Tansley’s 1917 paper on the competition between G. Saxatile and G. Sylvestre was insightful on the methods and results involved in early day investigations of plant population distribution and the factors involved between 2 different plant species in competition. The findings of from the report states that both species can establish and maintain themselves to a certain extent depending on the soil type both in their roots or shoots, the data that was gathered in this report appeared to be simplistic and the conclusions appeared to be more empirical. Oddly enough something crucial is missing from the data gathered that is constantly present in nearly all scientific reports with numerical data variables have, and that’s statistical analysis testing. A reason that may be the case would be that the statistical tests that became popular in scientific papers has not been invented or standardized yet. The usual test of significance widely used for scientific studies is the t-test, which was developed in 1908 by a chemist named William Sealy Gosset who worked for Guinness brewing company in Dublin, Ireland; he developed the test as an economical way of monitoring the quality of the popular stout that the company is known for. The reason that the test is formally known as Student’s t-test is because Gosset submitted the findings under the pseudonym of “Student” as the company policy didn’t allow the scientists to publish their findings and results to the public due to competition fears. The work of Gosset was referenced and popularized by well-known statistician and geneticist Sir Ronald Fisher. This could explain the lack of statistical analysis in Tansley’s paper as the idea of significance testing of numerical data variables was still under development and not yet mandatory in the scientific community, which speaks to the evolution of scientific thinking from an empirical thought or discovery to a testable hypothesis that can be supported or refuted.
Applied Plant Ecology Winter 2020 