University of Helsinki
At the next weeks Perspectives on Science -seminar (14.10.) Alkistis Elliott-Graves (University of Helsinki & TINT) will present her paper “The Future of Predictive Ecology“.
The seminar will take place in Porthania, room P673, from 14 to 16.
Author bio:
Alkistis Elliott-Graves is a philosopher of science specialized in the philosophy of ecology and the philosophy of social sciences, and her research addresses conceptual and methodological issues in scientific practice. She is a Marie Skłodowska-Curie fellow at the Center for Philosophy of the Social Sciences (TINT) and PI of a 3-year research project at the University of Helsinki. She is currently working on two projects: one addressing the danger of overgeneralization and the difficulty of making predictions in the fields of ecology and economics, and another that explores the difficulties of prediction faced by climate scientists.
Paper abstract:
Prediction is an important aspect of scientific practice, because it helps us to confirm theories and effectively intervene on the systems we are investigating. In ecology, prediction is a controversial topic: even though the number of papers focusing on prediction is constantly increasing, many ecologists believe that the quality of ecological predictions is unacceptably low, in the sense that they are not sufficiently accurate sufficiently often. Moreover, ecologists disagree on how predictions can be improved. On one side are the ‘theory-driven’ ecologists, those who believe that ecology lacks a sufficiently strong theoretical framework. For them, more general theories will yield more accurate predictions. On the other are the ‘applied’ ecologists, whose research is focused on effective interventions on ecological systems. For them, deeper knowledge of the system in question is more important than background theory. The theory-driven approach has sound philosophical commitments, but is not best suited to ecological systems, as they are not merely complex but also causally heterogeneous. Thus, there is a tradeoff between generalisability and predictive power. I am more sympathetic to the opposing view, as it is better suited to the reality of ecological systems, though I believe that it suffers from an important practical limitation. I will propose a way forwards for predictive ecology that takes into account the pros and cons of each view.