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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.
The ability of some chemical compounds to cause oxidative stress offers a fast and convenient way to study the responses of plants to reactive oxygen species (ROS). In order to unveil potential novel genetic players of the ROS-regulatory network, a population of similar to 2,000 randomly selected Arabidopsis thaliana T-DNA insertion mutants was screened for ROS sensitivity/resistance by growing seedlings on agar medium supplemented with stress-inducing concentrations of the superoxide-eliciting herbicide methyl viologen or the catalase inhibitor 3-amino-triazole. A semi-robotic setup was used to capture and analyze images of the chemically treated seedlings which helped interpret the screening results by providing quantitative information on seedling area and healthy-to-chlorotic tissue ratios for data verification. A ROS-related phenotype was confirmed in three of the initially selected 33 mutant candidates, which carry T-DNA insertions in genes encoding a Ring/Ubox superfamily protein, ABI5 binding protein 1 (AFP1), previously reported to be involved in ABA signaling, and a protein of unknown function, respectively. In addition, we identified six mutants, most of which have not been described yet, that are related to growth or chloroplast development and show defects in a ROS-independent manner. Thus, semi-automated image capturing and phenotyping applied on publically available T-DNA insertion collections adds a simple means for discovering novel mutants in complex physiological processes and identifying the genes involved.
Effects of intraspecific and community density on the lifetime fecundity of long-lived shrubs
(2013)
Intra- and interspecific density dependence has profound consequences for plant population and community dynamics. In long-lived plants, however, lifetime patterns and mechanisms of density dependence are difficult to study. Here, we examine effects of intraspecific and community density on the lifetime fecundity of two long-lived shrub species from South African Fynbos: Protea repens (animal-pollinated, hermaphroditic) and Leucadendron rubrum (wind-pollinated, dioecious). Both species are serotinous, retaining seeds in cones until fire kills the mother plant. We measured lifetime fecundity as the product of cone number, proportion of cones that are not damaged by predation and seed set (fertile seeds per intact cone). Intraspecific and community densities were quantified by counting individuals of target species and all Proteaceae in small- and large-scale neighbourhoods (10 m and 50 m radius) around each focal individual. Additionally, we determined the age and size of focal individuals. We found that lifetime fecundity of the wind-pollinated L rubrum is density independent. In contrast, the lifetime fecundity of the animal-pollinated P. repens increases with large-scale intraspecific density and shows a hump-shaped relationship to large-scale community density. Community density has a hump-shaped effect on seed set (probably through partial absence of generalized pollinators at low and competition for pollinators at high densities) and negatively affects cone number per individual. For both species, plant age decreases seed set while increasing lifetime fecundity. The qualitative differences in the density dependence of lifetime fecundity may arise from differences between animal and wind pollination. In particular, interactions with generalized animal pollinators may cause community-level Allee effects with profound consequences for the future dynamics of long-lived plant populations and communities.
A novel procedure has been developed to conduct cell structure measurements on increment core samples of conifers. The procedure combines readily available hardware and software equipment. The essential part of the procedure is the application of a confocal laser scanning microscope (CLSM) which captures images directly from increment cores surfaced with the advanced WSL core-microtome. Cell wall and lumen are displayed with a strong contrast due to the monochrome black and green nature of the images. Consecutive images are merged into long images representing entire increment cores which are then analysed for cell structures in suitable software.
Mean age of carbon in fine roots from temperate forests and grasslands with different management
(2013)
Fine roots are the most dynamic portion of a plant's root system and a major source of soil organic matter. By altering plant species diversity and composition, soil conditions and nutrient availability, and consequently belowground allocation and dynamics of root carbon (C) inputs, land-use and management changes may influence organic C storage in terrestrial ecosystems. In three German regions, we measured fine root radiocarbon (C-14) content to estimate the mean time since C in root tissues was fixed from the atmosphere in 54 grassland and forest plots with different management and soil conditions. Although root biomass was on average greater in grasslands 5.1 +/- 0.8 g (mean +/- SE, n = 27) than in forests 3.1 +/- 0.5 g (n = 27) (p < 0.05), the mean age of C in fine roots in forests averaged 11.3 +/- 1.8 yr and was older and more variable compared to grasslands 1.7 +/- 0.4 yr (p < 0.001). We further found that management affects the mean age of fine root C in temperate grasslands mediated by changes in plant species diversity and composition. Fine root mean C age is positively correlated with plant diversity (r = 0.65) and with the number of perennial species (r = 0.77). Fine root mean C age in grasslands was also affected by study region with averages of 0.7 +/- 0.1 yr (n= 9) on mostly organic soils in northern Germany and of 1.8 +/- 0.3 yr (n = 9) and 2.6 +/- 0.3 (n = 9) in central and southern Germany (p < 0.05). This was probably due to differences in soil nutrient contents and soil moisture conditions between study regions, which affected plant species diversity and the presence of perennial species. Our results indicate more long-lived roots or internal redistribution of C in perennial species and suggest linkages between fine root C age and management in grasslands. These findings improve our ability to predict and model belowground C fluxes across broader spatial scales.
Huntington disease (HD), a dominantly inherited neurodegenerative disorder caused by the expansion of a CAG-encoded polyglutamine (polyQ) repeat in huntingtin (Htt), displays a highly heterogeneous etiopathology and disease onset. Here, we show that the translation of expanded CAG repeats in mutant Htt exon 1 leads to a depletion of charged glutaminyl-transfer RNA (tRNA) Gln-CUG that pairs exclusively to the CAG codon. This results in translational frameshifting and the generation of various transframe-encoded species that differently modulate the conformational switch to nucleate fibrillization of the parental polyQ protein. Intriguingly, the frameshifting frequency varies strongly among different cell lines and is higher in cells with intrinsically lower concentrations of tRNA Gln-CUG. The concentration of tRNA Gln-CUG also differs among different brain areas in the mouse. We propose that translational frameshifting may act as a significant disease modifier that contributes to the cell-selective neurotoxicity and disease course heterogeneity of HD on both cellular and individual levels.
Habitat fragmentation is one of the most important causes for the decline of plant species. However, plants differing in phylogeny, habitat requirements and biology are likely to respond differently to habitat fragmentation. We ask whether case studies on the effects of habitat fragmentation conducted so far allow generalizations about its effects on the fitness and genetic diversity of populations of endangered plant species. We compared the characteristics of plant species endangered in Germany whose sensitivity to habitat fragmentation had been studied with those of the endangered species that had not been studied. We found strong discrepancies between the two groups with regard to their taxonomy and traits relevant to their sensitivity to habitat fragmentation. Monocots, graminoids, clonal, abiotically pollinated and self compatible species were underrepresented among the studied species, and most study species were from a few habitat types, in particular grasslands. We conclude that our current knowledge of the effects of habitat fragmentation on plant populations is not sufficient to provide widely applicable guidelines for species management. The selection of species studied so far has been biased toward species from certain habitats and species exhibiting traits that probably make them vulnerable to habitat fragmentation. Future studies should include community-wide approaches in different habitats, e.g. re-visitation studies in which the species pool is assessed at different time intervals, and population-biological studies of species from a wide range of habitats, and of different life forms and growth strategies. A more representative picture of the effects of habitat fragmentation would allow a better assessment of threats and more specific recommendations for optimally managing populations of endangered plants.
In this BEEBOOK paper we present a set of established methods for quantifying honey bee behaviour. We start with general methods for preparing bees for behavioural assays. Then we introduce assays for quantifying sensory responsiveness to gustatory, visual and olfactory stimuli. Presentation of more complex behaviours like appetitive and aversive learning under controlled laboratory conditions and learning paradigms under free-flying conditions will allow the reader to investigate a large range of cognitive skills in honey bees. Honey bees are very sensitive to changing temperatures. We therefore present experiments which aim at analysing honey bee locomotion in temperature gradients. The complex flight behaviour of honey bees can be investigated under controlled conditions in the laboratory or with sophisticated technologies like harmonic radar or RFID in the field. These methods will be explained in detail in different sections. Honey bees are model organisms in behavioural biology for their complex yet plastic division of labour. To observe the daily behaviour of individual bees in a colony, classical observation hives are very useful. The setting up and use of typical observation hives will be the focus of another section. The honey bee dance language has important characteristics of a real language and has been the focus of numerous studies. We here discuss the background of the honey bee dance language and describe how it can be studied. Finally, the mating of a honey bee queen with drones is essential to survival of the entire colony. We here give detailed and structured information how the mating behaviour of drones and queens can be observed and experimentally manipulated.
The ultimate goal of this chapter is to provide the reader with a comprehensive set of experimental protocols for detailed studies on all aspects of honey bee behaviour including investigation of pesticide and insecticide effects.
The digital laser rangefinder GLM Professional (R) BOSCH 250 VF was tested as a modified preproduction model with regard to its applicability of quantifying humans' height. The aim of this investigation was to determine and evaluate the instrument's precision, as well as its manageability within anthropometric field studies. Data collected by the digital laser rangefinder did not show a significant difference to data of control by an anthropometer. Furthermore, more than 96% of the difference values are located within area of agreement. Nevertheless, the GLM Professional (R) is a highly sensitive instrument and mean SD within threefold data acquisition is twice as high as SD resulting from data collection by an anthropometer. However, due to the minimal percentage differences within data acquisition and compared to the standard method, the GLM Professional (R) is proved to be a reliable instrument and to be highly applicable for anthropometric field studies. Furthermore, due to its excellent manageability and compact size, the GLM Professional (R) shows a very good applicability even for less trained anthropometrists and thus ameliorates the possibilities of collecting reliable data within anthropometric field studies.