Abstract
AbstractEcologists are studying increasingly complex and important issues such as climate change and ecosystem services. These topics often involve large data sets and the application of complicated quantitative models. We evaluated changes in statistics used by ecologists by searching nearly 20,000 published articles in ecology from 1990 to 2013. 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 one‐third of doctoral programs showed no record of required or optional statistics classes. Approximately one‐quarter of programs did require a statistics course, but most of those did not cover contemporary statistical philosophy or advanced techniques. Only one‐third 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.
Highlights
Ecological questions and data are becoming increasingly complex and as a result we are seeing the development and proliferation of sophisticated statistical approaches in the ecological literature
Our search of statistical techniques returned 19,526 different papers published between 1990 and 2013, 64.6% of all papers published in the seven journals we searched
This is partially due to the emergence of a new journal in 1998 (Ecology Letters); the number of papers published per year increased in the other six journals as well, by as few as 11 papers in Oecologia to as many as 88 papers in Ecology
Summary
Ecological questions and data are becoming increasingly complex and as a result we are seeing the development and proliferation of sophisticated statistical approaches in the ecological literature. TOUCHON AND McCOY asking “how much” and in “what direction” ecological processes are affected by different mechanisms (Burnham and Anderson 2002, McCarthy 2007, Bolker et al 2009, Symonds and Moussalli 2011, Denny and Benedetti-C ecchi 2012) This discussion is not new (e.g., Quinn and Dunham 1983), and several authors have pleaded for more intensive training in mathematics and statistics in ecology (e.g., Johnson 1999, Ellison and Dennis 2009, Robeva and Laubenbacher 2009, Hobbs and Ogle 2011), including students frustrated by their lack of training (Butcher et al 2007). We hope that our analysis will inspire ecology programs to re-evaluate their curriculums and improve quantitative training of tomorrow’s ecologists
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