Ground-truthing predictions of a demographic model driven by land surface temperatures with a weed biocontrol cage experiment

Herbivorous insects play important roles in agriculture as pests or as weed biological control agents. Predicting the timing of herbivore insect population development can thus be of paramount importance for agricultural planning and sustainable land management. Numerical simulation models driven by temperature are often used to predict insect pest population build-up in agriculture. Such simulation models intend to use station-derived temperatures to drive the development of the target insect, although this temperature may differ substantially from that experienced by the insect on the plant. To improve the estimations, it has been suggested to replace air temperature in the model by land surface temperature (LST) data. Here, we use a numerical simulation model of insect population dynamics driven by either air temperature (combined with atmospheric temperature soundings) or land surface temperature derived from satellites to predict the population trends of the leaf beetle Ophraella communa, a potential biological control agent of Ambrosia artemisiifolia in Europe. For this, we conducted an extensive field experiment that included caged O. communa populations at five sites along an altitudinal gradient (125–1250 m a.s.l.) in Northern Italy during 2015 and 2016. We compared our model predictions using air or land surface temperature with observed beetle population build-up. Model predictions with both air and land surface temperatures predicted a similar phenology to observed populations but overestimated the abundance of the observed populations. When taking into consideration the error of the two measurement methods, the predictions of the model were in overlapping timeframes. Therefore, the current model driven by LST can be used as a proxy for herbivore impact, which is a novel tool for weed biocontrol.