The formation of avian montane diversity across barriers and along elevational gradients

Tropical mountains harbor exceptional concentrations of Earth’s biodiversity. In topographically complex landscapes, montane species typically inhabit multiple mountainous regions, but are absent in intervening lowland environments. Here we report a comparative analysis of genome-wide DNA polymorphism data for population pairs from eighteen Indo-Pacific bird species from the Moluccan islands of Buru and Seram and from across the island of New Guinea. We test how barrier strength and relative elevational distribution predict population differentiation, rates of historical gene flow, and changes in effective population sizes through time. We find population differentiation to be consistently and positively correlated with barrier strength and a species’ altitudinal floor. Additionally, we find that Pleistocene climate oscillations have had a dramatic influence on the demographics of all species but were most pronounced in regions of smaller geographic area. Surprisingly, even the most divergent taxon pairs at the highest elevations experience gene flow across barriers, implying that dispersal between montane regions is important for the formation of montane assemblages.

The Last Two Remaining Populations of the Critically Endangered Estuarine Pipefish Are Inbred and Not Genetically Distinct

The critically endangered estuarine pipefish, Syngnathus watermeyeri, is one of Africa’s rarest fish species and currently faces a significant risk of extinction. A combination of anthropogenic and natural factors threaten submerged macrophyte beds in the two South African estuaries (Bushmans and Kariega) in which the species’ only two known remaining populations reside. Here, we genotyped 34 pipefish from both populations using genome-wide data to determine whether the two estuaries harbour distinct genetic diversity, such that translocating individuals between them might improve the genetic health of both. Our results show that both populations are highly inbred, and no statistically significant genetic structure was found between them. Moreover, individuals both within and between estuaries were very closely related to each other. These results indicate that the remaining populations of the estuarine pipefish suffer from the adverse genetic effects of small population sizes. Even though recent surveys have estimated population sizes in the order of thousands of individuals, these may fluctuate considerably. Although the translocation of genetically similar individuals between habitats will not increase local genetic diversity, the creation of additional populations across the species’ historical range may be a suitable conservation strategy to prevent further loss of genetic diversity, and to minimise the overall extinction risk posed by environmental stochasticity.

Estimating the Effects of Public Health Measures by SEIR(MH) Model of COVID-19 Epidemic in Local Geographic Areas

The COVID-19 pandemic of 2020–21 has been a major challenge to public health systems worldwide. Mathematical models of epidemic are useful tools for assessment of the situation and for providing decision-making support for relevant authorities. We developed and implemented SEIR(MH) model that extends the conventional SEIR model with parameters that define public lockdown (the level and start of lockdown) and the medical system capacity to contain patients. Comparative modeling of four regions in Europe that have similar population sizes and age structures, but different public health systems, was performed: Baden-Württemberg, Lombardy, Belgium, and Switzerland. Modeling suggests that the most effective measure for controlling epidemic is early lockdown (exponential effect), followed by the number of available hospital beds (linear effect if the capacity is insufficient, with diminishing returns when the capacity is sufficient). Dynamic management of lockdown levels is likely to produce better outcomes than strict lockdown.

A Methodology for Exploiting Smart Prosumers’ Flexibility in a Bottom-Up Aggregation Process

The electrical power system is evolving in a way that requires new measures for ensuring its secure and reliable operation. Demand-side aggregation represents one of the more interesting ways to provide ancillary services by the coordinated management of a multitude of different distributed resources. In this framework, aggregators play the main role in ensuring the effectiveness of the coordinated action of the distributed resources, usually becoming mediators in the relation between distribution system operators and smart prosumers. The research project DEMAND recently introduced a new concept in demand-side aggregation by proposing a scheme without a central aggregator where prosumers can share and combine their flexibility with a collaboration–competition mechanism in a platform called Virtual Aggregation Environment (VAE). This paper, after a brief introduction to the DEMAND project, presents the algorithm for the day-ahead estimation of prosumers’ flexibility and the cooperative–competitive algorithm for the bottom-up aggregation. The first algorithm evaluates various couples of power variation and desired remuneration to be sent to the VAE for further elaborations and, for showing its potentiality, is applied to two different case studies: a passive user with only controllable loads and prosumers with controllable loads, photovoltaics and a storage system. The aggregation algorithm is instead discussed in detail, and its performance is evaluated for different population sizes.

Tracking Hunter-Gatherer Impact on Vegetation in Last Interglacial and Holocene Europe: Proxies and Challenges

We review palaeoenvironmental proxies and combinations of these relevant for understanding hunter-gatherer niche construction activities in pre-agricultural Europe. Our approach consists of two steps: (1) identify the possible range of hunter-gatherer impacts on landscapes based on ethnographic studies; (2) evaluate proxies possibly reflecting these impacts for both the Eemian (Last Interglacial, Middle Palaeolithic) and the Early–Middle Holocene (Mesolithic). We found these paleoenvironmental proxies were not able to unequivocally establish clear-cut differences between specific anthropogenic, climatic and megafaunal impacts for either time period in this area. We discuss case studies for both periods and show that published evidence for Mesolithic manipulation of landscapes is based on the interpretation of comparable data as available for the Last Interglacial. If one applies the ‘Mesolithic’ interpretation schemes to the Neanderthal record, three common niche construction activities can be hypothesised: vegetation burning, plant manipulation and impact on animal species presence and abundance. Our review suggests that as strong a case can be made for a Neanderthal impact on landscapes as for anthropogenic landscape changes during the Mesolithic, even though the Neanderthal evidence comes from only one high-resolution site complex. Further research should include attempts (e.g. by means of modelling studies) to establish whether hunter-gatherer impact on landscapes played out at a local level only versus at a larger scale during both time periods, while we also need to obtain comparative data on the population sizes of Last Interglacial and Holocene hunter-gatherers, as these are usually inferred to have differed significantly.

The relative strength of selection on modifiers of genetic architecture under migration load

Gene flow between populations adapting to differing local environmental conditions creates a "migration load" because individuals might disperse to habitats where their survival is low or because they might reproduce with locally maladapted individuals. The amount by which the mean relative population fitness is kept below one creates an opportunity for modifiers of the genetic architecture to spread due to selection. Prior work that separately considered modifiers changing dispersal or recombination rates, or altering dominance or epistasis, has typically focused on the direction of selection rather than its absolute magnitude. We here develop methods to determine the strength of selection on modifiers of the genetic architecture, including modifiers of the dispersal rate, after populations evolved local adaptation. We consider scenarios with up to five loci contributing to local adaptation and derive a matrix model for the deterministic spread of modifiers. We find that selection for modifiers of epistasis and dominance is stronger than selection for decreased recombination, and that selection for partial reductions in recombination are extremely weak, regardless of the number of loci contributing to local adaptation. The spread of modifiers for a reduction in dispersal depends on the number of loci, pre-existing epistasis and extent of migration load. We identify a novel effect, that modifiers of dominance are more strongly selected when they are unlinked to the locus that they modify. Overall, these results help explain population differentiation and reproductive isolation and provide a benchmark to compare selection on genetic architecture modifiers in finite population sizes and under demographic stochasticity.

The evolution of donations on scale-free networks during a COVID-19 breakout

Having a large number of timely donations during the early stages of a COVID-19 breakout would normally be considered rare. Donation is a special public goods game with zero yield, and it has the characteristics of prisoners’ dilemma. This paper discusses why timely donations in the early stages of COVID-19 occur. Based on the idea that donation is a strategy adopted by interconnected players on account of their understanding of the environment, donation-related populations are placed in social networks and the inter-correlation structure in the population is described by scale-free networks. Players in donation-related groups are of four types: donors, illegal beneficiaries, legal beneficiaries, and inactive people. We model the evolutionary game of donation on a scale-free network. Donors, illegal beneficiaries and inactive people learn and update strategies under the Fermi Update Rule, whereas the conversion between the legal beneficiaries and the other three strategies is determined by the environment surrounding the players. We study the evolution of cooperative action when the agglomeration coefficient, the parameters in the utility function, the selection strength parameter, the utility discount coefficient, the public goods discount coefficient and the initial state of the population in the scale-free network change. For population sizes of 50,100,150 and 200, we give the utility functions and the agglomeration coefficients for promoting cooperation. And we study the corresponding steady state and structural characteristics of the population. We identify the best ranges of selection strength K, the public goods discount coefficient α and the utility discount coefficient β for promoting cooperation at different population sizes. Furthermore, with an increase of the population size, the Donor Trap are found. At the same time, it is discovered that the initial state of the population has a great impact on the steady state; thus the Upper and Lower Triangle Phenomena are proposed. We also find that population size itself is also an important factor for promoting donation, pointing out the direction of efforts to further promote donation and achieve better social homeostasis under the donation model.

Tight Bounds on the Expected Runtime of a Standard Steady State Genetic Algorithm

Recent progress in the runtime analysis of evolutionary algorithms (EAs) has allowed the derivation of upper bounds on the expected runtime of standard steady-state genetic algorithms (GAs). These upper bounds have shown speed-ups of the GAs using crossover and mutation over the same algorithms that only use mutation operators (i.e., steady-state EAs) both for standard unimodal (i.e., OneMax) and multimodal (i.e., Jump) benchmark functions. The bounds suggest that populations are beneficial to the GA as well as higher mutation rates than the default 1/n rate. However, making rigorous claims was not possible because matching lower bounds were not available. Proving lower bounds on crossover-based EAs is a notoriously difficult task as it is hard to capture the progress that a diverse population can make. We use a potential function approach to prove a tight lower bound on the expected runtime of the (2+1) GA for OneMax for all mutation rates c/n with $$c < 1.422$$ c < 1.422 . This provides the last piece of the puzzle that completes the proof that larger population sizes improve the performance of the standard steady-state GA for OneMax for various mutation rates, and it proves that the optimal mutation rate for the (2+1) GA on OneMax is $$(\sqrt{97}-5)/(4n) \approx 1.2122/n$$ ( 97 - 5 ) / ( 4 n ) ≈ 1.2122 / n .

Response of an Afro-Palearctic bird migrant to glaciation cycles

Migration allows animals to exploit spatially separated and seasonally available resources at a continental to global scale. However, responding to global climatic changes might prove challenging, especially for long-distance intercontinental migrants. During glacial periods, when conditions became too harsh for breeding in the north, avian migrants have been hypothesized to retract their distribution to reside within small refugial areas. Here, we present data showing that an Afro-Palearctic migrant continued seasonal migration, largely within Africa, during previous glacial–interglacial cycles with no obvious impact on population size. Using individual migratory track data to hindcast monthly bioclimatic habitat availability maps through the last 120,000 y, we show altered seasonal use of suitable areas through time. Independently derived effective population sizes indicate a growing population through the last 40,000 y. We conclude that the migratory lifestyle enabled adaptation to shifting climate conditions. This indicates that populations of resource-tracking, long-distance migratory species could expand successfully during warming periods in the past, which could also be the case under future climate scenarios.