scholarly journals Can constraint closure provide a generalized understanding of community dynamics in ecosystems?

2020 ◽  
Author(s):  
Steven L. Peck ◽  
Andrew Heiss
Keyword(s):  
Pattern Formation ◽  
Simulation Model ◽  
Community Dynamics ◽  
Species Turnover ◽  
Evolutionary Constraints ◽  
Computer Simulation Model ◽  
Ecosystem Stability ◽  
Ecological Communities ◽  
Agent Based ◽  
Evolutionary Forces

AbstractSince the inception of the discipline, understanding causal complexity in ecological communities has been a challenge. Here we draw insights from recent work on constraint closure that suggests ways of grappling with ecological complexity that yield generalizable theoretical insights. Using a set of evolutionary constraints on species flow through ecological communities, which include: selection, species drift, dispersal, and speciation, combined with multispecies interactions such as mutualistic interactions, and abiotic constraints, we demonstrate how constraint closure allows communities to emerge as semi-autonomous structures. Here we develop an agent-based model to explore how evolutionary constraints provide stability to ecological communities. The model is written in Netlogo, an agent based-modeling system, with advanced tools for manipulating spatially structured models and tools for tracking pattern formation. We articulate ways that ecological pattern formation, viewed through the lens of constraint closure, informs questions about stability and turnover in community ecology. The role of the chosen constraints was clear from the simulation results. It took the shape of both inducing stability and creating conditions for a more dynamic community with increases in species turnover through time. Key ecological and evolutionary variables showed overall stability in the landscape structure when plotted against the number of constraints, suggesting that these evolutionary forces act as constraints to the flow of species in such a way that constraint closure is achieved effecting semi-autonomy.Author SummaryEcosystems are among the most complex structures studied. They comprise elements that seem both stable and contingent. The stability of these systems depends on interactions among their evolutionary history, including the accidents of organisms moving through the landscape and microhabitats of the earth, and the biotic and abiotic conditions in which they occur. When ecosystems are stable, how is that achieved? Here we look at ecosystem stability through a computer simulation model that suggests that it may depend on what constrains the system and how those constraints are structured. Specifically, if the constraints found in an ecological community form a closed loop, that allows particular kinds of feedback may give structure to the ecosystem processes for a period of time. In this simulation model, we look at how evolutionary forces act in such a way these closed constraint loops may form. This may explain some kinds of ecosystem stability. This work will also be valuable to ecological theorists in understanding general ideas of stability in such systems.

An Agent-Based Simulation Model of the Economy: An Empirical Study of Negative Income Tax System in a Transition Economy

2011 ◽  
Vol 204-210 ◽  
pp. 718-723
Author(s):  
Xiang Yu Wan ◽  
Peng Jia
Keyword(s):  
Economic Growth ◽  
Simulation Model ◽  
Income Tax ◽  
Transition Economy ◽  
Computer Simulation Model ◽  
Tax System ◽  
Income Difference ◽  
Agent Based ◽  
Negative Income ◽  
Negative Income Tax

In this paper, we present an agent-based computer simulation model to analyze the dynamic relationship between economic growth and income difference in a transition economy and to evaluate the empirical effects of negative income tax system. Micro agents in the economy form the economic networks and enable the economy to evolve forward through the intelligential evolutionary system and mutual interactions between the agents. Based on the logical reasons of the transition economy, the model finally gives the results of the simulation: when the economy finishes rapid transition and enters into stable development, by implementing negative income tax system, government can effectively decrease income difference while at the same time maintain rapid economic growth.

scholarly journals A process-based metacommunity framework linking local and regional scale community ecology

2019 ◽  
Author(s):  
Patrick L. Thompson ◽  
Laura Melissa Guzman ◽  
Luc De Meester ◽  
Zsófia Horváth ◽  
Robert Ptacnik ◽  
...  
Keyword(s):  
Simulation Model ◽  
Community Ecology ◽  
Species Interactions ◽  
Community Dynamics ◽  
Regional Scale ◽  
Ecological Communities ◽  
Data Accessibility ◽  
Species Sorting ◽  
Wide Range ◽  
Underlying Processes

AbstractThe metacommunity concept has the potential to integrate local and regional dynamics within a general community ecology framework. To this end, the concept must move beyond the discrete archetypes that have largely defined it (e.g. neutral vs. species sorting) and better incorporate local scale species interactions and coexistence mechanisms. Here, we present a fundamental reconception of the framework that explicitly links local coexistence theory to the spatial processes inherent to metacommunity theory, allowing for a continuous range of competitive community dynamics. These dynamics emerge from the three underlying processes that shape ecological communities: 1) density-independent responses to abiotic conditions, 2) density-dependent biotic interactions, and 3) dispersal. Stochasticity is incorporated in the demographic realization of each of these processes. We formalize this framework using a simulation model that explores a wide range of competitive metacommunity dynamics by varying the strength of the underlying processes. Using this model and framework, we show how existing theories, including the traditional metacommunity archetypes, are linked by this common set of processes. We then use the model to generate new hypotheses about how the three processes combine to interactively shape diversity, functioning, and stability within metacommunities.Statement of authorshipThis project was conceived at the sTURN working group, of which all authors are members. PLT developed the framework and model with input from all authors. PLT wrote the model code. PLT and LMG performed the simulations. PLT produced the figures and wrote the first draft with input from LMG and JMC. All authors provided feedback and edits on several versions of the manuscript.Data accessibilityAll code for running the simulation model and producing the figures is archived on Zenodo - https://doi.org/10.5281/zenodo.3833035.

EMERGENT FEATURES IN A GENERAL FOOD WEB SIMULATION: LOTKA–VOLTERRA, GAUSE'S LAW, AND THE PARADOX OF ENRICHMENT

2013 ◽  
Vol 16 (08) ◽  
pp. 1350014 ◽  
Author(s):  
TED CARMICHAEL ◽  
MIRSAD HADZIKADIC
Keyword(s):  
Simulation Model ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Marine Ecosystem ◽  
System Level ◽  
Computer Simulation Model ◽  
Agent Based ◽  
Predator Prey ◽  
Paradox Of Enrichment ◽  
Complex Adaptive

Computer simulations of complex food-webs are important tools for deepening our understanding of these systems. Yet most computer models assume, rather than generate, key system-level patterns, or use mathematical modeling approaches that make it difficult to fully account for nonlinear dynamics. In this paper, we present a computer simulation model that addresses these concerns by focusing on assumptions of agent attributes rather than agent outcomes. Our model utilizes the techniques of complex adaptive systems and agent-based modeling so that system level patterns of a marine ecosystem emerge from the interactions of thousands of individual computer agents. This methodology is validated by using this general simulation model to replicate fundamental properties of a marine ecosystem, including: (i) the predator–prey oscillations found in Lotka–Volterra; (ii) the stepped pattern of biomass accrual from resource enrichment; (iii) the Paradox of Enrichment; and (iv) Gause's Law.

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