Metabolic profiling of rhizomes of native populations of the strictly endemic Croatian species Iris adriatica

Iris adriatica Trinajsti? ex Miti? (Iridaceae L.) is a strictly endemic taxon from Croatia. It is a rhizomatous dwarf plant from the I. pumila complex with a distribution area limited to the Croatian part of the Mediterranean area, mainly central Dalmatia. The genus Iris is known for its richness in isoflavonoids which also play a significant role in chemotaxonomy and biological activity. Hence, in the current study, different plant batches of I. adriatica collected in early spring of 2016 were analysed for their phytochemical profiles and qualitatively compared. UHPLC-PDA-ESI-MS analyses of methanolic rhizome extracts were performed. Altogether, 36 compounds, representing isoflavonoids (including 6,7-methylendioxy derivatives), benzophenones and xanthones were found as aglycones or in glycosidically bound form to be the main constituent groups of I. adriatica rhizomes. Qualitative results were identical between different batches of plant material from collection sites in central Dalmatia, they differed only in quantity. For some phenolic compounds of I. adriatica, chemotaxonomic relevance was detected.     

Cross-correlation analysis of invasive mango mealybug and its associated natural enemies in relation to meteorological factors: implications for biological control

Damage caused by invasive downey snow line mealybug, Rastrococcus iceryoides Green (Hemiptera: Pseudococcidae) has been reported to vary between 30% to complete crop loss where no control measure is applied. The current studies seek to determine factors influencing R. iceryoides population outbreaks, parasitoid – host and predator–prey relationships as well as predict optimal management strategies through weather modelling over a period of 28 months from 2008 to 2010 in Tanzania. The highest incidence of R. iceryoides was recorded during the dry season coinciding with the major mango fruiting season. The relationship between R. iceryoides and the parasitoid was positive but not significant, which implies the influence on outbreaks was negligible probably due to low percent parasitism (<12%). However, the predator abundance was directly and significantly related to that of R. iceryoides. Average temperature, average relative humidity, rainfall, and R. iceryoides abundance were autocorrelated to each other. Cross-correlation coef?cients vary significantly from ?0.286 to 0.589 for the pair-variable between R. iceryoides, temperature, relative humidity, rainfall, parasitism and predators. Our findings showed that temperature was the key climatic variable that significantly influenced R. iceryoides outbreaks while rainfall was significantly negatively associated with the pest. Time series analyses show R. iceryoides population increased 4 months after an increase in average temperature in all the sites, 11 months after rainfall and 11 months after relative humidity in Kibaha and Dar es Salaam, respectively. Our findings revealed that R. iceryoides is an excellent target for classical biological control. Thus, the importation of promising co-evolved parasitoid specific to R. iceryoides from the aboriginal home is crucial in formulating an efficient and sustainable management approaches against the invasive mealybug pest in mango agro-ecosystems.     

12个HoCP系列甘蔗种质资源初步鉴定和评价

为了解甘蔗(Saccharum spp.)亲本特性,以ROC22为对照,对12个重要Ho CP系列亲本种质进行了初步鉴定与评价。结果表明,Ho CP系列品系具有出苗率高、分蘖性好、有效茎数多、早熟高糖等特性。Ho CP01-564含糖量最高,Ho CP00-1142产量最高,Ho CP02-610发芽率和有效茎数最高,Ho CP07-613蔗糖分最高。聚类分析表明,12个Ho CP系列品系(种)可分为4类。因此,根据这些品系(种)特性可以合理配制杂交组合。     

基于红外相机技术对帚尾豪猪活动节律和时间分配初步观察

2012年8月至2013年7月,采用红外相机技术对广西弄岗国家级自然保护区15 hm^2森林动态监测样地及其周边区域内的帚尾豪猪(Atherurus macrourus)进行观察,采用活动强度指数分析其活动节律和时间分配,探讨月相和环境因子对其活动节律和时间分配的影响。结果表明,不同时间段内帚尾豪猪的活动强度存在极显著差异(t=4. 666,df=23,P=0. 001),活动峰值出现在20:00~21:00和05:00~06:00;夜间主要以移动(63. 2%)和觅食(23. 6%)为主。帚尾豪猪各月份间的时间分配存在极显著差异(t=8. 581,df=11,P=0. 001),旱、雨季间的时间分配存在显著差异(Z=-2. 166,P=0. 03)。各月相间帚尾豪猪出现的频次存在显著差异(χ~2=5. 00,df=1,P=0. 025),以新月期和满月期活动最为频繁,上弦月活动最少。相关性分析表明,活动强度指数与月降雨量、月最高温度及最低温度(R^2=0. 440,R^2=0. 435,R^2=0. 457)都存在显著的负相关,帚尾豪猪最适的活动温区为10℃~26℃。本研究初步掌握了帚尾豪猪在弄岗保护区的活动节律和时间分配,有助于后期理解栖息地和气候变化对其活动的影响。     

Correlation analysis of Normalized Different Vegetation Index (NDVI) difference series and climate variables in the Xilingole steppe, China from 1983 to 1999

There is a crucial need in the study of global change to understand how terrestrial ecosystems respond to the climate system. It has been demonstrated by many researches that Normalized Different Vegetation Index (NDVI) time series from remotely sensed data, which provide effective information of vegetation conditions on a large scale with highly temporal resolution, have a good relation with meteorological factors. However, few of these studies have taken the cumulative property of NDVI time series into account. In this study, NDVI difference series were proposed to replace the original NDVI time series with NDVI difference series to reappraise the relationship between NDVI and meteorological factors. As a proxy of the vegetation growing process, NDVI difference represents net primary productivity of vegetation at a certain time interval under an environment controlled by certain climatic conditions and other factors. This data replacement is helpful to eliminate the cumulative effect that exist in original NDVI time series, and thus is more appropriate to understand how climate system affects vegetation growth in a short time scale. By using the correlation analysis method, we studied the relationship between NOAA/AVHRR ten-day NDVI difference series and corresponding meteorological data from 1983 to 1999 from 11 meteorological stations located in the Xilingole steppe in Inner Mongolia. The results show that: (1) meteorological factors are found to be more significantly correlation with NDVI difference at the biomass-rising phase than that at the falling phase; (2) the relationship between NDVI difference and climate variables varies with vegetation types and vegetation communities. In a typical steppe dominated by Leymus chinensis, temperature has higher correlation with NDVI difference than precipitation does, and in a typical steppe dominated by Stipa krylovii, the correlation between temperature and NDVI difference is lower than that between precipitation and NDVI difference. In a typical steppe dominated by Stipa grandis, there is no significant difference between the two correlations. Precipitation is the key factor influencing vegetation growth in a desert steppe, and temperature has poor correlation with NDVI difference; (3) the response of NDVI difference to precipitation is fast and almost simultaneous both in a typical steppe and desert steppe, however, mean temperature exhibits a time-lag effect especially in the desert steppe and some typical steppe dominated by Stipa krylovii; (4) the relationship between NDVI difference and temperature is becoming stronger with global warming. __________ Translated from Acta Phytoecologica Sinica, 2005, 29(5): 753–765 [译自: 植物生态学报]     

Integer‐valued functional data analysis for measles forecasting

Measles presents a unique and imminent challenge for epidemiologists and public health officials: the disease is highly contagious, yet vaccination rates are declining precipitously in many localities. Consequently, the risk of a measles outbreak continues to rise. To improve preparedness, we study historical measles data both prevaccine and postvaccine, and design new methodology to forecast measles counts with uncertainty quantification. We propose to model the disease counts as an integer‐valued functional time series: measles counts are a function of time‐of‐year and time‐ordered by year. The counts are modeled using a negative‐binomial distribution conditional on a real‐valued latent process, which accounts for the overdispersion observed in the data. The latent process is decomposed using an unknown basis expansion, which is learned from the data, with dynamic basis coefficients. The resulting framework provides enhanced capability to model complex seasonality, which varies dynamically from year‐to‐year, and offers improved multimonth‐ahead point forecasts and substantially tighter forecast intervals (with correct coverage) compared to existing forecasting models. Importantly, the fully Bayesian approach provides well‐calibrated and precise uncertainty quantification for epi‐relevant features, such as the future value and time of the peak measles count in a given year. An R package is available online.     

Structural identifiability analysis of some highly structured families of statespace models using differential algebra

In this paper we identify biologically relevant families of models whose structural identifiability analysis could not be performed with available techniques directly. The models considered come from both the immunological and epidemiological literature.