Remote sensing-based time series models for malaria early warning in the highlands of Ethiopia

ABSTRACT: BACKGROUND: Malaria is one of the leading public health problems in most of sub-Saharan Africa, particularly in Ethiopia. Almost all demographic groups are at risk of malaria because of seasonal and unstable transmission of the disease. Therefore, there is a need to develop malaria early-warning systems to enhance public health decision making for control and prevention of malaria epidemics. Data from orbiting earth-observing sensors can monitor environmental risk factors that trigger malaria epidemics. Remotely sensed environmental indicators were used to examine the influences of climatic and environmental variability on temporal patterns of malaria cases in the Amhara region of Ethiopia. METHODS: In this study seasonal auto regressive integrated moving average (SARIMA) models were used to quantify the relationship between malaria cases and remotely sensed environmental variables, including rainfall, land-surface temperature (LST), vegetation indices (NDVI and EVI), and actual evapotranspiration (ETa) with lags ranging from one to three months. Predictions from the best model with environmental variables were compared to the actual observations from the last 12 months of the time series. RESULTS: Malaria cases exhibited positive associations with LST at a lag of one month and positive associations with indicators of moisture (rainfall, EVI and ETa) at lags from one to three months. SARIMA models that included these environmental covariates had better fits and more accurate predictions, as evidenced by lower AIC and RMSE values, than models without environmental covariates. CONCLUSIONS: Malaria risk indicators such as satellite-based rainfall estimates, LST, EVI, and ETa exhibited significant lagged associations with malaria cases in the Amhara region and improved model fit and prediction accuracy. These variables can be monitored frequently and extensively across large geographic areas using data from earth-observing sensors to support public health decisions.     

2000—2016年云南地区植被覆盖时空变化及其对水热因子的响应

基于2000-2016年MODIS-NDVI数据,利用趋势分析法以及线性相关分析等方法对云南地区植被月变化趋势、年际变化趋势进行详细分析;探讨植被覆盖变化与主要气候水热因子的关系。结果表明：研究区大部分地区植被覆盖良好,年NDVI的平均值为0.55,其中NDVI较高值（> 0.8）区域主要分布于南部,而西北部和中部城市地区NDVI值较低;自2000年开始,研究区NDVI总体呈显著（P < 0.05）增加趋势,年NDVI的变化斜率为0.0036,植被覆盖呈增加趋势的区域占研究区总面积79.80%;不同季节（春、夏、秋、冬）和生长季的植被状况均呈良性发展趋势;湿润指数和水热综合因子在滇西北与NDVI多呈负相关,在滇中地区以正相关为主;春、夏、秋3个季节NDVI受降水影响较大,而冬季NDVI则受气温影响较大;受降水影响较大的区域主要分布在中部和南部,受气温影响较大区域主要分布在滇西北、滇东北地区;NDVI在不同月份对气候因子的滞后时间存在差异,NDVI与当月气温的相关性强于与当月降水的相关性,植被生长对气温的响应无明显滞后效应,对降水存在3个月的滞后期。     

1982-2015年黄土高原NDVI时空演变及其对气候变化的季节响应

基于GIMMS NDVI、温度和降水数据,利用集合经验模态分解(EEMD)、线性回归分析、偏相关分析等方法分析了1982-2015年黄土高原植被覆盖时空变化及其对气候变化的季节响应。结果表明:年际变化趋势上,1982-2015年黄土高原生长季、春、夏、秋季NDVI均呈显著增长趋势,且各个季节NDVI增加速率逐年升高,尤其以夏季增加速率的变化最为明显;空间上,生长季、春、夏、秋季NDVI均呈由西北向东南递增的趋势,且在大部分地区呈显著上升趋势;线性回归表明,生长季、春、夏、秋季温度均呈显著上升趋势;生长季、秋季降水呈增加趋势,春、夏季降水呈减少趋势。EEMD分析进一步表明,生长季、春、夏、秋季温度均先升高后降低,降水均呈先减少后增加的趋势;空间变化趋势上,温度在生长季、春、夏、秋季大部分地区呈显著上升趋势,降水仅秋季有部分区域呈显著上升趋势;NDVI与温度在黄土高原东北部及西南部地区呈显著正相关,与降水在黄土高原北部及西北部地区呈显著正相关。     

黄土高原植被覆盖时空变化及其对气候因子的响应

为研究黄土高原地区退耕还林(草)后,植被覆盖变化及其对水热条件的响应,利用1999—2013年SPOT VGT NDVI 1km/10d分辨率数据,采用最大合成法、一元线性回归法和偏相关分析法,系统分析了黄土高原地区NDVI(归一化植被指数)的时空分布及变化趋势,及其与气候因子的关系。结果表明:黄土高原1999—2013年年最大NDVI的平均值为0.31,NDVI较高的区域位于黄土高原南部,而西北部植被覆盖度较低;自1999年开始,黄土高原地区NDVI呈极显著(P0.01)增加趋势,年最大NDVI的变化斜率为0.0099;不同季节(春、夏、秋、冬)和生长季的植被状况均呈现良性发展趋势;1998—2013年间,黄土高原地区气候呈现不显著的"冷湿化"特征;NDVI年际(及生长季和季节)变化与降雨和温度的相关性不显著,而在月时间尺度上,呈显著的相关性,并且月NDVI与当月降雨量的相关性要强于与当月温度的相关性;植被生长对温度的响应存在一个月的滞后期,而对降雨的响应无滞后效应。     

Population dynamics of two rodent species in agro-ecosystems of central Argentina: intra-specific competition,land-use,and climate effects

Understanding the role of feedback structure (endogenous processes) and exogenous (climatic and environmental) factors in shaping the dynamics of natural populations is a central challenge within the field of population ecology. We attempted to explain the numerical fluctuations of two sympatric rodent species in agro-ecosystems of central Argentina using Royama’s theoretical framework for analyzing the dynamics of populations influenced by exogenous climatic forces. We found that both rodent species show a first-order negative feedback structure, suggesting that these populations are regulated by intra-specific competition (limited by food, space, or enemy-free space). In Akodon azarae endogenous structure seems to be very strongly influenced by human land-use represented by annual minimum normalized difference vegetation index (NDVI), with spring and summer rainfall having little influence upon carrying capacity. Calomys venustus’ population dynamics, on the other hand, seem to be more affected by local climate, also with spring and summer rainfall influencing the carrying capacity of the environment, but combined with spring mean temperature. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Seasonal Acclimation of Stem Photosynthesis in Woody Legume Species from the Mojave and Sonoran Deserts of California

Photosynthesis (Pn) was measured in stems of two desert legumes, Caesalpinia virgata at a low elevation site (118 m) in the Sonoran Desert and Senna armata at a higher elevation (950 m) in the Mojave Desert. The lower elevation site experienced higher spring and summer temperatures than the higher elevation site, but the air vapor pressure, irradiance, and rainfall patterns were similar. Mid-morning maximum stem Pn was highest in May for C. virgata (7.8 [mu]mol m-2 s-1) and in July for S. armata (5.8 [mu]mol m-2 s-1). The seasonal variation in maximum stem Pn was not associated with changes in bulk tissue water potential or chlorenchyma tissue nitrogen concentration. The main environmental regulators of seasonal stem Pn were temperature and leaf to air vapor pressure gradient. Light-response curves indicated no major differences in apparent quantum yield or light compensation point between the spring and summer, but light-saturated stem Pn at ambient temperature decreased for C. virgata between these seasons. The optimal temperature for stem Pn remained the same for both species between the spring and the summer. However, stem Pn of both species increased at all temperatures between the spring and summer. Potential stem Pn under optimal conditions and CO2-saturated stem Pn increased for both species between spring and summer. The increase in stem Pn potential allowed these species to maintain stem Pn during the summer even though stem Pn responses to temperature and vapor pressure did not acclimate to seasonal climatic conditions.     

nter-annual Changes in Eurasian Continent NDVI and Its ensitivity to the Large-scale Climate Variations in the Last 20 Years

The influence of climate change on the terrestrial vegetation health (condition) is one of the most significant problems of global change study. The vegetation activity plays a key role in the global carbon cycle. The authors investigated the relationship of the advanced very high resolution radiometer-normalized difference vegetation index (AVHRR-NDVI) with the large-scale climate variations on the inter-annual time scale during the period 1982-2000 for the growing seasons (April-October). A singular value decomposition analysis was applied to the NDVI and surface air temperature data in the time-domain to detect the most predominant modes coupling them. The first paired-modes explain 60.9%, 39.5% and 24.6% of the squared covariance between NDVI and temperature in spring (April-May), summer (June-August), and autumn (September-October), respectively, which implies that there is the highest NDVI sensitivity to temperature in spring and the lowest in autumn. The spatial centers, as revealed by the maximum or minimum vector values corresponding to the leading singular values, indicate the high sensitive regions. Only considering the mode 1, the sensitive center for spring is located in western Siberia and the neighbor eastern Europe with a sensitivity of about 0.308 0 NDVI/℃. For summer, there are no predominantly sensitive centers, and on average for the relatively high center over 1000-1200 E by 450-600 N, the sensitivity is 0.248 0 NDVI/℃. For autumn, the center is located over the high latitudes of eastern Asia (1100-1400 E, 550-650 N), and the sensitivity is 0.087 5 NDVI/℃. The coherent patters as revealed by the singular decomposition analysis remain the same when coarser resolution NDVI data were used, suggesting a robust and stable climate/vegetation relationship.     

Effect of season on milk temperature,milk growth hormone,prolactin, and somatic cell counts of lactating cattle

Monthly fluctuations in milk temperature, somatic cell counts, milk growth hormone and prolactin of lactating cows were measured in milk samples over a 1 year period. The seasonal patterns in milk temperature, somatic cell count and milk prolactin concentration showed a positive trend with increasing environmental temperatures. Milk growth hormone concentration increased with lactation level and declined significantly during summer heat. Milk temperature and the measured hormonal levels may serve as indicators of the impact of the climatic environment on lactating cattle.     

基于MODIS数据的天山区域地表温度时空特征

基于2001-2013年MODIS地表温度产品及TM影像遥感解译的土地利用类型数据,对天山区域地表温度时空特征进行分析.结果表明: 2001-2013年,研究区地表平均温度达1.73 ℃,呈东高西低的特点,西北部分地区的地表温度年际变化幅度明显高于其他地区,局部地区在0.55 ℃以上;地表温度呈逐年缓慢增加趋势,增加率为0.147 ℃·a^-1,季节性差异明显,冬季地表温度波动幅度较大,变异系数达12.7%,地表温度的差异白天大于夜晚,夏季明显高于其他季节;不同土地利用类型的地表温度之间存在差异,与对应像元的归一化植被指数之间存在不同的拟合效果.随着植被盖度的增加,林地、草地地表温度下降明显,归一化植被指数每下降0.1时,林地和草地的地表温度降幅为3.74、5.04 ℃;受人为活动影响较多的城镇用地和农地的地表温度与归一化植被指数之间的敏感性高于其他土地利用类型.     

基于MODIS数据的天山区域地表温度时空特征

基于2001-2013年MODIS地表温度产品及TM影像遥感解译的土地利用类型数据,对天山区域地表温度时空特征进行分析.结果表明: 2001-2013年,研究区地表平均温度达1.73 ℃,呈东高西低的特点,西北部分地区的地表温度年际变化幅度明显高于其他地区,局部地区在0.55 ℃以上;地表温度呈逐年缓慢增加趋势,增加率为0.147 ℃·a^-1,季节性差异明显,冬季地表温度波动幅度较大,变异系数达12.7%,地表温度的差异白天大于夜晚,夏季明显高于其他季节;不同土地利用类型的地表温度之间存在差异,与对应像元的归一化植被指数之间存在不同的拟合效果.随着植被盖度的增加,林地、草地地表温度下降明显,归一化植被指数每下降0.1时,林地和草地的地表温度降幅为3.74、5.04 ℃;受人为活动影响较多的城镇用地和农地的地表温度与归一化植被指数之间的敏感性高于其他土地利用类型.     

Identifying the Environmental Conditions Favouring West Nile Virus Outbreaks in Europe

West Nile Virus (WNV) is a globally important mosquito borne virus, with significant implications for human and animal health. The emergence and spread of new lineages, and increased pathogenicity, is the cause of escalating public health concern. Pinpointing the environmental conditions that favour WNV circulation and transmission to humans is challenging, due both to the complexity of its biological cycle, and the under-diagnosis and reporting of epidemiological data. Here, we used remote sensing and GIS to enable collation of multiple types of environmental data over a continental spatial scale, in order to model annual West Nile Fever (WNF) incidence across Europe and neighbouring countries. Multi-model selection and inference were used to gain a consensus from multiple linear mixed models. Climate and landscape were key predictors of WNF outbreaks (specifically, high precipitation in late winter/early spring, high summer temperatures, summer drought, occurrence of irrigated croplands and highly fragmented forests). Identification of the environmental conditions associated with WNF outbreaks is key to enabling public health bodies to properly focus surveillance and mitigation of West Nile virus impact, but more work needs to be done to enable accurate predictions of WNF risk.     

基于MODIS NDVI的辽河保护区成立前后植被覆盖时空动态研究

以2010年成立以自然生态恢复为主的辽河保护区为研究对象,基于中分辨率成像光谱仪(MODIS)获取的500米分辨率的归一化植被指数(NDVI)数据,研究了辽河保护区成立前(2000—2009年)和成立后(2010—2015年)植被覆盖时空动态。结果表明:(1)2000—2015年NDVI呈现持续增加趋势;2000—2009年NDVI的年际增加主要发生在夏季,2010—2015年NDVI的年际增加主要发生在春季和冬季。辽河保护区成立后春季NDVI的逐年增加有利于该区域防风固沙功能的提升。(2)季节尺度上,2000—2009年春季降水量与春季和夏季NDVI显著正相关,夏季气温与夏季NDVI显著负相关;2010—2015年仅夏季NDVI动态受春季气温和夏季日照时数变化的影响。(3)月尺度上,气温是影响辽河保护区NDVI变化的主要气候因素,2000—2015年NDVI动态对气温变化的响应存在1个月的滞后期;2000—2009年NDVI动态对降水变化的响应存在1个月的滞后期,2010—2015年则无滞后效应。(4)2000—2009年影响NDVI动态的人类活动主要为农田耕作;辽河保护区成立后,河岸带封育区内的自然恢复和小型人工湿地建设促进了NDVI增加,大型人工湿地建设和人工经营牧草地对NDVI动态无显著影响。     

Seasonal dynamics of the helminths of bluegill (Lepomis macrochirus) in a subtropical region

Seasonal prevalence and abundance of the helminths of bluegill sunfish in a Louisiana oligohaline bayou were measured by a survey and a field "live-box" experiment. The survey took place from the spring of 1997 to the summer of 1998 and examined fish that were <7 cm. Three trematode species, Phagicola nana (Heterophyidae), Ascocotyle tenuicollis (Heterophyidae), and Posthodiplostomum minimum (Diplostomatidae), and 2 nematode species, Camallanus oxycephalus (Camallanidae) and Spinitectus carolini (Cystidicolidae), were examined. Camallanus oxycephalus was the only helminth that showed a distinct seasonal pattern. Abundance and prevalence peaked in summer, which was likely driven by concerted reproductive cycles of females. The survey data indicated that the other helminths fluctuated over time but did not seem to follow a distinct seasonal pattern. The fluctuations could be attributed to the variable nature of the habitat or to the stochastic events that influence transmission dynamics, particularly isolated events such as tropical storms, which cause dramatic changes in salinity. The live-box experiment successfully measured recruitment of A. tenauicollis and suggested a seasonal component of the distribution of this species, which was possibly caused by temperature-dependent emergence of cercariae from the snail intermediate host.     

Climate change impacts on West Nile virus transmission in a global context

West Nile virus (WNV), the most widely distributed virus of the encephalitic flaviviruses, is a vector-borne pathogen of global importance. The transmission cycle exists in rural and urban areas where the virus infects birds, humans, horses and other mammals. Multiple factors impact the transmission and distribution of WNV, related to the dynamics and interactions between pathogen, vector, vertebrate hosts and environment. Hence, among other drivers, weather conditions have direct and indirect influences on vector competence (the ability to acquire, maintain and transmit the virus), on the vector population dynamic and on the virus replication rate within the mosquito, which are mostly weather dependent. The importance of climatic factors (temperature, precipitation, relative humidity and winds) as drivers in WNV epidemiology is increasing under conditions of climate change. Indeed, recent changes in climatic conditions, particularly increased ambient temperature and fluctuations in rainfall amounts, contributed to the maintenance (endemization process) of WNV in various locations in southern Europe, western Asia, the eastern Mediterranean, the Canadian Prairies, parts of the USA and Australia. As predictions show that the current trends are expected to continue, for better preparedness, any assessment of future transmission of WNV should take into consideration the impacts of climate change.     

青藏高原草地植被覆盖变化及其与气候因子的关系

为揭示气候变化对青藏高原草地生态系统的影响及其生态适应机制,利用1982~1999年间的NOAA/AVHRR NDVI数据和对应的气候资料,研究了近20年来青藏高原草地植被覆盖变化及其与气候因子的关系。结果表明,18年来研究区生长季NDVI显著增加(p=0.015),其增加率和增加量分别为0.41% a^-1和0.001 0 a^-1。生长季提前和生长季生长加速是青藏高原草地植被生长季NDVI增加的主要原因。春季为NDVI增加率和增加量最大的季节,其增加率和增加量分别为0.92% a^-1和0.001 4 a^-1;夏季NDVI的增加对生长季NDVI增加的贡献相对较小,其增加率和增加量分别为0.37% a^-1和0.001 0 a^-1。3种草地(高寒草甸、高寒草原、温性草原)春季NDVI均显著增加(p<0.01;p=0.001; p=0.002); 高寒草甸夏季NDVI显著增加(p=0.027),而高寒草原和温性草原夏季NDVI呈增加趋势,但都不显著(p=0.106; p=0.087);3种草地秋季NDVI则没有明显的变化趋势(p=0.585; p=0.461; p=0.143)。3种草地春季NDVI的增加是由春季温度上升所致。高寒草地(高寒草甸和高寒草原)夏季NDVI的增加是夏季温度和春季降水共同作用的结果。温性草原夏季NDVI变化与气候因子并没有表现出显著的相关关系。高寒草地植被生长对气候变化的响应存在滞后效应。     

Seasonally different response of photosynthetic activity to daytime and night‐time warming in the Northern Hemisphere

Over the last century the Northern Hemisphere has experienced rapid climate warming, but this warming has not been evenly distributed seasonally, as well as diurnally. The implications of such seasonal and diurnal heterogeneous warming on regional and global vegetation photosynthetic activity, however, are still poorly understood. Here, we investigated for different seasons how photosynthetic activity of vegetation correlates with changes in seasonal daytime and night‐time temperature across the Northern Hemisphere (>30°N), using Normalized Difference Vegetation Index (NDVI) data from 1982 to 2011 obtained from the Advanced Very High Resolution Radiometer (AVHRR). Our analysis revealed some striking seasonal differences in the response of NDVI to changes in day‐ vs. night‐time temperatures. For instance, while higher daytime temperature (T_max) is generally associated with higher NDVI values across the boreal zone, the area exhibiting a statistically significant positive correlation between T_max and NDVI is much larger in spring (41% of area in boreal zone – total area 12.6 × 10⁶ km²) than in summer and autumn (14% and 9%, respectively). In contrast to the predominantly positive response of boreal ecosystems to changes in T_max, increases in T_max tended to negatively influence vegetation growth in temperate dry regions, particularly during summer. Changes in night‐time temperature (T_min) correlated negatively with autumnal NDVI in most of the Northern Hemisphere, but had a positive effect on spring and summer NDVI in most temperate regions (e.g., Central North America and Central Asia). Such divergent covariance between the photosynthetic activity of Northern Hemispheric vegetation and day‐ and night‐time temperature changes among different seasons and climate zones suggests a changing dominance of ecophysiological processes across time and space. Understanding the seasonally different responses of vegetation photosynthetic activity to diurnal temperature changes, which have not been captured by current land surface models, is important for improving the performance of next generation regional and global coupled vegetation‐climate models.     

A Bayesian-based approach for spatio-temporal modeling of county level prevalence of Schistosoma japonicum infection in Jiangsu province, China

Spatio-temporal variations of Schistosoma japonicum infection risk in Jiangsu province, China, were examined and the relationships between key climatic factors and infection prevalence at the county level were determined. The parasitological data were collected annually by means of cross-sectional surveys carried out in 47 counties from 1990 to 1998. Climatic factors, namely land surface temperature (LST) and normalized difference vegetation index (NDVI), were obtained from remote sensing satellite sensors. Bayesian spatio-temporal models were employed to analyze the data. The best fitting model showed that spatial autocorrelation in Jiangsu province decreased dramatically from 1990 to 1992 and increased gradually thereafter. A likely explanation of this finding arises from the large-scale administration of praziquantel for morbidity control of schistosomiasis. Our analysis suggested a negative association between NDVI and risk of S. japonicum infection. On the other hand, an increase in LST contributed to a significant increase in S. japonicum infection prevalence. We conclude that combining geographic information system, remote sensing and Bayesian-based statistical approaches facilitate integrated risk modeling of S. japonicum, which in turn is of relevance for allocation of scarce resources for control of schistosomiasis japonica in Jiangsu province and elsewhere in China, where the disease remains of public health and economic significance.     

宁夏近20年来植被覆盖度及其与气温降水的关系

利用1981—2004年的植被指数(NDVI)资料,结合实地植被调查资料,将宁夏植被类型划分4个区域,确定了各地植被指数与覆盖度的关系,分析了宁夏各区域植被覆盖度的年际变化、季节变化、植被覆盖度的面积变化及其与气温和降水量的关系。结果表明:24年来宁夏贺兰山与贺兰山东麓的年植被覆盖度呈下降趋势,中部干旱带植被覆盖度呈上升趋势;近4年来,贺兰山植被状况整体变好;贺兰山东麓植被状况整体变差;中部干旱带的植被状况夏季变差,秋季变好;南部山区的植被覆盖度整体变好。宁夏春夏季降水量是影响植被覆盖度的关键性因子,气温对植被覆盖度的影响不显著。     

Does climate determine broad‐scale patterns of species richness? A test of the causal link by natural experiment

Aim Broad‐scale spatial patterns of species richness are very strongly correlated with climatic variables. If there is a causal link, i.e. if climate directly or indirectly determines patterns of richness, then when the climatic variables change, richness should change in the manner that spatial correlations between richness and climate would predict. The present study tests this prediction using seasonal changes in climatic variables and bird richness. Location We used a grid of equal area quadrats (37 000 km²) covering North and Central America as far south as Nicaragua. Methods Summer and winter bird distribution data were drawn from monographs and field guides. Climatic data came from published sources. We also used remotely sensed NDVI (normalized difference vegetation index — a measure of greenness). Results Bird species richness changes temporally (between summer and winter) in a manner that is close to, but statistically distinguishable from, the change one would predict from models relating the spatial variation in richness at a single time to climatic variables. If one further takes into account the seasonal changes in NDVI and within‐season variability of temperature and precipitation, then winter and summer richness follow congruent, statistically indistinguishable patterns. Main conclusions Our results are consistent with the hypothesis that climatic variables (temperature and precipitation) and vegetation cover directly or indirectly influence patterns of bird species richness.