scholarly journals The Plankton Lifeform Extraction Tool: a digital tool to increase the discoverability and usability of plankton time-series data

2021 ◽  
Vol 13 (12) ◽  
pp. 5617-5642
Author(s):  
Clare Ostle ◽  
Kevin Paxman ◽  
Carolyn A. Graves ◽  
Mathew Arnold ◽  
Luis Felipe Artigas ◽  
...  

Abstract. Plankton form the base of the marine food web and are sensitive indicators of environmental change. Plankton time series are therefore an essential part of monitoring progress towards global biodiversity goals, such as the Convention on Biological Diversity Aichi Targets, and for informing ecosystem-based policy, such as the EU Marine Strategy Framework Directive. Multiple plankton monitoring programmes exist in Europe, but differences in sampling and analysis methods prevent the integration of their data, constraining their utility over large spatio-temporal scales. The Plankton Lifeform Extraction Tool brings together disparate European plankton datasets into a central database from which it extracts abundance time series of plankton functional groups, called “lifeforms”, according to shared biological traits. This tool has been designed to make complex plankton datasets accessible and meaningful for policy, public interest, and scientific discovery. It allows examination of large-scale shifts in lifeform abundance or distribution (for example, holoplankton being partially replaced by meroplankton), providing clues to how the marine environment is changing. The lifeform method enables datasets with different plankton sampling and taxonomic analysis methodologies to be used together to provide insights into the response to multiple stressors and robust policy evidence for decision making. Lifeform time series generated with the Plankton Lifeform Extraction Tool currently inform plankton and food web indicators for the UK's Marine Strategy, the EU's Marine Strategy Framework Directive, and for the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) biodiversity assessments. The Plankton Lifeform Extraction Tool currently integrates 155 000 samples, containing over 44 million plankton records, from nine different plankton datasets within UK and European seas, collected between 1924 and 2017. Additional datasets can be added, and time series can be updated. The Plankton Lifeform Extraction Tool is hosted by The Archive for Marine Species and Habitats Data (DASSH) at https://www.dassh.ac.uk/lifeforms/ (last access: 22 November 2021, Ostle et al., 2021). The lifeform outputs are linked to specific, DOI-ed, versions of the Plankton Lifeform Traits Master List and each underlying dataset.

2021 ◽  
Author(s):  
Clare Ostle ◽  
Kevin Paxman ◽  
Carolyn A. Graves ◽  
Mathew Arnold ◽  
Felipe Artigas ◽  
...  

Abstract. Plankton form the base of the marine food web and are sensitive indicators of environmental change. Plankton time-seriesare therefore an essential part of monitoring progress towards global biodiversity goals, such as the Convention onBiological Diversity Aichi Targets, and for informing ecosystem-based policy, such as the EU Marine Strategy FrameworkDirective. Multiple plankton monitoring programmes exist in Europe, but differences in sampling and analysis methodsprevent the integration of their data, constraining their utility over large spatio-temporal scales. The Plankton LifeformExtraction Tool brings together disparate European plankton datasets into a central database from which it extractsabundance time-series of plankton functional groups, called ‘lifeforms’, according to shared biological traits. This tool hasbeen designed to make complex plankton datasets accessible and meaningful for policy, public interest, and scientificdiscovery. It allows examination of large-scale shifts in lifeform abundance or distribution (for example, holoplankton beingpartially replaced by meroplankton), providing clues to how the marine environment is changing. The lifeform methodenables datasets with different plankton sampling and taxonomic analysis methodologies to be used together to provideinsights into the response to multiple stressors and robust policy evidence for decision making. Lifeform time-seriesgenerated with the Plankton Lifeform Extraction Tool currently inform plankton and food web indicators for the UK’sMarine Strategy, the EU’s Marine Strategy Framework Directive, and for the Convention for the Protection of the MarineEnvironment of the North- East Atlantic (OSPAR) biodiversity assessments. The Plankton Lifeform Extraction Toolcurrently integrates 155,000 samples, containing over 44 million plankton records, from 9 different plankton datasets withinUK and European Seas, collected between 1924 and 2017. Additional datasets can be added, and time-series updated. ThePlankton Lifeform Extraction Tool is hosted by The Archive for Marine Species and Habitats Data (DASSH) athttps://www.dassh.ac.uk/lifeforms/. The lifeform outputs are linked to specific, doi-ed, versions of the Plankton LifeformTraits Master List and each underlying dataset.


2018 ◽  
Author(s):  
Indraneel Bhowmik ◽  
PK Viswanathan

Time Series data of Natural Rubber


2018 ◽  
Author(s):  
Indraneel Bhowmik ◽  
PK Viswanathan

Time Series data of Natural Rubber


2013 ◽  
Author(s):  
Stephen J. Tueller ◽  
Richard A. Van Dorn ◽  
Georgiy Bobashev ◽  
Barry Eggleston

Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.


2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai

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