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The effect of cover plants on arthropod functional biodiversity was investigated in a vineyard in Northern Italy, through a 3-year field experiment. The following six ground cover plants were tested: Sweet Alyssum; Phacelia; Buckwheat; Faba Bean; Vetch and Oat; control. Arthropods were sampled using different techniques, including collection of leaves, vacuum sampling and sweeping net. Ground cover plant management significantly affected arthropod fauna, including beneficial groups providing ecosystem services like biological control against pests. Many beneficial groups were attracted by ground cover treatments in comparison with control, showing an aggregative numerical response in the plots managed with some of the selected plant species. Alyssum, Buckwheat and 'Vetch and Oat' mixture showed attractiveness on some Hymenoptera parasitoid families, which represented 72.3% of the insects collected by sweeping net and 45.7 by vacuum sampling. Phytoseiidae mites showed a significant increase on leaves of the vineyard plots managed with ground covers, in comparison with control, although they did not show any difference among the treatments. In general, the tested ground cover treatments did not increase dangerous Homoptera populations in comparison with control, with the exception of Alyssum. The potential of ground cover plant management in Italian vineyards is discussed: the overall lack of potential negative effects of the plants tested, combined with an aggregative numerical response for many beneficials, seems to show a potential for their use in Northern Italy vineyards.

Control interventions in sustainable pest management schemes are set according to the phenology and the population abundance of the pests. This information can be obtained using suitable mathematical models that describe the population dynamics based on individual life history responses to environmental conditions and resource availability. These responses are described by development, fecundity and survival rate functions, which can be estimated from laboratory experiments. If experimental data are not available, data on field population dynamics can be used for their estimation. This is the case of the extrinsic mortality term that appears in the mortality rate function due to biotic factors. We propose a Bayesian approach to estimate the probability density functions of the parameters in the extrinsic mortality rate function, starting from data on population abundance. The method investigates the time variability in the mortality parameters by comparing simulated and observed trajectories. The grape berry moth, a pest of great importance in European vineyards, has been considered as a case study. Simulated data have been considered to evaluate the convergence of the algorithm, while field data have been used to obtain estimates of the mortality for the grape berry moth.

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