Birgen Haest

1 Introduction The direct and indirect impacts of climate and other anthropogenic changes are causing wildlife across the globe to face ever-increasing threats in terms of individual health, altered behaviour, phenology, distribution and population dynamics (Acevedo-Whitehouse and Duffus 2009; Peñuelas et al. 2013; Razgour et al. 2018).

Abstract Aerial insects are vital for nature and society. Though methods to observe flying insects have consistently improved in the last decades, insects remain difficult to monitor systematically and consistently over large spatial and temporal scales. Remote sensing with radars has proved to be one of the more effective tools for observation.

Abstract 1. The ability to select statistical models based on how well they fit an empirical dataset is a central tenet of modern bioscience. How well this works, though, depends on how goodness-of-fit is measured. Likelihood and its derivatives (e.g. AIC) are popular and powerful tools when measuring goodness-of-fit, though inherently make assumptions about the data. One such assumption is absence of error on the x-axis (i.e. no error in the predictor).