RaMDry allows to study the dynamic use of forage ressources by herbivores in semi-arid savanna with an emphasis on effects of change of climate and management. Seasonal dynamics affects the amount and the nutritional values of the available forage.

This is an empirical model described in http://dx.doi.org/10.1016/j.landurbplan.2010.05.001. The objective of the model is to simulate how the decision-making of farmers/agents with different strategies can affect the landscape structure in a region in the Netherlands.

The agent-based model WEEM (Woodlot Establishment and Expansion Model) as described in the journal article, has been designed to make use of household socio-demographics (household status, birth, and death events of households), to better understand the temporal dynamics of woodlot in the buffer zones of Budongo protected forest reserve, Masindi district, Uganda. The results contribute to a mechanistic understanding of what determines the current gap between intention and actual behavior in forest land restoration at farm level.

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.

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.

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).

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 MML is a hybrid modeling environment that couples an agent-based model of small-holder agropastoral households and a cellular landscape evolution model that simulates changes in erosion/deposition, soils, and vegetation.

The TERROIR agent-based model was built for the multi-level analysis of biomass and nutrient flows within agro-sylvo-pastoral villages in West Africa. It explicitly takes into account both human organization and spatial extension of such flows.

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.