TY - JOUR
T1 - On the plains and prairies of Minnesota
T2 - The role of mathematical statistics in biological explanation
AU - Grosholz, Emily R.
N1 - Funding Information:
I hope that my explanation of Aster Models and these case studies show the readers (scientific and philosophical) why the use of mathematical statistics in biology, once expanded to use a variety of non-normal distributions, can be truly explanation and help us make predictions. Especially right now, we need to see what is coming towards us. As Aristotle shows in the Rhetoric, to decide what to do next, we must engage in practical deliberation, in this instance on the basis of well-understood and well-collected data. One of Ruth Geyer Shaw’s research projects is ‘Healthy Prairies Project: Prairie Sustainability through Seed Storage, Beneficial Microbes, and Adaptation,’ along with Georgiana May and Margaret Kuchenreuther; they also recruit undergraduate students at the University of Minnesota to help. https://ruthgshaw.wordpress.com/research/healthy-prairies-project . This project is funded by the Minnesota Environment and Natural Resources Trust Fund, and the Legistative-Citizen Commission on Minnesota Resources. So, this is also a good example of scientists interacting with those in government to make practical decisions: what should we do next? Scientists offer data from the field, and mathematical models, and both in conjunction offer helpful arguments to law-makers and elected officials about what actions we can take in the face of the local and global crisis that confronts us all.
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.
PY - 2021/12
Y1 - 2021/12
N2 - In this essay, I consider the use of mathematical statistics in the study of biological systems in the field, using as case studies the work of Ruth Geyer Shaw and her colleagues at the University of Minnesota. To address practical issues, like how to enhance prairie restoration, and how to prepare for (and perhaps prevent) the effect of rapid climate change, she and her colleagues combine mathematical modeling and intensive data collection in the field. Using ANOVA and the more versatile approach of Aster Models, they show the effects of inbreeding (which follows from the fragmentation of prairie) to lower the fitness of plant populations. They study the genetic variance of plants in stable populations, which is important when that population must deal with changing conditions. And they study the consequences of rapid climate change: even good genetic variance and initial fitness may not save a given population from extinction. This leads to a new alliance of science with local, state, federal and global politics.
AB - In this essay, I consider the use of mathematical statistics in the study of biological systems in the field, using as case studies the work of Ruth Geyer Shaw and her colleagues at the University of Minnesota. To address practical issues, like how to enhance prairie restoration, and how to prepare for (and perhaps prevent) the effect of rapid climate change, she and her colleagues combine mathematical modeling and intensive data collection in the field. Using ANOVA and the more versatile approach of Aster Models, they show the effects of inbreeding (which follows from the fragmentation of prairie) to lower the fitness of plant populations. They study the genetic variance of plants in stable populations, which is important when that population must deal with changing conditions. And they study the consequences of rapid climate change: even good genetic variance and initial fitness may not save a given population from extinction. This leads to a new alliance of science with local, state, federal and global politics.
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U2 - 10.1007/s11229-021-03029-3
DO - 10.1007/s11229-021-03029-3
M3 - Article
AN - SCOPUS:85100514266
SN - 0039-7857
VL - 199
SP - 5377
EP - 5393
JO - Synthese
JF - Synthese
IS - 1-2
ER -
