AI Article Synopsis
- Developed a predictive model for mountain pine beetle oviposition by integrating variations in oviposition rate and fecundity, along with a new method to assess time delay before oviposition.
- The model utilizes hourly phloem temperature and adult MPB attack data to estimate the probability of oviposition during the MPB season.
- An asymptotic approximation of the oviposition model was created for easier computation, and both the detailed model and its approximation were compared to existing models, evaluating their predictive effectiveness against previous observations.
Article Abstract
We develop a predictive oviposition model for a southern population of mountain pine beetle (MPB) using a previously developed rate curve, incorporating variation in both oviposition rate and fecundity. We also introduce a method for determining the time delay before oviposition. The model describes the probability of oviposition for a season of MPB attacks using hourly phloem temperature and adult MPB attack data. We also develop an asymptotic approximation of MPB oviposition that is much less computationally taxing. The detailed oviposition model and its asymptotic approximation are compared with other ovipositional models for MPB; the predictive capacity of each model is evaluated using previously published observations.
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| http://dx.doi.org/10.1007/s11538-022-01089-1 | DOI Listing |
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