Rooting cuttings of Syringa vulgaris cv. Charles Joly and Corylus avellana cv. Aurea: the influence of stock plant pruning and shoot growth

The relationship between shoot growth and rooting was examined in two, 'difficult-to root' amenity trees, Syringa vulgaris L. cv. Charles Joly and Corylus avellana L. cv. Aurea. A range of treatments reflecting severity of pruning was imposed on field-grown stock prior to bud break. To minimise variation due to the numbers of buds that developed under different treatments, bud number was restricted to 30 per plant. Leafy cuttings were harvested at different stages of the active growth phase of each species. With Syringa, rooting decreased with later harvests, but loss of rooting potential was delayed in cuttings collected from the most severe pruning treatment. Rooting potential was associated with the extent of post-excision shoot growth on the cutting but regression analyses indicated that this relationship could not entirely explain the loss of rooting with time, nor the effects due to pruning. Similarly, in Corylus rooting was promoted by severe pruning, but the relationship between apical growth on the cutting and rooting was weaker than in Syringa, and only at the last harvest did growth play a critical role in determining rooting. Another unusual factor of the last harvest of Corylus was a bimodal distribution of roots per cutting, with very few rooted cuttings having less than five roots. This implies that, for this harvest at least, the potential of an individual cutting to root is probably not limited by the number of potential rooting sites.

William Clark Russell and Chambers's Journal: elopement and the Victorian nautical novel

This essay examines aspects of the serialisation of the novels of William Clark Russell, the greatest late Victorian nautical novelist. Focusing on the treatment of his work by the Edinburgh firm of Messrs Chambers, the article provides an illuminating perspective on market censorship in this period. Drawing on the archives of Chatto & Windus and the literary agent A.P. Watt, it traces the network of relations between author, agent, magazine editor and book publisher, showing how the various components of the serial market operated in the late 1880s and early 1890s.

Climatic and oceanic associations with daily rainfall extremes over southern Africa

Changes in climate variability and, in particular, changes in extreme climate events are likely to be of far more significance for environmentally vulnerable regions than changes in the mean state. It is generally accepted that sea-surface temperatures (SSTs) play an important role in modulating rainfall variability. Consequently, SSTs can be prescribed in global and regional climate modelling in order to study the physical mechanisms behind rainfall and its extremes. Using a satellite-based daily rainfall historical data set, this paper describes the main patterns of rainfall variability over southern Africa, identifies the dates when extreme rainfall occurs within these patterns, and shows the effect of resolution in trying to identify the location and intensity of SST anomalies associated with these extremes in the Atlantic and southwest Indian Ocean. Derived from a Principal Component Analysis (PCA), the results also suggest that, for the spatial pattern accounting for the highest amount of variability, extremes extracted at a higher spatial resolution do give a clearer indication regarding the location and intensity of anomalous SST regions. As the amount of variability explained by each spatial pattern defined by the PCA decreases, it would appear that extremes extracted at a lower resolution give a clearer indication of anomalous SST regions.

Trends in the start of the wet season over Africa

A quarter of a century of daily rainfall data from the Global Telecommunications System are used to define the temporal and spatial variability of the start of the wet season over Africa and surrounding extreme south of Europe and parts of the Middle East. From 1978 to 2002, the start of the wet season arrived later in the year for the majority of the region, as time progressed. In some parts of the continent, there was an annual increase in the start date of up to 4 days per year. On average, the start of the wet season arrived 9–21 days later from 1978 to 2002, depending on the threshold used to define the start of the rains (varying from 10–30 mm over 2 days, with no dry period in the following 10 days). It is noted that the inter-annual variability of the start of the wet season is high with the range of start dates varying on average from 116 to 142 days dependent on the threshold used to determine the start date. These results may have important implications for agriculturists on all levels (from the individual farmer to those responsible for regional food supply), as knowledge of potential future climate changes starts to play an increasingly important role in the agricultural decision-making process, such as sowing and harvesting times.

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UKMeteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is underestimated (over-estimated) over wet (dry) regions of southern Africa.

Idealized SST anomaly regional climate model experiments: a note of caution

To date, a number of studies have focused on the influence of sea surface temperature (SST) on global and regional rainfall variability, with the majority of these focusing on certain ocean basins e.g. the Pacific, North Atlantic and Indian Ocean. In contrast, relatively less work has been done on the influence of the central South Atlantic, particularly in relation to rainfall over southern Africa. Previous work by the authors, using reanalysis data and general circulation model (GCM) experiments, has suggested that cold SST anomalies in the central southern Atlantic Ocean are linked to an increase in rainfall extremes across southern Africa. In this paper we present results from idealised regional climate model (RCM) experiments forced with both positive and negative SST anomalies in the southern Atlantic Ocean. These experiments reveal an unexpected response of rainfall over southern Africa. In particular it was found that SST anomalies of opposite sign can cause similar rainfall responses in the model experiments, with isolated increases in rainfall over central southern Africa as well as a large region of drying over the Mozambique Channel. The purpose of this paper is to highlight this finding and explore explanations for the behaviour of the climate model. It is suggested that the observed changes in rainfall might result from the redistribution of energy (associated with upper level changes to Rossby waves) or, of more concern, model error, and therefore the paper concludes that the results of idealised regional climate models forced with SST anomalies should be viewed cautiously.