Egg Phenotype Matching by Cuckoos in Relation to Discrimination by Hosts and Climatic

ELECTRONIC APPENDIX

Egg phenotype matching by cuckoos in relation to discrimination by

hosts and climatic conditions

Jesús M. Avilés1,2*, Johan R. Vikan2,3, Frode Fossøy2,3, Anton Antonov2,3|, Arne

2,3 2,3 2,4 2,4 Moksnes , Eivin Røskaft , Jacqui A. Shykoff , Anders P. Møller and Bård G.

Stokke2,3

1 Departamento de Ecología Morfológica y Funcional, Estación Experimental de Zonas

Áridas, C.S.I.C., Carretera de Sacramento s/n, Cañada de San Urbano, E-04001

Almería, Spain

2Centre for Advanced Study, Drammensveien 78, N-0271, Oslo, Norway

3Department of Biology, Norwegian University of Science and Technology, NO-7491

Trondheim, Norway

4Université Paris-Sud, Laboratoire Ecologie Systématique et Evolution, UMR 8079,

Orsay cedex, F-91405, France ESM1. Principal components in relation to wavelength, derived from reflectance spectra from cuckoo and reed warbler eggs in each clutch. PC1 indicates principal component 1, PC2 principal component 2, and PC3 principal component 3. PC1 describes achromatic variation and explains 92.8 % of overall variation in egg colouration. PC2 (blue-red chroma) and PC3 (UV-blue chroma), respectively, explain 68.1 % and 19.4 % of the chromatic variance in cuckoo and reed warbler egg colouration. ESM2. Application of the False Discovery Rate

This powerful procedure controls the proportion of falsely rejected null hypotheses (Type I error), rather than the chance of making even a single such error, which is the aim of, for instance, the Bonferroni and the sequential Bonferroni procedures [93]. Recent findings have shown that FDR procedures are more suitable for ecological research than the less powerful and very conservative Bonferroni procedures

[e.g. 94-97]. We followed the procedure to control FDR at an α level of 0.05 described in [92]: For m tests, rank the P values in ascending order P(1) ≤ P(2) ≤ … ≤ P(m), and denote by H(i) the null hypothesis corresponding to P(i); Let k be the largest i for which

P(i) ≤ α/m * i and reject all null hypotheses H(1)…. H(k). In other words, starting with the highest P value each P is checked for this requirement; at the first P that meets the requirement its corresponding null hypothesis and all having smaller P’s are rejected. A prerequisite in order to wisely apply FDR or other multiple testing procedures is to define appropriate groups, or families of hypotheses [92,96]. In our study, three families of hypotheses can be conservatively distinguished dealing with spatial variation in cuckoo-host egg mimicry: those concerning effect of cuckoo parasitism (N = 3 tests, all P values ≥.033 not significant after FDR control), those concerning effect of rejection rate on cuckoo- host egg phenotype matching (N = 3 tests, all P values ≥.033 not significant after FDR control), and those concerning consequences of climatic conditions (N = 6 tests, all P values ≥.05 not significant after FDR control). In addition, three families of hypotheses dealing with spatial variation in host egg phenotype can be distinguished: those concerned with the effect of cuckoo parasitism (N = 4 tests, all P values ≥.037 not significant after FDR control), those concerned with the effect of rejection rate on host egg phenotype (N = 4 tests, all P values ≥.05 not significant after FDR control), and those concerning relationships between climatic conditions and host egg phenotype (N =

8 tests, all P values ≥.037 not significant after FDR control). Finally, we distinguished three families of hypotheses dealing with spatial variation in cuckoo egg phenotype: those concerned with the effect of cuckoo parasitism (N = 4 tests, all P values ≥.025 not significant after FDR control), those concerned with the effect of rejection rate on cuckoo egg phenotype (N = 4 tests, all P values ≥.025 not significant after FDR control), and those concerning relationships between climatic conditions and host egg phenotype (N = 8 tests, all P values ≥.025 not significant after FDR control).

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