570 Biowissenschaften; Biologie
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Aim Growth is a multifarious phenomenon that has been studied by nutritionists, economists, paediatric endocrinologists; archaeologists, child psychologists and other experts. Yet, a unifying theory of understanding growth regulation is still lacking. Method Critical review of the literature. Results We summarise evidence linking social competition and its effect on hierarchies in social structures, with the neuronal networks of the ventromedial hypothalamus and body size. The endocrine signalling system regulating growth hormone, Insulin-like-Growth-Factor1 and skeletal growth, is well conserved in the evolution of vertebrata for some 400 million years. The link between size and status permits adaptive plasticity, competitive growth and strategic growth adjustments also in humans. Humans perceive size as a signal of dominance with tallness being favoured and particularly prevalent in the upper social classes. Conclusion Westernised societies are competitive. People are tall, and "open to change." Social values include striving for status and prestige implying socio-economic domination. We consider the transition of political and social values following revolutions and civil wars, as key elements that interact with the evolutionarily conserved neuroendocrine competence for adaptive developmental plasticity, overstimulate the hypothalamic growth regulation and finally lead to the recent historic increases in average height.
The shape of a defense-growth trade-off governs seasonal trait dynamics in natural phytoplankton
(2020)
Theory predicts that trade-offs, quantifying costs of functional trait adjustments, crucially affect community trait adaptation to altered environmental conditions, but empirical verification is scarce. We evaluated trait dynamics (antipredator defense, maximum growth rate, and phosphate affinity) of a lake phytoplankton community in a seasonally changing environment, using literature trait data and 21 years of species-resolved high-frequency biomass measurements. The trait data indicated a concave defense-growth trade-off, promoting fast-growing species with intermediate defense. With seasonally increasing grazing pressure, the community shifted toward higher defense levels at the cost of lower growth rates along the trade-off curve, while phosphate affinity explained some deviations from it. We discuss how low fitness differences of species, inferred from model simulations, in concert with stabilizing mechanisms, e.g., arising from further trait dimensions, may lead to the observed phytoplankton diversity. In conclusion, quantifying trade-offs is key for predictions of community trait adaptation and biodiversity under environmental change.
The shape of a defense-growth trade-off governs seasonal trait dynamics in natural phytoplankton
(2020)
Theory predicts that trade-offs, quantifying costs of functional trait adjustments, crucially affect community trait adaptation to altered environmental conditions, but empirical verification is scarce. We evaluated trait dynamics (antipredator defense, maximum growth rate, and phosphate affinity) of a lake phytoplankton community in a seasonally changing environment, using literature trait data and 21 years of species-resolved high-frequency biomass measurements. The trait data indicated a concave defense-growth trade-off, promoting fast-growing species with intermediate defense. With seasonally increasing grazing pressure, the community shifted toward higher defense levels at the cost of lower growth rates along the trade-off curve, while phosphate affinity explained some deviations from it. We discuss how low fitness differences of species, inferred from model simulations, in concert with stabilizing mechanisms, e.g., arising from further trait dimensions, may lead to the observed phytoplankton diversity. In conclusion, quantifying trade-offs is key for predictions of community trait adaptation and biodiversity under environmental change.
Nonribosomal peptides (NRP) are crucial molecular mediators in microbial ecology and provide indispensable drugs. Nevertheless, the evolution of the flexible biosynthetic machineries that correlates with the stunning structural diversity of NRPs is poorly understood. Here, we show that recombination is a key driver in the evolution of bacterial NRP synthetase (NRPS) genes across distant bacterial phyla, which has guided structural diversification in a plethora of NRP families by extensive mixing andmatching of biosynthesis genes. The systematic dissection of a large number of individual recombination events did not only unveil a striking plurality in the nature and origin of the exchange units but allowed the deduction of overarching principles that enable the efficient exchange of adenylation (A) domain substrates while keeping the functionality of the dynamic multienzyme complexes. In the majority of cases, recombination events have targeted variable portions of the A(core) domains, yet domain interfaces and the flexible A(sub) domain remained untapped. Our results strongly contradict the widespread assumption that adenylation and condensation (C) domains coevolve and significantly challenge the attributed role of C domains as stringent selectivity filter during NRP synthesis. Moreover, they teach valuable lessons on the choice of natural exchange units in the evolution of NRPS diversity, which may guide future engineering approaches.
Role of diversification rates and evolutionary history as a driver of plant naturalization success
(2020)
Human introductions of species beyond their natural ranges and their subsequent establishment are defining features of global environmental change. However, naturalized plants are not uniformly distributed across phylogenetic lineages, with some families contributing disproportionately more to the global alien species pool than others. Additionally, lineages differ in diversification rates, and high diversification rates have been associated with characteristics that increase species naturalization success. Here, we investigate the role of diversification rates in explaining the naturalization success of angiosperm plant families.
We use five global data sets that include native and alien plant species distribution, horticultural use of plants, and a time-calibrated angiosperm phylogeny. Using phylogenetic generalized linear mixed models, we analysed the effect of diversification rate, different geographical range measures, and horticultural use on the naturalization success of plant families.
We show that a family's naturalization success is positively associated with its evolutionary history, native range size, and economic use. Investigating interactive effects of these predictors shows that native range size and geographic distribution additionally affect naturalization success. High diversification rates and large ranges increase naturalization success, especially of temperate families.
We suggest this may result from lower ecological specialization in temperate families with large ranges, compared with tropical families with smaller ranges.
Role of diversification rates and evolutionary history as a driver of plant naturalization success
(2020)
Human introductions of species beyond their natural ranges and their subsequent establishment are defining features of global environmental change. However, naturalized plants are not uniformly distributed across phylogenetic lineages, with some families contributing disproportionately more to the global alien species pool than others. Additionally, lineages differ in diversification rates, and high diversification rates have been associated with characteristics that increase species naturalization success. Here, we investigate the role of diversification rates in explaining the naturalization success of angiosperm plant families.
We use five global data sets that include native and alien plant species distribution, horticultural use of plants, and a time-calibrated angiosperm phylogeny. Using phylogenetic generalized linear mixed models, we analysed the effect of diversification rate, different geographical range measures, and horticultural use on the naturalization success of plant families.
We show that a family's naturalization success is positively associated with its evolutionary history, native range size, and economic use. Investigating interactive effects of these predictors shows that native range size and geographic distribution additionally affect naturalization success. High diversification rates and large ranges increase naturalization success, especially of temperate families.
We suggest this may result from lower ecological specialization in temperate families with large ranges, compared with tropical families with smaller ranges.
Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.
Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.
RangeShiftR
(2021)
Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.
Due to continuously intensifying human usage of the marine environment worldwide ranging cetaceans face an increasing number of threats. Besides whaling, overfishing and by-catch, new technical developments increase the water and noise pollution, which can negatively affect marine species. Cetaceans are especially prone to these influences, being at the top of the food chain and therefore accumulating toxins and contaminants. Furthermore, they are extremely noise sensitive due to their highly developed hearing sense and echolocation ability. As a result, several cetacean species were brought to extinction during the last century or are now classified as critically endangered. This work focuses on two odontocetes. It applies and compares different molecular methods for inference of population status and adaptation, with implications for conservation. The worldwide distributed sperm whale (Physeter macrocephalus) shows a matrilineal population structure with predominant male dispersal. A recently stranded group of male sperm whales provided a unique opportunity to investigate male grouping for the first time. Based on the mitochondrial control region, I was able to infer that male bachelor groups comprise multiple matrilines, hence derive from different social groups, and that they represent the genetic variability of the entire North Atlantic. The harbor porpoise (Phocoena phocoena) occurs only in the northern hemisphere. By being small and occurring mostly in coastal habitats it is especially prone to human disturbance. Since some subspecies and subpopulations are critically endangered, it is important to generate and provide genetic markers with high resolution to facilitate population assignment and subsequent protection measurements. Here, I provide the first harbour porpoise whole genome, in high quality and including a draft annotation. Using it for mapping ddRAD seq data, I identify genome wide SNPs and, together with a fragment of the mitochondrial control region, inferred the population structure of its North Atlantic distribution range. The Belt Sea harbors a distinct subpopulation oppose to the North Atlantic, with a transition zone in the Kattegat. Within the North Atlantic I could detect subtle genetic differentiation between western (Canada-Iceland) and eastern (North Sea) regions, with support for a German North Sea breading ground around the Isle of Sylt. Further, I was able to detect six outlier loci which show isolation by distance across the investigated sampling areas. In employing different markers, I could show that single maker systems as well as genome wide data can unravel new information about population affinities of odontocetes. Genome wide data can facilitate investigation of adaptations and evolutionary history of the species and its populations. Moreover, they facilitate population genetic investigations, providing a high resolution, and hence allowing for detection of subtle population structuring especially important for highly mobile cetaceans.