1,720,955 research outputs found
The Metabolic Regimes at the Scale of an Entire Stream Network Unveiled Through Sensor Data and Machine Learning
Streams and rivers form dense networks that drain the terrestrial landscape and are relevant for biodiversity dynamics, ecosystem functioning, and transport and transformation of carbon. Yet, resolving in both space and time gross primary production (GPP), ecosystem respiration (ER) and net ecosystem production (NEP) at the scale of entire stream networks has been elusive so far. Here, combining Random Forest (RF) with time series of sensor data in 12 reach sites, we predicted annual regimes of GPP, ER, and NEP in 292 individual stream reaches and disclosed properties emerging from the network they form. We further predicted available light and thermal regimes for the entire network and expanded the library of stream metabolism predictors. We found that the annual network-scale metabolism was heterotrophic yet with a clear peak of autotrophy in spring. In agreement with the River Continuum Concept, small headwaters and larger downstream reaches contributed 16% and 60%, respectively, to the annual network-scale GPP. Our results suggest that ER rather than GPP drives the metabolic stability at the network scale, which is likely attributable to the buffering function of the streambed for ER, while GPP is more susceptible to flow-induced disturbance and fluctuations in light availability. Furthermore, we found large terrestrial subsidies fueling ER, pointing to an unexpectedly high network-scale level of heterotrophy, otherwise masked by simply considering reach-scale NEP estimations. Our machine learning approach sheds new light on the spatiotemporal dynamics of ecosystem metabolism at the network scale, which is a prerequisite to integrate aquatic and terrestrial carbon cycling at relevant scales
Modeling the coupled dynamics of stream metabolism and microbial biomass
Estimating and interpreting ecosystem metabolism remains an important challenge in stream ecology. Here, we propose a novel approach to model, estimate, and predict multiseasonal patterns of stream metabolism (gross primary production [GPP] and ecosystem respiration [ER]) at the reach scale leveraging on increasingly available long-term, high-frequency measurements of dissolved oxygen (DO). The model uses DO measurements to estimate the parameters of a simple ecosystem model describing the underlying dynamics of stream autotrophic and heterotrophic microbial biomass. The model has been applied to four reaches within the Ybbs river network, Austria. Even if microbial biomasses are not observed, that is, they are treated as latent variables, results show that by accounting for the temporal dynamics of biomass, the model reproduces variability in metabolic fluxes that is not explained by fluctuations of light, temperature, and resources. The model is particularly data-demanding: to estimate the 11 parameters used in this formulation, it requires sufficiently long, for example, annual, time series, and significant scouring events. On the other hand, the approach has the potential to separate ER into its autotrophic and heterotrophic components, estimate a richer set of ecosystem carbon fluxes (i.e., carbon uptake, loss, and scouring), extrapolate metabolism estimates for periods when DO measurements are unavailable, and predict how ecosystem metabolism would respond to variations of the driving forces. The model is seen as a building block to develop tools to fully appreciate multiseasonal patterns of metabolic activity in river networks and to provide reliable estimations of carbon fluxes from land to ocean
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
“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
Appropriate Similarity Measures for Author Cocitation Analysis
We 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
We 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
Author-wise bibliometric analysis based on entropy.</p
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