title: Capabilities and considerations for the implementation of a phycocyanin sensor to enhance cyanobacteria monitoring in lakes

authors: Cotterill, Vanessa

subjects: Phycocyanin quota

abstract: Bloom-forming cyanobacteria are problematic in recreational waters as humans may be exposed to their toxins via primary contact or ingestion. Cyanobacteria can be monitored using microscopy but this is time consuming, costly and requires taxonomic expertise. Phycocyanin (an accessory pigment specific to cyanobacteria) can be used as a proxy for cyanobacteria biomass. Phycocyanin sensors are thus increasingly being used to monitor cyanobacteria, even though many limitations to their use still exist. This research investigated the opportunities and challenges of use a phycocyanin sensor for cyanobacteria monitoring. It tested three hypotheses that: 1) there would be a strong relationship between phycocyanin and biovolumes in samples collected from the Te Arawa/Rotorua Lakes, North Island, New Zealand, 2) colony morphology and cell size affect phycocyanin readings, and 3) nutrient and light exposure would affect phycocyanin quotas independently of growth in Microcystis aeruginosa.

The relationship between phycocyanin and biovolume was investigated using data collected in the field from over two summers (2016 and 2017). A phycocyanin sensor was used to measure phycocyanin in situ, and biovolume was enumerated by microscopy. Eutrophic lakes with high biovolumes (>1.8 Mm³ L⁻¹) and single species dominance had stronger relationships between phycocyanin. Phycocyanin concentration >40 µg L⁻¹ derived from the sensor approximated a biovolume of 1.8 Mm³ L⁻¹, which is the health warning level for potentially toxic cyanobacteria species under the New Zealand guidelines for recreational monitoring of cyanobacteria in fresh waters.

The effect of colony morphology and cell size on phycocyanin detection was tested with serial dilutions of cultures of four cyanobacterial species. Large colonial Microcystis wesenbergii had the highest variability in phycocyanin readings from the sensor. Non-linear relationships in all four species resulted in low confidence for predicting low biovolumes <1.8 Mm³ L⁻¹ from phycocyanin.

The effects of nutrients and light intensity on growth and phycocyanin quota in M. aeruginosa were assessed by a laboratory experiment using a Central Composite design and Response Surface Methodology (RSM). RSM models tested for significant interactions and effects of 20 different combinations of nitrogen (26-84 mgL⁻¹), phosphorus (0.05-5.47 mg L⁻¹) and light intensity (10-300 µmol M⁻² s⁻¹) on the growth and phycocyanin quota. Phycocyanin from the sensor and cell concentrations from microscopy were measured over 26 days at five-day intervals. Phycocyanin quota was significantly (P<0.05) higher in four of the 20 treatments at day 18 compared to the day 22. RSM demonstrated that light and nutrient concentrations affected both growth rate and phycocyanin quota differently. Importantly phycocyanin quotas at day 18 and 22 were affected differently by light and nutrients. This experiment suggests phycocyanin quota changes in cyanobacteria, and this may result in over or underestimates of biomass by a sensor. Regardless of the challenges of using phycocyanin sensors with changing species compositions, morphology, density and with the effects of nutrients and light on phycocyanin and growth. Phycocyanin sensors offer an opportunity to increase current sampling capability and the prioritisation of high-risk samples for counting which may lead to improved protection of human health from the toxicity associated with cyanobacteria blooms.

text: Capabilities and considerations for the implementation of a phycocyanin sensor to enhance cyanobacteria monitoring in lakes Bloom-forming cyanobacteria are problematic in recreational waters as humans may be exposed to their toxins via primary contact or ingestion. Cyanobacteria can be monitored using microscopy but this is time consuming, costly and requires taxonomic expertise. Phycocyanin (an accessory pigment specific to cyanobacteria) can be used as a proxy for cyanobacteria biomass. Phycocyanin sensors are thus increasingly being used to monitor cyanobacteria, even though many limitations to their use still exist. This research investigated the opportunities and challenges of use a phycocyanin sensor for cyanobacteria monitoring. It tested three hypotheses that: 1) there would be a strong relationship between phycocyanin and biovolumes in samples collected from the Te Arawa/Rotorua Lakes, North Island, New Zealand, 2) colony morphology and cell size affect phycocyanin readings, and 3) nutrient and light exposure would affect phycocyanin quotas independently of growth in Microcystis aeruginosa.

The relationship between phycocyanin and biovolume was investigated using data collected in the field from over two summers (2016 and 2017). A phycocyanin sensor was used to measure phycocyanin in situ, and biovolume was enumerated by microscopy. Eutrophic lakes with high biovolumes (>1.8 Mm³ L⁻¹) and single species dominance had stronger relationships between phycocyanin. Phycocyanin concentration >40 µg L⁻¹ derived from the sensor approximated a biovolume of 1.8 Mm³ L⁻¹, which is the health warning level for potentially toxic cyanobacteria species under the New Zealand guidelines for recreational monitoring of cyanobacteria in fresh waters.

The effect of colony morphology and cell size on phycocyanin detection was tested with serial dilutions of cultures of four cyanobacterial species. Large colonial Microcystis wesenbergii had the highest variability in phycocyanin readings from the sensor. Non-linear relationships in all four species resulted in low confidence for predicting low biovolumes <1.8 Mm³ L⁻¹ from phycocyanin.

The effects of nutrients and light intensity on growth and phycocyanin quota in M. aeruginosa were assessed by a laboratory experiment using a Central Composite design and Response Surface Methodology (RSM). RSM models tested for significant interactions and effects of 20 different combinations of nitrogen (26-84 mgL⁻¹), phosphorus (0.05-5.47 mg L⁻¹) and light intensity (10-300 µmol M⁻² s⁻¹) on the growth and phycocyanin quota. Phycocyanin from the sensor and cell concentrations from microscopy were measured over 26 days at five-day intervals. Phycocyanin quota was significantly (P<0.05) higher in four of the 20 treatments at day 18 compared to the day 22. RSM demonstrated that light and nutrient concentrations affected both growth rate and phycocyanin quota differently. Importantly phycocyanin quotas at day 18 and 22 were affected differently by light and nutrients. This experiment suggests phycocyanin quota changes in cyanobacteria, and this may result in over or underestimates of biomass by a sensor. Regardless of the challenges of using phycocyanin sensors with changing species compositions, morphology, density and with the effects of nutrients and light on phycocyanin and growth. Phycocyanin sensors offer an opportunity to increase current sampling capability and the prioritisation of high-risk samples for counting which may lead to improved protection of human health from the toxicity associated with cyanobacteria blooms.

year: 2017

title: On dynamic feature weighting for feature drifting data streams

authors: Barddal, Jean Paul

subjects: computer science

abstract: The ubiquity of data streams has been encouraging the development of new incremental and adaptive learning algorithms. Data stream learners must be fast, memory-bounded, but mainly, tailored to adapt to possible changes in the data distribution, a phenomenon named concept drift. Recently, several works have shown the impact of a so far nearly neglected type of drifcccct: feature drifts. Feature drifts occur whenever a subset of features becomes, or ceases to be, relevant to the learning task. In this paper we (i) provide insights into how the relevance of features can be tracked as a stream progresses according to information theoretical Symmetrical Uncertainty; and (ii) how it can be used to boost two learning schemes: Naive Bayesian and k-Nearest Neighbor. Furthermore, we investigate the usage of these two new dynamically weighted learners as prediction models in the leaves of the Hoeffding Adaptive Tree classifier. Results show improvements in accuracy (an average of 10.69% for k-Nearest Neighbor, 6.23% for Naive Bayes and 4.42% for Hoeffding Adaptive Trees) in both synthetic and real-world datasets at the expense of a bounded increase in both memory consumption and processing time.

text: On dynamic feature weighting for feature drifting data streams The ubiquity of data streams has been encouraging the development of new incremental and adaptive learning algorithms. Data stream learners must be fast, memory-bounded, but mainly, tailored to adapt to possible changes in the data distribution, a phenomenon named concept drift. Recently, several works have shown the impact of a so far nearly neglected type of drifcccct: feature drifts. Feature drifts occur whenever a subset of features becomes, or ceases to be, relevant to the learning task. In this paper we (i) provide insights into how the relevance of features can be tracked as a stream progresses according to information theoretical Symmetrical Uncertainty; and (ii) how it can be used to boost two learning schemes: Naive Bayesian and k-Nearest Neighbor. Furthermore, we investigate the usage of these two new dynamically weighted learners as prediction models in the leaves of the Hoeffding Adaptive Tree classifier. Results show improvements in accuracy (an average of 10.69% for k-Nearest Neighbor, 6.23% for Naive Bayes and 4.42% for Hoeffding Adaptive Trees) in both synthetic and real-world datasets at the expense of a bounded increase in both memory consumption and processing time.

year: 2016

title: Eke panuku, eke tangaroa! How Black Ferns 7s athletes navigate Instagram and inspire the next generation in Aotearoa

authors: Keet, Thandiwe Maia

subjects: Gender

abstract: This thesis considers the role of Instagram in the lives of players on the New Zealand Black Ferns 7s rugby team, and audience engagement with players’ social media accounts. Using a mana wāhine methodology, this study explores how Black Ferns 7s players utilize and navigate Instagram, through mixed-methods enquiry, including a social media analysis of 8 players’ accounts, interviews with 3 Black Ferns 7s players, and talanoa sessions with members of the women’s rugby community in the Bay of Plenty, supplemented by input from Black Ferns players and fans via direct messages on Instagram. The quantitative social media analysis identified 4 key themes in players’ Instagram posts: achievement, team & rugby, life outside rugby, and culture & vulnerability. The analysis reveals that players post the most regarding their “team & rugby”, generating an “athlete first” self- representation. It finds a statistically significant difference in the thematic content of Instagram posts based on squad seniority and the number of followers a player has. Followers were found to engage most with posts regarding “achievement”, and the least with posts regarding “culture and vulnerability”.
The interviews elaborate upon these quantitative differences by highlighting why athletes specifically use Instagram, insights into Black Ferns aspirational team dynamics, and the importance of a player’s life outside of rugby. The thematic analysis also reveals the digital economic and collective labour involved in producing social media content as a member of this team, and what it means to be culturally “authentic” online in Aotearoa. It reveals the unique elements generated by the team-sport context of this study, including intra-team differences in social media usage. Furthermore, hauora, Indigenous role modeling, and Tall Poppy Syndrome emerge as factors particularly unique to the cultural context within which this study takes place. The discussions culminate in the establishment of a layered understanding of the external, internal, and individual factors which shape Instagram posting habits, and the features which most significantly impact why audiences follow the curated displays Black Ferns 7s athletes provide online.
This project contributes to international literature on sportswomen’s use of social media, demonstrating the powerful ways that players support one another in what, when, and how they post, and the importance of cultural identity in Māori and Pasifika players’ social media engagement. It further reveals the importance of team culture in shaping individual players’ social media and audience engagement. This thesis also highlights the significance of sporting and cultural histories and intersectional identities in digital self-representation and fan engagement with sportswomen’s social media usage.

text: Eke panuku, eke tangaroa! How Black Ferns 7s athletes navigate Instagram and inspire the next generation in Aotearoa This thesis considers the role of Instagram in the lives of players on the New Zealand Black Ferns 7s rugby team, and audience engagement with players’ social media accounts. Using a mana wāhine methodology, this study explores how Black Ferns 7s players utilize and navigate Instagram, through mixed-methods enquiry, including a social media analysis of 8 players’ accounts, interviews with 3 Black Ferns 7s players, and talanoa sessions with members of the women’s rugby community in the Bay of Plenty, supplemented by input from Black Ferns players and fans via direct messages on Instagram. The quantitative social media analysis identified 4 key themes in players’ Instagram posts: achievement, team & rugby, life outside rugby, and culture & vulnerability. The analysis reveals that players post the most regarding their “team & rugby”, generating an “athlete first” self- representation. It finds a statistically significant difference in the thematic content of Instagram posts based on squad seniority and the number of followers a player has. Followers were found to engage most with posts regarding “achievement”, and the least with posts regarding “culture and vulnerability”.
The interviews elaborate upon these quantitative differences by highlighting why athletes specifically use Instagram, insights into Black Ferns aspirational team dynamics, and the importance of a player’s life outside of rugby. The thematic analysis also reveals the digital economic and collective labour involved in producing social media content as a member of this team, and what it means to be culturally “authentic” online in Aotearoa. It reveals the unique elements generated by the team-sport context of this study, including intra-team differences in social media usage. Furthermore, hauora, Indigenous role modeling, and Tall Poppy Syndrome emerge as factors particularly unique to the cultural context within which this study takes place. The discussions culminate in the establishment of a layered understanding of the external, internal, and individual factors which shape Instagram posting habits, and the features which most significantly impact why audiences follow the curated displays Black Ferns 7s athletes provide online.
This project contributes to international literature on sportswomen’s use of social media, demonstrating the powerful ways that players support one another in what, when, and how they post, and the importance of cultural identity in Māori and Pasifika players’ social media engagement. It further reveals the importance of team culture in shaping individual players’ social media and audience engagement. This thesis also highlights the significance of sporting and cultural histories and intersectional identities in digital self-representation and fan engagement with sportswomen’s social media usage.

year: 2022