For example,
How changing landscapes lead new:
A new simulation shows that environmental changes through the main migration route of Asian birds could speed up viral development and increase the risk of dangerous influenza strains.
Study: Landscape changes raise the risk of diversification and emergence of avian flu virus in the Migration path of East-Asia-Australasia. In addition, Image credit: Albert Beukhof / Shutterstock
A recent study in the Proceedings of the National Academy of Sciences studied the impact of landscape changes in the Migration route of Asia in Asia-Australas on the distribution of migratory aquatic birds. Furthermore, their interaction with poultry, influencing the evolution of the AIV.
Avian flu virus: emergence. Furthermore, evolution
The highly pathogenic avian flu virus (HPAIV) A / H5N1 was detected for the first time in 1996, infecting domestic poultry. Moreover, Thereafter, this caused serious epidemics affecting the poultry industry and the populations of wild birds. Consequently, Over time, several new HPAiv H5 subtypes have appeared, including the recent discovery of H5N1.
H5N1 has proven to have the potential to transmit through new geographic regions. Meanwhile, hosts, including dairy cattle, which has strengthened the global concern of fauna, agriculture and public health. Moreover, A newly emerged H5N1 subtype with improved virus adaptability allows rapid transmission between wider host groups.
Although the highly pathogenic AIV strains come mainly from specific genetic mutations. Similarly, such as the insertions of polybasic cleavage site in the HA gene, the genetic restocking can also contribute to genetic diversity. Similarly, A viral strain with high genetic diversity how changing landscapes lead new has a higher risk of becoming pathogenic under favorable ecological conditions. Additionally, Similarly, and the study used the reassortment as a key indicator of these conditions.
Above all. Furthermore, the study used the impact of the restocking as an indirect indicator, and not a direct predictor of potential viral emergence, noting that real pathogenicity requires additional mutations. Similarly, Genetic restocking is a crucial mechanism associated with the exchange of genetic information between the co -fe to a host.
The savvy savage influences the evolution of avian influenza viruses
In 2002-2003. For example, the researchers isolated the first HPAIV of Savage Sauvagine in the migration path of East Asia-Australasian (EAAF). Furthermore, Initially, HPAIV infection in wild savage was considered an overflow of domestic poultry. Moreover, Each year. Nevertheless, millions of savagines migrate from the north of the breeding ground in Siberia and Mongolia towards wintering grounds in the how changing landscapes lead new Yangtze river basin in southeast China.
Seasonal migration facilitates long-distance propagation of viruses, which ultimately increases local viral diversity and the risk of co-infection. This phenomenon also raises the risk of emergence of new viruses. Several factors determine the distribution of aquatic birds during migration. including the characteristics of the landscape, in particular wetlands, the availability of surface water and the presence of rice fields.
Recent studies have revealed changes to the climate. man in the EAAF landscape, such as agricultural abandonment in Russia and the expansion of rice fields in northern China, which have a significant impact on the distribution of aquatic birds through the mine route. It is important to understand how these changes have influenced AIV dynamics.
The migration networks generated by the monitoring of telemetry, GLM predictions and IBM simulations for the 2000 and 2015 scenarios. (A) Network of DBBMM sites using 2015 telemetry monitoring data. (B) Network of predicted sites by GLM how changing landscapes lead new for 2000; (C) network based on sites simulated by IBM for 2000; D) Network of predicted sites by GLM for 2015; (E) Network based on sites simulated by IBM for 2015. Links in networks A. B and D use the length of the migration step, while links in the C and E networks use simulated IBM movement trajectories. Green and blue contours respectively show breeding and wintering ranges. In C. E networks, the color of the node indicates the number of birds visited and the bond width indicates the number of itinerant birds.
About the study
How changing landscapes lead new
This study studied how landscape changes in EAAF between 2000. 2015 affected the distribution of migratory aquatic birds, which can improve the potential risk of emergence of new subtypes.
Researchers combined the telemetry monitoring data of a host of Sauvagine Migrator. Ebird data, a larger goose with how changing landscapes lead new a white front (Albifrons considerGWFG), poultry distribution data and landscape data to develop an individual model (IBM). While the GWFG interactions with poultry provided a reference base. the development to the species probably underestimates the risks of overall transmission dominated by the ducks and the gulls that were cut.
This model was used to simulate the movements of the aquatic birds. the inter-species transmission at the Bird-Poultry Wild interface. In addition, this model combines a model of migratory flow network with compartments models. In a migratory flow network model, the edges represent potential movement paths and nodes represent sites.
The model simulates the dynamics of infections within wild and poultry populations. It also predicts the spinoffs of wild birds with poultry and the poultry response. The bird movement was determined by their habitat and their distance. The simulations between 2000. 2015 were compared to assess how the change of landscape how changing landscapes lead new has an impact on the risk of emergence of viruses by modifying the migration of birds.
Study results
A total of 50 sites. including 11 breeding sites, 7 wintering and 32 stop sites, were identified from telemetry monitoring data between 2014 and 2016. A generalized linear model (GLM) was developed to predict appropriate sites between 2000. 2015, which indicated an increased number of stop sites in Russia and a reduced number in the Magadan. However, a contrasting trend in reproduction and wintering sites has been observed.
Based on the 2015 data. IBM simulations indicated that improved connectivity and habitat passed birds from the high dependence of the Magadan site ill-connected to a larger network through Russia and the borders of Mongolia and northeast of China. Wetlands. Paddy rice have turned out to be the most important factors to shape GWFG distribution, especially in northeast China.
The increase how changing landscapes lead new in reproduction sites from 2000 to 2015 delayed the exposure and transmission of the virus to stopovers. However, this led to higher prevalence rates of infections, especially during the arrival and winter arrival in 2015. High rates of prevalence of infections accelerated the risk of viral transmission of stopping at wintering sites. to increasing cross -spread by improving environmental viral charges at winter sites.
Pathogenic avian flu viruses (LPAIV) were identified as the main contributor to infections in wild birds. causing 57% of infections in 2015 and 34% in 2000. Increased viral charges were associated with LPAIV in wild birds and poultry. The rate of inter-species transmission has greatly increased the reassortment, in particular in the 2015 scenario. The increase of 1,593% of the reassortment served as a key study of the study for a risk of high emergence. Furthermore, The results of the study support the fact that the how changing landscapes lead new landscape conditions modified in 2015 increased the role of. poultry in the promotion of LPAIV traffic.
The simulation model indicated that the risk of genetic reassures improved both the magnitude. the spatial extent between 2000 and 2015, especially in northeast of China, the borders suffering from Mongolia and Russia, and from Yangtze to the Yellow River basin.
How changing landscapes lead new
Conclusions
Landscape changes between 2000 and 2015 proved to reshape the distribution of migratory aquatic birds in EAAF. This sparked an increase in interactions with poultry which ultimately improves the risk of viral diversification. the emergence of subtypes. This study highlighted the role of environmental changes in the emergence and the AIV scheme.
The authors underlined the need for an interdisciplinary approach which integrates the dynamics of the landscape into viral evolution studies by combining the modeling of ecology. virology and landscape to predict AIV dynamics how changing landscapes lead new and precisely determine the areas at high risk.
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