Forecasting insect dynamics in a changing world

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1016/j.cois.2023.101133. This is version 4 of this Preprint.

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Authors

Christie A Bahlai 

Abstract

Predicting how insects will respond to stressors through time is difficult because of the diversity of insects, environments, and approaches used to monitor and model. Forecasting models take correlative/statistical, mechanistic models, and integrated forms; in some cases, temporal processes can be inferred from spatial models. Because of heterogeneity associated with broad community measurements, models are often unable to identify mechanistic explanations. Many present efforts to forecast insect dynamics are restricted to single-species models, which can offer precise predictions but limited generalizability. Trait-based approaches may offer a good compromise which limits the masking of the ranges of responses while still offering insight. Regardless of modeling approach, the data used to parameterize a forecasting model should be carefully evaluated for temporal autocorrelation, minimum data needs, and sampling biases in the data. Forecasting models can be tested using near-term predictions and revised to improve future forecasts.

DOI

https://doi.org/10.32942/X2BG76

Subjects

Ecology and Evolutionary Biology, Entomology

Keywords

Dates

Published: 2023-11-16 06:54

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License

CC BY Attribution 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
None

Data and Code Availability Statement:
Not applicable