Harmful algal bloom forecast system for SW Ireland. Part II: Are operational oceanographic models useful in a HAB warning system

This study investigated the application of a three-dimensional physical hydrodynamic model in a harmful algal bloom forecast system for Bantry Bay, southwest Ireland. Modelled oceanographic conditions were studied and used to help understand observed changes in the chemical and biological patterns from the national biotoxins and phytoplankton monitoring program. The study focused on two toxic events in 2013. An upwelling event was predicted by the model prior to the appearance and population increase of potentially toxic diatoms, Pseudo-nitzschia, and associated domoic acid in shellfish. A downwelling episode was provided as a forecast in the model prior to the arrival of a Dinophysis bloom and detection of its associated biotoxins in Bay shellfish. The modelled forecast products developed included expected surface, mid-depth and bottom current pathways at the mouth of the Bay and on the adjacent shelf. The rate and direction of water volume flow at the mouth and mid-bay sections were produced by the model to examine predicted upwelling and downwelling pulses. The model also calculated the evolution of water properties (temperature, salinity and density) with depth along the Bay axis and on the adjacent continental shelf. Direct measurements of water properties at a fixed point, mid-bay, were comparable to model calculations. The operational model for southwest Ireland produces a reliable 3-day physical hydrodynamic forecast of the dominant regional physical processes that result in water exchange events between Bantry Bay and its adjacent shelf. While simulated physical hydrodynamics were provided as a 3-day forecast, the upwelling and downwelling signals from the model, closely linked to toxic HAB episodes, were evident up to 10 days prior to the contamination of shellfish in the Bay.     

Some meteorological conditions associated with forest fires in Galicia (Spain)

The present paper offers data on the effect of certain meteorological parameters on the outbreak of forest fires in Galicia (Spain). In a day-to-day analysis, the values of the stability of the air column and the saturation deficit at the lower levels are related to the number of fires occurring in the following 24 h.     

Avoidable errors in the modelling of outbreaks of emerging pathogens, with special reference to Ebola

As an emergent infectious disease outbreak unfolds, public health response is reliant on information on key epidemiological quantities, such as transmission potential and serial interval. Increasingly, transmission models fit to incidence data are used to estimate these parameters and guide policy. Some widely used modelling practices lead to potentially large errors in parameter estimates and, consequently, errors in model-based forecasts. Even more worryingly, in such situations, confidence in parameter estimates and forecasts can itself be far overestimated, leading to the potential for large errors that mask their own presence. Fortunately, straightforward and computationally inexpensive alternatives exist that avoid these problems. Here, we first use a simulation study to demonstrate potential pitfalls of the standard practice of fitting deterministic models to cumulative incidence data. Next, we demonstrate an alternative based on stochastic models fit to raw data from an early phase of 2014 West Africa Ebola virus disease outbreak. We show not only that bias is thereby reduced, but that uncertainty in estimates and forecasts is better quantified and that, critically, lack of model fit is more readily diagnosed. We conclude with a short list of principles to guide the modelling response to future infectious disease outbreaks.     

农村地区慢性病流行现状及控制管理对策分析

慢性病严重危害人群健康,已成为疾病负担的主要原因。本文通过三间分布（人群分布、地区分布、时间分布）发现,我国农村地区慢性病患病率随年龄增加而增高;发病年龄提前;年龄越小,增幅越大;不同的慢性病在性别间呈现不同的发病趋势;农村居民现代医学知识缺乏,健康意识淡薄,对慢性病的知晓率、治疗率和控制卒低;农村地区经济收入低,医疗保障差,慢性病会对其经济上造成沉重的负担;农村的慢性病患病率增长已经快于城市,且在死因顺位中上升。针对目前我国农村地区慢性痛的这些流行现状,进一步分析了农村地区慢性病防治存在的主要问题,并提出了控制对策及管理方法。     

2003年稻纵卷叶螟重大迁入过程的大气动力机制分析

为了探明稻纵卷叶螟灾变性迁入的大气动力学机制,本研究在ArcGIS中对2003年我国稻纵卷叶螟的时空分布规律进行了简要的地学分析。在此基础上,选取了有典型意义的重大迁入过程2个,从PCVSATTM接收系统中调取覆盖各迁飞过程的实测气象数据和T213数值预报产品,输入MM5中尺度数值预报模式对迁飞和降落期间的大气动力场进行了数值模拟和客观分析。结果表明：（1）用850 hPa和925 hPa高度风向来分别描述稻纵卷叶螟北迁和南迁主迁飞层种群迁移的方向是比较合适的。北迁时,从源地到迁入地之间有比较一致的偏南气流;南迁时,从源地到迁入地之间则有相对均一的偏北气流。水平风场上的气旋式曲率区有利于害虫的起飞迁出,反气旋式曲率区则有利于其迁入降落。（2）垂直气流场中下沉气流的推动作用是稻纵卷叶螟迁入和降落的最直接大气动力机制,当稻纵卷叶螟迁入某一即将危害的稻区时,其降落前36～12 h以内的850 hPa等压面上常表现为相对强而宽广的下沉气流区。（3）在稻纵卷叶螟迁入与为害前36～12 h内的高空850 hPa和925 hPa散度场上,降虫区上空对应着比较一致的高值正散度区,表明有较强的下沉气流存在,这对降虫十分有利。（4）850 hPa、925 hPa等压面上的水平流场、垂直气流场和散度场的特征分布对预测稻纵卷叶螟的迁入和降落具有很好的指示意义。     

基于多源遥感数据的景观格局及预测研究

以TM、中巴资源卫星和环境与灾害监测预报小卫星等遥感影像为数据源,利用ENVI 4.7、ARCGIS 9.2、IDRISI 15等软件,研究了西安市辖区的景观特征与空间格局,预测了未来的景观变化,提出了景观格局预测的数据转化和多距离空间分析的精简步骤.结果表明:研究区的景观本底是一个由林地和耕地构成的复合景观基质,建设用地在研究时段内呈现持续增加趋势,且2004-2011年间的增加量高于2000-2004年间的增加量;林地面积略有降低,林地和草地总面积略呈增长趋势,水域和未利用地面积变化较小.研究时段内的景观破碎化程度在降低,林地景观的连通性增强了,耕地的降低了.各景观类型在所设定的最大预期研究尺度下均呈现显著的聚集空间格局;各年和各景观类型之间的聚集、随机和离散的临界阈值差别相对比较大;水域和未利用地的空间聚集强度明显高于耕地、林地、草地和城乡建设用地;耕地和草地空间分布存在一个异质性最大的特征尺度,且均出现了聚集分布、随机分布和离散分布3种分布格局,以2011年最为明显.利用景观指数法和多距离空间聚类分析方法研究景观格局特征的效果要比单一的景观指数法较理想.CA-Markov模型模拟的结果基本能够反映未来的景观格局状况.     

Teleconnection between the early immigration of brown planthopper (Nilaparvata lugens St?l) and ENSO indices: implication for its medium- and long-term forecast

Teleconnection between the early immigration of brown planthopper (BPH) and El Nino/Southern Oscillation (ENSO) indices from January of two years previously to the current June was investigated to make long-term forecast. The teleconnection results were as follows: ENSO indices which were significantly correlated with the early immigration of BPH were primarily sea surface temperature anomalies (SSTA) in N3, N4 and N3.4 regions, accounting for 71.8% of the total. Significant ENSO indices from two years and one year before the immigration events had a proportion of about 84%, while those in the current year only accounted for 16.7%. There was significantly negative correlation between the early immigration of BPH and SSTA in each Nino region from two years before to the previous spring, whereas there was significantly positive correlation between these two factors during the period from the previous winter to the current spring. The significant correlation between the early immigration of BPH and SSTA in each Nino region in the last summer and autumn did not show any obvious tendencies. The relationship between the southern oscillation index (SOI) and the early immigration of BPH was opposite to that between the immigration and SSTA in each Nino region. The above mentioned significant ENSO indices were used as key factors to build forecasting models for the early immigration of BPH by step-wise multiple linear regression analysis. Finally, 12 integrated forecasting models were obtained, which could make predictions 3–27 months ahead and had a predictive accuracy of 88.9%.     

Teleconnection between the early immigration of brown planthopper (Nilaparvata lugens Stål) and ENSO indices: implication for its medium- and long-term forecast

Teleconnection between the early immigration of brown planthopper (BPH) and El Nino/Southern Oscillation (ENSO) indices from January of two years previously to the current June was investigated to make long-term forecast. The teleconnection results were as follows: ENSO indices which were significantly correlated with the early immigration of BPH were primarily sea surface temperature anomalies (SSTA) in N3, N4 and N3.4 regions, accounting for 71.8% of the total. Significant ENSO indices from two years and one year before the immigration events had a proportion of about 84%, while those in the current year only accounted for 16.7%. There was significantly negative correlation between the early immigration of BPH and SSTA in each Nino region from two years before to the previous spring, whereas there was significantly positive correlation between these two factors during the period from the previous winter to the current spring. The significant correlation between the early immigration of BPH and SSTA in each Nino region in the last summer and autumn did not show any obvious tendencies. The relationship between the southern oscillation index (SOI) and the early immigration of BPH was opposite to that between the immigration and SSTA in each Nino region. The above mentioned significant ENSO indices were used as key factors to build forecasting models for the early immigration of BPH by step-wise multiple linear regression analysis. Finally, 12 integrated forecasting models were obtained, which could make predictions 3–27 months ahead and had a predictive accuracy of 88.9%.     

模糊综合评判法在斜纹夜蛾预测预报上的应用

通过分析多年斜纹夜蛾灯下虫量、田间虫量以及气象资料,采用模糊综合评判的原理和方法,组建了斜纹夜蛾发生量模糊综合评判模型。应用该模型对2006年和2007年斜纹夜蛾田间发生量进行预测,预测结果与田间发生实况基本相符。     

人类周期性活动对物种多样性的影响及其预测

人类活动通过作用于栖息地而影响着物种的种群动态,从而影响着物种多样性的变化。首次提出了不同时间尺度人类周期性活动干扰下的多物种竞争动力模式,模拟了千年时间尺度,物种多样性对人类周期性活动的响应过程,开展了人类周期性活动所导致的物种多样性的量的变化的预测研究。有关模拟和预测结果表明:在人类周期性活动的作用下,物种多度变化对栖息地变化的响应也做准周期振荡;同时人类活动强度越大,物种多度振荡的幅度也越大;并且在栖息地减少过程中,人类周期性活动对物种多样性的影响幅度要小于栖息地扩充过程中的。在一个完整的周期内,并没有物种的灭绝,只是物种的多度和强弱关系变化很大。当人类周期性活动仅持续1/4个周期时,最强的几个物种将灭绝,而其它物种做准周期振荡,但振幅相对较小。