Paper List
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Nyxus: A Next Generation Image Feature Extraction Library for the Big Data and AI Era
This paper addresses the core pain point of efficiently extracting standardized, comparable features from massive (terabyte to petabyte-scale) biomedi...
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Topological Enhancement of Protein Kinetic Stability
This work addresses the long-standing puzzle of why knotted proteins exist by demonstrating that deep knots provide a functional advantage through enh...
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A Multi-Label Temporal Convolutional Framework for Transcription Factor Binding Characterization
This paper addresses the critical limitation of existing TF binding prediction methods that treat transcription factors as independent entities, faili...
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Social Distancing Equilibria in Games under Conventional SI Dynamics
This paper solves the core problem of proving the existence and uniqueness of Nash equilibria in finite-duration SI epidemic games, showing they are a...
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Binding Free Energies without Alchemy
This paper addresses the core bottleneck of computational expense in Absolute Binding Free Energy calculations by eliminating the need for numerous al...
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SHREC: A Spectral Embedding-Based Approach for Ab-Initio Reconstruction of Helical Molecules
This paper addresses the core bottleneck in cryo-EM helical reconstruction: eliminating the dependency on accurate initial symmetry parameter estimati...
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Budget-Sensitive Discovery Scoring: A Formally Verified Framework for Evaluating AI-Guided Scientific Selection
This paper addresses the critical gap in evaluating AI-guided scientific selection strategies under realistic budget constraints, where existing metri...
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Probabilistic Joint and Individual Variation Explained (ProJIVE) for Data Integration
This paper addresses the core challenge of accurately decomposing shared (joint) and dataset-specific (individual) sources of variation in multi-modal...
可变食性范围模型中向泛化主义的缓慢演化
Department of Mathematical Sciences, University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom
30秒速读
IN SHORT: 通过证明是种群统计噪声(而非确定性动力学)驱动了模式形成和泛化食性的演化,解决了间接竞争下物种形成的悖论。
核心创新
- Methodology Develops a continuous-space resource-consumer model with explicit resource dynamics and evolvable dietary range, extending beyond fixed-preference Lotka-Volterra frameworks.
- Theory Demonstrates that deterministic analysis predicts homogeneous steady states (no species), but stochastic simulations with demographic noise induce persistent pattern formation interpreted as species.
- Methodology Uses Fourier analysis of linearized dynamics to predict the dominant perturbation modes (e.g., number of species) from the power spectrum, linking analytical predictions to simulation outcomes.
主要结论
- 对于固定食性范围(w=0.2),傅里叶分析预测在 kL/2π=5 处存在主导模式,这对应于在随机模拟中观察到的5个等间距物种的形成(图2,3A)。
- 在可演化食性范围模型中,动力学发生在两个时间尺度上:快速协同演化到准稳态流形,随后缓慢弛豫向均匀态。种群统计噪声阻止了这种弛豫,维持了模式。
- 泛化食性(宽w)在长时间尺度上随机演化,因为与由相同资源生产率支持的、种群规模较小的专化集群相比,它们更不易受到灭绝风险的影响。
摘要: 共享栖息地的物种会协同演化以利用可用资源,因为消费受到消费者与资源之间竞争和负反馈回路的调节。给定物种的食性范围决定了其可获取的资源,从而决定了与之竞争的其他物种。狭窄的食性范围以过度依赖少量资源为代价避免竞争;相反,广泛的食性范围提供了更多替代选择,但也增加了与其他物种竞争的机会。在此,我们研究了生态位形成数学模型中食性范围的演化。我们发现了高度路径依赖的协同演化动力学,其特征是长寿命的准稳态。最终,随机效应驱动了泛化食性的演化,正如我们在分析和模拟中所揭示的。