The Simulating Agroforestry Adoption in Rural Indonesia (SAFARI) model aims at exploring the adoption of illipe rubber agroforestry systems by farming households in the case study region in rural Indonesia. Thereby, the ABM simulates the interdependencies of agroforestry systems and local livelihoods, income, land use, biodiversity, and carbon fixation. The model contrasts development paths without agroforestry (business as usual (BAU) scenario), corresponding to a scenario where the government promotes rubber monoculture, with the introduction of illipe rubber agroforestry systems (IRA scenario) as an alternative. It aims to support policy-makers to assess the potential of IRA over larger temporal and spatial scales.

This model simulates the form and function of an idealised estuary with associated barrier-spit complex on the north east coast of New Zealand’s North Island (from Bream Bay to central Bay of Plenty) during the years 2010 - 2050 CE. It combines variables from social, ecological and geomorphic systems to simulate potential directions of change in shallow coastal systems in response to external forcing from land use, climate, pollution, population density, demographics, values and beliefs. The estuary is over 1000Ha, making it a large estuary according to Hume et al. (2007) - there are 12 large estuaries in the Auckland region alone (Suyadi et al., 2019). The model was developed as part of Andrew Allison’s PhD Thesis in Geography from the School of Environment and Institute of Marine Science, University of Auckland, New Zealand. The model setup allows for alteration of geomorphic, ecological and social variables to suit the specific conditions found in various estuaries along the north east coast of New Zealand’s North Island.
This model is not a predictive or forecasting model. It is designed to investigate potential directions of change in complex shallow coastal systems. This model must not be used for any purpose other than as a heuristic to facilitate researcher and stakeholder learning and for developing system understanding (as per Allison et al., 2018).

A simple model that aims to demonstrate the influence of agri-environmental payments on land-use patterns in a virtual landscape. The landscape consists of grassland (which can be managed extensively or intensively) and a river. Agri-environmental payments are provided for extensive management of grassland. Additionally, there are boni for (a) extensive grassland in proximity of the river; and (b) clusters (“agglomerations”) of extensive grassland. The farmers, who own randomly distributed grassland patches, make decisions either on the basis of simple income maximization or they maximize only up to an income threshold beyond which they seize making changes in management. The resulting landscape pattern is evaluated by means of three simple models for (a) agricultural yield, (b) habitat/biodiversity and (c) water quality. The latter two correspond to the two boni. The model has been developed within a small project called Aligning Agent-Based Modelling with Multi-Objective Land-Use Allocation (ALABAMA).

This model grows land use patterns that emerge as a result of land-use compatibilities stablished in urban development plans, land topography, and street networks. It contains urban brushes to paint streets and land uses as a way to learn about urban pattern emergence through free experimentation.

We construct a new type of agent-based model (ABM) that can simultaneously simulate land-use changes at multiple distant places (namely TeleABM, telecoupled agent-based model). We use soybean trade between Brazil and China as an example, where Brazil is the sending system and China is the receiving system because they are the world’s largest soybean exporter and importer respectively. We select one representative county in each country to calibrate and validate the model with spatio-temporal analysis of historical land-use changes and the empirical analysis of household survey data. The whole model is programmed on RePast Simphony. The most unique features of TeleABM are that it can simulate a telecoupled system and the flows between sending and receiving systems in this telecoupled system.

The model is designed to analyse the effects of mitigation measures on the European brown hare (Lepus europaeus), which is directly affected by ongoing land use change and has experienced widespread decline throughout Europe since the 1960s. As an input, we use two 4×4 km large model landscapes, which were generated by a landscape generator based on real field sizes and crop proportions and differed in average field size and crop composition. The crops grown annually are evaluated in terms of forage suitability, breeding suitability and crop richness for the hare. Six mitigation scenarios are implemented, defined by a 10 % increase in: (1) mixed silphie, (2) miscanthus, (3) grass-clover ley, (4) alfalfa, (5) set-aside, and (6) general crop richness. The model shows that that both landscape configuration and composition have a significant effect on hare population development, which responds particularly strongly to compositional changes.

The model aims at reproducing the evolution of the land-use in an agricultural territory at the plot scale. It enables to simulate the affectation of land-use, the crop rotation and technical operations for each plot of the different farms of the territory. It allows as well for crop farms to simulate the daily state of plots (sowed, plowed, harvested, biomass indicator). The model is used as an input for the water pollution model allowing to determine the flow of nitrate, phosphorus and suspended matter in the territory according to the landscape configuration.

RHEA aims to provide a methodological platform to simulate the aggregated impact of households’ residential location choice and dynamic risk perceptions in response to flooding on urban land markets. It integrates adaptive behaviour into the spatial landscape using behavioural theories and empirical data sources. The platform can be used to assess: how changes in households’ preferences or risk perceptions capitalize in property values, how price dynamics in the housing market affect spatial demographics in hazard-prone urban areas, how structural non-marginal shifts in land markets emerge from the bottom up, and how economic land use systems react to climate change. RHEA allows direct modelling of interactions of many heterogeneous agents in a land market over a heterogeneous spatial landscape. As other ABMs of markets it helps to understand how aggregated patterns and economic indices result from many individual interactions of economic agents.
The model could be used by scientists to explore the impact of climate change and increased flood risk on urban resilience, and the effect of various behavioural assumptions on the choices that people make in response to flood risk. It can be used by policy-makers to explore the aggregated impact of climate adaptation policies aimed at minimizing flood damages and the social costs of flood risk.

This model is an application of Brantingham’s neutral model to a real landscape with real locations of potential sources. The sources are represented as their sizes during current conditions, and from marine geophysics surveys, and the agent starts at a random location in Mossel Bay Region (MBR) surrounding the Archaeological Pinnacle Point (PP) locality, Western Cape, South Africa. The agent moves at random on the landscape, picks up and discards raw materials based only upon space in toolkit and probability of discard. If the agent happens to encounter the PP locality while moving at random the agent may discard raw materials at it based on the discard probability.

This model has been created with and for the researcher-farmers of the Muonde Trust (http://www.muonde.org/), a registered Zimbabwean non-governmental organization dedicated to fostering indigenous innovation. Model behaviors and parameters (mashandiro nemisiyano nedzimwe model) derive from a combination of literature review and the collected datasets from Muonde’s long-term (over 30 years) community-based research. The goals of this model are three-fold (muzvikamu zvitatu):
A) To represent three components of a Zimbabwean agro-pastoral system (crops, woodland grazing area, and livestock) along with their key interactions and feedbacks and some of the human management decisions that may affect these components and their interactions.
B) To assess how climate variation (implemented in several different ways) and human management may affect the sustainability of the system as measured by the continued provisioning of crops, livestock, and woodland grazing area.
C) To provide a discussion tool for the community and local leaders to explore different management strategies for the agro-pastoral system (hwaro/nzira yekudyidzana kwavanhu, zvipfuo nezvirimwa), particularly in the face of climate change.