Showing papers by "Xiangming Xiao published in 2013"

Green-up dates in the Tibetan Plateau have continuously advanced from 1982 to 2011

Abstract: As the Earth's third pole, the Tibetan Plateau has experienced a pronounced warming in the past decades. Recent studies reported that the start of the vegetation growing season (SOS) in the Plateau showed an advancing trend from 1982 to the late 1990s and a delay from the late 1990s to 2006. However, the findings regarding the SOS delay in the later period have been questioned, and the reasons causing the delay remain unknown. Here we explored the alpine vegetation SOS in the Plateau from 1982 to 2011 by integrating three long-term time-series datasets of Normalized Difference Vegetation Index (NDVI): Global Inventory Modeling and Mapping Studies (GIMMS, 1982-2006), SPOT VEGETATION (SPOT-VGT, 1998-2011), and Moderate Resolution Imaging Spectroradiometer (MODIS, 2000-2011). We found GIMMS NDVI in 2001-2006 differed substantially from SPOT-VGT and MODIS NDVIs and may have severe data quality issues in most parts of the western Plateau. By merging GIMMS-based SOSs from 1982 to 2000 with SPOT-VGT-based SOSs from 2001 to 2011 we found the alpine vegetation SOS in the Plateau experienced a continuous advancing trend at a rate of similar to 1.04 d.y(-1) from 1982 to 2011, which was consistent with observed warming in springs and winters. The satellite-derived SOSs were proven to be reliable with observed phenology data at 18 sites from 2003 to 2011; however, comparison of their trends was inconclusive due to the limited temporal coverage of the observed data. Longer-term observed data are still needed to validate the phenology trend in the future.

Predicting hotspots for influenza virus reassortment.

Abstract: The 1957 and 1968 influenza pandemics, each of which killed ≈1 million persons, arose through reassortment events. Influenza virus in humans and domestic animals could reassort and cause another pandemic. To identify geographic areas where agricultural production systems are conducive to reassortment, we fitted multivariate regression models to surveillance data on influenza A virus subtype H5N1 among poultry in China and Egypt and subtype H3N2 among humans. We then applied the models across Asia and Egypt to predict where subtype H3N2 from humans and subtype H5N1 from birds overlap; this overlap serves as a proxy for co-infection and in vivo reassortment. For Asia, we refined the prioritization by identifying areas that also have high swine density. Potential geographic foci of reassortment include the northern plains of India, coastal and central provinces of China, the western Korean Peninsula and southwestern Japan in Asia, and the Nile Delta in Egypt.

Migration strategies of Swan Geese Anser cygnoides from northeast Mongolia

Abstract: In 2006–2008, 25 Swan Geese Anser cygnoides were marked with solar-powered GPS satellite transmitters in northeast Mongolia to examine the timing and pathways of their migration Most geese began their autumn migration in August, flying southeast toward a staging area at the Yalu River Estuary on the China-North Korea border After staging for several weeks, the Swan Geese continued to their wintering grounds at wetlands along the Yangtze River Basin of eastern China in December Spring migration commenced in late February, and the birds following either a same-route or loop migration to arrive at the breeding grounds in mid April Swan Geese used a larger number of staging areas for a longer duration when they were north of 42°N latitude; they seemed to avoid staging for extended periods in the highly urbanised areas of eastern China Further research should examine threats and disturbances to the geese in relation to human population growth and increasing urbanisation

Impacts of ecological restoration projects on agricultural productivity in China

Abstract: The changes in cropland quantity and quality due to land use are critical concerns to national food security, particularly for China. Despite the significant ecological effects, the ecological restoration program (ERP), started from 1999, has evidently altered the spatial patterns of China’s cropland and agricultural productivity. Based on cropland dynamic data from 2000 to 2008 primarily derived from satellite images with a 30-m resolution and satellite-based net primary productivity models, we identified the impacts on agricultural productivity caused by ERP, including “Grain for Green” Program (GFGP) and “Reclaimed Cropland to Lake” (RCTL) Program. Our results indicated that the agricultural productivity lost with a rate of 132.67×104 t/a due to ERP, which accounted for 44.01% of the total loss rate caused by land use changes during 2000–2005. During 2005–2008, the loss rate due to ERP decreased to 77.18×104 t/a, which was equivalent to 58.17% of that in the first five years and 30.22% of the total loss rate caused by land use changes. The agricultural productivity loss from 2000–2008 caused by ERP was more attributed to GFGP (about 70%) than RCTL. Although ERP had a certain influence on cropland productivity during 2000–2008, its effect was still much less than that of urbanization; moreover, ERP was already converted from the project implementation phase to the consolidation phase.

Modelling gross primary production in semi-arid Inner Mongolia using MODIS imagery and eddy covariance data

Abstract: We evaluate the modelling of carbon fluxes from eddy covariance EC tower observations in different water-limited land-cover/land-use LCLU and biome types in semi-arid Inner Mongolia, China. The vegetation photosynthesis model VPM and modified VPM MVPM, driven by the enhanced vegetation index EVI and land-surface water index LSWI, which were derived from the Moderate Resolution Imaging Spectroradiometer MODIS surface-reflectance product MOD09A1, were used to model and validate the temporal changes in gross primary production GPP from the EC towers during the 2006 and 2007 growing seasons. The annual GPP predicted by the VPM model GPPVPM was predicted reasonably well in 2006 and 2007 at the cropland coefficient of determination, R 2 = 0.67 and 0.71, for 2006 and 2007, respectively and typical steppe R 2 = 0.80 and 0.73 sites. The predictive power of the VPM model varied in the desert steppe, which includes an irrigated poplar stand R 2 = 0.74 and 0.68 and shrubland R 2 = 0.31 and 0.49 sites. The comparison between GPP obtained from the eddy covariance tower GPPtower and GPP obtained from MVPM GPPMVPM predicted GPP showed good agreement for the typical steppe site of Xilinhaote R 2 = 0.84 and 0.70 in 2006 and 2007, respectively and for the Duolun steppe site R 2 = 0.63 and cropland site R 2 = 0.63 in 2007. The predictive power of the MVPM model decreased slightly in the desert steppe at the irrigated poplar stand R 2 = 0.56 and 0.47 in 2006 and 2007 respectively and the shrubland R 2 = 0.20 and 0.41. The results of this study demonstrate the feasibility of modelling GPP from EC towers in semi-arid regions.

Reply to Wang et al.: Snow cover and air temperature affect the rate of changes in spring phenology in the Tibetan Plateau

Abstract: We appreciate the comments on our recent study (1) from Wang et al. (2). Our study showed that the start of the growing season (SOS), derived from analysis of Normalized Difference Vegetation Index (NDVI), continued to advance in the Tibetan Plateau (TP) from 1982 to 2011. Wang et al. (2) agreed with this conclusion but stated that the SOS advancement rate could be overestimated after comparison with a few in situ herbaceous observations ca. 1990–2003 (3). As we discussed earlier (1), there are limited in situ long-term data to evaluate the rate of SOS advancement in the TP. Another study that used longer observations (ca. 1987–2007) at the same sites (3) reported a higher rate of SOS advancement (4). In addition, our results also showed that the rates of SOS advancement during 2000–2011 varied dependent upon the dataset used, for example, 13.5 d per decade for Systeme Pour l’Observation de la Terre vegetation (SPOT-VGT), and 7.8 d per decade for Moderate Resolution Imaging Spectroradiometer (MODIS) (1). Therefore, it remains challenging to quantify the rate of SOS advancement from remote sensing datasets.

Climate change affecting temperature and aridity zones: a case study in Eastern Inner Mongolia, China from 1960–2008

Abstract: Recent climate change is substantially affecting the spatial pattern of geographical zones, and the temporal and spatial inconsistency of climatic warming and drying patterns contributes to the complexity of the shifting of temperature and aridity zones. Eastern Inner Mongolia, China, located in the interface region of different biomes and ecogeographic zones, has experienced dramatic drying and warming over the past several decades. In this study, the annual accumulated temperature above 10 °C (AAT10) and the aridity index, two key indicators in geographical regionalization, are used to assess warming and drying processes and track the movements of temperature and aridity zones from 1960 to 2008. The results show a significant warming at the regional level from 1960 to 2008 with an AAT10 increase rate of 7.89 °C·d/year (p < 0.001) in Eastern Inner Mongolia, while the drying trend was not significant during this period. Spatial heterogeneity of warming and drying distributions was also evident. Analysis of warming and drying via piecewise regression revealed two separate, specific trends between the first 31 years (1960–1990) and the subsequent 18 years (1991–2008). Generally, mild warming and very slight wetting occurred prior to 1990, while after 1991 both warming and drying were significant and enhanced. Continuous warming drove a northward shift of temperature zones from the 1960s to 2000s, while aridity zones displayed enhanced temporal and spatial variability. Climate change effects on temperature and aridity zones imply that the patterns of cropping systems, macro-ecosystems, and human land use modes are potentially undergoing migration and modification due to climate change.

Rivers and flooded areas identified by medium-resolution remote sensing improve risk prediction of the highly pathogenic avian influenza H5N1 in Thailand.

Abstract: Thailand experienced several epidemic waves of the highly pathogenic avian influenza (HPAI) H5N1 between 2004 and 2005. This study investigated the role of water in the landscape, which has not been previously assessed because of a lack of high-resolution information on the distribution of flooded land at the time of the epidemic. Nine Landsat 7 - Enhanced Thematic Mapper Plus scenes covering 174,610 km(2) were processed using k-means unsupervised classification to map the distribution of flooded areas as well as permanent lakes and reservoirs at the time of the main epidemic HPAI H5N1 wave of October 2004. These variables, together with other factors previously identified as significantly associated with risk, were entered into an autologistic regression model in order to quantify the gain in risk explanation over previously published models. We found that, in addition to other factors previously identified as associated with risk, the proportion of land covered by flooding along with expansion of rivers and streams, derived from an existing, sub-district level (administrative level no. 3) geographical information system database, was a highly significant risk factor in this 2004 HPAI epidemic. These results suggest that water-borne transmission could have partly contributed to the spread of HPAI H5N1 during the epidemic. Future work stemming from these results should involve studies where the actual distribution of small canals, rivers, ponds, rice paddy fields and farms are mapped and tested against farm-level data with respect to HPAI H5N1.

Metapopulation dynamics enable persistence of influenza A, including A/H5N1, in poultry.

Abstract: Highly pathogenic influenza A/H5N1 has persistently but sporadically caused human illness and death since 1997. Yet it is still unclear how this pathogen is able to persist globally. While wild birds seem to be a genetic reservoir for influenza A, they do not seem to be the main source of human illness. Here, we highlight the role that domestic poultry may play in maintaining A/H5N1 globally, using theoretical models of spatial population structure in poultry populations. We find that a metapopulation of moderately sized poultry flocks can sustain the pathogen in a finite poultry population for over two years. Our results suggest that it is possible that moderately intensive backyard farms could sustain the pathogen indefinitely in real systems. This fits a pattern that has been observed from many empirical systems. Rather than just employing standard culling procedures to control the disease, our model suggests ways that poultry production systems may be modified.

Reply to Shen et al.: No evidence to show nongrowing season NDVI affects spring phenology trend in the Tibetan Plateau over the last decade

Abstract: We appreciate the comments on our article (1) from Shen et al. (2). They raise the issue of whether the nongrowing season (NGS) Normalized Difference Vegetation Index (NDVI) could affect spring phenology as interpreted from time series NDVI data. To address it, they compared the NGS NDVIs of two separate periods (1998–2000 and 2009–2011) and found a higher 2009–2011 NGS NDVI than that of 1998–2000, which was considered to negatively (e.g., advanced) bias retrieved spring phenology results [figure 1 A and B in the letter (2)]. We found that the NGS NDVI increase from 1998–2000 to 2009–2011 was overused to represent the trend from 1998 to 2011 because of the effects of outliers in 1998 and 2000 (Fig. 1A). We used snow depth data derived from passive microwave remote sensing for the studied area (3) and found that snow depth from January to April was significantly higher in 1998 and 2000 (Fig. 1B). The El Nino Southern Oscillation (ENSO) event resulted in the most severe snow storm in the 1997/1998 winter across the Tibetan Plateau (4), which led to lower NGS NDVI from January to April in 1998. The La Nina in year 1999/2000 also resulted in big snow and lower NGS NDVI on the plateau in 2000 (Fig. 1B). Actually, the trends of the NDVIs in February, March, and April were not statistically significant when we removed the outliers in 1998 and 2000 (Fig. 1C). January NDVI increasing was significant. However, it will not affect start of the vegetation growing season (SOS) retrieval because all of the green-up dates happened after March on the plateau.

Magnetic anisotropy in Fe films epitaxied by thermal deposition and pulse laser deposition on GaAs(001)

Abstract: The in-plane magnetic anisotropy of Fe films fabricated with thermal deposition (TD) and pulse laser deposition (PLD) techniques on GaAs(001) substrate was studied quantitatively. The volume anisotropy in TD Fe film is attributed to the constant strain anisotropy, supported by reflection high-energy electron diffraction analysis. The PLD growth was found to deeply influence the interface anisotropy at Fe/GaAs interface even through a 30 ML Fe TD underlayer. The volume anisotropy was found to exist in TD Fe film even grown on top of a PLD film. Our study indicates that the uniaxial magnetic anisotropy in Fe/GaAs(001) system can be controlled by a combination of TD and PLD growth.

Distribution and dynamics of risk factors associated with highly pathogenic avian influenza H5N1

Abstract: Within China's Poyang Lake region, close interactions between wild migratory birds and domestic poultry are common and provide an opportunity for the transmission and subsequent outbreaks of highly pathogenic avian influenza (HPAI) virus. We overlaid a series of ecological factors associated with HPAI to map the risk of HPAI in relation to natural and anthropogenic variables, and we identified two hotspots for potential HPAI outbreaks in the Poyang Lake region as well as three corridors connecting the two hotspot areas. In hotspot I, there is potential for migratory birds to bring new avian influenza (AI) strains that can reassort with existing strains to form new AI viruses. Hotspot II features high-density poultry production where outbreaks of endemic AI viruses are likely. The three communication corridors that link the two hotspots further promote HPAI H5N1 transmission and outbreaks and lead to the persistence of AI viruses in the Poyang Lake region. We speculate that the region's unevenly distributed poultry supply-and-demand system might be a key factor inducing HPAI H5N1 transmission and outbreaks in the Poyang Lake region.

Role of geoinformatics in ensuing global food security with special reference to dryland agro-ecosystems

Abstract: Agriculture plays an important role in providing food security in developing countries. Better agricultural information is one of the key factors in understanding current trends and status that determine food security from local to global scales. Open-access policies for sharing geospatial information and technology are becoming an integral part of solving the food security equation. Geospatial technologies (remote sensing, global positioning system and geographical information system) have progressed rapidly in the 21st century, and will keep expanding to provide powerful tools in almost every aspect of food security, including research, development and aid delivery programs, policy, and outreach. Recent advances in Geoinformatics have created new opportunities to apply to agro-ecosystems research. The International Center for Agricultural Research in Dry Areas (ICARDA) is one of the research centers of the Consultative Group on International Agricultural Research (CGIAR). ICARDA works closely with national agricultural research programs and partners worldwide to develop new technological solutions to improve dryland agriculture and productivity to provide food security while protecting fragile ecosystems in those countries. It also leads the CGIAR Research Program (CRP) on Dryland Systems, which targets the poor and highly vulnerable populations of the dry areas. The CRP on Dryland Systems aims to develop technology, policy, and institutional innovations to improve food security and livelihoods using an integrated systems approach. The proposed presentation highlights the role of the Geoinformatics in ensuring global food security with special references to dryland agro-ecosystems.