Decrease in social cohesion in a colonial seabird under a perturbation regime

Seabird's cry: repertoire and vocal expression of contextual valence in the little auk (Alle alle)

Many seabird species breed in colonies counting up to hundreds of thousands of individuals. Life in such crowded colonies might require special coding-decoding systems to reliably convey information through acoustic cues. This can include, for example, developing complex vocal repertoires and adjusting the properties of their vocal signals to communicate behavioural contexts, and thus regulate social interactions with their conspecifics. We studied vocalisations produced by the little auk (Alle alle)-a highly vocal, colonial seabird-over mating and incubation periods on the SW coast of Svalbard. Using passive acoustic recordings registered in a breeding colony, we extracted eight vocalisation types: single call, clucking, classic call, low trill, short call, short-trill, terror, and handling vocalisation. Calls were grouped by production context (based on the typically associated behaviour), to which a valence (positive vs negative) was later attributed, when possible, according to fitness threats, i.e. predator or human presence (negative) and promoters, i.e. interaction with a partner (positive). The effect of the putative valence on eight selected frequency and duration variables was then investigated. The putative contextual valence significantly affected the acoustic properties of the calls. Calls assigned positive valence had higher fundamental frequency and spectral centre of gravity as well as shorter sound duration than these assigned negative valence. These results indicate that the little auk's vocal communication system may facilitate expression of complex behavioural contexts, and seems to include vocal plasticity within vocalisation types-however, more data are necessary to better understand this effect and possible interplays of other factors.

Social copying drives a tipping point for nonlinear population collapse

Sudden changes in populations are ubiquitous in ecological systems, especially under perturbations. The agents of global change may increase the frequency and severity of anthropogenic perturbations, but complex populations' responses hamper our understanding of their dynamics and resilience. Furthermore, the long-term environmental and demographic data required to study those sudden changes are rare. Fitting dynamical models with an artificial intelligence algorithm to population fluctuations over 40 y in a social bird reveals that feedback in dispersal after a cumulative perturbation drives a population collapse. The collapse is well described by a nonlinear function mimicking social copying, whereby dispersal made by a few individuals induces others to leave the patch in a behavioral cascade for decision-making to disperse. Once a threshold for deterioration of the quality of the patch is crossed, there is a tipping point for a social response of runaway dispersal corresponding to social copying feedback. Finally, dispersal decreases at low population densities, which is likely due to the unwillingness of the more philopatric individuals to disperse. In providing the evidence of copying for the emergence of feedback in dispersal in a social organism, our results suggest a broader impact of self-organized collective dispersal in complex population dynamics. This has implications for the theoretical study of population and metapopulation nonlinear dynamics, including population extinction, and managing of endangered and harvested populations of social animals subjected to behavioral feedback loops.

Active breeding seabirds prospect alternative breeding colonies

Compared to other animal movements, prospecting by adult individuals for a future breeding site is commonly overlooked. Prospecting influences the decision of where to breed and has consequences on fitness and lifetime reproductive success. By analysing movements of 31 satellite- and GPS-tracked gull and tern populations belonging to 14 species in Europe and North America, we examined the occurrence and factors explaining prospecting by actively breeding birds. Prospecting in active breeders occurred in 85.7% of studied species, across 61.3% of sampled populations. Prospecting was more common in populations with frequent inter-annual changes of breeding sites and among females. These results contradict theoretical models which predict that prospecting is expected to evolve in relatively predictable and stable environments. More long-term tracking studies are needed to identify factors affecting patterns of prospecting in different environments and understand the consequences of prospecting on fitness at the individual and population level.

Modeling human migration driven by changing mindset, agglomeration, social ties, and the environment

Migration is an adaptation strategy to unfavorable conditions and is governed by a complex set of socio-economic and environmental drivers. Here we identified important drivers relatively underrepresented in many migration models-CHanging mindset, Agglomeration, Social ties, and the Environment (CHASE)-and asked: How does the interplay between these drivers influence transient dynamics and long-term outcomes of migration? We addressed this question by developing and analyzing a parsimonious Markov chain model. Our findings suggest that these drivers interact in nonlinear and complex ways. The system exhibits legacy effects, highlighting the importance of including migrants' changing priorities. The increased characteristic population size of the system counter-intuitively leads to fewer surviving cities, and this effect is mediated by how fast migrants change their mindsets and how strong the social ties are. Strong social ties result in less diverse populations across cities, but this effect is influenced by how many cities remain. To our knowledge, this is the first time that these drivers are incorporated in one coherent, mechanistic, parsimonious model and the effects of their interplay on migration systematically studied. The complex interplay underscores the need to incorporate these drivers into mechanistic migration models and implement such models for real-world cases.