Evolution Of Natural Systems Research Articles

Effects of Community Richness and Competitive Asymmetry on Protozoa Evolution in Sarracenia purpurea Leaves.

AbstractPredicting evolution in natural systems will require understanding how selection operates in multispecies communities. We predicted that the amount that traits evolve in multispecies mixtures would be less than the amount that would be predicted from the additive contributions of the pairwise interactions and that subordinate species will be more likely to evolve in competitive systems than dominant species. We conducted an experimental test of these predictions using a guild of protozoans found in the water-filled leaves of the pitcher plant Sarracenia purpurea. The response to selection did not significantly change as we increased richness from monocultures to two- and four-species mixtures. In accordance with our second prediction, subordinate species demonstrated greater growth in competition after selection than before, while dominant species generally showed no response to selection. Monod-type experiments to determine minimum resource levels found that the dominant species had much higher resource requirements than the subordinate species and that the minimum resource requirements evolved to be higher in the subordinate species. Importantly, these results suggest that subordinate species evolve to become more similar to dominant species, which may involve resource use convergence. Our findings and other recent works suggest that community diversity can affect evolution in surprising ways that warrant further investigation.

Evidence for continent-wide convergent evolution and stasis throughout 150 y of a biological invasion

The extent to which evolution can rescue a species from extinction, or facilitate range expansion, depends critically on the rate, duration, and geographical extent of the evolutionary response to natural selection. Adaptive evolution can occur quickly, but the duration and geographical extent of contemporary evolution in natural systems remain poorly studied. This is particularly true for species with large geographical ranges and for timescales that lie between “long-term” field experiments and the fossil record. Here, we introduce the Virtual Common Garden (VCG) to investigate phenotypic evolution in natural history collections while controlling for phenotypic plasticity in response to local growing conditions. Reconstructing 150 y of evolution in Lythrum salicaria (purple loosestrife) as it invaded North America, we analyze phenology measurements of 3,429 herbarium records, reconstruct growing conditions from more than 12 million local temperature records, and validate predictions across three common gardens spanning 10° of latitude. We find that phenological clines have evolved repeatedly throughout the range, during the first century of evolution. Thereafter, the rate of microevolution stalls, recapitulating macroevolutionary stasis observed in the fossil record. Our study demonstrates that preserved specimens are a critical resource for investigating limits to evolution in natural populations. Our results show how natural selection and trade-offs measured in field studies predict adaptive divergence observable in herbarium specimens over 15 decades at a continental scale.

Protein Cages: From Fundamentals to Advanced Applications.

Proteins that self-assemble into polyhedral shell-like structures are useful molecular containers both in nature and in the laboratory. Here we review efforts to repurpose diverse protein cages, including viral capsids, ferritins, bacterial microcompartments, and designed capsules, as vaccines, drug delivery vehicles, targeted imaging agents, nanoreactors, templates for controlled materials synthesis, building blocks for higher-order architectures, and more. A deep understanding of the principles underlying the construction, function, and evolution of natural systems has been key to tailoring selective cargo encapsulation and interactions with both biological systems and synthetic materials through protein engineering and directed evolution. The ability to adapt and design increasingly sophisticated capsid structures and functions stands to benefit the fields of catalysis, materials science, and medicine.

The Holocene evolution of Lake St Lucia, Africa's largest estuary: Geological implications for contemporary management

The Holocene evolution of one of Africa's largest estuaries, Lake St Lucia on the east coast of South Africa, is examined and juxtaposed with previous and contemporary management practices aimed at fixing the estuary state at a single point along the system's overall evolutionary pathway. The estuary has been heavily altered over the course of the last century, mostly through mouth management activities aimed at maintaining a direct connection with the ocean. Based on a high-resolution seismic reflection dataset, LiDAR and bathymetry data of the lake system, together with palaeontological (foraminifera and diatoms) and sulfur isotope geochemical data from three long (14–16 m) piston cores, we investigate the system-wide and coeval evolution of the three different sub-basins (False Bay, North Lake and South Lake) that comprise the current estuarine lake system. The northern and southern sections of the system evolved independently of each other since the Last Glacial Maximum, with each area responding differently to early sea-level forcings. In North Lake, the lagoon evolved from fully estuarine (8300 cal. BP) to a restricted lagoon with occasional marine incursions, steadily decreasing tidal prism and the development of marginal spits by wind-driven lagoonal waves. The tidal inlet closed approximately 6200 cal. BP and fluvial conditions became more dominant as main back-barrier conditions became attuned to fluvial supply. Similar conditions prevailed in the adjacent False Bay basin, albeit with an earlier onset due to sheltering by prominent bedrock peninsulas. In contrast, South Lake evolved from a fully estuarine system (9500 cal. BP) with a persistent ocean connection, to a segmented system with a diminished tidal connection by 5500 cal. BP. The inlet sealed at this point and an isolated back barrier system developed. This prompted the system-wide impoundment of waters causing back-barrier flooding and in situ drowning of bayhead deltas and segmenting spits. By 2000 cal. BP, these areas had flooded sufficiently to connect over a bedrock high that had diverted the initial palaeo-valleys to the north and south. A new, single lagoon, representative of the modern-day system formed, with a new marine connection to the modern day Mfolozi River and contemporary estuary. Periodic desiccation of the lake sub-basins since this point has been apparent. Given the complex management plans implemented to stop excess sedimentation, hypersaline events, and the continuation of “normal” lake levels, this is at odds with the natural system's evolution to a pan or wetland-type state. This geological background should be key to informing management plans that work within the natural evolutionary trajectory of the system, as opposed to attempting to maintain an unattainable status quo.

Evolutionary Dynamics of Treatment-Induced Resistance in Cancer Informs Understanding of Rapid Evolution in Natural Systems

Rapid evolution is ubiquitous in nature. We briefly review some of this quite broadly, particularly in the context of response to anthropogenic disturbances. Nowhere is this more evident, replicated and accessible to study than in cancer. Curiously cancer has been late - relative to fisheries, antibiotic resistance, pest management and evolution in human dominated landscapes - in recognizing the need for evolutionarily informed management strategies. The speed of evolution matters. Here, we employ game-theoretic modeling to compare time to progression with continuous maximum tolerable dose to that of adaptive therapy where treatment is discontinued when the population of cancer cells gets below half of its initial size and re-administered when the cancer cells recover, forming cycles with and without treatment. We show that the success of adaptive therapy relative to continuous maximum tolerable dose therapy is much higher if the population of cancer cells is defined by two cell types (sensitive vs. resistant in a polymorphic population). Additionally, the relative increase in time to progression increases with the speed of evolution. These results hold with and without a cost of resistance in cancer cells. On the other hand, treatment-induced resistance can be modeled as a quantitative trait in a monomorphic population of cancer cells. In that case, when evolution is rapid, there is no advantage to adaptive therapy. Initial responses to therapy are blunted by the cancer cells evolving too quickly. Our study emphasizes how cancer provides a unique system for studying rapid evolutionary changes within tumor ecosystems in response to human interventions; and allows us to contrast and compare this system to other human managed or dominated systems in nature.

Urban Development and Natural System Evolution in Coastal Areas

Li, X.; Ren, Y.X.; Shi, W.H., Ji, J., and Yin, W.D., 2020. Urban development and natural system evolution in coastal areas. In: Qiu, Y.; Zhu, H., and Fang, X. (eds.), Current Advancements in Marine and Coastal Research for Technological and Sociological Applications. Journal of Coastal Research, Special Issue No. 107, pp. 449-453. Coconut Creek (Florida), ISSN 0749-0208.The southeast coastal area, where several major urban agglomerations are concentrated in, is the main engine of national economic growth. Studying the natural development context of coastal cities will help to improve the urban scale structure, strengthen the relationship between urban space and surrounding areas as well as bring enlightenment for the coordinated development of regional economic belt. Taking Huzhou as an example, this paper studies the evolution of the natural system of coastal cities in the Taihu Lake River Basin. This research focuses on the formation of urban natural spatial pattern based on the city's natural development mechanism and try to sum up the traditional urban development mode through combining the evolution data of urban natural system in historical period, in order to put forward scientific theory and practical basis for the protection, construction and inheritance of traditional urban natural base in China. Through the field survey and graphic analysis, this article makes an in-depth analysis of the urban development and the evolution of natural system in Huzhou from three aspects: (1) the Urban Development of Ancient Huzhou; (2) the natural urban system of Ancient Huzhou; (3) the exploration of the natural urban development model of Huzhou, and the conclusion is that the relationship between the city and the natural system of Huzhou shows a spiral rise in the process of evolution.

Reaction kinetics: scientific passion or applicative tool?

The implications of chemical transformations in the description of the evolution of natural systems are revisited, starting from a historical perspective. The connection with information theory allows for the deepening of how the systems, not in equilibrium with the environment, are subjected to a change that favors the formation of structures of increasing complexity. Then, the metabolic processes, apt to convert bio molecules into the building blocks needed to sustain the cellular formation and growth, are discussed within the frame of synthetic biology, which is triggering interest towards an approach in which the microbial organisms are utilized as factories for the bioconversion of renewable resources to fuels or high-value chemicals. Finally, the role of chemical kinetics in the design of industrial chemical reactors and in simulation of turbulent flames is presented.

Collective dynamics of phase-repulsive oscillators solves graph coloring problem.

We show how to couple phase-oscillators on a graph so that collective dynamics "searches" for the coloring of that graph as it relaxes toward the dynamical equilibrium. This translates a combinatorial optimization problem (graph coloring) into a functional optimization problem (finding and evaluating the global minimum of dynamical non-equilibrium potential, done by the natural system's evolution). Using a sample of graphs, we show that our method can serve as a viable alternative to the traditional combinatorial algorithms. Moreover, we show that, with the same computational cost, our method efficiently solves the harder problem of improper coloring of weighed graphs.

Accelerating pathway evolution by increasing the gene dosage of chromosomal segments.

Experimental evolution is a critical tool in many disciplines, including metabolic engineering and synthetic biology. However, current methods rely on the chance occurrence of a key step that can dramatically accelerate evolution in natural systems, namely increased gene dosage. Our studies sought to induce the targeted amplification of chromosomal segments to facilitate rapid evolution. Since increased gene dosage confers novel phenotypes and genetic redundancy, we developed a method, Evolution by Amplification and Synthetic Biology (EASy), to create tandem arrays of chromosomal regions. In Acinetobacter baylyi, EASy was demonstrated on an important bioenergy problem, the catabolism of lignin-derived aromatic compounds. The initial focus on guaiacol (2-methoxyphenol), a common lignin degradation product, led to the discovery of Amycolatopsis genes (gcoAB) encoding a cytochrome P450 enzyme that converts guaiacol to catechol. However, chromosomal integration of gcoAB in Pseudomonas putida or A. baylyi did not enable guaiacol to be used as the sole carbon source despite catechol being a growth substrate. In ∼1,000 generations, EASy yielded alleles that in single chromosomal copy confer growth on guaiacol. Different variants emerged, including fusions between GcoA and CatA (catechol 1,2-dioxygenase). This study illustrates the power of harnessing chromosomal gene amplification to accelerate the evolution of desirable traits.

Development and validation of a morphological model for multiple sediment classes

The complexity of sediment dynamics in aquatic systems can be better understood by applying numerical models. The development of a comprehensive morphological model is presented in this paper. The model aims to predict the sediment transport and bed evolution in natural systems composed of different sediment types. The morphological model was implemented in MOHID, a modelling system that solves the three-dimensional hydrodynamics and advection-diffusion transport of suspended sediments. Multiple sediment classes were taken into account (non-cohesive and cohesive) considering the effects of sediment mixtures and bed consolidation on resistance to erosion. To represent bottom stratigraphy, the bottom column can be divided into several layers. The key points of the simulated processes are discussed in this paper. Model results are assessed in six test cases through comparison with analytic solutions or experimental data. The outcomes demonstrate the model׳s capacity to simulate the transport dynamics of non-cohesive and cohesive sediments. The speed up of morphological changes by an acceleration factor permitted modelling bed evolution for long time periods. Moreover, a test case for the Tagus Estuary demonstrated the model׳s capacity for generating realistic sediment distribution based on the local hydrodynamic conditions. Limitations in the availability of bed composition data can be overcome by considering a warm-up run to provide realistic initial conditions for further predictions of morphological developments.

Selection and drift influence genetic differentiation of insular Canada lynx (Lynx canadensis) on Newfoundland and Cape Breton Island.

Island populations have long been important for understanding the dynamics and mechanisms of evolution in natural systems. While genetic drift is often strong on islands due to founder events and population bottlenecks, the strength of selection can also be strong enough to counteract the effects of drift. Here, we used several analyses to identify the roles of genetic drift and selection on genetic differentiation and diversity of Canada lynx (Lynx canadensis) across eastern Canada, including the islands of Cape Breton and Newfoundland. Specifically, we assessed whether we could identify a genetic component to the observed morphological differentiation that has been reported across insular and mainland lynx. We used a dinucleotide repeat within the promoter region of a functional gene that has been linked to mammalian body size, insulin‐like growth factor‐1 (IGF‐1). We found high genetic differentiation at neutral molecular markers but convergence of allele frequencies at the IGF‐1 locus. Thus, we showed that while genetic drift has influenced the observed genetic structure of lynx at neutral molecular markers, natural selection has also played a role in the observed patterns of genetic diversity at the IGF‐1 locus of insular lynx.

On the mapping of genotype to phenotype in evolutionary algorithms

Analogies with molecular biology are frequently used to guide the development of artificial evolutionary search. A number of assumptions are made in using such reasoning, chief among these is that evolution in natural systems is an optimal, or at least best available, search mechanism, and that a decoupling of search space from behaviour encourages effective search. In this paper, we explore these assumptions as they relate to evolutionary algorithms, and discuss philosophical foundations from which an effective evolutionary search can be constructed. This framework is used to examine grammatical evolution (GE), a popular search method that draws heavily upon concepts from molecular biology. We identify several properties in GE that are in direct conflict with those that promote effective evolutionary search. The paper concludes with some recommendations for designing representations for effective evolutionary search.

Plant–soil feedbacks: connecting ecosystem ecology and evolution

Summary While an appreciation of plant–soil feedbacks (PSF) continues to expand for community and ecosystem ecology, the eco‐evolutionary mechanisms and consequences of such feedbacks remain largely unknown or untested. Determining the cause and effect of plant phenotypes is central for understanding these eco‐evolutionary dynamics since phenotypes respond to soil selective gradients that are, in turn, modified by plant traits. Genetic variation in plant phenotypes can change soil processes and biotic communities; oppositely, soil gradients and microbial communities can influence the expression and evolution of plant phenotypes. Although these processes represent the two halves of genetic based PSF, research in these areas has developed independently from one another. Greater connectivity between research on ecosystem consequences of plant genetic variation and soil selective gradients that drive plant phenotypic evolution will create novel and important opportunities to link ecology and evolution in natural systems. Papers in this special feature build on the inherent ecological and evolutionary processes involved in PSF, outlining many ways to identify and test mechanisms that connect ecosystem ecology and evolution.

A non-deterministic approach to forecasting the trophic evolution of lakes

<p>Limnologists have long recognized that one of the goals of their discipline is to increase its predictive capability. In recent years, the role of prediction in applied ecology escalated, mainly due to man’s increased ability to change the biosphere. Such alterations often came with unplanned and noticeably negative side effects mushrooming from lack of proper attention to long-term consequences. Regression analysis of common limnological parameters has been successfully applied to develop predictive models relating the variability of limnological parameters to specific key causes. These approaches, though, are biased by the requirement of a priori cause-relation assumption, oftentimes difficult to find in the complex, nonlinear relationships entangling ecological data. A set of quantitative tools that can help addressing current environmental challenges avoiding such restrictions is currently being researched and developed within the framework of ecological informatics. One of these approaches attempting to model the relationship between a set of inputs and known outputs, is based on genetic algorithms and programming (GP). This stochastic optimization tool is based on the process of evolution in natural systems and was inspired by a direct analogy to sexual reproduction and Charles Darwin’s principle of natural selection. GP works through genetic algorithms that use selection and recombination operators to generate a population of equations. Thanks to a 25-years long time-series of regular limnological data, the deep, large, oligotrophic Lake Maggiore (Northern Italy) is the ideal case study to test the predictive ability of GP. Testing of GP on the multi-year data series of this lake has allowed us to verify the forecasting efficacy of the models emerging from GP application. In addition, this non-deterministic approach leads to the discovery of non-obvious relationships between variables and enabled the formulation of new stochastic models.</p>

Spatially variable coevolution between a haemosporidian parasite and the MHC of a widely distributed passerine.

The environment shapes host–parasite interactions, but how environmental variation affects the diversity and composition of parasite-defense genes of hosts is unresolved. In vertebrates, the highly variable major histocompatibility complex (MHC) gene family plays an essential role in the adaptive immune system by recognizing pathogen infection and initiating the cellular immune response. Investigating MHC-parasite associations across heterogeneous landscapes may elucidate the role of spatially fluctuating selection in the maintenance of high levels of genetic variation at the MHC. We studied patterns of association between an avian haemosporidian blood parasite and the MHC of rufous-collared sparrows (Zonotrichia capensis) that inhabit environments with widely varying haemosporidian infection prevalence in the Peruvian Andes. MHC diversity peaked in populations with high infection prevalence, although intra-individual MHC diversity was not associated with infection status. MHC nucleotide and protein sequences associated with infection absence tended to be rare, consistent with negative frequency-dependent selection. We found an MHC variant associated with a ∽26% decrease in infection probability at middle elevations (1501–3100 m) where prevalence was highest. Several other variants were associated with a significant increase in infection probability in low haemosporidian prevalence environments, which can be interpreted as susceptibility or quantitative resistance. Our study highlights important challenges in understanding MHC evolution in natural systems, but may point to a role of negative frequency-dependent selection and fluctuating spatial selection in the evolution of Z. capensisMHC.

Economics of a global strategy for reduction of carbon emissions

The evolution of natural systems that feed and sustain human populations, and indeed the evolution of modern society, has occurred in the context of a moderate and stable climate. Therefore, recent trends in climate change, most likely caused by increasing concentrations of carbon dioxide and other radiative trace gases in the atmosphere, and the expected consequent global warming, are now a major concern. Carbon emissions from energy systems are considered one of the major contributors to climate change and are the focus of all studies on the prevention of climate changes and adaptation strategies. Two global energy scenarios (each with several options) are analysed in this paper: from a dynamic–as–usual concept to a more advanced concept with the goal of stabilising carbon dioxide concentrations in the atmosphere (equivalent to about a 60% reduction of carbon emission compared with today's level). It is shown that the stabilisation approach will require dramatic changes in energy systems: the share of non–carbon fuels will increase to about three quarters of the total primary energy consumption, which will itself grow by a factor of two by the middle of the next century. Surprisingly, the implementation costs turn out to be approximately the same for all scenarios (taking into account possible errors in the cost appraisals for several decades ahead). However, the cost distributions between energy production and use are quite different. Globally, these costs are 3–4% of the GNP, but for developing countries the share of energy investments is, on average, about 7–8% of the GNP, which is cause for concern and will greatly hamper economic and social progress in the Third World. The introduction of energy taxes or carbon taxes in developed countries and the raising of 'global energy funds' could help developing countries to overcome these difficulties. It is supposed that such a policy would stimulate economic growth in developing countries and, as a feedback, overlap the GNP losses in developed countries. The paper attempts to evaluate an optimal strategy for reducing carbon emissions for the next couple of decades, when large uncertainties surround global warming, and to show ways of establishing 'no–regret' policy.

Evolving functional and structural dynamism in coupled Boolean networks.

This article uses a recently presented abstract, tunable Boolean regulatory network model to further explore aspects of mobile DNA, such as transposons. The significant role of mobile DNA in the evolution of natural systems is becoming increasingly clear. This article shows how dynamically controlling network node connectivity and function via transposon-inspired mechanisms can be selected for to significant degrees under coupled regulatory network scenarios, including when such changes are heritable. Simple multicellular and coevolutionary versions of the model are considered.

Evolutionary Theory and the Florence Paleontological Collections

Abstract Florence has a tradition of Natural Philosophy, and since as early as the sixteenth century fossils were collected by the Granduke. The Museum of Natural History of the University of Florence houses today collections that belonged to Nicolas Steno, when fossils were for the first time used as documents to reconstruct Earth history. Natural philosophers and geologists, both Italian and foreigners, continued to study fossils collected in Tertiary strata of Tuscany until the nineteenth century, when the first speculations on the origin of species were proposed. Charles Darwin himself mentions fossil vertebrates that are today on show in our museum. In the last years, this part of the history of science has been proposed to the public. The aim was to foster an understanding of the centrality of fossils in two cultural revolutions, the discovery of deep time and the birth of evolutionary theory–connected among themselves and with the emergence of geology. Dedicated volumes, public conferences, guided visits to the collections, and field trips to paleontological sites have attracted an attentive and responsive public, showing that the history of science can help deliver modern evolutionary thinking. Other activities aimed at students of all ages have also shown that the interaction between schools, university teachers, and museum personnel is vital to form the mind of future generations on the reality of the evolution of natural systems.

Feature - Circuits and systems for high-throughput biology

High-throughput biological data acquisition and processing technologies have shifted the focus of biological research from the realm of traditional experimental science (wet biology) to that of information science (in silico biology). Powerful computation and communication means can be applied to the very large amount of apparently incoherent data coming from biomedical research. Part of the experiments and tests that we used to do in vitro and/or in vivo can now be done in silico. The concept of Laboratory (Lab) on Chip (LoC) is the natural evolution of System on Chip (SoC) by using an array of heterogeneous technologies. This paper reviews first hardware supports and technologies that allow the studies of whole bodies of molecules through the different steps of the biological information flow, and then some of the algorithms and softwares for data processing and integration

Fundamental and Modal Processes in the Evolution of Natural Systems

This paper offers a brief sketch of the evolution of natural systems within the context of cosmic evolution. The argument, conducted from an energy stance but without recourse to the mathematical apparatus of quantum physics, distinguishes the processes by which energy is transformed from the processes in which it is distributed in a local context. The main focus is on the energetic stratification of natural systems, its causes, and its consequences. A brief coda points to some implications of this treatment.