title: A data mining approach to evaluate suitability of dissolved oxygen sensor observations for lake metabolism analysis

authors: Muraoka, Kohji

subjects: computer science

abstract: Despite rapid growth in continuous monitoring of dissolved oxygen for lake metabolism studies, the current best practice still relies on visual assessment and manual data filtering of sensor observations by experienced scientists in order to achieve meaningful results. This time consuming approach is fraught with potential for inconsistency and individual subjectivity. An automated method to assure the quality of data for the purpose of metabolism modeling is clearly needed to obtain consistent results representative of collective expertise. We used a hybrid approach of expert panel and data mining for data filtration. Symbolic Aggregate approXimation (SAX) treats discretized numerical timeseries segments as symbolic indications, creating a series of strings which are literally comparable to human words and sentences. This conversion allows established text mining techniques, such as classification methods to be applied to timeseries data. Half‐hourly frequency surface dissolved oxygen data from 18 global lakes were used to create day‐long segments of the original time series data. Three hundred sets of 1‐d measurements were provided to a group of seven anonymous experts, experienced in manual filtering of oxygen data for metabolism modeling studies. The collective results were treated as expert panel decisions, and were used to rank the data by confidence level for use in metabolism calculations. While considerable variation occurred in the way the experts perceived the quality of the data, the model provides an objective and quantitative assessment method. The program output will assist the decision making process in determining whether data should be used for metabolism calculations. An R version of the program is available for download.

text: A data mining approach to evaluate suitability of dissolved oxygen sensor observations for lake metabolism analysis Despite rapid growth in continuous monitoring of dissolved oxygen for lake metabolism studies, the current best practice still relies on visual assessment and manual data filtering of sensor observations by experienced scientists in order to achieve meaningful results. This time consuming approach is fraught with potential for inconsistency and individual subjectivity. An automated method to assure the quality of data for the purpose of metabolism modeling is clearly needed to obtain consistent results representative of collective expertise. We used a hybrid approach of expert panel and data mining for data filtration. Symbolic Aggregate approXimation (SAX) treats discretized numerical timeseries segments as symbolic indications, creating a series of strings which are literally comparable to human words and sentences. This conversion allows established text mining techniques, such as classification methods to be applied to timeseries data. Half‐hourly frequency surface dissolved oxygen data from 18 global lakes were used to create day‐long segments of the original time series data. Three hundred sets of 1‐d measurements were provided to a group of seven anonymous experts, experienced in manual filtering of oxygen data for metabolism modeling studies. The collective results were treated as expert panel decisions, and were used to rank the data by confidence level for use in metabolism calculations. While considerable variation occurred in the way the experts perceived the quality of the data, the model provides an objective and quantitative assessment method. The program output will assist the decision making process in determining whether data should be used for metabolism calculations. An R version of the program is available for download.

year: 2018

title: Temperature-related changes in polar cyanobacterial mat diversity and toxin production

authors: Kleinteich, Julia

subjects: biodiversity and ecosystems

abstract: One of the fastest rates of recent climate warming has been reported for the Arctic and the maritime Antarctic; for example, mean annual temperatures increased by 0.5 °C per decade over the Antarctic Peninsula during the past 50 years. Owing to their comparatively simple and highly sensitive food webs, polar freshwater systems, with cyanobacterial mats representing the dominant benthic primary producers, seem well suited for monitoring environmental perturbation, including climate change. Prolonged climate change may challenge the resilience, plasticity and adaptability and thus affect the community composition of cyanobacterial mats. We demonstrate that exposing polar mat samples to raised temperatures for six months results in a change in species predominance. Mats exposed to a constant temperature of 8 °C or 16 °C showed high cyanobacterial diversity, commensurate with an increased presence of cyanobacterial toxins. In contrast, mats held at 4 °C and 23 °C seemed low in diversity. Our data thus indicate that a temperature shift to 8–16 °C, potentially reached during summer months in polar regions at the present warming rate, could affect cyanobacterial diversity, and in some instances result in a shift to toxin-producing species or to elevated toxin concentrations by pre-existing species that could profoundly alter freshwater polar ecosystems.

text: Temperature-related changes in polar cyanobacterial mat diversity and toxin production One of the fastest rates of recent climate warming has been reported for the Arctic and the maritime Antarctic; for example, mean annual temperatures increased by 0.5 °C per decade over the Antarctic Peninsula during the past 50 years. Owing to their comparatively simple and highly sensitive food webs, polar freshwater systems, with cyanobacterial mats representing the dominant benthic primary producers, seem well suited for monitoring environmental perturbation, including climate change. Prolonged climate change may challenge the resilience, plasticity and adaptability and thus affect the community composition of cyanobacterial mats. We demonstrate that exposing polar mat samples to raised temperatures for six months results in a change in species predominance. Mats exposed to a constant temperature of 8 °C or 16 °C showed high cyanobacterial diversity, commensurate with an increased presence of cyanobacterial toxins. In contrast, mats held at 4 °C and 23 °C seemed low in diversity. Our data thus indicate that a temperature shift to 8–16 °C, potentially reached during summer months in polar regions at the present warming rate, could affect cyanobacterial diversity, and in some instances result in a shift to toxin-producing species or to elevated toxin concentrations by pre-existing species that could profoundly alter freshwater polar ecosystems.

year: 2012

title: Location of Te Wahitapu Stream and other possible streams in 1877

authors: de Lange, Willem P.

abstract: Review of evidence to establish, with as much confidence as possible, the path of the Te Wahitapu Stream at Matapouri in 1877. The review also examines if other streams may have been present on or in the vicinity of Te Wahitapu Stream in 1877, and if the 1877 or later tsunami may have latered the course of the boundary stream.

text: Location of Te Wahitapu Stream and other possible streams in 1877 Review of evidence to establish, with as much confidence as possible, the path of the Te Wahitapu Stream at Matapouri in 1877. The review also examines if other streams may have been present on or in the vicinity of Te Wahitapu Stream in 1877, and if the 1877 or later tsunami may have latered the course of the boundary stream.

year: 2009