Societal determinants of flood-induced displacement.

What explains human consequences of weather-related disaster? Here, we explore how core socioeconomic, political, and security conditions shape flood-induced displacement worldwide since 2000. In-sample regression analysis shows that extreme displacement levels are more likely in contexts marked by low national income levels, nondemocratic political systems, high local economic activity, and prevalence of armed conflict. The analysis also reveals large residual differences across continents, where flood-induced displacement in the Global South often is much more widespread than direct human exposure measures would suggest. However, these factors have limited influence on our ability to accurately predict flood displacement on new data, pointing to important, hard-to-operationalize heterogeneity in flood impacts across contexts and critical data limitations. Although results are consistent with an interpretation that the sustainable development agenda is beneficial for disaster risk reduction, better data on societal consequences of natural hazards are critically needed to support evidence-based decision-making.

A Monte Carlo analysis of false inference in spatial conflict event studies.

Spatial event data is heavily used in contemporary research on political violence. Such data are oftentimes mapped onto grid-cells or administrative regions to draw inference about the determinants of conflict intensity. This setup can identify geographic determinants of violence, but is also prone to methodological issues. Problems resulting from spatial aggregation and dependence have been raised in methodological studies, but are rarely accounted for in applied research. As a consequence, we know little about the empirical relevance of these general problems and the trustworthiness of a popular research design. We address these questions by simulating conflict events based on spatial covariates from seven high-profile conflicts. We find that standard designs fail to deliver reliable inference even under ideal conditions at alarming rates. We also test a set of statistical remedies which strongly improve the results: Controlling for the geographic area of spatial units eliminates an important source of spurious correlation. In time-series analyses, the same result can be achieved with unit-level fixed effects. Under outcome diffusion, spatial lag models with area controls produce most reliable inference. When those are computationally intractable, geographically larger aggregations lead to similar improvements. Generally, all analyses should be performed at two separate levels of geographic aggregation. To facilitate future research into geographic methods, we release the Simple Conflict Event Generator (SCEG) developed for this analysis.

How indiscriminate violence fuels conflicts between groups: Evidence from Kenya.

Armed conflicts frequently fuel tensions between groups. The "cognitive perspective" of group identification offers a possible explanation, but is tacit on exact causal pathways. We predict that indiscriminate violence by armed actors induces fear of future attacks which in turn leads to prejudice, enhanced in-group cohesion, and calls for segregation. Selective violence does not have these effects. Relying on panel surveys conducted in Nairobi and Mombasa during the violent Kenyan elections in the Summer of 2017, we find evidence for the predicted effects among Christians in 2-way Fixed Effects estimation and an endorsement experiment.

Climatic conditions are weak predictors of asylum migration.

Recent research suggests that climate variability and change significantly affect forced migration, within and across borders. Yet, migration is also informed by a range of non-climatic factors, and current assessments are impeded by a poor understanding of the relative importance of these determinants. Here, we evaluate the eligibility of climatic conditions relative to economic, political, and contextual factors for predicting bilateral asylum migration to the European Union-form of forced migration that has been causally linked to climate variability. Results from a machine-learning prediction framework reveal that drought and temperature anomalies are weak predictors of asylum migration, challenging simplistic notions of climate-driven refugee flows. Instead, core contextual characteristics shape latent migration potential whereas political violence and repression are the most powerful predictors of time-varying migration flows. Future asylum migration flows are likely to respond much more to political changes in vulnerable societies than to climate change.

Chimpanzees behave prosocially in a group-specific manner.

Chimpanzees act cooperatively in the wild, but whether they afford benefits to others, and whether their tendency to act prosocially varies across communities, is unclear. Here, we show that chimpanzees from neighboring communities provide valuable resources to group members at personal cost, and that the magnitude of their prosocial behavior is group specific. Provided with a resource-donation experiment allowing free (partner) choice, we observed an increase in prosocial acts across the study period in most of the chimpanzees. When group members could profit (test condition), chimpanzees provided resources more frequently and for longer durations than when their acts produced inaccessible resources (control condition). Strikingly, chimpanzees' prosocial behavior was group specific, with more socially tolerant groups acting more prosocially. We conclude that chimpanzees may purposely behave prosocially toward group members, and that the notion of group-specific sociality in nonhuman animals should crucially inform discussions on the evolution of prosocial behavior.

The development of human social learning across seven societies.

Social information use is a pivotal characteristic of the human species. Avoiding the cost of individual exploration, social learning confers substantial fitness benefits under a wide variety of environmental conditions, especially when the process is governed by biases toward relative superiority (e.g., experts, the majority). Here, we examine the development of social information use in children aged 4-14 years (n = 605) across seven societies in a standardised social learning task. We measured two key aspects of social information use: general reliance on social information and majority preference. We show that the extent to which children rely on social information depends on children's cultural background. The extent of children's majority preference also varies cross-culturally, but in contrast to social information use, the ontogeny of majority preference follows a U-shaped trajectory across all societies. Our results demonstrate both cultural continuity and diversity in the realm of human social learning.

Saving Human Lives: What Complexity Science and Information Systems can Contribute.

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.

Chimpanzees (Pan troglodytes) flexibly adjust their behaviour in order to maximize payoffs, not to conform to majorities.

Chimpanzees have been shown to be adept learners, both individually and socially. Yet, sometimes their conservative nature seems to hamper the flexible adoption of superior alternatives, even to the extent that they persist in using entirely ineffective strategies. In this study, we investigated chimpanzees' behavioural flexibility in two different conditions under which social animals have been predicted to abandon personal preferences and adopt alternative strategies: i) under influence of majority demonstrations (i.e. conformity), and ii) in the presence of superior reward contingencies (i.e. maximizing payoffs). Unlike previous nonhuman primate studies, this study disentangled the concept of conformity from the tendency to maintain one's first-learned strategy. Studying captive (n=16) and semi-wild (n=12) chimpanzees in two complementary exchange paradigms, we found that chimpanzees did not abandon their behaviour in order to match the majority, but instead remained faithful to their first-learned strategy (Study 1a and 1b). However, the chimpanzees' fidelity to their first-learned strategy was overridden by an experimental upgrade of the profitability of the alternative strategy (Study 2). We interpret our observations in terms of chimpanzees' relative weighing of behavioural options as a function of situation-specific trade-offs. More specifically, contrary to previous findings, chimpanzees in our study abandoned their familiar behaviour to maximize payoffs, but not to conform to a majority.

Great apes infer others' goals based on context.

In previous studies claiming to demonstrate that great apes understand the goals of others, the apes could potentially have been using subtle behavioral cues present during the test to succeed. In the current studies, we ruled out the use of such cues by making the behavior of the experimenter identical in the test phase of both the experimental and control conditions; the only difference was the preceding "context." In the first study, apes interpreted a human's ambiguous action as having the underlying goal of opening a box, or not, based on that human's previous actions with similar boxes. In the second study, chimpanzees learned that when a human stood up she was going to go get food for them, but when a novel, unexpected event happened, they changed their expectation-presumably based on their understanding that this new event led the human to change her goal. These studies suggest that great apes do not need concurrent behavioral cues to infer others' goals, but can do so from a variety of different types of cues-even cues displaced in time.