The role of land use in climate change – from CO2 source to cost-efficient mitigation

The present studies focus on the land use contributions to industrial-age carbon emissions and future abatement potentials. A practicable estimation scheme is presented to transparently identify the driving terms behind past emissions and future mitigation possibilities. Regarding the major emissions sources, 10 % of total present CO2 emissions are possible in tail of primary forest clearing outside of wood consumption; 3 % are attributed to desertification and peat cultivation; on the opposite, 5 % are counteracted by sequestration from forest gain. Regarding mitigation, prudent land use has the potential to reduce more than 50 % of all present anthropogenic emissions at approximate zero costs. Prerequisite is that biomass be considered a scarce resource and therefore, carefully supported and solely used in high-efficiency applications.

Mixed precision path tracking for polynomial homotopy continuation

This article develops a new predictor-corrector algorithm for numerical path tracking in the context of polynomial homotopy continuation. In the corrector step, it uses a newly developed Newton corrector algorithm which rejects an initial guess if it is not an approximate zero. The algorithm also uses an adaptive step size control that builds on a local understanding of the region of convergence of Newton’s method and the distance to the closest singularity following Telen, Van Barel, and Verschelde. To handle numerically challenging situations, the algorithm uses mixed precision arithmetic. The efficiency and robustness are demonstrated in several numerical examples.

Basic Values Survey (BVS) - A 20-nation validation study

The present paper tests the structure and invariance of the Functional Theory of Human Values across 20 countries (N = 21,362). This theory proposes that values have the functions of guiding behaviour and expressing needs. The interplay between these two functions produces six subfunctions that in turn produce distinct content. These subfunctions are operationalised in the Basic Values Survey with three items each, forming an 18-item measure. Although this measure has been used for more than two decades, studies examining its psychometric properties in multiple-group data are scarce. Using multidimensional scaling (MDS), it was found that values were organised in a bidimensional space according to the hypothesised degree of congruence between subfunctions. Also, Confirmatory Factor Analysis (CFA) with a Bayes estimator and approximate zero cross-loadings and residual correlations supported the six-factor structure. A strict CFA with Robust-ML estimator did not support the model. Metric invariance was supported for all the items, except religiosity, using the alignment method and approximate Bayesian invariance.

Further Insights Into the German Version of the Multidimensional Assessment of Interoceptive Awareness (MAIA)

Interoception is defined as an iterative process that refers to receiving, accessing, appraising, and responding to body sensations. Recently, following an extensive process of development, Mehling and colleagues (2012) proposed a new instrument, the Multidimensional Assessment of Interoceptive Awareness (MAIA), which captures these different aspects of interoception with eight subscales. The aim of this study was to reexamine the dimensionality of the MAIA by applying maximum likelihood confirmatory factor analysis (ML-CFA), exploratory structural equation modeling (ESEM), and Bayesian structural equation modeling (BSEM). ML-CFA, ESEM, and BSEM were examined in a sample of 320 German adults. ML-CFA showed a poor fit to the data. ESEM yielded a better fit and contained numerous significant cross-loadings, of which one was substantial (≥ .30). The BSEM model with approximate zero informative priors yielded an excellent fit and confirmed the substantial cross-loading found in ESEM. The study demonstrates that ESEM and BSEM are flexible techniques that can be used to improve our understanding of multidimensional constructs. In addition, BSEM can be seen as less exploratory than ESEM and it might also be used to overcome potential limitations of ESEM with regard to more complex models relative to the sample size.