Ecosystem disturbances are a significant and ongoing threat to wildlife, caused by both natural environmental changes and human impacts. These disturbances can have a range of impacts, but one of the most crucial is on the wildlife habitat. In tropical forests, one such disturbance that is occurring at an alarming rate is peat fires. Peatfires impact the forest structure and fragmentation, which in turn directly relate to the wildlife habitat, ultimately threatening the population and even risking extinction for certain species. Of particular concern is the population of orangutans in Indonesia, which is at risk due to the impact of peat fires.
This research used an agent-based modelling approach to explore the impact of ecosystem disturbances on wildlife habitat. The focus was on the orangutan population in tropical forests affected by peat fires. A systematic review of agent-based models revealed a shift towards a more mechanistic representation of entities in wildlife response to disturbances. However, fire disturbances and primate species such as orangutans still have a limited number of models.
To address this gap, two agent-based models are presented: PeatFire, a model of the ignition and spread of tropical peatfire, validated using data from a fire pattern in South Sumatra; and the BORNEO model, which simulates the movement behaviour of orangutans in a disturbed forest using real tree inventory data and orangutan tracking data from the Sebangau forest in Central Kalimantan. The models were calibrated and validated using state-of-the-art methods and high-performance computing.
The study demonstrates the ability of ABM to tackle complex research problems in various fields, including wildlife response to disturbances. The models developed in this study are important examples of the shift towards a more mechanistic representation of agents in ABM, and contribute to advancing the field in this direction. The research offers insights into the impact of ecosystem disturbances on wildlife habitat and highlights the potential of ABM in addressing these issues.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:86244 |
| Date | 28 June 2023 |
| Creators | Widyastuti, Kirana |
| Contributors | Berger, Uta, Kramer-Schadt, Stephanie, Vincenot, Christian, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 10.1071/WF19213, 10.1071/WF19213 |
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