Incorporating variability in simulations of seasonally forced phenology using integral projection models

Journal Article · Sun Nov 26 00:00:00 EST 2017 · Ecology and Evolution

DOI:https://doi.org/10.1002/ece3.3590· OSTI ID:1439662

Goodsman, Devin W.  ^[1]; Aukema, Brian H. ^[2]; McDowell, Nate G. ^[3]; Middleton, Richard S. ^[1]; Xu, Chonggang ^[1]

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1. Earth and Environmental Science Division, Los Alamos National Laboratory, Los Alamos NM USA
2. Department of Entomology, University of Minnesota, St Paul MN USA
3. Pacific Northwest National Laboratory, Richland WA USA

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.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1439662
• Report Number(s): PNNL-SA-129909
• Journal Information: Ecology and Evolution, Vol. 8, Issue 1; ISSN 2045-7758
• Publisher: Wiley
• Country of Publication: United States
• Language: English