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Dalui, D.

Publications and source records attributed to Dalui, D..

2 recordsLinked to original sources

Influence of natural enemy specificity and functional response on victim coexistence

Natural enemies are thought to promote coexistence of competing victim species. Although existing theory suggests victim coexistence increases with enemy specialization, the dynamics and potential extinction of enemies is generally discounted. Where enemy dynamics have been considered, empirically atypical linear functional responses have been studied. These limitations could over-simplify inferences about enemy-mediated coexistence. We studied the dynamics of two competing victim species and two enemy species with a deterministic model. We derived equilibrium points, and used linear stability analysis, numerical simulations and Floquet theory to determine the influence of enemy specificity and non-linear functional responses on coexistence in this victim-enemy community. We found greater specificity could drive enemy equilibrium points to infeasible values. We found only accelerating enemy functional responses result in stable equilibrium point coexistence of otherwise equivalent competitor victims, in which case greater specificity results in greater stability. Linear and saturating responses produce complex dynamics (neutral or limit cycles, chaos) or extinction, with limit cycle stability highest at intermediate specificity. Our results indicate strict specificity may not maximize coexistence, and enemy functional response critically influences whether enemies promote victim coexistence. They highlight the need to incorporate enemy dynamics into the growing body of theory regarding enemy-mediated diversity maintenance.

ecology↗

Modeling the Tangled Bank: A Users Guide to Gillespie Eco-evolutionary Models using the Julia Programming Language

O_LIEco-evolutionary processes drive patterns in species abundances and traits. However, modeling complex ecological systems is challenging because of the many species and traits involved and because processes unfold in stochastic and non-equilibrium conditions. Gillespie Eco-evolutionary Models (GEMs) were created to simulate the eco-evolutinary dynamics in such complex scenarios. C_LIO_LIGEMs bridge the gap between ecological and evolutionary timescales, enabling tracking of trait dynamics and abundances simultaneously, and allowing real-time feedback between the two processes. Designed to capture demographic stochasticity and individual trait variation, GEMs enable tracking of multi-trait and multi-species evolution. Originally designed for a quantitative genetics approach, GEMs have now been expanded to handle both quantitative traits and discrete traits (genotypes or strains). C_LIO_LIIn this manuscript, we introduce an optimized and accessible framework for GEMs developed in the Julia programming language. We have simplified the simulation setup process by placing many of the information containers and design structures into functions that adapt to the model configurations chosen by the user. We use a birth-death logistic growth model as an example to illustrate the GEM setup. C_LIO_LIThis users guide is designed to make building GEMs for new models more streamlined and approachable. In addition to compartmentalized internal workings, the new framework also improves computational speed and efficiency. This lets users focus on model development rather than algorithmic complexities. C_LI

ecology↗