Tree-rings δ13C different responses to environmental factors in angiosperms and gymnosperms at global scale

2021 ◽  
Author(s):  
Xiaozhen Li ◽  
Guo Chen ◽  
Wenyi Qin ◽  
Peng Wang ◽  
Xiang Wang
Keyword(s):  
Tree Rings ◽  
Industrial Revolution ◽  
Isotope Composition ◽  
Environmental Parameters ◽  
Global Scale ◽  
Published Data ◽  
Atmospheric Concentration ◽  
Machine Learning Methods ◽  
Relationship Of ◽  
Climatic Information

<p>Tree-rings, was an extraordinary information base of climate. The global climatic change has been modifying ecosystem, it is important to understand mechanism of how plants respond to climate change. The carbon isotope composition of tree-rings corrected to the value before industrial revolution (δ<sup>13</sup>C<sub>ring</sub>) can provide climatic information and carbon and water balance relationship of plants. However, it was still a challenge to disentangle the influence of different environmental parameters on δ<sup>13</sup>C<sub>ring</sub> among different tree types. We collected published data of δ<sup>13</sup>C<sub>ring</sub> from published papers and study how angiosperms and gymnosperms responsed to different environmental parameters. The results showed that the δ<sup>13</sup>C<sub>ring </sub>of angiosperms and gymnosperms were significantly different and there was a decrasing trend in δ<sup>13</sup>C<sub>ring</sub> of angiosperms and gymnosperms. In this study, we found that atmospheric concentration (C<sub>a</sub>) was not the mainly factor to influence the δ<sup>13</sup>C<sub>ring</sub>, and the MAT and PRE were the most important environmental parameters to influence the decreasing trend of δ<sup>13</sup>C<sub>ring</sub> for angiosperms and gymnosperms, respectively. Additionally, the global isoscapes of δ<sup>13</sup>C<sub>ring</sub> were not established, in this study, three machine learning methods to predict the spatial distribution of δ<sup>13</sup>C<sub>ring</sub> were done, the results showed that RF was the best model to established the isoscapes of δ<sup>13</sup>C<sub>ring</sub>.</p>

scholarly journals Tritium and 14C in Tree Rings of the Last Three Decades

Radiocarbon ◽  
1989 ◽  
Vol 31 (03) ◽  
pp. 766-770 ◽  
Author(s):  
Kristóf Kozák ◽  
Bogomil Obelić ◽  
Nada Horvatinčić
Keyword(s):  
Tree Rings ◽  
Catalytic Reaction ◽  
Water Samples ◽  
Proportional Counter ◽  
Liquid Scintillation ◽  
Global Scale ◽  
Scintillation Counting ◽  
Published Data ◽  
The Past ◽  
Free Hydrogen

Tree rings spanning the past three decades were collected from Picea spp trees grown in Matra, northern Hungary. Cellulose was prepared from the wood and samples were separately combusted for tritium and 14C analyses. Methane was synthesized from CO2 obtained by sample combustion via catalytic reaction with tritium-free hydrogen. 14C activity was measured by proportional counter. The exchangeable tritium was removed from cellulose samples used for tritium analysis. Water samples produced by combustion were measured by liquid scintillation counting. The distribution of tritium and 14C activities in tree rings are shown for years 1956–1986. Results are compared with published data on global-scale distribution of 14C and HTO. A comparison of tritium activity in precipitation and wine samples from the same region is presented.

HUBUNGAN KEPADATAN BIVALVIA DENGAN PARAMETER LINGKUNGAN DI PESISIR TANJUNG PURA KABUPATEN BANGKA TENGAH

2020 ◽  
Vol 13 (2) ◽  
pp. 112-121
Author(s):  
Sudiyar . ◽  
Okto Supratman ◽  
Indra Ambalika Syari
Keyword(s):  
Negative Impact ◽  
Principal Component ◽  
Environmental Parameters ◽  
Data Retrieval ◽  
Distribution Patterns ◽  
Random System ◽  
System Method ◽  
Relationship Of ◽  
The Relationship ◽  
Anadara Granosa

The destructive fishing feared will give a negative impact on the survival of this organism. This study aims to analyze the density of bivalves, distribution patterns, and to analyze the relationship of bivalves with environmental parameters in Tanjung Pura village. This research was conducted in March 2019. The systematic random system method was used for collecting data of bivalves. The collecting Data retrieval divided into five research stasions. The results obtained 6 types of bivalves from 3 families and the total is 115 individuals. The highest bivalve density is 4.56 ind / m², and the lowest bivalves are located at station 2,1.56 ind / m²,  The pattern of bivalve distribution in the Coastal of Tanjung Pura Village is grouping. The results of principal component analysis (PCA) showed that Anadara granosa species was positively correlated with TSS r = 0.890, Dosinia contusa, Anomalocardia squamosa, Mererix meretrix, Placamen isabellina, and Tellinella spengleri were positively correlated with currents r = 0.933.

Climate and land-use effects on hydrological and vegetation signals during the last three millennia: Evidence from sedimentary leaf waxes in southwestern Morocco

The Holocene ◽  
2021 ◽  
pp. 095968362098805
Author(s):  
Asmae Baqloul ◽  
Enno Schefuß ◽  
Martin Kölling ◽  
Lydie Dupont ◽  
Jeroen Groeneveld ◽  
...  
Keyword(s):  
Land Use ◽  
Carbon Isotope ◽  
Vegetation History ◽  
Isotope Composition ◽  
Stable Carbon Isotope ◽  
Economic Stress ◽  
Published Data ◽  
Leaf Waxes ◽  
Argan Tree ◽  
Precipitation Changes

The southwest of Morocco is considered to be an area of refuge within the Mediterranean region, hosting the endemic tropical Argan tree. This region is presently subject to severe droughts, desertification and land degradation, and likely facing increased climate variability and socio-economic stress in the future. Here, we use the stable hydrogen and carbon isotope composition (δD and δ13C) of plant-waxes in a high-resolution marine sediment core (GeoB8601-3) collected off Cape Ghir in southwestern Morocco, in combination with published data on pollen and XRF element ratios from the same archive. We aim to reconstruct the hydroclimate and vegetation history during the last 3000 years. Stable carbon isotope compositions of leaf waxes (δ13Cwax) show that natural vegetation in southwestern Morocco consists of C3 plants. Minor variations in δ13Cwax were positively correlated to changes in stable hydrogen isotope compositions of leaf waxes (δDwax) before 700 CE. Changes in rainfall amounts and water use efficiency indicate a clear vegetation response to precipitation changes and thus to climate forcing. After 700 CE, δDwax and δ13Cwax became de-coupled suggesting that the plant wax discharge and their isotope signals were no longer solely controlled by climate; the waxes likely mainly originate from the lowlands and carry an enriched (dry) δD signal but a depleted 13C signature. The depletion of δ13Cwax correlates with the increase of Argan pollen concentration in the record. The period between ~700 and 900 CE coincides with the Arabization of Morocco which had an impact on the demographic composition of the country leading to new agricultural habits and, as a result, on the land-use triggering a higher erosion of lowland material by the Souss River.

scholarly journals Global ocean dimethyl sulfide climatology estimated from observations and an artificial neural network

2020 ◽  
Author(s):  
Wei-Lei Wang ◽  
Guisheng Song ◽  
François Primeau ◽  
Eric S. Saltzman ◽  
Thomas G. Bell ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Solar Radiation ◽  
Mixed Layer ◽  
Dimethyl Sulfide ◽  
Mixed Layer Depth ◽  
Environmental Parameters ◽  
Global Scale ◽  
Global Ocean ◽  
Layer Depth

Abstract. Marine dimethyl sulfide (DMS) is important to climate due to the ability of DMS to alter Earth's radiation budget. However, a knowledge of the global-scale distribution, seasonal variability, and sea-to-air flux of DMS is needed in order to understand the factors controlling surface ocean DMS and its impact on climate. Here we examine the use of an artificial neural network (ANN) to extrapolate available DMS measurements to the global ocean and produce a global climatology with monthly temporal resolution. A global database of 57 810 ship-based DMS measurements in surface waters was used along with a suite of environmental parameters consisting of lat-lon coordinates, time-of-day, time-of-year, solar radiation, mixed layer depth, sea surface temperature, salinity, nitrate, phosphate, silicate, and oxygen. Linear regressions of DMS against the environmental parameters show that on a global scale mixed layer depth and solar radiation are the strongest predictors of DMS, however, they capture 14 % and 12 % of the raw DMS data variance, respectively. The multi-linear regression can capture more (∼29 %) of the raw data variance, but strongly underestimates high DMS concentrations. In contrast, the ANN captures ~61 % of the raw data variance in our database. Like prior climatologies our results show a strong seasonal cycle in DMS concentration and sea-to-air flux. The highest concentrations (fluxes) occur in the high-latitude oceans during the summer. We estimate a lower global sea-to-air DMS flux (17.90 ± 0.34 Tg S yr−1) than the prior estimate based on a map interpolation method when the same gas transfer velocity parameterization is used.

scholarly journals Approach to an automatic prediction of the state of industrial manipulators using machine learning methods

2021 ◽  
Vol 24 (1) ◽  
pp. 48-54
Author(s):  
A. S. Goncharov ◽  
◽  
A. O. Savelev ◽  
A. S. Pisankin ◽  
A. Y. Chepkasov ◽  
...  
Keyword(s):  
Machine Learning ◽  
Information Technologies ◽  
Industrial Revolution ◽  
Industrial Robots ◽  
Learning Methods ◽  
Emergency Situations ◽  
Machine Learning Methods ◽  
Technological Chain ◽  
Using Data ◽  
Working Out

Due to intensive development of information technologies and the onset of 4th industrial revolution the number of robotic industries is steadily growing. The volume of production and the use of robots is also increasing. At the same time, the support and the management of digital production is being rapidly developing. The robotic systems are incapable of completely excluding a person from the technological chain, since they need timely maintenance and personnel working out the emergency situations. One of the solutions to reduce the risk of unexpected breakdowns is a predictive approach to the maintenance. The implementation of this approach is carried out using data analysis tools. This study presents the results of applying machine learning methods to analyze data from industrial robots in order to predict potential failures

scholarly journals A psychrometric model to assess the biological decay of the SARS-CoV-2 virus in aerosols

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11024
Author(s):  
Clive B. Beggs ◽  
Eldad J. Avital
Keyword(s):  
Air Temperature ◽  
Vapour Pressure ◽  
Half Life ◽  
Analytical Study ◽  
Decay Constant ◽  
Meteorological Data ◽  
Environmental Parameters ◽  
Published Data ◽  
Reasonable Accuracy ◽  
The Impact

There is increasing evidence that the 2020 COVID-19 pandemic has been influenced by variations in air temperature and humidity. However, the impact that these environmental parameters have on survival of the SARS-CoV-2 virus has not been fully characterised. Therefore, an analytical study was undertaken using published data to develop a psychrometric model to assess the biological decay rate of the virus in aerosols. This revealed that it is possible to describe with reasonable accuracy (R2 = 0.718, p < 0.001) the biological decay constant for the SARS-CoV-2 virus using a regression model with enthalpy, vapour pressure and specific volume as predictors. Applying this to historical meteorological data from London, Paris and Milan over the pandemic period, produced results which indicate that the average half-life of the virus in aerosols outdoors was in the region 13–22 times longer in March 2020, when the outbreak was accelerating, than it was in August 2020 when epidemic in Europe was at its nadir. However, indoors, this variation is likely to be much less. As such, this suggests that changes in virus survivability due the variations in the psychrometric qualities of the air might influence the transmission of SARS-CoV-2.

scholarly journals Integration of Pedagogical and Production Factors in the Process of the Formation of Industry 4.0

TEM Journal ◽  
2021 ◽  
pp. 1964-1970
Author(s):  
Nikolay Chapaev ◽  
Olga Akimova ◽  
Yevgeniy Dorozhkin ◽  
Andrey Efanov ◽  
Ekaterina Bychkova
Keyword(s):  
Industry 4.0 ◽  
Industrial Revolution ◽  
Rapid Development ◽  
Student Assessment ◽  
Teacher Assessment ◽  
Educational Process ◽  
Production Factors ◽  
Ancient Times ◽  
Relationship Of ◽  
The Relationship

The rapid development of Industry 4.0 as a result of the Fourth Industrial Revolution brings back the relationship of pedagogy and production to mutual integration that has been their characteristic since ancient times. The study revealed high digital readiness of students (4.24 according to the student assessment and 2.82 according to the teacher assessment on a 5- point scale) and very low readiness of production to accept integrated learning (1.68 and 2.67, respectively), as well as the poor digitalization of the educational process according to the students and teachers, who are more closely familiar with the reality of production (2.03 and 2.45, respectively).

scholarly journals A global comparison of grassland biomass responses to CO 2 and nitrogen enrichment

2010 ◽  
Vol 365 (1549) ◽  
pp. 2047-2056 ◽  
Author(s):  
Mark Lee ◽  
Pete Manning ◽  
Janna Rist ◽  
Sally A. Power ◽  
Charles Marsh
Keyword(s):  
Large Scale ◽  
Meta Analysis ◽  
C Sequestration ◽  
Global Scale ◽  
Scale Model ◽  
Published Data ◽  
Climate Data ◽  
Forage Production ◽  
Global Comparison ◽  
N Enrichment

Grassland ecosystems cover vast areas of the Earth's surface and provide many ecosystem services including carbon (C) storage, biodiversity preservation and the production of livestock forage. Predicting the future delivery of these services is difficult, because widespread changes in atmospheric CO 2 concentration, climate and nitrogen (N) inputs are expected. We compiled published data from global change driver manipulation experiments and combined these with climate data to assess grassland biomass responses to CO 2 and N enrichment across a range of climates. CO 2 and N enrichment generally increased aboveground biomass (AGB) but effects of CO 2 enrichment were weaker than those of N. The response to N was also dependent on the amount of N added and rainfall, with a greater response in high precipitation regions. No relationship between response to CO 2 and climate was detected within our dataset, thus suggesting that other site characteristics, e.g. soils and plant community composition, are more important regulators of grassland responses to CO 2 . A statistical model of AGB response to N was used in conjunction with projected N deposition data to estimate changes to future biomass stocks. This highlighted several potential hotspots (e.g. in some regions of China and India) of grassland AGB gain. Possible benefits for C sequestration and forage production in these regions may be offset by declines in plant biodiversity caused by these biomass gains, thus necessitating careful management if ecosystem service delivery is to be maximized. An approach such as ours, in which meta-analysis is combined with global scale model outputs to make large-scale predictions, may complement the results of dynamic global vegetation models, thus allowing us to form better predictions of biosphere responses to environmental change.

Trace elements and Pb isotope composition of annual tree rings and pine needles growing in highly industrialized region in southern Poland

2021 ◽  
Author(s):  
Barbara Sensuła ◽  
Nathalie Fagel
Keyword(s):  
Trace Elements ◽  
Chemical Composition ◽  
Tree Rings ◽  
Wet Deposition ◽  
Isotope Ratio ◽  
Isotope Composition ◽  
Pine Needles ◽  
Pb Isotope ◽  
Southern Poland ◽  
Icp Ms

&lt;p&gt;Trees can provide annual records of ecosystem changes connected with human activity over several decades. These changes can be recorded in the pattern of variation of tree-rings widths and in the variation in the elemental composition of wood. Analysis of trace metal pollution is based on the assumption that element concentrations in tree foliage and tree rings represent element availability in the environment.&lt;/p&gt;&lt;p&gt;We determined the chemical composition of pine needles and annual tree rings to monitor environmental contamination in an urban forest environment in the most industrialized part of southern Poland.&lt;/p&gt;&lt;p&gt;The concentrations of trace elements (Cr, Co, Ni, Cu, Zn, Pb) and the Pb isotope composition were measured in needles from&amp;#160;Pinus sylvestris&amp;#160;L. growing in nine urban forests near five factories. Trace elemental concentration and Pb isotope ratio were determined by ICP-MS and MC-ICP-MS, respectively. The needles were characterized based on the concentrations of Cr, ranging from 0.05 to 0.7 mg/kg, Co, from 0.005 to 0.075 mg/kg, Ni, from 0.12 to 0.66 mg/kg, Cu, from 0.49 to 1.0 mg/kg, Zn, from 3.9 to 14 mg/kg, and Pb, from 0.06 to 0.53 mg/kg. The&amp;#160;&lt;sup&gt;208&lt;/sup&gt;Pb/&lt;sup&gt;206&lt;/sup&gt;Pb ratio ranged from 2.08 to 2.11 and the&amp;#160;&lt;sup&gt;206&lt;/sup&gt;Pb/&lt;sup&gt;207&lt;/sup&gt;Pb ratio between 1.15 and 1.17. The heterogeneity of Pb isotope ratio indicates that there are different sources affecting the Pb isotopic composition of pine needles (Sensu&amp;#322;a et al., 2021).&lt;/p&gt;&lt;p&gt;In one of the investigated site, a radial trace-element profiles were determined by Laser Ablation Inductively Coupled Plasma-Mass Spectrometry (Laser ablation: New Wave Research UP-193 FX Fast Excimer, ICP-MS: Thermo Scientific X-Series2 with CCT -Collision Cell Technology) at Royal Museum for Central Africa (Belgium). LA-ICP-MS provides a repeatable, minimally destructive, sensitive method for determining many elements in wood tissue, with relatively high spatial resolution.Temporal variations of element concentration (median) in annual tree-rings of pines were compared with time series of wet deposition of pollutant and air pollutant concentration in the investigated area.&amp;#160;The similar trends of magnitudes changes can be observed between analysed elements concentration (Na, Mg, Fe, Ni, Zn) and total wet deposition of these elements in the environment during vegetation period or these elements concentration in the rain (Sensu&amp;#322;a et al. 2017).&amp;#160;&lt;/p&gt;&lt;p&gt;Different space-time patterns of element accumulation in pine needles and annaul tree rings were observed. The variation in isotopic composition reflects a mix between different anthropogenic sources.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;References:&lt;/p&gt;&lt;p&gt;Sensu&amp;#322;a, B., Wilczy&amp;#324;ski, S., Monin, L., Allan, M., Pazdur, A., &amp; Fagel, N. (2017). Variations of tree ring width and chemical composition of wood of pine growing in the area nearby chemical factories,&amp;#160;Geochronometria,&amp;#160;44(1), 226-239. doi:&amp;#160;https://doi.org/10.1515/geochr-2015-0064&lt;/p&gt;&lt;p&gt;Sensu&amp;#322;a, B., Fagel, N., &amp; Michczy&amp;#324;ski, A. (2021). Radiocarbon, trace elements and pb isotope composition of pine needles from a highly industrialized region in southern Poland.&amp;#160;Radiocarbon,&amp;#160;1-14. doi:10.1017/RDC.2020.132&lt;/p&gt;

People, Technology and Human Resource Development (HRD) Philosophy

2012 ◽  
pp. 759-770 ◽  
Author(s):  
Claretha Hughes ◽  
Matthew W. Gosney
Keyword(s):  
Competitive Advantage ◽  
Human Resource Development ◽  
Human Resource ◽  
Industrial Revolution ◽  
Resource Development ◽  
Corporate America ◽  
Hrd Professionals ◽  
Relationship Of ◽  
The Relationship

Technology and people are present in all organizations. How they are managed and developed is essential to the competitive advantage of organizations. Understanding the dynamics of this relationship is an area that needs to be better understood within the Human Resource Development (HRD) field. This chapter will explore the extent that HRD philosophy addresses the relationship of people and technology. Comparing people and technology has been a debate since the industrial revolution occurred in America (Swanson, 1982; Swanson, & Torraco, 1994). Man and machine are as essential to organizational prosperity as air and water is to living; yet, it is not often researched and published in HRD literature (Githens, Dirani, Gitonga, and Teng, 2008). Could this be why HRD professionals do not have a seat at the proverbial table in corporate America? Are HRD professionals and researchers denying that there is a relationship between people and technology in organizations? Are HRD professionals and researchers limited by their beliefs concerning the comparison of people to technology?

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