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Brood parasites lay their eggs in the nests of other species that may then raise their young and pay the costs associated with parental care1,2,3. This act of deception to outwit the host on the part of the parasite and sleuthing to detect the parasite on the part of the host provides strong selective pressures on both actors. In some cases of avian brood parasitism, the host's recognition of disparate parasitic eggs selects for parasites that mimic host eggs, which produces an evolutionary arms race between host and parasite4. Studying brood parasitism is important because it is a model system for investigating coevolutionary dynamics and decision-making in the wild5. Egg rejection experiments are one of the most common methods used for studying avian brood parasitism in the field and an important tool that ecologists use to investigate interspecific interactions6.
During the course of egg rejection experiments, researchers typically introduce natural or model eggs and assess the host's response to these experimental eggs over a standardized period. Such experiments can involve swapping real eggs (that vary in appearance) between nests7, or dyeing or painting the surfaces of real eggs (optionally adding patterns) and returning them to their original nests8, or generating model eggs that have manipulated traits such as color9, spotting10, size11, and/or shape12. The host response to eggs of varying appearance can provide valuable insight into the information content they use to reach an egg rejection decision13 and just how different that egg needs to be to elicit a response14. Optimal acceptance threshold theory15 states that hosts should balance the risks of mistakenly accepting a parasitic egg (acceptance error) or mistakenly removing their own egg (rejection error) by examining the difference between their own eggs (or an internal template of those eggs) and the parasitic eggs. As such, an acceptance threshold exists beyond which hosts decide a stimulus is too different to tolerate. When parasitism risk is low, the risk of acceptance errors is lower than when the risk of parasitism is high; thus, decisions are context specific and will shift appropriately as perceived risks change14,16,17.
Optimal acceptance threshold theory assumes that hosts base decisions upon continuous variation in host and parasite phenotypes. Therefore, measuring host responses to varying parasite phenotypes is necessary to establish how tolerant a host population (with its own phenotypic variation) is to a range of parasitic phenotypes. However, virtually all prior studies have relied on categorical egg color and maculation treatments (e.g., mimetic/non-mimetic). Only if host eggshell phenotypes do not vary, which is not a biologically practical expectation, would all responses be directly comparable (regardless of the degree of mimicry). Otherwise, a "mimetic" egg model will vary in how similar it is to host eggs within and between populations, which could potentially lead to confusion when comparing findings18. Theory suggests that host decisions are based upon the difference between the parasitic egg and their own14, not necessarily a particular parasitic egg color. Therefore, using a single egg model type is not an ideal approach to test hypotheses on host decision thresholds or discrimination abilities, unless the just noticeable difference (hereafter JND) between the egg model type and individual host egg color is the variable of interest. This also applies to experimental studies that swap or add natural eggs to test host responses to a natural range of colors19. However, while these studies do allow for variation in host and parasite phenotypes, they are limited by natural variation found in traits6, particularly when using conspecific eggs7.
By contrast, researchers that make artificial eggs of varied colors are free from the constraints of natural variation (e.g., they can investigate responses to superstimuli20), allowing them to probe the limits of host perception6. Recent research has used novel techniques to measure host responses across a phenotypic range, by painting experimental eggs designed to match and surpass the natural range of variation in eggshell9 and spot colors21. Studying host responses to eggs with colors along gradients can uncover underlying cognitive processes because theoretical predictions, such as acceptance thresholds15 or coevolved mimicry4, are based on continuous differences between traits. For example, by using this approach, Dainson et al.21 established that when chromatic contrast between eggshell ground coloration and spot coloration is higher, the American Robin Turdus migratorius tends to reject eggs more strongly. This finding provides valuable insights on how this host processes information, in this case through spotting, to decide whether to remove a parasitic egg. By customizing paint mixtures, researchers can precisely manipulate the similarity between an experimental egg's color and host's egg color, while standardizing other confounding factors such as spotting patterns10, egg size22 and egg shape23.
To encourage further replication and metareplication24 of classic and recent egg rejection work, it is important that scientists use methodologies that are standardized across phylogeny (different host species)7,22, space (different host populations)7,22,25,26 and time (different breeding seasons)7,22,25,26,27, which was done only rarely. Methodologies that were not standardized28 were later shown to lead to artefactual results29,30. This paper serves as a set of guidelines for researchers seeking to replicate this type of egg rejection experiment that examines responses to continuous variation and highlights a number of important methodological concepts: the importance of control nests, a priori hypotheses, metareplication, pseudoreplication, and color and spectral analysis. Despite egg rejection experiments dominating the field of avian host-parasite coevolution, no comprehensive protocol exists yet. Therefore, these guidelines will be a valuable resource to increase inter- and intra-lab repeatability as the true test of any hypothesis lies in metareplication, i.e., repeating whole studies across phylogeny, space and time24, which can only be meaningfully done when using consistent methods29,30,31.