Eco-evolutionary dynamics are well studied but the term is applied to a wide variety of effects and interactions. Yet comparing these different types of studies on eco-evolutionary dynamics will inform on how this field can move forward, which is precisely the aim of a recent British Ecological Society cross-journal Special Feature. Here I discuss a study published within this Special Feature that investigates how an eco-evolutionary feedback loop between population dynamics and fighter expression affects the evolution of alternative reproductive tactics.
The current generation of graduate students are poised to become the leaders of their respective fields by the middle of the century. It is their ideas that will be of greatest influence in advancing the field of ecology in the decades to. So, what are their ideas? How do they think long-term research will provide new insights in 10, 20, 30 years? Maybe in 30 years we’ll find out our projections were wrong, but reflection won’t be possible if we don’t first scan the horizon.
“Improv helped us realize that virtually every profession can benefit from being viewed as a type of performance. And as with any performance, your ability to reach and hold the audience’s attention rests on your performance skills.”
I provide here examples of situations when it is understandable or acceptable to decline peer reviewing a manuscript.
“Where do I go from here?” is one of the hardest, but most frequent, questions a graduate student faces during their PhD program and many of us turn to our mentors to determine the right direction. Unfortunately, as many students know either from personal experience or online reading, mentors come in a variety of competencies (and even with the best of mentors, one person can only provide one perspective). It is critical for students to learn the art of mentoring themselves. So where do we begin with DIY mentoring?
Our experiences of the natural world are increasingly mediated, which is why I use citizen science to bring ecology students outside and learn naturalist skills
: All quantitative research methods are based on models. All statistical tests, all summary statistics, all raw data, and even our ideas are models. Failing to appreciate the ubiquity of models leads to misunderstanding the epistemology of science itself. Conversely, realizing that all science is an act in model building leads to more creative and robust inquiries, and, ultimately, better inference.