Nectar resource diversity organises flower-visitor community structure

Communities of nectar-producing plants show high spatio-temporal variation in the patterns of volume and concentration presentation. We illustrate a novel approach for quantifying nectar reward structures in complex communities, demonstrating that nectar resource diversity (defined as the variety of nectar volume-concentration combinations available) may be a fundamental factor organising nectarivore communities. In a series of diverse bee and entomophilous flower communities in Israel, our measure of nectar resource diversity alone explains the majority of variation in bee species richness, while other nectar variables (volume, concentration, energy value, and water content) have little predictive value per se. The new measure of nectar resource diversity is highly correlated with floral species richness and particularly with the species richness of annuals, yet it is additive in its effect on bee diversity. We conclude that relying solely upon measurements of mean nectar volume and mean nectar concentration overlooks a key characteristic of community-level reward structure, nectar resource diversity, so that previous studies may have failed to identify an important determinant of flower-visitor community structure.

A framework for revitalisation of rural education and training systems in sub-Saharan Africa: Strengthening the human resource base for food security and sustainable livelihoods

Recent studies of the current state of rural education and training (RET) systems in sub-Saharan Africa have assessed their ability to provide for the learning needs essential for more knowledgeable and productive small-scale rural households. These are most necessary if the endemic causes of rural poverty (poor nutrition, lack of sustainable livelihoods, etc.) are to be overcome. A brief historical background and analysis of the major current constraints to improvement in the sector are discussed. Paramount among those factors leading to its present 'malaise' is the lack of a whole-systems perspective and the absence of any coherent policy framework in most countries. There is evidence of some recent innovations, both in the public sector and through the work of non-governmental organisations (NGOs), civil society organisations (CSOs) and other private bodies. These provide hope of a new sense of direction that could lead towards meaningful 'revitalisation' of the sector. A suggested framework offers 10 key steps which, it is argued, could largely be achieved with modest internal resources and very little external support, provided that the necessary leadership and managerial capacities are in place. (C) 2006 Elsevier Ltd. All rights reserved.

Graphical tracking systems revisited: a practical approach to computer scheduling in horticulture

Graphical tracking is a technique for crop scheduling where the actual plant state is plotted against an ideal target curve which encapsulates all crop and environmental characteristics. Management decisions are made on the basis of the position of the actual crop against the ideal position. Due to the simplicity of the approach it is possible for graphical tracks to be developed on site without the requirement for controlled experimentation. Growth models and graphical tracks are discussed, and an implementation of the Richards curve for graphical tracking described. In many cases, the more intuitively desirable growth models perform sub-optimally due to problems with the specification of starting conditions, environmental factors outside the scope of the original model and the introduction of new cultivars. Accurate specification for a biological model requires detailed and usually costly study, and as such is not adaptable to a changing cultivar range and changing cultivation techniques. Fitting of a new graphical track for a new cultivar can be conducted on site and improved over subsequent seasons. Graphical tracking emphasises the current position relative to the objective, and as such does not require the time consuming or system specific input of an environmental history, although it does require detailed crop measurement. The approach is flexible and could be applied to a variety of specification metrics, with digital imaging providing a route for added value. For decision making regarding crop manipulation from the observed current state, there is a role for simple predictive modelling over the short term to indicate the short term consequences of crop manipulation.

Developing protocols for nursery based scheduling trials

Most existing crop scheduling models are cultivar specific and are developed using academic resources. As such they rarely meet the particular needs of a grower. A series of protocols have been created to generate effective schedules for a changing product range using data generated on site at a commercial nursery. A screening programme has been developed to help determine a cultivar's photoperiod sensitivity and vernalisation requirement. Experimental conditions were obtained using a cold store facility set to 5degreesC and photoperiod cloches. Eight and 16 hour photoperiod treatments were achieved at low cost by growing plants in cloches of opaque plastic with a motorised rolling screen. Natural light conditions were extended where necessary using a high pressure sodium lamp. Batches of plants were grown according to different schedules based on these treatments. The screening programme found Coreopsis grandiflora 'Flying Saucers' to be a long day plant. Data to form the basis of graphical tracks was taken using variations on commercial schedules. The work provides a nursery based approach to the continuous improvement of crop scheduling practises.

Stabilizing swarm intelligence search via positive feedback resource allocation

A novel Swarm Intelligence method for best-fit search, Stochastic Diffusion Search, is presented capable of rapid location of the optimal solution in the search space. Population based search mechanisms employed by Swarm Intelligence methods can suffer lack of convergence resulting in ill defined stopping criteria and loss of the best solution. Conversely, as a result of its resource allocation mechanism, the solutions SDS discovers enjoy excellent stability.