INSTAR: An Agent-Based Model that integrates existing knowledge to simulate the population dynamics of a forest pest
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Suárez Muñoz, María; Bonet, Francisco Javier; Hodar Correa, José Antonio; Herrero, Javier; Tanase, Mihai; Torres Muros, LucíaEditorial
Elsevier BV
Materia
Thaumetopoea pityocampa Agent-Based model (ABM) Forest pest Population dynamics Pattern-oriented
Date
2019-09-21Referencia bibliográfica
Suárez-Muñoz, M., Bonet-García, F., Hódar, J. A., Herrero, J., Tanase, M., & Torres-Muros, L. (2019). INSTAR: An Agent-Based Model that integrates existing knowledge to simulate the population dynamics of a forest pest. Ecological Modelling, 411, 108764.
Sponsorship
The project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 641762.Abstract
Pine plantations, very common in the Mediterranean basin, are recurrently affected by forest pests due to intrinsic
characteristics (high density, low spatial heterogeneity) and external factors (consistent trend towards a
warmer and drier climate). INSTAR is an Agent-Based Model aiming to simulate the population dynamics of the
Thaumetopoea pityocampa forest pest. The model has been designed using a modular approach: several interconnected
modules (submodels) facilitate the incorporation of new knowledge about the pest biology and can
serve as template for the design of other similar models. The model is spatially and temporally explicit and
allows its implementation under different climate and land use scenarios. INSTAR is described in detail in this
manuscript using the standardized ODD (Overview, Design concepts and Details) protocol.
Temperature is known to be one of the main factors modulating the population dynamics of T. pityocampa. In
order to be coherent and structurally realistic, INSTAR should faithfully reproduce the effect of this factor on the
species’ phenology. This requirement has been assessed here through a consistency test of the submodules responsible
for species development. This assessment is constituted by a calibration analysis of the pest phenology
and a stress test performed by exposing the model to extreme climate inputs. As a result of calibration, the model
successfully reproduces the phenology of the species in the simulated study area. Moreover, the stress test
confirmed that the model behaves as expected when exposed to extreme input values. The results presented in
this manuscript constitute a first internal validation of the development submodels. After this, INSTAR is ready
for a deeper analysis consisting on a sensitivity and uncertainty analysis.