Yali Si

Environmental factors influencing the spread of the highly pathogenic avian influenza H5N1 virus in wild birds in Europe

A large number of occurrences of the highly pathogenic avian influenza (HPAI) H5N1 virus in wild birds were reported in Europe. The relationship between the occurrence pattern and environmental factors has, however, not yet been explored. This research uses logistic regression to quantify the relationships between anthropogenic or physical environmental factors and HPAI H5N1 occurrences. Our results indicate that HPAI H5N1 occurrences are highly correlated with the following: the increased normalized difference vegetation index (NDVI) in December; intermediate NDVI in March; lower elevations; increased minimum temperatures in January; and reduced precipitation in January. A predictive risk map of HPAI H5N1 occurrences in wild birds in Europe was generated on the basis of five key environmental factors. Independent validation of the risk map showed the predictive model to be of high accuracy (79%). The analysis suggests that HPAI H5N1 occurrences in wild birds are strongly influenced by the availability of food resources and are facilitated by increased temperatures and reduced precipitation. We therefore deduced that HPAI H5N1 occurrences in wild birds in Europe are probably caused by contact with other wild birds and not by contact with domestic poultry. These findings are important considerations for the global surveillance of HPAI H5N1 occurrences in wild birds.

Different environmental drivers of highly pathogenic avian influenza H5N1 outbreaks in poultry and wild birds.

A large number of highly pathogenic avian influenza (HPAI) H5N1 outbreaks in poultry and wild birds have been reported in Europe since 2005. Distinct spatial patterns in poultry and wild birds suggest that different environmental drivers and potentially different spread mechanisms are operating. However, previous studies found no difference between these two outbreak types when only the effect of physical environmental factors was analysed. The influence of physical and anthropogenic environmental variables and interactions between the two has only been investigated for wild bird outbreaks. We therefore tested the effect of these environmental factors on HPAI H5N1 outbreaks in poultry, and the potential spread mechanism, and discussed how these differ from those observed in wild birds. Logistic regression analyses were used to quantify the relationship between HPAI H5N1 outbreaks in poultry and environmental factors. Poultry outbreaks increased with an increasing human population density combined with close proximity to lakes or wetlands, increased temperatures and reduced precipitation during the cold season. A risk map was generated based on the identified key factors. In wild birds, outbreaks were strongly associated with an increased Normalized Difference Vegetation Index (NDVI) and lower elevation, though they were similarly affected by climatic conditions as poultry outbreaks. This is the first study that analyses the differences in environmental drivers and spread mechanisms between poultry and wild bird outbreaks. Outbreaks in poultry mostly occurred in areas where the location of farms or trade areas overlapped with habitats for wild birds, whereas outbreaks in wild birds were mainly found in areas where food and shelters are available. The different environmental drivers suggest that different spread mechanisms might be involved: HPAI H5N1 spread to poultry via both poultry and wild birds, whereas contact with wild birds alone seems to drive the outbreaks in wild birds.

Distribution of Barnacle Geese Branta leucopsis in Relation to Food Resources, Distance to Roosts, and the Location of Refuges

We used GPS satellite tracking data and field measurements of vegetation to investigate the effect of food resources, distance to roosts, and the location of refuges on the distribution of Barnacle Geese Branta leucopsis in the northern part of The Netherlands. To deal with spatial dependence among the data, a spatial lag model was used. A significant quadratic effect was found between sward height and goose distribution, indicating that geese prefer patches with intermediate sward heights. The manipulation of sward height can therefore be used to attract geese to refuges and thus reduce goose grazing in agricultural land. No relationship was found between grass nitrogen content and grazing intensity, indicating that geese do not distinguish between areas based on nitrogen content. A higher grazing intensity was observed in areas located within 2 km from roosts. The eight tracked geese spent 80% of their foraging time in refuges, demonstrating the importance of the refuge system.

Do Arctic breeding geese track or overtake a green wave during spring migration

Geese breeding in the Arctic have to do so in a short time-window while having sufficient body reserves. Hence, arrival time and body condition upon arrival largely influence breeding success. The green wave hypothesis posits that geese track a successively delayed spring flush of plant development on the way to their breeding sites. The green wave has been interpreted as representing either the onset of spring or the peak in nutrient biomass. However, geese tend to adopt a partial capital breeding strategy and might overtake the green wave to accomplish a timely arrival on the breeding site. To test the green wave hypothesis, we link the satellite-derived onset of spring and peak in nutrient biomass with the stopover schedule of individual Barnacle Geese. We find that geese track neither the onset of spring nor the peak in nutrient biomass. Rather, they arrive at the southernmost stopover site around the peak in nutrient biomass, and gradually overtake the green wave to match their arrival at the breeding site with the local onset of spring, thereby ensuring gosling benefit from the peak in nutrient biomass. Our approach for estimating plant development stages is critical in testing the migration strategies of migratory herbivores.

Geographical Analysis of the Distribution and Spread of Human Rabies in China from 2005 to 2011

Background Rabies is a significant public health problem in China in that it records the second highest case incidence globally. Surveillance data on canine rabies in China is lacking and human rabies notifications can be a useful indicator of areas where animal and human rabies control could be integrated. Previous spatial epidemiological studies lacked adequate spatial resolution to inform targeted rabies control decisions. We aimed to describe the spatiotemporal distribution of human rabies and model its geographical spread to provide an evidence base to inform future integrated rabies control strategies in China. Methods We geo-referenced a total of 17,760 human rabies cases of China from 2005 to 2011. In our spatial analyses we used Gaussian kernel density analysis, average nearest neighbor distance, Spatial Temporal Density-Based Spatial Clustering of Applications with Noise and developed a model of rabies spatiotemporal spread. Findings Human rabies cases increased from 2005 to 2007 and decreased during 2008 to 2011 companying change of the spatial distribution. The ANN distance among human rabies cases increased between 2005 and 2011, and the degree of clustering of human rabies cases decreased during that period. A total 480 clusters were detected by ST-DBSCAN, 89.4% clusters initiated before 2007. Most of clusters were mainly found in South of China. The number and duration of cluster decreased significantly after 2008. Areas with the highest density of human rabies cases varied spatially each year and in some areas remained with high outbreak density for several years. Though few places have recovered from human rabies, most of affected places are still suffering from the disease. Conclusion Human rabies in mainland China is geographically clustered and its spatial extent changed during 2005 to 2011. The results provide a scientific basis for public health authorities in China to improve human rabies control and prevention program.

Migration Patterns of Two Endangered Sympatric Species from a Remote Sensing Perspective

Giant pandas (Ailitropoda melanoleuca) and golden takin (Budorcas taxicolor bedfordi) are large mammals that occur together throughout the southern part of the Qin ling Mountains in China. Both species have the habit of altitudinal migration in a mixed forest-bamboo landscape. Although previous studies have reported that the migration patterns of giant pandas and golden takin seem different, little is known about these differences in relation to their food quality and quantity. We used radio-telemetry data from six giant pandas and three golden takin groups to determine whether differences in their migration patterns are related to satellite-derived plant phenology (a surrogate of food quality) and bamboo abundance (a surrogate of food quantity). Our results suggest that the altitudinal migration patterns of both the giant panda and the golden takin follow the phenological development of plants in the study area, and the difference between them seems to be attributable to the difference in the phenology of bamboo and non-bamboo plants, and thus the abundance and quality of food available to these two species.

Using a global reference sample set and a cropland map for area estimation in China

A technically transparent and freely available reference sample set for validation of global land cover mapping was recently established to assess the accuracies of land cover maps with multiple resolutions. This sample set can be used to estimate areas because of its equal-area hexagon-based sampling design. The capabilities of these sample set-based area estimates for cropland were investigated in this paper. A 30-m cropland map for China was consolidated using three thematic maps (cropland, forest and wetland maps) to reduce confusion between cropland and forest/wetland. We compared three area estimation methods using the sample set and the 30 m cropland map. The methods investigated were: (1) pixel counting from a complete coverage map, (2) direct estimation from reference samples, and (3) model-assisted estimation combining the map with samples. Our results indicated that all three methods produced generally consistent estimates which agreed with cropland area measured from an independent national land use dataset. Areas estimated from the reference sample set were less biased by comparing with a National Land Use Dataset of China (NLUD-C). This study indicates that the reference sample set can be used as an alternative source to estimate areas over large regions.

Patterns of Bacillary Dysentery in China, 2005–2010

Although the incidence of bacillary dysentery in China has been declining progressively, a considerable disease burden still exists. Few studies have analyzed bacillary dysentery across China and knowledge gaps still exist in the aspects of geographic distribution and ecological drivers, seasonality and its association with meteorological factors, urban-rural disparity, prevalence and distribution of Shigella species. Here, we performed nationwide analyses to fill the above gaps. Geographically, we found that incidence increased along an east-west gradient which was inversely related to the economic conditions of China. Two large endemically high-risk regions in western China and their ecological drivers were identified for the first time. We characterized seasonality of bacillary dysentery incidence and assessed its association with meteorological factors, and saw that it exhibits north-south differences in peak duration, relative amplitude and key meteorological factors. Urban and rural incidences among China’s cities were compared, and disparity associated with urbanization level was invariant in most cities. Balanced decrease of urban and rural incidence was observed for all provinces except Hunan. S. flexneri and S. sonnei were identified as major causative species. Increasing prevalence of S. sonnei and geographic distribution of Shigella species were associated with economic status. Findings and inferences from this study draw broader pictures of bacillary dysentery in mainland China and could provide useful information for better interventions and public health planning.

The distributions of the six species constituting the smooth newt species complex ( Lissotriton vulgaris sensu lato and L. montandoni ) – an addition to the New Atlas of Amphibians and Reptiles of Europe

The ‘smooth newt’, the taxon traditionally referred to as Lissotriton vulgaris , consists of multiple morphologically distinct taxa. Given the uncertainty concerning the validity and rank of these taxa, L. vulgaris sensu lato has often been treated as a single, polytypic species. A recent study, driven by genetic data, proposed to recognize five species, L. graecus , L. kosswigi , L. lantzi , L. schmidtleri and a more restricted L. vulgaris . The Carpathian newt L. montandoni was confirmed to be a closely related sister species. We propose to refer to this collective of six Lissotriton species as the smooth newt or Lissotriton vulgaris species complex. Guided by comprehensive genomic data from throughout the range of the smooth newt species complex we 1) delineate the distribution ranges, 2) provide a distribution database, and 3) produce distribution maps according to the format of the New Atlas of Amphibians and Reptiles of Europe, for the six constituent species. This allows us to 4) highlight regions where more research is needed to determine the position of contact zones.

No evidence that migratory geese disperse avian influenza viruses from breeding to wintering ground

Low pathogenic avian influenza virus can mutate to a highly pathogenic strain that causes severe clinical signs in birds and humans. Migratory waterfowl, especially ducks, are considered the main hosts of low pathogenic avian influenza virus, but the role of geese in dispersing the virus over long-distances is still unclear. We collected throat and cloaca samples from three goose species, Bean goose (Anser fabalis), Barnacle goose (Branta leucopsis) and Greater white-fronted goose (Anser albifrons), from their breeding grounds, spring stopover sites, and wintering grounds. We tested if the geese were infected with low pathogenic avian influenza virus outside of their wintering grounds, and analysed the spatial and temporal patterns of infection prevalence on their wintering grounds. Our results show that geese were not infected before their arrival on wintering grounds. Barnacle geese and Greater white-fronted geese had low prevalence of infection just after their arrival on wintering grounds in the Netherlands, but the prevalence increased in successive months, and peaked after December. This suggests that migratory geese are exposed to the virus after their arrival on wintering grounds, indicating that migratory geese might not disperse low pathogenic avian influenza virus during autumn migration.