Individual-Based Modeling Approach to Assessment of the Impacts of Landscape Complexity and Climate on Dispersion, Detectability and Fate of Incipient Medfly Populations

Abstract

The objective of the presented study was to demonstrate the potential of a bottom-up “ethological” approach and individual-based model of Markov-like stochastic processes, employed to gain insights into the factors driving behavior and fate of the invasive propagule, which determine the initial stages of pest invasion and “cryptic” existence of the localized, ultra-low density incipient pest populations. The applied model, PESTonFARM, is driven by the parameters derived directly from the behavior and biology of the target insect species, and spatiotemporal traits of the local terrain and climate. The model projections are actively generated by behavior of the primary causative actors of the invasion processes—individual “virtual” insects—members of the initial propagules or incipient populations. Algorithms of the model were adjusted to reflect behavior and ecology of the Mediterranean fruit fly, Ceratitis capitata, used as a case-example in the presented study. The model was parametrized based on compiled published experimental information about C. capitata behavior and development, and validated using published data from dispersion and trapping studies. The model reliably simulated behavior, development and dispersion of individual members of an invasive cohort, and allowed to quantify pest establishment and detection chances in landscapes of varying spatiotemporal complexity, host availability and climates. The results support the common view that, under optimal conditions (farmland with continuous fruit availability and suitable climate), even a single propagule of medium size (100 females) usually results in pest establishment and detection within the first year post-invasion. The results demonstrate, however, that under specific sub-optimal conditions determined by the local climate, weather fluctuations and landscape topography (e.g., sub-urban), the incipient cryptic populations may occasionally continue for several generations, and remain undetected by typical pest surveillance grids for the periods extending beyond 2-years post-invasion.

Back-yard medfly is a key factor in area-wide management in Southern Europe. Data from Attiki Greece, 38

“…Unless these numerous medfly-breeding hot spots are taken care of, no area-wide medfly management initiative could be undertaken. In addition, our findings corroborate other recent studies that highlight the significance of urban environments for the gradual establishment of incipient populations of insects, some of which might stay undetected for years (Papadopoulos et al 2013, Lux 2018. In at least some of these countries, given the opposition of back-yard owners to any control practices, especially with insecticides, no legislation exists permitting forced drastic control or eradication of the fly.…”

Non-linear physiological responses to climate change: the case of Ceratitis capitata distribution and abundance in Europe

“…Stable C. capitata populations have been reported in southern France (Cayol and Causse 1993), northern Italy (Rigamonti et al 2002;Rigamonti 2004Rigamonti , 2005Zanoni 2018; Zanoni et al 2019), and Austria (Egartner et al 2017) suggesting the capacity of the species to complete its life-cycle in areas far above its traditional northward distribution limit. Climate change is expected to play a primary role in altering the potential distribution and performance of the species worldwide (Gutierrez and Ponti 2011;Sultana et al 2020), and in the species' capacity to reinvade new areas by local transient populations (Lux 2018).…”

Harmonic radar tracking of individual melon flies, Zeugodacus cucurbitae, in Hawaii: Determining movement parameters in cage and field settings

“…Additionally, fly movement data will allow better modeling of pest populations to understand potential pest distribution, quarantine deployment, optimizing trapping networks, and predicting pest outbreaks [13]. Dispersal capacity (specifically step-distance and flight directionality), spatial distribution, and density of pest insects are particularly important for improving agent-based modeling [14][15][16][17].…”

“…In areas where particular tephritids are invasive or in "fruit fly free zones" [18] measurement of fly movement in the field can be extremely helpful for improving increasingly sophisticated models aimed at improving detection, delimitation, and eradication. In recent years there have been a number of Agent-based simulations for addressing management and eradication of tephritids [14,16,17]. While not all of these are spatially-explicit, one of the reasons for this usually includes lack of movement parameters, such as turning angles and step-distances, for the target species.…”