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23 September 2017 Arthropod Development's Response to Temperature: a Review and New Software for Modeling
Mohammad Ali Mirhosseini, Yaghoub Fathipour, Gadi V. P. Reddy
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Abstract

Among environmental factors, temperature has a direct and crucial influence on the key life processes of survival, development, reproduction, and movement of poikilothermic animals and hence their population dynamics. The lower and upper temperature thresholds and optimal temperature have ramifications for all major life processes, where within a specific range, a temperature change results in a proportional rise or fall of the rate of any given process. There are some basic approaches for modeling development response to temperature in arthropods. The oldest and most widely used model is a simple linear description of arthropod development in relation to temperature. The linear model forms the basis of the well-known thermal summation or degree-day (DD) approach to timing prediction. The second approach for predicting arthropod development rate is nonlinear mathematical models. However, given the fundamental role of thermal models in forecasting and integrated pest management programs, the main purpose of this paper was to facilitate the use of thermal models to estimate the developmental response of arthropods to temperature and select the appropriate model with a view to goodness-of-fit and generalizability by designing a user-friendly software. In this paper, the linear and most common nonlinear thermal models and the main criteria for selecting appropriate models are also reviewed.

© The Author 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Mohammad Ali Mirhosseini, Yaghoub Fathipour, and Gadi V. P. Reddy "Arthropod Development's Response to Temperature: a Review and New Software for Modeling," Annals of the Entomological Society of America 110(6), 507-520, (23 September 2017). https://doi.org/10.1093/aesa/sax071
Received: 17 July 2017; Accepted: 15 August 2017; Published: 23 September 2017
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KEYWORDS
ArthroThermoModel software
degree-day
forecasting
integrated pest management
physiological time
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