Phenology models are becoming increasingly important tools to accurately predict how climate change will impact the life histories of organisms. We propose a class of integral projection phenology models derived from stochastic individual-based models of insect development and demography. Our derivation, which is based on the rate summation concept, produces integral projection models that capture the effect of phenotypic rate variability on insect phenology, but which are typically more computationally frugal than equivalent individual-based phenology models. We demonstrate our approach using a temperature-dependent model of the demography of the mountain pine beetle (Dendroctonus ponderosae Hopkins), an insect that kills mature pine trees. This work illustrates how a wide range of stochastic phenology models can be reformulated as integral projection models. Due to their computational efficiency, these integral projection models are suitable for deployment in large-scale simulations, such as studies of altered pest distributions under climate change.
Bibliographical noteFunding Information:
We thank Alberta Agriculture and Forestry for access to mountain pine beetle flight trap data for model validation. We are also grateful for comments from five anonymous reviewers. This research was funded by the Center for Space and Earth Sciences (CSES) and the Directed Research and Development (LDRD) program at Los Alamos National Laboratory as well as by the Earth System Modeling program within the Biology and Environmental Research (BER) program at the Department of Energy (DOE) Office of Science. We thank Jacques
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- bark beetle
- individual-based model
- phenology model