Signaling of need, sibling competition, and the cost of honesty

Young birds and mammals frequently solicit food by means of extravagant and apparently costly begging displays. Much attention has been devoted to the idea that these displays are honest signals of need, and that their apparent cost serves to maintain their honesty. Recent analyses, however, have shown that the cost needed to maintain a fully informative, honest signal may often be so great that both offspring (signaler) and parent (receiver) would do better to refrain from communication. This apparently calls into question the relevance of the costly signaling hypothesis. Here, I show that this argument overlooks the impact of sibling competition. When multiple signalers must compete for the attention of a receiver (as is commonly the case in parent–offspring interactions), I show that (all other things being equal) individual equilibrium signal costs will typically be lower. The greater the number of competitors, the smaller the mean cost, though the maximum level of signal intensity employed by very needy signalers may actually increase with the number of competitors. At the same time, costs become increasingly sensitive to relatedness among signalers as opposed to relatedness between signalers and receivers. As a result of these trends, signaling proves profitable for signalers under a much wider range of conditions when there is competition (though it is still likely to be unprofitable for receivers).

A joint hazard and time scaling model to compare survival curves.

To provide a more general method for comparing survival experience, we propose a model that independently scales both hazard and time dimensions. To test the curve shape similarity of two time-dependent hazards, h1(t) and h2(t), we apply the proposed hazard relationship, h12(tKt)/ h1(t) = Kh, to h1. This relationship doubly scales h1 by the constant hazard and time scale factors, Kh and Kt, producing a transformed hazard, h12, with the same underlying curve shape as h1. We optimize the match of h12 to h2 by adjusting Kh and Kt. The corresponding survival relationship S12(tKt) = [S1(t)]KtKh transforms S1 into a new curve S12 of the same underlying shape that can be matched to the original S2. We apply this model to the curves for regional and local breast cancer contained in the National Cancer Institute's End Results Registry (1950-1973). Scaling the original regional curves, h1 and S1 with Kt = 1.769 and Kh = 0.263 produces transformed curves h12 and S12 that display congruence with the respective local curves, h2 and S2. This similarity of curve shapes suggests the application of the more complete curve shapes for regional disease as templates to predict the long-term survival pattern for local disease. By extension, this similarity raises the possibility of scaling early data for clinical trial curves according to templates of registry or previous trial curves, projecting long-term outcomes and reducing costs. The proposed model includes as special cases the widely used proportional hazards (Kt = 1) and accelerated life (KtKh = 1) models.