Within the field of species distribution modelling an apparent dichotomy exists between process-based and correlative approaches, where the processes are explicit in the former and implicit in the latter. However, these intuitive distinctions can become blurred when comparing species distribution modelling approaches in more detail. In this review article, we contrast the extremes of the correlativeprocess spectrum of species distribution models with respect to core assumptions, model building and selection strategies, validation, uncertainties, common errors and the questions they are most suited to answer. The extremes of such approaches differ clearly in many aspects, such as model building approaches, parameter estimation strategies and transferability. However, they also share strengths and weaknesses. We show that claims of one approach being intrinsically superior to the other are misguided and that they ignore the processcorrelation continuum as well as the domains of questions that each approach is addressing. Nonetheless, the application of process-based approaches to species distribution modelling lags far behind more correlative (process-implicit) methods and more research is required to explore their potential benefits. Critical issues for the employment of species distribution modelling approaches are given, together with a guideline for appropriate usage. We close with challenges for future development of process-explicit species distribution models and how they may complement current approaches to study species distributions.
The aim of this study was the development and psychometric assessment of a questionnaire for functions of OCD (FFZ). The instrument was analyzed using factor and item analyses with a sample of 120 OCD patients within the first 5 weeks of an inpatient cognitive-behavioral treatment. The revealed scales were OCD as self-confirmation, emotion regulation, avoidance of responsibility, interpersonal regulation and OCD as occupation. The reliabilities of all subscales and the total value were satisfactory to nearly excellent. The factorial validity was good, content validity was excellent. The FFZ shows correlations with measures of interpersonal problems and emotional competence, but none with measures of self-reflection and therapy experience. No differences were found for gender or age. The results provide initial support for the reliability and validity of the FFZ.
Learning to regulate anger is an important task in childhood development, as maladaptive anger regulation has been linked to a variety of problems, including aggression and social rejection. To assess anger regulation in situ, in a previous study we developed a behavioural observation measure and demonstrated its cross-sectional construct and criterion validity in a sample of 599 children with a mean age of 8.1years. The present study further validated the measure by demonstrating its predictive validity. About 10months after the behavioural observation, participants were asked to imagine two anger-eliciting situations and report what they would do to get rid of their anger. Observed anger regulation strategies at T1 correlated significantly with self-reported regulatory behaviour at T2, suggesting that the behavioural observation measure is an ecologically valid approach for assessing anger regulation in middle childhood.
Flood loss modeling is an important component for risk analyses and decision support in flood risk management. Commonly, flood loss models describe complex damaging processes by simple, deterministic approaches like depth-damage functions and are associated with large uncertainty. To improve flood loss estimation and to provide quantitative information about the uncertainty associated with loss modeling, a probabilistic, multivariable Bagging decision Tree Flood Loss Estimation MOdel (BT-FLEMO) for residential buildings was developed. The application of BT-FLEMO provides a probability distribution of estimated losses to residential buildings per municipality. BT-FLEMO was applied and validated at the mesoscale in 19 municipalities that were affected during the 2002 flood by the River Mulde in Saxony, Germany. Validation was undertaken on the one hand via a comparison with six deterministic loss models, including both depth-damage functions and multivariable models. On the other hand, the results were compared with official loss data. BT-FLEMO outperforms deterministic, univariable, and multivariable models with regard to model accuracy, although the prediction uncertainty remains high. An important advantage of BT-FLEMO is the quantification of prediction uncertainty. The probability distribution of loss estimates by BT-FLEMO well represents the variation range of loss estimates of the other models in the case study.
Bumps in river profiles
(2017)
The analysis of longitudinal river profiles is an important tool for studying landscape evolution. However, characterizing river profiles based on digital elevation models (DEMs) suffers from errors and artifacts that particularly prevail along valley bottoms. The aim of this study is to characterize uncertainties that arise from the analysis of river profiles derived from different, near-globally available DEMs. We devised new algorithms quantile carving and the CRS algorithm - that rely on quantile regression to enable hydrological correction and the uncertainty quantification of river profiles. We find that globally available DEMs commonly overestimate river elevations in steep topography. The distributions of elevation errors become increasingly wider and right skewed if adjacent hillslope gradients are steep. Our analysis indicates that the AW3D DEM has the highest precision and lowest bias for the analysis of river profiles in mountainous topography. The new 12m resolution TanDEM-X DEM has a very low precision, most likely due to the combined effect of steep valley walls and the presence of water surfaces in valley bottoms. Compared to the conventional approaches of carving and filling, we find that our new approach is able to reduce the elevation bias and errors in longitudinal river profiles.
Previous research offers equivocal results regarding the effect of
social networking site use on individuals’ self-esteem. We con-
duct a systematic literature review to examine the existing litera-
ture and develop a theoretical framework in order to classify the
results. The framework proposes that self-esteem is affected by
three distinct processes that incorporate self-evaluative informa-
tion: social comparison processes, social feedback processing,
and self-reflective processes. Due to particularities of the social
networking site environment, the accessibility and quality of self-
evaluative information is altered, which leads to online-specific
effects on users’ self-esteem. Results of the reviewed studies
suggest that when a social networking site is used to compare
oneself with others, it mostly results in decreases in users’ self-
esteem. On the other hand, receiving positive social feedback
from others or using these platforms to reflect on one’s own self is
mainly associated with benefits for users’ self-esteem.
Nevertheless, inter-individual differences and the specific activ-
ities performed by users on these platforms should be considered
when predicting individual effects.
Contemporary drought impact assessments have been constrained due to data availability, leading to an incomplete representation of impact trends. To address this, we present a novel method for the comprehensive and near-real-time monitoring of drought socio-economic impacts based on media reports. We tested its application using the case of the exceptional 2018/19 German drought. By employing text mining techniques, 4839 impact statements were identified, relating to livestock, agriculture, forestry, fires, recreation, energy and transport sectors. An accuracy of 95.6% was obtained for their automatic classification. Furthermore, high levels of performance in terms of spatial and temporal precision were found when validating our results against independent data (e.g. soil moisture, average precipitation, population interest in droughts, crop yield and forest fire statistics). The findings highlight the applicability of media data for rapidly and accurately monitoring the propagation of drought consequences over time and space. We anticipate our method to be used as a starting point for an impact-based early warning system.
Here, a reliable and sensitive method for the determination of 38 (modified) mycotoxins was developed. Using a QuEChERS-based extraction method [acetonitrile/water/formic acid (75:20:5, v/v/v)], followed by two runs of high performance liquid chromatography tandem mass spectrometry with different conditions, relevant mycotoxins in cereals were analyzed. The method was validated according to the performance criteria defined by the European Commission (EC) in Commission Decision no. 657/2002. Limits of quantification ranged from 0.05 to 150 μg/kg. Good linearity (R2 > 0.99), recovery (61–120%), repeatability (RSDr < 15%), and reproducibility (RSDR < 20%) were obtained for most mycotoxins. However, validation results for Alternaria toxins and fumonisins were unsatisfying. Matrix effects (−69 to +59%) were compensated for using standard addition. Application on reference materials gave correct results while analysis of samples from local retailers revealed contamination, especially with deoxynivalenol, deoxynivalenol-3-glucoside, fumonisins, and zearalenone, in concentrations up to 369, 58, 1002, and 21 μg/kg, respectively.
The Strengths and Difficulties Questionnaire (SDQ) is a frequently used screening instrument for behavioral problems in children and adolescents. There is an ongoing controversy—not only in educational research—regarding the factor structure of the SDQ. Research results speak for a 3-factor as well as a 5-factor structure. The narrowband scales (5-factor structure) can be combined into broadband scales (3-factor structure). The question remains: Which factors (narrowband vs. broadband) are better predictors? With the prediction of child and adolescent outcomes (academic grades, well-being, and self-belief), we evaluated whether the broadband scales of internalizing and externalizing behavior (3-factor structure) or narrowband scales of behavior (5-factor structure) are better suited for predictive purposes in a cross-sectional study setting. The sample includes students in grades 5 to 9 (N = 4642) from the representative German Health Interview and Examination Survey for Children and Adolescents (KiGGS study). The results of model comparisons (broadband scale vs. narrowband scales) did not support the superiority of the broadband scales with regard to the prediction of child and adolescent outcomes. There is no benefit from subsuming narrowband scales (5-factor structure) into broadband scales (3-factor structure). The application of narrowband scales, providing a more differentiated picture of students’ academic and social situation, was more appropriate for predictive purposes. For the purpose of identifying students at risk of struggling in educational contexts, using the set of narrowband dimensions of behavior seems to be more suitable.
The Strengths and Difficulties Questionnaire (SDQ) is a frequently used screening instrument for behavioral problems in children and adolescents. There is an ongoing controversy—not only in educational research—regarding the factor structure of the SDQ. Research results speak for a 3-factor as well as a 5-factor structure. The narrowband scales (5-factor structure) can be combined into broadband scales (3-factor structure). The question remains: Which factors (narrowband vs. broadband) are better predictors? With the prediction of child and adolescent outcomes (academic grades, well-being, and self-belief), we evaluated whether the broadband scales of internalizing and externalizing behavior (3-factor structure) or narrowband scales of behavior (5-factor structure) are better suited for predictive purposes in a cross-sectional study setting. The sample includes students in grades 5 to 9 (N = 4642) from the representative German Health Interview and Examination Survey for Children and Adolescents (KiGGS study). The results of model comparisons (broadband scale vs. narrowband scales) did not support the superiority of the broadband scales with regard to the prediction of child and adolescent outcomes. There is no benefit from subsuming narrowband scales (5-factor structure) into broadband scales (3-factor structure). The application of narrowband scales, providing a more differentiated picture of students’ academic and social situation, was more appropriate for predictive purposes. For the purpose of identifying students at risk of struggling in educational contexts, using the set of narrowband dimensions of behavior seems to be more suitable.