Announcements

Applications are now closed.

Free workshop: 1-6 June 2025
Ghost Ranch Retreat and Education Center, Abiquiu, New Mexico, USA
Motivation and Topics
Biologists from all subdisciplines are called upon to provide explanations of natural phenomena based upon a thorough understanding of the mechanisms that drive them. As expectations for accuracy in these explanations increase, quantitative models are emerging as useful tools to meet these needs. Of particular use are data-driven inferential models that seek to quantify parameters describing biological mechanisms. However, applications of inferential models across biological disciplines are uneven, and many biologists lack the foundational training necessary to apply them to their research or interpret their results. We maintain that all biologists are capable of sophisticated quantitative modeling in their work, and the primary goal of this workshop is to expand the understanding and use of data-driven modeling among practicing biologists.

The workshop will focus on several learning objectives: (i) to better appreciate the importance of models in biology, (ii) to recognize inference gaps in commonly used models, (iii) to understand the building blocks, the construction, and the analysis of data driven inferential models, and (iv) to communicate clearly about and critically evaluate models developed independently or encountered elsewhere.

Broadly, the workshop will be organized around the following topics:

• Why model at all? Taming uncertainty for stronger inferences
• Answering the questions biologists want answered: why is that so hard?
• Building blocks of inferential models: probability distributions
• Combining building blocks into models: graphical models
• Quantitative meaning of graphical models
• Solving the (almost) impossible: data-driven inferences
• Should you believe your inference? Quality assurance
• Where can I apply this new knowledge? Recognizing modeling opportunities

Workshop Location

This five-day workshop will be held at the beautiful and remote Ghost Ranch Retreat and Education Center on the edge of Santa Fe National Forest in northern New Mexico. The location is well-known as the one-time home and frequent artistic subject of the painter Georgia O’Keeffe. All meals and lodging will be provided at the Education Center. We will have plenty of time to focus on quantitative modeling, and also ample opportunities to explore the desert landscape that inspired some of Georgia O’Keefe’s most famous work.

Participant Expectations

We encourage a diversity of participants, including practicing scientists at all levels (especially graduate students, postdoctoral researchers, and early career scientists) as well as managers and policymakers (e.g., agency biologists charged with resource management). Although our own research expertise focuses on population and community biology, we seek a broad representation of biological disciplines, as we have found in our own work that quantitative modeling is applicable to diverse systems across the field of biology.

We do not expect students to have prior experience in statistical modeling or coding. In-class activities will rely primarily on R statistical software, and an introduction to the software will be provided over Zoom the week before the workshop.

Those participants meeting the following expectations will benefit most and will be prioritized if space in the workshop is limited:

• Having a basic curiosity regarding how inferential modeling could help improve one’s own work and being open to exploring new approaches to modeling, even if they differ from one’s own experience and expertise.
• Having at least a passing foundation in basic statistics. We recognize that some participants may have last been immersed in this long ago and others may not yet have solidified their understanding. Consequently, we will remind everyone of this as needed, but some background would be helpful.
• Having at least a passing foundation in basic algebra. It is hard to think about quantitative modeling without some foundation in mathematics.
• Ideally, participants will be focused on some scientific problem that needs solving and to which data-driven inferential modeling will apply. We hope to help participants formulate at least preliminary modeling ideas to work with after the workshop.

Application–due by Feb 20, 2025 at 3 pm EST

Travel, lodging, and meals will be provided for workshop participants through OSyM. To attend the workshop, please fill out the application form. In the case of over-enrollment, we will select participants based on their interests and backgrounds, so please give thought to your responses.