Biology subjects

Schulze, M.

Publications and source records attributed to Schulze, M..

3 recordsLinked to original sources

bioRxiv2026

Energetic benefits of differential migration strategies shift under climate change for a migratory bird

Understanding how migratory birds balance energetic costs of movement with wintering benefits requires quantifying their energy expenditure across the full annual cycle. Here, we present a novel approach to reconstruct annual energy budget from multi-sensor geolocator data on atmospheric pressure and activity. We apply this method to tracking data of Eurasian Wrynecks from a European breeding population exhibiting striking variation in migration distance: short-distance migration to southern Europe, medium-distance to northern Africa, and long-distance to sub-Saharan Africa. Long-distance migrants had 21-26% lower annual energy expenditure than shorter-distance migrants, primarily due to reduced thermoregulation costs during boreal winter. However, they faced extreme physiological demands during migration, with daily energy expenditure exceeding 9.5 times basal metabolic rate. Since 1950, climate warming has progressively reduced winter thermoregulation demands disproportionately benefiting and potentially promoting shorter-distance strategies. These results reveal shifting energetic trade-offs under climate change, potentially driving evolution of migration patterns.

ecology↗

bioRxiv2025

All You Need Is Water: Converging Ligand Binding Simulations with Hydration Collective Variables

Selecting appropriate collective variables (CVs) is a crucial bottleneck in enhanced sampling molecular dynamics (MD) simulations. Although progress has been made with data-driven and intuition-based approaches, optimal CVs remain system-specific. Meanwhile, simple geometric descriptors are still widely used due to their transferability. A promising, yet under-explored, candidate for a more efficient CV is solvation. Indeed, despite its central role in ligand binding and folding, the complexity of solvent behavior has hindered its widespread use. Here, we introduce a data-driven and automatic strategy to construct robust solvation-based CVs. Our method identifies critical hydration sites by analyzing the radial distribution function of water around a ligand. Remarkably, using only these hydration CVs within on-the-fly probability enhanced sampling (OPES) simulations, we successfully converge the binding free energy landscapes for a series of host-guest systems. These landscapes show excellent agreement with those from more computationally expensive benchmark methods. We further demonstrate that the choice of where to bias water is key to efficient convergence, providing clear guidelines for implementation. This work not only underscores the central role of water in molecular recognition but also offers a powerful and generalizable framework for enhancing the sampling of complex biomolecular events.

biophysics↗

bioRxiv2020

gauseR: Simple methods for fitting Lotka-Volterra models describing Gause's "Struggle for Existence"

The ecological models of Alfred J. Lotka and Vito Volterra have had an enormous impact on ecology over the past century. Some of the earliest - and clearest - experimental tests of these models were famously conducted by Georgy Gause in the 1930s. Although well known, the data from these experiments are not widely available, and are often difficult to analyze using standard statistical and computational tools. Here, we introduce the gauseR package, a collection of tools for fitting Lotka-Volterra models to time series data of one or more species. The package includes several methods for parameter estimation and optimization, and includes 42 datasets from Gauses species interaction experiments and related work. Additionally, we include with this paper a short blog post discussing the historical importance of these data and models, and an R vignette with a walk-through introducing the package methods. The package is available for download at github.com/adamtclark/gauseR. To demonstrate the package, we apply it to several classic experimental studies from Gause, as well as two other well-known datasets on multi-trophic dynamics on Isle Royale, and in spatially structured mite populations. In almost all cases, models fit observations closely, and fitted parameter values make ecological sense. Taken together, we hope that the methods, data, and analyses that we present here provide a simple and user-friendly way to interact with complex ecological data. We are optimistic that these methods will be especially useful to students and educators who are studying ecological dynamics, as well as researchers who would like a fast tool for basic analyses.

ecology↗