Molt-breeding overlap in birds: phenology and trade-offs at the individual and the community levels

Life history cycles in organisms represent evolutionary adaptations to selection pressures that act both through environmental and intrinsic factors. As a result, life history cycles are adjusted to temporal patterns in resource availability, in predation and in competition, among others, to maximize individual fitness. For species that live in different environments and that undergo fewer life history stages within a given cycle, the organization of annual schedules may deviate from the widely studied temperate zone species that typically undergo a number of different life history stages in strict sequence and temporal separation. The study of life history schedules and evolution is mostly concerned with the timing of each life state and the factors that regulate the schedule as well as each separate event. However, it has been noted in various species that not all states are fully separated and that some overlap may occur between them, with only full co-occurrence of states reported to date in birds. I explored the interaction, regulations and consequences of tropical molt- breeding overlap by studying the occurrence of such an overlap stage at individual and community levels as well as comparing controlled laboratory conditions and with the wild setting. I addressed several major questions: How common is the overlap of reproduction and molt in this bird community as a whole? What environmental factors are associated with the overlap? During the overlap, are both life history stages indeed slowed down? Do any trade-offs that may affect fitness arise from the overlap? By assessing reproductive and molting condition in all individuals, I was able to show the occurrence of overlap between these events as a frequent phenomenon in montane tropical birds, with approximately half of the species studied displaying the overlap not only at a population level, but also within individuals. I outline some environmental factors that might increase the frequency of the overlap in the community, while encountering yearly variations based on precipitation, which could point to phenotypical plasticity in the regulation of the life cycle. Based on captive work, I show some of the changes and alterations in molt dynamics and behavior that individuals incurring the overlap might face. By comparing zebra finches (Taeniopygia guttata) that were allowed to overlap with those that just molted, I was able to show differences in individual feather growth rates, molt intensity and time budgets. Overlapping individuals undertake slower flight-feather replacement, with out the clear sex-difference that was initially predicted. Cost and consequences were explored in a wild population of Slaty-brush finch (Atlapetes schistaceus) in Colombia, over a period of four years. In this population individuals in all major states of the life cycle can be found at a given time. For overlapping individuals, I have determined a decrease in feather quality, as well as in flight performance that could affect survival, and therefor fitness, in this long-lived species. Contrary to the captive experiment, and in accordance with prior expectations, sex differences were present in the wild population, with females showing lower quality flight feathers. The frequency of molt-breeding overlap in montane cloud forests poses significant questions to regulation and mechanisms of control and integration of the life-cycle stages. In this work I have pointed to a clear trade-off when both events occur simultaneously, and I have shown how some individuals might cope with it. Molt-breeding overlap offers a unique opportunity to study life history evolution in both mechanistic and ecological aspects, given its variation in a wide range of organisms and environments

Variables included in the final GLMM model analysing the speed of: a) escape flight and b) normal flight.

<p>∞State: whether an individual was a moulter, a breeder or an overlapper; for post-hoc test please see text. For details on all variables included into each statistical model please see Statistical Analysis in text; variables with p>0.1 were not included in the final model.</p

Normalised feather mass (by feather length) of the 7^th primary for individuals in different states.

<p>Box and whisker plots show median, range, first and third quartiles. Filled circles indicate individual data points. Numbers indicate sample sizes.</p

Escape flight speed (m/s, mean ± SE) according to state (***p<0.0001).

<p>Numbers inside bars indicate sample sizes.</p

Wing load components.

<p>a) wing area (mm²) and b) body mass (g) for individuals in different states. Box and whisker plots show median, range, first and third quartiles. Filled circles indicate individual data points. Numbers indicate sample size.</p

The social nestwork: tree structure determines nest placement in Kenyan weaverbird colonies.

Group living is a life history strategy employed by many organisms. This strategy is often difficult to study because the exact boundaries of a group can be unclear. Weaverbirds present an ideal model for the study of group living, because their colonies occupy a space with discrete boundaries: a single tree. We examined one aspect of group living. nest placement, in three Kenyan weaverbird species: the Black-capped Weaver (Pseudonigrita cabanisi), Grey-capped Weaver (P. arnaudi) and White-browed Sparrow Weaver (Ploceropasser mahali). We asked which environmental, biological, and/or abiotic factors influenced their nest arrangement and location in a given tree. We used machine learning to analyze measurements taken from 16 trees and 516 nests outside the breeding season at the Mpala Research Station in Laikipia Kenya, along with climate data for the area. We found that tree architecture, number of nests per tree, and nest-specific characteristics were the main variables driving nest placement. Our results suggest that different Kenyan weaverbird species have similar priorities driving the selection of where a nest is placed within a given tree. Our work illustrates the advantage of using machine learning techniques to investigate biological questions

Selected observed variables and corresponding coefficients based on interpretability and Kaiser criterion for PCA analyses of Weaver birds nest arrangement.

<p>Selected observed variables and corresponding coefficients based on interpretability and Kaiser criterion for PCA analyses of Weaver birds nest arrangement.</p

Random Forest evaluation.

<p>Mean square-error (%IncMSE) and node purity (IncNodePurity) corresponding to the original variables when nest location is represented by nest height over tree height. dtru: distance to the trunk, tnest: total number of nests, cano: canopy size, Thei: tree height, dnest: distance to closes neighbour, birdsp: bird species, entr: entrance, DBH: diameter at breast height, nsize: nest size, Temp: temperature, widdi: wind direction, bran: branching pattern, condi: condition of the nest, tresp: tree species, use: whether in use or not, masEv: if the nest was part of a mass event.</p

Tree 5.

<p>Tree located at Mpala Research Station with colonies of both Grey-capped and black-capped weavers.</p

Random Forest models using three normalized variables as representations of nest location for weaver birds in Mpala Research Station.

<p>Random Forest models using three normalized variables as representations of nest location for weaver birds in Mpala Research Station.</p