printer friendly pageEARTHSYS 149: Wild Writing (EARTHSYS 249)
What is the wild? What is our relationship to nature, and why does this relationship matter? We will interrogate these questions through the work of influential, diverse, primarily American environmental writers who have given voice to many ways of knowing the wonder, fragility, complexity, and power of the natural world and have inspired readers to act on behalf of social-environmental causes. This course centers the work of diverse voices, including Indigenous, Black, and Chicana writers, enabling us to consider some of the many ways that people have understood and experienced nature throughout history and the relevance of these manifold ways of knowing to our conceptualizations of nature today. Students will develop their responses to the question of what is the wild and why it matters through a series of synchronous and asynchronous in-the-field writing exercises that integrate personal narrative and environmental scholarship, culminating in a ~3000-word narrative nonfiction essay.
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What is the wild? What is our relationship to nature, and why does this relationship matter? We will interrogate these questions through the work of influential, diverse, primarily American environmental writers who have given voice to many ways of knowing the wonder, fragility, complexity, and power of the natural world and have inspired readers to act on behalf of social-environmental causes. This course centers the work of diverse voices, including Indigenous, Black, and Chicana writers, enabling us to consider some of the many ways that people have understood and experienced nature throughout history and the relevance of these manifold ways of knowing to our conceptualizations of nature today. Students will develop their responses to the question of what is the wild and why it matters through a series of synchronous and asynchronous in-the-field writing exercises that integrate personal narrative and environmental scholarship, culminating in a ~3000-word narrative nonfiction essay. This course will provide students with knowledge, tools, experience, and skills that will empower them to become more persuasive environmental storytellers and advocates.If you are interested in signing up for the course, complete this pre-registration form:
https://stanforduniversity.qualtrics.com/jfe/form/SV_9XqZeZs036WIvop
Terms: Spr
| Units: 3
| UG Reqs: WAY-CE
EARTHSYS 151: Biological Oceanography (EARTHSYS 251, ESS 151, ESS 251)
Required for Earth Systems students in the oceans track. Interdisciplinary look at how oceanic environments control the form and function of marine life. Topics include distributions of planktonic production and abundance, nutrient cycling, the role of ocean biology in the climate system, expected effects of climate changes on ocean biology. Local weekend field trips.
Terms: Spr
| Units: 3-4
| UG Reqs: WAY-SMA
Instructors:
Arrigo, K. (PI)
;
Lauer, J. (TA)
EARTHSYS 152: Marine Chemistry (EARTHSYS 252, ESS 152, ESS 252, OCEANS 152, OCEANS 252)
Introduction to the interdisciplinary knowledge and skills required to critically evaluate problems in marine chemistry and related disciplines. Physical, chemical, and biological processes that determine the chemical composition of seawater. Air-sea gas exchange, carbonate chemistry, and chemical equilibria, nutrient and trace element cycling, particle reactivity, sediment chemistry, and diagenesis. Examination of chemical tracers of mixing and circulation and feedbacks of ocean processes on atmospheric chemistry and climate. Designed to be taken concurrently with Biological Oceanography (ESS/
EARTHSYS 151/251)
Last offered: Spring 2023
| UG Reqs: WAY-AQR, WAY-SMA
EARTHSYS 153: Solving Social Problems with Data (COMM 140X, DATASCI 154, ECON 163, MS&E 134, POLISCI 154, PUBLPOL 155, SOC 127)
Introduces students to the interdisciplinary intersection of data science and the social sciences through an in-depth examination of contemporary social problems. Provides a foundational skill set for solving social problems with data including quantitative analysis, modeling approaches from the social sciences and engineering, and coding skills for working directly with big data. Students will also consider the ethical dimensions of working with data and learn strategies for translating quantitative results into actionable policies and recommendations. Lectures will introduce students to the methods of data science and social science and apply these frameworks to critical 21st century challenges, including education & inequality, political polarization, and health equity & algorithmic design in the fall quarter, and social media, climate change, and school choice & segregation in the spring quarter. In-class exercises and problem sets will provide students with the opportunity to use
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Introduces students to the interdisciplinary intersection of data science and the social sciences through an in-depth examination of contemporary social problems. Provides a foundational skill set for solving social problems with data including quantitative analysis, modeling approaches from the social sciences and engineering, and coding skills for working directly with big data. Students will also consider the ethical dimensions of working with data and learn strategies for translating quantitative results into actionable policies and recommendations. Lectures will introduce students to the methods of data science and social science and apply these frameworks to critical 21st century challenges, including education & inequality, political polarization, and health equity & algorithmic design in the fall quarter, and social media, climate change, and school choice & segregation in the spring quarter. In-class exercises and problem sets will provide students with the opportunity to use real-world datasets to discover meaningful insights for policymakers and communities. This course is the required gateway course for the new major in Data Science & Social Systems. Preference given to Data Science & Social Systems B.A. majors and prospective majors. Course material and presentation will be at an introductory level. Enrollment and participation in one discussion section is required. Sign up for the discussion section will occur on Canvas at the start of the quarter. Prerequisites:
CS106A (required),
DATASCI 112 (recommended as pre or corequisite). Limited enrollment. Please complete the interest form here:
https://forms.gle/8ui9RPgzxjGxJ9k29. A permission code will be given to admitted students to register for the class.
Terms: Aut, Spr
| Units: 5
| UG Reqs: WAY-AQR, WAY-SI
Instructors:
Nobles, M. (PI)
;
Weinstein, J. (PI)
;
Castro Pena, D. (TA)
...
more instructors for EARTHSYS 153 »
Instructors:
Nobles, M. (PI)
;
Weinstein, J. (PI)
;
Castro Pena, D. (TA)
;
Charmot, S. (TA)
;
Dann, C. (TA)
;
Ma, S. (TA)
;
Ross, D. (TA)
;
Upadhyay, R. (TA)
;
Vasilenok, N. (TA)
EARTHSYS 155: Science of Soils (ESS 155)
Physical, chemical, and biological processes within soil systems. Emphasis is on factors governing nutrient availability, plant growth and production, land-resource management, and pollution within soils. How to classify soils and assess nutrient cycling and contaminant fate. Recommended: introductory chemistry and biology.
Terms: Spr
| Units: 4-5
| UG Reqs: WAY-SMA, GER: DB-NatSci
EARTHSYS 156: The Future of Global Systemic Risk (SOC 128, STS 156)
The global risk environment is changing. Seemingly distinct large-scale risks affect what we now realize are mutually interdependent human, socio-technical, and ecological systems. As a result, consequences are more catastrophic, and costs are set to accelerate. How do we determine the top risks of this decade to prioritize actions, and how are both risks and actions likely to evolve and interact? This course investigates the data, methods, and insights mobilized by key actors such as corporations, governments, and academics to assess systemic risk, create future scenarios, and generate predictions. What are the track records of recognized systemic risk assessment and modeling toolkits? Going forward, how can we get better at risk prevention and mitigation? This year, the course will focus on combined risks from the environmental, health, and emerging tech domains. The key objective is to quickly learn relevant vocabularies (risk, tech, and futurist) by engaging with both traditional a
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The global risk environment is changing. Seemingly distinct large-scale risks affect what we now realize are mutually interdependent human, socio-technical, and ecological systems. As a result, consequences are more catastrophic, and costs are set to accelerate. How do we determine the top risks of this decade to prioritize actions, and how are both risks and actions likely to evolve and interact? This course investigates the data, methods, and insights mobilized by key actors such as corporations, governments, and academics to assess systemic risk, create future scenarios, and generate predictions. What are the track records of recognized systemic risk assessment and modeling toolkits? Going forward, how can we get better at risk prevention and mitigation? This year, the course will focus on combined risks from the environmental, health, and emerging tech domains. The key objective is to quickly learn relevant vocabularies (risk, tech, and futurist) by engaging with both traditional and emerging assessment methods, in order to discover how to shape positive societal outcomes in the next decade and beyond. The course prepares students for key roles in the assessment, management, and prediction of risks, technologies, markets, industries, infrastructures, and futures. People with these skills can affect the governance principles, strategies, and leadership of corporations, philanthropies, states, economies, and entire societies.
Terms: Spr
| Units: 3-4
Instructors:
Undheim, T. (PI)
EARTHSYS 157: Stanford Science Podcast (PWR 91JS)
In this course, students will explore how podcasts can be used as a tool for effective science communication. Through a series of workshops and guest speakers, students in this course will learn the necessary journalistic and technical skills to produce high quality podcast episodes, from interviewing and storytelling to audio editing and digital publishing. Podcast episodes will highlight the cutting edge research being done at Stanford, and students will choose specific stories based on their own interests, from earth sciences to public health to big data. Final podcast episodes will be published on iTunes.
Last offered: Spring 2021
| UG Reqs: WAY-CE
EARTHSYS 158: Geomicrobiology (BIO 190, EARTHSYS 258, ESS 158, ESS 258)
How microorganisms shape the geochemistry of the Earth's crust including oceans, lakes, estuaries, subsurface environments, sediments, soils, mineral deposits, and rocks. Topics include mineral formation and dissolution; biogeochemical cycling of elements (carbon, nitrogen, sulfur, and metals); geochemical and mineralogical controls on microbial activity, diversity, and evolution; life in extreme environments; and the application of new techniques to geomicrobial systems. Recommended: introductory chemistry and microbiology such as
CEE 274A.
Last offered: Winter 2023
| UG Reqs: WAY-SMA
EARTHSYS 160: Sustainable Cities (URBANST 164)
Community-engaged learning course that exposes students to sustainability concepts and urban planning as a tool for determining sustainable outcomes in the Bay Area. The focus will be on land use and transportation planning to housing and employment patterns, mobility, public health, and social equity. Topics will include government initiatives to counteract urban sprawl and promote smart growth and livability, political realities of organizing and building coalitions around sustainability goals, and increasing opportunities for low-income and communities of color to achieve sustainability outcomes. Students will participate in remote team-based projects in collaboration with Bay Area community partners. Prerequisites: Consent of the instructor. (Cardinal Course certified by the Haas Center.) Apply here:
https://docs.google.com/forms/d/e/1FAIpQLSfhY1w5A_PCjmKdMcGNaZ6Hic24T2zvgF7CfcGrL2tWCWnQGg/viewform
Terms: Spr
| Units: 4-5
| UG Reqs: WAY-SI, WAY-EDP
Instructors:
Kos, R. (PI)
EARTHSYS 162: Data for Sustainable Development (CS 325B, EARTHSYS 262)
The sustainable development goals (SDGs) encompass many important aspects of human and ecosystem well-being that are traditionally difficult to measure. This project-based course will focus on ways to use inexpensive, unconventional data streams to measure outcomes relevant to SDGs, including poverty, hunger, health, governance, and economic activity. Students will apply machine learning techniques to various projects outlined at the beginning of the quarter. The main learning goals are to gain experience conducting and communicating original research. Prior knowledge of machine learning techniques, such as from
CS 221,
CS 229,
CS 231N,
STATS 202, or
STATS 216 is required. Open to both undergraduate and graduate students. Enrollment limited to 24. Students must apply for the class by filling out the form at
https://goo.gl/forms/9LSZF7lPkHadix5D3. A permission code will be given to admitted students to register for the class.
Terms: Aut
| Units: 3-5
| Repeatable
for credit
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