Information for Prospective Graduate Students

For students entering my lab, I place a premium on quantitative skills, intellectual creativity, hard work, and independence. I am not interested in students who take a casual, leisurely approach to graduate school or have applied here because they would like to live in Vermont. I want students who are excited about ecology, and who will work hard in the field and laboratory, write grants and seek external funding for their work, and publish their research in refereed journals. Attitude and commitment are at least as important as grades and experience. I am interested in collaborating with you, teaching you the tricks of the trade, and helping you to develop independently as a scientist. If this sounds like you, please contact me about openings in my lab.

What kinds of skills do you need for success in community ecology? I think two things are important. First, you should invest the time in learning a programming/statistical language so that you are not constrained by the limitations of existing software. S-Plus (or the free version R) and Delphi are the two languages that I recommend. If you are adept at programming, a lot of research doors will open up for you, and there is no better (or more enjoyable) way to learn about statistics and ecological theory than by programming.

Second, you should invest some time in becoming a taxonomic "expert" in identifying and keying out a taxon that interests you: New England goldenrods, southwestern ground-foraging ants, diatoms from high-elevation streams in the Rockies. Whatever the group is that you fancy, study the morphological keys, correspond with taxonomists, learn how to prepare material, and gain confidence in your identification skills. The basic data of community ecology are collections of individuals that are classified into species (or higher taxa). How can you begin your work as a community ecologist without knowing how to do this? Genetic analysis may also be helpful, but not until you recognize the morphological species first. Both programming and species identification are life-long learning tasks, but they will really pay off in your research and personal satisfaction.



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