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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.
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.
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.
The onset of modern central Asian atmospheric circulation is traditionally linked to the interplay of surface uplift of the Mongolian and Tibetan-Himalayan orogens, retreat of the Paratethys sea from central Asia and Cenozoic global cooling. Although the role of these players has not yet been unravelled, the vast dust deposits of central China support the presence of arid conditions and modern atmospheric pathways for the last 25 million years (Myr). Here, we present provenance data from older (42-33 Myr) dust deposits, at a time when the Tibetan Plateau was less developed, the Paratethys sea still present in central Asia and atmospheric pCO(2) much higher. Our results show that dust sources and near-surface atmospheric circulation have changed little since at least 42 Myr. Our findings indicate that the locus of central Asian high pressures and concurrent aridity is a resilient feature only modulated by mountain building, global cooling and sea retreat.
Taxonomy plays a central role in biological sciences. It provides a communication system for scientists as it aims to enable correct identification of the studied organisms. As a consequence, species descriptions should seek to include as much available information as possible at species level to follow an integrative concept of 'taxonomics'. Here, we describe the cryptic species Epimeria frankei sp. nov. from the North Sea, and also redescribe its sister species, Epimeria cornigera. The morphological information obtained is substantiated by DNA barcodes and complete nuclear 18S rRNA gene sequences. In addition, we provide, for the first time, full mitochondrial genome data as part of a metazoan species description for a holotype, as well as the neotype. This study represents the first successful implementation of the recently proposed concept of taxonomics, using data from high-throughput technologies for integrative taxonomic studies, allowing the highest level of confidence for both biodiversity and ecological research.
Dating growth strata and basin fill by combining 26Al/10Be burial dating and magnetostratigraphy
(2018)
Cosmogenic burial dating enables dating of coarse-grained, Pliocene-Pleistocene sedimentary units that are typically difficult to date with traditional methods, such as magnetostratigraphy. In the actively deforming western Tarim Basin in NW China, Pliocene-Pleistocene conglomerates were dated at eight sites, integrating Al-26/Be-10 burial dating with previously published magnetostratigraphic sections. These samples were collected from growth strata on the flanks of growing folds and from sedimentary units beneath active faults to place timing constraints on the initiation of deformation of structures within the basin and on shortening rates on active faults. These new basin-fill and growthstrata ages document the late Neogene and Quaternary growth of the Pamir and Tian Shan orogens between >5 and 1 Ma and delineate the eastward propagation of deformation at rates up to 115 km/m.y. and basinward growth of both mountain belts at rates up to 12 km/m.y.
The enormous species richness of flowering plants is at least partly due to floral diversification driven by interactions between plants and their animal pollinators [1, 2]. Specific pollinator attraction relies on visual and olfactory floral cues [3-5]; floral scent can not only attract pollinators but also attract or repel herbivorous insects [6-8]. However, despite its central role for plant-animal interactions, the genetic control of floral scent production and its evolutionary modification remain incompletely understood [9-13]. Benzenoids are an important class of floral scent compounds that are generated from phenylalanine via several enzymatic pathways [14-17]. Here we address the genetic basis of the loss of floral scent associated with the transition from outbreeding to selfing in the genus Capsella. While the outbreeding C. grandiflora emits benzaldehyde as a major constituent of its floral scent, this has been lost in the selfing C. rubella. We identify the Capsella CNL1 gene encoding cinnamate: CoA ligase as responsible for this variation. Population genetic analysis indicates that CNL1 has been inactivated twice independently in C. rubella via different novel mutations to its coding sequence. Together with a recent study in Petunia [18], this identifies cinnamate: CoA ligase as an evolutionary hotspot for mutations causing the loss of benzenoid scent compounds in association with a shift in the reproductive strategy of Capsella from pollination by insects to self-fertilization.
Background
The flowering plant Primula veris is a common spring blooming perennial that is widely cultivated throughout Europe. This species is an established model system in the study of the genetics, evolution, and ecology of heterostylous floral polymorphisms. Despite the long history of research focused on this and related species, the continued development of this system has been restricted due the absence of genomic and transcriptomic resources.
Results
We present here a de novo draft genome assembly of P. veris covering 301.8 Mb, or approximately 63% of the estimated 479.22 Mb genome, with an N50 contig size of 9.5 Kb, an N50 scaffold size of 164 Kb, and containing an estimated 19,507 genes. The results of a RADseq bulk segregant analysis allow for the confident identification of four genome scaffolds that are linked to the P. veris S-locus. RNAseq data from both P. veris and the closely related species P. vulgaris allow for the characterization of 113 candidate heterostyly genes that show significant floral morph-specific differential expression. One candidate gene of particular interest is a duplicated GLOBOSA homolog that may be unique to Primula (PveGLO2), and is completely silenced in L-morph flowers.
Conclusions
The P. veris genome represents the first genome assembled from a heterostylous species, and thus provides an immensely important resource for future studies focused on the evolution and genetic dissection of heterostyly. As the first genome assembled from the Primulaceae, the P. veris genome will also facilitate the expanded application of phylogenomic methods in this diverse family and the eudicots as a whole.
The transition from pollinator-mediated outbreeding to selfing has occurred many times in angiosperms. This is generally accompanied by a reduction in traits attracting pollinators, including reduced emission of floral scent. In Capsella, emission of benzaldehyde as a main component of floral scent has been lost in selfing C. rubella by mutation of cinnamate-CoA ligase CNL1. However, the biochemical basis and evolutionary history of this loss remain unknown, as does the reason for the absence of benzaldehyde emission in the independently derived selfer Capsella orientalis. We used plant transformation, in vitro enzyme assays, population genetics and quantitative genetics to address these questions. CNL1 has been inactivated twice independently by point mutations in C. rubella, causing a loss of enzymatic activity. Both inactive haplotypes are found within and outside of Greece, the centre of origin of C. rubella, indicating that they arose before its geographical spread. By contrast, the loss of benzaldehyde emission in C. orientalis is not due to an inactivating mutation in CNL1. CNL1 represents a hotspot for mutations that eliminate benzaldehyde emission, potentially reflecting the limited pleiotropy and large effect of its inactivation. Nevertheless, even closely related species have followed different evolutionary routes in reducing floral scent.
A contemporary challenge in Ecology and Evolutionary Biology is to anticipate the fate of populations of organisms in the context of a changing world. Climate change and landscape changes due to anthropic activities have been of major concern in the contemporary history. Organisms facing these threats are expected to respond by local adaptation (i.e., genetic changes or phenotypic plasticity) or by shifting their distributional range (migration). However, there are limits to their responses. For example, isolated populations will have more difficulties in developing adaptive innovations by means of genetic changes than interconnected metapopulations. Similarly, the topography of the environment can limit dispersal opportunities for crawling organisms as compared to those that rely on wind. Thus, populations of species with different life history strategy may differ in their ability to cope with changing environmental conditions. However, depending on the taxon, empirical studies investigating organisms’ responses to environmental change may become too complex, long and expensive; plus, complications arising from dealing with endangered species. In consequence, eco-evolutionary modeling offers an opportunity to overcome these limitations and complement empirical studies, understand the action and limitations of underlying mechanisms, and project into possible future scenarios. In this work I take a modeling approach and investigate the effect and relative importance of evolutionary mechanisms (including phenotypic plasticity) on the ability for local adaptation of populations with different life strategy experiencing climate change scenarios. For this, I performed a review on the state of the art of eco-evolutionary Individual-Based Models (IBMs) and identify gaps for future research. Then, I used the results from the review to develop an eco-evolutionary individual-based modeling tool to study the role of genetic and plastic mechanisms in promoting local adaption of populations of organisms with different life strategies experiencing scenarios of climate change and environmental stochasticity. The environment was simulated through a climate variable (e.g., temperature) defining a phenotypic optimum moving at a given rate of change. The rate of change was changed to simulate different scenarios of climate change (no change, slow, medium, rapid climate change). Several scenarios of stochastic noise color resembling different climatic conditions were explored. Results show that populations of sexual species will rely mainly on standing genetic variation and phenotypic plasticity for local adaptation. Population of species with relatively slow growth rate (e.g., large mammals) – especially those of small size – are the most vulnerable, particularly if their plasticity is limited (i.e., specialist species). In addition, whenever organisms from these populations are capable of adaptive plasticity, they can buffer fitness losses in reddish climatic conditions. Likewise, whenever they can adjust their plastic response (e.g., bed-hedging strategy) they will cope with bluish environmental conditions as well. In contrast, life strategies of high fecundity can rely on non-adaptive plasticity for their local adaptation to novel environmental conditions, unless the rate of change is too rapid. A recommended management measure is to guarantee interconnection of isolated populations into metapopulations, such that the supply of useful genetic variation can be increased, and, at the same time, provide them with movement opportunities to follow their preferred niche, when local adaptation becomes problematic. This is particularly important for bluish and reddish climatic conditions, when the rate of change is slow, or for any climatic condition when the level of stress (rate of change) is relatively high.