SIMULATING RAT DENSITY IN URBAN ENVIRONMENTS

Abstract

Urban centers are constantly growing, and cities are becoming some of the most widespread habitats. Metropolises represent ecosystem hubs, hosting more and more species. The number of animals choosing cities as their ideal habitat has grown to such extent that the word synurbic has been coined to describe the phenomena. Cohabitation of different animals in urban areas can develop beneficial synergies which should be protected and incentivized. However, in some circumstances it might be necessary to control the expansion of species and brown rats often fall in this category. Rats are considered a threat to food quality, urban infrastructure, and public physical and mental health. Multiple efforts have been made to control their spread. However, despite their presence dating back to the 18th century, not many successful ways to manage rats have been developed. The inefficiency to regulate rodents’ infestations can be linked with a general lack of knowledge on their environmental behaviors. Such gap partly depends on the complexity of developing efficient techniques to study rats in the wild. This study aims at experimenting with Agent Based Models (ABMs) as possible tools to gain more insights on rat presence and movements in cities. In this project, the process to create an ABM with the GAMA software is described and the growth of a hypothetical rat population is simulated in the Rivierenbuurt neighborhood of Amsterdam. The model analyzes the correlation between the availability of food and the colonization time. It also proposes some application scenarios, exploring possible inputs for rats’ management strategies. The final findings identified that, based on the simulation, the amount of food has a stronger impact on the capacity of the block than its distribution. The results also showcased how in the context of the Rivierenbuurt, control strategies based on predator’s introduction or on a revision of the garbage collection plan might be more effective than spatial ones such as the construction of some rat barriers or a buildings renovation intervention. This project finalized some observations and conclusions that can be considered valuable information for the interested case study area. However, it remains difficult to comprehend the accuracy of the outputs when transferred from the simulated reality to the actual world.