Population dynamics of Mytilicola intestinalis in Mytilus edulis in south west England

The population dynamics of Mytilicola intestinalis Steuer in mussels (Mytilus edulis L.) from the River Lynher, Cornwall, England, have been studied over 3 years. By transplanting uninfested mussels from the River Erme, South Devon, into the Lynher mussel bed, the study was extended to the growth and development of new infestations under natural conditions. Female Mytilicola intestinalis are shown to breed twice, and two generations of parasites coexist for most of the year, with recruitment taking place in summer and autumn. One generation contributes its first brood to the autumn recruits before overwintering and contributing its second brood to the following summer's recruits. The other generation overwinters as juvenile and immature stages to contribute its two broods successively to the summer and autumn recruits. Environmental temperatures are believed to control the rates of development at all stages rather than acting as triggers in the onset or cessation of breeding at specific times. There is no evidence to support the contention that heavily infested mussels are killed, and parasite mortality is shown to be density-independent.     

Phase relations between a circadian rhythm and its zeitgeber within the range of entrainment

The regular day-night changes in tissues, physiologic functions, and behavior of organisms are based on endogenous rhythmic processes which under constant conditions continue with periods slightly deviating from 24h. These ‘arcadian’ rhythms have properties of self-sustained oscillators. Under natural conditions, circadian rhythms are synchronized (entrained) to 24 h by periodic factors in the environment, the so-called ‘Zeitgebers’. In the laboratory, circadian rhythms can also be entrained to periods other than 24 h within certain limits. Data on the phase relationship between the circadian rhythm and an entraining light-dark cycle for vertebrates, insects, plants, and unicellular organisms are reviewed.     

Transport of particulate matter in natural waters — modelling and in situ-measurements

The significant processes controlling the fate of particulates are convection an dispersion on one hand, and sedimentation on the other hand. Due to inteparticulated reactions, larger aggregates can be formed from smaller units thus changing the sedimentation characteristics. These phenomena are summarized in a mathematical model whereby hydrodynamic effects as well as the control mechanisms of the dissolved phase are included. A relationship was derived on the basis of energy considerations leading to the formulation of a critical sedimentation velocity of the suspensa, which determines the transport capacity of the flowing system. The sedimentation term is calculated from the above discussed transport capacity, hydro-dynamic parameters and suspending media properties. Aggregation effects are taken into account as an increase of sedimentation velocities of the particles. The equations are solved in a particular computational routine such that the horizontal distribution of suspended solids in a natural system can be describe as function of the above discussed phenomena. The model was tested with in situ-measurements. It was found that the observed processes are described satisfactorily by this model.     

Managing the urban environment in a developing country: The Ogunpa river channelization scheme in Ibadan City,Nigeria

A disastrous flood in Ibadan City, Nigeria in April 1978 aroused public interest in the Ogunpa river channelization scheme which had earlier been embarked upon by government. A questionnaire survey of 399 residents near the river was designed to examine three issues: (a) the losses sustained and the people's reaction to and perception of the causes of the flood; (b) their perception of the present and future uses of the river; and (c) their perception of the prospects of the channelization scheme.The results show that about 75% of the respondents were affected by the flood; 41% each lost property worth about N2960.00. Yet, many could not hope to move out of the flood zone mainly because of shortage of residential accomodation in the city. The factors given as being responsible for the flood were poor drainage, heavy rains, refuse disposal in the river, shallowness of the river channel and the unplanned layout of streets and buildings. Indeed, the major use of the river has been as a refuse dump, so that it is heavily polluted. Many respondents would like the river to be reclaimed to alleviate some of the socioeconomic problems confronting them. Recreational use of the river was not much considered. Majority of respondents thought the channelization scheme would bring some benefit. But, they are sceptical about its lasting impact unless it is done within the framework of a comprehensive programme of urban land management and protection and the improvement of living conditions in the city.     

Traceability,quality assurance,and standards

The development of traceability in low-level radioactivity measurements is discussed. The role that the development of large quantities of natural matrix standards can play is also discussed.     

Threshold and dose response estimation using the “filter model”

The “filter model” has been developed to explain the biologic effects of radiation and chemicals. We have examined nearly 300 sets of dose response data, of which 50 are presented here. Responses (induced by radiation and chemicals) which have been examined include in vitro survival studies on animal and plant tissues, induction of cellular aberrations and time to tumor or death. Similar data from in vivo studies has also been examined. All of the data appear to fit the model R = a lnD + b(lnD)² + c, where R is the response, a and b are parameters fitted by regression to a particular set of data, and c is the response at zero (or lowest) dose. By writing this model in exponential form, it can be seen that the response R results from multistage filtering (by net amounts a and b) of the initial dose, D. The threshold is obtained from this model as the point, $\text{D}\text{?}{}_{\mathrm{T}}$, at which the second derivative becomes zero. This is given by $\text{D}\text{?}{}_{\mathrm{T}}\text{=}\text{exp}\text{(1 ?}\text{a}\text{2b}\text{)}$ when a and b are oppositelt signed.