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Developmental Models for Estimating Ecological Responses to Environmental Variability: Structural, Parametric, and Experimental Issues

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Abstract

Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and non-linear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear versus non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development.

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Acknowledgements

This work was supported in part by the Ecology of Infectious Disease program of the National Science Foundation under Grant No. 0622743, by the National Institute for Allergy and Infectious Disease (K01AI091864) and by the Global Health Institute at Emory University. JLM acknowledges the support of a training grant from the National Institute for Allergy and Infectious Disease (T32AI055404), a NSF Graduate Research Fellowship (award number DGE-0940903), and a NSF GK-12 Fellowship (under DGE grant #0841297 to S.L. Williams and B. Ludaescher). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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  1. Julia L. Moore

    Present address: Department of Evolution and Ecology, University of California Davis, Davis, CA, 95616, USA

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  1. Program in Population Biology, Ecology and Evolution, Graduate Division of Biological and Biomedical Sciences, Emory University, 1510 Clifton Rd, Atlanta, GA, 30322, USA

    Julia L. Moore

  2. Department of Environmental Health, Rollins School of Public Health, Emory University, 1518 Clifton Rd Room 2023, Atlanta, GA, 30322, USA

    Justin V. Remais

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Moore, J.L., Remais, J.V. Developmental Models for Estimating Ecological Responses to Environmental Variability: Structural, Parametric, and Experimental Issues. Acta Biotheor 62, 69–90 (2014). https://doi.org/10.1007/s10441-014-9209-9

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