Computational Model Library

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Peer reviewed Agent-based model to simulate equilibria and regime shifts emerged in lake ecosystems

no contributors listed | Published Tuesday, January 25, 2022

(An empty output folder named “NETLOGOexperiment” in the same location with the LAKEOBS_MIX.nlogo file is required before the model can be run properly)
The model is motivated by regime shifts (i.e. abrupt and persistent transition) revealed in the previous paleoecological study of Taibai Lake. The aim of this model is to improve a general understanding of the mechanism of emergent nonlinear shifts in complex systems. Prelimnary calibration and validation is done against survey data in MLYB lakes. Dynamic population changes of function groups can be simulated and observed on the Netlogo interface.
Main functional groups in lake ecosystems were modelled as super-individuals in a space where they interact with each other. They are phytoplankton, zooplankton, submerged macrophyte, planktivorous fish, herbivorous fish and piscivorous fish. The relationships between these functional groups include predation (e.g. zooplankton-phytoplankton), competition (phytoplankton-macrophyte) and protection (macrophyte-zooplankton). Each individual has properties in size, mass, energy, and age as physiological variables and reproduce or die according to predefined criteria. A system dynamic model was integrated to simulate external drivers.
Set biological and environmental parameters using the green sliders first. If the data of simulation are to be logged, set “Logdata” as true and input the name of the file you want the spreadsheet(.csv) to be called. You will need create an empty folder called “NETLOGOexperiment” in the same level and location with the LAKEOBS_MIX.nlogo file. Press “setup” to initialise the system and “go” to start life cycles.

A road freight transport (RFT) operation involves the participation of several types of companies in its execution. The TRANSOPE model simulates the subcontracting process between 3 types of companies: Freight Forwarders (FF), Transport Companies (TC) and self-employed carriers (CA). These companies (agents) form transport outsourcing chains (TOCs) by making decisions based on supplier selection criteria and transaction acceptance criteria. Through their participation in TOCs, companies are able to learn and exchange information, so that knowledge becomes another important factor in new collaborations. The model can replicate multiple subcontracting situations at a local and regional geographic level.
The succession of n operations over d days provides two types of results: 1) Social Complex Networks, and 2) Spatial knowledge accumulation environments. The combination of these results is used to identify the emergence of new logistics clusters. The types of actors involved as well as the variables and parameters used have their justification in a survey of transport experts and in the existing literature on the subject.
As a result of a preferential selection process, the distribution of activity among agents shows to be highly uneven. The cumulative network resulting from the self-organisation of the system suggests a structure similar to scale-free networks (Albert & Barabási, 2001). In this sense, new agents join the network according to the needs of the market. Similarly, the network of preferential relationships persists over time. Here, knowledge transfer plays a key role in the assignment of central connector roles, whose participation in the outsourcing network is even more decisive in situations of scarcity of transport contracts.

The model explores the informational causes of polarization and bi-polarization of opinions in groups. To this end it expands the model of the Argument Communication Theory of Bi-polarization. The latter is an argument-based multi-agent model of opinion dynamics inspired by Persuasive Argument Theory. The original model can account for polarization as an outcome of pure informational influence, and reproduces bi-polarization effects by postulating an additional mechanism of homophilous selection of communication partners. The expanded model adds two dimensions: argument strength and more sophisticated protocols of informational influence (argument communication and opinion update).

The Communication-Based Model of Perceived Descriptive Norm Dynamics in Digital Networks (COMM-PDND) is an agent-based model specifically created to examine the dynamics of perceived descriptive norms in the context of digital network structures. The model, developed as part of a master’s thesis titled “The Dynamics of Perceived Descriptive Norms in Digital Network Publics: An Agent-Based Simulation,” emphasizes the critical role of communication processes in norm formation. It focuses on the role of communicative interactions in shaping perceived descriptive norms.

The COMM-PDND is tuned to explore the effects of normative deviance in digital social networks. It provides functionalities for manipulating agents according to their network position, and has a versatile set of customizable parameters, making it adaptable to a wide range of research contexts.

The code and data in this repository are associated with the article titled: “Locating Cultural Holes Brokers in Diffusion Dynamics across Bright Symbolic Boundaries.” The NetLogo code (version 6.4.0) is designed to be a standalone piece of code although it uses the ‘nw’ and ‘matrix’ extensions that come integrated with NetLogo 6.4.0. The code was ran on a Windows 10 x 64 machine.

Grasslands have a large share of the world’s land cover and their sustainable management is important for the protection and provisioning of grassland ecosystem services. The question of how to manage grassland sustainably is becoming increasingly important, especially in view of climate change, which on the one hand extends the vegetation period (and thus potentially allows use intensification) and on the other hand causes yield losses due to droughts. Fertilization plays an important role in grassland management and decisions are usually made at farm level. Data on fertilizer application rates are crucial for an accurate assessment of the effects of grassland management on ecosystem services. However, these are generally not available on farm/field scale. To close this gap, we present an agent-based model for Fertilization In Grasslands (FertIG). Based on animal, land-use, and cutting data, the model estimates grassland yields and calculates field-specific amounts of applied organic and mineral nitrogen on grassland (and partly cropland). Furthermore, the model considers different legal requirements (including fertilization ordinances) and nutrient trade among farms. FertIG was applied to a grassland-dominated region in Bavaria, Germany comparing the effects of changes in the fertilization ordinance as well as nutrient trade. The results show that the consideration of nutrient trade improves organic fertilizer distribution and leads to slightly lower Nmin applications. On a regional scale, recent legal changes (fertilization ordinance) had limited impacts. Limiting the maximum applicable amount of Norg to 170 kg N/ha fertilized area instead of farm area as of 2020 hardly changed fertilizer application rates. No longer considering application losses in the calculation of fertilizer requirements had the strongest effects, leading to lower supplementary Nmin applications. The model can be applied to other regions in Germany and, with respective adjustments, in Europe. Generally, it allows comparing the effects of policy changes on fertilization management at regional, farm and field scale.

The model objective’s is to explore the management choice set to uncover which subsets of strategies are most effective at maximizing species coexistence on a fragmented landscape.

The Pampas Model is an Agent-Based Model intended to explore the dynamics of structural and land use changes in agricultural systems of the Argentine Pampas in response to climatic, technological economic, and political drivers.

The model explores the emergence of inequality in cognitive and socio-emotional skills at the societal level within and across generations that results from differences in parental investment behavior during childhood and adolescence.

AMBAWA simulates the flows of biomass between crop and livestock systems at the field, farm, and village scales in order to showcase innovating management practices of soil fertility in West Africa.

Displaying 10 of 1079 results for "Bin-Tzong Chi" clear search

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