Ground-Penetrating Radar as phenotyping tool for characterizing intraspecific variability in root traits of a widespread conifer

Background and Aim Drought is the main abiotic stress affecting Mediterranean forests. Root systems are responsible for water uptake, but intraspecific variability in tree root morphology is poorly understood mainly owing to sampling difficulties. The aim of this study was to gain knowledge on the adaptive relevance of rooting traits for a widespread pine using a non-invasive, high-throughput phenotyping technique. Methods Ground-Penetrating Radar (GPR) was used to characterize variability in coarse root features (depth, diameter and frequency) among populations of the Mediterranean conifer Pinus halepensis evaluated in a common garden. GPR records were examined in relation to aboveground growth and climate variables at origin of populations. Results Variability was detected for root traits among 56 range-wide populations categorized into 16 ecotypes. Root diameter decreased eastward within the Mediterranean basin. In turn, root frequency, but not depth and diameter, decreased following a northward gradient. Root traits also varied with climatic variables at origin such as the ratio of summer to annual precipitation, summer temperature or solar radiation. Particularly, root frequency increased with aridity, whereas root depth and diameter were maximum for ecotypes occupying the thermal midpoint of the species distribution range. Conclusion GPR is a high-throughput phenotyping tool that allows detection of intraspecific variation in root traits of P. halepensis and its dependencies on eco-geographic characteristics at origin, thereby informing on the adaptive relevance of root systems for the species. It is also potentially suited for inferring population divergence in resource allocation above- and belowground in forest genetic trials.

Stratification of populations with skewed distribution

The problem of efficient stratification in the case of skewed population is considered. Four stratification methods are examined. A new adjusted geometric stratification method is introduced. This method is compared by simulation with the Dalenius-Hodges cumulative root frequency method, the geometric method proposed by Gunning and Horgan [2], and the power method offered by Plikusas in [6]. The simulation results show that in most cases considered the power method is the most efficient one.

Ground-penetrating Radar as Phenotyping Tool for Characterizing Intraspecific Variability in Root Traits of Pinus Halepensis

Background and AimDrought is the main factor limiting Mediterranean forest ecosystem productivity. Root systems are responsible for water uptake but intraspecific variability in root morphology is poorly understood, mainly due to sampling complexity. The main aim of this study was to gain knowledge on the adaptive relevance of rooting traits for a widespread conifer using a non-invasive high-throughput technique.MethodsGround-Penetrating Radar (GPR) was used to characterize variability in coarse root features (frequency, depth, and diameter) among populations of the Mediterranean pine Pinus halepensis evaluated in a common garden. GPR records were analysed in relation to aboveground growth and also climate variables at origin of populations.ResultsGenotypic variability was detected for root traits among 56 range-wide populations categorized into 16 ecotypes. Root diameter of populations decreased eastward within the Mediterranean basin. Root frequency, but not depth and diameter, decreased following a northward gradient. Genotypic variation in root traits varied with climatic variables at origin such as summer to annual precipitation ratio, summer temperature and solar radiation. Particularly, root frequency increased with aridity, whereas root depth and diameter were maximum in ecotypes occupying the thermal midpoint of the species distribution range.Conclusion GPR is a high-throughput phenotyping tool that allows detection of intraspecific variation in root traits of Aleppo pine and its dependencies of eco-geographic characteristics at origin, thereby informing on the adaptive relevance of root systems for the species. It is also potentially suited for inferring population divergence in resource allocation above and belowground in forest genetic trials.

An Analysis of Extent of Use of Online Utility Services in Punjab, India

Aim: To analyze the extent of use of online utility services. Study Design: Descriptive survey research design. Place and Duration of Study: Rural (Doraha and Sidhwan Bet block), peri-urban (Ayali Kalan, Sunet and Threeke villages of Ludhiana I block) and urban areas of Ludhiana district, between August 2018 to May 2019. Methodology: Using a structured interview schedule, data was collected randomly from 180 respondents having sixty online utility service users each from rural, peri-urban and urban areas of Ludhiana district of Punjab, India. The statistical tools such as frequency distribution, percentage, arithmetic mean, category interval method, Kruskal Wallis H-test for k independent samples and cumulative cube root frequency method were used for the analysis of data along with Statistical Package for Social Sciences (SPSS) software. Results: Overall, higher percentage of the respondents had moderate to high extent of use of online utility services and were using them for bill payment, online/mobile banking, entertainment, online shopping and for other miscellaneous services. Conclusion: Extent of use of different online utility services was comparatively higher among urban respondents.

Lexical dynamics for low-frequency complex words

In this study we examine the word recognition process for low-frequency morphologically complex words. One goal of the study was to replicate and expand upon findings suggesting facilitative effects of morphological relatives of a target word. A second goal was to demonstrate the need for a reinterpretation of root and surface frequency effects, which traditionally have been taken as indicators of parsing-based and memory-driven processing, respectively. In a first study, we used the same stimuli across auditory and visual lexical decision and naming. Mixed-effects statistical modeling revealed that surface frequency was a robust predictor of RTs even in the very low end of the distribution, but root frequency was not. Also, the nature of the similarity between a target and its lexical competitors is crucial. Measures gauging the influence of morphological relatives of the target were facilitative, while measures gauging the influence of words related only in form were inhibitory. A second study analyzing data from the English Lexicon Project, for a large sample of words from across the full frequency range, supports these conclusions. An information-theoretical analysis of root and surface frequency explains why surface frequency must be the most important predictor, with only a marginal role for root frequency.