To answer this question we derived additive regression models for three response (Y) variables pertaining to the mechanical properties: ultimate strength, extensibility and toughness, and eight predictor (xi) variables: thread width (x1), FWHM of the amorphous halo (x2), FWHM of the (200) diffraction peak (x3), crystallinity (x4), long period (x5), proline composition (x6), glycine composition (x7), and alanine composition (x8) using data from all species excluding L. hasselti. The variables chosen were those that our analyses above found to differ across treatments in at least one species. Our models showed crystallinity to predominantly influence the ultimate strength in nutritionally affected MA silks (Table 2A). Long period, which represents the nanostructure alignment across the silk’s amorphous and lamellar regions, and alanine and proline composition, were predominantly influential over extensibility (Table 2B). Long period, along with glycine, alanine and proline compositions, influenced silk toughness (Table 2C).