Data_Sheet_1_Effects of Measuring Devices and Sampling Strategies on the Interpretation of Monitoring Data for Long-Term Trend Analysis.pdf

A thorough and reliable assessment of changes in sea surface water temperatures (SSWTs) is essential for understanding the effects of global warming on long-term trends in marine ecosystems and their communities. The first long-term temperature measurements were established almost a century ago, esp...

Full description

Bibliographic Details
Main Authors: Philipp Fischer (11099057), Peter Dietrich (5148866), Eric P. Achterberg (337732), Norbert Anselm (11781827), Holger Brix (11447773), Ingeborg Bussmann (11447770), Laura Eickelmann (11781830), Götz Flöser (11447776), Madlen Friedrich (8453250), Hendrik Rust (8453256), Claudia Schütze (11781833), Uta Koedel (11781836)
Format: Dataset
Language:unknown
Published: 2021
Subjects:
Online Access:https://doi.org/10.3389/fmars.2021.770977.s001
id ftsmithonian:oai:figshare.com:article/17111531
record_format openpolar
spelling ftsmithonian:oai:figshare.com:article/17111531 2023-05-15T15:04:53+02:00 Data_Sheet_1_Effects of Measuring Devices and Sampling Strategies on the Interpretation of Monitoring Data for Long-Term Trend Analysis.pdf Philipp Fischer (11099057) Peter Dietrich (5148866) Eric P. Achterberg (337732) Norbert Anselm (11781827) Holger Brix (11447773) Ingeborg Bussmann (11447770) Laura Eickelmann (11781830) Götz Flöser (11447776) Madlen Friedrich (8453250) Hendrik Rust (8453256) Claudia Schütze (11781833) Uta Koedel (11781836) 2021-12-02T10:54:44Z https://doi.org/10.3389/fmars.2021.770977.s001 unknown https://figshare.com/articles/dataset/Data_Sheet_1_Effects_of_Measuring_Devices_and_Sampling_Strategies_on_the_Interpretation_of_Monitoring_Data_for_Long-Term_Trend_Analysis_pdf/17111531 doi:10.3389/fmars.2021.770977.s001 CC BY 4.0 CC-BY Oceanography Marine Biology Marine Geoscience Biological Oceanography Chemical Oceanography Physical Oceanography Marine Engineering precision accuracy sensor selection sampling scheme environmental monitoring Kongsfjorden long-term data coastal waters Dataset 2021 ftsmithonian https://doi.org/10.3389/fmars.2021.770977.s001 2021-12-19T20:22:34Z A thorough and reliable assessment of changes in sea surface water temperatures (SSWTs) is essential for understanding the effects of global warming on long-term trends in marine ecosystems and their communities. The first long-term temperature measurements were established almost a century ago, especially in coastal areas, and some of them are still in operation. However, while in earlier times these measurements were done by hand every day, current environmental long-term observation stations (ELTOS) are often fully automated and integrated in cabled underwater observatories (UWOs). With this new technology, year-round measurements became feasible even in remote or difficult to access areas, such as coastal areas of the Arctic Ocean in winter, where measurements were almost impossible just a decade ago. In this context, there is a question over what extent the sampling frequency and accuracy influence results in long-term monitoring approaches. In this paper, we address this with a combination of lab experiments on sensor accuracy and precision and a simulated sampling program with different sampling frequencies based on a continuous water temperature dataset from Svalbard, Arctic, from 2012 to 2017. Our laboratory experiments showed that temperature measurements with 12 different temperature sensor types at different price ranges all provided measurements accurate enough to resolve temperature changes over years on a level discussed in the literature when addressing climate change effects in coastal waters. However, the experiments also revealed that some sensors are more suitable for measuring absolute temperature changes over time, while others are more suitable for determining relative temperature changes. Our simulated sampling program in Svalbard coastal waters over 5 years revealed that the selection of a proper sampling frequency is most relevant for discriminating significant long-term temperature changes from random daily, seasonal, or interannual fluctuations. While hourly and daily sampling could deliver reliable, stable, and comparable results concerning temperature increases over time, weekly sampling was less able to reliably detect overall significant trends. With even lower sampling frequencies (monthly sampling), no significant temperature trend over time could be detected. Although the results were obtained for a specific site, they are transferable to other aquatic research questions and non-polar regions. Dataset Arctic Arctic Ocean Climate change Global warming Kongsfjord* Kongsfjorden Svalbard Unknown Arctic Arctic Ocean Svalbard
institution Open Polar
collection Unknown
op_collection_id ftsmithonian
language unknown
topic Oceanography
Marine Biology
Marine Geoscience
Biological Oceanography
Chemical Oceanography
Physical Oceanography
Marine Engineering
precision
accuracy
sensor selection
sampling scheme
environmental monitoring
Kongsfjorden
long-term data
coastal waters
spellingShingle Oceanography
Marine Biology
Marine Geoscience
Biological Oceanography
Chemical Oceanography
Physical Oceanography
Marine Engineering
precision
accuracy
sensor selection
sampling scheme
environmental monitoring
Kongsfjorden
long-term data
coastal waters
Philipp Fischer (11099057)
Peter Dietrich (5148866)
Eric P. Achterberg (337732)
Norbert Anselm (11781827)
Holger Brix (11447773)
Ingeborg Bussmann (11447770)
Laura Eickelmann (11781830)
Götz Flöser (11447776)
Madlen Friedrich (8453250)
Hendrik Rust (8453256)
Claudia Schütze (11781833)
Uta Koedel (11781836)
Data_Sheet_1_Effects of Measuring Devices and Sampling Strategies on the Interpretation of Monitoring Data for Long-Term Trend Analysis.pdf
topic_facet Oceanography
Marine Biology
Marine Geoscience
Biological Oceanography
Chemical Oceanography
Physical Oceanography
Marine Engineering
precision
accuracy
sensor selection
sampling scheme
environmental monitoring
Kongsfjorden
long-term data
coastal waters
description A thorough and reliable assessment of changes in sea surface water temperatures (SSWTs) is essential for understanding the effects of global warming on long-term trends in marine ecosystems and their communities. The first long-term temperature measurements were established almost a century ago, especially in coastal areas, and some of them are still in operation. However, while in earlier times these measurements were done by hand every day, current environmental long-term observation stations (ELTOS) are often fully automated and integrated in cabled underwater observatories (UWOs). With this new technology, year-round measurements became feasible even in remote or difficult to access areas, such as coastal areas of the Arctic Ocean in winter, where measurements were almost impossible just a decade ago. In this context, there is a question over what extent the sampling frequency and accuracy influence results in long-term monitoring approaches. In this paper, we address this with a combination of lab experiments on sensor accuracy and precision and a simulated sampling program with different sampling frequencies based on a continuous water temperature dataset from Svalbard, Arctic, from 2012 to 2017. Our laboratory experiments showed that temperature measurements with 12 different temperature sensor types at different price ranges all provided measurements accurate enough to resolve temperature changes over years on a level discussed in the literature when addressing climate change effects in coastal waters. However, the experiments also revealed that some sensors are more suitable for measuring absolute temperature changes over time, while others are more suitable for determining relative temperature changes. Our simulated sampling program in Svalbard coastal waters over 5 years revealed that the selection of a proper sampling frequency is most relevant for discriminating significant long-term temperature changes from random daily, seasonal, or interannual fluctuations. While hourly and daily sampling could deliver reliable, stable, and comparable results concerning temperature increases over time, weekly sampling was less able to reliably detect overall significant trends. With even lower sampling frequencies (monthly sampling), no significant temperature trend over time could be detected. Although the results were obtained for a specific site, they are transferable to other aquatic research questions and non-polar regions.
format Dataset
author Philipp Fischer (11099057)
Peter Dietrich (5148866)
Eric P. Achterberg (337732)
Norbert Anselm (11781827)
Holger Brix (11447773)
Ingeborg Bussmann (11447770)
Laura Eickelmann (11781830)
Götz Flöser (11447776)
Madlen Friedrich (8453250)
Hendrik Rust (8453256)
Claudia Schütze (11781833)
Uta Koedel (11781836)
author_facet Philipp Fischer (11099057)
Peter Dietrich (5148866)
Eric P. Achterberg (337732)
Norbert Anselm (11781827)
Holger Brix (11447773)
Ingeborg Bussmann (11447770)
Laura Eickelmann (11781830)
Götz Flöser (11447776)
Madlen Friedrich (8453250)
Hendrik Rust (8453256)
Claudia Schütze (11781833)
Uta Koedel (11781836)
author_sort Philipp Fischer (11099057)
title Data_Sheet_1_Effects of Measuring Devices and Sampling Strategies on the Interpretation of Monitoring Data for Long-Term Trend Analysis.pdf
title_short Data_Sheet_1_Effects of Measuring Devices and Sampling Strategies on the Interpretation of Monitoring Data for Long-Term Trend Analysis.pdf
title_full Data_Sheet_1_Effects of Measuring Devices and Sampling Strategies on the Interpretation of Monitoring Data for Long-Term Trend Analysis.pdf
title_fullStr Data_Sheet_1_Effects of Measuring Devices and Sampling Strategies on the Interpretation of Monitoring Data for Long-Term Trend Analysis.pdf
title_full_unstemmed Data_Sheet_1_Effects of Measuring Devices and Sampling Strategies on the Interpretation of Monitoring Data for Long-Term Trend Analysis.pdf
title_sort data_sheet_1_effects of measuring devices and sampling strategies on the interpretation of monitoring data for long-term trend analysis.pdf
publishDate 2021
url https://doi.org/10.3389/fmars.2021.770977.s001
geographic Arctic
Arctic Ocean
Svalbard
geographic_facet Arctic
Arctic Ocean
Svalbard
genre Arctic
Arctic Ocean
Climate change
Global warming
Kongsfjord*
Kongsfjorden
Svalbard
genre_facet Arctic
Arctic Ocean
Climate change
Global warming
Kongsfjord*
Kongsfjorden
Svalbard
op_relation https://figshare.com/articles/dataset/Data_Sheet_1_Effects_of_Measuring_Devices_and_Sampling_Strategies_on_the_Interpretation_of_Monitoring_Data_for_Long-Term_Trend_Analysis_pdf/17111531
doi:10.3389/fmars.2021.770977.s001
op_rights CC BY 4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.3389/fmars.2021.770977.s001
_version_ 1766336625408737280