Effect and design of buffer zones in the Nordic climate: The influence of width, amount of surface runoff, seasonal variation and vegetation type on retention efficiency for nutrient and particle runoff

Loss of nutrients and sediments from agricultural runoff causes eutrophication in surface water. Vegetated buffer zones adjacent to a stream can effectively remove and retain nutrients and sediments. It is, therefore, important to study design criteria which optimise the effect of buffer zones (BZ). This paper describes the influence of four criteria: (i) buffer zone width, (ii) amount of surface runoff water entering the BZ, (iii) seasonal variation and (iv) vegetation type. These parameters were studied after simulated and natural runoff at four different sites in Southern Norway with cold temperate climate. Surface runoff was collected before entering and after passing the BZs. The simulation experiments were short-term experiments carried out over a few days in 1992 and 1993. In the natural runoff experiments, volume proportional mixed samples were collected after each runoff period during 1992–1999. The results show significantly higher removal efficiency (in %) from 10 m wide BZs compared to 5 m widths, however, the specific retention (per m²) is higher in 5 m BZ. Buffer zones can receive particle runoff over several days without a significant decrease in their removal level. Retention efficiency between summer and autumn varied depending on the measured parameter (phosphorus, particles and nitrogen), and there were no significant differences in removal efficiency between summer and winter. The results show no significant differences between forest buffer zones (FBZ) and grass buffer zones (GBZ) regarding their retention efficiency for nitrogen and phosphorus. There was significantly higher retention efficiency in FBZ for particles. Average removal efficiencies from both simulated and natural runoff experiments varied from 60–89%, 37–81% and 81–91% for phosphorus, nitrogen and particles, respectively.     

Assessment of vulnerability to climate change using a multi-criteria outranking approach with application to heat stress in Sydney

Climate change vulnerability assessment is a complex form of risk assessment which accounts for both geophysical and socio-economic components of risk. In indicator-based vulnerability assessment (IBVA), indicators are used to rank the vulnerabilities of socio-ecological systems (SESs). The predominant aggregation approach in the literature, sometimes based on multi-attribute utility theory (MAUT), typically builds a global-scale, utility function based on weighted summation, to generate rankings. However, the corresponding requirement for additive independence and complete knowledge of system interactions by analyst are rarely if ever satisfied in IBVA.We build an analogy between the structures of Multi-Criteria Decision Analysis (MCDA) and IBVA problems and show that a set of techniques called Outranking Methods, developed in MCDA to deal with criteria incommensurability, data uncertainty and preference imprecision, offer IBVA a sound alternative to additive or multiplicative aggregation. We reformulate IBVA problems within an outranking framework, define thresholds of difference and use an outranking method, ELECTRE III, to assess the relative vulnerability to heat stress of 15 local government areas in metropolitan Sydney. We find that the ranking outcomes are robust and argue that an outranking approach is better suited for assessments characterized by a mix of qualitative, semi-quantitative and quantitative indicators, threshold effects and uncertainties about the exact relationships between indicators and vulnerability.     

Postoperative peak serum C-reactive protein is a predictor of outcome following liver transplantation for hepatocellular carcinoma

Context: C-reactive protein (CRP), a biomarker of inflammation, may correlate with prognosis in several malignancies.

Objective: To investigate the prognostic impact of early postoperative peak serum levels of CRP on tumor-specific outcome in 106 liver transplant patients with hepatocellular carcinoma (HCC).

Methods and results: In multivariate Cox regression analysis, a posttransplant elevated peak CRP level (>versus?≤?3.5?mg/dl) was identified as an independent predictor of poor recurrence-free survival (p?=?0.01; HR?=?4.04; CI?=?1.399–11.640).

Conclusion: Early postoperative serum CRP may serve as a useful inflammation-based biomarker of outcome in liver transplant patients with HCC.     

Performance evaluation of reactors designed for bioconversion of wheat straw to animal feed

A chronology of reactor design from laboratory scale to pilot scale for the bioconversion of wheat straw to animal feed is presented. The engineering criteria considered at each stage of development are discussed. Designs were executed at each stage and their performance was compared based on engineering and bioconversion parameters. Illustrative detailed analyses of data obtained from performance evaluation experiments from selected designs are provided. Schematics diagrams of the different generations of reactor designs are also presented.     

Defining a role for herbarium data in Red List assessments: a case study of Plectranthus from eastern and southern tropical Africa

Red Lists are widely used to indicate species at risk of extinction. Specimen sheets in herbaria provide an important source of data relevant for Red List assessments. The aims of this paper are to establish which data can be sourced from specimen information to satisfy IUCN Red Data List criteria and to identify the specific criteria that can be used. Red List parameters are measured within a Geographical Information System (GIS), as this provides an objective and repeatable methodology which is less subjective than manual methods. Data used to explore this were gathered during the course of preparing a monograph on Plectranthus (Lamiaceae). Criteria relating to distribution (extent of occurrence, area of occupancy and fragmentation) and population profile (projected continuing decline and number of subpopulations) proved most suitable for assigning categories of threat. Estimates of mature individuals, generation length, population size, population reduction, extreme fluctuation and number of locations could not be derived from herbarium material without making inconsistent subjective decisions. In addition to comprehensively databased specimen information, extensive field knowledge is required to produce better estimates for assessing extinction risk. In order to enhance the usefulness of specimen information in the future, improvements in recording additional botanical data at the time of collection would be beneficial. Overall, herbaria provide a useful starting point for conservation-related work and can help to guide future work.     

Comparison of Two U.S. Environmental Protection Agency Species Sensitivity Distribution Methods for Calculating Ecological Risk Criteria

Two major methods used by the U. S. Environmental Protection Agency (USEPA) to calculate ecological risk criteria using “species sensitivity distributions” (SSD) are compared using identical datasets. One method is the current USEPA Office of Water method for deriving acute numeric water quality criteria (EPA-FAV method). The 95% protection level generated by this method is the Final Acute Value (FAV). The other method is the USEPA Office of Pesticide Programs log normal distribution regression method that uses all available toxicological data in performing ecological risk assessments (OPP-Ecorisk method). Of the 50 comparisons made, 38% of the 95% protection levels calculated by the OPP-Ecorisk method are within a factor of 1.5 of the EPA FAV, 68% are within a factor of 2.0, 86% are within a factor of 2.5 and 92% are within a factor of 3.5. For pollutants where the difference between the OPP-Ecorisk 95% protection level and the EPA FAV are greatest, the OPP-Ecorisk 95% protection level is more protective than the EPA FAV. Where there are major differences, an analysis of the toxicity data indicates that the majority of the differences can be attributed to outliers, especially on the least sensitive ends of the toxicity distribution. In the one example dataset presented with one very sensitive genus, the OPP-Ecorisk method gave a protection level that was much closer to the lowest GMAV than the EPA-FAV method.     

Increasing numbers of bird species result from taxonomic progress,not taxonomic inflation

The impact and significance of modern taxonomy on other fields in biology have been subjects of much debate. It has been proposed that increasing numbers of vertebrate species are largely owing to ‘taxonomic inflation’. According to this hypothesis, newly recognized species result from reinterpretations of species limits based on phylogenetic species concepts (PSCs) rather than from new discoveries. Here, I examine 747 proposals to change the taxonomic rank of birds in the period 1950–2007. The trend to recognize more species of birds started at least two decades before the introduction of PSCs. Most (84.6%) newly recognized species were supported by new taxonomic data. Proposals to recognize more species resulted from application of all six major taxonomic criteria. Many newly recognized species (63.4%) were not based exclusively on PSC-based criteria (diagnosability, monophyly and exclusive coalescence of gene trees). Therefore, this study finds no empirical support for the idea that the increase in species is primarily epistemological rather than data-driven. This study shows that previous claims about the causes and effects of taxonomic inflation lack empirical support. I argue that a more appropriate term for the increase in species is ‘taxonomic progress’.