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Record W7011668560

Monitoring and Mitigation of Elevated CO<sub>2</sub> Impacts using Microalgae

2016· article· en· W7011668560 on OpenAlexfundno aff

Bibliographic record

VenueDigital Commons - University of South Florida (University of South Florida) · 2016
Typearticle
Languageen
FieldChemistry
TopicCoordination Chemistry and Organometallics
Canadian institutionsnot available
FundersEuropean CommissionFlorida Department of Agriculture and Consumer ServicesUniversity of South FloridaMcGill UniversityHarvard UniversityNational Science Foundation
KeywordsExclosureVegetation (pathology)Climate changePrecipitationEctothermCarbon dioxide in Earth's atmosphere
DOInot available

Abstract

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Climate change is arguably the greatest environmental and economic challenge of our time. There are considerable documented and projected impacts to both human and natural systems as a result of climate change. These impacts include changes in temperature, sea level, precipitation patterns, and biogeography of ecologically and economically relevant species, including pathogens. One of the main drivers of climate change is elevated levels of atmospheric carbon dioxide (CO2), a greenhouse gas. Since pre-industrial times, atmospheric CO2 levels have increased from approximately 280 ppm to over 400 ppm, as a result of fossil fuel combustion, cement production and land use change.\nIn addition to being a driver of climate change and a direct contributor to the increase in global average temperatures, elevated atmospheric CO2 also affects biogeochemical cycles. When ocean surface waters equilibrate with higher levels of atmospheric CO2, there is an increase in acidification and resulting effects on marine biota, such as changes to community composition and decreases in calcifying organisms. Freshwater systems are less understood, but many freshwater systems are experiencing acidification and the resulting ramifications as well. Microalgae, as the primary producers in these systems, are often studied as sentinels of such change.\nHere, I present studies using microalgae to monitor and mitigate elevated CO2. The goals of the investigation were to conduct 1) a field study to determine if microalgae in a freshwater stream were impacted by an elevated CO2 treatment; 2) a meta-analysis of elevated CO2 effects on freshwater microalgae; and 3) a laboratory study to optimize growth of microalgae for biofuels production.\nIn the first chapter, I provide background information and the framework for the studies that follow. Past, present and future atmospheric carbon dioxide levels are discussed as well as their impacts to marine and freshwater systems. The importance of microalgae to these aquatic systems is described. Then I discuss the role of microalgae in elevated CO2 monitoring and mitigation.\nIn the second chapter, I present a field study of elevated CO2 effects on a freshwater stream. The study took place at the University of Michigan Biological Station at the Stream Research Facility. Once-through artificial stream channels were employed to grow microalgae in simulated natural stream conditions. The stream channels were subjected to ambient or elevated CO2 treatments and impacts to stream water chemistry and microalgae were measured. Stream water chemistry was impacted by the elevated CO2 treatment such that there were significant decreases in pH and significant increases in dissolved inorganic carbon. However, these chemical changes did not have a measured impact on the stream microalgae, as measured by microalgal biomass, elemental composition, and community composition. Perhaps microalgae will not be the first to be impacted by increasing levels of atmospheric CO2, though freshwater systems vary considerably and more research is needed to confirm this conclusion.\nIn the third chapter, I present the results of a meta-analysis of elevated CO2 effects on freshwater algae. We conducted a literature search in ISI Web of Science of all publications on freshwater microalgal response to elevated CO2 and chose studies that used elevated CO2 levels of less than or equal to 2,000 ppm, which is the highest level projected for the future by the Intergovernmental Panel on Climate Change. From the twenty-two papers that met the inclusion criteria, qualitative and quantitative data were extracted and categorized into response classes including water chemistry, microalgal growth, carbon fixation and photosynthesis, nutrient uptake, and consumer response. Effect sizes for elevated CO2 were calculated, and CO2 enrichment significantly increased water acidity and dissolved inorganic carbon concentrations, microalgal growth, carbon fixation and photosynthesis, and algal nutrient uptake. Algal consumers (e.g., herbivores) in general were negatively affected, but the overall result was not statistically significant. We also analyzed a variety of experimental parameters and determined that experimental design and algal culture conditions did not impact elevated CO2 effects on freshwater microalgae in the studies conducted to date.\nIn the fourth chapter, I provide the results of a laboratory-based study of the marine microalgae Picochlorum oculatum, which has shown promise as a source of biofuel because of its high lipid production and relative ease of growing in culture. We ran a series of lab experiments to optimize growth conditions and maximize growth of P. oculatum. Experiments included tests of light source (LED or metal halide), CO2 delivery (continuously or in pH-controlled pulses), inoculum size (10%, 15% or 20%), and culture pH (7.0, 7.5, or 8.0); these variations did not significantly impact growth so future experiments were run in the most cost-effective manner using LED lights, with pH-controlled pulses, 10% inoculum size and at culture pH of 7.5. We also tested different sources of supplied nitrogen in an effort to reduce culture costs and potentially improve sustainability by using urea and ammonium, sources of nitrogen readily available from wastewater treatment. Growth was comparable using the standard artificial nitrogen source, nitrate, and the wastewater-constituent urea, indicating that urea may be a cost-effective and sustainable source of nitrogen for microalgal cultures grown on an industrial scale for biofuel production. Growth using ammonium was not successful even when concentrations were reduced and a buffer was added to reduce acidification of the growth medium resulting from ammonium uptake by the algae. More research is needed to determine if ammonium can be a suitable nitrogen source for microalgae. Experiments were also conducted in an outdoor setting to determine if high growth levels were maintained when the cultures were grown at a larger scale and in variable natural conditions; successful growth was demonstrated over 68 days, indicating that P. oculatum may be a promising candidate for biofuel production. Additional research is needed to further optimize culture growth and streamline operations.\nThe body of work herein examines the role of microalgae in elevated CO2 monitoring and mitigation. There is considerable evidence that elevated atmospheric CO2 impacts aquatic chemistry through increases in dissolved inorganic carbon and acidity. These chemical changes have varied impacts on aquatic biota, including microalgae, which play foundational roles in ecosystems as primary producers and bases of food webs. Microalgal responses to elevated CO2 may impact other trophic levels and have widespread effects on aquatic ecosystems. Additional research is needed on elevated CO2 effects on microalgae, particularly in freshwater systems, which are less understood than marine systems and perhaps less predictable due to the wide variability in their physical, chemical and biological compositions. Microalgae may also play a significant role in elevated CO2 mitigation because of their potential in biofuel production. With additional research focused on reducing costs and improving sustainability, microalgae may play an important role in reducing elevated CO2, one of the main drivers of climate change.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.194
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2016
Admission routes1
Has abstractyes

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