Sampling-Design Effects on Properties of Species-Area Relationships - A Case Study from Estonian Dry Grassland Communities

Despite widespread use of species-area relationships (SARs), dispute remains over the most representative SAR model. Using data of small-scale SARs of Estonian dry grassland communities, we address three questions: (1) Which model describes these SARs best when known artifacts are excluded? (2) How do deviating sampling procedures (marginal instead of central position of the smaller plots in relation to the largest plot; single values instead of average values; randomly located subplots instead of nested subplots) influence the properties of the SARs? (3) Are those effects likely to bias the selection of the best model? Our general dataset consisted of 16 series of nested-plots (1 cm(2)-100 m(2), any-part system), each of which comprised five series of subplots located in the four corners and the centre of the 100-m(2) plot. Data for the three pairs of compared sampling designs were generated from this dataset by subsampling. Five function types (power, quadratic power, logarithmic, Michaelis-Menten, Lomolino) were fitted with non-linear regression. In some of the communities, we found extremely high species densities (including bryophytes and lichens), namely up to eight species in 1 cm(2) and up to 140 species in 100 m(2), which appear to be the highest documented values on these scales. For SARs constructed from nested-plot average-value data, the regular power function generally was the best model, closely followed by the quadratic power function, while the logarithmic and Michaelis-Menten functions performed poorly throughout. However, the relative fit of the latter two models increased significantly relative to the respective best model when the single-value or random-sampling method was applied, however, the power function normally remained far superior. These results confirm the hypothesis that both single-value and random-sampling approaches cause artifacts by increasing stochasticity in the data, which can lead to the selection of inappropriate models.

How are climate change adaptation strategies put into practice? A case study comparison of natural hazard prevention

Climate change affects increasingly the management of natural resources and has diverse impacts of environmental, social and economic nature. To take this complexity into account, climate change adaptation policies consider the principle of sustainable development. Sustainability is an integrative concept which should insure a long-term and multi-sectoral response to climate change. But the question appears if sustainable development is only retained at the conceptual level or effectively implemented in practice. This paper pursues this question by comparing three projects addressing natural hazard in Swiss mountains. The aim is to investigate how sustainable development is perceived by involved stakeholders and implemented in practice. Two dimensions are thus taken into account: the type of actors participating in these projects and their preferences and interests. The first dimension thus analyzes if diverse actors representing the environmental, economic and social arenas are integrated; the second dimension investigates if different interests and preferences in the sense of sustainability were incorporated in the design and implementation of climate change adaptation. Data were gathered through a standardized survey among all actors involved in the three projects. Preliminary results show that sustainability receives diverse weight and interest in the different cases.

Social Salience and the Sociolinguistic Monitor: a Case Study of ING and TH-fronting in Britain

This article examines the role of social salience, or the relative ability of a linguistic variable to evoke social meaning, in structuring listeners’ perceptions of quantitative sociolinguistic distributions. Building on the foundational work of Labov et al. (2006, 2011) on the “sociolinguistic monitor” (a proposed cognitive mechanism responsible for sociolinguistic perception), we examine whether listeners’ evaluative judgments of speech change as a function of the type of variable presented. We consider two variables in British English, ING and TH-fronting, which we argue differ in their relative social salience. Replicating the design of Labov et al.’s studies, we test 149 British listeners’ reactions to different quantitative distributions of these variables. Our experiments elicit a very different pattern of perceptual responses than those reported previously. In particular, our results suggest that a variable’s social salience determines both whether and how it is perceptually evaluated. We argue that this finding is crucial for understanding how sociolinguistic information is cognitively processed.

Using the contribution matrix to evaluate complex study limitations in a network meta-analysis: a case study of bipolar maintenance pharmacotherapy review.

BACKGROUND Limitations in the primary studies constitute one important factor to be considered in the grading of recommendations assessment, development, and evaluation (GRADE) system of rating quality of evidence. However, in the network meta-analysis (NMA), such evaluation poses a special challenge because each network estimate receives different amounts of contributions from various studies via direct as well as indirect routes and because some biases have directions whose repercussion in the network can be complicated. FINDINGS In this report we use the NMA of maintenance pharmacotherapy of bipolar disorder (17 interventions, 33 studies) and demonstrate how to quantitatively evaluate the impact of study limitations using netweight, a STATA command for NMA. For each network estimate, the percentage of contributions from direct comparisons at high, moderate or low risk of bias were quantified, respectively. This method has proven flexible enough to accommodate complex biases with direction, such as the one due to the enrichment design seen in some trials of bipolar maintenance pharmacotherapy. CONCLUSIONS Using netweight, therefore, we can evaluate in a transparent and quantitative manner how study limitations of individual studies in the NMA impact on the quality of evidence of each network estimate, even when such limitations have clear directions.