Lack of quantitative training among early-career ecologists: a survey of the problem and potential solutions.

PeerJ

Département de Biologie, Chimie et Géographie, Université du Québec à Rimouski , Rimouski (QC) , Canada ; Québec Centre for Biodiversity Sciences, McGill University, Canada.

Published: April 2014

Proficiency in mathematics and statistics is essential to modern ecological science, yet few studies have assessed the level of quantitative training received by ecologists. To do so, we conducted an online survey. The 937 respondents were mostly early-career scientists who studied biology as undergraduates. We found a clear self-perceived lack of quantitative training: 75% were not satisfied with their understanding of mathematical models; 75% felt that the level of mathematics was "too low" in their ecology classes; 90% wanted more mathematics classes for ecologists; and 95% more statistics classes. Respondents thought that 30% of classes in ecology-related degrees should be focused on quantitative disciplines, which is likely higher than for most existing programs. The main suggestion to improve quantitative training was to relate theoretical and statistical modeling to applied ecological problems. Improving quantitative training will require dedicated, quantitative classes for ecology-related degrees that contain good mathematical and statistical practice.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3961151PMC
http://dx.doi.org/10.7717/peerj.285DOI Listing

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