Are ecology's classic patterns statistical rather than ecological?

Every community has a few common species and many rare ones, and the number of species rises with area in a remarkably regular way. If such patterns follow from simple constraints, such as the numbers of species and individuals, matching them says little about ecological mechanisms; if not, the deviations are where the ecology lies.

Question

To what extent are widely studied ecological patterns, such as the species-abundance distribution (SAD) and the species-area relationship (SAR), the outcome of statistical processes (sampling, random placement of individuals, constraints set by species richness $S$ and total abundance $N$) rather than of ecological processes such as competition, dispersal and niche differences?

Background

This is one of 100 fundamental ecological questions drawn up for the British Ecological Society's centenary from 754 questions submitted by 388 participants, in the theme on methods [1]. Theories are often judged by how well they reproduce these patterns, so if a pattern follows from constraints alone, reproducing it is weak evidence for any mechanism.

What is known

• The maximum entropy theory of ecology (METE) predicts the SAD (a Fisher log-series), the SAR and other patterns from state variables alone (area, $S$, $N$ and total metabolic rate), without invoking specific ecological mechanisms [2].
• Given only $S$ and $N$, a maximum-entropy model predicted 83–93% of the variation in rank abundance across 15,848 communities of birds, mammals, plants and butterflies [3].
• Most abundance distributions possible with the same $S$ and $N$ (the "feasible set") are hollow curves highly correlated with observed ones, though real SADs are often more uneven and less variable [4].
• In 60 forest communities, METE captured 96% and 89% of the variation in species abundance and individual size distributions, but did poorly on the size–density relationship [5].

What would count as progress

No single result settles a question like this; contributions like these would move it forward:

• Constraint-based null models for the SAR and other patterns, not only the SAD, with predictions fixed in advance and tested on large open datasets, quantifying the variation left once constraints are accounted for.
• Tests of whether the residual deviations from constraint-based predictions correlate with measured ecological processes, such as dispersal limitation or environmental heterogeneity.
• Shared data compilations and code, so that competing theories are scored on the same communities with the same statistics.

References

1. Sutherland, W. J. et al. (2013). Identification of 100 fundamental ecological questions. Journal of Ecology 101(1), 58–67.
2. Harte, J., Zillio, T., Conlisk, E. & Smith, A. B. (2008). Maximum entropy and the state-variable approach to macroecology. Ecology 89(10), 2700–2711.
3. White, E. P., Thibault, K. M. & Xiao, X. (2012). Characterizing species abundance distributions across taxa and ecosystems using a simple maximum entropy model. Ecology 93(8), 1772–1778.
4. Locey, K. J. & White, E. P. (2013). How species richness and total abundance constrain the distribution of abundance. Ecology Letters 16(9), 1177–1185.
5. Xiao, X., McGlinn, D. J. & White, E. P. (2015). A strong test of the maximum entropy theory of ecology. The American Naturalist 185(3), E70–E80.

Source

Imported from Identification of 100 fundamental ecological questions, question 97, curated by Sutherland et al. Listed as open in the source (2013) and still an active research question as of 2026-10-20. The statement above is written in our own words; see the source for the original wording, history and discussion.