This model was developed to study the combination of electric vehicles (EVs) and intermitten renewable energy sources. The model presents an EV fleet in a fictional area, divided into a residential area, an office area and commercial area. The area has renewable energy sources: wind and PV solar panels. The agents can be encouraged to charge their electric vehicles at times of renewable energy surplus by introducing different policy interventions. Other interesting variables in the model are the installed renewable energy sources, EV fleet composition and available charging infrastructure. Where possible, use emperical data as input for our model. We expand upon previous models by incorporating environmental self-identity and range anxiety as agent variables.

Overview

Purpose

Modeling an economy with stable macro signals, that works as a benchmark for studying the effects of the agent activities, e.g. extortion, at the service of the elaboration of public policies..
…

The fight against poverty is an urgent global challenge. Microinsurance is promoted as a valuable instrument for buffering income losses due to health or climate-related risks of low-income households in developing countries. However, apart from direct positive effects they can have unintended side effects when insured households lower their contribution to traditional arrangements where risk is shared through private monetary support.

RiskNetABM is an agent-based model that captures dynamics between income losses, insurance payments and informal risk-sharing. The model explicitly includes decisions about informal transfers. It can be used to assess the impact of insurance products and informal risk-sharing arrangements on the resilience of smallholders. Specifically, it allows to analyze whether and how economic needs (i.e. level of living costs) and characteristics of extreme events (i.e. frequency, intensity and type of shock) influence the ability of insurance and informal risk-sharing to buffer income shocks. Two types of behavior with regard to private monetary transfers are explicitly distinguished: (1) all households provide transfers whenever they can afford it and (2) insured households do not show solidarity with their uninsured peers.

The model is stylized and is not used to analyze a particular case study, but represents conditions from several regions with different risk contexts where informal risk-sharing networks between smallholder farmers are prevalent.

…

This agent-based model simulates the interactions between smallholder farming households, land-use dynamics, and ecosystem services in a rural landscape of Eastern Madagascar. It explores how alternative agricultural practices —shifting agriculture, rice cultivation, and agroforestry—combined with varying levels of forest protection, influence food production, food security, dietary diversity, and forest biodiversity over time. The landscape is represented as a grid of spatially explicit patches characterized by land use, ecological attributes, and regeneration dynamics. Agents make yearly decisions on land management based on demographic pressures, agricultural returns, and institutional constraints. Crop yields are affected by stochastic biotic and abiotic disruptions, modulated by local ecosystem regulation functions. The model additionally represents foraging as a secondary food source and pressure on biodiversity. The model supports the analysis of long-term trade-offs between agricultural productivity, human nutrition, and conservation under different policy and land-use scenarios.

LogoClim is a NetLogo model designed to be integrated into other simulations through the LevelSpace extension (Hjorth et al., 2020), providing high resolution climate data from sources validated and used by the Intergovernmental Panel on Climate Change (IPCC).

The model simplifies and standardizes the integration of climate data into NetLogo, allowing researchers to focus their efforts on the model itself with the assurance of using reliable and widely recognized data. Although its main use is as a component of larger simulations, LogoClim also has its own graphical interface for monitoring and checking the datasets.

The climate data comes from the WorldClim 2.1 project (Fick & Hijmans, 2017), for which LogoClim works as an interface to NetLogo. The model supports all three WorldClim data series: (1) Historical Climate Data (1970 to 2000), with 12 monthly points for minimum, mean, and maximum temperature, precipitation, solar radiation, wind speed, vapor pressure, elevation, and bioclimatic variables; (2) Historical Monthly Weather Data (1951 to 2024), based on downscaling of CRU-TS-4.09, developed by the Climatic Research Unit at the University of East Anglia (Harris et al., 2020), with minimum and maximum temperature and total precipitation; and (3) Future Climate Data, based on downscaling climate projections derived from global climate models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) (Eyring et al., 2016) for four future periods (2021 to 2040, 2041 to 2060, 2061 to 2080, and 2081 to 2100) and four scenarios based on the Shared Socioeconomic Pathways (SSPs 126, 245, 370, and 585), covering minimum and maximum temperature, total precipitation, and bioclimatic variables. All series are available at multiple spatial resolutions, from 10 minutes (about 340 km² at the equator) to 30 seconds (about 1 km² at the equator).

…

WeDiG Sim- Weighted Directed Graph Simulator - is an open source application that serves to simulate complex systems. WeDiG Sim reflects the behaviors of those complex systems that put stress on scale-free, weightedness, and directedness. It has been implemented based on “WeDiG model” that is newly presented in this domain. The WeDiG model can be seen as a generalized version of “Barabási-Albert (BA) model”. WeDiG not only deals with weighed directed systems, but also it can handle the […]

Logônia is a NetLogo model that simulates the growth response of a fictional plant, Logônia, under different climatic conditions. The model uses climate data from WorldClim 2.1 (Fick & Hijmans, 2017) and demonstrates how to integrate the LogoClim model through the LevelSpace extension.

The model was developed according to the FAIR principles for research software (Barker et al., 2022) and is openly available on the CoMSES Network and GitHub.

RAGE models a stylized common property grazing system. Agents follow a certain behavioral type. The model allows analyzing how household behavior with respect to a social norm on pasture resting affects long-term social-ecological system dynamics.

Overview

The Weather model is a procedural generation model designed to create realistic daily weather data for socioecological simulations. It generates synthetic weather time series for solar radiation, temperature, and precipitation using algorithms based on sinusoidal and double logistic functions. The model incorporates stochastic variation to mimic unpredictable weather patterns and aims to provide realistic yet flexible weather inputs for exploring diverse climate scenarios.

The Weather model can be used independently or integrated into larger models, providing realistic weather patterns without extensive coding or data collection. It can be customized to meet specific requirements, enabling users to gain a better understanding of the underlying mechanisms and have greater confidence in their applications.

…

The NIER model is intended to add qualitative variables of building owner types and peer group scales to existing energy efficiency retrofit adoption models. The model was developed through a combined methodology with qualitative research, which included interviews with key stakeholders in Cleveland, Ohio and Detroit and Grand Rapids, Michigan. The concepts that the NIER model adds to traditional economic feasibility studies of energy retrofit decision-making are differences in building owner types (reflecting strategies for managing buildings) and peer group scale (neighborhoods of various sizes and large-scale Districts). Insights from the NIER model include: large peer group comparisons can quickly raise the average energy efficiency values of Leader and Conformist building owner types, but leave Stigma-avoider owner types as unmotivated to retrofit; policy interventions such as upgrading buildings to energy-related codes at the point of sale can motivate retrofits among the lowest efficient buildings, which are predominantly represented by the Stigma-avoider type of owner; small neighborhood peer groups can successfully amplify normal retrofit incentives.