Why not WhyWhere: The need for more complex models of simpler environmental spaces

doi:10.1016/j.ecolmodel.2006.12.023

Ecological Modelling

Volume 203, Issues 3–4, 10 May 2007, Pages 527-530

https://doi.org/10.1016/j.ecolmodel.2006.12.023 Get rights and content

Abstract

WhyWhere has recently been introduced by Stockwell as a new tool for ecological niche modeling or species distribution modeling. I address two features of WhyWhere and its presentation: (1) the assertion that hundreds of environmental data layers are necessary to summarize ecological variation across environments, and (2) the idea that species’ ecological needs can be summarized in just 2 or 3 dimensions. I present evidence that neither idea is valid, effectively arguing that environmental spaces are simpler than Stockwell envisages, but that more complex and dimensional models are necessary to describe species’ ecological niches. Beyond these conceptual problems, WhyWhere suffers from several more practical problems, which render it little useful for any practical application.

Section snippets

Complexity of ecological landscapes

Ecological landscapes can be divided at the outset into those that are physical characteristics of environments (“scenopoetic variables”) versus those that are shaped and modified by biotic factors (Hutchinson, 1978)—both Stockwell and I refer to the former, and reserve the latter from consideration, at least for the present. Stockwell, however, puts considerable weight on the fact that WhyWhere surveys hundreds of data layers that summarize ecological variation across landscapes, and as such

Simplicity of ecological niches

On the other side of the coin, considerably more serious is WhyWhere's assumption that the ecological niches of species can be summarized in very few, “typically two,” environmental dimensions. This viewpoint flies in the face of decades of ecological research—indeed, dating back to the very beginning of the field, researchers have appreciated a more complex, multivariate nature of factors limiting species’ geographic and ecological distributions (Grinnell, 1917, Grinnell, 1924, Hutchinson, 1957

Conclusion

Given the challenge of sorting through the impressive diversity of geospatial data now available for ecological niche modeling, Stockwell should be congratulated on his development of a data-mining-based approach to this challenge. The idea of integrating data mining and modeling is a useful addition to the literature. What is more, WhyWhere's remote data access features seem also to be a useful development, although I was not able to download or upload data sets as Stockwell had promised.

Acknowledgements

Many thanks to David Stockwell for discussion of these ideas, to Jorge Soberón for a careful read of the manuscript, and to two anonymous readers for insightful comments.

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View full text

Short communicationWhy not WhyWhere: The need for more complex models of simpler environmental spaces

Abstract

Section snippets

Complexity of ecological landscapes

Simplicity of ecological niches

Other problems

Conclusion

Acknowledgements

Forest Ecol. Manag.

Ecol. Model.

Ecol. Model.

Ecol. Model.

Ecol. Model.

Ecol. Model.

Ecol. Model.

Measurement of the realized qualitative niche: environmental niches of five Eucalyptus species

Ecol. Monogr.

DOMAIN: a flexible modeling procedure for mapping potential distributions of animals and plants

Biodiversity Conservation

Predictions and their validation: rare plants in the Central Highlands, Victoria

Novel methods improve prediction of species’ distributions from occurrence data

Ecography

Field tests of theories concerning distributional control

Am. Nat.

Geography and Evolution

Ecology

Error Propagation in Environmental Modelling with GIS

Short communication
Why not WhyWhere: The need for more complex models of simpler environmental spaces