Biology subjects

Marsland, R.

Publications and source records attributed to Marsland, R..

12 recordsLinked to original sources

bioRxiv2025

The equalizing effect of adaptive foraging increases plant coexistence in plant-pollinator networks

The role of pollination in plant coexistence remains contested, with studies using Lotka-Volterra models suggesting pollination hinders while consumer-resource approaches indicating it can promote plant coexistence. Through the lens of modern coexistence theory, we analyze how network nestedness and pollinator foraging behavior influence plant coexistence via stabilizing (increasing the relative effect of intraspecific to interspecific competition) or equalizing (reducing fitness differences) mechanisms. Our findings reveal that while nestedness alone threatens specialist plant persistence, adaptive foraging by pollinators generates equalizing mechanisms by benefiting specialist over generalist plants which promotes plant coexistence, helping explain the contrasting conclusions from previous studies.

ecology↗

bioRxiv2023

Metabolic similarity and the predictability of microbial community assembly

AbstractWhen microbial communities form, their composition is shaped by selective pressures imposed by the environment. Can we predict which communities will assemble under different environmental conditions? Here, we hypothesize that quantitative similarities in metabolic traits across metabolically similar environments lead to predictable similarities in community composition. To that end, we measured the growth rate and by-product profile of a library of proteobacterial strains in a large number of single nutrient environments. We found that growth rates and secretion profiles were positively correlated across environments when the supplied substrate was metabolically similar. By analyzing hundreds of in-vitro communities experimentally assembled in an array of different synthetic environments, we then show that metabolically similar substrates select for taxonomically similar communities. These findings lead us to propose and then validate a comparative approach for quantitatively predicting the effects of novel substrates on the composition of complex microbial consortia.

ecology↗

bioRxiv2022

Fewer but higher quality of pollinator visits determines plant invasion success in simulated plant-pollinator networks

Invasive plants often use mutualisms to establish in their new habitats and tend to be visited by resident pollinators similarly or more frequently than native plants. The quality and resulting reproductive success of those visits, however, have rarely been studied in a network context. Here, we use a dynamic model to evaluate the invasion success and impacts on natives of various types of non-native plant species introduced into thousands of plant-pollinator networks of varying structure. We found that network structure properties did not predict invasion success, but non-native traits and interactions did. Specifically, non-native plants producing high amounts of floral rewards but visited by few pollinators at the moment of their introduction were the only plant species able to invade the networks. This result is determined by the transient dynamics occurring right after the plant introduction. Successful invasions increased the abundance of pollinators that visited the invader, but the reallocation of the pollinators foraging effort from native plants to the invader reduced the quantity and quality of visits received by native plants and made the networks slightly more modular and nested. The positive and negative effects of the invader on pollinator and plant abundance, respectively, were buffered by plant richness. Our results call for evaluating the impact of invasive plants not only on visitation rates and network structure, but also on processes beyond pollination including seed production and recruitment of native plants.

ecology↗

bioRxiv2021

Cross-feeding shapes both competition and cooperation in microbial ecosystems

Recent work suggests that cross-feeding - the secretion and consumption of metabolic biproducts by microbes - is essential for understanding microbial ecology. Yet how cross-feeding and competition combine to give rise to ecosystem-level properties remains poorly understood. To address this question, we analytically analyze the Microbial Consumer Resource Model (MiCRM), a prominent ecological model commonly used to study microbial communities. Our mean-field solution exploits the fact that unlike replicas, the cavity method does not require the existence of a Lyapunov function. We use our solution to derive new species-packing bounds for diverse ecosystems in the presence of cross-feeding, as well as simple expressions for species richness and the abundance of secreted resources as a function of cross-feeding (metabolic leakage) and competition. Our results show how a complex interplay between competition for resources and cooperation resulting from metabolic exchange combine to shape the properties of microbial ecosystems.

ecology↗

bioRxiv2020

Niche theory for mutualism: A graphical approach to plant-pollinator network dynamics

Contemporary Niche Theory is a useful framework for understanding how organisms interact with each other and with their shared environment. Its graphical representation, popularized by Tilman’s Resource Ratio Hypothesis, facilitates the analysis of the equilibrium structure of complex dynamical models including species coexistence. This theory has been applied primarily to resource competition since its early beginnings. Here, we integrate mutualism into niche theory by expanding Tilman’s graphical representation to the analysis of consumer-resource dynamics of plant-pollinator networks. We graphically explain the qualitative phenomena previously found by numerical simulations, including the effects on community dynamics of nestedness, adaptive foraging, and pollinator invasions. Our graphical approach promotes the unification of niche and network theories, and deepens the synthesis of different types of interactions within a consumer-resource framework.Secondary Abstract Teoría de Nicho para Mutualismos: Una aproximación gráfica a la dinámica de redes planta-polinizadorLa Teoría Contemporánea de Nicho es un marco útil para entender cómo los organismos interactúan entre ellos y con su ambiente compartido. Su representatión gráfica, popularizada por la Hipótesis de Razón de Recursos de Tilman, facilita el análisis de la estructura de equilibrio de modelos dinámicos complejos, incluyendo la coexistencia de especies. Esta teoría ha sido aplicada primariamente a competencia por recursos desde sus inicios. Aquí, integramos el mutualismo dentro de la teoría de nicho al expandir la representatión gráfica de Tilman al análisis de la dinámica consumidor-recurso de las redes planta-polinizador. Explicamos gráficamente fenómenos cualitativos encontrados previamente mediante simulaciones numéricas, incluyendo los efectos sobre la dinámica comunitaria del anidamiento, forrajeo adaptativo y de las invasiones por polinizadores. Nuestra aproximación gráfica promueve la unificatión de las teorías de nicho y de redes, y profundiza la síntesis de diferentes tipos de interacciones dentro de un marco de consumidor-recurso.Competing Interest StatementThe authors have declared no competing interest.View Full Text

ecology↗

bioRxiv2019

The effect of resource dynamics on species packing in diverse ecosystems

The competitive exclusion principle asserts that coexisting species must occupy distinct ecological niches (i.e. the number of surviving species can not exceed the number of resources). An open question is to understand if and how different resource dynamics affect this bound. Here, we analyze a generalized consumer resource model with externally supplied resources and show that - in contrast to self-renewing resources - species can occupy only half of all available environmental niches. This motivates us to construct a new schema for classifying ecosystems based on species packing properties.

biophysics↗

bioRxiv2019

A minimal model for microbial biodiversity can reproduce experimentally observed ecological patterns

Surveys of microbial biodiversity such as the Earth Microbiome Project (EMP) and the Human Microbiome Project (HMP) have revealed robust ecological patterns across different environments. A major goal in ecology is to leverage these patterns to identify the ecological processes shaping microbial ecosystems. One promising approach is to use minimal models that can relate mechanistic assumptions at the microbe scale to community-level patterns. Here, we demonstrate the utility of this approach by showing that the Microbial Consumer Resource Model (MiCRM) - a minimal model for microbial communities with resource competition, metabolic crossfeeding and stochastic colonization - can qualitatively reproduce patterns found in survey data including compositional gradients, dissimilarity/overlap correlations, richness/harshness correlations, and nestedness of community composition. By using the MiCRM to generate synthetic data with different environmental and taxonomical structure, we show that large scale patterns in the EMP can be reproduced by considering the energetic cost of surviving in harsh environments and HMP patterns may reflect the importance of environmental filtering in shaping competition. We also show that recently discovered dissimilarity-overlap correlations in the HMP likely arise from communities that share similar environments rather than reflecting universal dynamics. We identify ecologically meaningful changes in parameters that alter or destroy each one of these patterns, suggesting new mechanistic hypotheses for further investigation. These findings highlight the promise of minimal models for microbial ecology.

microbiology↗

bioRxiv2019

The Community Simulator: A Python package for microbial ecology

Natural microbial communities contain hundreds to thousands of interacting species. For this reason, computational simulations are playing an increasingly important role in microbial ecology. In this manuscript, we present a new open-source, freely available Python package called Community Simulator for simulating microbial population dynamics in a reproducible, transparent and scalable way. The Community Simulator includes five major elements: tools for preparing the initial states and environmental conditions for a set of samples, automatic generation of dynamical equations based on a dictionary of modeling assumptions, random parameter sampling with tunable levels of metabolic and taxonomic structure, parallel integration of the dynamical equations, and support for metacommunity dynamics with migration between samples. To significantly speed up simulations using Community Simulator, our Python package implements a new Expectation-Maximization (EM) algorithm for finding equilibrium states of community dynamics that exploits a recently discovered duality between ecological dynamics and convex optimization. We present data showing that this EM algorithm improves performance by between one and two orders compared to direct numerical integration of the corresponding ordinary differential equations. We conclude by listing several recent applications of the Community Simulator to problems in microbial ecology, and discussing possible extensions of the package for directly analyzing microbiome compositional data.

ecology↗

bioRxiv2019

Diverse communities behave like typical random ecosystems

With a brief letter to Nature in 1972, Robert May triggered a worldwide research program in theoretical ecology and complex systems that continues to this day[1]. Building on powerful mathematical results about large random matrices, he argued that systems with sufficiently large numbers of interacting components are generically unstable. In the ecological context, Mays thesis directly contradicted the longstanding ecological intuition that diversity promotes stability[2-4]. In economics and finance, Mays work helped to consolidate growing concerns about the fragility of an increasingly interconnected global marketplace[5-7]. In this Letter, we draw on recent theoretical progress in random matrix theory and statistical physics to fundamentally extend and reinterpret Mays theorem. We confirm that a wide range of ecological models become unstable at the point predicted by May, even when the models do not strictly follow his assumptions. Surprisingly, increasing the interaction strength or diversity beyond the May threshold results in a reorganization of the ecosystem - through extinction of a fixed fraction of species - into a new stable state whose properties are well described by purely random interactions. This self-organized state remains stable for arbitrarily large ecosystem and suggests a new interpretation of Mays original conclusions: when interacting complex systems with many components become sufficiently large, they will generically undergo a transition to a \"typical\" self-organized, stable state.

ecology↗

bioRxiv2019

The Minimum Environmental Perturbation Principle: A New Perspective on Niche Theory

Contemporary niche theory is a powerful conceptual framework for understanding how organisms interact with each other and with their shared environment. Here we show that a large segment of niche theory is equivalent to a Minimum Environmental Perturbation Principle (MEPP): ecosystems self-organize into a state that minimizes the impact of organisms on their environment. Different choices of environmental dynamics naturally give rise to distinct dissimilarity measures for quantifying environmental impact. The MEPP allows for the analysis of ecosystems with large numbers of species and environmental factors and provides a new avenue for analyzing ecological invasions. The MEPP also rigorously connects ecological bistability with the existence of multiple minima in a statistical-physics inspired landscapes. We show that the presence of environmental feedbacks where organisms can produce new resources in addition to depleting them violates the global MEPP. However, even in the presence of such feedbacks, a weaker, local version of the MEPP still applies in a limited region of resource space.

ecology↗

bioRxiv2018

Boundary conditions for early life converge to an organo-sulfur metabolism

It has been suggested that a deep memory of early life is hidden in the architecture of metabolic networks, whose reactions could have been catalyzed by small molecules or minerals prior to genetically encoded enzymes (1-6). A major challenge in unraveling these early steps is assessing the plausibility of a connected, thermodynamically consistent proto-metabolism under different geochemical conditions, which are still surrounded by high uncertainty. Here we combine network-based algorithms (9, 10) with physicochemical constraints on chemical reaction networks to systematically show how different combinations of parameters (temperature, pH, redox potential and availability of molecular precursors) could have affected the evolution of a proto-metabolism. Our analysis of possible trajectories indicates that a subset of boundary conditions converges to an organo-sulfur-based proto-metabolic network fueled by a thioester- and redox-driven variant of the reductive TCA cycle, capable of producing lipids and keto acids. Surprisingly, environmental sources of fixed nitrogen and low-potential electron donors seem not to be necessary for the earliest phases of biochemical evolution. We use one of these networks to build a steady-state dynamical metabolic model of a proto-cell, and find that different combinations of carbon sources and electron acceptors can support the continuous production of a minimal ancient \"biomass\" composed of putative early biopolymers and fatty acids.

systems biology↗

bioRxiv2018

Available energy fluxes drive a phase transition in the diversity, stability, and functional structure of microbial communities

A fundamental goal of microbial ecology is to understand what determines the diversity, stability, and structure of microbial ecosystems. The microbial context poses special conceptual challenges because of the strong mutual influences between the microbes and their chemical environment through the consumption and production of metabolites. By analyzing a generalized consumer resource model that explicitly includes cross-feeding, stochastic colonization, and thermodynamics, we show that complex microbial communities generically exhibit a transition as a function of available energy fluxes from a "resource-limited" regime where community structure and stability is shaped by energetic and metabolic considerations to a diverse regime where the dominant force shaping microbial communities is the overlap between species consumption preferences. These two regimes have distinct species abundance patterns, different functional profiles, and respond differently to environmental perturbations. Our model reproduces large-scale ecological patterns observed across multiple experimental settings such as nestedness and differential beta diversity patterns along energy gradients. We discuss the experimental implications of our results and possible connections with disorder-induced phase transitions in statistical physics.

biophysics↗