Artificial selection has been practiced by humans since the dawn of agriculture, but only recently have evolutionary ecologists turned to this tool to understand nature. To perform artificial selection, the phenotypic trait of interest is measured on a population, and the individuals with the most extreme phenotypic values are bred to produce the next generation. The change in the mean of the selected trait across each generation is the response to selection, and other traits can also evolve due to genetic correlations with the selected trait. Artificial selection can directly answer the question of how quickly a trait will evolve under a given strength of selection. This kind of result can help ecologists determine whether range or niche boundaries are determined by a lack of variation for a key phenotypic trait or trade-offs due to genetic correlations with other fitness-related traits. In a related approach, controlled natural selection, the organisms are not selected according to their values for a given trait, but rather are allowed to evolve for one to several generations under experimentally imposed environmental treatments such as temperature, light, nutrients, presence or absence of predators or competitors, etc. The results of this kind of study can tell us how quickly a population can adapt to a given environmental change, either natural or anthropogenic. Finally, artificial selection can create more variation for measurements of natural selection or can be coupled with QTL mapping; both these combinations provide new insights into adaptation. I discuss advantages and disadvantages of these approaches relative to other kinds of studies and highlight case studies showing how these tools can answer a wide range of basic and applied questions in ecology, ranging from niche and range boundaries and character displacement to climate change and invasive species.