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Collinearity a review of methods to deal with it and a simulation study evaluating their performance
(2013)
Collinearity refers to the non independence of predictor variables, usually in a regression-type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one region or time, and predicted to another with a different or unknown structure of collinearity. To demonstrate the reach of the problem of collinearity in ecology, we show how relationships among predictors differ between biomes, change over spatial scales and through time. Across disciplines, different approaches to addressing collinearity problems have been developed, ranging from clustering of predictors, threshold-based pre-selection, through latent variable methods, to shrinkage and regularisation. Using simulated data with five predictor-response relationships of increasing complexity and eight levels of collinearity we compared ways to address collinearity with standard multiple regression and machine-learning approaches. We assessed the performance of each approach by testing its impact on prediction to new data. In the extreme, we tested whether the methods were able to identify the true underlying relationship in a training dataset with strong collinearity by evaluating its performance on a test dataset without any collinearity. We found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection. Our results highlight the value of GLM in combination with penalised methods (particularly ridge) and threshold-based pre-selection when omitted variables are considered in the final interpretation. However, all approaches tested yielded degraded predictions under change in collinearity structure and the folk lore'-thresholds of correlation coefficients between predictor variables of |r| >0.7 was an appropriate indicator for when collinearity begins to severely distort model estimation and subsequent prediction. The use of ecological understanding of the system in pre-analysis variable selection and the choice of the least sensitive statistical approaches reduce the problems of collinearity, but cannot ultimately solve them.
BERNDT, K.-P.: Interdisziplinäres multimediales Lehr- und Lernprojekt "Biodiversität in Großökosystemen" ; FELGENTREFF, C.: Hochwasser im Kontext. Zur Rekonstruktion des Oderhochwassers 1997 in Brandenburg und seiner Folgen ; GIEST, H.; WALGENBACH, W.: Entwicklung von Multimedia-Bausteinen zur Ökologischen Grundbildung ; GREIL, H. et al.: Anthropometrische Grundlagen für die Entwicklung maßgerechter 3D-Computersimulationen des menschlichen Körpers zum Einsatz bei der Gestaltung körpernaher Umweltelemente ; SCHEFFLER, C. et al.: Maß- und funktionsgerechte Gestaltung der körpernahen Umwelt älterer Menschen ; SCHILITZ, A. et al.: Körperliche Entwicklung von Brandenburger Schülern und Schülerinnen als Indikator für komplexe Veränderungen von Umweltbedingungen ; SEGERT, A.; ZIERKE, I.: Handlungsstrukturen in einer ökologisch orientierten Genossenschaft ; WIPPER, R.: Interaktive multimediale Bildungssoftware "Ökosystem Wald - Artenvielfalt in Brandenburg"
EXO modifies sucrose and trehalose responses and connects the extracellular carbon status to growth
(2013)
Plants have the capacity to adapt growth to changing environmental conditions. This implies the modulation of metabolism according to the availability of carbon (C). Particular interest in the response to the C availability is based on the increasing atmospheric levels of CO2. Several regulatory pathways that link the C status to growth have emerged. The extracellular EXO protein is essential for cell expansion and promotes shoot and root growth. Homologous proteins were identified in evolutionarily distant green plants. We show here that the EXO protein connects growth with C responses. The exo mutant displayed altered responses to exogenous sucrose supplemented to the growth medium. Impaired growth of the mutant in synthetic medium was associated with the accumulation of starch and anthocyanins, altered expression of sugar-responsive genes, and increased abscisic acid levels. Thus, EXO modulates several responses related to the C availability. Growth retardation on medium supplemented with 2-deoxy-glucose, mannose, and palatinose was similar to the wildtype. Trehalose feeding stimulated root growth and shoot biomass production of exoplants where as it inhibited growth of the wildtype. The phenotypic features of the exo mutant suggest that apoplastic processes coordinate growth and C responses.
SDM performance varied for different range dynamics. Prediction accuracies decreased when abrupt range shifts occurred as species were outpaced by the rate of climate change, and increased again when a new equilibrium situation was realised. When ranges contracted, prediction accuracies increased as the absences were predicted well. Far- dispersing species were faster in tracking climate change, and were predicted more accurately by SDMs than short- dispersing species. BRTs mostly outperformed GLMs. The presence of a predator, and the inclusion of its incidence as an environmental predictor, made BRTs and GLMs perform similarly. Results are discussed in light of other studies dealing with effects of ecological traits and processes on SDM performance. Perspectives are given on further advancements of SDMs and for possible interfaces with more mechanistic approaches in order to improve predictions under environmental change.
Little is known about genes that control growth and development under low carbon (C) availability. The Arabidopsis (Arabidopsis thaliana) EXORDIUM-LIKE1 (EXL1) gene (At1g35140) was identified as a brassinosteroid-regulated gene in a previous study. We show here that the EXL1 protein is required for adaptation to C-and energy-limiting growth conditions. In-depth analysis of EXL1 transcript levels under various environmental conditions indicated that EXL1 expression is controlled by the C and energy status. Sugar starvation, extended night, and anoxia stress induced EXL1 gene expression. The C status also determined EXL1 protein levels. These results suggested that EXL1 is involved in the C-starvation response. Phenotypic changes of an exl1 loss-of-function mutant became evident only under corresponding experimental conditions. The mutant showed diminished biomass production in a short-day/low-light growth regime, impaired survival during extended night, and impaired survival of anoxia stress. Basic metabolic processes and signaling pathways are presumed to be barely impaired in exl1, because the mutant showed wild-type levels of major sugars, and transcript levels of only a few genes such as QUA-QUINE STARCH were altered. Our data suggest that EXL1 is part of a regulatory pathway that controls growth and development when C and energy supply is poor.
The NFX1-LIKE1 (NFXL1) and NFXL2 genes were identified as regulators of salt stress responses. The NFXL1 protein is a nuclear factor that positively affects adaptation to salt stress. The nfxl1-1 loss-of-function mutant displayed reduced survival rates under salt and high light stress. In contrast, the nfxl2-1 mutant, defective in the NFXL2 gene, and NFXL2-antisense plants exhibited enhanced survival under these conditions. We show here that the loss of NFXL2 function results in abscisic acid (ABA) overaccumulation, reduced stomatal conductance, and enhanced survival under drought stress. The nfxl2-1 mutant displayed reduced stomatal aperture under all conditions tested. Fusicoccin treatment, exposition to increasing light intensities, and supply of decreasing CO2 concentrations demonstrated full opening capacity of nfxl2-1 stomata. Reduced stomatal opening presumably is a consequence of elevated ABA levels. Furthermore, seedling growth, root growth, and stomatal closure were hypersensitive to exogenous ABA. The enhanced ABA responses may contribute to the improved drought stress resistance of the mutant. Three NFXL2 splice variants were cloned and named NFXL2-78, NFXL2-97, and NFXL2-100 according to the molecular weight of the putative proteins. Translational fusions to the green fluorescent protein suggest nuclear localisation of the NFXL2 proteins. Stable expression of the NFXL2-78 splice variant in nfxl2-1 plants largely complemented the mutant phenotype. Our data show that NFXL2 controls ABA levels and suppresses ABA responses. NFXL2 may prevent unnecessary and costly stress adaptation under favourable conditions.
This study quantifies the distributional effects of the minimum wage introduced in Germany in 2015. Using detailed Socio-Economic Panel survey data, we assess changes in the hourly wages, working hours, and monthly wages of employees who were entitled to be paid the minimum wage. We employ a difference-in-differences analysis, exploiting regional variation in the “bite” of the minimum wage. At the bottom of the hourly wage distribution, we document wage growth of 9% in the short term and 21% in the medium term. At the same time, we find a reduction in working hours, such that the increase in hourly wages does not lead to a subortionate increase in monthly wages. We conclude that working hours adjustments play an important role in the distributional effects of minimum wages.
We assess the short-term employment effects of the introduction of a national statutory minimum wage in Germany in 2015. For this purpose, we exploit variation in the regional treatment intensity, assuming that the stronger a minimum wage ‘bites’ into the regional wage distribution, the stronger the regional labour market will be affected. In contrast to previous studies, we construct two regional bite indicators based upon detailed individual wage data from the Structure of Earnings Survey (SES) 2014 and combine it with administrative information on regional employment. Moreover, using the Socio-Economic Panel (SOEP), we are able to affirm the absence of anticipation effects and verify the assumption of a common trend in wages before the reform. In sum, we find only moderate negative effects on overall employment of about 140,000 (0.4%) jobs, which are mainly driven by a sharp decline of marginal employment (‘mini-jobs’), while we do not find pronounced significant effects for regular employment in most specifications. Our results are robust to a variety of sensitivity tests.
This paper evaluates the short-run impact of the introduction of a statutory minimum wage in Germany on the hourly wages and monthly earnings of workers targeted by the reform. We first provide detailed descriptive evidence of changes to the wage structure in particular at the bottom of the distribution and distinguish between trends for regularly employed and marginally employed workers. In the causal analysis, we then employ a differential trend adjusted difference-in-differences (DTADD) strategy to identify the extent to which these changes in wages and earnings can be attributed to the minimum wage introduction. We find that the minimum wage introduction can account for hourly wage growth in the order of roughly 6.5 % or (sic)0.45/hour and an increase in monthly earnings of 6.6 % or (sic)53/month. Despite finding wage growth at the bottom of the distribution, the paper documents widespread non-compliance with the mandated wage floor of (sic)8.50/hour.
SOEP-LEE2
(2023)
This article presents the new linked employee-employer study of the Socio-Economic Panel (SOEP-LEE2), which offers new research opportunities for various academic fields. In particular, the study contains two waves of an employer survey for persons in dependent work that is also linkable to the SOEP, a large representative German annual household panel (SOEP-LEE2-Core). Moreover, SOEP-LEE2 includes two waves of self-employed surveys based on self-employed in the SOEP-Core (SOEP-LEE2-Self-employed) and three additional representative employer surveys, independent of the SOEP in terms of sampling employers (SOEP-LEE2-Compare). Survey topics include digitalisation and cybersecurity, human capital formation, COVID-19, and human resource management. Here, we describe the content, survey design, and comparability of the different datasets in the SOEP-LEE2 to potential users in different disciplines of research.