Many of the greatest challenges facing humanity over the next several decades are ecological in nature—climate change, loss of biodiversity and ecosystem services, emerging pathogens, and sustainable management of fisheries, forest and agriculture. Solving these crises will demand that we are able to tackle increasingly complex problems with big data. These challenges do not fit neatly into the confines of null hypothesis significance testing and are often not amenable to simple experimental designs and manipulations. In this essay we perform a quantitative examination of recent changes in the use of statistical approaches in ecological research and cogitate on academic training in ecology. The trend towards applications of increasingly sophisticated statistics may seem obvious in the literature, but they have not been objectively quantified. Our goals are threefold: (1) to document how the use of different statistical techniques have changed since 1990, (2) to assess change in the use of several commonly cited statistical software programs over that same time period, and (3) to assess if current curricula of doctoral programs in ecology in the United States mirrors these trends. We hope that our analysis will inspire ecology programs to re-evaluate their curriculums and improve quantitative training of future ecologists.
Results/Conclusions
We found that there has been a rise in sophisticated and computationally intensive statistical techniques such as mixed effects models and Bayesian statistics and a decline in reliance on approaches such as ANOVA or t-tests. Similarly, ecologists have shifted away from software such as SAS and SPSS to the open source program R. We also searched the published curricula and syllabi of 154 doctoral programs in the United States and found that despite obvious changes in the statistical practices of ecologists, more than 1/3 of doctoral programs showed no record of required or optional statistics classes. Approximately 1/4 of programs did require a statistics course, but most of those did not cover contemporary statistical philosophy or advanced techniques. Only 1/3 of doctoral programs surveyed even listed an optional course that teaches some aspect of contemporary statistics. We call for graduate programs to lead the charge in improving training of future ecologists with skills needed to address and understand the ecological challenges facing humanity.