Adaptive inference for distinguishing credible from incredible patterns in nature

  • Holling C
  • Allen C
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Abstract

Strong inference is a powerful and rapid tool that can be used to identify and explain patterns in molecular biology, cell biology, and physiology. It is effective where causes are single and separable and where discrimination between pairwise alternative hypotheses can be determined experimentally by a simple yes or no answer. But causes in ecological systems are multiple and overlapping and are not entirely separable. Frequently, competing hypoth- eses cannot be distinguished by a single unambig- uous test, but only by a suite of tests of different kinds, that produce a body of evidence to support one line of argument and not others. We call this process "adaptive inference". Instead of pitting each member of a pair of hypotheses against each other, adaptive inference relies on the exuberant inven- tion of multiple, competing hypotheses, after which carefully structured comparative data are used to explore the logical consequences of each. Herein we present an example that demonstrates the at- tributes of adaptive inference that have developed out of a 30-year study of the resilience of ecosys- tems.

Author-supplied keywords

  • Adaptive inference
  • Cross-scale dynamics
  • Ecosystem structure
  • Hypothesis testing
  • Lumps
  • Resilience
  • Strong inference
  • Textural discontinuity hypothesis

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Authors

  • C. S. Holling

  • Craig R. Allen

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