Four principles for improved statistical ecology

• Published in: Methods in ecology and evolution 2024-02, Vol.15 (2), p.266-281
• Main Authors: Popovic, Gordana, Mason, Tanya Jane, Drobniak, Szymon Marian, Marques, Tiago André, Potts, Joanne, Joo, Rocío, Altwegg, Res, Burns, Carolyn Claire Isabelle, McCarthy, Michael Andrew, Johnston, Alison, Nakagawa, Shinichi, McMillan, Louise, Devarajan, Kadambari, Taggart, Patrick Leo, Wunderlich, Alison, Mair, Magdalena M., Martínez‐Lanfranco, Juan Andrés, Lagisz, Malgorzata, Pottier, Patrice
• Format: Article
• Language: English
• ISSN: 2041-210X; 2041-210X
• DOI: 10.1111/2041-210X.14270

Increasing attention has been drawn to the misuse of statistical methods over recent years, with particular concern about the prevalence of practices such as poor experimental design, cherry picking and inadequate reporting. These failures are largely unintentional and no more common in ecology than in other scientific disciplines, with many of them easily remedied given the right guidance. Originating from a discussion at the 2020 International Statistical Ecology Conference, we show how ecologists can build their research following four guiding principles for impactful statistical research practices: (1) define a focussed research question, then plan sampling and analysis to answer it; (2) develop a model that accounts for the distribution and dependence of your data; (3) emphasise effect sizes to replace statistical significance with ecological relevance; and (4) report your methods and findings in sufficient detail so that your research is valid and reproducible. These principles provide a framework for experimental design and reporting that guards against unsound practices. Starting with a well‐defined research question allows researchers to create an efficient study to answer it, and guards against poor research practices that lead to poor estimation of the direction, magnitude, and uncertainty of ecological relationships, and to poor replicability. Correct and appropriate statistical models give sound conclusions. Good reporting practices and a focus on ecological relevance make results impactful and replicable. Illustrated with two examples—an experiment to study the impact of disturbance on upland wetlands, and an observational study on blue tit colouring—this paper explains the rationale for the selection and use of effective statistical practices and provides practical guidance for ecologists seeking to improve their use of statistical methods. La atención acerca del uso incorrecto de métodos estadísticos en ecología y áreas relacionadas ha aumentado mucho en los últimos años, con especial énfasis en la incidencia elevada de malas prácticas en el diseño de los estudios, así como también en el reporte inadecuado de los hallazgos, incluyendo resultados parciales o sesgados. Estos fallos son en gran parte involuntarios y, en general, podrían prevenirse con la instrucción adecuada. Con orígen en un taller de trabajo en el marco de la Conferencia Internacional de Ecología Estadística en 2020, proponemos una serie de cuatro principios orientadores par