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

Goodsman, Devin W.; Aukema, Brian H.; McDowell, Nate G.; Middleton, Richard S.; Xu, Chonggang

doi:10.1002/ece3.3590

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

Journal Article · 26 November 2017 · Ecology and Evolution

DOI: https://doi.org/10.1002/ece3.3590 · OSTI ID:1410367

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

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Univ. of Minnesota, Minneapolis, MN (United States). Dept. of Entomology
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

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.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER); LANL Laboratory Directed Research and Development (LDRD) Program; USDOE

Grant/Contract Number:: AC52-06NA25396; AC05-76RL01830; XWDM00

OSTI ID:: 1410367

Alternate ID(s):: OSTI ID: 1410368; OSTI ID: 1412886; OSTI ID: 1413516

Report Number(s):: LA-UR-16-28400; PNNL-SA-129909

Journal Information:: Ecology and Evolution, Vol. 8, Issue 1; ISSN 2045-7758

Publisher:: WileyCopyright Statement

Country of Publication:: United States

Language:: English

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54 ENVIRONMENTAL SCIENCES
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