README.Rmd

---
title: "README"
author: "btupper"
date: "2025-12-03"
output: github_document
---

# JP297Dj Ocean Forecasting: AI, Ecology, and Data Justice on the Seas  

Instructors: Nick Record, Ben Tupper - Bigelow Laboratory for Ocean Science

e-mail: 

 - Nick Record: nrrecord@colby.edu, nrecord@bigelow.org [both arrive at the Bigelow email]
 
 - Ben Tupper: btupper@bigelow.org

phone: 

  - Nick Record:  207-315-2567 x316

Meeting times: Mon, Tues and Thurs 1:00-4:00 pm

Virtual (zoom) office hours by appointment - just contact [Ben Tupper](mailto:btupper@bigelow.org)

Location: Miller 205


## Handy links
  + [Coding Tutorial Pages](https://bigelowlab.github.io/ColbyForecasting/)

  + [Coding Wiki Tips, Tricks and free Advice](https://github.com/BigelowLab/ColbyForecasting/wiki) 

  + [Github repository](https://github.com/BigelowLab/ColbyForecasting)

  + [RSeek - an R centric search engine](https://www.rseek.org/)

## **COURSE DESCRIPTION**

There is an increasing demand for real-time forecasts of the world around us. With the proliferation of big data sources and learning algorithms, it is possible to produce forecasts on wide ranging phenomenon, from the migrations of endangered species to outbreaks of toxic plankton. Such forecasts have the potential to improve health, quality of life, and economic activity. However, the algorithms and data on which forecasts are based can also carry hidden biases and lead to unintended consequences. This course will take a broad look at ocean forecasting, from stakeholder engagement, to coding and analyzing forecasts, to understanding the complexities of forecasts' impacts.

____________________________________________________________________________

## **SCHEDULE** (changes will be noted)

### 1. Tuesday Jan 6
 
  - Syllabus & Introductions
  
  - Discussion: What are we forecasting?
  
  - [Discussion notes](https://docs.google.com/document/d/1YNo4EiQP9spu2X-jKcjaEqujNmfNFCV2vHqsuTsw1iI/edit?tab=t.0)
  
  - [Superforecasting challenge](https://docs.google.com/forms/d/1BNwFlr1gvsdxa4CP8sKJJXYmClo5jaqkj9eQnRPvKIs/viewform?edit_requested=true#settings)
  
 - Lecture: Forecasting Introduction
 
 - R Tutorial: [Coding](https://bigelowlab.github.io/ColbyForecasting/C00_coding.html)
 
 - Reading assignment for next time:
   The Gulf of Maine articles in this [folder](https://github.com/BigelowLab/ColbyForecasting/tree/main/reading/Woodard)

### 2. Thurs Jan 8
 
  - Lecture: Ocean Science / Gulf of Maine Primer
 
  - Discussion: [Forecast cards](https://docs.google.com/spreadsheets/d/1gPwJF2XAKD9WftHAgRY9X_CXpn-S0gQFDZeF7yxdIGo/edit?gid=0#gid=0) and [Table 1 in this paper](https://github.com/BigelowLab/ColbyForecasting/blob/main/reading/RecordEtal2025inreview.pdf)
  
  - R Tutorial: [Observations](https://bigelowlab.github.io/ColbyForecasting/C01_observations.html)
 
  - Reading assignment for next time: [Mollomo 1998](https://github.com/BigelowLab/ColbyForecasting/blob/main/reading/Mollomo1998.pdf)

  - Lecture: Predicting the distributions of right whales and white sharks in the Gulf of Maine (Camille and Kyle guest lectures)
  
  - Discussion: Where does our data come from?
 
  - R Tutorial: [Background Points](https://bigelowlab.github.io/ColbyForecasting/C02_background.html)
  
  - Reading assignment for next time: [Brickman 2020](https://github.com/BigelowLab/ColbyForecasting/blob/main/reading/Brickman.elementa.2020.20.00055.pdf)


### 3. Monday Jan 12
  - Lecture: Forecasting Methodologies
 
  - R Tutorial: [Covariates](https://bigelowlab.github.io/ColbyForecasting/C03_covariates.html)
 
  - Reading assignment for next time: TBD

## 4. Tuesday Jan 13

  - Lecture: Algorithms and Accountability
 
  - Discussion: Forecasting unintended consequences
  
  - R Tutorial: [Modeling](https://bigelowlab.github.io/ColbyForecasting/C04_models.html)
  
  - Reading assignment for next time: [(a) What is algorithmic bias](https://bdtechtalks.com/2018/03/26/racist-sexist-ai-deep-learning-algorithms/), [(b) Predictive Policing](https://www.science.org/content/article/can-predictive-policing-prevent-crime-it-happens) and [(c) Managing bias in AI](https://lin-web.clarkson.edu/~jmatthew/publications/ManagingBiasInAI_CAMERAREADY.pdf)


## 5. Thursday Jan 15 
  
  - Lecture: Algorithm Accountability
 
  - R Tutorial: [Predicting](https://bigelowlab.github.io/ColbyForecasting/C05_prediction.html)
  
  - Reading assignment for next time: TBD
   
## Monday Jan 23
  
  No class, [Dr. Martin Luther King Day](https://en.wikipedia.org/wiki/Martin_Luther_King_Jr._Day)
 
## 6. Tuesday Jan 20

 - R Tutorial: Spillover and catch-up
 
 - Reading assignment for next time: [(a) Pershing 2020](https://github.com/BigelowLab/ColbyForecasting/blob/main/reading/Pershing.elementa.2020.00076.pdf) and [(b) Hobday 2020](https://github.com/BigelowLab/ColbyForecasting/blob/main/reading/Hobday2020.pdf)
     
## 7. Thursday Jan 27 [Project presentations](https://github.com/BigelowLab/ColbyForecasting/blob/main/assignments/presentation.md)

We will have a mini scientific conference where you will present your project as you might do at a scientific conference. Plan your presentation to be 10 minutes. You may use a slide show (e.g.power point), but you are also welcome to use other styles. You should aim at communicating a condensed version of what is in your project write-up. Because the project write-up isn’t due for a few more days, it is acceptable to have open-ended questions or areas where you ask the audience for feedback. At the end of the presentations, we will have a discussion that attempts to bring this collection of projects together into an integrated description of what the Gulf of Maine might look like in future decades.
   
## 8. Mon Jan 26
 
 - Making your own [Markdown documents](https://rmarkdown.rstudio.com/)
 
 - R Tutorial: Additional time for project help

## 9. Tuesday Jan 27
 - Final project due
   - A ~2,000 word write-up of your Gulf of Maine projection. [Details can be found here](https://github.com/BigelowLab/ColbyForecasting/blob/main/assignments/writeup.md).
   

## **LEARNING OUTCOMES**
 - Describe an ocean forecast, the iterative forecasting cycle, and how forecasts are used
 - Construct simple models to generate forecasts of ecosystem properties with uncertainty
 - Adjust model parameters and inputs to study how they affect forecast performance relative to observations
 - Examine how a forecast may affect decision-making
 - Understand how stakeholder needs affect forecasting decision support
 - Discuss factors which influence uncertainty in forecast output and how forecast uncertainty relates to decision-making
 - Explore and visualize data and forecast output
 - Understand environmental data justice and datasets in the context of data justice
 - Understand algorithm accountability
 - Understanding and synthesizing primary literature and primary data sources


## **TEXTS**

There is no textbook for this course. Readings will be provided (including primarly literature searches by the students). The tutorial for the coding portion is provided [here](https://bigelowlab.github.io/ColbyForecasting/).

Other resources of interest:
 
 - [TidyModels](https://www.tidymodels.org/)
 
 - [Forecasting Principles and Practice](https://otexts.com/fpp3/)
 
 - [Tidy Species Distribution Modeling](https://evolecolgroup.github.io/tidysdm/)
 
 - [Tidyverse - data science tools](https://tidyverse.org/)
 

## **GRADING**

 - Class discussions		10%
 - Coding Tutorials and Assignments		30%
 - Final presentation 20%
 - Final Project					40%


## **ATTENDANCE**

Attendance is required at all classes. Please contact the instructors if you must miss a class. Unexcused absences will be reflected in the Discussions portion of your grade. If a class must be missed, arrangements can be made–just contact the instructors as soon as possible.


## **ACADEMIC ACCOMMODATIONS**

We are committed to creating a course that is inclusive in its design. If you encounter barriers, please let us know immediately so we can determine if there is a design adjustment that can be made. We are happy to consider creative solutions as long as they do not compromise the intent of the assessment or learning activity.

If you are a student with a disability, or think you may have a disability, you are also welcome to initiate this conversation with the Dean of Students Office. The Dean of Students Office works with students with disabilities and faculty members to identify reasonable accommodations. Please [visit their website](https://www.colby.edu/studentadvising/student-access-and-disability-services/) for contact and other information. If you have already been approved for academic accommodations, please connect within the two weeks of the start of the semester so the office can develop an implementation plan.


## **MENTAL AND EMOTIONAL HEALTH**

We are invested in the mental and emotional health of our students. Even as we establish and maintain the academic standards of our course, we value each of you as individuals with complex lives, identities, and challenges.

Throughout the semester, the responsibilities of your Colby education may interact with situational as well as ongoing mental and emotional challenges in foreseeable and unforeseeable ways. If you are in need of reasonable flexibility due to an emotional situation or an ongoing mental health issue, please communicate as openly as possible with your Class Dean, and/or members of the office of Access and Disability Services, preferably in advance of the need, so that we can discuss how your circumstances interface with course requirements. Together, we will consider what is needed and what is possible. If we can discuss the situation, we can manage the situation together.

Please do not allow academic responsibilities to prevent you from getting help you need. Colby Counseling Services staff (207-859-4490) and the staff in the Dean of Studies office (207-859-4560) are available to connect with you. The safety of my students and every member of this community is paramount. If you or someone you know is struggling with thoughts of suicide or may be a danger to themselves or others, please call the on-call counselor immediately (207-859-4490, press ‘0’).”


## **RESPECT FOR DIVERSITY**

It is our intent that students from diverse backgrounds and perspectives be well-served by this course, that students' learning needs be addressed both in and out of class, and that the diversity that students bring to this class be viewed as a resource, strength, and benefit. We expect you to feel challenged and sometimes outside of your comfort zone in this course, but it is our intent to present materials and activities that are inclusive and respectful of all persons, no matter their gender, sexual orientation, disability, age, socioeconomic status, ethnicity, race, culture, perspective, and other characteristics.  

Class rosters are provided to each instructor with the student's legal name. We will gladly honor your request to address you by an alternate name and/or gender pronoun. Please advise us of this early in the course so that we may make appropriate changes to my records.


## **ACADEMIC INTEGRITY AND CONSEQUENCES FOR ACADEMIC DISHONESTY**

Honesty, integrity, and personal responsibility are cornerstones of a Colby education and provide the foundation for scholarly inquiry, intellectual discourse, and an open and welcoming campus community. These values are articulated in the Colby Affirmation and are central to this course. You are expected to demonstrate academic honesty in all aspects of this course. If you understand our course expectations, give credit to those whose work you rely on, and submit your best work, you are highly unlikely to commit an act of academic dishonesty.  

Academic dishonesty includes, but is not limited to: violating clearly stated rules for taking an exam or completing homework; plagiarism (including material from sources without a citation and quotation marks around any borrowed words); claiming another’s work or a modification of another’s work as one’s own; buying or attempting to buy papers or projects for a course; fabricating information or citations; knowingly assisting others in acts of academic dishonesty; misrepresentations to faculty within the context of a course; and submitting the same work, including an essay that you wrote, in more than one course without the permission of the instructors.

Academic dishonesty is a serious offense against the college. Sanctions for academic dishonesty are assigned by an academic review board and may include: failure on the assignment, failure in the course, or suspension or expulsion from the College.  
For more on recognizing and avoiding plagiarism, see: libguides.colby.edu/avoidingplagiarism . For resources and information on academic integrity, see: www.colby.edu/academicintegrity .


## **SEXUAL MISCONDUCT / TITLE IX STATEMENT**

Colby College prohibits and will not tolerate sexual misconduct or gender-based discrimination of any kind. Colby is legally obligated to investigate sexual misconduct (including, but not limited to, sexual assault and sexual harassment) and other specific forms of behavior that violate federal and state laws (Title IX and Title VII, and the Maine Human Rights Act). Such behavior also requires the College to fulfill certain obligations under two other federal laws, the Violence Against Women Act (VAWA) and the Jeanne Clery Disclosure of Campus Security Policy and Campus Statistics Act (Clery Act). To learn more about what constitutes sexual misconduct or to report an incident, see: https://life.colby.edu/your-safety/community-values-conflict-resolution-and-restorative-practice/student-handbook/ .

We are committed to all Colby students feeling safe, accepted, and included in all aspects of their college experiences, including this course. Colby prohibits and will not tolerate sexual misconduct or gender based discrimination of any kind and is obligated, by federal and state laws, to respond to reports and provide resources to students. As your professor, I am considered a "responsible employee" which requires me to report incidence of sexual assault, sexual harassment, dating violence, or stalking to the Title IX Coordinator.

If you wish to access confidential support services, you may contact:
 - The Counseling Center: 207-859-4490
 - The Title IX Confidential Advocate, Emily Schusterbauer: 207-859-4093
 - The Office of Religious and Spiritual Life: 207-859-4272
 - Maines's 24/7 Sexual Assault Helpline: 1-800-871-7741