A comparison of vector population indices for forecasting barley yellow dwarf virus in autumn sown cereal crops

Two approaches based on the concept of a vector population index are considered as possible deterministic elements for an empirical forecast of barley yellow dwarf virus (BYDV) in autumn sown cereals. The first, an aerial vector index, is a further elaboration of the infectivity index proposed by Plumb, Lennon & Gutteridge (1981), which assumes that virus damage is a function of the number of infective migrant alatae of the two main aphid vectors, Rhopalosiphum padi L. and Sitobion avenae F., integrated over time from crop planting or emergence. The new formulation, however, excludes holocyclic alate morphs (i.e. males and gynoparae) of the former species, which, although generally abundant in autumn, are nevertheless perceived as relatively unimportant virus vectors since they colonise only the alternative woody host, Prunus padus (the bird-cherry tree). The second approach, a crop vector index, is a more fundamental departure which argues that field populations of viruliferous aphids, both alatae and apterae, which have already colonised cereals, may be a better criterion of potential virus spread than the density of aerial migrant vectors. This index retains a similar integral form, but evaluates crop exposure to BYDV as accumulated infectious aphid-days. A method is described whereby this function can be derived from irregular or infrequent aphid samples in the crop. Both methods, unlike Plumb's (1976) original concept, produced indices which were significantly related to subsequent virus infection and yield loss in winter barley at Long Ashton (S.W. England, UK), 1978–1986. The best models were obtained with the crop vector index, fitted to observed virus infection by generalised linear regression using a complementary log-log link function, or to observed yield loss by simple linear regression using a log transformation of yield (r = 0.84 in each case; compared with r-values > 0.65 for the aerial vector index, and > 0.35 for Plumb's (1976) index). However, the residual errors and hence confidence limits of these fitted regressions were too large for predicting damage that was significantly less than a reasonable economic damage threshold for BYDV control. Analyses of the separate components of each index showed a good general relationship between aphid infectivity and the severity of crop infection, confirming the epidemiological importance of this factor. The functional expressions of aphid density, however, were not significant. This evident weakness in the models, and alternative approaches to BYDV forecasting are discussed.     

Two centuries of growth among Czech children and youth

The trend of increasing height can be interpreted as a reflection of the unfolding progress of civilization. Height changes among children and adolescents are good markers of this trend. We analyze the secular trend in the heights of children and adolescents in the Czech Republic on the basis of data from anthropological surveys. The earliest height data pertain to Czech youths who attended the Military Schools in Austria in 1800-1809. Data also exist for 1895 and continue in 1951 and at 10-year intervals thereafter. Growth curves were obtained for separate age groups by fitting mean values via third-order polynomial smoothing splines. Between 1951 and 2001, the mean heights of boys and girls aged 2.5 years increased by 2.7 and 3 cm, respectively. Since 1895, the mean height of 13-year-old boys has increased by 19.4 cm, and the mean height of girls has increased by 18.3 cm.     

Local population differences in emergence of cabbage root flies from south-west Lancashire: implications for pest forecasting and population divergence

ABSTRACT.

• 1 Emergence of cabbage root fly, Delia radicum (L.), from overwintering populations of puparia collected from twenty-one sites in south-west Lancashire, was extremely variable.
• 2 The patterns of emergence indicated that there were two extreme biotypes, one with early- and the other with late-emerging flies. There was also evidence of an intermediate biotype, tending more to early than to late emergence.
• 3 This gradient of biotypes, or clinal divergence, was maintained by populations breeding at different times and by females mating close to their sites of emergence. Non-dispersive females then perpetuated their genotype within their own locality.
• 4 The time of emergence was not obviously associated with the type of host-crop on which larvae had developed.
• 5 The late-emerging biotype was most prevalent around Halsall. The minimum distance between populations of the late- and the early-emerging biotypes was 16 km. 20 km south-east from Halsall only half of the fly population was early-emerging, possibly a result of a displacement of the Halsall biotype by the prevailing NW wind.
• 6 Regional-based forecasts will need to take into account the emergence characteristics of the populations to predict the peak periods of cabbage root fly activity adequately in south-west Lancashire and other areas where emergence patterns differ.

     

白背飞虱种群动态关联分析及预测模型的研究

根据灰色系统关联分析的基本原理,提出了白背飞虱种群动态的加权关联度预测法。衢县早稻后期白背飞虱发生量与历年6月25～30日平均百丛虫量X_1（t）、同期若虫比例X_2（t）、迟熟品种比例X_3（t）、6月下旬水分积分指数X_4（t）和平均气温X_5（t）等因素的关联序为：X_2（t）＞X_1（t）＞X_3（t）＞X_5（t）＞X_4（t）。据此建立的加权关联度预测模型,经12年资料回测和试报验证,结果令人满意。     

闽北地区四代三化螟发生动态Fuzzy预测模型研究

根据Fuzzy数学原理和三化螟生物学特性,组建了四代三化螟发生动态综合预测模型经对福建省将乐县16年四代三化螟发生期、发生量回报及1995年的预报,拟合率及正确率均达100％。     

高粱蚜灰色灾变长期预测模型

本文应用灰色系统灾变预测理论建立了吕梁地区高粱蚜发生量预测模型．     

Summer drought exposure,stand structure,and soil properties jointly control the growth of European beech along a steep precipitation gradient in northern Germany

Increasing exposure to climate warming-related drought and heat threatens forest vitality in many regions on earth, with the trees' vulnerability likely depending on local climatic aridity, recent climate trends, edaphic conditions, and the drought acclimatization and adaptation of populations. Studies exploring tree species' vulnerability to climate change often have a local focus or model the species' entire distribution range, which hampers the separation of climatic and edaphic drivers of drought and heat vulnerability. We compared recent radial growth trends and the sensitivity of growth to drought and heat in central populations of a widespread and naturally dominant tree species in Europe, European beech (Fagus sylvatica), at 30 forest sites across a steep precipitation gradient (500–850 mm year⁻¹) of short length to assess the species' adaptive potential. Size-standardized basal area increment remained more constant during the period of accelerated warming since the early 1980s in populations with >360 mm growing season precipitation (April–September), while growth trends were negative at sites with <360 mm. Climatic drought in June appeared as the most influential climatic factor affecting radial growth, with a stronger effect at drier sites. A decadal decrease in the climatic water balance of the summer was identified as the most important factor leading to growth decline, which is amplified by higher stem densities. Inter-annual growth variability has increased since the early 1980s, and variability is generally higher at drier and sandier sites. Similarly, within-population growth synchrony is higher at sandier sites and has increased with a decrease in the June climatic water balance. Our results caution against predicting the drought vulnerability of trees solely from climate projections, as soil properties emerged as an important modulating factor. We conclude that beech is facing recent growth decline at drier sites in the centre of its distribution range, driven by climate change-related climate aridification.     

Ranking species based on sensitivity to perturbations under non-equilibrium community dynamics

Managing ecological communities requires fast detection of species that are sensitive to perturbations. Yet, the focus on recovery to equilibrium has prevented us from assessing species responses to perturbations when abundances fluctuate over time. Here, we introduce two data-driven approaches (expected sensitivity and eigenvector rankings) based on the time-varying Jacobian matrix to rank species over time according to their sensitivity to perturbations on abundances. Using several population dynamics models, we demonstrate that we can infer these rankings from time-series data to predict the order of species sensitivities. We find that the most sensitive species are not always the ones with the most rapidly changing or lowest abundance, which are typical criteria used to monitor populations. Finally, using two empirical time series, we show that sensitive species tend to be harder to forecast. Our results suggest that incorporating information on species interactions can improve how we manage communities out of equilibrium.