-temporal variations of water table and their effects on vegetation in a semiarid environment. A 9.71 km2 area within the HSL was chosen and well-instrumented to continuously measure hydrometeorologic parameters (e.g., water table). The area comprises of meadow lands and sandy dunes as well as transitional zones in between. In addition to those measured data, this study also used Landsat TM and MODIS imageries and meteorological data at a station near the study area. The spatio-temporal variations were examined using visual plots and contour maps, while the effects on vegetation were determined by overlaying a water table depth map with a vegetation index map derived from the MODIS imageries. The results indicated that water table was mainly dependent on local topography, localized geological settings, and human activities (e.g., reclamation). At annual and monthly scales, water table was mainly a function of precipitation and potential evapotranspiration. A region within the study area where depth to water table was smaller tended to have better (i.e., more dense and productive) vegetation cover. Further, the results revealed that water table fluctuation was more sensitive for vegetations in the meadow lands than in the transitional zones, but it was least sensitive for vegetations in the sandy dunes.

scholarly journals Spatio-Temporal Variations of Satellite-Based PM2.5 Concentrations and Its Determinants in Xinjiang, Northwest of China

2020 ◽  
Vol 17 (6) ◽  
pp. 2157 ◽  
Author(s):  
Wei Wang ◽  
Alim Samat ◽  
Jilili Abuduwaili ◽  
Yongxiao Ge
Keyword(s):  
Population Density ◽  
Tarim Basin ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fine Particulate Matter ◽  
Temporal Variations ◽  
Central China ◽  
Dominant Factor ◽  
Tianshan Mountain ◽  
Spatio Temporal

With the aggravation of air pollution in recent years, a great deal of research on haze episodes is mainly concentrated on the east-central China. However, fine particulate matter (PM2.5) pollution in northwest China has rarely been discussed. To fill this gap, based on the standard deviational ellipse analysis and spatial autocorrelation statistics method, we explored the spatio-temporal variation and aggregation characteristics of PM2.5 concentrations in Xinjiang from 2001 to 2016. The result showed that annual average PM2.5 concentration was high both in the north slope of Tianshan Mountain and the western Tarim Basin. Furthermore, PM2.5 concentrations on the northern slope of the Tianshan Mountain increased significantly, while showing an obviously decrease in the western Tarim Basin during the period of 2001–2016. Based on the result of the geographical detector method (GDM), population density was the most dominant factor of the spatial distribution of PM2.5 concentrations (q = 0.550), followed by road network density (q = 0.423) and GDP density (q = 0.413). During the study period (2001–2016), the driving force of population density on the distribution of PM2.5 concentrations showed a gradual downward trend. However, other determinants, like DEM (Digital elevation model), NSL (Nighttime stable light), LCT (Land cover type), and NDVI (Normalized Difference Vegetation Index), show significant increased trends. Therefore, further effort is required to reveal the role of landform and vegetation in the spatio-temporal variations of PM2.5 concentrations. Moreover, the local government should take effective measures to control urban sprawl while accelerating economic development.

scholarly journals SPATIO-TEMPORAL ANALYSIS TO PREDICT ENVIRONMENTAL INFLUENCE ON MALARIA

2018 ◽  
Vol XLII-3 ◽  
pp. 2615-2617 ◽  
Author(s):  
S. Baig ◽  
M. S. Sarfraz
Keyword(s):  
Environmental Factors ◽  
Vegetation Index ◽  
Environmental Influence ◽  
Temporal Patterns ◽  
Temporal Analysis ◽  
Water Bodies ◽  
Morbidity And Mortality ◽  
Spatial And Temporal Patterns ◽  
Different Seasons ◽  
Spatio Temporal

Malaria is a vector borne disease which is a major cause of morbidity and mortality. It is one of the major diseases in the category of infectious diseases. The survival and bionomics of malaria is affected by environmental factors such as climatic, demographic and land-use/land-cover etc. Currently, a very few under developing countries are using Geo-informatics approaches to control this disease. Gujrat a district of Pakistan, is still under threat of malaria disease. Current research is carried on malaria incidents obtained from District Executive Officer of Health Gujrat. The objective of this study was to explore the spatio-temporal patterns of malaria in district Gujrat and to identify the areas being affected by Malaria. Furthermore, it has been also analyzed the relationship between malaria incident and environmental factors in highly favorable zones. Data is analyzed based on spatial and temporal patterns using (Moran’s I). Moreover cluster and hot spots analysis were performed on the incident data. This study shows positive correlation with rainfall, vegetation index, population density and water bodies; while it shows positive and negative correlation with temperature in different seasons. However, variation between amount of vegetation and water bodies were observed. Finding of this research can help the decision makers to take preventive measures and reduce the morbidity and mortality related with malaria in Gujrat, Pakistan.

scholarly journals A global spatially Continuous Solar Induced Fluorescence (CSIF) dataset using neural networks

2018 ◽  
Author(s):  
Yao Zhang ◽  
Joanna Joiner ◽  
Seyed Hamed Alemohammad ◽  
Sha Zhou ◽  
Pierre Gentine
Keyword(s):  
Primary Production ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Gross Primary Production ◽  
Terrestrial Ecosystems ◽  
Temporal Variations ◽  
Clear Sky ◽  
Spatio Temporal ◽  
The Individual ◽  
Sky Conditions

Abstract. Satellite-retrieved Solar Induced Chlorophyll Fluorescence (SIF) has shown great potential to monitor the photosynthetic activity of terrestrial ecosystems. However, several issues, including low spatial and temporal resolution of the gridded datasets and high uncertainty of the individual retrievals, limit the applications of SIF. In addition, inconsistency in measurements footprints also hinder the direct comparison between gross primary production (GPP) from eddy covariance (EC) flux towers and satellite-retrieved SIF. In this study, by training a neural network (NN) with surface reflectance from the MODerate-resolution Imaging Spectroradiometer (MODIS) and SIF from Orbiting Carbon Observatory-2 (OCO-2), we generated two global spatially continuous SIF (CSIF) datasets at moderate spatio-temporal resolutions (0.05 degree 4-day) during 2001–2016, one for clear-sky conditions and the other one in all-sky conditions. The clear-sky instantaneous CSIF (CSIFclear-inst) shows high accuracy against the clear-sky OCO-2 SIF and little bias across biome types. The all-sky daily average CSIF (CSIFall-daily) dataset exhibits strong spatial, seasonal and interannual dynamics that are consistent with daily SIF from OCO-2 and the Global Ozone Monitoring Experiment-2 (GOME-2). An increasing trend (0.39 %) of annual average CSIFall-daily is also found, confirming the greening of Earth in most regions. Since the difference between satellite observed SIF and CSIF is mostly caused by the environmental down-regulation on SIFyield, the ratio between OCO-2 SIF and CSIFclear-inst can be an effective indicator of drought stress that is more sensitive than normalized difference vegetation index and enhanced vegetation index. By comparing CSIFall-daily with gross primary production (GPP) estimates from 40 EC flux towers across the globe, we find a large cross-site variation (c.v. = 0.36) of GPP-SIF relationship with the highest regression slopes for evergreen needleleaf forest. However, the cross-biome variation is relatively limited (c.v. = 0.15). These two continuous SIF datasets and the derived GPP-SIF relationship enable a better understanding of the spatial and temporal variations of the GPP across biomes and climate.

scholarly journals SPATIO-TEMPORAL ANALYSIS OF URBAN HEAT ISLAND IN MANDAUE CITY, PHILIPPINES

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 361-367
Author(s):  
A. M. Rejuso ◽  
A. C. Cortes ◽  
A. C. Blanco ◽  
C. A. Cruz ◽  
J. B. Babaan
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Temporal Analysis ◽  
High Heat ◽  
Temporal Variations ◽  
The Philippines ◽  
Water Index ◽  
Spatio Temporal

Abstract. Extensive urbanization alters the natural landscape as vegetation were replaced with infrastructures composed of materials with low albedo and high heat capacity often resulting to increase in land surface temperatures (LST). The present study focused on the spatial and temporal variations of LST in Mandaue City, one of the metropolitan cities in the Philippines that had undergone a rapid rate of urbanization over the past years. Climate Engine (CE), a cloud computing tool that processes satellite images, was used in this study. Preprocessed LST, normalized difference water index (NDWI), normalized difference vegetation index (NDVI), shortwave infrared (SWIR 1) and near-infrared (NIR) layers were directly downloaded from CE while the normalized difference built-up index (NDBI) maps were calculated. Time-series dataset of these indices were analyzed to determine the impacts of reduced vegetation cover and increased built-up areas on surface temperature from years 2013 to 2019. The spatial distribution of LST were analyzed using Univariate Local Moran’s I in GeoDa to identify hotspots within the city. Analysis results showed that the hotspots are barangays Tipolo (100%), Bakilid (100%), Ibabao-Estancia (93.5%), Alang-Alang (87.2%), Guizo (84.4%), Subangdaku (84.1%), and Centro (79.4%). The results indicated that there is a linear relationship between LST and NDBI (r = 0.659, p < 0.01) while an inverse relationship was observed between LST with NDVI (r = −0.527, p < 0.1) and NDWI (r = −0.620, p < 0.01).

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