Spawning behaviour and sex hormone levels in adult and precocious brown trout (Salmo trutta L.) males and the effect of anosmia

Summary. In the present experiment the behaviour and endocrine status of males of the brown trout, Salmo trutta L., (Salmoniformes: Salmonidae) were studied when males were kept in a stream tank with a nest digging female. Groups of mature adult males and precocious intact or anosmic male parr were placed with the nesting female so that the group resembled a natural spawning situation with big anadromous fish acting as dominant males and precocious parr acting as “sneakers”. A control experiment was also run with only males without a female present. In intact parr there were significant positive correlations between the per cent of the total observation time spent with a female, milt volume, and plasma concentration of 17α, 20β-dihydroxy-4-pregnen-3-one. Anosmic parr had significantly lower volumes of strippable milt and gonadal steroid hormone levels compared with intact parr. However, no differences were found in the control experiment. Significantly fewer anosmic parr attended and courted the nesting female and those anosmic fish that attended the female had significantly lower plasma levels of gonadal hormones. Intact parr also displayed a greater number of agonistic acts against other parr without any difference in fighting ability. No differences in aggression occured in the control experiment. In adult males together with a female, post-experimental gonadal steroid hormone levels were higher than pre-experimental levels. Positive correlations between aggression and androgen hormone levels were observed in adult males. No differences in plasma hormone levels were observed between adult males and intact precocious males. The results show that olfactory occlusion results in low steroid hormone levels and milt volumes in precocious males placed in a spawning situation. The courting behaviour was also affected by anosmia. Odours from the nesting female may have caused the enhanced plasma hormone levels and stimulated the males to attend the female. Received 15 May 1997; accepted 29 June 1997.     

Restricted adaptive cluster sampling

Adaptive cluster sampling can be a useful design for sampling rare and patchy populations. With this design the initial sample size is fixed but the size of the final sample (and total sampling effort) cannot be predicted prior to sampling. For some populations the final sample size can be quite variable depending on the level of patchiness. Restricted adaptive cluster sampling is a proposed modification where a limit is placed on the sample size prior to sampling and quadrats are selected sequentially for the initial sample size. As a result there is less variation in the final sample size and the total sampling effort can be predicted with some certainty, which is impor- tant for many ecological studies. Estimates of density are biased with the restricted design but under some circumstances the bias can be estimated well by bootstrapping. © Rapid Science 1998     

Semi-parametric statistical approaches for space-time process prediction

The problem of estimation and prediction of a spatial-temporal stochastic process, observed at regular times and irregularly in space, is considered. A mixed formulation involving a non- parametric component, accounting for a deterministic trend and the effect of exogenous variables, and a parametric component representing the purely spatio-temporal random variation is proposed. Correspondingly, a two-step procedure, first addressing the estimation of the non- parametric component, and then the estimation of the parametric component is developed from the residual series obtained, with spatial-temporal prediction being performed in terms of suitable spatial interpolation of the temporal variation structure. The proposed model formula-tion, together with the estimation and prediction procedure, are applied using a Gaussian ARMA structure for temporal modelling to space-time forecasting from real data of air pollution concentration levels in the region surrounding a power station in northwest Spain.     

利用玉米浸泡液产电的微生物燃料电池研究

以玉米淀粉生产过程中的浸泡液（玉米浸泡液）作为接种液和基质,利用“三合一”膜电极的单室空气阴极微生物燃料电池进行试验,采用在线监测电压和废水分析方法对产电功率和化学需氧量（COD）、氨氮进行测定,探讨高COD、高氨氮有机废水产电及废水处理的可行性.结果表明,经过94 d（1个周期）的连续运行（固定外电阻为1 000 Ω）,17 d时输出电压达到最大（525.0 mV）,稳定期最大输出功率可达169.6 mW/m²,此时电池相应的电流密度为440.2 mA/m²,内阻约为350 Ω,开路电压619.5 mV;但燃料电池电子利用效率较低（库仑效率为1.6%）;1个周期结束时浸泡液的COD去除率达到51.6%,氨氮去除率25.8%.本试验利用玉米浸泡液成功获得电能,同时对浸泡液有效地进行了处理,为其资源化利用提供新途径.     

Global sensitivity analysis of a process-based model for ammonia emissions from manure storage and treatment structures

The development of process-based models to estimate ammonia emissions from animal feeding operations (AFOSs) is sought to replace costly and time-consuming direct measurements. Critical to process-based model development is conducting sensitivity analysis to determine the input parameters and their interactions that contribute most to the variance of the model output. Global and relative sensitivity analyses were applied to a process-based model for predicting ammonia emissions from the surface of anaerobic lagoons for treating and storing manure. The objectives were to compare global sensitivity analysis (GSA) to relative (local) sensitivity analysis (RSA) on a process-based model for ammonia emissions. Based on the first-order coefficient, both GSA and RSA showed the model input parameters in order of importance in process model for ammonia emissions from lagoon surfaces were: (i) pH, (ii) lagoon liquid temperature, (iii) wind speed above the lagoon surface, and (iv) the concentration of ammoniacal nitrogen in the lagoon. The GSA revealed that interactions between model parameters accounted for over two-thirds of the model variance, a result that cannot be achieved using traditional RSA. Also, the GSA showed that parameter interactions involving liquid pH had more impact on the model output variance than the single parameters: (i) temperature, (ii) wind speed, or (iii) total ammoniacal nitrogen. This study demonstrates that GSA provides a more complete analysis of model input parameters and their interactions on the model output compared to RSA. A comprehensive tutorial regarding the application of GSA to a process model is presented.     

Specific Features of Wild Boar,Sus scrofa,Rooting Activity at the Northern Boundary of Its Range in Western Siberia

Russian Journal of Ecology -     

The Edge Effect on the Herb–Dwarf Shrub Layer of Urbanized Southern Taiga Forests

Russian Journal of Ecology - We estimated when the edge effect appears in the herb–dwarf shrub layer of pine forests near Yekaterinburg (Central Urals; Southern Taiga subzone) on 14 transects...     

The socio-economic vulnerability of the Australian east coast grazing sector to the impacts of climate change

Regional Environmental Change - Research that projects biophysical changes under climate change is more advanced than research that projects socio-economic changes. There is a need in adaptation...     

Designing the next generation of climate adaptation research for development

Adaptation research has changed significantly in recent years as funders and researchers seek to encourage greater impact, ensure value for money and promote interdisciplinarity across the natural and social sciences. While these developments are inherently positive, they also bring fresh challenges. With this in mind, this paper presents an agenda for the next generation of climate adaptation research for development. The agenda is based on insights from a dialogue session held at the 2016 Adaptation Futures conference as well as drawing on the collective experience of the authors. We propose five key areas that need to be changed in order to meet the needs of future adaptation research, namely: increasing transparency and consultation in research design; encouraging innovation in the design and delivery of adaptation research programmes; demonstrating impact on the ground; addressing incentive structures; and promoting more effective brokering, knowledge management and learning. As new international funding initiatives start to take shape, we underscore the importance of learning from past experiences and scaling-up of successful innovations in research funding models.