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. 2015 Jan 14;2(1):140452.
doi: 10.1098/rsos.140452. eCollection 2015 Jan.

How the zebra got its stripes: a problem with too many solutions

Affiliations

How the zebra got its stripes: a problem with too many solutions

Brenda Larison et al. R Soc Open Sci. .

Abstract

The adaptive significance of zebra stripes has thus far eluded understanding. Many explanations have been suggested, including social cohesion, thermoregulation, predation evasion and avoidance of biting flies. Identifying the associations between phenotypic and environmental factors is essential for testing these hypotheses and substantiating existing experimental evidence. Plains zebra striping pattern varies regionally, from heavy black and white striping over the entire body in some areas to reduced stripe coverage with thinner and lighter stripes in others. We examined how well 29 environmental variables predict the variation in stripe characteristics of plains zebra across their range in Africa. In contrast to recent findings, we found no evidence that striping may have evolved to escape predators or avoid biting flies. Instead, we found that temperature successfully predicts a substantial amount of the stripe pattern variation observed in plains zebra. As this association between striping and temperature may be indicative of multiple biological processes, we suggest that the selective agents driving zebra striping are probably multifarious and complex.

Keywords: ecological predictions; patterning; random forest; species distribution modelling; stripes; zebra.

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Figures

Figure 1.
Figure 1.
(a) Importance scores for each environmental variable used as input to random forest algorithm models for hind leg stripe thickness and torso stripe definition. Variables with higher mean square error (calculated as the average increase in squared residuals when the variable is permuted) are more important. Variables having an importance score greater than the absolute value of the lowest negative scoring variable (solid vertical line) are potentially important and informative [30]. Variables shown with a black circle are those that remained important as the model was refined. (b) Correlations between observed and predicted values for hind leg stripe thickness and torso stripe definition.
Figure 2.
Figure 2.
Predicted levels of hind leg stripe thickness (left) and torso stripe definition (right), from a random forest model based on 16 populations. Hind leg stripe thickness is best predicted by BIO3 and BIO11. Torso stripe definition is best predicted by BIO3, BIO11 and BIO13.

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