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Many marine ecosystems have undergone ‘regime shifts’, i.e. abrupt reorganizations across trophic levels. Establishing whether these constitute shifts between alternative stable states is of key importance for the prospects of ecosystem recovery and for management. We show how mechanisms underlying alternative stable states caused by predator–prey interactions can be revealed in field data, using analyses guided by theory on size-structured community dynamics. This is done by combining data on individual performance (such as growth and fecundity) with information on population size and prey availability. We use Atlantic cod (Gadus morhua) and their prey in the Baltic Sea as an example to discuss and distinguish two types of mechanisms, ‘cultivation-depensation’ and ‘overcompensation’, that can cause alternative stable states preventing the recovery of overexploited piscivorous fish populations. Importantly, the type of mechanism can be inferred already from changes in the predators' body growth in different life stages. Our approach can thus be readily applied to monitored stocks of piscivorous fish species, for which this information often can be assembled. Using this tool can help resolve the causes of catastrophic collapses in marine predatory–prey systems and guide fisheries managers on how to successfully restore collapsed piscivorous fish stocks.

The Mediterranean Region is considered one of the areas most exposed to climate warming, with artificial lakes and coastal lagoons representing particularly vulnerable ecosystems, that provide essential goods and services. Amongst the extreme events linked to warming, heatwaves are of growing concern, yet their ecological effects on the functioning of Mediterranean aquatic systems remain poorly investigated. We present a methodological framework designed by the Project “ a warmer Future world: effects on plankton commUnities and paThogens in Mediterranean vUlneRable Ecosystems (FUTURE) “ to study how natural plankton communities respond to abrupt and sustained thermal stress. The approach targets on entire plankton communities, from bacteria to zooplankton, integrates laboratory experiments and field monitoring activities and combines classical techniques with molecular tools to capture changes in biodiversity, food web size-structure and the occurrence of potentially pathogenic and antibiotic-resistant bacteria. We selected two diverse aquatic ecosystems in the western Mediterranean as case studies: an artificial lake, an important source for drinking water and a coastal lagoon vital for fishery, both of high ecological and economic importance. By applying controlled experimental simulations with ecological relevance, the framework provides a replicable approach to investigate plankton community-level responses to heatwaves. This methodological contribution provides a comparative framework for vulnerable Mediterranean ecosystems and promotes standardised approaches to assess the impacts of extreme climate-driven events. The scalable and reproducible protocol presented here fills a critical regional knowledge gap and will support the effective management of climate-sensitive aquatic ecosystems.

Ecological disturbances are often hypothesized to alter community assembly processes that influence variation in community composition (β‐diversity). Disturbance can cause convergence in community composition (low β‐diversity) by increasing niche selection of disturbance‐tolerant species. Alternatively, disturbance can cause divergence in community composition (high β‐diversity) by increasing habitat filtering across environmental gradients. However, because disturbance may also influence β‐diversity through random sampling effects owing to changes in the number of individuals in local communities (community size) or abundances in the regional species pool, observed patterns of β‐diversity alone cannot be used to unambiguously discern the relative importance of community assembly mechanisms. We compared β‐diversity of woody plants and inferred assembly mechanisms among unburned forests and forests managed with prescribed fires in the Missouri Ozarks, USA. Using a null‐model approach, we compared how environmental gradients influenced β‐diversity after controlling for differences in local community size and regional species abundances between unburned and burned landscapes. Observed β‐diversity was higher in burned landscapes. However, this pattern disappeared or reversed after controlling for smaller community size in burned landscapes. β‐diversity was higher than expected by chance in both landscapes, indicating an important role for processes that create clumped species distributions. Moreover, fire appeared to decrease clumping of species at broader spatial scales, suggesting homogenization of community composition through niche selection of disturbance‐tolerant species. Environmental variables, however, explained similar amounts of variation in β‐diversity in both landscapes, suggesting that disturbance did not alter the relative importance of habitat filtering. Our results indicate that contingent responses of communities to fire reflect a combination of fire‐induced changes in local community size and scale‐dependent effects of fire on species clumping across landscapes. Synthesis. Although niche‐based mechanisms of community assembly are often invoked to explain changes in community composition following disturbance, our results suggest that these changes also arise through random sampling effects owing to the influence of disturbance on community size. Comparative studies of these processes across disturbed ecosystems will provide important insights into the ecological conditions that determine when disturbance alters the interplay of deterministic and stochastic processes in natural and human‐modified landscapes.

Understanding worldwide patterns of language diversity has long been a goal for evolutionary scientists, linguists and philosophers. Research over the past decade has suggested that linguistic diversity may result from differences in the social environments in which languages evolve. Specifically, recent work found that languages spoken in larger communities typically have more systematic grammatical structures. However, in the real world, community size is confounded with other social factors such as network structure and the number of second languages learners in the community, and it is often assumed that linguistic simplification is driven by these factors instead. Here, we show that in contrast to previous assumptions, community size has a unique and important influence on linguistic structure. We experimentally examine the live formation of new languages created in the laboratory by small and larger groups, and find that larger groups of interacting participants develop more systematic languages over time, and do so faster and more consistently than small groups. Small groups also vary more in their linguistic behaviours, suggesting that small communities are more vulnerable to drift. These results show that community size predicts patterns of language diversity, and suggest that an increase in community size might have contributed to language evolution.

A bacterium was once a component of the ancestor of all eukaryotic cells, and much of the human genome originated in microorganisms. Today, all vertebrates harbour large communities of microorganisms (microbiota), particularly in the gut, and at least 20% of the small molecules in human blood are products of the microbiota. Changing human lifestyles and medical practices are disturbing the content and diversity of the microbiota, while simultaneously reducing our exposures to the so-called old infections and to organisms from the natural environment with which human beings co-evolved. Meanwhile, population growth is increasing the exposure of human beings to novel pathogens, particularly the crowd infections that were not part of our evolutionary history. Thus some microbes have co-evolved with human beings and play crucial roles in our physiology and metabolism, whereas others are entirely intrusive. Human metabolism is therefore a tug-of-war between managing beneficial microbes, excluding detrimental ones, and channelling as much energy as is available into other essential functions (eg, growth, maintenance, reproduction). This tug-of-war shapes the passage of each individual through life history decision nodes (eg, how fast to grow, when to mature, and how long to live).

A heterogeneous mean-field SIRS infectious disease stochastic dynamic model with population size is established, the main period of the model and the average extinction time of the disease are obtained, and the critical community size threshold of the model is obtained by using the relationship between the main period and average extinction time. The results show that: when average degrees of networks are equal but degree distributions differ, or vice versa, the thresholds for critical community size vary significantly. Population size is an important parameter affecting the extinction of stochastic infectious diseases, and this result can provide a theoretical basis for the control and eradication of infectious diseases.

The present study investigated the link between the sizes of the Chinese community to the health of Chinese seniors in Canada. A secondary data analysis of survey data from a representative sample of 2,272 Chinese older adults aged 55 and over was conducted. Hierarchical regression analyses were performed to assess the effects of the size of Chinese communities in Chinese seniors’ health. Chinese seniors residing in the community with a small Chinese population reported better physical and mental health than the Chinese seniors residing in communities with a larger Chinese population. The findings were contrary to expectations that health of Chinese seniors should be higher in cities with large Chinese communities. These findings raise new questions for future investigations into the dynamics and impact of ethnic community size, and the importance of studying intragroup differences within ethno-cultural groups to better understand health disparities in ethnic groups.

Digital networks, mobile devices, and the possibility of mining the ever-increasing amount of digital traces that we leave behind in our daily activities are changing the way we can approach the study of human and social interactions. Large-scale datasets, however, are mostly available for collective and statistical behaviors, at coarse granularities, while high-resolution data on person-to-person interactions are generally limited to relatively small groups of individuals. Here we present a scalable experimental framework for gathering real-time data resolving face-to-face social interactions with tunable spatial and temporal granularities. We use active Radio Frequency Identification (RFID) devices that assess mutual proximity in a distributed fashion by exchanging low-power radio packets. We analyze the dynamics of person-to-person interaction networks obtained in three high-resolution experiments carried out at different orders of magnitude in community size. The data sets exhibit common statistical properties and lack of a characteristic time scale from 20 seconds to several hours. The association between the number of connections and their duration shows an interesting super-linear behavior, which indicates the possibility of defining super-connectors both in the number and intensity of connections. Taking advantage of scalability and resolution, this experimental framework allows the monitoring of social interactions, uncovering similarities in the way individuals interact in different contexts, and identifying patterns of super-connector behavior in the community. These results could impact our understanding of all phenomena driven by face-to-face interactions, such as the spreading of transmissible infectious diseases and information.

The dynamical process of epidemic spreading has drawn much attention of the complex network community. In the network paradigm, diseases spread from one person to another through the social ties amongst the population. There are a variety of factors that govern the processes of disease spreading on the networks. A common but not negligible factor is people's reaction to the outbreak of epidemics. Such reaction can be related information dissemination or self-protection. In this work, we explore the interactions between disease spreading and population response in terms of information diffusion and individuals' alertness. We model the system by mapping multiplex networks into two-layer networks and incorporating individuals' risk awareness, on the assumption that their response to the disease spreading depends on the size of the community they belong to. By comparing the final incidence of diseases in multiplex networks, we find that there is considerable mitigation of diseases spreading for full phase of spreading speed when individuals' protection responses are introduced. Interestingly, the degree of community overlap between the two layers is found to be critical factor that affects the final incidence. We also analyze the consequences of the epidemic incidence in communities with different sizes and the impacts of community overlap between two layers. Specifically, as the diseases information makes individuals alert and take measures to prevent the diseases, the effective protection is more striking in small community. These phenomena can be explained by the multiplexity of the networked system and the competition between two spreading processes.

We examine whether electoral preferences depend on a community's population size by studying post-Second World War Baden-Württemberg in Southwest Germany. Our identification strategy exploits the fact that the French administration zone prohibited German expellees from entering, contrary to the contiguous American zone. Population size positively predicts voting for the Social Democrats (the party advocating substantial government involvement in practically all domains) and negatively for the Christian Democrats (the small-government party advocating free-market policies). Results are neither driven by pre-existing voting patterns, religious compositions, and location- and time-specific unobservables, nor other measurable cultural, demographic, economic, or political characteristics. Alternative explanations pertaining to expellee voting behaviour or a backlash of natives against expellees appear unlikely – population size prevails as a predominant voting predictor.