scholarly journals Resilience of Epiphytic Lichens to Combined Effects of Increasing Nitrogen and Solar Radiation

2021 ◽  
Vol 7 (5) ◽  
pp. 333
Author(s):  
Lourdes Morillas ◽  
Javier Roales ◽  
Cristina Cruz ◽  
Silvana Munzi
Keyword(s):  
Global Change ◽  
Solar Radiation ◽  
Functional Groups ◽  
Physiological Response ◽  
Functional Group ◽  
Environmental Drivers ◽  
Combined Effects ◽  
Environmental Stressor ◽  
Comprehensive Understanding ◽  
Direct Sunlight

Lichens are classified into different functional groups depending on their ecological and physiological response to a given environmental stressor. However, knowledge on lichen response to the synergistic effect of multiple environmental factors is extremely scarce, although vital to get a comprehensive understanding of the effects of global change. We exposed six lichen species belonging to different functional groups to the combined effects of two nitrogen (N) doses and direct sunlight involving both high temperatures and ultraviolet (UV) radiation for 58 days. Irrespective of their functional group, all species showed a homogenous response to N with cumulative, detrimental effects and an inability to recover following sunlight, UV exposure. Moreover, solar radiation made a tolerant species more prone to N pollution’s effects. Our results draw attention to the combined effects of global change and other environmental drivers on canopy defoliation and tree death, with consequences for the protection of ecosystems.

scholarly journals Morpho-physiological response of Solanum macrocarpon L. seedlings to different light intensities

2018 ◽  
Vol 5 (10) ◽  
pp. 481-487
Author(s):  
Damilola Grace Ogunrotimi ◽  
Joshua Kayode
Keyword(s):  
Solar Radiation ◽  
Leaf Area ◽  
Plant Height ◽  
Physiological Response ◽  
Growth Parameters ◽  
Direct Sunlight ◽  
Stunted Growth ◽  
Light Intensities ◽  
Different Levels ◽  
Better Than

Seedlings of Solanum macrocarpon L. were transplanted into experimental pots containing 3 kg soil and placed under different levels of solar radiation to investigate their response to light intensities. The growth parameters revealed that seedlings under direct sunlight performed better than the ones under shade of mesh net. The plants growing under the shade had stunted growth and were highly susceptible to leaf abscission compared to those under direct sunlight which produced healthy stem and sturdy leaves. This could suggest S. macrocarpon possess higher tolerance to solar radiation. However, seedlings of under direct sunlight produced higher leaf area, leaf number, plant height and stem diameter than those under shade. High leaf area is important for light interception to allow for photosynthesis. These findings revealed that Solanum macrocarpon grows optimally under direct sunlight.

scholarly journals Intricacies of Social Movement Outcome Research and beyond: “How can you Tell” Social Movements Prompt Changes?

2012 ◽  
Vol 17 (4) ◽  
pp. 92-102 ◽  
Author(s):  
Doowon Suh
Keyword(s):  
Social Movements ◽  
Outcome Research ◽  
Evaluation Criteria ◽  
Combined Effects ◽  
Comprehensive Understanding ◽  
Specific Context ◽  
Invariant Model ◽  
Historical Progress ◽  
Collective Actors ◽  
Multiple Variables

Most scholars of social movements have been drawn to research on the politically contentious behavior of collective actors because of the conviction that social movements sometimes generate significant historical progress and social change. Yet movement outcome research has been least developed in the literature. This irony emanates from methodological and causal intricacies that fail to clearly explicate how social movements create change. The challenges encompass the heaped typologies, mutual inconsistencies, causal heterogeneities, and conflictive evaluation criteria of movement outcomes. To overcome these quandaries, this paper proposes that (1) any attempt to find an invariant model or general theorization of a movement outcome is inevitably futile; (2) instead, attention to the specific context of time and place in which social movements produce outcomes is necessary; and (3) a comprehensive understanding of the origins of a movement outcome becomes possible when multiple variables are considered and their combined effects are analyzed.

scholarly journals Food Additives Frequency in processed baby products in Cochabamba, Bolivia

2021 ◽  
Vol 17 (Especial) ◽  
pp. 19-27
Author(s):  
Nelcy Aguilar Sasari ◽  
Milenka Alessandra Fernández Ledezma ◽  
Tania Araujo-Burgos
Keyword(s):  
Shelf Life ◽  
Functional Groups ◽  
Frequency Analysis ◽  
Metropolitan Area ◽  
Sodium Nitrate ◽  
Functional Group ◽  
Food Additives ◽  
Processed Food ◽  
Food Labels ◽  
Organoleptic Properties

Additives are necessary substances to improve the nutritional and organoleptic properties and the shelf life of processed food. In addition, their use is regulated, and it must be declared on the food labels. Thus, the objective of this research was to determine the frequency of food additives in processed baby products in Cochabamba metropolitan area (Bolivia). Data were collected by label reading and a frequency analysis was performed by additives and by functional group. 26 baby products were found where 41 food additives were identified with an occurrence of 256 times, and a mean of 9,8 additives per product. Moreover, the functional groups most widely used are antioxidants and colorants. Finally, the most frequent additives are mostly harmless, except for sodium nitrate and copper sulfate.

scholarly journals Multi-model seascape genomics identifies distinct environmental drivers of selection among sympatric marine species

2020 ◽  
Author(s):  
Erica Nielsen ◽  
Romina Henriques ◽  
Maria Beger ◽  
Robert Toonen ◽  
Sophie von der Heyden
Keyword(s):  
Global Change ◽  
Outlier Detection ◽  
Genomic Variation ◽  
Sea Surface ◽  
Environmental Drivers ◽  
Comparative Approach ◽  
Evolutionary Potential ◽  
Environmental Selection ◽  
Outlier Loci ◽  
Isolation By Environment

Abstract Background: As global change and anthropogenic pressures continue to increase, conservation and management increasingly needs to consider species’ potential to adapt to novel environmental conditions. Therefore, it is imperative to characterise the main selective forces acting on ecosystems, and how these may influence the evolutionary potential of populations and species. Using a multi-model seascape genomics approach, we compare putative environmental drivers of selection in three sympatric southern African marine invertebrates with contrasting ecology and life histories: Cape urchin (Parechinus angulosus), Common shore crab (Cyclograpsus punctatus), and Granular limpet (Scutellastra granularis). Results: Using pooled (Pool-seq), restriction-site associated DNA sequencing (RAD-seq), and seven outlier detection methods, we characterise genomic variation between populations along a strong biogeographical gradient. Of the three species, only S. granularis showed significant isolation-by-distance, and isolation-by-environment driven by sea surface temperatures (SST). In contrast, sea surface salinity (SSS) and range in air temperature correlated more strongly with genomic variation in C. punctatus and P. angulosus. Differences were also found in genomic structuring between the three species, with outlier loci contributing to two clusters in the East and West Coasts for S. granularis and P. angulosus, but not for C. punctatus. Conclusion: The findings illustrate distinct evolutionary potential across species, suggesting that species-specific habitat requirements and responses to environmental stresses may be better predictors of evolutionary patterns than the strong environmental gradients within the region. We also found large discrepancies between outlier detection methodologies, and thus offer a novel multi-model approach to identifying the principal environmental selection forces acting on species. Overall, this work highlights how adding a comparative approach to seascape genomics (both with multiple models and species) can elucidate the intricate evolutionary responses of ecosystems to global change.

scholarly journals Multi-model seascape genomics identifies distinct environmental drivers of selection among sympatric marine species

2020 ◽  
Author(s):  
Erica Nielsen ◽  
Romina Henriques ◽  
Maria Beger ◽  
Robert Toonen ◽  
Sophie von der Heyden
Keyword(s):  
Global Change ◽  
Outlier Detection ◽  
Genomic Variation ◽  
Sea Surface ◽  
Environmental Drivers ◽  
Comparative Approach ◽  
Evolutionary Potential ◽  
Environmental Selection ◽  
Outlier Loci ◽  
Isolation By Environment

Abstract Background: As global change and anthropogenic pressures continue to increase, conservation and management increasingly needs to consider species’ potential to adapt to novel environmental conditions. Therefore, it is imperative to characterise the main selective forces acting on ecosystems, and how these may influence the evolutionary potential of populations and species. Using a multi-model seascape genomics approach, we compare the dominant environmental drivers of selection in three sympatric southern African marine invertebrates with contrasting ecology and life histories: Cape urchin ( Parechinus angulosus ), Common shore crab ( Cyclograpsus punctatu s), and Granular limpet ( Scutellastra granularis ). Results: Using pooled (Pool-seq), restriction-site associated DNA sequencing (RAD-seq), and seven outlier detection methods, we characterise genomic variation between populations along a strong biogeographical gradient. Of the three species, only S. granularis showed significant isolation-by-distance, and isolation-by-environment driven by sea surface temperatures (SST). In contrast, sea surface salinity (SSS) and range in air temperature correlated more strongly with genomic variation in C. punctatus and P. angulosus . Differences were also found in genomic structuring between the three species, with outlier loci contributing to two clusters in the East and West Coasts for S. granularis and P. angulosus , but not for C. punctatus . Conclusion: The findings illustrate distinct evolutionary potential across species, suggesting that species-specific habitat requirements and responses to environmental stresses better predict evolutionary patterns than the strong environmental gradients within the region. We also found large discrepancies between outlier detection methodologies, and thus offer a novel multi-model approach to identifying the principal environmental selection forces acting on species. Overall, this work highlights how adding a comparative approach to seascape genomics (both with multiple models and species) can elucidate the intricate evolutionary responses of ecosystems to global change.

scholarly journals Phytochemical Screening, Spectrum Profile of Functional Groups, and Effervescent Formulation of Kepok Banana Peels Stem Extract

2021 ◽  
Vol 4 (2) ◽  
pp. 66-72
Author(s):  
Robby Candra Purnama ◽  
Annisa Primadiamanti
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Secondary Metabolites ◽  
Functional Groups ◽  
Functional Group ◽  
Screening Method ◽  
Phytochemical Screening ◽  
Stem Extract ◽  
Group Profile ◽  
Banana Stem

Kepok banana plants contain secondary metabolites such as tannins and flavonoids. Tannins and flavonoids have various properties for human health. Research has been carried out to identify secondary metabolite compounds (tannins, flavonoids, and saponins) by using the phytochemical screening method to see the functional group profile contained in the extract of kepok banana stem waste. Kepok banana stem waste was extracted in 96% ethanol, then evaporated and screened phytochemically. This extract was used to prepare effervescently. Screening results showed that tannin and flavonoids were identified by the appearance of the following color black-green and dark red, respectively. Meanwhile, saponins were negative because the foam formed had a height of 0.3 cm and did not meet the saponins' positive requirements (1-3 cm high foam and stable for 5 minutes). Identification of functional groups in the extract of kepok banana stem waste using Fourier-transform Infrared Spectroscopy (FTIR) showed that C-C stretching in the area 2927.24 cm-1, O-H stretching in the 3423.87 cm-1 area, C=O stretching in the 1648.87 cm-1 area. Also appeared bending CH2 in the region of 1421.45 cm-1, and C-C in the area of 1149.98 cm-1. The characteristics of three different formulas (A, B, and C) of effervescent have been investigated: the moisture content of 2.51%; 2.55%, and 2.52%, respectively. Then, flow rate of 8.81 g/s; 8.83 g/s; and 8.82 g/s, compressibility of 14.5%; 14.4%; and 14.5%, and a pH of 5.97; 5.98; and 5.97 respectively. All parameters are eligible.

scholarly journals Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models

2021 ◽  
Author(s):  
Abigail Enders ◽  
Nicole North ◽  
Chase Fensore ◽  
Juan Velez-Alvarez ◽  
Heather Allen
Keyword(s):  
Machine Learning ◽  
Gas Phase ◽  
Functional Groups ◽  
Functional Group ◽  
Spectroscopic Method ◽  
Group Identification ◽  
Spectroscopic Technique ◽  
Ftir Spectra ◽  
Spectral Interpretation ◽  
Time Required

<p>Fourier Transform Infrared Spectroscopy (FTIR) is a ubiquitous spectroscopic technique. Spectral interpretation is a time-consuming process, but it yields important information about functional groups present in compounds and in complex substances. We develop a generalizable model via a machine learning (ML) algorithm using Convolutional Neural Networks (CNNs) to identify the presence of functional groups in gas phase FTIR spectra. The ML models will reduce the amount of time required to analyze functional groups and facilitate interpretation of FTIR spectra. Through web scraping, we acquire intensity-frequency data from 8728 gas phase organic molecules within the NIST spectral database and transform the data into images. We successfully train models for 15 of the most common organic functional groups, which we then determine via identification from previously untrained spectra. These models serve to expand the application of FTIR measurements for facile analysis of organic samples. Our approach was done such that we have broad functional group models that inference in tandem to provide full interpretation of a spectrum. We present the first implementation of ML using image-based CNNs for predicting functional groups from a spectroscopic method.</p>

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