The impact of interpolated daily temperature data on landscape-wide predictions of invertebrate pest phenology

摘要

Insect phenology depends upon temperature, and data from scattered synoptic weather stations are the principle inputs for phenology models used in decision support systems. The paper assesses the spatial dynamics of the penalty, as measured through errors in the timing of predicted insect development stages, that results when entomologists use daily maximum and minimum temperature data from the nearest station to a location, in comparison with an interpolated temperature equivalent, to drive their models. Jack-knife cross-validated estimates of temperature were propagated through an example phenology model, in this case for codling moth (Cydia pomonella). The intention was to contrast the effect of two interpolation methods on phenological results through time at different geographical locations.