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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.
In this article, we present our experience with over a decade of strict simplicity orientation in the development and evolution of plug-ins. The point of our approach is to enable our graphical modeling framework jABC to capture plug-in development in a domain-specific setting. The typically quite tedious and technical plug-in development is shifted this way from a programming task to the modeling level, where it can be mastered also by application experts without programming expertise. We show how the classical plug-in development profits from a systematic domain-specific API design and how the level of abstraction achieved this way can be further enhanced by defining adequate building blocks for high-level plug-in modeling. As the resulting plug-in models can be compiled and deployed automatically, our approach decomposes plug-in development into three phases where only the realization phase requires plug-in-specific effort. By using our modeling framework jABC, this effort boils down to graphical, tool-supported process modeling. Furthermore, we support the automatic completion of process sketches for executability. All this will be illustrated along the most recent plug-in-based evolution of the jABC framework, which witnessed quite some bootstrapping effects.
In both animal and plant kingdoms, body size is a fundamental but still poorly understood attribute of biological systems. Here we report that the Arabidopsis NAC transcription factor Regulator of Proteasomal Gene Expression' (RPX) controls leaf size by positively modulating proteasome activity. We further show that the cis-element recognized by RPX is evolutionarily conserved between higher plant species. Upon over-expression of RPX, plants exhibit reduced growth, which may be reversed by a low concentration of the pharmacological proteasome inhibitor MG132. These data suggest that the rate of protein turnover during growth is a critical parameter for determining final organ size.
Glyco-assemblies derived from amphiphilic sugar-decorated block copolymers (ASBCs) have emerged prominently due to their wide application, for example, in biomedicine and as drug carriers. However, to efficiently construct these glyco-assemblies is still a challenge. Herein, we report an efficient technology for the synthesis of glyco-inside nano-assemblies by utilizing RAFT polymerization of a galactose-decorated methacrylate for polymerization-induced self-assembly (PISA). Using this approach, a series of highly ordered glyco-inside nano-assemblies containing intermediate morphologies were fabricated by adjusting the length of the hydrophobic glycoblock and the polymerization solids content. A specific morphology of complex vesicles was captured during the PISA process and the formation mechanism is explained by the morphology of its precursor and intermediate. Thus, this method establishes a powerful route to fabricate glyco-assemblies with tunable morphologies and variable sizes, which is significant to enable the large-scale fabrication and wide application of glyco-assemblies.
Hyenas (family Hyaenidae), as the sister group to cats (family Felidae), represent a deeply diverging branch within the cat-like carnivores (Feliformia). With an estimated population size of <10,000 individuals worldwide, the brown hyena (Parahyaena brunnea) represents the rarest of the four extant hyena species and has been listed as Near Threatened by the IUCN. Here, we report a high-coverage genome from a captive bred brown hyena and both mitochondrial and low-coverage nuclear genomes of 14 wild-caught brown hyena individuals from across southern Africa. We find that brown hyena harbor extremely low genetic diversity on both the mitochondrial and nuclear level, most likely resulting from a continuous and ongoing decline in effective population size that started similar to 1 Ma and dramatically accelerated towards the end of the Pleistocene. Despite the strikingly low genetic diversity, we find no evidence of inbreeding within the captive bred individual and reveal phylogeographic structure, suggesting the existence of several potential subpopulations within the species.
Venomous snakes often display extensive variation in venom composition both between and within species. However, the mechanisms underlying the distribution of different toxins and venom types among populations and taxa remain insufficiently known. Rattlesnakes (Crotalus, Sistrurus) display extreme inter-and intraspecific variation in venom composition, centered particularly on the presence or absence of presynaptically neurotoxic phospholipases A2 such as Mojave toxin (MTX). Interspecific hybridization has been invoked as a mechanism to explain the distribution of these toxins across rattlesnakes, with the implicit assumption that they are adaptively advantageous. Here, we test the potential of adaptive hybridization as a mechanism for venom evolution by assessing the distribution of genes encoding the acidic and basic subunits of Mojave toxin across a hybrid zone between MTX-positive Crotalus scutulatus and MTX-negative C. viridis in southwestern New Mexico, USA. Analyses of morphology, mitochondrial and single copy-nuclear genes document extensive admixture within a narrow hybrid zone. The genes encoding the two MTX subunits are strictly linked, and found in most hybrids and backcrossed individuals, but not in C. viridis away from the hybrid zone. Presence of the genes is invariably associated with presence of the corresponding toxin in the venom. We conclude that introgression of highly lethal neurotoxins through hybridization is not necessarily favored by natural selection in rattlesnakes, and that even extensive hybridization may not lead to introgression of these genes into another species.