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BY670/770 Scientific Communication (Fall 2016, Spring 2018, Fall 2019)
Becoming a professional biologist is challenging and requires mastering a variety of skills. This course complements the biological knowledge graduate students gain from other courses and their thesis research by providing training, experience, and critical feedback in the following areas. Students will gain valuable experience in:
              • Science and social media
              • Professional presentations (oral, PowerPoint, and poster)
              • Grant writing
              • Curriculum vitae
              • Peer-review system and giving/receiving constructive criticism
              • Scientific ethics
              • Interviewing for graduate schools and employment

Here are related posts written by Stacy and her students for ​The Molecular Ecologist:
Jackson, J (2018) In it to win it: selective advantage through host-selected mutations 
Momeni, M (2018) Cricket plays a song of systems biology 
Sahawneh, K (2018) A master manipulator: how a bacterium tells a plant what to do 
Keister, E (2018) Are we restoring coral reefs for today or for tomorrow?
Krueger-Hadfield SA (2018) To present data is human, to communicate data is divine 
Aida, V (2017) Mapping genomes and navigating behavior for wildlife conservation. ​   
Hayes, M (2017) Like turtles, terrapin research moves a little slow. ​
Latimer, M (2017) Small Molecules, Big Differences.
​Roegner, M (2017) Molting on the molecular level: how blue crabs become soft-shell crabs.
Adkins, S (2017) Dishing out art: 'Soiling' our microbiology curriculum. 
Heiser, S (2017) Have we got the power? ​
Krueger-Hadfield, SA​ (2017) I think we're NOT alone now.
BY429/491/629 Evolutionary Processes (Fall 2017, Spring 2018, Fall 2019)
This course will introduce the history of evolutionary thought and modern evolutionary theory. Our discussions will cover (but are not limited to) the history of life, mechanisms of evolutionary change, adaptation, speciation, life-history evolution, sexual selection and molecular evolution. We will also discuss historical and contemporary studies of evolution on a wide variety of topics and organisms.
​
It's been said that "nothing in biology makes sense except in the light of evolution" (Theodosius Dobzhansky, 1973). Why?  We'll consider that question in depth in this course, taking a look at the science of biological evolution from a number of perspectives.  We will follow the Zimmer textbook closely and will read a few other sources as well.  A lot of what we do will involve in-class discussions and problem solving of the readings as well as applying concepts to novel questions, and you will be expected to actively work with the course material to develop an intuitive understanding of evolution.  Some overarching themes we will cover are:
  • Evolution is a necessary property of any finite, self-replicating system.
  • Evolution is both (mathematical) theory and (measureable) fact.
  • Evolution is not a "deep time" question, but happening constantly, measurably, around us every day.
  • Evolution ≠ natural selection.
  • Evolution occurs because of random chance, but yields non-random outcomes
  • The theoretical framework of biological evolution is broadly applicable, with influence on computer science, economics, medicine, psychology, politics, etc.​

​Here are related posts written by Stacy and her students for ​The Molecular Ecologist:
  • Livett, S (2018) Racing against the climate ​
BY468/668/768 Conservation Genetics (Fall 2018, Spring 2019, Spring 2020)
This intensive course will introduce students to the genetic tools of modern population biology – which ones are available, practical, and useful for particular questions – and how these genetic analyses have been applied to a wide variety of ecological topics, including: dispersal, life cycles, recruitment, habitat and mate choice, local selection, genetic differentiation, the conservation of biodiversity, and speciation. Importantly, this course is an opportunity to become proficient at applying molecular tools to bolster ecological studies. Time will be spent in lectures, discussions, reviewing the primary literature, and learning practical coding and data analyses.

At the end of the course, students will understand how to apply population genetics principles to understand genetic variation in natural populations. This requires an understanding of the appropriate theory, designing appropriate experiments and/or sampling, collecting the appropriate data, and understanding how to analyze these data. Students will learn each step in this process through lectures, discussions, independent projects, and practical application of population genetic tools. This course will help students create an informed framework for thought about issues in evolutionary ecology, with an emphasis on applying concepts and tools of genetics to problems in conservation.

If you are an undergrad, it is highly recommended that you have already passed BY311 Molecular Genetics (or equivalent) AND BY429 Evolution. For grad students, it is also recommended that you have an undergrad- or grad-level genetics and evolution course. We will briefly review fundamental concepts, but we will not spend as much time as in a genetics or evolution course.

​Here are related posts written by Stacy and her students for 
​The Molecular Ecologist:
  • Conner, N (2019) Snapshots of biodiversity: eDNA as a methodology of species detection
  • Bonka, A (2019) Genetics of returning turtles
  • Curtis, M (2019) The ultimate party animal
  • Keister, E (2019) Is taxonomy still relevant to innovative science?
  • Heiser, S (2019) "Through endurance we conquer*" Are humans really the only ones who can make it across the Drake's Passage?
  • O' Connor, AM** (2019) Kelp forests: the underwater woodlands​​
BY655/755 Biometry (Spring 2019)
This is an introductory course for graduate students for application and implementation of statistical analyses in the biological sciences. The course will cover many topics covered in the first two semesters of introductory statistics, from samples means to linear regression. All analyses will be completed either by hand or with the statistical program R. Each class meeting will consist of both lecture and working practice problems in R. At the end of the course, students should feel well versed enough to apply basic statistical concepts to data collected from their own experiments. Students will also gain some basic knowledge of the R programming language in order to store, manipulate, graph, and analyze data.
© S.A. Krueger-Hadfield 2019
    
All photographs are subject to copyright and may not be used without permission.
Updated September 2019
  • Home
    • Krueger-Hadfield Lab News
  • People
    • Stacy A. Krueger-Hadfield
    • Collaborators
    • Post-docs
    • Students
  • Publications
  • Teaching
  • Outreach, press and presentations
  • Contact