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To Model or not to Model, That is no Longer the Question for Ecologists
- Source :
- Ecosystems (New York, N.Y.)
- Publication Year :
- 2017
-
Abstract
- Here, I argue that we should abandon the division between "field ecologists" and "modelers," and embrace modeling and empirical research as two powerful and often complementary approaches in the toolbox of 21st century ecologists, to be deployed alone or in combination depending on the task at hand. As empirical research has the longer tradition in ecology, and modeling is the more recent addition to the methodological arsenal, I provide both practical and theoretical reasons for integrating modeling more deeply into ecosystem research. Empirical research has epistemological priority over modeling; however, that is, for models to realize their full potential, and for modelers to wield this power wisely, empirical research is of fundamental importance. Combining both methodological approaches or forming "super ties" with colleagues using different methods are promising pathways to creatively exploit the methodological possibilities resulting from increasing computing power. To improve the proficiency of the growing group of model users and ensure future innovation in model development, we need to increase the modeling literacy among ecology students. However, an improved training in modeling must not curtail education in basic ecological principles and field methods, as these skills form the foundation for building and applying models in ecology.
- Subjects :
- 0106 biological sciences
010504 meteorology & atmospheric sciences
Exploit
Ecology (disciplines)
media_common.quotation_subject
education in ecology
Biology
ecological megatrends
010603 evolutionary biology
01 natural sciences
Literacy
Article
Power (social and political)
Empirical research
model development
computer simulation
Environmental Chemistry
Ecology, Evolution, Behavior and Systematics
0105 earth and related environmental sciences
media_common
Philosophy of science
ecosystem modeling
Ecology
Management science
Toolbox
Quantitative ecology
philosophy of science
Subjects
Details
- Language :
- English
- ISSN :
- 14350629 and 14329840
- Volume :
- 20
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Ecosystems (New York, N.Y.)
- Accession number :
- edsair.doi.dedup.....905a538938205238c738262f6251ec11