Carbon Dioxide Fertilization of Marine Microalgae (Dunalliela sp.) Cultures

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In this experiment, students investigate the importance of carbon dioxide to the reproductive growth of a marine microalga, Dunalliela sp. (Note that the directions are for teachers and that students protocol sheets will need to be created by teachers.)

HS-LS2-5 Develop a model to illustrate the role of photosynthesis and cellular respiration in the cycling of carbon among the biosphere, atmosphere, hydrosphere, and geosphere.

MS-LS2-1 Analyze and interpret data to provide evidence for the effects of resource availability on organisms and populations of organisms in an ecosystem.

MS-LS2-3 Develop a model to describe the cycling of matter and flow of energy among living and nonliving parts of an ecosystem.

Distinguish between causal and correlational relationships in data.

Analyze and interpret data to provide evidence for phenomena.

Consider limitations of data analysis (e.g., measurement error, sample selection) when analyzing and interpreting data.

Construct an explanation that includes qualitative or quantitative relationships between variables that predict(s) and/or describe(s) phenomena.

Construct a scientific explanation based on valid and reliable evidence obtained from sources (including the students’ own experiments) and the assumption that theories and laws that describe the natural world operate today as they did in the past and will continue to do so in the future.

Apply scientific reasoning, theory, and/or models to link evidence to the claims to assess the extent to which the reasoning and data support the explanation or conclusion.

Develop and/or revise a model to show the relationships among variables, including those that are not observable but predict observable phenomena.

Develop and/or use a model to generate data to test ideas about phenomena in natural or designed systems, including those representing inputs and outputs, and those at unobservable scales.

Develop and/or use a model (including mathematical and computational) to generate data to support explanations, predict phenomena, analyze systems, and/or solve problems.

Conduct an investigation and/or evaluate and/or revise the experimental design to produce data to serve as the basis for evidence that meet the goals of the investigation.

Plan and conduct an investigation individually and collaboratively to produce data to serve as the basis for evidence, and in the design: decide on types, how much, and accuracy of data needed to produce reliable measurements and consider limitations on the precision of the data (e.g., number of trials, cost, risk, time), and refine the design accordingly.

Select appropriate tools to collect, record, analyze, and evaluate data.

Make directional hypotheses that specify what happens to a dependent variable when an independent variable is manipulated.

Moreover, anthropogenic changes (induced by human activity) in the environment—including habitat destruction, pollution, introduction of invasive species, overexploitation, and climate change—can disrupt an ecosystem and threaten the survival of some species.

Organisms, and populations of organisms, are dependent on their environmental interactions both with other living things and with nonliving factors.

Growth of organisms and population increases are limited by access to resources.

Photoelectric materials emit electrons when they absorb light of a high-enough frequency.

Empirical evidence is required to differentiate between cause and correlation and make claims about specific causes and effects.

Changes of energy and matter in a system can be described in terms of energy and matter flows into, out of, and within that system.

Much of science deals with constructing explanations of how things change and how they remain stable.

Cause and effect relationships can be suggested and predicted for complex natural and human designed systems by examining what is known about smaller scale mechanisms within the system.

When investigating or describing a system, the boundaries and initial conditions of the system need to be defined and their inputs and outputs analyzed and described using models.

Cause and effect relationships may be used to predict phenomena in natural or designed systems.

Energy drives the cycling of matter within and between systems.

Empirical evidence is needed to identify patterns.

Models can be used to predict the behavior of a system, but these predictions have limited precision and reliability due to the assumptions and approximations inherent in models.

Stability might be disturbed either by sudden events or gradual changes that accumulate over time.

Patterns in rates of change and other numerical relationships can provide information about natural systems.

Patterns can be used to identify cause-and-effect relationships.

Within a natural or designed system, the transfer of energy drives the motion and/or cycling of matter.

Models are limited in that they only represent certain aspects of the system under study.

Carbon Dioxide Fertilization of Marine Microalgae (Dunalliela sp.) Cultures

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