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Prediction of the Arbutus unedo colonization time via an agent-based distribution model
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Advisor(s)
Abstract(s)
Species distribution models (SDMs) have been used to predict the
distribution of species in an environment. Usually, this prediction is based on
previous species occurrence data. Nowadays, several species are facing climatic
changes that impact the way species behave. Global warming has implicated
species displacement from their natural habitat to new suitable places. SDMs can
be used to anticipate possible impacts of the climatic changes in species distribution,
preventing species extinction scenarios. New SDMs approaches are needed
to give valuable information that better approximates these models to reality.
This paper presents a novel approach to the prediction of species distribution. It
starts by using an agent-based model (ABM) to establish an approximate mapping
between the geological and the computational times. Afterwards, the implemented
ABM can be used to predict the species distribution at different time
intervals.
The presented case study concerns the distribution of the Arbutus unedo in the
Iberian peninsula, a species with relevant socio-economic impact in Portugal.
The results show that the measurement of the geological time, supported by the
approximate correspondence to the number of epochs of an ABM, can be a valuable
tool for the prediction of the species distribution in a changing environmental
scenario.
Description
Keywords
Agent-based distribution model Colonization time Species distribution model
Citation
Bioco J., Prata P., Cánovas F., Fazendeiro, P.. (2022). Prediction of the Arbutus unedo colonization time via an agent-based distribution model. 5th International Conference for Emerging Technologies in Computing (iCETiC’22), Chester, United Kingdom.
Publisher
IAER