Elgaardhay2416

Such limited biotic defence may mask strong physical and chemical defence mechanisms of Acacia trees against elephant damage. Ant assemblages in West Africa, unlike those in the more productive East Africa, are particularly species-poor. However, there is a convergence between these two regions in low rate of ant co-occurrence which might indicate strong competitive exclusion. Our study suggests that such low ant species richness while limiting the efficacy of mutualism in controlling mega-herbivore damage may mask a strong defence syndrome.Soil heterogeneity significantly affects plant dynamics such as plant growth and biomass. Most studies developed soil heterogeneity in two dimensions, i.e. either horizontally or vertically. However, soil heterogeneity in natural ecosystems varies both horizontally and vertically, i.e. in three dimensions. Previous studies on plant biomass and biomass allocation rarely considered the joint effects of soil heterogeneity and species composition. Thus, to investigate such joint effects on plant biomass and biomass allocation, a controlled experiment was conducted, where three levels of soil heterogeneity and seven types of species compositions were applied. Such soil heterogeneity was developed by filling nutrient-rich and nutrient-poor substrates in an alternative pattern in pots with different patch sizes (small, medium or large), and species compositions was achieved by applying three plant species (i.e. Festuca elata, Bromus inermis, Elymus breviaristatus) in all possible combinations (growing either in monoculture or in mixtures). Results showed that patch size significantly impacted plant biomass and biomass allocation, which differed among plant species. Specially, at the pot scale, with increasing patch size, shoot biomass decreased, while root biomass and RS ratio increased, and total biomass tended to show a unimodal pattern, where the medium patch supported higher total biomass. Moreover, at the substrate scale, more shoot biomass and total biomass were found in nutrient-rich substrate. Furthermore, at the community scale, two of the three target plant species growing in monoculture had more shoot biomass than those growing together with other species. Thus, our results indicate soil heterogeneity significantly affected plant biomass and biomass allocation, which differ among plant species, though more research is needed on the generalization on biomass allocation. We propose that soil heterogeneity should be considered more explicitly in studies with more species in long-term experiments.Pollen and nectar are the primary rewards offered by flowers to pollinators. In floral visitors of some plant species, pollen thieves and nectar robbers cause the reduction in pollen grain number and nectar volume, respectively. However, it remains unclear whether the absence of either of the two rewards in a given flower reduces its attraction to nectar- and pollen-collecting pollinators. We hypothesized that flowers removed of either nectar or pollen would attract fewer pollinators. We studied protandrous Impatiens oxyanthera, whose flowers provide bumblebee pollinators with both nectar and pollen in the male phase. We conducted floral reward manipulation experiments to explore how the removal of either nectar or pollen from flowers influences pollinator behaviour by comparing their visitation rates and visit duration. Compared with the control flowers, the flowers removed of pollen attracted significantly more bumblebee pollinators per 30 min, but the flowers removed of nectar or those removed of both pollen and nectar attracted significantly fewer bumblebee pollinators per 30 min. Moreover, the visit duration of bumblebee pollinators to control flowers or flowers removed of pollen was longer than that to flowers removed of nectar or those removed of both pollen and nectar. Our investigations indicated that compared with control flowers, the flowers removed of nectar attracted fewer bumblebee pollinators, supporting our hypothesis. However, our other hypothesis that pollen removal would reduce pollinator visits was not supported by our results. Instead, compared with control flowers, the flowers that contained only nectar attracted more bumblebee pollinators. Nectar seems to be the main reward, and bumblebee pollinators mainly used the absence of pollen as a visual signal to locate I. oxyanthera flowers with a potentially higher amount of nectar.Seasonal changes in climate are accompanied by shifts in carbon allocation and phenological changes in woody angiosperms, the timing of which can have broad implications for species distributions, interactions and ecosystem processes. During critical transitions from autumn to winter and winter to spring, physiological and anatomical changes within the phloem could impose a physical limit on the ability of woody angiosperms to transport carbon and signals. There is a paucity of the literature that addresses tree (floral or foliar) phenology, seasonal phloem anatomy and seasonal phloem physiology together, so our knowledge of how carbon transport could fluctuate seasonally, especially in temperate climates is limited. We review phloem phenology focussing on how sieve element anatomy and phloem sap flow could affect carbon availability throughout the year with a focus on winter. To investigate whether flow is possible in the winter, we construct a simple model of phloem sap flow and investigate how changes to the sap concentration, pressure gradient and sieve plate pores could influence flow during the winter. Our model suggests that phloem transport in some species could occur year-round, even in winter, but current methods for measuring all the parameters surrounding phloem sap flow make it difficult to test this hypothesis. We highlight outstanding questions that remain about phloem functionality in the winter and emphasize the need for new methods to address gaps in our knowledge about phloem function.Melatonin is an indolamine bioactive molecule that regulates a wide range of physiological processes during plant growth and enhances abiotic stress tolerance. Here we examined the putative role of exogenous melatonin application (foliar or root zone) in improving drought stress tolerance in soybean seedlings. Pre-treatment of soybean seedlings with melatonin (50 and 100 µM) was found to significantly mitigate the negative effects of drought stress on plant growth-related parameters and chlorophyll content. The beneficial impacts against drought were more pronounced by melatonin application in the rhizosphere than in foliar treatments. The melatonin-induced enhanced tolerance could be attributed to improved photosynthetic activity, reduction of abscisic acid and drought-induced oxidative damage by lowering the accumulation of reactive oxygen species and malondialdehyde. Interestingly, the contents of jasmonic acid and salicylic acid were significantly higher following melatonin treatment in the root zone than in foliar treatment compared with the control. The activity of major antioxidant enzymes such as superoxide dismutase, catalase, polyphenol oxidase, peroxidase and ascorbate peroxidase was stimulated by melatonin application. In addition, melatonin counteracted the drought-induced increase in proline and sugar content. These findings revealed that modifying the endogenous plant hormone content and antioxidant enzymes by melatonin application improved drought tolerance in soybean seedlings. Our findings provide evidence for the stronger physiological role of melatonin in the root zone than in leaves, which may be useful in the large-scale field level application during drought.Axonopus compressus also known as carpet grass is a robust, stoloniferous grass that can grow in minimal fertilization and resists well to abiotic and biotic stresses including low nitrogen (LN) stress. This study aimed at characterizing the agro-morphological and metabolome responses to LN in carpet grass leaves. Under LN stress, carpet grass increased yellowness of leaves and root dry matter while reduced turf quality and shoot dry weight. The metabolome comparison between samples from optimum and LN conditions indicated 304 differentially accumulated metabolites (DAMs), which could be classified into 12 major and 31 subclasses. The results revealed that the leaf tissues accumulated more anthocyanins and other flavonoid metabolites under LN stress. Conversely, amino acids, nucleic acids and their derivatives were reduced in response to LN stress. The overall evaluation of individual metabolites and pathways, and previous studies on metabolomes indicated that carpet grass reduced its energy consumption in leaves and increased the level of organic acid metabolism and secondary metabolism in order to resist LN stress conditions.Preterm birth (PTB) in a pregnant woman is the most serious issue in the field of Gynaecology and Obstetrics, especially in rural India. In recent years, various clinical prediction models for PTB have been developed to improve the accuracy of learning models. However, to the best of the authors' knowledge, most of them suffer from selecting the most accurate features from the medical dataset in linear time. The present paper attempts to design a machine learning model named as risk prediction conceptual model (RPCM) for the prediction of PTB. In this paper, a feature selection approach is proposed based on the notion of entropy. The novel approach is used to find the best maternal features (responsible for PTB) from the obstetrical dataset and aims to predict the classifier's accuracy at the highest level. The paper first deals with the review of PTB cases (which is neglected in many developing countries including India). Next, we collect obstetrical data from the Community Health Centre of rural areas (Kamdara, Jharkhand). The suggested approach is then applied on collected data to identify the excellent maternal features (text-based symptoms) present in pregnant women in order to classify all birth cases into term birth and PTB. The machine learning part of the model is implemented using three different classifiers, namely, decision tree (DT), logistic regression (LR), and support vector machine (SVM) for PTB prediction. The performance of the classifiers is measured in terms of accuracy, specificity, and sensitivity. Finally, the SVM classifier generates an accuracy of 90.9%, which is higher than other learning classifiers used in this study.Parkinson's disease (PD) is a neurodegenerative disorder characterized by progressive neuronal loss in different brain regions, including the dopaminergic (DA) neurons of the substantia nigra pars compacta (SNc). The aggregation of α-synuclein (α-Syn) plays an essential role in the progression of PD-related neuron toxicity. In this study, bioinformatic analysis was used to confirm differentially expressed genes between patients with PD and healthy donors. Immunofluorescence was used to study the aggregation of α-Syn. Flow cytometry was used to confirm the apoptosis of neurons. Western blot was used to investigate the underlying mechanism. Coimmunoprecipitation (co-IP) was used to verify the interaction between proteins. Luciferase activity assay was used to confirm the target gene of miRNA. In vitro protein ubiquitination assay was used to ascertain the role of S-phase kinase-associated protein 1 (SKP1) on the ubiquitination processes of polo-like kinase 2 (PLK2). The result indicated that miR-101-3p was overexpressed in the substantia nigra of the postmortem brains of patients with PD.