Insects are poikilothermic organisms that are sensitive to abiotic factors and, thus, it is not surprising that they have been used as a model organism to describe the environmental effects on species phenological, behavioural and physiological rhythms. Traditionally, such processes are described using empirical models, which in their most simple courses are given based on antiquated rules of temperature-dependency. Recently, as we include more variables and proceed to more complex population systems, these are characterized by large uncertainties as well as inherent (self-sustained) biological rhythms, make such models less accurate. Particularly, considering population development growth as a macroscopic revelation of enzyme reactions, in which environmental factors and stochastic noise exert a catalytic effect at both cellular and macroscopic-population levels, researchers now more often prefer stochastic modelling approaches.
In this Research Topic we encourage contributions relative to current trends in modelling insect biological processes, either at the individual or population levels. Particularly we would like to document how recent models may be used as powerful tools to describe cyclical patterns in physiological systems, including poikilothermic development and seasonality of insects and related arthropods. Stochastic population models are employed to key out the climatic influence on insect physiology, phenology and demography to offer solutions on how temporal rhythms (daily, weekly, seasonal and annual) are governed by external (non-indigenous) forces.
Climate change modelling stochastic weather generators can be used to produce synthetic weather series of precipitation, solar radiation and temperature, useful in environmental modelling of pest risk assessment. Furthermore, the output of the models should be discussed in terms of usefulness to climate change adaptation strategies, especially for plant protection.
Some major themes additionally may include the emerging role of modern statistical techniques in bringing together experimental and theoretical studies and the importance of long-term experimentation to describe insect population dynamics such as seasonal phenology, and demography. A further theme may include different applications of climate change models to model the impact on agricultural insect pests. Lastly, because insects and related arthropods are excellent ‘experimental tools’, as demonstrated in seminal works in modelling biological rhythms, we will try to address a rather difficult and multi-disciplinary research question, namely that of self-organization within such biological systems.
Insects are poikilothermic organisms that are sensitive to abiotic factors and, thus, it is not surprising that they have been used as a model organism to describe the environmental effects on species phenological, behavioural and physiological rhythms. Traditionally, such processes are described using empirical models, which in their most simple courses are given based on antiquated rules of temperature-dependency. Recently, as we include more variables and proceed to more complex population systems, these are characterized by large uncertainties as well as inherent (self-sustained) biological rhythms, make such models less accurate. Particularly, considering population development growth as a macroscopic revelation of enzyme reactions, in which environmental factors and stochastic noise exert a catalytic effect at both cellular and macroscopic-population levels, researchers now more often prefer stochastic modelling approaches.
In this Research Topic we encourage contributions relative to current trends in modelling insect biological processes, either at the individual or population levels. Particularly we would like to document how recent models may be used as powerful tools to describe cyclical patterns in physiological systems, including poikilothermic development and seasonality of insects and related arthropods. Stochastic population models are employed to key out the climatic influence on insect physiology, phenology and demography to offer solutions on how temporal rhythms (daily, weekly, seasonal and annual) are governed by external (non-indigenous) forces.
Climate change modelling stochastic weather generators can be used to produce synthetic weather series of precipitation, solar radiation and temperature, useful in environmental modelling of pest risk assessment. Furthermore, the output of the models should be discussed in terms of usefulness to climate change adaptation strategies, especially for plant protection.
Some major themes additionally may include the emerging role of modern statistical techniques in bringing together experimental and theoretical studies and the importance of long-term experimentation to describe insect population dynamics such as seasonal phenology, and demography. A further theme may include different applications of climate change models to model the impact on agricultural insect pests. Lastly, because insects and related arthropods are excellent ‘experimental tools’, as demonstrated in seminal works in modelling biological rhythms, we will try to address a rather difficult and multi-disciplinary research question, namely that of self-organization within such biological systems.
