Carbon (C), nitrogen (N) and phosphorus (P) are the three most important essential elements limiting growth of primary producers. Submerged macrophytes generally absorb nutrients from sediments by root uptake. However, the C:N:P stoichiometric signatures of plant tissue are affected by many additional factors such as taxonomy, nutrient availability, and light availability. We first revealed the relative importance of taxonomy, sediment, and water column on plant C:N:P stoichiometry using variance partitioning based on partial redundancy analyses. Results showed that taxonomy was the most important factor in determining C:N:P stoichiometry, then the water column and finally the sediment. In this study, a significant positive relationship was found between community C concentration and macrophyte community biomass, indicating that the local low C availability in macrophytes probably was the main reason why submerged macrophytes declined in Yangtze floodplain shallow lakes. Based on our study, it is suggested that submerged macrophytes in Yangtze floodplain shallow lakes are primarily limited by low light levels rather than nutrient availability.
Ambient concentrations of many pollutants are associated with emissions due to human activity, such as road transport and other combustion sources. In this paper we consider air pollution as a multi-level phenomenon on a continental scale within a Bayesian hierarchical model. We examine different scales of variation in pollution concentrations ranging from large scale transboundary effects to more localised effects which are directly related to human activity. Specifically, in the first stage of the model, we isolate underlying patterns in pollution concentrations due to global factors such as underlying climate and topography, which are modelled together with spatial structure. At this stage measurements from monitoring sites located within rural areas are used which, as far as possible, are chosen to reflect background concentrations. Having isolated these global effects, in the second stage we assess the effects of human activity on pollution in urban areas. The proposed model was applied to concentrations of nitrogen dioxide measured throughout the EU for which significant increases are found to be associated with human activity in urban areas. The approach proposed here provides valuable information that could be used in performing health impact assessments and to inform policy. 相似文献