Modeling: Neutral, Null, and Baseline

William C Bausman

doi:10.1086/699021

Abstract

Two strategies for using a model as “null” are distinguished.Null modelingevaluates whether a process is causally responsible for a pattern by testing it against a null model.Baseline modelingmeasures the relative significance of various processes responsible for a pattern by detecting deviations from a baseline model. When these strategies are conflated, models are illegitimately privileged as accepted until rejected. I illustrate this using the neutral theory of ecology and draw general lessons from this case. First, scientists cannot draw certain conclusions using null modeling. Second, these conclusions follow using baseline modeling, but doing so requires more evidence.

Highlights

Nitecki and Hoffman begin the volume Neutral Models in Biology by saying, “Neutral model” belongs to a whole family of terms, which are sometimes . . . used interchangeably; these are “null hypothesis,” “null model,” “random model,” “baseline model,” “stochastic approach,” “neutral theory,” etc. (1987, 3)This ambiguity remains today
Valen identified the same problem in a short scientific correspondence in Nature2: In the past decade or so a subtle misuse of null hypotheses has become almost standard in ecology, biogeography, functional morphology and theoretical paleontology . . . The difficulty here comes when a null hypothesis is placed in a privileged position, to be accepted at least provisionally until disproved. (1985, 230)
The relevant difference for this paper is that null modeling tests the hypothesis that a process is causally responsible for a type of pattern, while null hypothesis testing tests the hypothesis that a pattern was due to sampling error, measurement error, or randomness and independent causes

Summary

Introduction

Nitecki and Hoffman begin the volume Neutral Models in Biology by saying, “Neutral model” belongs to a whole family of terms, which are sometimes . . . used interchangeably; these are “null hypothesis,” “null model,” “random model,” “baseline model,” “stochastic approach,” “neutral theory,” etc. (1987, 3). I focus on the case of the neutral theory of ecology and show how Hubbell and other ecologists privilege the neutral model qua “null” as accepted until rejected To show why this reasoning does not establish its conclusions, and to enable ecologists to state their intended methods, I introduce a distinction between two important methodological uses of models: null modeling and baseline modeling. Ecologists using neutral theory, in contrast, start by assuming that there are no relevant differences between species and that every individual, regardless of species, is functionally equivalent They first try to understand observed patterns as the result of history and chance. This support cannot, come from the neutrality of the model

Background

Conclusion