The influence of sampling design on tree-ring-based quantification of forest growth

Tree-rings offer one of the few possibilities to empirically quantify and reconstruct forest growth dynamics over years to millennia. Contemporaneously with the growing scientific community employing tree-ring parameters, recent research has suggested that commonly applied sampling designs (i.e. how and which trees are selected for dendrochronological sampling) may introduce considerable biases in quantifications of forest responses to environmental change. To date, a systematic assessment of the consequences of sampling design on dendroecological and-climatological conclusions has not yet been performed. Here, we investigate potential biases by sampling a large population of trees and replicating diverse sampling designs. This is achieved by retroactively subsetting the population and specifically testing for biases emerging for climate reconstruction, growth response to climate variability, long-term growth trends, and quantification of forest productivity. We find that commonly applied sampling designs can impart systematic biases of varying magnitude to any type of tree-ring-based investigations, independent of the total number of samples considered. Quantifications of forest growth and productivity are particularly susceptible to biases, whereas growth responses to short-term climate variability are less affected by the choice of sampling design. The world's most frequently applied sampling design, focusing on dominant trees only, can bias absolute growth rates by up to 459% and trends in excess of 200%. Our findings challenge paradigms, where a subset of samples is typically considered to be representative for the entire population. The only two sampling strategies meeting the requirements for all types of investigations are the (i) sampling of all individuals within a fixed area; and (ii) fully randomized selection of trees. This result advertises the consistent implementation of a widely applicable sampling design to simultaneously reduce uncertainties in tree-ring-based quantifications of forest growth and increase the comparability of datasets beyond individual studies, investigators, laboratories, and geographical boundaries.

Resource-Mediated Indirect Effects of Grassland Management on Arthropod Diversity

Intensive land use is a driving force for biodiversity decline in many ecosystems. In semi-natural grasslands, land-use activities such as mowing, grazing and fertilization affect the diversity of plants and arthropods, but the combined effects of different drivers and the chain of effects are largely unknown. In this study we used structural equation modelling to analyse how the arthropod communities in managed grasslands respond to land use and whether these responses are mediated through changes in resource diversity or resource quantity (biomass). Plants were considered resources for herbivores which themselves were considered resources for predators. Plant and arthropod (herbivores and predators) communities were sampled on 141 meadows, pastures and mown pastures within three regions in Germany in 2008 and 2009. Increasing land-use intensity generally increased plant biomass and decreased plant diversity, mainly through increasing fertilization. Herbivore diversity decreased together with plant diversity but showed no response to changes in plant biomass. Hence, land-use effects on herbivore diversity were mediated through resource diversity rather than quantity. Land-use effects on predator diversity were mediated by both herbivore diversity (resource diversity) and herbivore quantity (herbivore biomass), but indirect effects through resource quantity were stronger. Our findings highlight the importance of assessing both direct and indirect effects of land-use intensity and mode on different trophic levels. In addition to the overall effects, there were subtle differences between the different regions, pointing to the importance of regional land-use specificities. Our study underlines the commonly observed strong effect of grassland land use on biodiversity. It also highlights that mechanistic approaches help us to understand how different land-use modes affect biodiversity.

Simultaneous quantification of delta-9-THC, THC-acid A, CBN and CBD in seized drugs using HPLC-DAD

An HPLC-DAD method for the quantitative analysis of Δ(9)-tetrahydrocannabinol (THC), Δ(9)-tetrahydrocannabinolic acid-A (THCA-A), cannabidiol (CBD), and cannabinol (CBN) in confiscated cannabis products has been developed, fully validated and applied to analyse seized cannabis products. For determination of the THC content of plant material, this method combines quantitation of THCA-A, which is the inactive precursor of THC, and free THC. Plant material was dried, homogenized and extracted with methanol by ultrasonication. Chromatographic separation was achieved with a Waters Alliance 2695 HPLC equipped with a Merck LiChrospher 60 RP-Select B (5μm) precolumn and a Merck LiChroCart 125-4 LiChrospher 60 RP-Select B (5μm) analytical column. Analytes were detected and quantified using a Waters 2996 photo diode array detector. This method has been accepted by the public authorities of Switzerland (Bundesamt für Gesundheit, Federal Office of Public Health), and has been used to analyse 9092 samples since 2000. Since no thermal decarboxylation of THCA-A occurs, the method is highly reproducible for different cannabis materials. Two calibration ranges are used, a lower one for THC, CBN and CBD, and a higher one for THCA-A, due to its dominant presence in fresh plant material. As provider of the Swiss proficiency test, the robustness of this method has been tested over several years, and homogeneity tests even in the low calibration range (1%) show high precision (RSD≤4.3%, except CBD) and accuracy (bias≤4.1%, except CBN).

Detection and quantification of leptospires in urine of dogs: a maintenance host for the zoonotic disease leptospirosis.

Leptospirosis is a global zoonotic disease. Pathogenic Leptospira species, the causative agent of leptospirosis, colonize the renal tubules of chronically infected maintenance hosts such as dogs, rats and cattle. Maintenance hosts typically remain clinically asymptomatic and shed leptospires into the environment via urine. In contrast, accidental hosts such as humans can suffer severe acute forms of the disease. Infection results from direct contact with infected urine or indirectly, through contaminated water sources. In this study, a quantitative real-time PCR specific for lipL32 was designed to detect the urinary shedding of leptospires from dogs. The sensitivity and specificity of the assay was evaluated using both a panel of pathogenic Leptospira species and clinical microbial isolates, and samples of urine collected from experimentally infected rats and non-infected controls. The lower limit of detection was approximately 3 genome equivalents per reaction. The assay was applied to canine urine samples collected from local dog sanctuaries and the University Veterinary Hospital (UVH) at University College Dublin. Of 525 canine urine samples assayed, 37 were positive, indicating a prevalence of urinary shedding of leptospires of 7.05%. These results highlight the need to provide effective canine vaccination strategies and raise public health awareness.

Postmortem MR quantification of the heart for characterization and differentiation of ischaemic myocardial lesions.

OBJECTIVES Recently, an MRI quantification sequence has been developed which can be used to acquire T1- and T2-relaxation times as well as proton density (PD) values. Those three quantitative values can be used to describe soft tissue in an objective manner. The purpose of this study was to investigate the applicability of quantitative cardiac MRI for characterization and differentiation of ischaemic myocardial lesions of different age. MATERIALS AND METHODS Fifty post-mortem short axis cardiac 3 T MR examinations have been quantified using a quantification sequence. Myocardial lesions were identified according to histology and appearance in MRI images. Ischaemic lesions were assessed for mean T1-, T2- and proton density values. Quantitative values were plotted in a 3D-coordinate system to investigate the clustering of ischaemic myocardial lesions. RESULTS A total of 16 myocardial lesions detected in MRI images were histologically characterized as acute lesions (n = 8) with perifocal oedema (n = 8), subacute lesions (n = 6) and chronic lesions (n = 2). In a 3D plot comprising the combined quantitative values of T1, T2 and PD, the clusters of all investigated lesions could be well differentiated from each other. CONCLUSION Post-mortem quantitative cardiac MRI is feasible for characterization and discrimination of different age stages of myocardial infarction. KEY POINTS • MR quantification is feasible for characterization of different stages of myocardial infarction. • The results provide the base for computer-aided MRI cardiac infarction diagnosis. • Diagnostic criteria may also be applied for living patients.

Temperature dependence of postmortem MR quantification for soft tissue discrimination.

OBJECTIVES To investigate and correct the temperature dependence of postmortem MR quantification used for soft tissue characterization and differentiation in thoraco-abdominal organs. MATERIAL AND METHODS Thirty-five postmortem short axis cardiac 3-T MR examinations were quantified using a quantification sequence. Liver, spleen, left ventricular myocardium, pectoralis muscle and subcutaneous fat were analysed in cardiac short axis images to obtain mean T1, T2 and PD tissue values. The core body temperature was measured using a rectally inserted thermometer. The tissue-specific quantitative values were related to the body core temperature. Equations to correct for temperature differences were generated. RESULTS In a 3D plot comprising the combined data of T1, T2 and PD, different organs/tissues could be well differentiated from each other. The quantitative values were influenced by the temperature. T1 in particular exhibited strong temperature dependence. The correction of quantitative values to a temperature of 37 °C resulted in better tissue discrimination. CONCLUSION Postmortem MR quantification is feasible for soft tissue discrimination and characterization of thoraco-abdominal organs. This provides a base for computer-aided diagnosis and detection of tissue lesions. The temperature dependence of the T1 values challenges postmortem MR quantification. Equations to correct for the temperature dependence are provided. KEY POINTS • Postmortem MR quantification is feasible for soft tissue discrimination and characterization • Temperature dependence of the T1 values challenges the MR quantification approach • The results provide the basis for computer-aided postmortem MRI diagnosis • Diagnostic criteria may also be applied for living patients.

Quantification of nanoparticles at the single-cell level: an overview about state-of-the-art techniques and their limitations.

With the increasing production and use of engineered nanoparticles it is crucial that their interaction with biological systems is understood. Due to the small size of nanoparticles, their identification and localization within single cells is extremely challenging. Therefore, various cutting-edge techniques are required to detect and to quantify metals, metal oxides, magnetic, fluorescent, as well as electron-dense nanoparticles. Several techniques will be discussed in detail, such as inductively coupled plasma atomic emission spectroscopy, flow cytometry, laser scanning microscopy combined with digital image restoration, as well as quantitative analysis by means of stereology on transmission electron microscopy images. An overview will be given regarding the advantages of those visualization/quantification systems, including a thorough discussion about limitations and pitfalls.

Detection and quantification of Flavobacterium psychrophilum in water and fish tissue samples by quantitative real time PCR.

BACKGROUND Flavobacterium psychrophilum is the agent of Bacterial Cold Water Disease and Rainbow Trout Fry Syndrome, two diseases leading to high mortality. Pathogen detection is mainly carried out using cultures and more rapid and sensitive methods are needed. RESULTS We describe a qPCR technique based on the single copy gene β' DNA-dependent RNA polymerase (rpoC). Its detection limit was 20 gene copies and the quantification limit 103 gene copies per reaction. Tests on spiked spleens with known concentrations of F. psychrophilum (106 to 101 cells per reaction) showed no cross-reactions between the spleen tissue and the primers and probe. Screening of water samples and spleens from symptomless and infected fishes indicated that the pathogen was already present before the outbreaks, but F. psychrophilum was only quantifiable in spleens from diseased fishes. CONCLUSIONS This qPCR can be used as a highly sensitive and specific method to detect F. psychrophilum in different sample types without the need for culturing. qPCR allows a reliable detection and quantification of F. psychrophilum in samples with low pathogen densities. Quantitative data on F. psychrophilum abundance could be useful to investigate risk factors linked to infections and also as early warning system prior to potential devastating outbreak.

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

Why do adaptable people feel less insecure? Indirect effects of career adaptability on job and career insecurity via two types of perceived marketability

The aim of the present study was to analyze if and how career adaptability reduces different types of insecurity. More specifically, we argue in a theoretical model at the intersection of career and organizational research that perceived internal and external marketability serve as connecting variables in the link between career adaptability and job and career insecurity. We tested our assumptions by means of multiple indirect effects path analyses across two measurement points (6 month timespan) with data from 142 university researchers working in the STEM fields. The results showed that career adaptability was positively related to perceived internal and external marketability, which both subsequently were negatively associated with job and career insecurity. We draw theoretical implications for career research in intra- and extraorganizational settings and discuss practical implications for fostering secure employment.

Social Support at the Workplace, Motivation to Transfer, and Training Transfer: A Multi-Level Indirect Effects Model

Supervisor support, peer support and transfer motivation have been identified as important predictors for training transfer. Transfer motivation is supposed to mediate the support–training transfer relationship. Especially after team training interventions that include all team members (i.e., intact-team training), individual perception of these factors might be shared among team members. However, an integration of the team level in the training transfer process is rare, yet still needed. Analyzing 194 employees from 34 teams in the context of intact-team training interventions, we found similar relationships and processes at both levels of analysis: Social support enhances transfer motivation at the individual and team levels. Furthermore, motivation to transfer increases training transfer and serves as a connecting mechanism in the social support–training transfer link. The results underline the importance of (1) considering multiple levels in theories and research about the training transfer process and (2) ensuring the practice of individual-directed support and a shared, supportive climate within teams.