The unit builds toward the following NGSS Performance Expectations (PE):

• HS-LS4-2* Construct an explanation based on evidence that the process of evolution primarily results from four factors: (1) the potential for a species to increase in number, (2) the heritable genetic variation of individuals in a species due to mutation and sexual reproduction, (3) competition for limited resources, and (4) the proliferation of those organisms that are better able to survive and reproduce in the environment. 
• HS-LS4-3 Apply concepts of statistics and probability to support explanations that organisms with an advantageous heritable trait tend to increase in proportion to organisms lacking this trait.
• HS-LS4-4* Construct an explanation based on evidence for how natural selection leads to adaptation of populations. 
• HS-LS4-5* Evaluate the evidence supporting claims that changes in environmental conditions may result in: (1) increases in the number of individuals of some species, (2) the emergence of new species over time, and (3) the extinction of other species. 
• HS-LS4-6 Create or revise a simulation to test a solution to mitigate adverse impacts of human activity on biodiversity.
• HS-ETS1-3†. Evaluate a solution to a complex real-world problem based on prioritized criteria and trade-offs that account for a range of constraints, including cost, safety, reliability, and aesthetics as well as possible social, cultural, and environmental impacts.

* This performance expectation is developed across multiple units. 

†This performance expectation is developed across multiple courses.

LS4.B: Natural Selection

• Natural selection occurs only if there is both (1) variation in the genetic information between organisms in a population and (2) variation in the expression of that genetic information—that is, trait variation—that leads to differences in performance among individuals. 
• The traits that positively affect survival are more likely to be reproduced and thus are more common in the population. 

LS4.C: Adaptation

• Evolution is a consequence of the interaction of four factors: (1) the potential for a species to increase in number, (2) the genetic variation of individuals in a species due to mutation and sexual reproduction, (3) competition for an environment’s limited supply of the resources that individuals need in order to survive and reproduce, and (4) the ensuing proliferation of those organisms that are better able to survive and reproduce in that environment. 
• Natural selection leads to adaptation, that is, to a population dominated by organisms that are anatomically, behaviorally, and physiologically well suited to survive and reproduce in a specific environment. That is, the differential survival and reproduction of organisms in a population that have an advantageous heritable trait leads to an increase in the proportion of individuals in future generations that have the trait and to a decrease in the proportion of individuals that do not. 
• Adaptation also means that the distribution of traits in a population can change when conditions change. (HS-LS4-3)
• Changes in the physical environment, whether naturally occurring or human-induced, have thus contributed to the expansion of some species, the emergence of new distinct species as populations diverge under different conditions, and the decline–and sometimes the extinction–of some species. 
• Species become extinct because they can no longer survive and reproduce in their altered environment. If members cannot adjust to change that is too fast or drastic, the opportunity for the species’ evolution is lost. 

LS4.D: Biodiversity and Humans

• Biodiversity is increased by the formation of new species (speciation) and decreased by the loss of species (extinction). (secondary)
• Humans depend on the living world for the resources and other benefits provided by biodiversity. But human activity is also having adverse impacts on biodiversity through overpopulation, overexploitation, habitat destruction, pollution, introduction of invasive species, and climate change. Thus, sustaining biodiversity so that ecosystem functioning and productivity are maintained is essential to supporting and enhancing life on Earth. Sustaining biodiversity also aids humanity by preserving landscapes of recreational or inspirational value. 

ETS1.B: Developing Possible Solutions

• When evaluating solutions, it is important to take into account a range of constraints, including cost, safety, reliability, and aesthetics, and to consider social, cultural, and environmental impacts. (secondary)
• Both physical models and computers can be used in various ways to aid in the engineering design process. Computers are useful for a variety of purposes, such as running simulations to test different ways of solving a problem or to see which one is most efficient or economical; and in making a persuasive presentation to a client about how a given design will meet his or her needs. (secondary)

This unit intentionally develops students’ engagement in these practice elements:

Analyzing and Interpreting Data

• 4.2 Apply concepts of statistics and probability (including determining function fits to data, slope, intercepts, and correlation coefficients for linear fits) to scientific and engineering questions and problems, using digital tools when feasible.
• 4.4 Compare and contrast various types of data sets (e.g., self-generated, archival) to examine consistency of measurements and observations.
• 4.5 Evaluate the impact of new data on a working explanation and/or model of a proposed process or system.

Construction Explanations

• 6.2 Construct and revise an explanation based on valid and reliable evidence obtained from a variety of sources (including students’ own investigations, models, theories, simulations, peer review) 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.
• 6.3 Apply scientific ideas, principles, and/or evidence to provide an explanation of phenomena and solve design problems, taking into account possible unanticipated effects.

The following practices are also key to the sensemaking in this unit:

Asking Questions and Defining Problems

• 1.1 Ask questions that arise from careful observation of phenomena or unexpected results to clarify and/or seek additional information.
• 1.4 Ask questions to clarify and refine a model, an explanation, or an engineering problem.
• 1.6 Ask questions that can be investigated within the scope of the school laboratory, research facilities, or field (e.g., outdoor environment) with available resources and, when appropriate, frame a hypothesis based on a model or theory.

Developing and Using Models

• 2.3 Develop, revise, and/or use a model based on evidence to illustrate and/or predict the relationships between systems or between components of a system.
• 2.6 Develop and/or use a model (including mathematical and computational) to generate data to support explanations, predict phenomena, analyze systems, and/or solve problems.

Planning and Carrying Out Investigations

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

Using Mathematics and Computational Thinking

• 5.2 Use mathematical, computational, and/or algorithmic representations of phenomena or design solutions to describe and/or support claims and/or explanations.

Engaging in Argument from Evidence

• 7.6 Evaluate competing design solutions to a real-world problem based on scientific ideas and principles, empirical evidence, and/or logical arguments regarding relevant factors (e.g., economic, societal, environmental, ethical considerations).

This unit intentionally develops students’ engagement in these crosscutting concept elements:

Cause and Effect

• 2.1 Empirical evidence is required to differentiate between cause and correlation and make claims about specific causes and effects.
• 2.2 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.
• 2.3 Systems can be designed to cause a desired effect.
• 2.4 Changes in systems may have various causes that may not have equal effects.

The following crosscutting concepts are also key to the sensemaking in this unit:

Patterns

• 1.1 Different patterns may be observed at each of the scales at which a system is studied and can provide evidence for causality in explanations of phenomena.

Stability and Change

• 7.1 Much of science deals with constructing explanations of how things change and how they remain stable.
• 7.4 Systems can be designed for greater or lesser stability.

Which elements of NOS are developed in the unit?

• Science knowledge is based on empirical evidence. (NOS-SEP)
• Science arguments are strengthened by multiple lines of evidence supporting a single explanation. (NOS-SEP)
• New technologies can have deep impacts on society and the environment, including some that were not anticipated. Analysis of costs and benefits is a critical aspect of decisions about technology. (NOS-CCC)
• Scientific knowledge is based on the assumption that natural laws operate today as they did in the past and they will continue to do so in the future. (NOS-CCC)

How are they developed?

• Students engage with empirical evidence in the form of scientific articles, common garden experiments, data, and images throughout the unit.
• Students gather multiple types of evidence (e.g., historical data, data collected themselves, data from common garden experiments, data from mathematical models) to support their ideas.
• Students use their understanding of human-created wildlife corridors to compare criteria and constraints developed by citizens of Buckeye and with those they develop themselves in Lesson 9. They evaluate two proposed designs for urbanizing Buckeye, AZ, focusing on how to balance the needs of the human and nonhuman populations. 
• Students use their understanding of natural selection and evolution over time to compare the model they developed to Lamarck and Darwin’s theories on Models of Population Change. 

In the anchoring phenomenon, students are introduced to the phenomenon of urbanization and discover that continued urbanization is happening worldwide. They consider what this means for nonhuman populations and make observations about differences in urban populations of hawksbeard, rats, and juncos. They wonder how urbanization could be a driving force for change.  

This anchoring phenomenon was chosen from a group of phenomena aligned with the target performance expectations based on the results of a survey administered to students from across the country and in consultation with external advisory panels that include teachers, subject matter experts, and state science administrators. The anchor was chosen for the following reasons:

• Teachers and administrators saw high relevance to students’ everyday experiences.
• Explaining how urbanization affects change addresses all the DCIs in the bundle at a high school level.
• Students can apply their ideas to a real-world scenario they are likely to encounter in the future.

This unit is the fourth unit in the OpenSciEd High School Biology course sequence and is designed to build on student ideas about genetic variation, inheritance, and change over time. In the third OpenSciEd High School Biology unit, students explored genetics and figured out that the sources of variation in genetic traits are mutations and genetic recombination. In this unit, they will build on those ideas as they look at the genetics of populations over time to explain differences in urban and rural populations of the same organisms.

The unit is organized into two lesson sets. Lesson Set 1 (Lessons 1-6) focuses on how students can make sense of the way urbanization could have caused changes in hawksbeard, rat, and junco populations. This lesson set culminates in a transfer task where students apply what they have figured out so far to explain how bacteria develop resistance to antibiotics. Lesson Set 2 (Lessons 7-11) helps students to use what they know about natural selection to design cities that support resilient populations and ecosystems. At the end of Lesson Set 2, students investigate the conflicting requirements for protecting biodiversity while urbanizing and providing for the needs of human populations in Buckeye, AZ. Students then evaluate two proposed designs for urbanizing Buckeye, AZ, focusing on how to balance the needs of human and nonhuman populations. This unit culminates with a transfer task where they apply all of their understanding about natural selection to consider ways to protect banana crops from fungal infections.

This is the fourth High School Biology Course unit in the OpenSciEd Scope and Sequence. Given this placement, several modifications would need to be made if teaching this earlier in the year. These include the following adjustments:

• If taught before OpenSciEd Unit B.1: How do ecosystems work, and how can understanding them help us protect them? (Serengeti Unit), supplemental teaching of biodiversity, resilience, group behavior, and carrying capacity will be required. Additionally, students will need additional scaffolding for transfer tasks and the practices of asking questions and defining problems, developing and using models, and using mathematics and computational thinking.
• If taught before OpenSciEd Unit B.2: What causes fires in ecosystems to burn and how should we manage them? (Fires Unit), supplemental scaffolding of the practice of constructing explanations and Crosscutting Concepts of cause and effect will be helpful.

If taught before OpenSciEd Unit B.3: Who gets cancer and why? Where should we focus efforts on treatment and prevention? (Genetics Unit), supplemental teaching of inheritance, variation, and mutation will be required.

The following are example options to shorten or condense parts of the unit without eliminating important sensemaking for students:

• Lesson 1: Instead of taking students outside to look for examples of the effect of urbanization on nonhuman populations, do a virtual walk in another city.
• Lesson 2: Model and collect all field/non-urban data together, as a class and then send students to complete the urban investigation in groups.
• Lesson 4: Instead of having the students visit both locations in pairs using Google Earth, have the teacher do it as a demonstration that students watch and record what they see.
• Lesson 10: Remove the future transportation map from Buckeye Development Designs so there is less material for students to consider as they evaluate designs.

To extend or enhance the unit, consider the following:

• Lesson 2: Ask students to make a logical quantitative prediction for the change in the proportion of the outcome of the investigation. Ask students: What would happen in the next generation of plants? How could you model it?
• Lesson 2: As an extension, challenge students to think about the role bees play in determining the (genetic) makeup of the next generation of plants. In the common garden experiment, bees pollinated ALL plants regardless of their origin. In a natural setting, a single bee would not be able to visit flowers located 30 km apart. Students could investigate how far bumblebees normally fly and think about which populations might be able to cross-pollinate and which would not impact the differential survival and reproduction of traits in the population. This impact of fragmentation will be brought up in Lesson Set 2.
• Lesson 8: For students interested in an extension about genetic drift and how population size influences allele fixation, direct them to experiment with changing allele frequency parameters and population sizes in the computer Population Genetics simulation at https://www.radford.edu/~rsheehy/Gen_flash/popgen/ .
• Lesson 8: Evodots, http://faculty.washington.edu/herronjc/SoftwareFolder/EvoDots.html/ , is a virtual alternative for investigation. It can also be used as an extension if students benefit from more time and another modality for processing ideas.
• Lesson 8: As an extension, instruct students how to create their preferred graph using a computer spreadsheet program or CODAP to produce graphs similar to those shown in Model Instructions/Key. Explain how to organize data in the spreadsheet, make simple calculations, and cut and paste repeated formulas.
• Lesson 9: Students can use CODAP to analyze data spread using r2 and Statistics Extension.
• Lesson 10: Criteria and constraints in this lesson were distilled from the Imagine Buckeye: General Plan 2040 Update. As an extension to DCI: ETS1.B.1, students could pursue answers to specific questions about Buckeye in this document.

• Sara Krauskopf, Revision Unit Lead, University of Colorado Boulder
• Douglas Watkins, Field Test Unit Lead, 3D Science Instruction
• Kate Henson, Writer, University of Colorado Boulder
• Will Lindsay, Writer, University of Colorado Boulder
• Joseph Marlen, Writer, Denver Public Schools
• Jamie Deutch Noll, Writer, BSCS Science Learning
• Andres Rodriquez, Writer, Denver Public Schools
• Margee Will, Writer
• Wayne Wright, Writer, University of Colorado Boulder
• Dana Warnecke, Consultant Expert, White Tank Mountain Conservancy

inquiryHub, University of Colorado Boulder

• Maria Gonzales, Copy Editor
• Madison Hammer, Production Manager
• Amanda Howard, Copy Editor
• Erin Howe, Project Manager
• Celeste Moreno, Media Producer

An integral component of OpenSciEd’s development process is external validation of alignment to the Next Generation Science Standards by NextGenScience’s Science Peer Review Panel using the EQuIP Rubric for Science. We are proud that this unit has earned the highest score available and has been awarded the NGSS Design Badge. You can find additional information and read this unit’s review on the nextgenscience.org website.