Database update flowchart. this shows how updates from mcdw,… – figure 1 of 10

African swine fever (ASF) causes severe socio-economic impacts due to high mortality and trade restrictions. Database sharding Many risk factors of ASF have been identified at farm level. Database keys with example However, understanding the risk factors, especially wild suid hosts, determining ASF transmission at regional level remains limited.

Based on ASF outbreak data in domestic pigs during 2006–2014, we here tested, separately for West and East Africa, which risk factors were linked to ASF presence at a regional level, using generalized linear mixed models.

Our results show that ASF infections in the preceding year was an important predictor for ASF presence in both West and East Africa. Data recovery xfs Both pig density and human density were positively associated with ASF presence in West Africa. Database management systems 3rd edition In East Africa, ASF outbreaks in domestic pigs were also correlated with higher percentages of areas occupied by giant forest hogs and by high-tick-risk areas.

Our results suggest that regional ASF risk in East Africa and in West Africa were associated with different sets of risk factors. Database engineer salary Regional ASF risk in West Africa mainly followed the domestic cycle, whereas the sylvatic cycle may influence regional ASF risk in East Africa. Jstor database With these findings, we contribute to the better understanding of the risk factors of ASF occurrence at regional scales that may aid the implementation of effective control measures.

[Show abstract] [Hide abstract] ABSTRACT: Dryland ecosystems are highly vulnerable to environmental changes. E m database Monitoring is vital in order to evaluate their response to fluctuating rainfall and temperature patterns for long-term ecosystem safeguarding. Data recovery richmond va Monitoring of long term changes of normalized difference vegetation index (NDVI) and climate variables are fundamental for better understanding of change trajectories in dryland ecosystem, and to ascertain their potential interaction with anthropogenic drivers. Data recovery software In this study, we identify determinant factors of dryland changes by using MODIS NDVI, precipitation and temperature data for Breaks for Additive Seasonal and Trend (BFAST) and Mann Kendall test statistic. Data recovery advisor BFAST predicts iteratively time and number of changes within a time series data to depict the size and direction of changes. Database host name Analysis of NDVI, precipitation and temperature time series data showed substantial changes during the study period of 2000–2014. Database performance There is a reduction trend in vegetation showed by the decline in NDVI, with significant breakpoints till 2009 and recovery afterwards, without a significant change in annual trends of precipitation (α < 0.05) for the same study period. Data recovery broken hard drive Furthermore 2 positive climate trends were founded: a) a significant positive trend on long term annual rainfall during the main rainy seasons and; 2) a significant (α < 0.05) annual increment of the long term mean minimum and mean maximum temperature of 0.03 °C/year and 0.04 °C/year, respectively. Database xe This assessment showed that climate variables cannot be considered as the main factors in explaining the observed patterns of vegetation dynamics. Database yml mysql Seasonal and interannual precipitation changes have a lower weight as driving factors for the reduction in vegetation trends. 5 database is locked Hence, the decline in vegetation productivity of the region can be attributed to the increasing pressure of human activities.

[Show abstract] [Hide abstract] ABSTRACT: Receding mountain glaciers affect the hydrology of downslope ecosystems with consequences for drinking water, agriculture, and hydropower production. Database fundamentals Here we combined land cover derived from satellite imagery and other environmental data from the northern Peruvian Andes into a first differencing regression model to assess wetland hydrologic connectivity. Database concepts Wetland area was considered the response variable and a variety of land cover, climatic, and stream discharge explanatory variables were tested to evaluate effects of possible hydrologic connectivity. Database icon The results indicate that there were two primary spatial driving forces of wetland change in Peru’s Cordillera Blanca from 1987 to 1995: 1) loss in glacier area was associated with increased wetland area, controlling for other factors; while 2) an increase in mean annual stream discharge in the previous 12 months increased wetland area. Database versioning The general approach we used expands the ways that connectivity between landscape changes and hydrologic and ecosystem processes can be assessed.