A critical review of the use and performance of different function types for modeling temperature-dependent development of arthropod larvae

Abstract

ABSTRACTTemperature-dependent development influences production rates of arthropods, including crustaceans important to fisheries and agricultural pests. Numerous candidate equation types (development functions) exist to describe the effect of temperature on development time, yet most studies use only a single type of equation and there is no consensus as to which, if any model predicts development rates better than the others, nor what the consequences of selecting a potentially incorrect model equation are on predicted development times. In this study, a literature search was performed of studies fitting development functions to development of arthropod larvae (99 species). The published data of most (79) of these species were then fit with 33 commonly-used development functions. Overall performance of each function type and consequences of using a function other than the best one to model data were assessed. Performance was also related to taxonomy and the range of temperatures examined. The majority (91.1 %) of studies were found to not use the best function out of those tested. Using the incorrect model lead to significantly less accurate (e.g., mean difference ± SE 85.9 ± 27.4 %, range: −1.7 to 1725.5 %) predictions of development times than the best function. Overall, more complex functions performed poorly relative to simpler ones. However, performance of some complex functions improved when wide temperature ranges were tested, which tended to be confined to studies of insects or arachnids compared with those of crustaceans. Results indicate the biological significance of choosing the best-fitting model to describe temperature-dependent development time data.HighlightsTemperature-dependent development functions of arthropod larvae were reviewed79 published datasets were re-tested and fit with 33 different function types91.1 % of published studies did not fit their data with the best function of those testedPerformance differed among functions and was related to taxon and temperature range testedFunction type impacted predicted development times, so using the best function matters