How Phenological Variation Affects Species Spreading Speeds
2018
In this paper, we develop a phenologically explicit reaction–diffusion model to analyze the spatial spread of a univoltine insect species. Our model assumes four explicit life stages: adult, two larval, and pupa, with a fourth, implicit, egg stage modeled as a time delay between oviposition and emergence as a larva. As such, our model is broadly applicable to holometabolous insects. To account for phenology (seasonal biological timing), we introduce four time-dependent phenological functions describing adult emergence, oviposition and larval conversion, respectively. Emergence is defined as the per-capita probability of an adult emerging from the pupal stage at a particular time. Oviposition is defined as the per-capita rate of adult egg deposition at a particular time. Two functions deal with the larva stage 1 to larva stage 2, and larva stage 2 to pupa conversion as per-capita rate of conversion at a particular time. This very general formulation allows us to accommodate a wide variety of alternative insect phenologies and lifestyles. We provide the moment-generating function for the general linearized system in terms of phenological functions and model parameters. We prove that the spreading speed of the linearized system is the same as that for nonlinear system. We then find explicit solutions for the spreading speed of the insect population for the limiting cases where (1) emergence and oviposition are impulsive (i.e., take place over an extremely narrow time window), larval conversion occurs at a constant rate, and larvae are immobile, (2) emergence and oviposition are impulsive (i.e., take place over an extremely narrow time window), larval conversion occurs at a constant rate starting at a delayed time from egg hatch, and larvae are immobile, and (3) emergence, oviposition, and larval conversion are impulsive. To consider other biological scenarios, including cases with emergence and oviposition windows of finite width as well as mobile larvae, we use numerical simulations. Our results provide a framework for understanding how phenology can interact with spatial spread to facilitate (or hinder) species expansion. This is an important area of research within the context of global change, which brings both new invasive species and range shifts for native species, all the while causing perturbations to species phenology that may impact the abilities of native and invasive populations to spread.
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