1,721,057 research outputs found
Communication and public participation in environmental decision making
No full textIncludes bibliographical references (p. 267-300) and index.edited by Stephen P. Depoe, John W. Delicath, Marie-France Aepli Elsenbeer
How can statistical models help to determine driving factors of landslides?
No full textLandslides are a hazard for humans and artificial structures. From an ecological point of view, they represent an important ecosystem disturbance, especially in tropical montane forests. Here, shallow translational landslides are a frequent natural phenomenon and one local determinant of high levels of biodiversity. In this paper, we apply weighted ensembles of advanced phenomenological models from statistics and machine learning to analyze the driving factors of natural landslides in a tropical montane forest in South Ecuador. We exclusively interpret terrain attributes, derived from a digital elevation model, as proxies to several driving factors of landslides and use them as predictors in our models which are trained on a set of five historical landslide inventories. We check the model generality by transferring them in time and use three common performance criteria (i.e. AUC, explained deviance and slope of model calibration curve) to, on the one hand, compare several state-of-the-art model approaches and on the other hand, to create weighted model ensembles. Our results suggest that it is important to consider more than one single performance criterion. Approaching our main question, we compare responses of weighted model ensembles that were trained on distinct functional units of landslides (i.e. initiation, transport and deposition zones). This way, we are able to show that it is quite possible to deduce driving factors of landslides, if the consistency between the training data and the processes is maintained. Opening the 'black box' of statistical models by interpreting univariate model response curves and relative importance of single predictors regarding their plausibility, we provide a means to verify this consistency. With the exception of classification tree analysis, all techniques performed comparably well in our case study while being outperformed by weighted model ensembles. Univariate response curves of models trained on distinct functional units of landslides exposed different shapes following our expectations. Our results indicate the occurrence of landslides to be mainly controlled by factors related to the general position along a slope (i.e. ridge, open slope or valley) while landslide initiation seems to be favored by small scale convexities on otherwise plain open slopes. © 2011 Elsevier B.V
ppartition - Test for Associations between Plant Species and Soil Nutrients
No full text<p>Bundle of R functions used to analyze the associations between tree species and enzyme-labile soil phosphorus on a 50 ha forest plot on Barro Colorado Island in Panama. This package is supplement to the journal article 'Evidence for Soil Phosphorus Resource Partitioning in a Diverse Tropical Tree Community' by R. Müller, H. Elsenbeer and B. L. Turner.</p>
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Soil organic carbon concentrations and stocks on Barro Colorado Island - Digital soil mapping using Random Forests analysis
No full textSpatial estimates of tropical soil organic carbon (SOC) concentrations and stocks are crucial to understanding the role of tropical SOC in the global carbon cycle. They also allow for spatial variation of SOC in environmental process models. SOC is spatially highly variable. In traditional approaches, SOC concentrations and stocks have been derived from estimates for single or very few profiles and spatially linked to existing units of soil or vegetation maps. However, many existing soil profile data are incomplete and untested as to whether they are representative or unbiased. Also single means for soil or vegetation map units cannot characterize SOC spatial variability within these units. We here use the digital soil mapping approach to predict the spatial distribution of SOC. This relies on a soil inference model based on spatially referenced environmental layers of topographic attributes, soil units, parent material, and forest history. We sampled soils at 165 sites, stratified according to topography and lithology, on Barro Colorado Island (BCI), Panama, at depths of 0-10 cm, 10-20 cm, 20-30 cm, and 30-50 cm, and analyzed them for SOC by dry combustion. We applied Random Forest (RF) analysis as a modeling tool to the SOC data for each depth interval in order to compare vertical and lateral distribution patterns. RF has several advantages compared to other modeling approaches, for instance, the fact that it is neither sensitive to overfitting nor to noise features. The RF-based digital SOC mapping approach provided SOC estimates of high spatial resolution and estimates of error and predictor importance. The environmental variables that explained most of the variation in the topsoil (0-10 cm) were topographic attributes. In the subsoil (10-50 cm), SOC distribution was best explained by soil texture classes as derived from soil mapping units. The estimates for SOC stocks in the upper 30 cm ranged between 38 and 116 Mg ha- 1, with lowest stocks on midslope and highest on toeslope positions. This digital soil mapping approach can be applied to similar landscapes to refine the spatial resolution of SOC estimates. © 2008 Elsevier B.V. All rights reserved
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Biotic controls on shallow translational landslides
No full textIn undisturbed tropical montane rainforests massive organic layers accommodate the majority of roots and only a small fraction of roots penetrate the mineral soil. We investigated the contribution of vegetation to slope stability in such environments by modifying a standard model for slope stability to include an organic layer with distinct mechanical properties. The importance of individual model parameters was evaluated using detailed measurements of soil and vegetation properties to reproduce the observed depth of 11 shallow landslides in the Andes of southern Ecuador. By distinguishing mineral soil, organic layer and above-ground biomass, it is shown that in this environment vegetation provides a destabilizing effect mainly due to its contribution to the mass of the organic layer (up to 973 t ha-1 under wet conditions). Sensitivity analysis shows that the destabilizing effect of the mass of soil and vegetation can only be effective on slopes steeper than 37.9°. This situation applies to 36% of the study area. Thus, on the steep slopes of this megadiverse ecosystem, the mass of the growing forest promotes landsliding, which in turn promotes a new cycle of succession. This feedback mechanism is worth consideration in further investigations of the impact of landslides on plant diversity in similar environments. © 2012 John Wiley & Sons, Ltd
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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