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How do ecosystems respond to climate change, and how can ecosystems affect climate? This course describes, quantitatively and qualitatively, the different feedback mechanisms between the land surface and climate at both local and global scales. We will also discuss how these processes can be modelled and measured across earth's diverse ecosystems, and how they affect prospects for nature-based climate solutions. Basic familiarity with programming is helpful.

This class discusses the methods available for remote sensing of the components of the terrestrial hydrologic cycle and how to use them. Topics include the hydrologic cycle, relevant sensor types and the electromagnetic spectrum, active/passive microwave remote sensing (snow, soil moisture, canopy water content, rainfall), thermal sensing of evapotranspiration, gravity and hyperspectral methods, as well as an introduction to data assimilation and calibration/validation approaches for hydrologic variables. Pre-requisite: programming experience. Please complete problem set 0 to ensure pre-requisite programming knowledge is sufficient for success in the course

Decision science is the study of how people make decisions. It aims to describe these processes in ways that will help people make better or more well-informed decisions. It is an interdisciplinary field that draws upon psychology, economics, political science, and management, among other disciplines. It is being used in a number of domain areas and for a variety of applications, including managing freshwater resources, designing decision support tools to aid in coastal adaptation to sea-level rise, and creating "nudges" to enhance energy efficiency behaviors. This course covers behavioral theories of probabilistic inference, intuitive prediction, preference, and decision making. Topics include heuristics and biases, risk perceptions and attitudes, strategies for combining different sources of information and dealing with conflicting objectives, and the roles of group and emotional processes in decision making. This course will introduce students to foundational theories of decision science, and will involve applying these theories to understand decisions about environmental threats.

This course considers and utilizes systems frameworks and models for thinking about and pursuing sustainability (defined by the goal of inclusive intra- and intergenerational well-being) in complex, adaptive, intertwined social-environmental systems. It argues that meeting the goal of sustainability requires drawing on assets (or resources) from five major groups ? human, social, manufactured, natural and knowledge capital assets ? while at the same time building and sustaining them over time. The course illustrates, using lectures, readings, and case study analyses, why analyzing and managing those assets within complex and dynamic integrated systems is challenging, and discusses the characteristics of complex systems that make achieving sustainability goals so challenging. It provides an overview of how to intervene in complex systems to pursue sustainability, including visioning, collaboration, and change theories; governing for sustainability; and strategies, tools, and metrics that assist with the pursuit of sustainability goals. The course draws on readings from one core text (Matson et al. 2016) as well as from a variety of other published literature and case studies. Priority given to SUST students. Enrollment open to seniors and graduate students only. Please contact Bhe Balde (ebalde@stanford.edu) for permission code.

Climate change is one of the greatest crises facing our world. Increasing soil organic carbon storage may be a key strategy for mitigating global climate change, with the potential to offset approximately 20% of annual global fossil fuel emissions. In this course, we will learn about soil carbon cycling, its contribution to the global carbon cycle, how carbon is stored in soil, and land management practices that can increase or decrease soil carbon stocks, thereby mitigating or exacerbating climate change. Although the content is centered on soil carbon, the processes and skills learned in this course can be applied to design solutions to any environmental problem.Prerequisites: Some knowledge of soils, introductory chemistry, and introductory biology would be useful but not necessary. Please email the instructor if you have any concerns or questions.

Addressing climate displacement is one of the central sustainability challenges facing current and future generations. The climate crisis is already driving people to move. According to the Internal Displacement Monitoring Centre, approximately 31.8 million people around the world were displaced by floods, storms, fires, and other weather-related hazards in 2022 alone. Coastal communities in the U.S. and beyond are already in the process of planning relocation to escape erosion, rising sea levels, and other slow-onset effects of climate change. Displacement has significant economic, social, psychological, and cultural costs. Yet persistent knowledge gaps on these costs and how to mitigate them impede the efforts of leaders, advocates, and policymakers who face climate displacement challenges today. Join us for a one-unit seminar as we explore how to make sense of the human impacts of climate change on individuals, communities, and governments - and, in particular, on the ways in which the climate crisis is already forcing people to move or reconfigure their communities. Joined by a series of guest speakers who bring personal, policy, and scholarly expertise to this emerging issue, this seminar will speak to the phenomena of both internal and cross-border migration driven by climate change. The seminar will focus on both understanding the challenges that come with the climate crisis as well as proposed solutions to these challenges and opportunities for correcting past injustices and harms. Possible thematic focuses for our discussions include: (1) Legal, policy and governance implications of internal versus cross-border displacement, (2) The nexus of climate with conflict/public health/agriculture as drivers of migration, (3) Individual- vs. community-centric displacement solutions (e.g., household buyouts vs. community planned relocations), and (4) Indigenous sovereignty and rights in context of climate-related migration.

(Formerly GEOLSCI 140 and 240) Overview of some of the most important data science methods (statistics, machine learning & computer vision) relevant for geological sciences, as well as other fields in the Earth Sciences. Areas covered are: extreme value statistics for predicting rare events; compositional data analysis for geochemistry; multivariate analysis for designing data & computer experiments; probabilistic aggregation of evidence for spatial mapping; functional data analysis for multivariate environmental datasets, spatial regression and modeling spatial uncertainty with covariate information (geostatistics). Identification & learning of geo-objects with computer vision. Focus on practicality rather than theory. Matlab exercises on realistic data problems. Change of Department Name: Earth and Planetary Science (Formerly Geologic Sciences).

How to observe and interpret physical and biological changes in the oceans using satellite technologies. Topics: principles of satellite remote sensing, classes of satellite remote sensors, converting radiometric data into biological and physical quantities, sensor calibration and validation, interpreting large-scale oceanographic features.

For upper-division undergraduates and graduate students. For upper-division undergraduate and graduate students interested in an in-depth look at biological processes in the world's oceans. Themes will vary from year to year but will include such topics as marine bio-optics, marine ecological modeling, phytoplankton primary production, and others. Hands-on laboratory and computer activities will be an integral part of the course, as will field trips into local waters. May be repeated for credit. Enrollment by instructor consent only.