996 resultados para Klinkmann, Sven-Erik


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v.1--G. Stjernhjelm, G. Rosenhane, och J. Columbus. v.2--Thomas, Urban, Carl Urban, Johan och Erland Fredrik Hjärne. v.4--P. Lagerlöf, E. Lindschöld, Edmund, Nils och Carl Gripenhjelm, J. G. Werwing och J. T. Geisler. v.5--Wollimhaus-Gyllenborg. v.6--G. Eurelius, C. Leyoncrona I. Holmstrm̈, J. Paulinus och O. Wexionius. v.7--Magnus Gabriel de la Gardie, Jacob Arrhenius, Israel Kolmodin, Gustaf Ollon, Jacob Boëthius och Peter Brask. v.8--Märta Berendes, Ebba Marie och Joh. Eleonora de la Gardie, Amalia Wilh. och Maria Aurora von Königsmark, Thorsten Rudeen samt Carl och Ulrik Rudenschöld. v.9--Sven Dalius. Lars Wivallius och Johan Gabriel von Beyer. v.10--Lasse Johanson (Lucidor den Olycklige) och Nils Keder. v.11--En svensk fånge i Simbirsk, And. Rydelius, Harald Oxe, Germund, Carl Gustaf och Carl Wilhelm Cederhjelm. v.12--Olaf Rudbeck, (Far och sön) Erik Wennaesius, Carl Arosell, och Henrik Georg von Brobergen. v.13--Andreas Wallenius, Johan Vultejus, Christ. Tiburtius, Ernst Gestrinius, Michael Renner, Jonas Hjortzberg, och Peter Warnmark. v.15--J. Svedberg, H. Ausius, A. Amnelius, N. Tiällman, J. Schmedeman, P. Törnevall, och C. Eldh. v.16--Samuel Westhius, Gabr. Tuderus, W. von Rosenfeldt, Lars Stjerneld, Didr. Granatenflycht, Daniel Achrelius, Johan Risell, Lars Salvius, och Olof Carelius. v.17--Sophia Elisabeth Brenner. v.19--Johan Göstaf Hallman, Gustaf Palmfelt, och Carl Johan Lohman. v.22--Samuel Petri Brask, Magnus Stenbock, Jacob Fabricius.

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Edited by E. W. Dahlgren and Axel Lagrelius.

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Mode of access: Internet.

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Mode of access: Internet.

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When applying multivariate analysis techniques in information systems and social science disciplines, such as management information systems (MIS) and marketing, the assumption that the empirical data originate from a single homogeneous population is often unrealistic. When applying a causal modeling approach, such as partial least squares (PLS) path modeling, segmentation is a key issue in coping with the problem of heterogeneity in estimated cause-and-effect relationships. This chapter presents a new PLS path modeling approach which classifies units on the basis of the heterogeneity of the estimates in the inner model. If unobserved heterogeneity significantly affects the estimated path model relationships on the aggregate data level, the methodology will allow homogenous groups of observations to be created that exhibit distinctive path model estimates. The approach will, thus, provide differentiated analytical outcomes that permit more precise interpretations of each segment formed. An application on a large data set in an example of the American customer satisfaction index (ACSI) substantiates the methodology’s effectiveness in evaluating PLS path modeling results.

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The exponential growth of studies on the biological response to ocean acidification over the last few decades has generated a large amount of data. To facilitate data comparison, a data compilation hosted at the data publisher PANGAEA was initiated in 2008 and is updated on a regular basis (doi:10.1594/PANGAEA.149999). By January 2015, a total of 581 data sets (over 4 000 000 data points) from 539 papers had been archived. Here we present the developments of this data compilation five years since its first description by Nisumaa et al. (2010). Most of study sites from which data archived are still in the Northern Hemisphere and the number of archived data from studies from the Southern Hemisphere and polar oceans are still relatively low. Data from 60 studies that investigated the response of a mix of organisms or natural communities were all added after 2010, indicating a welcomed shift from the study of individual organisms to communities and ecosystems. The initial imbalance of considerably more data archived on calcification and primary production than on other processes has improved. There is also a clear tendency towards more data archived from multifactorial studies after 2010. For easier and more effective access to ocean acidification data, the ocean acidification community is strongly encouraged to contribute to the data archiving effort, and help develop standard vocabularies describing the variables and define best practices for archiving ocean acidification data.

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Land-use change and intensification threaten bee populations worldwide, imperilling pollination services. Global models are needed to better characterise, project, and mitigate bees' responses to these human impacts. The available data are, however, geographically and taxonomically unrepresentative; most data are from North America and Western Europe, overrepresenting bumblebees and raising concerns that model results may not be generalizable to other regions and taxa. To assess whether the geographic and taxonomic biases of data could undermine effectiveness of models for conservation policy, we have collated from the published literature a global dataset of bee diversity at sites facing land-use change and intensification, and assess whether bee responses to these pressures vary across 11 regions (Western, Northern, Eastern and Southern Europe; North, Central and South America; Australia and New Zealand; South East Asia; Middle and Southern Africa) and between bumblebees and other bees. Our analyses highlight strong regionally-based responses of total abundance, species richness and Simpson's diversity to land use, caused by variation in the sensitivity of species and potentially in the nature of threats. These results suggest that global extrapolation of models based on geographically and taxonomically restricted data may underestimate the true uncertainty, increasing the risk of ecological surprises.