Reproductive individuality of clonal fish raised in near-identical environments and its link to early-life behavioral individuality.

Recent studies have documented among-individual phenotypic variation that emerges in the absence of apparent genetic and environmental differences, but it remains an open question whether such seemingly stochastic variation has fitness consequences. We perform a life-history experiment with naturally clonal fish, separated directly after birth into near-identical (i.e., highly standardized) environments, quantifying 2522 offspring from 152 broods over 280 days. We find that (i) individuals differ consistently in the size of offspring and broods produced over consecutive broods, (ii) these differences are observed even when controlling for trade-offs between brood size, offspring size and reproductive onset, indicating individual differences in life-history productivity and (iii) early-life behavioral individuality in activity and feeding patterns, with among-individual differences in feeding being predictive of growth, and consequently offspring size. Thus, our study provides experimental evidence that even when minimizing genetic and environmental differences, systematic individual differences in life-history measures and ultimately fitness can emerge.

Leveraging big data to uncover the eco-evolutionary factors shaping behavioural development.

Mapping the eco-evolutionary factors shaping the development of animals' behavioural phenotypes remains a great challenge. Recent advances in 'big behavioural data' research-the high-resolution tracking of individuals and the harnessing of that data with powerful analytical tools-have vastly improved our ability to measure and model developing behavioural phenotypes. Applied to the study of behavioural ontogeny, the unfolding of whole behavioural repertoires can be mapped in unprecedented detail with relative ease. This overcomes long-standing experimental bottlenecks and heralds a surge of studies that more finely define and explore behavioural-experiential trajectories across development. In this review, we first provide a brief guide to state-of-the-art approaches that allow the collection and analysis of high-resolution behavioural data across development. We then outline how such approaches can be used to address key issues regarding the ecological and evolutionary factors shaping behavioural development: developmental feedbacks between behaviour and underlying states, early life effects and behavioural transitions, and information integration across development.

Developmental feedbacks and the emergence of individuality.

Behavioural individuality is a hallmark of animal life, with major consequences for fitness, ecology, and evolution. One of the most widely invoked explanations for this variation is that feedback loops between an animal's behaviour and its state (e.g. physiology, informational state, social rank, etc.) trigger and shape the development of individuality. Despite their often-cited importance, however, little is known about the ultimate causes of such feedbacks. Expanding on a previously employed model of adaptive behavioural development under uncertainty, we find that (i) behaviour-state feedbacks emerge as a direct consequence of adaptive behavioural development in particular selective environments and (ii) that the sign of these feedbacks, and thus the consequences for the development of behavioural individuality, can be directly predicted by the shape of the fitness function, with increasing fitness benefits giving rise to positive feedbacks and trait divergence and decreasing fitness benefits leading to negative feedbacks and trait convergence. Our findings provide a testable explanatory framework for the emergence of developmental feedbacks driving individuality and suggest that such feedbacks and their associated patterns of behavioural diversity are a direct consequence of adaptive behavioural development in particular selective environments.

Social interaction can select for reduced ability.

Animals, including humans, differ in a wide range of physical and cognitive abilities ranging from measures of running speed and physical strength to learning ability and intelligence. We consider the evolution of ability when individuals interact pairwise over their contribution to a common good. In this interaction, the contribution of each is assumed to be the best given their own ability and the contribution of their partner. Since there is a tendency for individuals to partially compensate for a low contribution by their partner, low-ability individuals can do well. As a consequence, for benefit and cost structures for which individuals have a strong response to partner's contribution, there can be selection for reduced ability. Furthermore, there can be disruptive selection on ability, leading to a bimodal distribution of ability under some modes of inheritance.

The emergence and development of behavioral individuality in clonal fish.

Behavioral individuality is a ubiquitous phenomenon in animal populations, yet the origins and developmental trajectories of individuality, especially very early in life, are still a black box. Using a high-resolution tracking system, we mapped the behavioral trajectories of genetically identical fish (Poecilia formosa), separated immediately after birth into identical environments, over the first 10 weeks of their life at 3 s resolution. We find that (i) strong behavioral individuality is present at the very first day after birth, (ii) behavioral differences at day 1 of life predict behavior up to at least 10 weeks later, and (iii) patterns of individuality strengthen gradually over developmental time. Our results establish a null model for how behavioral individuality can develop in the absence of genetic and environmental variation and provide experimental evidence that later-in-life individuality can be strongly shaped by factors pre-dating birth like maternal provisioning, epigenetics and pre-birth developmental stochasticity.

Avoiding costly mistakes in groups: The evolution of error management in collective decision making.

Individuals continuously have to balance the error costs of alternative decisions. A wealth of research has studied how single individuals navigate this, showing that individuals develop response biases to avoid the more costly error. We, however, know little about the dynamics in groups facing asymmetrical error costs and when social influence amplifies either safe or risky behavior. Here, we investigate this by modeling the decision process and information flow with a drift-diffusion model extended to the social domain. In the model individuals first gather independent personal information; they then enter a social phase in which they can either decide early based on personal information, or wait for additional social information. We combined the model with an evolutionary algorithm to derive adaptive behavior. We find that under asymmetric costs, individuals in large cooperative groups do not develop response biases because such biases amplify at the collective level, triggering false information cascades. Selfish individuals, however, undermine the group's performance for their own benefit by developing higher response biases and waiting for more information. Our results have implications for our understanding of the social dynamics in groups facing asymmetrical errors costs, such as animal groups evading predation or police officers holding a suspect at gunpoint.

Pooling decisions decreases variation in response bias and accuracy.

Decision makers in contexts as diverse as medical, judicial, and political decision making are known to differ substantially in response bias and accuracy, and these differences are a major factor undermining the reliability and fairness of the respective decision systems. Using theoretical modeling and empirical testing across five domains, we show that collective systems based on pooling decisions robustly overcome this important but as of now unresolved problem of experts' heterogeneity. In breast and skin cancer diagnostics and fingerprint analysis, we find that pooling the decisions of five experts reduces the variation in sensitivity among decision makers by 52%, 54%, and 41%, respectively. Similar reductions are achieved for specificity and response bias, and in other domains. Thus, although outcomes in individual decision systems are highly variable and at the mercy of individual decision makers, collective systems based on pooling decrease this variation, thereby promoting reliability, fairness, and possibly even trust.

Durable Complete Remission and Long-Term Survival in FDG-PET Staged Patients with Stage III Follicular Lymphoma, Treated with Wide-Field Radiation Therapy.

Advanced-stage follicular lymphoma (FL) is generally considered incurable with conventional systemic therapies, but historic series describe long-term disease-free survival in stage III disease treated with wide-field radiation therapy (WFRT), encompassing all known disease sites. We report outcomes for patients staged with 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) and treated with CT-planned WFRT, given as either comprehensive lymphatic irradiation (CLI) or total nodal irradiation (TNI). This analysis of a prospective cohort includes PET-staged patients given curative-intent WFRT as a component of initial therapy, or as sole treatment for stage III FL. Thirty-three PET-staged patients with stage III FL received WFRT to 24-30Gy between 1999 and 2017. Fifteen patients also received planned systemic therapy (containing rituximab in 11 cases) as part of their primary treatment. At 10 years, overall survival and freedom from progression (FFP) were 100% and 75%, respectively. None of the 11 rituximab-treated patients have relapsed. Nine relapses occurred; seven patients required treatment, and all responded to salvage therapies. A single death occurred at 16 years. The principal acute toxicity was transient hematologic; one patient had residual grade two toxicity at one year. With FDG-PET staging, most patients with stage III FL experience prolonged FFP after WFRT, especially when combined with rituximab.

Quorums enable optimal pooling of independent judgements in biological systems.

Collective decision-making is ubiquitous, and majority-voting and the Condorcet Jury Theorem pervade thinking about collective decision-making. Thus, it is typically assumed that majority-voting is the best possible decision mechanism, and that scenarios exist where individually-weak decision-makers should not pool information. Condorcet and its applications implicitly assume that only one kind of error can be made, yet signal detection theory shows two kinds of errors exist, 'false positives' and 'false negatives'. We apply signal detection theory to collective decision-making to show that majority voting is frequently sub-optimal, and can be optimally replaced by quorum decision-making. While quorums have been proposed to resolve within-group conflicts, or manage speed-accuracy trade-offs, our analysis applies to groups with aligned interests undertaking single-shot decisions. Our results help explain the ubiquity of quorum decision-making in nature, relate the use of sub- and super-majority quorums to decision ecology, and may inform the design of artificial decision-making systems. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Naturally clonal vertebrates are an untapped resource in ecology and evolution research.

Science requires replication. The development of many cloned or isogenic model organisms is a testament to this. But researchers are reluctant to use these traditional animal model systems for certain questions in evolution or ecology research, because of concerns over relevance or inbreeding. It has largely been overlooked that there are a substantial number of vertebrate species that reproduce clonally in nature. Here we highlight how use of these naturally evolved, phenotypically complex animals can push the boundaries of traditional experimental design and contribute to answering fundamental questions in the fields of ecology and evolution.

The effect of tyrosine kinase inhibitor interruption and interferon use on pregnancy outcomes and long-term disease control in chronic myeloid leukemia.

The management of CML in pregnancy is challenging with the need to balance disease control against potential teratogenic effects of TKI therapy. In this multi-center case-cohort study of 16 women in chronic phase, CML ceased TKI treatment pre- or post-conception during their first pregnancy. Thirteen patients were on imatinib; 9 ceased their TKI prior to conception and 7 ceased at pregnancy confirmation. Twelve patients had achieved either MMR or better at time of TKI cessation. Eleven women lost MMR during pregnancy and two patients lost CHR. Fourteen women reestablished MMR on TKI recommenced. The depth molecular response prior to conception appeared to correlate well with restoration of disease control on TKI recommencement though duration of MMR did not appear to be as important. While interruption of TKI treatment for pregnancy usually leads to loss of molecular response, loss of hematological response is uncommon and disease control is reestablished with resumption of therapy in the majority of women.

Target site specificity and in vivo complexity of the mammalian arginylome.

Protein arginylation mediated by arginyltransferase ATE1 is a key regulatory process essential for mammalian embryogenesis, cell migration, and protein regulation. Despite decades of studies, very little is known about the specificity of ATE1-mediated target site recognition. Here, we used in vitro assays and computational analysis to dissect target site specificity of mouse arginyltransferases and gain insights into the complexity of the mammalian arginylome. We found that the four ATE1 isoforms have different, only partially overlapping target site specificity that includes more variability in the target residues than previously believed. Based on all the available data, we generated an algorithm for identifying potential arginylation consensus motif and used this algorithm for global prediction of proteins arginylated in vivo on the N-terminal D and E. Our analysis reveals multiple proteins with potential ATE1 target sites and expand our understanding of the biological complexity of the intracellular arginylome.

Using a robotic fish to investigate individual differences in social responsiveness in the guppy.

Responding towards the actions of others is one of the most important behavioural traits whenever animals of the same species interact. Mutual influences among interacting individuals may modulate the social responsiveness seen and thus make it often difficult to study the level and individual variation in responsiveness. Here, open-loop biomimetic robots that provide standardized, non-interactive social cues can be a useful tool. These robots are not affected by the live animal's actions but are assumed to still represent valuable and biologically relevant social cues. As this assumption is crucial for the use of biomimetic robots in behavioural studies, we hypothesized (i) that meaningful social interactions can be assumed if live animals maintain individual differences in responsiveness when interacting with both a biomimetic robot and a live partner. Furthermore, to study the level of individual variation in social responsiveness, we hypothesized (ii) that individual differences should be maintained over the course of multiple tests with the robot. We investigated the response of live guppies (Poecilia reticulata) when allowed to interact either with a biomimetic open-loop-controlled fish robot-'Robofish'-or with a live companion. Furthermore, we investigated the responses of live guppies when tested three times with Robofish. We found that responses of live guppies towards Robofish were weaker compared with those of a live companion, most likely as a result of the non-interactive open-loop behaviour of Robofish. Guppies, however, were consistent in their individual responses between a live companion and Robofish, and similar individual differences in response towards Robofish were maintained over repeated testing even though habituation to the test environment was detectable. Biomimetic robots like Robofish are therefore a useful tool for the study of social responsiveness in guppies and possibly other small fish species.

Spatial and topical imbalances in biodiversity research.

The rapid erosion of biodiversity is among the biggest challenges human society is facing. Concurrently, major efforts are in place to quantify changes in biodiversity, to understand the consequences for ecosystem functioning and human wellbeing, and to develop sustainable management strategies. Based on comprehensive bibliometric analyses covering 134,321 publications, we report systematic spatial biases in biodiversity-related research. Research is dominated by wealthy countries, while major research deficits occur in regions with disproportionately high biodiversity as well as a high share of threatened species. Similarly, core scientists, who were assessed through their publication impact, work primarily in North America and Europe. Though they mainly exchange and collaborate across locations of these two continents, the connectivity among them has increased with time. Finally, biodiversity-related research has primarily focused on terrestrial systems, plants, and the species level, and is frequently conducted in Europe and Asia by researchers affiliated with European and North American institutions. The distinct spatial imbalances in biodiversity research, as demonstrated here, must be filled, research capacity built, particularly in the Global South, and spatially-explicit biodiversity data bases improved, curated and shared.

Individuals fail to reap the collective benefits of diversity because of over-reliance on personal information.

Collective intelligence refers to the ability of groups to outperform individuals in solving cognitive tasks. Although numerous studies have demonstrated this effect, the mechanisms underlying collective intelligence remain poorly understood. Here, we investigate diversity in cue beliefs as a mechanism potentially promoting collective intelligence. In our experimental study, human groups observed a sequence of cartoon characters, and classified each character as a cooperator or defector based on informative and uninformative cues. Participants first made an individual decision. They then received social information consisting of their group members' decisions before making a second decision. Additionally, individuals reported their beliefs about the cues. Our results showed that individuals made better decisions after observing the decisions of others. Interestingly, individuals developed different cue beliefs, including many wrong ones, despite receiving identical information. Diversity in cue beliefs, however, did not predict collective improvement. Using simulations, we found that diverse collectives did provide better social information, but that individuals failed to reap those benefits because they relied too much on personal information. Our results highlight the potential of belief diversity for promoting collective intelligence, but suggest that this potential often remains unexploited because of over-reliance on personal information.

Behavioural individuality in clonal fish arises despite near-identical rearing conditions.

Behavioural individuality is thought to be caused by differences in genes and/or environmental conditions. Therefore, if these sources of variation are removed, individuals are predicted to develop similar phenotypes lacking repeatable individual variation. Moreover, even among genetically identical individuals, direct social interactions are predicted to be a powerful factor shaping the development of individuality. We use tightly controlled ontogenetic experiments with clonal fish, the Amazon molly (Poecilia formosa), to test whether near-identical rearing conditions and lack of social contact dampen individuality. In sharp contrast to our predictions, we find that (i) substantial individual variation in behaviour emerges among genetically identical individuals isolated directly after birth into highly standardized environments and (ii) increasing levels of social experience during ontogeny do not affect levels of individual behavioural variation. In contrast to the current research paradigm, which focuses on genes and/or environmental drivers, our findings suggest that individuality might be an inevitable and potentially unpredictable outcome of development.

Boosting medical diagnostics by pooling independent judgments.

Collective intelligence refers to the ability of groups to outperform individual decision makers when solving complex cognitive problems. Despite its potential to revolutionize decision making in a wide range of domains, including medical, economic, and political decision making, at present, little is known about the conditions underlying collective intelligence in real-world contexts. We here focus on two key areas of medical diagnostics, breast and skin cancer detection. Using a simulation study that draws on large real-world datasets, involving more than 140 doctors making more than 20,000 diagnoses, we investigate when combining the independent judgments of multiple doctors outperforms the best doctor in a group. We find that similarity in diagnostic accuracy is a key condition for collective intelligence: Aggregating the independent judgments of doctors outperforms the best doctor in a group whenever the diagnostic accuracy of doctors is relatively similar, but not when doctors' diagnostic accuracy differs too much. This intriguingly simple result is highly robust and holds across different group sizes, performance levels of the best doctor, and collective intelligence rules. The enabling role of similarity, in turn, is explained by its systematic effects on the number of correct and incorrect decisions of the best doctor that are overruled by the collective. By identifying a key factor underlying collective intelligence in two important real-world contexts, our findings pave the way for innovative and more effective approaches to complex real-world decision making, and to the scientific analyses of those approaches.

The making of winners (and losers): how early dominance interactions determine adult social structure in a clonal fish.

Across a wide range of animal taxa, winners of previous fights are more likely to keep winning future contests, just as losers are more likely to keep losing. At present, such winner and loser effects are considered to be fairly transient. However, repeated experiences with winning and/or losing might increase the persistence of these effects, generating long-lasting consequences for social structure. To test this, we exposed genetically identical individuals of a clonal fish, the Amazon molly (Poecilia formosa), to repeated winning and/or losing dominance interactions during the first two months of their life. We subsequently investigated whether these experiences affected the fish's ability to achieve dominance in a hierarchy five months later after sexual maturity, a major life-history transition. Individuals that had only winning interactions early in life consistently ranked at the top of the hierarchy. Interestingly, individuals with only losing experience tended to achieve the middle dominance rank, whereas individuals with both winning and losing experiences generally ended up at the bottom of the hierarchy. In addition to demonstrating that early social interactions can have dramatic and long-lasting consequences for adult social behaviour and social structure, our work also shows that higher cumulative winning experience early in life can counterintuitively give rise to lower social rank later in life.