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

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.
ORCiD logo [1] ;  [2] ;  [3] ;  [1] ;  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Univ. of Minnesota, Minneapolis, MN (United States). Dept. of Entomology
  3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Publication Date:
Report Number(s):
Journal ID: ISSN 2045-7758
Grant/Contract Number:
Published Article
Journal Name:
Ecology and Evolution
Additional Journal Information:
Journal Name: Ecology and Evolution; Journal ID: ISSN 2045-7758
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); LANL Laboratory Directed Research and Development (LDRD) Program
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES; bark beetle; individual-based model; insect; phenology model
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1410368; OSTI ID: 1412886