Risk assessment of contaminated sediments in river basins--theoretical considerations and pragmatic approach

In order to ensure chemical quality of river basins, measures as required in the Water Framework Directive will also have to address contaminated sediments with subsequent monitoring of their successful application. Financial resources need to be allocated as part of a river basin plan to those contaminated sites that pose the biggest risk to the river basin. In order to differentiate between areas with elevated contaminant levels ("areas of concern") and those sites from which contaminated sediments can become resuspended and transported with the river, affecting the water phase and downstream sites in the catchment ("areas of risk"), the dynamics of sediment and suspended matter need to come into focus. Hydrological data have to be combined with concentration of suspended matter and its contaminant concentration to allow assessment of particle bound contaminant load. Each of these kinds of data, however, are subject to uncertainties--e.g. due to natural variability, heterogeneity of the matrix, challenges during sampling and chemical analyses of the suspended matter. Considering these uncertainties throughout the traceability chains of data collection, use of different lines of evidence and tools like fuzzy logic will increase the confidence of potentially costly management decisions.     

A simulation model for organic phosphorus transformation in a forest soil ecosystem

A numerical model which simulates the decomposition of litter and mineralization and immobilization of P in the humus layer of a temperate forest (beech site of Solling) is described. The model takes into account the effect of moisture, temperature and C/N ratio. The simulated concentration of P in the effluent of the humus layer agrees well with the measured values. The model predicts an increase in the C/P ratio of the unde-composed litter with time and that there is no direct mineralization of P from litter without passing through a microbial body. The net rate of mineralization is, however, always positive with its highest peak in July. Maximum immobilization of P from solution occurs in June and the minimum in January.The model is stable against changes in the litter input, its C/P ratio and other initial conditions, but it is very sensitive to changes in the efficiency factor which represents the fraction of decomposed C incorporated into microbial tissue. This is a site-specific model but can be used for grassland or agricultural systems with changes in certain parameters.     

Null model analysis of species nestedness patterns

Nestedness is a common biogeographic pattern in which small communities form proper subsets of large communities. However, the detection of nestedness in binary presence-absence matrices will be affected by both the metric used to quantify nestedness and the reference null distribution. In this study, we assessed the statistical performance of eight nestedness metrics and six null model algorithms. The metrics and algorithms were tested against a benchmark set of 200 random matrices and 200 nested matrices that were created by passive sampling. Many algorithms that have been used in nestedness studies are vulnerable to type I errors (falsely rejecting a true null hypothesis). The best-performing algorithm maintains fixed row and fixed column totals, but it is conservative and may not always detect nestedness when it is present. Among the eight indices, the popular matrix temperature metric did not have good statistical properties. Instead, the Brualdi and Sanderson discrepancy index and Cutler's index of unexpected presences performed best. When used with the fixed-fixed algorithm, these indices provide a conservative test for nestedness. Although previous studies have revealed a high frequency of nestedness, a reanalysis of 288 empirical matrices suggests that the true frequency of nested matrices is between 10% and 40%.     

How do nutrient conditions and species identity influence the impact of mesograzers in eelgrass-epiphyte systems?

Coastal eutrophication is thought to cause excessive growth of epiphytes in eelgrass beds, threatening the health and survival of these ecologically and economically valuable ecosystems worldwide. Mesograzers, small crustacean and gastropod grazers, have the potential to prevent seagrass loss by grazing preferentially and efficiently on epiphytes. We tested the impact of three mesograzers on epiphyte biomass and eelgrass productivity under threefold enriched nutrient concentrations in experimental indoor mesocosm systems under summer conditions. We compared the results with earlier identical experiments that were performed under ambient nutrient supply. The isopod Idotea baltica, the periwinkle Littorina littorea, and the small gastropod Rissoa membranacea significantly reduced epiphyte load under high nutrient supply with Rissoa being the most efficient grazer, but only high densities of Littorina and Rissoa had a significant positive effect on eelgrass productivity. Although all mesograzers increased epiphyte ingestion with higher nutrient load, most likely as a functional response to the quantitatively and qualitatively better food supply, the promotion of eelgrass growth by Idotea and Rissoa was diminished compared to the study performed under ambient nutrient supply. Littorina maintained the level of its positive impact on eelgrass productivity regardless of nutrient concentrations.